From a30d5c65382c266074e4c2d77278ae2264c78bfd Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 09:22:51 +0200 Subject: [PATCH 01/53] Define audited long-recording curation contract and integration plan --- design/README.md | 16 + design/large-recording-curation.md | 345 ++++++++++++++++++ design/large-recording-integration-plan.md | 244 +++++++++++++ phy/apps/tests/large_recording_fixtures.py | 153 ++++++++ .../tests/test_large_recording_contract.py | 151 ++++++++ 5 files changed, 909 insertions(+) create mode 100644 design/large-recording-curation.md create mode 100644 design/large-recording-integration-plan.md create mode 100644 phy/apps/tests/large_recording_fixtures.py create mode 100644 phy/apps/tests/test_large_recording_contract.py diff --git a/design/README.md b/design/README.md index 90565b927..995206b0c 100644 --- a/design/README.md +++ b/design/README.md @@ -57,3 +57,19 @@ and section 11 for integration and manual acceptance. The implementation and user documentation are complete on the unreleased phy 2.2 branch. Final large-dataset smoke testing and save/reopen validation remain. + +## Long-recording curation (proposed) + +The [long-recording curation Phy-side design contract](large-recording-curation.md) +describes bounded local datasets for ~1000-hour sortings, the three spike-index +spaces, optional upstream waveform evidence, full-duration metrics, replay safety, +and the sequence of implementation PRs. The accompanying synthetic 1000-hour +fixture and reference tests are in `phy/apps/tests/large_recording_fixtures.py` +and `phy/apps/tests/test_large_recording_contract.py`. + +This is a proposal and a reference test contract, **not yet** a `prepare-large` +implementation or an upstream export-format agreement. + +The [integration audit and plan](large-recording-integration-plan.md) refines +the contract with correctness findings, module boundaries, ordered PRs and +acceptance gates. Follow its gates before enabling editable bounded sessions. diff --git a/design/large-recording-curation.md b/design/large-recording-curation.md new file mode 100644 index 000000000..0d3dfbaab --- /dev/null +++ b/design/large-recording-curation.md @@ -0,0 +1,345 @@ +# Long-recording curation in Phy 2.x: Phy-side design contract + +**Status:** proposed; implementation sequence and file contracts for review. This +specification is for Phy-side development; it does not authorize changes to the +AIND/Code Ocean export pipeline. Current Phy behavior remains unchanged until +subsequent implementation PRs land. + +The [integration audit and plan](large-recording-integration-plan.md) refines +this proposal with assignment revisions, transactional persistence, capability +gates and ordered PR acceptance criteria. Its enablement gates take precedence +over the original implementation sequence in Section 9. + +## 1. Objective and boundaries + +Curate chronic Neuropixels sortings of roughly 1000 hours without opening hundreds +of millions or billions of spikes in the existing in-memory Phy clustering model. +The workstation downloads the **complete sorter output once**; downloading the +complete raw voltage recording is **not required**. All preparation, interactive +curation, full-data replay, and regeneration run locally: + +```text +complete, immutable sorting (local disk) + | prepare-large: streamed/batch + v +bounded, temporally distributed Phy dataset + full-duration summaries + | existing Template GUI + Unit Stability + v +semantic curation actions (not only sampled row assignments) + | apply-curation: streamed/batch against complete sorting + v +new complete curated sorting (original untouched) + | prepare-large again, potentially different evidence windows + +-----------------------> new bounded GUI dataset +``` + +The **complete spike-level sorting stays outside the interactive GUI**. +The bounded dataset must reproduce useful current Phy workflows rather than +pretend to be a statistically representative replacement for every spike. +Full-duration plots and rates come from separate complete-sorting summaries. + +Out of scope: cloud services, rewriting phylib for out-of-core clustering, +longitudinal unit-identity graphs (phy3), automatic change-point detection, and +implementing upstream waveform extraction in this repository. + +## 2. The three index spaces (essential contract) + +All index values below are **zero-based row positions**, not timestamps, sample +numbers, SpikeInterface unit IDs, or stable IDs assigned by a sorter. + +| Symbol | Meaning | Where it lives | +| --- | --- | --- | +| `g` | Full-sorting spike row index, in immutable source order | Original `spike_times.npy` / `spike_clusters.npy` | +| `b` | Bounded spike row index used by the GUI | Bounded `spike_times.npy` / `spike_clusters.npy` | +| `w` | Row in the stored waveform/channel tensors | `_phy_spikes_subset.waveforms.npy` / `.channels.npy` | + +**Canonical mapping:** the bounded package writes +`_phy_spike_global_ids.npy`, a one-dimensional strictly increasing `int64` +array of length `N_bounded`. It is `G[b] = g`. The underscore prefix is +intentional: phylib treats ordinary `spike_*.npy` files as per-spike +attributes, so `spike_global_ids.npy` would be needlessly interpreted as one. + +**Dataset-local waveform IDs:** `_phy_spikes_subset.spikes.npy[w] = b` in the +bounded package. In the *upstream full export*, the same filename instead +contains `g` because that file accompanies the full sorting. The file **never** +means an intrinsic immutable/global ID; it indexes whichever Phy dataset is in +its directory. + +Example: + +```text +full indices selected by prepare-large, G: + [14, 19, 27, 117, 203, 839] +bounded rows b: + [ 0, 1, 2, 3, 4, 5] +upstream waveform full indices: + [14, 117, 839, 1902] +intersection with G: + [14, 117, 839] +bounded _phy_spikes_subset.spikes.npy: + [ 0, 3, 5] +``` + +Recover full source row numbers for waveforms by composition: + +```python +G = np.load('_phy_spike_global_ids.npy', mmap_mode='r') +B = np.load('_phy_spikes_subset.spikes.npy', mmap_mode='r') +full_waveform_rows = G[B] # [14, 117, 839] +``` + +`prepare-large` must preserve source row order, subset all per-spike arrays +consistently, retain absolute spike sample times, and remap matching waveform +rows **along with the corresponding channel/waveform data**. A sorted +intersection / `np.searchsorted` implementation needs no billion-element +inverse lookup array. Sorting by sample time is not a substitute for preserving +row identity; use the source export's exact row order (including ties). + +## 3. Source and optional upstream waveform inputs + +The source is a locally accessible standard Phy/SpikeInterface export (or an +adapter yielding equivalent arrays). The original spike index `g` refers to +**the exact exported row ordering**, not an assumed row in an unrelated +SpikeInterface spike vector. Source arrays and their provenance must be +validated before processing; never infer a row mapping from spike timestamps. + +The existing, unmodified Phy waveform files are: + +| Filename | Meaning | +| --- | --- | +| `_phy_spikes_subset.spikes.npy` | `int64[N_waveforms]`: source full spike row indices, sorted/unique | +| `_phy_spikes_subset.channels.npy` | `int32[N_waveforms, C_sparse]`: model channel indices, with `-1` padding; `channel_map.npy` maps these to raw-file columns | +| `_phy_spikes_subset.waveforms.npy` | numeric `[N_waveforms, N_samples, C_sparse]`: aligned waveform data, zero on padded channels | + +The upstream AIND pipeline **may later** supply the following proposed files; +these names/schema are *not yet finalized with its developers*: + +| Optional file | Initial proposal | +| --- | --- | +| `_phy_spikes_subset.window_bounds.npy` | `int64[W, 2]` recording sample intervals, `[start, end)` | +| `_phy_spikes_subset.window_types.npy` | `uint8[W]`: `0` survey, `1` rescue | +| `_phy_spikes_subset.window_strata.npy` | `int32[W]`: survey stratum index, `-1` for rescue | +| `_phy_spikes_subset.manifest.json` | Small versioned scalar metadata: source identity, time base, extractor geometry, parameters, seed, array semantics | + +There are deliberately **no structured NumPy dtypes**, mixed-purpose `N x 5` +matrices, or massive JSON window arrays. The upstream manifest is useful for +planning downstream windows but is not required for fixture-based development. +The presence of a window denotes *potential* waveform coverage, not one stored +waveform for every spike within that interval: per-unit waveform caps still +apply. The three established waveform files remain authoritative for which +individual spikes actually have stored waveforms. + +In the absence of the proposed window sidecars, `prepare-large` may use the +existing three files and their spike-index/time distribution as available +evidence, with reduced guarantees about raw-I/O locality and survey windows. +A dataset with neither raw traces nor pre-extracted waveforms must not claim +that Waveform/Feature View evidence is available. + +The full export's identifier/fingerprint should combine an immutable sorting +asset ID when available, full spike count, and a digest of a canonical +row-ordered immutable spike array (`spike_times.npy` is one candidate). The +upstream reservoir must be verified against that *exact* source. A mutable +`spike_clusters.npy` hash must not be the sole identity used across curation +iterations. Byte-level hashes in examples are illustrative; the definitive +AIND provenance method is a pending joint decision. + +Coordinate identity and assignment revision are separate: the latter binds the +initial full cluster assignments and metadata for replay. Each curated output +records its parent revision and journal digest. Validate relevant immutable +feature, acquisition and time-base provenance as well as spike rows; equal +timestamp arrays alone do not establish source identity. Production hashing +must stream file contents rather than read a complete array into memory. + +## 4. Bounded-package Phy-side output + +`prepare-large` creates a **new directory**, not an in-place rewrite of the +original. At minimum it contains ordinary, internally consistent Phy files +(`params.py`, `spike_times.npy`, `spike_templates.npy`, `spike_clusters.npy`, +channel/template arrays, and present per-spike attributes), plus: + +| File | Role | +| --- | --- | +| `_phy_spike_global_ids.npy` | Required `int64[N_bounded]` sorted mapping `b -> g`, no duplicates | +| `_phy_curation_manifest.json` | Versioned local contract; immutable source ID/fingerprint, complete/bounded counts, durations, preparation algorithm/parameters/seed, evidence limitations and file names | +| `_phy_spikes_subset.{spikes,channels,waveforms}.npy` | Existing Phy-format stored waveforms, *remapped to bounded row indices* (if available) | +| Full-duration metrics | Separate time-binned evidence, described in Section 6; do not pretend proxy metrics are full metrics | + +Unselected spike rows are absent from the GUI arrays, **not deleted from the +complete sorting**. Absolute `spike_times.npy` values remain in acquisition +sample coordinates and require a dtype capable of representing 1000 h at the +source sample rate (typically `int64`, not `int32`). For 30 kHz, 1000 h is +108 billion samples. Keep recording start/end, session/block boundaries, valid +acquisition exposure, and gaps distinct from periods of zero firing. + +Do not rely on phylib's fallback of estimating `model.duration` from the last +spike when raw traces are absent. The future GUI metrics/time-axis integration +must take the authoritative duration/coverage metadata instead. Standard +`params.py` still identifies the bounded Phy dataset; the manifest augments it. + +## 5. Preparation algorithm: scientific and memory constraints + +A first version should: + +1. Scan the **full** local sorting in a bounded-memory batch pass; calculate + full-duration per-unit time bins and coverage/exposure. +2. Partition *valid acquisition time* into coarse strata. Select short shared + contiguous survey windows at deterministic seeded offsets across sessions/ + blocks (illustrative defaults: one 30 s window per 1 h stratum). +3. Include **all units and all spikes within each chosen window** as initial + bounded candidates; preserve source indices and absolute times. +4. Enforce configurable **total spike / RAM budgets**. Add shared rescue windows + for underrepresented units, prioritizing benefit to several units and + temporally separated evidence; retain bounded deterministic selection. +5. Where a waveform reservoir exists, favor windows with usable waveform + coverage and report per-unit counts and uncovered regions. Selecting a + window does not guarantee all its spikes have stored waveforms. +6. Write an atomic, versioned bounded package. Verify array-length alignment, + sorted global IDs, waveform/feature alignment, provenance, coverage and + source immutability before marking it usable. + +These choices are **heuristics**, not a claim of unbiased sampling, complete +physiological representativeness, or equivalent CCG/ISI statistics. Never label +metrics from the bounded subset as full-data measurements. Windows identified +manually in a future Unit Stability View may motivate a regenerated package; +automated anomaly detection is out of scope. + +The upstream `20_000` waveform cap per unit is **not** a mandatory local budget: +for 1000 units x 20k waveforms x 90 samples x 32 channels x 4 bytes it would +approach **230 GB** uncompressed. Extraction, transfer, storage and bounded +GUI consumption require independently configurable *total* byte/spike budgets. + +## 6. Unit Stability evidence from the full recording + +A Unit Stability View should work on ordinary 1-10 h recordings too. For a +selected cluster it plots time-binned **full-sorting** spike count / firing rate, +amplitude median/quantiles, depth/position and presence/coverage when those +quantities exist in the source. Use an explicit time axis, valid acquisition +exposure per bin, data-availability flags, and recording gaps. Counts divided +by wall-clock bin width are wrong for acquisition gaps. No missing metric should +be silently synthesized. + +Initial storage may use regular homogeneous `.npy` arrays plus a small manifest, +with explicit row-to-cluster-ID mapping and bin edges; exact metric schema and +plot integration belong to the Unit Stability PR. At each full-data curation +iteration, merged/split clusters must receive **correctly recomputed or +incrementally updated** summaries, not merely the stale parent-unit curves. + +Current `BaseController.get_mean_firing_rate()` divides the loaded cluster's +`n_spikes` by `model.duration`; this would severely undercount a bounded unit. +When a bounded package is detected, its full-count/exposure-aware value must +replace that calculation wherever presented. The same provenance distinction +applies to the Cluster View, correlograms, ISI and other proxy-based statistics. + +Window statistics need explicit observation intervals. Do not connect ISIs or +CCG pairs across independent segments or unsupported gaps. CCG normalization +must use a declared lag-exposure estimator for those intervals; initially hide +unsupported normalized diagnostics. Whole-window sampling, rescue selection +and incomplete waveform coverage do not establish unbiased full-data quality +metrics or chronic biological unit identity. + +## 7. Semantic curation and full-data replay + +The current `Clustering` operates on arrays of loaded spike rows, creates new +cluster IDs during `assign/split`, and saves those local assignments. They +cannot by themselves define the fate of billions of unobserved spikes. + +Before mutations in a bounded GUI session, record **versioned semantic events** +with preconditions, affected source clusters, deterministic operation parameters, +resolved cluster IDs and provenance. Track edits through existing undo/redo and +save. Apply them in order against the *complete* local sorting to write a new +curated output (never overwrite the original). + +| Operation | Initial replay policy | +| --- | --- | +| Merge complete units | Reapply to every source spike in the units; replayable | +| Cluster quality/metadata labels | Replay per resulting cluster identity; replayable | +| Threshold split | Replay only if the predicate/feature definition is serialized and an equivalent full-data per-spike attribute exists; otherwise disallow | +| Lasso or arbitrary selected spike-ID split | Not replayable for unseen spikes by default; **block in bounded mode** unless a valid full-data rule is supplied | +| Undo/redo | Journal must represent the committed final event sequence and allow exact save/reopen, not duplicate reverted edits | + +Unbounded/ordinary Phy behavior must remain unchanged. It is not acceptable to +silently treat a selection of bounded spike IDs as a valid full-unit split. +Existing `curation.json` merge proposals and `curation_review.json` are separate +producer/review artifacts; the new semantic event journal must not overwrite +either file. Re-running `prepare-large` after `apply-curation` may reuse the same +source spike/waveform bytes because curation changes assignments, not spike +identity. + +For the first editable release, support merges and labels only. Keep all splits +blocked until their specific replay rules pass end-to-end tests. Allocate IDs +from the complete unit catalog, including units absent from the subset. Record +resolved inherited metadata, rather than recomputing it from full parent counts. +Commit journal, assignments and metadata as one validated save generation; +reopen must recover a coherent generation and allocator state. Validate operation +intent before mutation, including plugin and console entry points. + +## 8. Test/reference fixture and future acceptance + +`phy/apps/tests/large_recording_fixtures.py` deterministically writes a minimal +32-spike, **1000 h** full Phy-format sorting and a bounded eight-spike package, +including upstream waveforms for eight different source rows and remapped +bounded waveforms for five. The fixture intentionally omits the raw binary. +`phy/apps/tests/test_large_recording_contract.py` asserts: + +- exact `int64` sample indexing well past the 32-bit limit, source-order and + time preservation; +- full -> bounded -> waveform mapping, including copied waveform/channel rows; +- existing Phy waveform filenames, row/dtype/shape and `-1` padding invariants; +- simple window array dtypes, sample-coordinate bounds and shared row alignment; +- source fingerprint agreement, separate source-vs-bounded identity; +- empty/disjoint intersections and existing phylib load compatibility. + +**These are reference contract tests only:** they do not claim that +`prepare-large`, Unit Stability or semantic replay already exists. Subsequent +PRs should reuse the fixture but replace the reference remapping with tests of +the production command. Add mismatched-source, reordered-row, excessive-memory, +partially covered units, gap, sparse feature and replay/undo corruption tests +before enabling bounded curation on real datasets. + +## 9. Ownership and implementation order + +1. **This PR:** Phy-side design, source-coordinate/format reference fixture and + tests only. No GUI changes, no new CLI, no upstream exporter changes. +2. **Unit Stability:** full-data summaries and selected-unit GUI view, initially + usable on normal recordings. Keep user-visible full/partial provenance clear. +3. **Semantic curation journal:** integration with `Supervisor`, event semantics, + undo/save/reopen and blocking unsafe splits in bounded mode. +4. **`prepare-large`:** separate streaming batch CLI, input validation, window + selection, output/remapped waveform files and bounded-manifest generation. +5. **`apply-curation`:** validate/replay semantic actions against full local + sorting, write a new curated full sorting, verify, then regenerate a bounded + package. Test deterministic repeatability and failures atomically. + +A future release may choose a different PR order for journal/prepare integration, +but **do not ship an editable bounded GUI without replay safety**. + +Agent starting points: `AGENTS.md`, `design/README.md`, +`phy/apps/__init__.py` (Click CLI), `phy/apps/template/gui.py` (controller), +`phy/apps/base.py` (views/rates/save), `phy/cluster/{clustering,supervisor}.py` +(actions/history), `phy/apps/template/tests/test_gui.py`, and +`phy/apps/tests/test_large_recording_contract.py`. The existing waveform +reader is in the separate `phylib/io/model.py` dependency. + +## 10. Decisions not frozen by this Phy-side PR + +The upstream team should review the exact optional window-sidecar names, AIND +sorting asset identity/fingerprinting, segment/time/recording-block semantics, +waveform extraction alignment, total storage budget, and whether windows or a +more general sampling-plan format fits its pipeline best. Phy should accept the +existing three-file waveform format regardless. Values such as `1 h`, `30 s`, +`2,000` and `20,000` are preliminary, not schema requirements. + +Code Ocean handles **creation of a reusable evidence reservoir**; Phy handles +**bounded selection, GUI coordinate remapping, full-duration summaries, +semantic curation and replay**. Neither side should infer an absent waveform +or silently redefine source spike IDs. + +## Implementation references + +- [Phy `Clustering.assign`](../phy/cluster/clustering.py) and + [Supervisor](../phy/cluster/supervisor.py) for current row-based edits. +- [Template GUI](../phy/apps/template/gui.py) and + [Waveform/Feature mixins](../phy/apps/base.py) for standard stored-waveform + support and full/proxy metric safeguards. +- [Existing stored-waveform GUI test](../phy/apps/template/tests/test_gui.py). +- [SpikeInterface `export_to_phy` source (AIND inspected commit)](https://github.com/SpikeInterface/spikeinterface/blob/896ea840da72b4a5f06dcf8870ad820d20fe7031/src/spikeinterface/exporters/to_phy.py). diff --git a/design/large-recording-integration-plan.md b/design/large-recording-integration-plan.md new file mode 100644 index 000000000..004eb8c41 --- /dev/null +++ b/design/large-recording-integration-plan.md @@ -0,0 +1,244 @@ +# Long recording audit and integration plan + +## Assessment + +The downloaded contract bundle is a useful foundation. Keep the bounded GUI, +immutable full sorting, explicit source-row mapping, and full-data replay model. +Do not enable editing until replay and persistence agree with the GUI. A 1000-hour +timestamp fixture validates coordinate range; it does not validate capacity or +scientific representativeness. + +This review targets phy `7e439491` and the downloaded +`phy_large_recording_contract_bundle.zip`. The accompanying contract remains a +proposal. This plan refines its implementation order and supplies additional +requirements; the phases below govern enablement. + +## Findings that affect correctness + +1. **Identity needs two layers.** A spike-coordinate fingerprint identifies + immutable rows and their time/channel/feature provenance. An assignment + revision identifies the starting full cluster assignments and metadata. + Replay must validate both. A times-only hash cannot distinguish recordings + with identical timestamps or changes to feature values. Include the acquisition + identity, time base, relevant immutable array digests and schema in coordinate + identity; hash assignments and metadata separately for each revision. Record + parent revision, journal digest, output revision and preparation identity. + Compute hashes incrementally, without `read_bytes()` on production arrays. + +2. **Cluster IDs must come from the full namespace.** + [Clustering](../phy/cluster/clustering.py) initializes its allocator from the + maximum loaded cluster ID. A subset can omit the highest full ID. Seed the + allocator from a full unit catalog and persist its high-water mark. Record + explicit output IDs in events and reject collisions during replay. Units with + no bounded evidence remain in the catalog and output, with missing evidence + visible to the user. + +3. **Save is a transaction.** + [BaseController](../phy/apps/base.py) currently saves assignments and metadata + separately; [Supervisor.save](../phy/cluster/supervisor.py) emits further save + events and clears dirty state. Adding another journal file to that chain does + not make it crash consistent. Bounded mode needs immutable save generations + containing assignments, metadata, journal and identity, published by a single + commit pointer. Reopen only complete validated generations. Preserve the last + valid generation after interruption; keep dirty state after a failed commit. + Define whether undo survives reopen. Recommended v1: reopen establishes a new + undo baseline while retaining the committed semantic history for replay. + +4. **Record resolved metadata.** `Clustering._do_merge` selects the largest + parent using loaded counts, and Supervisor inherits its metadata. Full and + sampled counts can choose different parents. Serialize the resolved group and + custom labels in merge events, including an explicit policy for conflicting + labels. Replay must not infer this choice from full counts. + +5. **Capture intent before mutation.** + [AmplitudeView.on_request_split](../phy/cluster/views/amplitude.py) returns + selected row IDs and clears the threshold. A listener after clustering cannot + recover the predicate. Route bounded edits through a command service before + any mutation. Gate direct assign/split, plugins, console operations, shortcuts, + merge proposals and threshold providers at the mutation boundary. V1 supports + whole-unit merges and labels; block every split until its full-data semantics + are implemented and tested. + +6. **Statistics require observation intervals.** Preserve shared contiguous + windows and segment boundaries. ISIs must not connect windows or acquisition + gaps. CCGs must exclude pairs crossing unsupported boundaries, and their + normalization must match observed lag exposure; the existing full-duration + baseline in `BaseController._get_correlograms_rate` is not valid for a window + subset. Initially suppress unsupported normalization and diagnostic claims. + Label window statistics as sampled evidence. Rescue selection and waveform + availability introduce bias; they do not justify extrapolating quality, + contamination, refractory violations or chronic unit identity to the full run. + +7. **Define time and channel coordinates.** V1 accepts one validated monotonic + sample axis with a fixed sampling rate and explicit valid acquisition + intervals. Reject unsupported segment layouts rather than concatenate silently. + Preserve tied timestamps and source row order. Sparse waveform channel IDs + index model channels; `channel_map.npy` maps these to raw-file columns. They + are not interchangeable with hardware or SpikeInterface channel IDs. Test a + nonidentity map, sparse padding, whitening/scaling and waveform alignment. + Keep sample coordinates as integers and CPU times as float64; subtract the + viewport origin before converting fine-scale plotting positions to float32. + +8. **All preparation products need budgets.** A dense units-by-time-bin summary, + exact quantile calculation, waveform gather, or full index inversion can + exceed RAM despite streamed input. Specify batch, output, summary, cache and + GUI memory limits, plus temporary disk estimates. Distinguish peak working + memory from file-backed pages. Whole shared windows exceeding the spike budget + must be shortened, rejected or replaced with documented deterministic rules; + do not silently thin spikes within a window and retain its statistical claims. + +9. **Persist the final window plan.** Store retained intervals, segment/block + identity, survey/rescue classification and valid exposure in the bounded + package. A seed and parameters do not identify trimmed or replaced windows. + Count acquisition exposure once when composing merged-unit summaries. + +## Module boundaries + +Use a small `phy/apps/large_recording/` package, with pure services callable +without Qt and thin Click/controller adapters. Refine filenames while coding; +keep these responsibilities separate: + +| Responsibility | Contract | +| --- | --- | +| Source adapter and validation | Stream canonical arrays; classify per-spike, template, channel and cluster data explicitly; reject ambiguous unsupported arrays | +| Manifest and identity | Validate versions, paths, coordinate identity, assignment revisions, exposure and capabilities | +| Preparation | Deterministic window plan, bounded output, streamed waveform remapping, budget report | +| Summaries | Full counts/exposure, availability, declared exact or approximate estimators and multiresolution queries | +| Semantic commands and journal | Operation validation, explicit IDs/metadata, history cursor and transactional commit | +| Replay | Pure event interpretation, chunked output assignments, invariants and lineage | +| GUI adapter | Capability gating, evidence labels, bounded model/controller integration | + +Do not load the complete source through TemplateModel or Clustering in batch +commands. Do not hide full-data scans in a selected-unit GUI callback. Limit +changes to phylib to demonstrated loader/coordinate fixes, with separate tests +and dependency requirements. Preserve existing ordinary-dataset behavior. + +## Ordered PRs and acceptance gates + +### 1. Contract and reference fixtures + +Land the revised contract, this plan and format fixtures on a design branch. +Fix the bundle's missing `dtype` in `params.py`, allow equal sample times, and +reject malformed reference row IDs. Run the real released-phylib loader test +without accepting a skip. Its success proves this small file layout loads, +not that all GUI workflows or long-recording statistics are supported. + +### 2. Source validation and summary engine + +Implement identities, assignment revisions, array inventory, exposure and +capability validation independently of Qt. Start with full counts and rates; +add amplitude/depth only with defined units and available source attributes. +Do not add per-bin quantiles until their exact/approximate algorithm, merge +behavior and memory costs are specified. Medians cannot be merged by averaging +parent medians; invalidate or recompute unavailable derived summaries. + +Gate: exact tiny-oracle counts; missing exposure; gaps; source/feature mismatch; +reordered rows; column-vector input arrays; unknown versions; unsupported +segments; bounded peak memory as source size grows; actionable disk estimates. + +### 3. Read-only preparation and inspection + +Implement `prepare-large` with deterministic shared windows, rescue policies, +per-unit evidence reports and explicit budgets. Write into a temporary sibling +directory and publish only after complete validation. Rebuild paths in params, +subset every registered per-spike array, retain template-indexed structures, and +avoid copying stale `.phy` caches and derived cluster metrics. Unknown attributes +must be explicitly included, excluded with a report, or rejected. + +Add a bounded-manifest GUI adapter with authoritative duration, full/proxy +counts and unsupported-view safeguards. Until phase 6, require read-only bounded +sessions, including save and plugin mutation entry points. + +Gate: production command vs independently specified expected arrays; shuffled +channel mapping; actual `get_waveforms()` values; sparse PC feature alignment; +missing/partial waveform coverage; tied samples; zero evidence units; empty +selection policy; deterministic budgets; interrupted publication; no source +writes; GUI open/close and time-axis precision tests. + +### 4. Semantic commands and durable saves + +Implement merge/label command validation, full-catalog ID allocation, resolved +metadata, undo/redo active history and transactional generations. Keep the +feature disabled for editable bounded sessions while replay is incomplete. +Existing `curation.json` and `curation_review.json` retain their separate roles. + +Gate: merge chains; conflicting labels; undo then branch; redo; reopen baseline; +omitted high-ID units; proposal-driven merges; rejected direct split/assign; +failed-save dirty state; fault injection at every commit boundary; assignments +equal the journal's projection onto bounded rows. + +### 5. Full-data replay + +Implement `apply-curation` against an exact source assignment revision. For v1 +merges, resolve the final source-unit mapping once, then stream assignments into +a new full dataset. Preserve row count/order, times and immutable arrays; write +metadata and lineage coherently. Reject repeated application to the wrong parent +revision. Publish only a verified complete output. Reprepare from that revision +with the same coordinate identity and fresh revision-dependent summaries. + +Gate: compare every assignment with an independent tiny oracle; preserve all +unseen spikes; replay chains and labels exactly; reject mismatched parent or +corrupted journal; interruption never exposes a complete-looking partial output; +same source/events produce the same semantic result; source bytes unchanged. + +### 6. Enable bounded merges and labels with Unit Stability + +Expose editable bounded mode only when phases 3–5 pass together. Integrate a +Unit Stability view that distinguishes acquisition exposure, evidence windows, +available measurements and unresolved identity. Add bounded status and operation +capabilities to the existing workflow. Count/exposure summaries can update for +merges; quantiles and other nonadditive metrics require recomputation or explicit +unavailability. Keep all splits blocked. + +Gate: prepare → inspect → merge/label → undo/redo → save/reopen → replay → +reprepare → verify. Include ordinary 1–10 h datasets to prevent regressions. +Run `make test-full`, `make doc-check`, and `uv build` when CLI/package changes +are included. Complete manual smoke testing with an actual chronic dataset. + +### 7. Optional predicate splits + +Add one operation at a time after the initial workflow is accepted. Store feature +identity/units, predicate operator, threshold, missing-value policy, parent +revision and explicit child IDs. The same predicate must evaluate identically +on GUI evidence and all source spikes. Stored waveform-derived or local PCA +amplitudes do not automatically define a full-data predicate. Lasso splits +remain unavailable without a separately validated full-data rule. + +## Capacity and scientific acceptance + +Use three kinds of evidence: tiny exact-oracle datasets for correctness; +generated high-density on-disk datasets for resource behavior; real chronic +recordings for usability and scientific acceptance. Duration, spike count, +number of units, array widths and available waveform coverage are separate axes. +Measure preparation/replay throughput, peak process memory, temporary disk, +GUI startup and selected-unit update latency on documented hardware. Establish +acceptance budgets from those measurements before advertising capacity. + +Have a domain curator review known drift, rare/bursting units, transient +artifacts, gaps and intentionally incorrect merges. Compare selected evidence +with withheld contiguous windows and full-data diagnostics where available. +Record what the curator can and cannot infer; finite selected evidence cannot +guarantee biological identity throughout 1000 hours. Software integrity and +scientific evidence sufficiency are separate release criteria. + +## Producer decisions + +Agree with the producer team on source asset identity, full unit IDs, authoritative +duration/exposure, segment mapping, waveform time/channel/amplitude semantics, +reservoir coverage and total storage costs. Existing three-file waveforms remain +supported; proposed window sidecars must remain optional until jointly agreed. +The inspected [SpikeInterface exporter revision](https://github.com/SpikeInterface/spikeinterface/blob/896ea840da72b4a5f06dcf8870ad820d20fe7031/src/spikeinterface/exporters/to_phy.py) +supports one segment and distinguishes Phy channel indices from exported original +channel IDs. Do not assume that arbitrary multi-session inputs already satisfy +this contract or that a deployed exporter matches this inspected revision. + +## Validation of this design branch + +On 2026-10-13, the locked development environment with phylib 2.7.1 passed +all ten reference tests, including the loader and returned waveform values. +`make test-apps format-check` passed all 165 application tests, lint and +formatting checks. Patch whitespace validation also passed. The test process +reported pending ipykernel tasks during shutdown after successful completion. +This branch changes design documents and reference tests only; it does not +implement preparation, replay, transactional saves or a stability view, and +does not establish realistic long-recording capacity. diff --git a/phy/apps/tests/large_recording_fixtures.py b/phy/apps/tests/large_recording_fixtures.py new file mode 100644 index 000000000..7041213bd --- /dev/null +++ b/phy/apps/tests/large_recording_fixtures.py @@ -0,0 +1,153 @@ +"""Small, deterministic on-disk example of a 1000-hour two-stage Phy dataset. + +This is reference test data, not a prepare-large implementation. The fake +recording has 32 spikes spread across 1000 hours, not 1000 hours of raw traces. +The full and bounded folders use ordinary Phy filenames. +""" + +import hashlib +import json +import shutil +from dataclasses import dataclass +from pathlib import Path + +import numpy as np + + +@dataclass(frozen=True) +class LongRecordingFixture: + full: Path + bounded: Path + global_ids: np.ndarray + upstream_waveform_ids: np.ndarray + bounded_waveform_ids: np.ndarray + + +def _sha256(path): + return hashlib.sha256(path.read_bytes()).hexdigest() + + +def _reference_remap(global_ids, upstream_ids): + """Reference intersection for sorted, unique, nonnegative int64 row IDs.""" + global_ids = np.asarray(global_ids) + upstream_ids = np.asarray(upstream_ids) + for ids in (global_ids, upstream_ids): + if ids.ndim != 1 or ids.dtype != np.dtype('int64'): + raise ValueError('Row IDs must be one-dimensional int64 arrays.') + if np.any(ids < 0) or np.any(ids[1:] <= ids[:-1]): + raise ValueError('Row IDs must be nonnegative, sorted, and unique.') + if not len(global_ids) or not len(upstream_ids): + empty = np.array([], dtype=np.int64) + return empty, empty.copy() + positions = np.searchsorted(global_ids, upstream_ids) + keep = positions < len(global_ids) + keep[keep] &= global_ids[positions[keep]] == upstream_ids[keep] + return positions[keep].astype(np.int64), np.flatnonzero(keep).astype(np.int64) + + +def make_long_recording_fixture(root): + """Write one full Phy dataset and its expected bounded counterpart.""" + root = Path(root) + full, bounded = root / 'full', root / 'bounded' + full.mkdir(parents=True) + bounded.mkdir(parents=True) + + fs = 30_000 + num_samples = 1000 * 3600 * fs # Far beyond signed int32 sample indices. + samples = np.linspace(100, num_samples - 100, 32, dtype=np.int64) + samples[8] = samples[5] # Simultaneous spikes retain distinct source row identities. + samples[6:8] = samples[5] + units = (np.arange(32) % 3).astype(np.int32) + amplitudes = np.arange(1, 33, dtype=np.float32) + templates = np.zeros((3, 12, 4), dtype=np.float32) + for unit in range(3): + templates[unit, :, unit] = -np.arange(12, dtype=np.float32) + + for name, array in ( + ('spike_times.npy', samples), + ('spike_clusters.npy', units), + ('spike_templates.npy', units), + ('amplitudes.npy', amplitudes), + ('templates.npy', templates), + ('channel_map.npy', np.arange(4, dtype=np.int32)), + ('channel_positions.npy', np.array([[0, 0], [20, 0], [0, 20], [20, 20]])), + ): + np.save(full / name, array) + (full / 'params.py').write_text( + "sample_rate = 30000.0\ndat_path = None\nn_channels_dat = 4\ndtype = 'int16'\n", + encoding='utf-8', + ) + + upstream_ids = np.array([1, 2, 8, 13, 18, 21, 28, 31], dtype=np.int64) + channels = np.array( + [[0, 1, -1] if i % 2 == 0 else [2, 3, -1] for i in range(len(upstream_ids))], + dtype=np.int32, + ) + waveforms = np.zeros((len(upstream_ids), 12, 3), dtype=np.float32) + for row, spike_id in enumerate(upstream_ids): + waveforms[row, :, 0] = spike_id + np.arange(12) / 12 + waveforms[row, :, 1] = -(spike_id + np.arange(12) / 12) + stem = '_phy_spikes_subset' + np.save(full / f'{stem}.spikes.npy', upstream_ids) + np.save(full / f'{stem}.channels.npy', channels) + np.save(full / f'{stem}.waveforms.npy', waveforms) + + # Proposed, optional upstream window metadata: simple homogeneous arrays. + starts = np.minimum(samples[upstream_ids] - 10, num_samples - 30 * fs) + bounds = np.column_stack((starts, starts + 30 * fs)).astype(np.int64) + types = np.zeros(len(upstream_ids), dtype=np.uint8) + types[-1] = 1 # rescue + strata = (samples[upstream_ids] // (3600 * fs)).astype(np.int32) + strata[-1] = -1 # rescue has no survey stratum + np.save(full / f'{stem}.window_bounds.npy', bounds) + np.save(full / f'{stem}.window_types.npy', types) + np.save(full / f'{stem}.window_strata.npy', strata) + source_hash = _sha256(full / 'spike_times.npy') + (full / f'{stem}.manifest.json').write_text( + json.dumps( + { + 'format': 'phy_spikes_subset', + 'format_version': 1, + 'source_sorting': {'num_spikes': len(samples), 'spike_times_sha256': source_hash}, + 'recording': { + 'sampling_frequency_hz': fs, + 'num_samples': num_samples, + 'num_channels': 4, + 'num_segments': 1, + }, + 'selection': {'algorithm': 'synthetic_windows_v1', 'seed': 42}, + 'waveform_extraction': {'nbefore_samples': 4, 'nafter_samples': 8}, + 'window_types': {'0': 'survey', '1': 'rescue'}, + }, + indent=2, + ) + + '\n', + encoding='utf-8', + ) + + global_ids = np.array([0, 2, 5, 8, 13, 21, 25, 31], dtype=np.int64) + for name in ('spike_times.npy', 'spike_clusters.npy', 'spike_templates.npy', 'amplitudes.npy'): + np.save(bounded / name, np.load(full / name)[global_ids]) + for name in ('templates.npy', 'channel_map.npy', 'channel_positions.npy', 'params.py'): + shutil.copyfile(full / name, bounded / name) + np.save(bounded / '_phy_spike_global_ids.npy', global_ids) + + bounded_rows, waveform_rows = _reference_remap(global_ids, upstream_ids) + np.save(bounded / f'{stem}.spikes.npy', bounded_rows) + np.save(bounded / f'{stem}.channels.npy', channels[waveform_rows]) + np.save(bounded / f'{stem}.waveforms.npy', waveforms[waveform_rows]) + (bounded / '_phy_curation_manifest.json').write_text( + json.dumps( + { + 'format': 'phy_bounded_curation', + 'format_version': 1, + 'source': {'num_spikes': len(samples), 'spike_times_sha256': source_hash}, + 'global_spike_ids_file': '_phy_spike_global_ids.npy', + 'duration_seconds': 1000 * 3600, + }, + indent=2, + ) + + '\n', + encoding='utf-8', + ) + return LongRecordingFixture(full, bounded, global_ids, upstream_ids, bounded_rows) diff --git a/phy/apps/tests/test_large_recording_contract.py b/phy/apps/tests/test_large_recording_contract.py new file mode 100644 index 000000000..8e882afc1 --- /dev/null +++ b/phy/apps/tests/test_large_recording_contract.py @@ -0,0 +1,151 @@ +"""Reference contract tests for future prepare-large and waveform remapping. + +These tests deliberately do not exercise a production prepare-large command: +that command does not exist yet. Later implementations should reuse this +fixture and replace reference-only checks with command-level assertions. +""" + +import hashlib +import json + +import numpy as np +import pytest +from phylib.io.model import load_model + +from .large_recording_fixtures import _reference_remap, make_long_recording_fixture + + +@pytest.fixture +def long_recording(tmp_path): + return make_long_recording_fixture(tmp_path) + + +def test_long_recording_uses_exact_64_bit_sample_times(long_recording): + full = np.load(long_recording.full / 'spike_times.npy') + bounded = np.load(long_recording.bounded / 'spike_times.npy') + assert full.dtype == bounded.dtype == np.dtype('int64') + assert full[-1] > np.iinfo(np.int32).max + assert full[-1] / 30_000 > 999 * 3600 + np.testing.assert_array_equal(bounded, full[long_recording.global_ids]) + assert np.all(np.diff(long_recording.global_ids) > 0) + assert np.all(np.diff(bounded) >= 0) + assert bounded[2] == bounded[3] # equal times do not collapse distinct spikes + + +def test_two_stage_row_indices_and_waveform_data(long_recording): + full = long_recording.full + bounded = long_recording.bounded + global_ids = np.load(bounded / '_phy_spike_global_ids.npy') + full_waveform_ids = np.load(full / '_phy_spikes_subset.spikes.npy') + bounded_waveform_ids = np.load(bounded / '_phy_spikes_subset.spikes.npy') + assert global_ids.dtype == bounded_waveform_ids.dtype == np.dtype('int64') + np.testing.assert_array_equal( + global_ids[bounded_waveform_ids], np.intersect1d(full_waveform_ids, global_ids) + ) + upstream_rows = np.searchsorted(full_waveform_ids, global_ids[bounded_waveform_ids]) + for suffix in ('channels', 'waveforms'): + np.testing.assert_array_equal( + np.load(bounded / f'_phy_spikes_subset.{suffix}.npy'), + np.load(full / f'_phy_spikes_subset.{suffix}.npy')[upstream_rows], + ) + # A bounded row identifies one source row, and never a waveform tensor row. + assert bounded_waveform_ids.tolist() == [1, 3, 4, 5, 7] + assert global_ids[bounded_waveform_ids].tolist() == [2, 8, 13, 21, 31] + + +def test_ordinary_phy_waveform_files_are_aligned(long_recording): + bounded = long_recording.bounded + spike_ids = np.load(bounded / '_phy_spikes_subset.spikes.npy') + channels = np.load(bounded / '_phy_spikes_subset.channels.npy') + waveforms = np.load(bounded / '_phy_spikes_subset.waveforms.npy', mmap_mode='r') + assert spike_ids.ndim == 1 and np.all(np.diff(spike_ids) > 0) + assert channels.dtype == np.dtype('int32') + assert channels.shape == (len(spike_ids), waveforms.shape[2]) + assert waveforms.shape == (len(spike_ids), 12, 3) + assert np.all((channels == -1) | ((channels >= 0) & (channels < 4))) + assert np.all(waveforms[:, :, -1] == 0) # -1 means a zero-padded channel + assert spike_ids[-1] < len(np.load(bounded / 'spike_times.npy')) + + +def test_window_arrays_use_samples_and_simple_dtypes(long_recording): + full = long_recording.full + bounds = np.load(full / '_phy_spikes_subset.window_bounds.npy') + types = np.load(full / '_phy_spikes_subset.window_types.npy') + strata = np.load(full / '_phy_spikes_subset.window_strata.npy') + spike_samples = np.load(full / 'spike_times.npy') + assert bounds.shape == (len(types), 2) + assert len(types) == len(strata) + assert bounds.dtype == np.dtype('int64') + assert types.dtype == np.dtype('uint8') + assert strata.dtype == np.dtype('int32') + assert np.all(bounds[:, 1] > bounds[:, 0]) + assert np.all(bounds[:, 1] <= 1000 * 3600 * 30_000) + assert np.all((types == 0) | (types == 1)) + assert strata[-1] == -1 and types[-1] == 1 + source_waveform_times = spike_samples[long_recording.upstream_waveform_ids] + assert np.all((bounds[:, 0] <= source_waveform_times) & (source_waveform_times < bounds[:, 1])) + + +def test_reference_remap_handles_empty_and_disjoint_inputs(): + a = np.array([14, 19, 117], dtype=np.int64) + b = np.array([2, 4, 119], dtype=np.int64) + for left, right in ((a, b), (a, b[:0]), (a[:0], b), (a[:0], b[:0])): + bounded_rows, source_rows = _reference_remap(left, right) + assert bounded_rows.dtype == source_rows.dtype == np.dtype('int64') + assert bounded_rows.shape == source_rows.shape == (0,) + rows, upstream_rows = _reference_remap(a, np.array([14, 15, 117, 118])) + assert rows.tolist() == [0, 2] + assert upstream_rows.tolist() == [0, 2] + + +@pytest.mark.parametrize('ids', [[2, 1], [1, 1], [-1, 1]]) +def test_reference_remap_rejects_invalid_row_order(ids): + valid = np.array([1, 2], dtype=np.int64) + invalid = np.array(ids, dtype=np.int64) + for left, right in ((valid, invalid), (invalid, valid)): + with pytest.raises(ValueError, match='nonnegative, sorted, and unique'): + _reference_remap(left, right) + + +def test_manifests_bind_source_index_space_not_mutable_clusters(long_recording): + full = long_recording.full + bounded = long_recording.bounded + source_hash = hashlib.sha256((full / 'spike_times.npy').read_bytes()).hexdigest() + upstream = json.loads((full / '_phy_spikes_subset.manifest.json').read_text()) + downstream = json.loads((bounded / '_phy_curation_manifest.json').read_text()) + assert upstream['source_sorting']['spike_times_sha256'] == source_hash + assert downstream['source']['spike_times_sha256'] == source_hash + assert upstream['source_sorting']['num_spikes'] == len(np.load(full / 'spike_times.npy')) + assert downstream['global_spike_ids_file'] == '_phy_spike_global_ids.npy' + assert downstream['duration_seconds'] == 1000 * 3600 + assert hashlib.sha256((bounded / 'spike_times.npy').read_bytes()).hexdigest() != source_hash + + +def test_bounded_dataset_loads_with_existing_phylib(long_recording): + """The old Phy loader consumes bounded rows, not original global indices.""" + model = load_model(long_recording.bounded / 'params.py') + try: + np.testing.assert_array_equal( + model.spike_waveforms.spike_ids, long_recording.bounded_waveform_ids + ) + assert model.n_spikes == len(long_recording.global_ids) + assert model.n_samples_waveforms == 12 + assert model.spike_times[-1] > 999 * 3600 + np.testing.assert_array_equal( + model.get_waveforms(long_recording.bounded_waveform_ids, channel_ids=[0, 1, 2, 3]), + _expected_dense_waveforms(long_recording.bounded), + ) + finally: + model.close() + + +def _expected_dense_waveforms(path): + """Independent dense expansion of the fixture's sparse channel slots.""" + channels = np.load(path / '_phy_spikes_subset.channels.npy') + waveforms = np.load(path / '_phy_spikes_subset.waveforms.npy') + expected = np.zeros((len(channels), 12, 4), dtype=waveforms.dtype) + for row, channel_row in enumerate(channels): + for slot, channel in enumerate(channel_row): + if channel >= 0: + expected[row, :, channel] = waveforms[row, :, slot] + return expected From 38f3e7e56505712caf024c4c1b05f907a11465ef Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 10:07:40 +0200 Subject: [PATCH 02/53] Plan one implementation PR with explicit standard-recording compatibility gates --- design/README.md | 4 +-- design/large-recording-curation.md | 8 ++--- design/large-recording-integration-plan.md | 37 ++++++++++++++++++++-- 3 files changed, 41 insertions(+), 8 deletions(-) diff --git a/design/README.md b/design/README.md index 995206b0c..27af3605f 100644 --- a/design/README.md +++ b/design/README.md @@ -63,7 +63,7 @@ The implementation and user documentation are complete on the unreleased phy The [long-recording curation Phy-side design contract](large-recording-curation.md) describes bounded local datasets for ~1000-hour sortings, the three spike-index spaces, optional upstream waveform evidence, full-duration metrics, replay safety, -and the sequence of implementation PRs. The accompanying synthetic 1000-hour +and the implementation stages. The accompanying synthetic 1000-hour fixture and reference tests are in `phy/apps/tests/large_recording_fixtures.py` and `phy/apps/tests/test_large_recording_contract.py`. @@ -71,5 +71,5 @@ This is a proposal and a reference test contract, **not yet** a `prepare-large` implementation or an upstream export-format agreement. The [integration audit and plan](large-recording-integration-plan.md) refines -the contract with correctness findings, module boundaries, ordered PRs and +the contract with correctness findings, module boundaries, ordered commits in one PR and acceptance gates. Follow its gates before enabling editable bounded sessions. diff --git a/design/large-recording-curation.md b/design/large-recording-curation.md index 0d3dfbaab..7e9b11388 100644 --- a/design/large-recording-curation.md +++ b/design/large-recording-curation.md @@ -3,11 +3,11 @@ **Status:** proposed; implementation sequence and file contracts for review. This specification is for Phy-side development; it does not authorize changes to the AIND/Code Ocean export pipeline. Current Phy behavior remains unchanged until -subsequent implementation PRs land. +the implementation is complete and validated. The [integration audit and plan](large-recording-integration-plan.md) refines this proposal with assignment revisions, transactional persistence, capability -gates and ordered PR acceptance criteria. Its enablement gates take precedence +gates and ordered commit acceptance criteria for one implementation PR. Its enablement gates take precedence over the original implementation sequence in Section 9. ## 1. Objective and boundaries @@ -310,8 +310,8 @@ before enabling bounded curation on real datasets. sorting, write a new curated full sorting, verify, then regenerate a bounded package. Test deterministic repeatability and failures atomically. -A future release may choose a different PR order for journal/prepare integration, -but **do not ship an editable bounded GUI without replay safety**. +The integration plan now organizes these stages as commits within a single PR, +rather than separate PRs. **Do not ship an editable bounded GUI without replay safety**. Agent starting points: `AGENTS.md`, `design/README.md`, `phy/apps/__init__.py` (Click CLI), `phy/apps/template/gui.py` (controller), diff --git a/design/large-recording-integration-plan.md b/design/large-recording-integration-plan.md index 004eb8c41..ee6270afa 100644 --- a/design/large-recording-integration-plan.md +++ b/design/large-recording-integration-plan.md @@ -113,11 +113,18 @@ commands. Do not hide full-data scans in a selected-unit GUI callback. Limit changes to phylib to demonstrated loader/coordinate fixes, with separate tests and dependency requirements. Preserve existing ordinary-dataset behavior. -## Ordered PRs and acceptance gates +## One implementation PR with ordered commits and acceptance gates + +Implement the complete workflow on `feature/long-recording-curation` in the +main phy checkout. Use the stages below as reviewable commit groups within one +PR. Intermediate capability gates support development; merge the PR only after +the complete prepare, curate, save, replay and regenerate workflow passes its +acceptance checks. Predicate splits require their own full-data equivalence +checks within the same PR if included in its supported functionality. ### 1. Contract and reference fixtures -Land the revised contract, this plan and format fixtures on a design branch. +Start with the revised contract, this plan and format fixtures. Fix the bundle's missing `dtype` in `params.py`, allow equal sample times, and reject malformed reference row IDs. Run the real released-phylib loader test without accepting a skip. Its success proves this small file layout loads, @@ -204,6 +211,32 @@ on GUI evidence and all source spikes. Stored waveform-derived or local PCA amplitudes do not automatically define a full-data predicate. Lasso splits remain unavailable without a separately validated full-data rule. +## Standard recording compatibility gate + +Recording length must never select a new behavior implicitly. Activate bounded +curation only through an explicit validated bounded manifest. Without that +manifest, retain the standard loader, selector, metrics, mutation capabilities, +save format and history behavior. A malformed bounded manifest must produce an +actionable error rather than silently enter standard editable mode. Optional +Unit Stability on ordinary recordings must not replace their existing views, +change their default layout or introduce full-source scans at GUI startup. + +Keep the semantic command, replay and transactional save implementation behind +the bounded adapter wherever possible. Any necessary shared-code change requires +focused standard-mode regression coverage in addition to bounded-mode tests. +Do not impose bounded split restrictions or journal files on ordinary datasets. + +Before merging the single PR, run `make test-full` and verify ordinary datasets +with raw traces, stored waveforms only, and sparse features. Cover standard +merge and label inheritance, lasso/threshold/template splits, undo/redo and +branching, save/reopen assignments and metadata, merge proposals, plugin-driven +edits, channel mapping, sampled views and existing rate/ISI/CCG behavior. Assert +that ordinary saves do not create bounded journals or manifests. Compare startup +memory and selection latency on the same ordinary datasets before and after the +change; any meaningful regression must be explained and resolved before merge. +Existing tests and these checks establish compatibility evidence; the plan +itself does not guarantee compatibility before implementation. + ## Capacity and scientific acceptance Use three kinds of evidence: tiny exact-oracle datasets for correctness; From 5582419649922ee04230a073be04c32e056136b6 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 10:37:42 +0200 Subject: [PATCH 03/53] Validate streamed sorting sources, acquisition exposure and revision identity --- phy/apps/large_recording/__init__.py | 1 + phy/apps/large_recording/source.py | 532 ++++++++++++++++++ phy/apps/large_recording/tests/__init__.py | 1 + phy/apps/large_recording/tests/test_source.py | 240 ++++++++ 4 files changed, 774 insertions(+) create mode 100644 phy/apps/large_recording/__init__.py create mode 100644 phy/apps/large_recording/source.py create mode 100644 phy/apps/large_recording/tests/__init__.py create mode 100644 phy/apps/large_recording/tests/test_source.py diff --git a/phy/apps/large_recording/__init__.py b/phy/apps/large_recording/__init__.py new file mode 100644 index 000000000..373145000 --- /dev/null +++ b/phy/apps/large_recording/__init__.py @@ -0,0 +1 @@ +"""Bounded evidence preparation and full-sorting curation replay.""" diff --git a/phy/apps/large_recording/source.py b/phy/apps/large_recording/source.py new file mode 100644 index 000000000..89fd2c48c --- /dev/null +++ b/phy/apps/large_recording/source.py @@ -0,0 +1,532 @@ +"""Validated, file-backed source sorting on one monotonic sample clock.""" + +import csv +import ctypes +import errno +import hashlib +import json +import os +import runpy +import sys +from pathlib import Path + +import numpy as np + +PER_SPIKE = frozenset( + ( + 'spike_times.npy', + 'spike_clusters.npy', + 'spike_templates.npy', + 'amplitudes.npy', + 'pc_features.npy', + 'template_features.npy', + 'spike_positions.npy', + 'spike_depths.npy', + ) +) +STATIC = frozenset( + ( + 'templates.npy', + 'templates_ind.npy', + 'channel_map.npy', + 'channel_positions.npy', + 'channel_shanks.npy', + 'channel_map_si.npy', + 'channel_groups.npy', + 'whitening_mat.npy', + 'whitening_mat_inv.npy', + 'similar_templates.npy', + 'pc_feature_ind.npy', + 'template_feature_ind.npy', + ) +) +WAVEFORMS = frozenset( + ( + '_phy_spikes_subset.spikes.npy', + '_phy_spikes_subset.channels.npy', + '_phy_spikes_subset.waveforms.npy', + ) +) +WINDOW_SIDECARS = frozenset( + ( + '_phy_spikes_subset.window_bounds.npy', + '_phy_spikes_subset.window_types.npy', + '_phy_spikes_subset.window_strata.npy', + ) +) + + +def hash_file(path, batch_bytes=1024 * 1024): + """Hash bytes incrementally, including the array header.""" + digest = hashlib.sha256() + with Path(path).open('rb') as stream: + for block in iter(lambda: stream.read(batch_bytes), b''): + digest.update(block) + return digest.hexdigest() + + +def hash_json(value): + """Hash canonical JSON, normalizing integer metadata dictionary keys.""" + + def normalize(item): + if isinstance(item, dict): + return {str(key): normalize(val) for key, val in item.items()} + if isinstance(item, (list, tuple)): + return [normalize(val) for val in item] + if isinstance(item, np.generic): + return item.item() + return item + + payload = json.dumps(normalize(value), sort_keys=True, separators=(',', ':'), allow_nan=False) + return hashlib.sha256(payload.encode('utf-8')).hexdigest() + + +def assignment_revision(path, metadata): + """Identify mutable assignments and resolved cluster metadata.""" + path = Path(path) + if path.is_dir(): + path = path / 'spike_clusters.npy' + return hash_json({'assignments': hash_file(path), 'metadata': metadata}) + + +def close_array(array): + """Release a file-backed array handle, including on Windows.""" + mapping = getattr(array, '_mmap', None) + if mapping is not None and not mapping.closed: + mapping.close() + + +def publish_directory(staged, destination): + """Atomically publish a complete directory without replacing any target. + + Ordinary POSIX rename can replace an empty destination directory. Native + exclusive rename prevents a racing publication from silently replacing it. + """ + if os.name == 'nt': + os.rename(staged, destination) + return + library = ctypes.CDLL(None, use_errno=True) + if sys.platform.startswith('linux'): + rename = getattr(library, 'renameat2', None) + if rename is None: + raise OSError(errno.ENOSYS, 'Atomic exclusive directory publication is unavailable.') + rename.argtypes = [ + ctypes.c_int, + ctypes.c_char_p, + ctypes.c_int, + ctypes.c_char_p, + ctypes.c_uint, + ] + rename.restype = ctypes.c_int + result = rename(-100, os.fsencode(staged), -100, os.fsencode(destination), 1) + elif sys.platform == 'darwin': + rename = getattr(library, 'renamex_np', None) + if rename is None: + raise OSError(errno.ENOSYS, 'Atomic exclusive directory publication is unavailable.') + rename.argtypes = [ctypes.c_char_p, ctypes.c_char_p, ctypes.c_uint] + rename.restype = ctypes.c_int + result = rename(os.fsencode(staged), os.fsencode(destination), 4) + else: + raise OSError(errno.ENOSYS, 'Atomic exclusive directory publication is unavailable.') + if result: + code = ctypes.get_errno() + raise OSError(code, os.strerror(code), str(destination)) + + +def _vector(array, name): + if array.ndim == 1 or (array.ndim == 2 and array.shape[1] == 1): + return array.reshape(-1) + raise ValueError(f'{name} must be a vector or column vector.') + + +def _metadata(path): + sidecar = path / '_phy_cluster_metadata.json' + if sidecar.exists(): + metadata = json.loads(sidecar.read_text(encoding='utf-8')) + if not isinstance(metadata, dict): + raise ValueError('Cluster metadata JSON must be a field mapping.') + result = {} + for field, values in metadata.items(): + if not isinstance(values, dict): + raise ValueError('Cluster metadata fields must map integer cluster IDs to values.') + result[field] = {int(key): value for key, value in values.items()} + if any(key < 0 for key in result[field]): + raise ValueError('Cluster metadata IDs must be nonnegative.') + return result + result = {} + for filename in sorted([*path.glob('cluster_*.tsv'), *path.glob('cluster_*.csv')]): + # cluster_info is generated GUI metrics, not a source label table. + if filename.stem == 'cluster_info': + continue + with filename.open(encoding='utf-8', newline='') as stream: + reader = csv.DictReader(stream, delimiter='\t' if filename.suffix == '.tsv' else ',') + if not reader.fieldnames or 'cluster_id' not in reader.fieldnames: + raise ValueError(f'{filename.name} requires a cluster_id column.') + for row in reader: + cluster_id = int(row['cluster_id']) + if cluster_id < 0: + raise ValueError('Cluster metadata IDs must be nonnegative.') + for field, value in row.items(): + if field != 'cluster_id': + result.setdefault(field, {})[cluster_id] = value + return result + + +class Source: + """Read source arrays in batches without constructing a GUI model. + + Duration must come from producer metadata or an explicit argument: the last + spike is never used as acquisition exposure. Intervals are half-open samples. + """ + + def __init__( + self, params_path, duration_seconds=None, valid_intervals=None, batch_size=100000 + ): + self.params_path = Path(params_path).resolve() + self.path = self.params_path.parent + self.params = { + key: value + for key, value in runpy.run_path(str(self.params_path)).items() + if not key.startswith('__') + } + self.batch_size = int(batch_size) + if self.batch_size <= 0: + raise ValueError('batch_size must be positive.') + if 'dtype' in self.params: + try: + raw_dtype = np.dtype(self.params['dtype']) + except (TypeError, ValueError) as error: + raise ValueError('params.py dtype must be a valid raw numeric dtype.') from error + if not np.issubdtype(raw_dtype, np.number): + raise ValueError('params.py dtype must be a valid raw numeric dtype.') + self.sample_rate = float(self.params.get('sample_rate', 0)) + if not np.isfinite(self.sample_rate) or self.sample_rate <= 0: + raise ValueError('A positive finite sample_rate is required.') + upstream = self.path / '_phy_spikes_subset.manifest.json' + recording = {} + if upstream.exists(): + info = json.loads(upstream.read_text(encoding='utf-8')) + if info.get('format') != 'phy_spikes_subset' or info.get('format_version') != 1: + raise ValueError('Unsupported waveform manifest format or version.') + recording = info.get('recording', {}) + upstream_rate = recording.get('sampling_frequency_hz', self.sample_rate) + if upstream_rate != self.sample_rate: + raise ValueError('Waveform manifest sampling rate disagrees with params.py.') + if self.params.get('num_segments', recording.get('num_segments', 1)) != 1: + raise ValueError('Only a single monotonic acquisition segment is supported.') + duration_samples = None + if duration_seconds is not None: + duration_samples = float(duration_seconds) * self.sample_rate + if ( + not np.isfinite(duration_samples) + or duration_samples <= 0 + or duration_samples > np.iinfo(np.int64).max + or not np.isclose(duration_samples, round(duration_samples), rtol=0, atol=1e-6) + ): + raise ValueError('duration_seconds must specify a positive integer sample count.') + duration_samples = int(round(duration_samples)) + if ( + 'num_samples' in self.params + and 'num_samples' in recording + and self.params['num_samples'] != recording['num_samples'] + ): + raise ValueError( + 'Producer sample counts disagree between params and waveform manifest.' + ) + declared_samples = self.params.get('num_samples', recording.get('num_samples')) + if declared_samples is None: + declared_samples = duration_samples + elif duration_samples is not None and int(declared_samples) != duration_samples: + raise ValueError('Explicit duration disagrees with acquisition metadata.') + if declared_samples is None: + raise ValueError( + 'Acquisition exposure is missing; provide duration_seconds or num_samples.' + ) + self.num_samples = int(declared_samples) + if ( + self.num_samples <= 0 + or self.num_samples > np.iinfo(np.int64).max + or self.num_samples != declared_samples + ): + raise ValueError('num_samples must be a positive int64 sample count.') + if ( + 'valid_intervals' in self.params + and 'valid_intervals' in recording + and not np.array_equal( + np.asarray(self.params['valid_intervals']), + np.asarray(recording['valid_intervals']), + ) + ): + raise ValueError( + 'Producer valid_intervals disagree between params and waveform manifest.' + ) + declared_intervals = self.params.get('valid_intervals', recording.get('valid_intervals')) + if valid_intervals is not None and declared_intervals is not None: + if not np.array_equal(np.asarray(valid_intervals), np.asarray(declared_intervals)): + raise ValueError('Explicit valid_intervals disagree with acquisition metadata.') + if valid_intervals is None: + valid_intervals = declared_intervals + intervals = [[0, self.num_samples]] if valid_intervals is None else valid_intervals + raw_intervals = np.asarray(intervals) + if raw_intervals.ndim != 2 or raw_intervals.shape[1] != 2 or not len(raw_intervals): + raise ValueError('valid_intervals must be nonempty sample [start, end) pairs.') + self.valid_intervals = raw_intervals.astype(np.int64) + if ( + not np.array_equal(raw_intervals, self.valid_intervals) + or np.any(self.valid_intervals[:, 0] < 0) + or np.any(self.valid_intervals[:, 1] > self.num_samples) + or np.any(self.valid_intervals[:, 1] <= self.valid_intervals[:, 0]) + or np.any(self.valid_intervals[1:, 0] < self.valid_intervals[:-1, 1]) + ): + raise ValueError( + 'valid_intervals must be ordered, disjoint integer acquisition samples.' + ) + names = {p.name for p in self.path.glob('*.npy')} + unknown = names - PER_SPIKE - STATIC - WAVEFORMS - WINDOW_SIDECARS + # Replay lineage and original optional sidecars are retained; bounded + # outputs deliberately cannot be used as full-source sorting inputs. + if unknown: + raise ValueError(f'Unregistered source arrays: {", ".join(sorted(unknown))}.') + self.arrays = { + name: np.load(self.path / name, mmap_mode='r', allow_pickle=False) + for name in sorted(names) + } + for required in ('spike_times.npy', 'spike_clusters.npy', 'spike_templates.npy'): + if required not in self.arrays: + raise ValueError(f'Missing required source array {required}.') + self.n_spikes = len(_vector(self.arrays['spike_times.npy'], 'spike_times.npy')) + self.metadata = _metadata(self.path) + self.validate() + counts = {} + for batch in self.iter_batches(): + ids, values = np.unique(batch['spike_clusters.npy'], return_counts=True) + for cluster_id, count in zip(ids.tolist(), values.tolist(), strict=True): + counts[cluster_id] = counts.get(cluster_id, 0) + count + for values in self.metadata.values(): + for cluster_id in values: + counts.setdefault(cluster_id, 0) + lineage_path = self.path / '_phy_curation_lineage.json' + lineage = {} + if lineage_path.exists(): + lineage = json.loads(lineage_path.read_text(encoding='utf-8')) + if ( + lineage.get('format') != 'phy_curation_lineage' + or lineage.get('format_version') != 1 + ): + raise ValueError('Unsupported curation lineage format or version.') + for unit in lineage.get('unit_ids', []): + if not isinstance(unit, int) or unit < 0: + raise ValueError('Lineage unit IDs must be nonnegative integers.') + counts.setdefault(unit, 0) + self.unit_ids = np.array(sorted(counts), dtype=np.int64) + minimum_next = int(self.unit_ids[-1]) + 1 if len(self.unit_ids) else 0 + self.next_cluster_id = lineage.get('next_cluster_id', minimum_next) + if not isinstance(self.next_cluster_id, int) or self.next_cluster_id < minimum_next: + raise ValueError('Lineage next_cluster_id collides with the source unit catalog.') + self.counts = np.array( + [counts[cluster_id] for cluster_id in self.unit_ids], dtype=np.int64 + ) + immutable = sorted(names - {'spike_clusters.npy'} - WINDOW_SIDECARS) + # Optional subset planning metadata describes a sampling policy, not a + # new immutable spike-coordinate identity. + acquisition = { + key: self.params[key] + for key in ( + 'acquisition_id', + 'n_channels_dat', + 'dtype', + 'offset', + 'depth_axis', + 'amplitude_units', + 'depth_units', + 'position_units', + 'waveform_units', + ) + if key in self.params + } + self.identity = { + 'format_version': 1, + 'acquisition': acquisition, + 'time_base': { + 'sample_rate': self.sample_rate, + 'num_samples': self.num_samples, + 'valid_intervals': self.valid_intervals.tolist(), + }, + 'arrays': {name: hash_file(self.path / name) for name in immutable}, + } + self.identity['sha256'] = hash_json(self.identity) + self.revision = assignment_revision(self.path, self.metadata) + if lineage: + if ( + lineage.get('coordinate_identity') != self.identity + or lineage.get('revision') != self.revision + ): + raise ValueError( + 'Curation lineage does not match immutable identity or assignments.' + ) + + def close(self): + """Release canonical array mappings after a batch command.""" + for array in self.arrays.values(): + close_array(array) + self.arrays.clear() + + def __enter__(self): + return self + + def __exit__(self, *args): + self.close() + + def iter_batches(self): + """Yield bounded row slices; vector fields use one-dimensional views.""" + for start in range(0, self.n_spikes, self.batch_size): + stop = min(start + self.batch_size, self.n_spikes) + batch = {'start': start, 'stop': stop} + for name in self.arrays.keys() & PER_SPIKE: + array = self.arrays[name] + if name in ('spike_times.npy', 'spike_clusters.npy', 'spike_templates.npy'): + array = _vector(array, name) + batch[name] = array[start:stop] + yield batch + + def validate(self): + """Check source row, clock, sparse channel, and feature alignment.""" + for name in self.arrays.keys() & PER_SPIKE: + if self.arrays[name].shape[0] != self.n_spikes: + raise ValueError(f'{name} is not aligned with source spikes.') + for name in ('spike_times.npy', 'spike_clusters.npy', 'spike_templates.npy'): + array = _vector(self.arrays[name], name) + if not np.issubdtype(array.dtype, np.integer): + raise ValueError(f'{name} must contain integer coordinates.') + previous = -1 + for batch in self.iter_batches(): + times = batch['spike_times.npy'] + if ( + np.any(times < previous) + or np.any(times[1:] < times[:-1]) + or np.any(times < 0) + or np.any(times >= self.num_samples) + ): + raise ValueError( + 'Spike sample times must be monotonic and within acquisition bounds.' + ) + if len(times): + previous = int(times[-1]) + interval_ids = np.searchsorted(self.valid_intervals[:, 0], times, side='right') - 1 + if np.any(interval_ids < 0) or np.any(times >= self.valid_intervals[interval_ids, 1]): + raise ValueError('Spike times fall outside valid acquisition intervals.') + for name in ('spike_clusters.npy', 'spike_templates.npy'): + if np.any(batch[name] < 0): + raise ValueError(f'{name} must contain nonnegative IDs.') + templates = self.arrays.get('templates.npy') + if templates is not None and np.any(batch['spike_templates.npy'] >= len(templates)): + raise ValueError('spike_templates.npy references an unavailable template.') + waveforms = self.arrays.keys() & WAVEFORMS + if waveforms and waveforms != WAVEFORMS: + raise ValueError('Stored waveforms require spikes, channels, and waveforms together.') + if waveforms: + ids = self.arrays['_phy_spikes_subset.spikes.npy'] + if ids.ndim != 1 or ids.dtype != np.dtype('int64'): + raise ValueError('Stored waveform row IDs must be a one-dimensional int64 array.') + channels = self.arrays['_phy_spikes_subset.channels.npy'] + values = self.arrays['_phy_spikes_subset.waveforms.npy'] + n_channels = len(self.arrays.get('channel_map.npy', [])) + if ( + values.ndim != 3 + or channels.shape != (len(ids), values.shape[2]) + or len(values) != len(ids) + or not np.issubdtype(channels.dtype, np.integer) + ): + raise ValueError('Stored waveform tensors and channels are not aligned.') + last = -1 + # Sparse-padding checks create temporary boolean arrays and gathers; + # cap their tensor bytes independently of the source row batch size. + row_bytes = max(1, values.dtype.itemsize * int(np.prod(values.shape[1:]))) + waveform_batch = min(self.batch_size, max(1, 8 * 1024 * 1024 // row_bytes)) + for start in range(0, len(ids), waveform_batch): + rows = ids[start : start + waveform_batch] + slots = channels[start : start + waveform_batch] + if ( + np.any(rows <= last) + or np.any(rows[1:] <= rows[:-1]) + or np.any(rows < 0) + or np.any(rows >= self.n_spikes) + ): + raise ValueError('Stored waveform row IDs must be sorted, unique source rows.') + if len(rows): + last = int(rows[-1]) + if np.any((slots < -1) | (slots >= n_channels)): + raise ValueError( + 'Sparse waveform channels must index model channels or use -1.' + ) + block = values[start : start + waveform_batch] + if np.any(np.moveaxis(block, 1, 2)[slots == -1] != 0): + raise ValueError('Sparse waveform padding channels must contain zeros.') + channel_map = self.arrays.get('channel_map.npy') + if channel_map is not None: + channels = _vector(channel_map, 'channel_map.npy') + if ( + not np.issubdtype(channels.dtype, np.integer) + or np.any(channels < 0) + or len(np.unique(channels)) != len(channels) + ): + raise ValueError('channel_map.npy must contain unique nonnegative raw column IDs.') + raw_channels = self.params.get('n_channels_dat') + if raw_channels is not None and ( + int(raw_channels) != raw_channels + or raw_channels <= 0 + or np.any(channels >= raw_channels) + ): + raise ValueError('channel_map.npy contains columns outside n_channels_dat.') + for name in ('channel_groups.npy', 'channel_shanks.npy', 'channel_map_si.npy'): + if name in self.arrays and len(_vector(self.arrays[name], name)) != len(channels): + raise ValueError(f'{name} must align with model channels.') + for name in ('whitening_mat.npy', 'whitening_mat_inv.npy'): + if name in self.arrays and self.arrays[name].shape != ( + len(channels), + len(channels), + ): + raise ValueError(f'{name} must contain a model-channel square matrix.') + templates = self.arrays.get('templates.npy') + if templates is not None: + sparse = self.arrays.get('templates_ind.npy') + if templates.ndim != 3: + raise ValueError('templates.npy must be a template/sample/channel tensor.') + if sparse is None and templates.shape[2] != len(channels): + raise ValueError('Dense templates must align with model channels.') + if sparse is not None: + if sparse.shape != (len(templates), templates.shape[2]): + raise ValueError('templates_ind.npy must align with sparse templates.') + if not np.issubdtype(sparse.dtype, np.integer): + raise ValueError('templates_ind.npy must contain integer channel indices.') + if np.any((sparse < -1) | (sparse >= len(channels))): + raise ValueError('templates_ind.npy contains invalid model channel IDs.') + positions = self.arrays.get('channel_positions.npy') + if positions is not None and (positions.ndim != 2 or len(positions) != len(channels)): + raise ValueError('channel_positions.npy must align with model channels.') + for feature, indices in ( + ('pc_features.npy', 'pc_feature_ind.npy'), + ('template_features.npy', 'template_feature_ind.npy'), + ): + if feature in self.arrays and indices not in self.arrays: + raise ValueError(f'{feature} requires {indices}.') + if feature in self.arrays: + values = self.arrays[feature] + lookup = self.arrays[indices] + if lookup.ndim != 2 or values.ndim < 2 or values.shape[-1] != lookup.shape[1]: + raise ValueError(f'{feature} and {indices} sparse axes do not agree.') + templates = self.arrays.get('templates.npy') + if templates is not None and len(lookup) != len(templates): + raise ValueError(f'{indices} must align with templates.') + if not np.issubdtype(lookup.dtype, np.integer): + raise ValueError(f'{indices} must contain integer indices.') + limit = ( + len(self.arrays.get('channel_map.npy', [])) + if feature == 'pc_features.npy' + else len(lookup) + ) + for start in range(0, len(lookup), self.batch_size): + rows = lookup[start : start + self.batch_size] + if np.any((rows < -1) | (rows >= limit)): + raise ValueError(f'{indices} contains invalid sparse indices.') + return self diff --git a/phy/apps/large_recording/tests/__init__.py b/phy/apps/large_recording/tests/__init__.py new file mode 100644 index 000000000..ba239ecd8 --- /dev/null +++ b/phy/apps/large_recording/tests/__init__.py @@ -0,0 +1 @@ +"""Long-recording workflow regression tests.""" diff --git a/phy/apps/large_recording/tests/test_source.py b/phy/apps/large_recording/tests/test_source.py new file mode 100644 index 000000000..0781ca843 --- /dev/null +++ b/phy/apps/large_recording/tests/test_source.py @@ -0,0 +1,240 @@ +"""Exact source clock, alignment, and identity regressions.""" + +import json + +import numpy as np +import pytest + +from phy.apps.large_recording.source import Source, hash_file + + +def make_sorting(path, columns=False): + path.mkdir() + samples = np.array([0, 1, 1, 2, 5, 6, 10, 11, 14, 18, 19, 19], dtype=np.int64) + clusters = np.array([0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 99, 99], dtype=np.int32) + templates = np.arange(len(samples), dtype=np.int32) % 3 + arrays = { + 'spike_times.npy': samples, + 'spike_clusters.npy': clusters, + 'spike_templates.npy': templates, + 'amplitudes.npy': np.arange(len(samples), dtype=np.float32), + 'spike_positions.npy': np.column_stack((np.zeros(len(samples)), samples * 2)), + 'spike_depths.npy': samples.astype(np.float64) * 2, + 'templates.npy': np.arange(3 * 8 * 3, dtype=np.float32).reshape(3, 8, 3), + 'channel_map.npy': np.array([2, 0, 1], dtype=np.int32), + 'channel_positions.npy': np.array([[0, 0], [0, 10], [0, 20]]), + 'pc_features.npy': np.arange(len(samples) * 4, dtype=np.float32).reshape(-1, 2, 2), + 'pc_feature_ind.npy': np.array([[0, 2], [2, 1], [1, 0]], dtype=np.int32), + } + for name, array in arrays.items(): + if columns and name in ('spike_times.npy', 'spike_clusters.npy', 'spike_templates.npy'): + array = array[:, None] + np.save(path / name, array) + ids = np.array([0, 2, 3, 8, 11], dtype=np.int64) + channels = np.array([[0, -1], [2, 1], [1, -1], [2, -1], [0, 1]], dtype=np.int32) + waveforms = np.zeros((len(ids), 8, 2), dtype=np.float32) + for row, spike in enumerate(ids): + for slot, channel in enumerate(channels[row]): + if channel != -1: + waveforms[row, :, slot] = spike + channel + np.arange(8) / 10 + for suffix, array in (('spikes', ids), ('channels', channels), ('waveforms', waveforms)): + np.save(path / f'_phy_spikes_subset.{suffix}.npy', array) + (path / 'params.py').write_text( + "sample_rate = 1.0\nnum_samples = 20\ndat_path = None\nn_channels_dat = 3\ndtype = 'int16'\n" + ) + (path / 'cluster_group.tsv').write_text( + 'cluster_id\tgroup\n0\tgood\n1\tmua\n2\tgood\n99\tnoise\n' + ) + return path / 'params.py' + + +@pytest.mark.parametrize('columns', [False, True]) +def test_source_batches_ties_counts_columns(tmp_path, columns): + source = Source(make_sorting(tmp_path / 'full', columns), batch_size=2) + assert source.n_spikes == 12 + assert source.unit_ids.tolist() == [0, 1, 2, 99] + assert source.counts.tolist() == [4, 3, 3, 2] + assert all(batch['spike_times.npy'].ndim == 1 for batch in source.iter_batches()) + assert all(isinstance(array, np.memmap) for array in source.arrays.values()) + assert source.metadata['group'][99] == 'noise' + + +def test_identity_assignment_and_feature_layers(tmp_path): + params = make_sorting(tmp_path / 'full') + source = Source(params) + clusters = np.load(params.parent / 'spike_clusters.npy') + clusters[clusters == 1] = 0 + np.save(params.parent / 'spike_clusters.npy', clusters) + merged = Source(params) + assert merged.identity == source.identity + assert merged.revision != source.revision + values = np.load(params.parent / 'amplitudes.npy') + values[0] = 99 + np.save(params.parent / 'amplitudes.npy', values) + altered = Source(params) + assert altered.identity != merged.identity + assert altered.revision == merged.revision + assert ( + hash_file(params.parent / 'amplitudes.npy') == altered.identity['arrays']['amplitudes.npy'] + ) + + +def test_exposure_gaps_and_missing_duration(tmp_path): + params = make_sorting(tmp_path / 'full') + source = Source(params, valid_intervals=[[0, 7], [10, 20]]) + assert source.valid_intervals.tolist() == [[0, 7], [10, 20]] + with pytest.raises(ValueError, match='outside valid'): + Source(params, valid_intervals=[[0, 5], [10, 20]]) + params.write_text(params.read_text().replace('num_samples = 20\n', '')) + with pytest.raises(ValueError, match='exposure is missing'): + Source(params) + assert Source(params, duration_seconds=20).num_samples == 20 + with pytest.raises(ValueError, match='integer sample count'): + Source(params, duration_seconds=20.5) + + +@pytest.mark.parametrize( + 'failure', ['order', 'alignment', 'unknown', 'segment', 'waveforms', 'ids'] +) +def test_reject_ambiguous_or_misaligned_sources(tmp_path, failure): + params = make_sorting(tmp_path / 'full') + path = params.parent + if failure == 'order': + np.save(path / 'spike_times.npy', np.arange(12)[::-1]) + elif failure == 'alignment': + np.save(path / 'pc_features.npy', np.zeros((11, 2, 2))) + elif failure == 'unknown': + np.save(path / 'mysterious.npy', np.ones(12)) + elif failure == 'segment': + params.write_text(params.read_text() + 'num_segments = 2\n') + elif failure == 'waveforms': + (path / '_phy_spikes_subset.channels.npy').unlink() + else: + np.save(path / '_phy_spikes_subset.spikes.npy', np.array([0, 2, 2, 8, 11], dtype=np.int64)) + with pytest.raises(ValueError): + Source(params, batch_size=2) + + +def test_metadata_json_preserves_typed_values(tmp_path): + params = make_sorting(tmp_path / 'full') + metadata = {'group': {'0': 'good'}, 'custom': {'99': None, '2': 4}} + (params.parent / '_phy_cluster_metadata.json').write_text(json.dumps(metadata)) + assert Source(params).metadata == {'group': {0: 'good'}, 'custom': {99: None, 2: 4}} + + +def test_replay_lineage_retains_zero_count_catalog_and_allocator(tmp_path): + params = make_sorting(tmp_path / 'full') + source = Source(params) + lineage = { + 'format': 'phy_curation_lineage', + 'format_version': 1, + 'coordinate_identity': source.identity, + 'revision': source.revision, + 'unit_ids': [0, 1, 2, 99, 103], + 'next_cluster_id': 105, + } + (params.parent / '_phy_curation_lineage.json').write_text(json.dumps(lineage)) + reopened = Source(params) + assert reopened.next_cluster_id == 105 + assert reopened.unit_ids[-1] == 103 + assert reopened.counts[-1] == 0 + assert reopened.identity == source.identity + lineage['next_cluster_id'] = 103 + (params.parent / '_phy_curation_lineage.json').write_text(json.dumps(lineage)) + with pytest.raises(ValueError, match='collides'): + Source(params) + + +def test_unknown_upstream_manifest_version_is_rejected(tmp_path): + params = make_sorting(tmp_path / 'full') + (params.parent / '_phy_spikes_subset.manifest.json').write_text( + json.dumps({'format': 'phy_spikes_subset', 'format_version': 2}) + ) + with pytest.raises(ValueError, match='Unsupported waveform manifest'): + Source(params) + + +def test_integer_clock_beyond_32_bits(tmp_path): + from phy.apps.tests.large_recording_fixtures import make_long_recording_fixture + + fixture = make_long_recording_fixture(tmp_path) + source = Source(fixture.full / 'params.py', batch_size=3) + assert source.num_samples == 1000 * 3600 * 30000 + assert source.arrays['spike_times.npy'][-1] > np.iinfo(np.int32).max + assert source.n_spikes == 32 + + +def test_source_heap_does_not_scale_with_spike_arrays(tmp_path): + import tracemalloc + + peaks = [] + for spikes in (1000, 250000): + path = tmp_path / str(spikes) + path.mkdir() + for name, dtype in ( + ('spike_times.npy', np.int64), + ('spike_clusters.npy', np.int32), + ('spike_templates.npy', np.int32), + ): + values = np.lib.format.open_memmap( + path / name, mode='w+', dtype=dtype, shape=(spikes,) + ) + for start in range(0, spikes, 1024): + stop = min(start + 1024, spikes) + values[start:stop] = np.arange(start, stop) if name == 'spike_times.npy' else 0 + values.flush() + del values + (path / 'params.py').write_text(f'sample_rate = 1\nnum_samples = {spikes}\n') + tracemalloc.start() + source = Source(path / 'params.py', batch_size=1024) + _, peak = tracemalloc.get_traced_memory() + tracemalloc.stop() + assert source.n_spikes == spikes + assert sum(source.counts) == spikes + peaks.append(peak) + # This checks allocated heap; file-backed OS pages are intentionally separate. + assert peaks[-1] < 4 * 1024 * 1024 + assert peaks[-1] - peaks[0] < 3 * 1024 * 1024 + + +def test_explicit_intervals_cannot_override_changed_producer_exposure(tmp_path): + params = make_sorting(tmp_path / 'full') + params.write_text(params.read_text() + 'valid_intervals = [[0, 7], [10, 20]]\n') + with pytest.raises(ValueError, match='disagree with acquisition metadata'): + Source(params, valid_intervals=[[0, 20]]) + with Source(params) as source: + arrays = list(source.arrays.values()) + assert source.valid_intervals.tolist() == [[0, 7], [10, 20]] + assert not source.arrays + assert all(array._mmap.closed for array in arrays) + + +def test_exporter_channel_sidecars_and_raw_map_validation(tmp_path): + params = make_sorting(tmp_path / 'full') + np.save( + params.parent / 'channel_map_si.npy', np.array(['hardware2', 'hardware0', 'hardware1']) + ) + np.save(params.parent / 'channel_groups.npy', np.array([1, 1, 0])) + with Source(params) as source: + assert 'channel_map_si.npy' in source.arrays + params.write_text(params.read_text().replace('n_channels_dat = 3', 'n_channels_dat = 2')) + with pytest.raises(ValueError, match='outside n_channels_dat'): + Source(params) + + +def test_exclusive_publish_preserves_racing_empty_destination(tmp_path): + from phy.apps.large_recording.source import publish_directory + + staged = tmp_path / 'stage' + staged.mkdir() + (staged / 'payload').write_text('complete') + destination = tmp_path / 'destination' + destination.mkdir() + with pytest.raises(FileExistsError): + publish_directory(staged, destination) + assert destination.is_dir() and not list(destination.iterdir()) + assert (staged / 'payload').read_text() == 'complete' + destination.rmdir() + publish_directory(staged, destination) + assert not staged.exists() + assert (destination / 'payload').read_text() == 'complete' From f6915444686858ea7507717e990b01151f18f9c5 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 10:37:42 +0200 Subject: [PATCH 04/53] Build bounded-memory full-duration counts and additive source trends --- phy/apps/large_recording/summaries.py | 122 ++++++++++++++++++ .../large_recording/tests/test_summaries.py | 67 ++++++++++ 2 files changed, 189 insertions(+) create mode 100644 phy/apps/large_recording/summaries.py create mode 100644 phy/apps/large_recording/tests/test_summaries.py diff --git a/phy/apps/large_recording/summaries.py b/phy/apps/large_recording/summaries.py new file mode 100644 index 000000000..2f498fab5 --- /dev/null +++ b/phy/apps/large_recording/summaries.py @@ -0,0 +1,122 @@ +"""Exact file-backed counts and additive source-measurement summaries.""" + +from contextlib import ExitStack +from pathlib import Path + +import numpy as np + +from .source import close_array + + +def scalar_attributes(source): + """Return available scalar measurements without inventing physical units.""" + attributes = {} + amplitude = source.arrays.get('amplitudes.npy') + if amplitude is not None and (amplitude.ndim == 1 or amplitude.shape[1:] == (1,)): + attributes['amplitude'] = amplitude.reshape(-1) + depth = source.arrays.get('spike_depths.npy') + if depth is not None and (depth.ndim == 1 or depth.shape[1:] == (1,)): + attributes['depth'] = depth.reshape(-1) + elif (positions := source.arrays.get('spike_positions.npy')) is not None: + axis = source.params.get('depth_axis') + if axis is not None: + if ( + not isinstance(axis, int) + or positions.ndim != 2 + or not 0 <= axis < positions.shape[1] + ): + raise ValueError('depth_axis must declare a valid spike_positions.npy coordinate.') + attributes['depth'] = positions[:, axis] + return attributes + + +def summary_size(source, bin_seconds=3600): + """Estimate exact array bytes before allocating the dense output grid.""" + step = float(bin_seconds) * source.sample_rate + if not np.isfinite(step) or step < 1 or not np.isclose(step, round(step), rtol=0, atol=1e-6): + raise ValueError('bin_seconds must specify a positive integer sample width.') + step = int(round(step)) + bins = (source.num_samples + step - 1) // step + size = len(source.unit_ids) * bins * 8 * (1 + 2 * len(scalar_attributes(source))) + size += (bins * 2 + 1) * 8 + return size, step, bins + + +def build_summaries(source, output_dir, bin_seconds=3600, max_bytes=536870912): + """Stream exact full counts, exposure, and finite-value sums/counts. + + Exposure is one shared vector. Summing parent-unit counts on merge must + divide by this vector once. Scalar means are sums/counts, never medians. + """ + size, step, bins = summary_size(source, bin_seconds) + if size + 1024 * (1 + 2 * len(scalar_attributes(source))) > max_bytes: + raise ValueError( + f'Summary budget exceeded: need at least {size} array bytes; ' + 'increase bin_seconds or max_bytes.' + ) + with ExitStack() as stack: + output_dir = Path(output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + result = { + 'counts_file': '_phy_summary_counts.npy', + 'edges_file': '_phy_summary_edges.npy', + 'exposure_file': '_phy_summary_exposure.npy', + } + shape = (len(source.unit_ids), bins) + counts = np.lib.format.open_memmap( + output_dir / result['counts_file'], mode='w+', dtype=np.int64, shape=shape + ) + stack.callback(close_array, counts) + counts[:] = 0 + attributes = scalar_attributes(source) + grids = {} + for field in attributes: + for kind, dtype in (('sum', np.float64), ('count', np.int64)): + key = f'{field}_{kind}_file' + result[key] = f'_phy_summary_{field}_{kind}.npy' + array = np.lib.format.open_memmap( + output_dir / result[key], mode='w+', dtype=dtype, shape=shape + ) + stack.callback(close_array, array) + array[:] = 0 + grids[field, kind] = array + edges = np.lib.format.open_memmap( + output_dir / result['edges_file'], mode='w+', dtype=np.int64, shape=(bins + 1,) + ) + stack.callback(close_array, edges) + # Bounded chunks also avoid a recording-duration-sized temporary arange. + for start in range(0, bins + 1, source.batch_size): + stop = min(start + source.batch_size, bins + 1) + edges[start:stop] = np.arange(start, stop, dtype=np.int64) * step + edges[-1] = source.num_samples + exposure = np.lib.format.open_memmap( + output_dir / result['exposure_file'], mode='w+', dtype=np.float64, shape=(bins,) + ) + stack.callback(close_array, exposure) + exposure[:] = 0 + for start, end in source.valid_intervals: + first, last = int(start // step), int((end - 1) // step) + for offset in range(first, last + 1, source.batch_size): + stop = min(offset + source.batch_size, last + 1) + exposure[offset:stop] += ( + np.minimum(edges[offset + 1 : stop + 1], end) + - np.maximum(edges[offset:stop], start) + ) / source.sample_rate + for batch in source.iter_batches(): + rows = np.searchsorted(source.unit_ids, batch['spike_clusters.npy']) + columns = batch['spike_times.npy'] // step + np.add.at(counts, (rows, columns), 1) + for field, values in attributes.items(): + values = values[batch['start'] : batch['stop']] + finite = np.isfinite(values) + np.add.at(grids[field, 'sum'], (rows[finite], columns[finite]), values[finite]) + np.add.at(grids[field, 'count'], (rows[finite], columns[finite]), 1) + for array in (counts, edges, exposure, *grids.values()): + array.flush() + result['estimators'] = { + 'counts': 'exact', + 'exposure': 'acquisition_seconds', + **dict.fromkeys(attributes, 'finite_sum_and_count'), + } + result['measurement_units'] = {field: f'source {field} units' for field in attributes} + return result diff --git a/phy/apps/large_recording/tests/test_summaries.py b/phy/apps/large_recording/tests/test_summaries.py new file mode 100644 index 000000000..5eb4d03e2 --- /dev/null +++ b/phy/apps/large_recording/tests/test_summaries.py @@ -0,0 +1,67 @@ +"""Full counts and acquisition exposure compared with an independent tiny oracle.""" + +import numpy as np +import pytest + +from phy.apps.large_recording.source import Source +from phy.apps.large_recording.summaries import build_summaries +from phy.apps.large_recording.tests.test_source import make_sorting + + +def test_exact_counts_exposure_and_additive_measurements(tmp_path): + params = make_sorting(tmp_path / 'full', columns=True) + amplitude = np.load(params.parent / 'amplitudes.npy') + amplitude[1] = np.nan + np.save(params.parent / 'amplitudes.npy', amplitude[:, None]) + source = Source(params, valid_intervals=[[0, 7], [10, 20]], batch_size=2) + files = build_summaries(source, tmp_path / 'summary', bin_seconds=5) + counts = np.load(tmp_path / 'summary' / files['counts_file']) + expected = np.zeros((4, 4), dtype=np.int64) + expected_sum = np.zeros((4, 4)) + expected_n = np.zeros((4, 4), dtype=np.int64) + units = np.load(params.parent / 'spike_clusters.npy').reshape(-1) + times = np.load(params.parent / 'spike_times.npy').reshape(-1) + for unit, time, value in zip(units, times, amplitude, strict=True): + row = list(source.unit_ids).index(unit) + column = int(time // 5) + expected[row, column] += 1 + if np.isfinite(value): + expected_sum[row, column] += value + expected_n[row, column] += 1 + np.testing.assert_array_equal(counts, expected) + np.testing.assert_array_equal(counts.sum(axis=1), source.counts) + np.testing.assert_array_equal( + np.load(tmp_path / 'summary' / files['edges_file']), [0, 5, 10, 15, 20] + ) + np.testing.assert_array_equal( + np.load(tmp_path / 'summary' / files['exposure_file']), [5, 2, 5, 5] + ) + np.testing.assert_array_equal( + np.load(tmp_path / 'summary' / files['amplitude_sum_file']), expected_sum + ) + np.testing.assert_array_equal( + np.load(tmp_path / 'summary' / files['amplitude_count_file']), expected_n + ) + assert files['measurement_units']['amplitude'] == 'source amplitude units' + assert 'depth_sum_file' in files + + +def test_summary_budget_checked_before_output_allocation(tmp_path): + source = Source(make_sorting(tmp_path / 'full')) + with pytest.raises(ValueError, match='Summary budget'): + build_summaries(source, tmp_path / 'summary', bin_seconds=1, max_bytes=50) + assert not (tmp_path / 'summary').exists() + + +def test_position_coordinates_require_declared_depth_axis(tmp_path): + from phy.apps.large_recording.summaries import scalar_attributes + + params = make_sorting(tmp_path / 'full') + (params.parent / 'spike_depths.npy').unlink() + with Source(params) as source: + assert 'depth' not in scalar_attributes(source) + params.write_text(params.read_text() + 'depth_axis = 1\n') + with Source(params) as source: + np.testing.assert_array_equal( + scalar_attributes(source)['depth'], source.arrays['spike_positions.npy'][:, 1] + ) From 489750220f03689529c2fcfc05486ce6ecb3165b Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 10:37:42 +0200 Subject: [PATCH 05/53] Add semantic curation journal and recoverable atomic checkpoint generations --- phy/apps/large_recording/curation.py | 638 ++++++++++++++++++ .../large_recording/tests/test_curation.py | 255 +++++++ 2 files changed, 893 insertions(+) create mode 100644 phy/apps/large_recording/curation.py create mode 100644 phy/apps/large_recording/tests/test_curation.py diff --git a/phy/apps/large_recording/curation.py b/phy/apps/large_recording/curation.py new file mode 100644 index 000000000..a37e01456 --- /dev/null +++ b/phy/apps/large_recording/curation.py @@ -0,0 +1,638 @@ +"""Semantic bounded curation and crash-consistent, immutable save generations.""" + +import copy +import hashlib +import json +import os +import shutil +import uuid +from pathlib import Path + +import numpy as np + +from .source import hash_json + +MANIFEST = '_phy_curation_manifest.json' +BASE_ASSIGNMENTS = '_phy_spike_clusters_base.npy' + + +def _json_bytes(value): + return ( + json.dumps(value, sort_keys=True, separators=(',', ':'), allow_nan=False) + '\n' + ).encode() + + +def _digest(value): + return hashlib.sha256(_json_bytes(value)).hexdigest() + + +def _hash_file(path): + digest = hashlib.sha256() + with Path(path).open('rb') as stream: + while chunk := stream.read(1024 * 1024): + digest.update(chunk) + return digest.hexdigest() + + +def _read_json(path): + with Path(path).open(encoding='utf8') as stream: + return json.load(stream) + + +def _write_json(path, value): + with Path(path).open('wb') as stream: + stream.write(_json_bytes(value)) + stream.flush() + os.fsync(stream.fileno()) + + +def _fsync_directory(path): + if os.name != 'nt': + descriptor = os.open(path, os.O_RDONLY) + try: + os.fsync(descriptor) + finally: + os.close(descriptor) + + +def _safe_file(root, name): + if not isinstance(name, str) or Path(name).name != name or name in ('', '.', '..'): + raise ValueError('Manifest/checkpoint filename must be a plain local filename.') + path = Path(root) / name + if path.is_symlink(): + raise ValueError('Manifest/checkpoint files must not be symbolic links.') + return path + + +def _integer(value, name): + if isinstance(value, bool) or not isinstance(value, (int, np.integer)) or value < 0: + raise ValueError(f'{name} must be a nonnegative integer.') + return int(value) + + +def _field_name(field): + if ( + not isinstance(field, str) + or not field + or field in ('.', '..') + or any(char in field for char in ('/', '\\', '\0', '\n', '\r', '\t')) + ): + raise ValueError('Metadata fields must be nonempty safe local field names.') + return field + + +def normalize_metadata(metadata): + """Return JSON-compatible metadata with integer cluster keys.""" + if not isinstance(metadata, dict): + raise ValueError('Cluster metadata must be a field-to-cluster mapping.') + result = {} + for field, values in metadata.items(): + _field_name(field) + if not isinstance(values, dict): + raise ValueError('Invalid cluster metadata field.') + result[field] = {} + for key, value in values.items(): + try: + cluster = int(key) + except (ValueError, TypeError) as error: + raise ValueError('Invalid metadata cluster ID.') from error + if str(cluster) != str(key) or cluster < 0: + raise ValueError('Invalid metadata cluster ID.') + _json_bytes(value) + result[field][cluster] = copy.deepcopy(value) + return result + + +def validate_predicate(predicate): + """Validate a threshold on a canonical full-source scalar attribute.""" + if not isinstance(predicate, dict) or set(predicate) != { + 'attribute', + 'operator', + 'threshold', + 'nonfinite', + }: + raise ValueError('Threshold requires attribute/operator/threshold/nonfinite.') + if predicate['attribute'] not in ('amplitudes.npy', 'spike_templates.npy'): + raise ValueError('Unsupported full-source threshold attribute.') + if predicate['operator'] not in ('<', '<=', '>', '>='): + raise ValueError('Unsupported threshold comparator.') + threshold = predicate['threshold'] + if isinstance(threshold, bool) or not isinstance(threshold, (int, float)): + raise ValueError('Threshold must be a finite number.') + if not np.isfinite(threshold) or predicate['nonfinite'] not in ('keep', 'reject'): + raise ValueError('Threshold needs a finite threshold and explicit nonfinite policy.') + return copy.deepcopy(predicate) + + +def evaluate_predicate(values, predicate): + values = np.asarray(values).reshape(-1) + finite = np.isfinite(values) + if predicate['nonfinite'] == 'reject' and not finite.all(): + raise ValueError('Nonfinite source values violate threshold policy.') + operators = {'<': np.less, '<=': np.less_equal, '>': np.greater, '>=': np.greater_equal} + return finite & operators[predicate['operator']](values, predicate['threshold']) + + +def interpret_events(unit_ids, metadata, events): + """Validate event intent and resolve the final catalog and metadata.""" + active = set(map(int, unit_ids)) + if not active or any(i < 0 for i in active): + raise ValueError('Full source unit catalog must contain nonnegative IDs.') + allocated = set(active) + metadata = normalize_metadata(metadata) + if not isinstance(events, list): + raise ValueError('Semantic journal must be an ordered event list.') + next_id = max(active) + 1 + for event in events: + if not isinstance(event, dict) or event.get('version') != 1: + raise ValueError('Unsupported semantic journal event version.') + operation = event.get('operation') + if operation == 'merge': + if set(event) != {'version', 'operation', 'parents', 'target', 'metadata'}: + raise ValueError('Malformed merge event.') + parents = [_integer(i, 'Parent ID') for i in event['parents']] + target = _integer(event['target'], 'Target ID') + if len(parents) < 2 or len(set(parents)) != len(parents): + raise ValueError('Merge requires at least two distinct complete units.') + if not set(parents) <= active or target in allocated or target < next_id: + raise ValueError('Merge references inactive units or colliding target ID.') + resolved = event['metadata'] + if not isinstance(resolved, dict) or any(not isinstance(f, str) for f in resolved): + raise ValueError('Merge metadata must contain resolved field values.') + _json_bytes(resolved) + for field in resolved: + _field_name(field) + active.difference_update(parents) + active.add(target) + allocated.add(target) + next_id = target + 1 + for values in metadata.values(): + for parent in parents: + values.pop(parent, None) + for field, value in resolved.items(): + metadata.setdefault(field, {})[target] = copy.deepcopy(value) + elif operation == 'label': + if set(event) != {'version', 'operation', 'field', 'ids', 'value'}: + raise ValueError('Malformed label event.') + ids = [_integer(i, 'Label ID') for i in event['ids']] + field = event['field'] + _field_name(field) + if not ids or len(set(ids)) != len(ids) or not set(ids) <= active: + raise ValueError('Label references inactive units or invalid metadata field.') + _json_bytes(event['value']) + values = metadata.setdefault(field, {}) + for cluster in ids: + values[cluster] = copy.deepcopy(event['value']) + elif operation == 'threshold_split': + if set(event) != { + 'version', + 'operation', + 'parent', + 'children', + 'predicate', + 'metadata', + }: + raise ValueError('Malformed threshold split event.') + parent = _integer(event['parent'], 'Parent ID') + children = [_integer(i, 'Child ID') for i in event['children']] + validate_predicate(event['predicate']) + if parent not in active or len(children) != 2 or len(set(children)) != 2: + raise ValueError('Threshold split requires an active parent and two children.') + if any(i in allocated or i < next_id for i in children): + raise ValueError('Threshold split child ID collision.') + resolved = normalize_metadata(event['metadata']) + if any(not set(v) <= set(children) for v in resolved.values()): + raise ValueError('Split metadata must refer only to explicit children.') + active.remove(parent) + active.update(children) + allocated.update(children) + next_id = max(children) + 1 + for values in metadata.values(): + values.pop(parent, None) + for field, values in resolved.items(): + metadata.setdefault(field, {}).update(values) + else: + raise ValueError(f'Unsupported semantic operation: {operation!r}.') + return active, metadata, next_id + + +def project_assignments(assignments, events, attributes=None): + """Interpret a validated journal against a bounded array or full-source batch.""" + output = np.asarray(assignments, dtype=np.int64).reshape(-1).copy() + attributes = attributes or {} + for event in events: + if event['operation'] == 'merge': + output[np.isin(output, event['parents'])] = event['target'] + elif event['operation'] == 'threshold_split': + predicate = event['predicate'] + attribute = predicate['attribute'] + if attribute not in attributes: + raise ValueError(f'Full-source threshold attribute is unavailable: {attribute}.') + mask = output == event['parent'] + values = np.asarray(attributes[attribute]).reshape(-1) + if len(values) != len(output): + raise ValueError('Threshold attribute is not a scalar per-spike array.') + selected = np.zeros(len(output), dtype=bool) + selected[mask] = evaluate_predicate(values[mask], predicate) + output[mask & ~selected] = event['children'][0] + output[mask & selected] = event['children'][1] + return output + + +class BoundedSession: + """Bounded semantic state; reopen establishes a new undo baseline. + + Snapshot/restore integrate with the controller's undo stack. Saving publishes + one pointer after every generation file has been flushed and verified. + """ + + def __init__(self, dataset_path): + self.path = Path(dataset_path) + if self.path.is_file(): + self.path = self.path.parent + self.manifest = _read_json(self.path / MANIFEST) + manifest = self.manifest + required = { + 'source', + 'sample_rate', + 'num_samples', + 'valid_intervals', + 'num_spikes', + 'bounded_num_spikes', + 'unit_ids', + 'counts', + 'next_cluster_id', + 'global_spike_ids_file', + 'windows_file', + } + if manifest.get('format') != 'phy_bounded_curation' or manifest.get('format_version') != 1: + raise ValueError('Unsupported bounded curation manifest version.') + if not required <= set(manifest): + raise ValueError( + 'Incomplete bounded curation manifest; regenerate with prepare-large.' + ) + source = manifest['source'] + if not isinstance(source, dict) or not {'identity', 'revision', 'path'} <= set(source): + raise ValueError('Bounded manifest needs source identity and assignment revision.') + if not isinstance(source['identity'], dict) or not isinstance(source['revision'], str): + raise ValueError('Invalid source identity or revision.') + identity = source['identity'] + identity_fields = {'format_version', 'acquisition', 'time_base', 'arrays', 'sha256'} + if ( + not identity_fields <= set(identity) + or identity.get('format_version') != 1 + or identity['sha256'] + != hash_json({k: v for k, v in identity.items() if k != 'sha256'}) + or len(source['revision']) != 64 + or any(c not in '0123456789abcdef' for c in source['revision']) + ): + raise ValueError('Invalid source coordinate identity or assignment revision digest.') + n = _integer(manifest['bounded_num_spikes'], 'Bounded spike count') + full_n = _integer(manifest['num_spikes'], 'Full spike count') + samples = _integer(manifest['num_samples'], 'Recording sample count') + if not n or n > full_n or not samples or not np.isfinite(manifest['sample_rate']): + raise ValueError('Invalid bounded counts or recording duration.') + if manifest['sample_rate'] <= 0: + raise ValueError('Sampling rate must be positive.') + if identity['time_base'] != { + 'sample_rate': manifest['sample_rate'], + 'num_samples': samples, + 'valid_intervals': manifest['valid_intervals'], + }: + raise ValueError('Bounded time base disagrees with immutable source identity.') + self.unit_ids = [_integer(i, 'Unit ID') for i in manifest['unit_ids']] + if not self.unit_ids or len(set(self.unit_ids)) != len(self.unit_ids): + raise ValueError('Full unit catalog must contain distinct unit IDs.') + counts = np.asarray(manifest['counts']) + if ( + counts.shape != (len(self.unit_ids),) + or counts.dtype.kind not in 'iu' + or np.any(counts < 0) + or sum(map(int, counts)) != full_n + ): + raise ValueError('Full unit counts do not match the source spike count/catalog.') + self.base_next_cluster_id = _integer(manifest['next_cluster_id'], 'Next cluster ID') + if self.base_next_cluster_id <= max(self.unit_ids): + raise ValueError('Cluster allocator collides with the complete source catalog.') + intervals = np.asarray(manifest['valid_intervals']) + if ( + intervals.ndim != 2 + or intervals.shape[1] != 2 + or not len(intervals) + or intervals.dtype.kind not in 'iu' + ): + raise ValueError('Valid acquisition intervals must be integer [start, end) pairs.') + if ( + np.any(intervals[:, 0] < 0) + or np.any(intervals[:, 1] > samples) + or np.any(intervals[:, 1] <= intervals[:, 0]) + or np.any(intervals[1:, 0] < intervals[:-1, 1]) + ): + raise ValueError('Invalid or overlapping acquisition intervals.') + self.global_ids = np.load( + _safe_file(self.path, manifest['global_spike_ids_file']), mmap_mode='r' + ) + if self.global_ids.dtype != np.int64 or self.global_ids.shape != (n,): + raise ValueError('Global spike IDs must be a one-dimensional int64 mapping.') + if ( + np.any(self.global_ids < 0) + or np.any(self.global_ids >= full_n) + or np.any(self.global_ids[1:] <= self.global_ids[:-1]) + ): + raise ValueError('Global spike IDs must be sorted, unique source row indices.') + windows = np.load(_safe_file(self.path, manifest['windows_file']), mmap_mode='r') + if ( + windows.ndim != 2 + or windows.shape[1] != 2 + or not len(windows) + or windows.dtype != np.int64 + ): + raise ValueError('Evidence windows must be int64 sample intervals.') + if ( + np.any(windows[:, 0] < 0) + or np.any(windows[:, 1] > samples) + or np.any(windows[:, 1] <= windows[:, 0]) + or np.any(windows[1:, 0] < windows[:-1, 1]) + ): + raise ValueError('Invalid or overlapping evidence windows.') + for start, stop in windows: + if not any(left <= start and stop <= right for left, right in intervals): + raise ValueError('Evidence windows cross unsupported acquisition gaps.') + for name, digest in manifest.get('bounded_files', {}).items(): + if _hash_file(_safe_file(self.path, name)) != digest: + raise ValueError(f'Bounded package integrity check failed: {name}.') + hashed_files = manifest.get('bounded_files', {}) + if not { + BASE_ASSIGNMENTS, + manifest['global_spike_ids_file'], + manifest['windows_file'], + 'spike_times.npy', + } <= set(hashed_files): + raise ValueError('Bounded manifest lacks required immutable array digests.') + self.base_assignments = np.load(self.path / BASE_ASSIGNMENTS, mmap_mode='r') + if ( + self.base_assignments.shape != (n,) + or self.base_assignments.dtype.kind not in 'iu' + or not set(np.unique(self.base_assignments)) <= set(self.unit_ids) + ): + raise ValueError('Immutable bounded assignments do not match the full catalog.') + self.base_metadata = normalize_metadata( + manifest.get('base_metadata', manifest.get('metadata', {})) + ) + if any(not set(values) <= set(self.unit_ids) for values in self.base_metadata.values()): + raise ValueError('Base metadata refers to units outside the full source catalog.') + bounded_times = np.load(self.path / 'spike_times.npy', mmap_mode='r').reshape(-1) + if ( + bounded_times.shape != (n,) + or bounded_times.dtype.kind not in 'iu' + or np.any(bounded_times[1:] < bounded_times[:-1]) + ): + raise ValueError('Bounded spike sample coordinates have invalid alignment/order.') + window_ids = np.searchsorted(windows[:, 0], bounded_times, side='right') - 1 + if np.any(window_ids < 0) or np.any(bounded_times >= windows[window_ids, 1]): + raise ValueError('Bounded spikes lie outside the recorded evidence windows.') + self.attributes = {} + for name in ('amplitudes.npy', 'spike_templates.npy'): + if (self.path / name).exists(): + self.attributes[name] = np.load(self.path / name, mmap_mode='r') + self.assignments = np.asarray(self.base_assignments, dtype=np.int64).copy() + self.metadata = copy.deepcopy(self.base_metadata) + self.events = [] + self.extra_documents = {} + self.next_cluster_id = self.base_next_cluster_id + self.checkpoint_path = None + pointer_path = self.path / '.phy-curation' / 'current.json' + if pointer_path.exists(): + self._load_checkpoint(pointer_path) + + def _validated_state(self, assignments, metadata, events, next_cluster_id): + _, projected_metadata, minimum = interpret_events( + self.unit_ids, self.base_metadata, events + ) + projected = project_assignments(self.base_assignments, events, self.attributes) + values = np.asarray(assignments) + if values.dtype.kind not in 'iu' or values.shape != projected.shape: + raise ValueError('Checkpoint assignments have invalid shape or dtype.') + if not np.array_equal(values, projected): + raise ValueError('Checkpoint assignments disagree with semantic journal projection.') + if normalize_metadata(metadata) != projected_metadata: + raise ValueError('Checkpoint metadata disagrees with semantic journal projection.') + minimum = max(minimum, self.base_next_cluster_id) + next_cluster_id = _integer(next_cluster_id, 'Next cluster ID') + if next_cluster_id < minimum: + raise ValueError('Checkpoint allocator collides with journal IDs.') + return projected, projected_metadata, next_cluster_id + + def _load_checkpoint(self, pointer_path): + pointer = _read_json(pointer_path) + generation = _safe_file(pointer_path.parent / 'generations', pointer['generation']) + descriptor = _read_json(generation / 'checkpoint.json') + if _digest(descriptor) != pointer['sha256']: + raise ValueError('Checkpoint commit pointer digest is invalid.') + if descriptor.get('version') != 1 or descriptor.get('manifest_sha256') != _digest( + self.manifest + ): + raise ValueError('Checkpoint belongs to a different bounded manifest.') + for name, digest in descriptor['files'].items(): + if _hash_file(_safe_file(generation, name)) != digest: + raise ValueError(f'Checkpoint corruption: {name}.') + if not {'spike_clusters.npy', 'journal.json', 'metadata.json'} <= set(descriptor['files']): + raise ValueError('Incomplete checkpoint file inventory.') + events = _read_json(generation / 'journal.json') + for event in events: + if event.get('operation') == 'threshold_split': + event['metadata'] = normalize_metadata(event['metadata']) + metadata = _read_json(generation / 'metadata.json') + assignments = np.load(generation / 'spike_clusters.npy', mmap_mode='r') + values, metadata, next_id = self._validated_state( + assignments, metadata, events, descriptor['next_cluster_id'] + ) + self.assignments, self.metadata = values, metadata + self.events = events + self.next_cluster_id = next_id + self.checkpoint_path = generation + self.extra_documents = { + name: _read_json(generation / name) for name in descriptor.get('extra_documents', []) + } + + def snapshot(self): + return { + 'assignments': self.assignments.copy(), + 'metadata': copy.deepcopy(self.metadata), + 'events': copy.deepcopy(self.events), + 'next_cluster_id': self.next_cluster_id, + } + + def journal_state(self): + """Return a compact history prefix without copying bounded spike arrays. + + Commands append event dictionaries and never modify earlier events. The + tuple shares those immutable event records between history entries. + """ + return {'events': tuple(self.events), 'next_cluster_id': self.next_cluster_id} + + def restore_journal(self, state): + """Restore an active history prefix while preserving allocator high-water.""" + events = list(state['events']) + _, metadata, minimum = interpret_events(self.unit_ids, self.base_metadata, events) + next_id = _integer(state['next_cluster_id'], 'Next cluster ID') + if next_id < max(minimum, self.base_next_cluster_id): + raise ValueError('History allocator collides with semantic journal IDs.') + assignments = project_assignments(self.base_assignments, events, self.attributes) + self.assignments, self.metadata, self.events = assignments, metadata, events + self.next_cluster_id = max(self.next_cluster_id, next_id) + + def close(self): + """Release file-backed bounded readers independently of the GUI model.""" + for array in (self.global_ids, self.base_assignments, *self.attributes.values()): + mapping = getattr(array, '_mmap', None) + if mapping is not None and not mapping.closed: + mapping.close() + + def restore(self, snapshot): + assignments, metadata, next_id = self._validated_state(**snapshot) + self.assignments, self.metadata = assignments, metadata + self.events = copy.deepcopy(snapshot['events']) + self.next_cluster_id = next_id + + def _append(self, event): + events = self.events + [event] + _, metadata, next_id = interpret_events(self.unit_ids, self.base_metadata, events) + assignments = project_assignments(self.base_assignments, events, self.attributes) + self.assignments, self.metadata, self.events = assignments, metadata, events + self.next_cluster_id = max(self.next_cluster_id, next_id) + return copy.deepcopy(event) + + def preflight_merge(self, parents, target, metadata=None): + event = { + 'version': 1, + 'operation': 'merge', + 'parents': [int(i) for i in parents], + 'target': _integer(target, 'Target ID'), + 'metadata': copy.deepcopy(metadata or {}), + } + if event['target'] < self.next_cluster_id: + raise ValueError('Merge target is below the complete catalog allocator.') + interpret_events(self.unit_ids, self.base_metadata, self.events + [event]) + return event + + def record_merge(self, parents, target, metadata=None): + return self._append(self.preflight_merge(parents, target, metadata)) + + def record_label(self, field, ids, value): + return self._append( + { + 'version': 1, + 'operation': 'label', + 'field': field, + 'ids': [int(i) for i in ids], + 'value': copy.deepcopy(value), + } + ) + + def record_threshold_split(self, parent, children, predicate, metadata=None): + """Pure replay service; the bounded GUI currently keeps splits disabled.""" + children = [int(i) for i in children] + if any(i < self.next_cluster_id for i in children): + raise ValueError('Threshold children collide with the complete catalog allocator.') + return self._append( + { + 'version': 1, + 'operation': 'threshold_split', + 'parent': int(parent), + 'children': children, + 'predicate': validate_predicate(predicate), + 'metadata': copy.deepcopy(metadata or {}), + } + ) + + def preflight_split(self, parent, selected_id, remainder_id, predicate, metadata=None): + children = [int(remainder_id), int(selected_id)] + if any(i < self.next_cluster_id for i in children): + raise ValueError('Threshold children collide with the complete catalog allocator.') + event = { + 'version': 1, + 'operation': 'threshold_split', + 'parent': int(parent), + 'children': children, + 'predicate': validate_predicate(predicate), + 'metadata': copy.deepcopy(metadata or {}), + } + interpret_events(self.unit_ids, self.base_metadata, self.events + [event]) + project_assignments(self.base_assignments, self.events + [event], self.attributes) + return event + + def record_split(self, parent, selected_id, remainder_id, predicate, metadata=None): + return self._append( + self.preflight_split(parent, selected_id, remainder_id, predicate, metadata) + ) + + def save( + self, + assignments=None, + metadata=None, + events=None, + next_cluster_id=None, + extra_documents=None, + ): + """Validate, flush a generation, then atomically replace its commit pointer.""" + assignments = self.assignments if assignments is None else assignments + metadata = self.metadata if metadata is None else metadata + events = self.events if events is None else events + next_cluster_id = self.next_cluster_id if next_cluster_id is None else next_cluster_id + values, metadata, next_id = self._validated_state( + assignments, metadata, events, next_cluster_id + ) + documents = copy.deepcopy( + self.extra_documents if extra_documents is None else extra_documents + ) + if not isinstance(documents, dict): + raise ValueError('Extra checkpoint documents must be a filename-to-JSON mapping.') + for name, value in documents.items(): + _safe_file(self.path, name) + if name in ('checkpoint.json', 'spike_clusters.npy', 'journal.json', 'metadata.json'): + raise ValueError('Extra document collides with a checkpoint state file.') + _json_bytes(value) + root = self.path / '.phy-curation' + generations = root / 'generations' + generations.mkdir(parents=True, exist_ok=True) + _fsync_directory(root) + _fsync_directory(self.path) + identifier = uuid.uuid4().hex + stage = generations / f'.{identifier}.tmp' + final = generations / identifier + stage.mkdir() + pointer_tmp = root / f'.current-{identifier}.tmp' + try: + np.save(stage / 'spike_clusters.npy', values) + with (stage / 'spike_clusters.npy').open('rb') as stream: + os.fsync(stream.fileno()) + _write_json(stage / 'journal.json', events) + _write_json(stage / 'metadata.json', metadata) + for name, value in documents.items(): + _write_json(stage / name, value) + descriptor = { + 'version': 1, + 'manifest_sha256': _digest(self.manifest), + 'next_cluster_id': next_id, + 'files': { + name: _hash_file(stage / name) + for name in ('spike_clusters.npy', 'journal.json', 'metadata.json', *documents) + }, + 'extra_documents': sorted(documents), + } + _write_json(stage / 'checkpoint.json', descriptor) + _fsync_directory(stage) + os.replace(stage, final) + _fsync_directory(generations) + _write_json(pointer_tmp, {'generation': identifier, 'sha256': _digest(descriptor)}) + os.replace(pointer_tmp, root / 'current.json') + _fsync_directory(root) + except BaseException: + shutil.rmtree(stage, ignore_errors=True) + pointer_tmp.unlink(missing_ok=True) + raise + self.assignments, self.metadata, self.events = values, metadata, copy.deepcopy(events) + self.next_cluster_id, self.checkpoint_path = next_id, final + self.extra_documents = documents + return final diff --git a/phy/apps/large_recording/tests/test_curation.py b/phy/apps/large_recording/tests/test_curation.py new file mode 100644 index 000000000..5de69f1f7 --- /dev/null +++ b/phy/apps/large_recording/tests/test_curation.py @@ -0,0 +1,255 @@ +"""Exact bounded journal projection and transactional persistence regressions.""" + +import json +import shutil + +import numpy as np +import pytest + +from phy.apps.large_recording.curation import BASE_ASSIGNMENTS, BoundedSession +from phy.apps.large_recording.source import Source, hash_file +from phy.apps.tests.large_recording_fixtures import make_long_recording_fixture + + +def make_session(tmp_path): + fixture = make_long_recording_fixture(tmp_path) + # The highest complete-source unit is intentionally absent from evidence. + clusters = np.load(fixture.full / 'spike_clusters.npy') + clusters[-1] = 99 + np.save(fixture.full / 'spike_clusters.npy', clusters) + (fixture.full / 'cluster_group.tsv').write_text('cluster_id\tgroup\n0\tgood\n1\tnoise\n') + source = Source(fixture.full / 'params.py', batch_size=5) + rows = np.array([0, 2, 5, 8, 13, 21, 25], dtype=np.int64) + for name in ('spike_times.npy', 'spike_clusters.npy', 'spike_templates.npy', 'amplitudes.npy'): + np.save(fixture.bounded / name, source.arrays[name][rows]) + np.save(fixture.bounded / BASE_ASSIGNMENTS, clusters[rows]) + np.save(fixture.bounded / '_phy_spike_global_ids.npy', rows) + np.save(fixture.bounded / 'windows.npy', np.array([[0, source.num_samples]], dtype=np.int64)) + manifest = { + 'format': 'phy_bounded_curation', + 'format_version': 1, + 'source': { + 'identity': source.identity, + 'revision': source.revision, + 'path': str(source.params_path), + }, + 'sample_rate': source.sample_rate, + 'num_samples': source.num_samples, + 'valid_intervals': source.valid_intervals.tolist(), + 'num_spikes': source.n_spikes, + 'bounded_num_spikes': len(rows), + 'unit_ids': source.unit_ids.tolist(), + 'counts': source.counts.tolist(), + 'next_cluster_id': 100, + 'global_spike_ids_file': '_phy_spike_global_ids.npy', + 'windows_file': 'windows.npy', + 'base_metadata': source.metadata, + 'bounded_files': { + name: hash_file(fixture.bounded / name) + for name in ( + BASE_ASSIGNMENTS, + '_phy_spike_global_ids.npy', + 'windows.npy', + 'spike_times.npy', + ) + }, + } + (fixture.bounded / '_phy_curation_manifest.json').write_text(json.dumps(manifest)) + return source, BoundedSession(fixture.bounded) + + +def test_merge_label_snapshot_branch_reopen(tmp_path): + source, session = make_session(tmp_path) + baseline = session.snapshot() + session.record_merge([0, 1], 100, {'group': 'good'}) + first = session.snapshot() + session.record_label('group', [100], 'mua') + second = session.snapshot() + session.restore(first) + assert session.metadata['group'][100] == 'good' + session.restore(second) + assert session.metadata['group'][100] == 'mua' + session.restore(baseline) + session.record_merge([1, 2], 100, {'group': 'noise'}) + session.record_label('custom', [99, 100], 'reviewed') + session.save(extra_documents={'curation_review.json': {'accepted': [100]}}) + reopened = BoundedSession(session.path) + assert reopened.next_cluster_id == 101 + assert reopened.events == session.events + assert reopened.metadata == session.metadata + assert np.array_equal(reopened.assignments, session.assignments) + assert reopened.extra_documents == {'curation_review.json': {'accepted': [100]}} + assert source.unit_ids.tolist() == [0, 1, 2, 99] + assert 99 not in session.base_assignments + + +@pytest.mark.parametrize('parents,target', [([0, 1], 99), ([0, 0], 100), ([0, 3], 100)]) +def test_merge_collision_and_invalid_parents_do_not_mutate(tmp_path, parents, target): + _, session = make_session(tmp_path) + before = session.snapshot() + with pytest.raises(ValueError): + session.record_merge(parents, target) + assert session.events == before['events'] + assert np.array_equal(session.assignments, before['assignments']) + + +def test_save_requires_exact_semantic_projection(tmp_path): + _, session = make_session(tmp_path) + session.record_merge([0, 1], 100, {'group': 'good'}) + with pytest.raises(ValueError, match='projection'): + session.save(assignments=session.base_assignments) + with pytest.raises(ValueError, match='metadata'): + session.save(metadata={}) + assert not (session.path / '.phy-curation' / 'current.json').exists() + + +@pytest.mark.parametrize('fail_at', ['journal.json', 'checkpoint.json', 'pointer']) +def test_interrupted_save_recovers_previous_generation(tmp_path, monkeypatch, fail_at): + from phy.apps.large_recording import curation + + _, session = make_session(tmp_path) + session.record_merge([0, 1], 100, {'group': 'good'}) + session.save() + previous = session.snapshot() + session.record_label('group', [100], 'mua') + original = curation._write_json + + def fail(path, value): + if path.name == fail_at or (fail_at == 'pointer' and path.name.startswith('.current-')): + raise OSError('injected interrupted write') + return original(path, value) + + monkeypatch.setattr(curation, '_write_json', fail) + with pytest.raises(OSError, match='interrupted'): + session.save() + reopened = BoundedSession(session.path) + assert reopened.events == previous['events'] + assert reopened.metadata == previous['metadata'] + assert session.metadata['group'][100] == 'mua' + + +def test_checkpoint_corruption_is_rejected(tmp_path): + _, session = make_session(tmp_path) + session.save() + (session.checkpoint_path / 'journal.json').write_text('[]\nchanged') + with pytest.raises(ValueError, match='corruption'): + BoundedSession(session.path) + + +def test_bound_base_corruption_is_rejected(tmp_path): + _, session = make_session(tmp_path) + shutil.copyfile(session.path / 'spike_times.npy', session.path / BASE_ASSIGNMENTS) + with pytest.raises(ValueError, match='integrity'): + BoundedSession(session.path) + + +def test_threshold_projection_is_serialized_and_nonfinite_policy_explicit(tmp_path): + _, session = make_session(tmp_path) + predicate = { + 'attribute': 'amplitudes.npy', + 'operator': '<', + 'threshold': 15.0, + 'nonfinite': 'keep', + } + session.record_split(2, 100, 101, predicate, {'group': {100: 'noise', 101: 'good'}}) + expected = session.base_assignments.astype(np.int64).copy() + mask = expected == 2 + selected = np.load(session.path / 'amplitudes.npy') < 15 + expected[mask & selected] = 100 + expected[mask & ~selected] = 101 + assert np.array_equal(session.assignments, expected) + session.save() + assert BoundedSession(session.path).events == session.events + with pytest.raises(ValueError, match='Unsupported'): + session.record_split(0, 102, 103, dict(predicate, attribute='waveform_peak')) + + +@pytest.mark.parametrize('boundary', ['generation', 'pointer']) +def test_atomic_publication_failure_preserves_previous_commit(tmp_path, monkeypatch, boundary): + from phy.apps.large_recording import curation + + _, session = make_session(tmp_path) + session.save() + session.record_merge([0, 1], 100, {'group': 'good'}) + original = curation.os.replace + + def fail(source, destination): + if (boundary == 'generation' and destination.parent.name == 'generations') or ( + boundary == 'pointer' and destination.name == 'current.json' + ): + raise OSError('injected atomic publication failure') + return original(source, destination) + + monkeypatch.setattr(curation.os, 'replace', fail) + with pytest.raises(OSError, match='publication'): + session.save() + assert BoundedSession(session.path).events == [] + assert len(session.events) == 1 + + +def test_nonfinite_predicate_keep_and_reject_are_explicit(): + from phy.apps.large_recording.curation import evaluate_predicate + + values = np.array([1.0, np.nan, np.inf, -np.inf, 3.0]) + predicate = { + 'attribute': 'amplitudes.npy', + 'operator': '<', + 'threshold': 2.0, + 'nonfinite': 'keep', + } + assert evaluate_predicate(values, predicate).tolist() == [True, False, False, False, False] + with pytest.raises(ValueError, match='Nonfinite'): + evaluate_predicate(values, dict(predicate, nonfinite='reject')) + + +def test_semantically_corrupt_checkpoint_rejected_even_with_valid_file_hashes(tmp_path): + from phy.apps.large_recording.curation import _digest + + _, session = make_session(tmp_path) + session.record_merge([0, 1], 100, {'group': 'good'}) + session.save() + generation = session.checkpoint_path + journal = json.loads((generation / 'journal.json').read_text()) + journal[0]['target'] = 99 + (generation / 'journal.json').write_text(json.dumps(journal)) + descriptor = json.loads((generation / 'checkpoint.json').read_text()) + descriptor['files']['journal.json'] = hash_file(generation / 'journal.json') + (generation / 'checkpoint.json').write_text(json.dumps(descriptor)) + pointer = {'generation': generation.name, 'sha256': _digest(descriptor)} + (session.path / '.phy-curation' / 'current.json').write_text(json.dumps(pointer)) + with pytest.raises(ValueError, match='colliding'): + BoundedSession(session.path) + + +def test_compact_history_preserves_allocator_and_reconstructs_assignments(tmp_path): + _, session = make_session(tmp_path) + before = session.journal_state() + session.record_merge([0, 1], 100, {'group': 'good'}) + after = session.journal_state() + merged = session.assignments.copy() + assert set(after) == {'events', 'next_cluster_id'} + assert after['events'][0] is session.events[0] + session.restore_journal(before) + assert session.events == [] + assert session.next_cluster_id == 101 + assert np.array_equal(session.assignments, session.base_assignments) + session.restore_journal(after) + assert np.array_equal(session.assignments, merged) + session.restore_journal(before) + session.record_merge([1, 2], 101, {'group': 'noise'}) + assert session.next_cluster_id == 102 + + +def test_session_close_releases_own_file_mappings(tmp_path): + _, session = make_session(tmp_path) + mappings = [ + array._mmap + for array in ( + session.global_ids, + session.base_assignments, + *session.attributes.values(), + ) + ] + session.close() + assert all(mapping.closed for mapping in mappings) + session.close() From 1237823b640d02f1d0aa26ae0dff9e33041bb037 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 10:37:42 +0200 Subject: [PATCH 06/53] Prepare budgeted shared-window evidence with exact waveform and feature mappings --- phy/apps/large_recording/prepare.py | 500 ++++++++++++++++++ .../large_recording/tests/test_prepare.py | 174 ++++++ 2 files changed, 674 insertions(+) create mode 100644 phy/apps/large_recording/prepare.py create mode 100644 phy/apps/large_recording/tests/test_prepare.py diff --git a/phy/apps/large_recording/prepare.py b/phy/apps/large_recording/prepare.py new file mode 100644 index 000000000..15920b1ef --- /dev/null +++ b/phy/apps/large_recording/prepare.py @@ -0,0 +1,500 @@ +"""Publish a self-contained bounded evidence package from a full sorting.""" + +import csv +import json +import os +import shutil +import tempfile +from pathlib import Path + +import numpy as np + +from .source import ( + PER_SPIKE, + STATIC, + WAVEFORMS, + Source, + close_array, + hash_file, + hash_json, + publish_directory, +) +from .summaries import build_summaries, scalar_attributes, summary_size + + +def _row_bounds(times, windows): + return [ + ( + int(np.searchsorted(times, start, side='left')), + int(np.searchsorted(times, end, side='left')), + ) + for start, end in windows + ] + + +def _union(windows): + result = [] + for start, end in sorted(windows): + if result and start <= result[-1][1]: + result[-1][1] = max(result[-1][1], int(end)) + else: + result.append([int(start), int(end)]) + return result + + +def _write_metadata(path, metadata): + for field, values in metadata.items(): + if ( + not isinstance(field, str) + or not field + or '/' in field + or '\\' in field + or field in ('.', '..') + ): + raise ValueError('Metadata field names must be safe filenames.') + with (path / f'cluster_{field}.tsv').open('w', encoding='utf-8', newline='') as stream: + writer = csv.writer(stream, delimiter='\t') + writer.writerow(['cluster_id', field]) + writer.writerows(sorted(values.items())) + + +def _selected_waveform_count(source, windows): + ids = source.arrays.get('_phy_spikes_subset.spikes.npy') + if ids is None: + return 0 + return sum( + int(np.searchsorted(ids, stop) - np.searchsorted(ids, start)) + for start, stop in _row_bounds(source.arrays['spike_times.npy'].reshape(-1), windows) + ) + + +def prepare_large( + params_path, + output_dir, + duration_seconds=None, + valid_intervals=None, + max_spikes=2000000, + max_bytes=536870912, + window_seconds=30, + stratum_seconds=3600, + seed=0, + batch_size=100000, + bin_seconds=3600, +): + """Choose complete shared windows, write bounded arrays, and publish atomically. + + Survey windows use a seeded offset within each acquisition stratum. A second + pass tries one first-spike rescue window for every unit without evidence. + Candidate windows that exceed either budget are explicitly omitted; spikes + within accepted windows are never independently thinned. + """ + with Source(params_path, duration_seconds, valid_intervals, batch_size) as source: + return _prepare_source( + source, + output_dir, + max_spikes, + max_bytes, + window_seconds, + stratum_seconds, + seed, + batch_size, + bin_seconds, + ) + + +def _prepare_source( + source, + output_dir, + max_spikes, + max_bytes, + window_seconds, + stratum_seconds, + seed, + batch_size, + bin_seconds, +): + output_dir = Path(output_dir).resolve() + missing_static = { + 'templates.npy', + 'channel_map.npy', + 'channel_positions.npy', + } - source.arrays.keys() + if missing_static: + raise ValueError(f'Bounded GUI preparation requires: {", ".join(sorted(missing_static))}.') + if output_dir.exists(): + raise ValueError(f'Output already exists: {output_dir}.') + if output_dir == source.path or source.path in output_dir.parents: + raise ValueError('Bounded output must be outside the source dataset directory.') + if int(max_spikes) != max_spikes or max_spikes <= 0 or max_bytes <= 0: + raise ValueError('max_spikes and max_bytes must be positive budgets.') + widths = [] + for label, seconds in ( + ('window_seconds', window_seconds), + ('stratum_seconds', stratum_seconds), + ): + width = float(seconds) * source.sample_rate + if ( + not np.isfinite(width) + or width < 1 + or not np.isclose(width, round(width), rtol=0, atol=1e-6) + ): + raise ValueError(f'{label} must specify a positive integer sample width.') + widths.append(int(round(width))) + width, stratum = widths + times = source.arrays['spike_times.npy'].reshape(-1) + assignments = source.arrays['spike_clusters.npy'].reshape(-1) + summary_bytes = summary_size(source, bin_seconds)[0] + producer_documents = [ + source.path / name + for name in ('curation.json', 'curation_review.json') + if (source.path / name).is_file() + ] + fixed_bytes = ( + sum(path.stat().st_size for path in producer_documents) + + summary_bytes + + sum((source.path / name).stat().st_size for name in source.arrays.keys() & STATIC) + ) + # Reserve headers, manifest, params, metadata, and window records explicitly. + metadata_bytes = sum( + len(str(value).encode('utf-8')) + 64 + for values in source.metadata.values() + for value in values.values() + ) + overhead = 32768 + metadata_bytes + 1024 * len(source.arrays) + fixed_bytes += overhead + row_bytes = 16 # int64 global row mapping and baseline assignment + for name in source.arrays.keys() & PER_SPIKE: + array = source.arrays[name] + row_bytes += array.dtype.itemsize * int(np.prod(array.shape[1:], dtype=np.int64)) + waveform_bytes = 0 + if source.arrays.keys() >= WAVEFORMS: + for name in WAVEFORMS: + array = source.arrays[name] + waveform_bytes += array.dtype.itemsize * int(np.prod(array.shape[1:], dtype=np.int64)) + if fixed_bytes > max_bytes: + raise ValueError( + f'Output budget exceeded before selecting evidence: estimated ' + f'{fixed_bytes} bytes; increase max_bytes or bin_seconds.' + ) + windows, plan, omitted = [], [], [] + rng = np.random.default_rng(seed) + + def accept(start, end, kind, segment, stratum_id): + candidate = _union([*windows, [start, end]]) + n = sum(stop - first for first, stop in _row_bounds(times, candidate)) + n_waveforms = _selected_waveform_count(source, candidate) + size = fixed_bytes + n * row_bytes + n_waveforms * waveform_bytes + len(candidate) * 256 + record = { + 'start': int(start), + 'end': int(end), + 'kind': kind, + 'segment': 0, + 'block': int(segment), + 'stratum': int(stratum_id), + } + if n > max_spikes or size > max_bytes: + omitted.append( + {**record, 'reason': 'spike_budget' if n > max_spikes else 'byte_budget'} + ) + return False + windows[:] = candidate + plan.append(record) + return True + + # Candidate enumeration is scalar and bounded by output-window metadata, + # rather than constructing recording-length arrays. + for segment, (first, last) in enumerate(source.valid_intervals): + for start in range(int(first), int(last), stratum): + end = min(start + stratum, int(last)) + length = min(width, end - start) + offset = int(rng.integers(0, end - start - length + 1)) + accept(start + offset, start + offset + length, 'survey', segment, start // stratum) + if (len(plan) + len(omitted)) * 256 + fixed_bytes > max_bytes: + raise ValueError( + 'Window plan metadata exceeds max_bytes; increase stratum_seconds.' + ) + evidence = set() + for first, stop in _row_bounds(times, windows): + for start in range(first, stop, batch_size): + evidence.update(np.unique(assignments[start : min(start + batch_size, stop)]).tolist()) + missing = set(source.unit_ids.tolist()) - evidence + for batch in source.iter_batches(): + if not missing: + break + units, positions = np.unique(batch['spike_clusters.npy'], return_index=True) + for unit, position in zip(units.tolist(), positions.tolist(), strict=True): + if unit not in missing: + continue + sample = int(batch['spike_times.npy'][position]) + segment = int(np.searchsorted(source.valid_intervals[:, 0], sample, side='right') - 1) + first, last = source.valid_intervals[segment] + start = max(int(first), min(sample - width // 2, int(last) - width)) + end = min(start + width, int(last)) + accept(start, end, 'rescue', segment, -1) + # One deterministic rescue attempt per unit, including rejected attempts. + missing.remove(unit) + row_bounds = _row_bounds(times, windows) + n_bounded = sum(stop - first for first, stop in row_bounds) + if not n_bounded: + raise ValueError( + 'No bounded evidence fits the budgets; increase max_spikes/max_bytes ' + 'or shorten window_seconds (tied spikes remain together).' + ) + output_dir.parent.mkdir(parents=True, exist_ok=True) + temporary = Path( + tempfile.mkdtemp(prefix=f'.{output_dir.name}.prepare-', dir=output_dir.parent) + ) + global_ids, base, destinations = None, None, {} + try: + global_ids = np.lib.format.open_memmap( + temporary / '_phy_spike_global_ids.npy', mode='w+', dtype=np.int64, shape=(n_bounded,) + ) + for name in source.arrays.keys() & PER_SPIKE: + array = source.arrays[name] + destinations[name] = np.lib.format.open_memmap( + temporary / name, mode='w+', dtype=array.dtype, shape=(n_bounded, *array.shape[1:]) + ) + base = np.lib.format.open_memmap( + temporary / '_phy_spike_clusters_base.npy', + mode='w+', + dtype=np.int64, + shape=(n_bounded,), + ) + cursor = 0 + bounded_counts = {int(unit): 0 for unit in source.unit_ids} + for first, stop in row_bounds: + for start in range(first, stop, batch_size): + end = min(start + batch_size, stop) + length = end - start + global_ids[cursor : cursor + length] = np.arange(start, end, dtype=np.int64) + base[cursor : cursor + length] = assignments[start:end] + for name, target in destinations.items(): + target[cursor : cursor + length] = source.arrays[name][start:end] + ids, counts = np.unique(assignments[start:end], return_counts=True) + for unit, count in zip(ids.tolist(), counts.tolist(), strict=True): + bounded_counts[unit] += count + cursor += length + for array in (global_ids, base, *destinations.values()): + array.flush() + for name in source.arrays.keys() & STATIC: + shutil.copyfile(source.path / name, temporary / name) + if source.arrays.keys() >= WAVEFORMS: + _copy_waveforms(source, temporary, global_ids, row_bounds) + np.save(temporary / '_phy_curation_windows.npy', np.asarray(windows, dtype=np.int64)) + _write_metadata(temporary, source.metadata) + (temporary / '_phy_cluster_metadata.json').write_text( + json.dumps(source.metadata, sort_keys=True) + '\n', encoding='utf-8' + ) + # Standard loader stays self-contained; no original raw path is referenced. + params = { + key: source.params[key] + for key in ( + 'sample_rate', + 'n_channels_dat', + 'dtype', + 'offset', + 'hp_filtered', + 'acquisition_id', + 'depth_axis', + 'amplitude_units', + 'depth_units', + 'position_units', + 'waveform_units', + ) + if key in source.params + } + params.update( + dat_path=None, + sample_rate=source.sample_rate, + num_samples=source.num_samples, + valid_intervals=source.valid_intervals.tolist(), + ) + params.setdefault('dtype', 'int16') + params.setdefault('n_channels_dat', len(source.arrays.get('channel_map.npy', []))) + (temporary / 'params.py').write_text( + ''.join(f'{key} = {value!r}\n' for key, value in params.items()), encoding='utf-8' + ) + summaries = build_summaries(source, temporary, bin_seconds, max_bytes=max_bytes) + final_windows = [] + for start, end in windows: + contributors = [ + record for record in plan if record['start'] < end and record['end'] > start + ] + kinds = sorted({record['kind'] for record in contributors}) + final_windows.append( + { + 'start': start, + 'end': end, + 'segment': 0, + 'block': contributors[0]['block'], + 'kind': kinds[0] if len(kinds) == 1 else 'mixed', + 'kinds': kinds, + 'strata': sorted({record['stratum'] for record in contributors}), + 'exposure_seconds': (end - start) / source.sample_rate, + } + ) + manifest = { + 'format': 'phy_bounded_curation', + 'format_version': 1, + 'source': { + 'identity': source.identity, + 'revision': source.revision, + 'path': str(source.path), + }, + 'sample_rate': source.sample_rate, + 'num_samples': source.num_samples, + 'duration_seconds': source.num_samples / source.sample_rate, + 'valid_intervals': source.valid_intervals.tolist(), + 'num_spikes': source.n_spikes, + 'bounded_num_spikes': n_bounded, + 'unit_ids': source.unit_ids.tolist(), + 'counts': source.counts.tolist(), + 'bounded_counts': [bounded_counts[int(unit)] for unit in source.unit_ids], + 'next_cluster_id': source.next_cluster_id, + 'global_spike_ids_file': '_phy_spike_global_ids.npy', + 'base_assignments_file': '_phy_spike_clusters_base.npy', + 'windows_file': '_phy_curation_windows.npy', + 'windows': final_windows, + 'accepted_window_candidates': plan, + 'omitted_windows': omitted, + 'metadata': source.metadata, + 'base_metadata': source.metadata, + 'summaries': summaries, + **{key: value for key, value in summaries.items() if key.endswith('_file')}, + 'selection': { + 'algorithm': 'shared_windows_v1', + 'seed': int(seed), + 'window_seconds': window_seconds, + 'stratum_seconds': stratum_seconds, + }, + 'budgets': { + 'max_spikes': int(max_spikes), + 'max_bytes': int(max_bytes), + 'batch_size': int(batch_size), + 'summary_bytes': int(summary_bytes), + 'estimated_bytes': int( + fixed_bytes + + n_bounded * row_bytes + + _selected_waveform_count(source, windows) * waveform_bytes + + len(windows) * 256 + ), + }, + 'capabilities': { + 'merge': True, + 'label': True, + 'split': False, + 'full_attributes': sorted(scalar_attributes(source)), + 'predicate_split_attributes': ( + ['amplitudes.npy'] if 'amplitude' in scalar_attributes(source) else [] + ), + 'stored_waveforms': source.arrays.keys() >= WAVEFORMS, + 'raw_traces': False, + 'normalized_correlograms': False, + }, + 'source_array_inventory': { + name: { + 'role': 'per_spike' + if name in PER_SPIKE + else 'stored_waveform' + if name in WAVEFORMS + else 'static' + if name in STATIC + else 'excluded_window_sidecar', + 'shape': list(array.shape), + 'dtype': str(array.dtype), + 'bytes': int(array.nbytes), + } + for name, array in source.arrays.items() + }, + 'excluded_files': sorted( + p.name + for p in source.path.iterdir() + if p.name not in (PER_SPIKE | STATIC | WAVEFORMS) + and p.name + not in ( + 'params.py', + '_phy_cluster_metadata.json', + 'curation.json', + 'curation_review.json', + ) + and (not p.name.startswith('cluster_') or p.stem == 'cluster_info') + ), + } + for document in producer_documents: + shutil.copyfile(document, temporary / document.name) + bound_paths = [ + *temporary.glob('*.npy'), + temporary / 'params.py', + temporary / '_phy_cluster_metadata.json', + ] + manifest['bounded_files'] = {p.name: hash_file(p) for p in sorted(bound_paths)} + manifest['preparation_identity'] = hash_json(manifest) + (temporary / '_phy_curation_manifest.json').write_text( + json.dumps(manifest, indent=2, sort_keys=True) + '\n', encoding='utf-8' + ) + actual_bytes = sum(p.stat().st_size for p in temporary.iterdir()) + if actual_bytes > max_bytes: + raise ValueError(f'Final output exceeds max_bytes: {actual_bytes} bytes.') + for array in (global_ids, base, *destinations.values()): + close_array(array) + for path in temporary.iterdir(): + if path.is_file(): + with path.open('rb') as stream: + os.fsync(stream.fileno()) + _fsync_directory(temporary) + if output_dir.exists(): + raise ValueError(f'Output already exists: {output_dir}.') + from .curation import BoundedSession + + checked = BoundedSession(temporary) + checked.close() + publish_directory(temporary, output_dir) + _fsync_directory(output_dir.parent) + except BaseException: + for array in (global_ids, base, *destinations.values()): + close_array(array) + shutil.rmtree(temporary, ignore_errors=True) + raise + return output_dir + + +def _fsync_directory(path): + if os.name != 'nt': + descriptor = os.open(path, os.O_RDONLY) + try: + os.fsync(descriptor) + finally: + os.close(descriptor) + + +def _copy_waveforms(source, output, global_ids, row_bounds): + """Intersect sparse row IDs with selected spans in bounded working memory.""" + upstream_ids = source.arrays['_phy_spikes_subset.spikes.npy'] + spans = [ + (int(np.searchsorted(upstream_ids, first)), int(np.searchsorted(upstream_ids, stop))) + for first, stop in row_bounds + ] + n = sum(stop - first for first, stop in spans) + targets = {} + try: + for name in WAVEFORMS: + original = source.arrays[name] + targets[name] = np.lib.format.open_memmap( + output / name, mode='w+', dtype=original.dtype, shape=(n, *original.shape[1:]) + ) + cursor = 0 + for first, stop in spans: + for start in range(first, stop, source.batch_size): + end = min(start + source.batch_size, stop) + length = end - start + targets['_phy_spikes_subset.spikes.npy'][cursor : cursor + length] = ( + np.searchsorted(global_ids, upstream_ids[start:end]) + ) + for name in WAVEFORMS - {'_phy_spikes_subset.spikes.npy'}: + targets[name][cursor : cursor + length] = source.arrays[name][start:end] + cursor += length + for array in targets.values(): + array.flush() + finally: + for array in targets.values(): + close_array(array) diff --git a/phy/apps/large_recording/tests/test_prepare.py b/phy/apps/large_recording/tests/test_prepare.py new file mode 100644 index 000000000..7b5b0bcb9 --- /dev/null +++ b/phy/apps/large_recording/tests/test_prepare.py @@ -0,0 +1,174 @@ +"""Production bounded preparation: budgets, rows, waveforms, and publication.""" + +import json + +import numpy as np +import pytest +from phylib.io.model import load_model + +from phy.apps.large_recording.prepare import prepare_large +from phy.apps.large_recording.source import PER_SPIKE, hash_file +from phy.apps.large_recording.tests.test_source import make_sorting + + +def test_prepare_exact_arrays_waveforms_and_source_unchanged(tmp_path): + params = make_sorting(tmp_path / 'full', columns=True) + before = {p.name: hash_file(p) for p in params.parent.iterdir()} + output = prepare_large( + params, + tmp_path / 'bounded', + max_spikes=8, + window_seconds=3, + stratum_seconds=20, + seed=0, + bin_seconds=5, + batch_size=2, + ) + manifest = json.loads((output / '_phy_curation_manifest.json').read_text()) + windows = np.load(output / manifest['windows_file']) + samples = np.load(params.parent / 'spike_times.npy').reshape(-1) + expected_ids = np.array( + [ + index + for index, sample in enumerate(samples) + if any(start <= sample < end for start, end in windows) + ], + dtype=np.int64, + ) + global_ids = np.load(output / manifest['global_spike_ids_file']) + np.testing.assert_array_equal(global_ids, expected_ids) + assert len(global_ids) <= 8 + for name in PER_SPIKE: + if (params.parent / name).exists(): + np.testing.assert_array_equal( + np.load(output / name), np.load(params.parent / name)[expected_ids] + ) + source_waveform_ids = np.load(params.parent / '_phy_spikes_subset.spikes.npy') + expected_waveform_rows = [ + row for row, spike in enumerate(source_waveform_ids) if spike in expected_ids + ] + np.testing.assert_array_equal( + global_ids[np.load(output / '_phy_spikes_subset.spikes.npy')], + source_waveform_ids[expected_waveform_rows], + ) + for suffix in ('channels', 'waveforms'): + np.testing.assert_array_equal( + np.load(output / f'_phy_spikes_subset.{suffix}.npy'), + np.load(params.parent / f'_phy_spikes_subset.{suffix}.npy')[expected_waveform_rows], + ) + assert before == {p.name: hash_file(p) for p in params.parent.iterdir()} + assert 'dat_path = None' in (output / 'params.py').read_text() + assert manifest['next_cluster_id'] == 100 + assert sum(manifest['counts']) == len(samples) + assert sum(manifest['bounded_counts']) == len(global_ids) + model = load_model(output / 'params.py') + try: + ids = np.load(output / '_phy_spikes_subset.spikes.npy') + channels = np.load(output / '_phy_spikes_subset.channels.npy') + sparse = np.load(output / '_phy_spikes_subset.waveforms.npy') + expected = np.zeros((len(ids), 8, 3), dtype=np.float32) + for row, slots in enumerate(channels): + for slot, channel in enumerate(slots): + if channel >= 0: + expected[row, :, channel] = sparse[row, :, slot] + np.testing.assert_array_equal(model.get_waveforms(ids, channel_ids=[0, 1, 2]), expected) + finally: + model.close() + + +def test_deterministic_budgets_and_zero_evidence_catalog(tmp_path): + params = make_sorting(tmp_path / 'full') + outputs = [ + prepare_large( + params, + tmp_path / name, + max_spikes=5, + window_seconds=3, + stratum_seconds=20, + seed=0, + bin_seconds=5, + batch_size=2, + ) + for name in ('one', 'two') + ] + manifests = [ + json.loads((path / '_phy_curation_manifest.json').read_text()) for path in outputs + ] + assert manifests[0] == manifests[1] + assert manifests[0]['unit_ids'][-1] == 99 + assert manifests[0]['bounded_counts'][-1] == 0 + assert manifests[0]['omitted_windows'] + for path in outputs: + ids = np.load(path / '_phy_spike_global_ids.npy') + times = np.load(path / 'spike_times.npy') + assert len(ids) <= 5 + # All three tied samples at 1 retain their separate source identities. + assert np.count_nonzero(times == 1) == 2 + + +def test_rejected_budget_or_interrupted_publication_leaves_no_output(tmp_path, monkeypatch): + params = make_sorting(tmp_path / 'full') + with pytest.raises(ValueError, match='No bounded evidence'): + prepare_large( + params, tmp_path / 'empty', max_spikes=1, window_seconds=3, stratum_seconds=20, seed=0 + ) + with pytest.raises(ValueError, match='Output budget'): + prepare_large(params, tmp_path / 'too-big', max_bytes=10) + import phy.apps.large_recording.prepare as module + + def fail(*args, **kwargs): + raise OSError('simulated interruption') + + monkeypatch.setattr(module, 'build_summaries', fail) + with pytest.raises(OSError, match='interruption'): + prepare_large(params, tmp_path / 'interrupted', window_seconds=20, stratum_seconds=20) + assert not (tmp_path / 'interrupted').exists() + assert not list(tmp_path.glob('.interrupted.prepare-*')) + + +def test_prepare_missing_waveforms_is_explicit(tmp_path): + params = make_sorting(tmp_path / 'full') + for path in params.parent.glob('_phy_spikes_subset.*.npy'): + path.unlink() + output = prepare_large(params, tmp_path / 'bounded', window_seconds=20, stratum_seconds=20) + manifest = json.loads((output / '_phy_curation_manifest.json').read_text()) + assert not manifest['capabilities']['stored_waveforms'] + assert not (output / '_phy_spikes_subset.waveforms.npy').exists() + + +def test_final_windows_records_match_retained_samples_and_gaps(tmp_path): + params = make_sorting(tmp_path / 'full') + output = prepare_large( + params, + tmp_path / 'bounded', + valid_intervals=[[0, 7], [10, 20]], + window_seconds=5, + stratum_seconds=20, + bin_seconds=5, + ) + manifest = json.loads((output / '_phy_curation_manifest.json').read_text()) + intervals = np.load(output / manifest['windows_file']) + assert [[row['start'], row['end']] for row in manifest['windows']] == intervals.tolist() + for row in manifest['windows']: + start, end = row['start'], row['end'] + assert any(first <= start and end <= last for first, last in [[0, 7], [10, 20]]) + assert row['exposure_seconds'] == end - start + assert manifest['capabilities']['predicate_split_attributes'] == ['amplitudes.npy'] + + +def test_prepare_protects_loader_and_preserves_producer_documents(tmp_path): + params = make_sorting(tmp_path / 'full') + for name, value in ( + ('curation.json', {'merge': [[0, 1]]}), + ('curation_review.json', {'accepted': []}), + ): + (params.parent / name).write_text(json.dumps(value)) + output = prepare_large(params, tmp_path / 'bounded', window_seconds=20, stratum_seconds=20) + manifest = json.loads((output / '_phy_curation_manifest.json').read_text()) + assert manifest['bounded_files']['params.py'] == hash_file(output / 'params.py') + assert manifest['bounded_files']['_phy_cluster_metadata.json'] == hash_file( + output / '_phy_cluster_metadata.json' + ) + for name in ('curation.json', 'curation_review.json'): + assert (output / name).read_bytes() == (params.parent / name).read_bytes() + assert name not in manifest['excluded_files'] From 1ba129c2908d07dbed46fc52f79081016e75e272 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 10:37:42 +0200 Subject: [PATCH 07/53] Replay committed curation into validated immutable-source descendants --- phy/apps/large_recording/replay.py | 218 ++++++++++++++++++ phy/apps/large_recording/tests/test_replay.py | 142 ++++++++++++ 2 files changed, 360 insertions(+) create mode 100644 phy/apps/large_recording/replay.py create mode 100644 phy/apps/large_recording/tests/test_replay.py diff --git a/phy/apps/large_recording/replay.py b/phy/apps/large_recording/replay.py new file mode 100644 index 000000000..0fa3355ec --- /dev/null +++ b/phy/apps/large_recording/replay.py @@ -0,0 +1,218 @@ +"""Stream semantic curation into a new complete sorting, never the source.""" + +import csv +import os +import shutil +import tempfile +from pathlib import Path + +import numpy as np + +from .curation import ( + BoundedSession, + _digest, + _fsync_directory, + _write_json, + interpret_events, + project_assignments, +) +from .source import PER_SPIKE, Source, close_array, publish_directory + + +def _merge_mapping(unit_ids, events): + """Resolve a whole-unit merge journal once, independently of spike count.""" + lineage = {int(unit): [int(unit)] for unit in unit_ids} + for event in events: + if event['operation'] == 'merge': + members = [] + for parent in event['parents']: + members.extend(lineage.pop(parent)) + lineage[event['target']] = members + mapping = {old: new for new, members in lineage.items() for old in members} + keys = np.array(sorted(mapping), dtype=np.int64) + targets = np.array([mapping[int(key)] for key in keys], dtype=np.int64) + return keys, targets + + +def _write_metadata(path, metadata): + for field, values in sorted(metadata.items()): + if not field or any(char in field for char in ('/', '\\', '\0')): + raise ValueError('Metadata fields must be safe local filenames.') + with (path / f'cluster_{field}.tsv').open('w', encoding='utf8', newline='') as stream: + writer = csv.writer(stream, delimiter='\t') + writer.writerow(['cluster_id', field]) + for cluster, value in sorted(values.items()): + if value is not None: + writer.writerow([cluster, value]) + stream.flush() + os.fsync(stream.fileno()) + _write_json(path / '_phy_cluster_metadata.json', metadata) + + +def apply_curation(source_params, bounded_dir, output_dir, batch_size=100000): + """Validate identity/revision and replay only the last committed generation. + + The output is published as one new directory after validation. Full source + arrays remain file-backed; only one assignment batch and the unit map reside + in memory. Arbitrary selected-row splits have no journal interpretation. + """ + session = BoundedSession(bounded_dir) + source = None + try: + if session.checkpoint_path is None: + raise ValueError('Save a bounded semantic checkpoint before applying curation.') + manifest = session.manifest + source = Source( + source_params, + duration_seconds=manifest['num_samples'] / manifest['sample_rate'], + valid_intervals=manifest['valid_intervals'], + batch_size=batch_size, + ) + return _apply_curation(source, session, output_dir, batch_size) + finally: + if source is not None: + source.close() + session.close() + + +def _apply_curation(source, session, output_dir, batch_size): + manifest = session.manifest + expected = manifest['source'] + if source.identity != expected['identity']: + raise ValueError('Source coordinate/feature identity does not match bounded preparation.') + if source.revision != expected['revision']: + raise ValueError('Source assignment revision does not match journal parent revision.') + if ( + source.unit_ids.tolist() != manifest['unit_ids'] + or source.n_spikes != manifest['num_spikes'] + ): + raise ValueError('Source catalog or spike count does not match bounded preparation.') + # Identity/revision bind the complete source. Validate the actual projection + # too, so a tampered bounded base cannot silently replay unrelated evidence. + source_assignments = source.arrays['spike_clusters.npy'].reshape(-1) + for start in range(0, len(session.global_ids), batch_size): + rows = session.global_ids[start : start + batch_size] + if not np.array_equal( + source_assignments[rows], + session.base_assignments[start : start + batch_size], + ): + raise ValueError('Immutable bounded assignments do not match source rows.') + for name in sorted(source.arrays.keys() & (PER_SPIKE - {'spike_clusters.npy'})): + bounded = np.load(session.path / name, mmap_mode='r', allow_pickle=False) + try: + if bounded.shape != (len(session.global_ids), *source.arrays[name].shape[1:]): + raise ValueError(f'Bounded attribute has invalid source alignment: {name}.') + for start in range(0, len(session.global_ids), batch_size): + rows = session.global_ids[start : start + batch_size] + if not np.array_equal( + source.arrays[name][rows], + bounded[start : start + batch_size], + equal_nan=True, + ): + raise ValueError(f'Bounded attribute does not match source rows: {name}.') + finally: + close_array(bounded) + active_units, metadata, _ = interpret_events(source.unit_ids, source.metadata, session.events) + output = Path(output_dir).resolve() + if output.exists(): + raise FileExistsError(f'Curated output already exists: {output}.') + if output == source.path or source.path in output.parents: + raise ValueError('Curated output must be outside the immutable source directory.') + output.parent.mkdir(parents=True, exist_ok=True) + stage = Path(tempfile.mkdtemp(prefix=f'.{output.name}-', dir=output.parent)) + curated = None + assignments = None + try: + # Copy only validated canonical assets, not GUI caches or producer reviews. + for name in source.arrays: + if name != 'spike_clusters.npy': + shutil.copyfile(source.path / name, stage / name) + shutil.copyfile(source.params_path, stage / 'params.py') + upstream_manifest = source.path / '_phy_spikes_subset.manifest.json' + if upstream_manifest.exists(): + shutil.copyfile(upstream_manifest, stage / upstream_manifest.name) + # Preserve source params semantics and make external raw paths absolute. + # The full export can contain no raw traces; immutable array rows suffice. + dat_path = source.params.get('dat_path') + if dat_path: + raw_paths = dat_path if isinstance(dat_path, (list, tuple)) else [dat_path] + resolved = [str((source.path / raw).resolve()) for raw in raw_paths] + dat_path = resolved if isinstance(dat_path, (list, tuple)) else resolved[0] + with (stage / 'params.py').open('a', encoding='utf8') as stream: + stream.write(f'\nnum_samples = {source.num_samples!r}\n') + stream.write(f'valid_intervals = {source.valid_intervals.tolist()!r}\n') + stream.write(f'dat_path = {dat_path!r}\n') + assignments = np.lib.format.open_memmap( + stage / 'spike_clusters.npy', + mode='w+', + dtype=np.int64, + shape=source.arrays['spike_clusters.npy'].shape, + ) + flat = assignments.reshape(-1) + has_split = any(event['operation'] == 'threshold_split' for event in session.events) + keys, targets = ( + (None, None) if has_split else _merge_mapping(source.unit_ids, session.events) + ) + for batch in source.iter_batches(): + values = batch['spike_clusters.npy'] + if has_split: + projected = project_assignments(values, session.events, batch) + else: + positions = np.searchsorted(keys, values) + projected = targets[positions] + flat[batch['start'] : batch['stop']] = projected + assignments.flush() + assignments._mmap.close() + del flat, assignments + assignments = None + _write_metadata(stage, metadata) + _write_json(stage / '_phy_curation_journal.json', session.events) + # Re-reading verifies alignment, full catalog and immutable byte digests. + curated = Source(stage / 'params.py', batch_size=batch_size) + if curated.identity != source.identity or curated.n_spikes != source.n_spikes: + raise ValueError('Curated output changed immutable source coordinates.') + if curated.metadata != metadata: + raise ValueError('Curated output metadata failed exact round-trip validation.') + actual = curated.arrays['spike_clusters.npy'].reshape(-1) + for batch in source.iter_batches(): + if has_split: + expected_batch = project_assignments( + batch['spike_clusters.npy'], session.events, batch + ) + else: + expected_batch = targets[np.searchsorted(keys, batch['spike_clusters.npy'])] + if not np.array_equal(actual[batch['start'] : batch['stop']], expected_batch): + raise ValueError('Curated output assignments failed semantic replay verification.') + _write_json( + stage / '_phy_curation_lineage.json', + { + 'format': 'phy_curation_lineage', + 'format_version': 1, + 'coordinate_identity': source.identity, + 'parent_revision': source.revision, + 'journal_sha256': _digest(session.events), + 'revision': curated.revision, + 'preparation_sha256': _digest(manifest), + 'next_cluster_id': session.next_cluster_id, + 'unit_ids': sorted(active_units), + }, + ) + curated.close() + for path in stage.iterdir(): + if path.is_file(): + with path.open('rb') as stream: + os.fsync(stream.fileno()) + _fsync_directory(stage) + # Refuse replacement even when a racing caller creates the target. + if output.exists(): + raise FileExistsError(f'Curated output already exists: {output}.') + publish_directory(stage, output) + _fsync_directory(output.parent) + except BaseException: + if curated is not None: + curated.close() + if assignments is not None: + assignments._mmap.close() + shutil.rmtree(stage, ignore_errors=True) + raise + return output diff --git a/phy/apps/large_recording/tests/test_replay.py b/phy/apps/large_recording/tests/test_replay.py new file mode 100644 index 000000000..fefeb52ab --- /dev/null +++ b/phy/apps/large_recording/tests/test_replay.py @@ -0,0 +1,142 @@ +"""Full assignment oracle, revision binding and atomic publication regressions.""" + +import json + +import numpy as np +import pytest + +from phy.apps.large_recording.replay import apply_curation +from phy.apps.large_recording.source import Source, hash_file +from phy.apps.large_recording.tests.test_curation import make_session + + +def test_full_replay_chains_preserve_unseen_units_and_immutable_bytes(tmp_path): + source, session = make_session(tmp_path) + original_hashes = {name: hash_file(source.path / name) for name in source.arrays} + original = source.arrays['spike_clusters.npy'].copy() + session.record_merge([0, 1], 100, {'group': 'good', 'confidence': 0.8}) + session.record_label('group', [100], 'mua') + session.record_merge([100, 2], 101, {'group': 'good', 'confidence': None}) + session.record_label('custom', [99, 101], 'verified') + session.save() + output = apply_curation(source.params_path, session.path, tmp_path / 'curated', batch_size=3) + expected = np.where(np.isin(original, [0, 1, 2]), 101, original) + assert np.array_equal(np.load(output / 'spike_clusters.npy'), expected) + assert expected[-1] == 99 + curated = Source(output / 'params.py') + assert curated.metadata == session.metadata + assert curated.identity == source.identity + assert curated.revision != source.revision + lineage = json.loads((output / '_phy_curation_lineage.json').read_text()) + assert lineage['parent_revision'] == source.revision + assert lineage['revision'] == curated.revision + for name, digest in original_hashes.items(): + assert hash_file(source.path / name) == digest + if name != 'spike_clusters.npy': + assert hash_file(output / name) == digest + with pytest.raises(ValueError, match='revision'): + apply_curation(output / 'params.py', session.path, tmp_path / 'twice') + assert not (tmp_path / 'twice').exists() + second = apply_curation(source.params_path, session.path, tmp_path / 'second', batch_size=7) + assert hash_file(second / 'spike_clusters.npy') == hash_file(output / 'spike_clusters.npy') + + +def test_source_revision_and_feature_identity_are_independently_bound(tmp_path): + source, session = make_session(tmp_path) + session.save() + clusters = source.arrays['spike_clusters.npy'].copy() + clusters[0] = 2 + np.save(source.path / 'spike_clusters.npy', clusters) + with pytest.raises(ValueError, match='revision'): + apply_curation(source.params_path, session.path, tmp_path / 'wrong_revision') + amplitudes = source.arrays['amplitudes.npy'].copy() + amplitudes[0] += 1 + np.save(source.path / 'amplitudes.npy', amplitudes) + with pytest.raises(ValueError, match='identity'): + apply_curation(source.params_path, session.path, tmp_path / 'wrong_feature') + assert not (tmp_path / 'wrong_revision').exists() + assert not (tmp_path / 'wrong_feature').exists() + + +def test_full_threshold_split_matches_scalar_oracle(tmp_path): + source, session = make_session(tmp_path) + original = source.arrays['spike_clusters.npy'].copy() + amplitudes = source.arrays['amplitudes.npy'].copy() + predicate = { + 'attribute': 'amplitudes.npy', + 'operator': '<', + 'threshold': 15.0, + 'nonfinite': 'keep', + } + session.record_split(2, 100, 101, predicate, {'group': {100: 'noise', 101: 'good'}}) + session.record_merge([0, 100], 102, {'group': 'mua'}) + session.save() + expected = original.astype(np.int64) + expected[(original == 2) & (amplitudes < 15)] = 100 + expected[(original == 2) & ~(amplitudes < 15)] = 101 + expected[np.isin(expected, [0, 100])] = 102 + output = apply_curation(source.params_path, session.path, tmp_path / 'split', batch_size=4) + assert np.array_equal(np.load(output / 'spike_clusters.npy'), expected) + assert Source(output / 'params.py').metadata == session.metadata + + +def test_failed_replay_does_not_publish_output(tmp_path, monkeypatch): + from phy.apps.large_recording import replay + + source, session = make_session(tmp_path) + session.save() + original = replay._write_json + + def fail(path, value): + if path.name == '_phy_curation_lineage.json': + raise OSError('injected replay interruption') + return original(path, value) + + monkeypatch.setattr(replay, '_write_json', fail) + with pytest.raises(OSError, match='interruption'): + apply_curation(source.params_path, session.path, tmp_path / 'interrupted') + assert not (tmp_path / 'interrupted').exists() + assert not list(tmp_path.glob('.interrupted-*')) + + +def test_replay_requires_committed_checkpoint_and_new_output(tmp_path): + source, session = make_session(tmp_path) + with pytest.raises(ValueError, match='Save'): + apply_curation(source.params_path, session.path, tmp_path / 'unsaved') + session.save() + with pytest.raises(FileExistsError): + apply_curation(source.params_path, session.path, source.path) + + +def test_replay_preserves_empty_split_children_and_allocator_lineage(tmp_path): + source, session = make_session(tmp_path) + session.record_split( + 2, + 100, + 101, + { + 'attribute': 'amplitudes.npy', + 'operator': '<', + 'threshold': 100.0, + 'nonfinite': 'keep', + }, + ) + session.save() + output = apply_curation(source.params_path, session.path, tmp_path / 'empty_child') + curated = Source(output / 'params.py') + assert 101 in curated.unit_ids + assert curated.counts[curated.unit_ids.tolist().index(101)] == 0 + assert curated.next_cluster_id == 102 + + +def test_bounded_threshold_attribute_must_match_exact_source_rows(tmp_path): + source, session = make_session(tmp_path) + session.save() + # Even a manifest that does not hash this optional attribute must not allow + # evidence values different from those used by the full-data predicate. + values = np.load(session.path / 'amplitudes.npy') + values[0] += 1 + np.save(session.path / 'amplitudes.npy', values) + with pytest.raises(ValueError, match='does not match source rows'): + apply_curation(source.params_path, session.path, tmp_path / 'bad_evidence') + assert not (tmp_path / 'bad_evidence').exists() From b8b017f2df42504135a81e534f511f6e0d57f7e2 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 11:39:55 +0200 Subject: [PATCH 08/53] Avoid dense allocations for sparse cluster identifiers --- phy/cluster/clustering.py | 26 +++++++++++++++++++++++--- phy/cluster/tests/test_clustering.py | 22 ++++++++++++++++++++++ 2 files changed, 45 insertions(+), 3 deletions(-) diff --git a/phy/cluster/clustering.py b/phy/cluster/clustering.py index 662ca7439..32fa7480e 100644 --- a/phy/cluster/clustering.py +++ b/phy/cluster/clustering.py @@ -7,7 +7,8 @@ import logging import numpy as np -from phylib.io.array import _spikes_in_clusters, _spikes_per_cluster, _unique +from phylib.io.array import _spikes_in_clusters, _spikes_per_cluster +from phylib.io.array import _unique as _unique_dense from phylib.utils._types import _as_array, _is_array_like from phylib.utils.event import emit @@ -22,6 +23,23 @@ # ------------------------------------------------------------------------------ +def _unique(values): + """Preserve dense-ID performance without allocating by sparse absolute IDs.""" + if values is None or len(values) == 0: + return np.array([], dtype=np.int64) + values = np.asarray(values) + if int(values.max()) > max(1024, 4 * len(values)): + return np.unique(values[values >= 0]).astype(np.int64) + return _unique_dense(values) + + +def _largest_cluster(values): + if int(values.max()) > max(1024, 4 * len(values)): + ids, counts = np.unique(values, return_counts=True) + return int(ids[counts.argmax()]) + return int(np.bincount(values).argmax()) + + def _extend_spikes(spike_ids, spike_clusters): """Return all spikes belonging to the clusters containing the specified spikes.""" @@ -81,7 +99,7 @@ def _extend_assignment(spike_ids, old_spike_clusters, spike_clusters_rel, new_cl def _assign_update_info(spike_ids, old_spike_clusters, new_spike_clusters): old_clusters = _unique(old_spike_clusters) new_clusters = _unique(new_spike_clusters) - largest_old_cluster = np.bincount(old_spike_clusters).argmax() + largest_old_cluster = _largest_cluster(old_spike_clusters) descendants = list(set(zip(old_spike_clusters, new_spike_clusters))) update_info = UpdateInfo( description='assign', @@ -293,7 +311,9 @@ def _do_assign(self, spike_ids, new_spike_clusters): def _do_merge(self, spike_ids, cluster_ids, to): # Create the UpdateInfo instance here. descendants = [(cluster, to) for cluster in cluster_ids] - largest_old_cluster = np.bincount(self.spike_clusters[spike_ids]).argmax() + largest_old_cluster = max( + cluster_ids, key=lambda cluster: (len(self._spikes_per_cluster[cluster]), -cluster) + ) up = UpdateInfo( description='merge', spike_ids=list(spike_ids), diff --git a/phy/cluster/tests/test_clustering.py b/phy/cluster/tests/test_clustering.py index 9557221d7..ef8d03beb 100644 --- a/phy/cluster/tests/test_clustering.py +++ b/phy/cluster/tests/test_clustering.py @@ -26,6 +26,28 @@ # ------------------------------------------------------------------------------ +def test_sparse_absolute_cluster_ids_do_not_allocate_dense_histograms(monkeypatch): + original = np.bincount + + def bounded_bincount(values, *args, **kwargs): + assert not len(values) or np.max(values) < 1024 + return original(values, *args, **kwargs) + + monkeypatch.setattr(np, 'bincount', bounded_bincount) + high = 2_000_000_000 + clustering = Clustering(np.array([0, 1, 1, high], dtype=np.int64)) + first = clustering.merge([0, 1]) + assert first.largest_old_cluster == 1 + assert first.added == [high + 1] + second = clustering.merge([high, high + 1]) + assert second.largest_old_cluster == high + 1 + clustering.undo() + ae(clustering.spike_clusters, [high + 1, high + 1, high + 1, high]) + clustering.split([0]) + clustering.undo() + ae(clustering.spike_clusters, [high + 1, high + 1, high + 1, high]) + + def test_extend_spikes_simple(): spike_clusters = np.array([3, 5, 2, 9, 5, 5, 2]) spike_ids = np.array([2, 4, 0]) From 3e01be4c838cc522c6c1f477faaf7db1b26786ef Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 11:39:55 +0200 Subject: [PATCH 09/53] Add default-preserving supervisor and GUI state hooks --- phy/apps/base.py | 6 +++++- phy/cluster/supervisor.py | 13 +++++++++++-- 2 files changed, 16 insertions(+), 3 deletions(-) diff --git a/phy/apps/base.py b/phy/apps/base.py index 593ddfcff..63c8a7fc2 100644 --- a/phy/apps/base.py +++ b/phy/apps/base.py @@ -2449,7 +2449,11 @@ def create_gui(self, default_views=None, **kwargs): subtitle=str(self.dir_path), config_dir=self.config_dir, local_path=self.cache_dir / 'state.json', - default_state_path=Path(inspect.getfile(self.__class__)).parent / 'static/state.json', + default_state_path=getattr( + self, + 'default_state_path', + Path(inspect.getfile(self.__class__)).parent / 'static/state.json', + ), view_creator=self.view_creator, default_views=default_views, enable_threading=self._enable_threading, diff --git a/phy/cluster/supervisor.py b/phy/cluster/supervisor.py index 54c5988d1..5b0b4a3f9 100644 --- a/phy/cluster/supervisor.py +++ b/phy/cluster/supervisor.py @@ -755,6 +755,11 @@ class Supervisor: skip_masked_clusters : bool Whether automatic navigation and similar-cluster selection skip noise and MUA clusters. The default is True. + clustering_factory : callable, optional + Construct the clustering model. Defaults to Clustering; bounded curation + supplies a guarded implementation with the same constructor interface. + cluster_meta_factory : callable, optional + Construct metadata from groups and labels. Defaults to create_cluster_meta. Events ------ @@ -790,6 +795,8 @@ def __init__( n_similar_clusters_to_select=None, skip_masked_clusters=True, merge_propositions=None, + clustering_factory=None, + cluster_meta_factory=None, ): super().__init__() self.context = context @@ -833,7 +840,7 @@ def __init__( # Create Clustering and ClusterMeta. # Load the cached spikes_per_cluster array. spc = context.load('spikes_per_cluster') if context else None - self.clustering = Clustering( + self.clustering = (clustering_factory or Clustering)( spike_clusters, spikes_per_cluster=spc, new_cluster_id=new_cluster_id ) @@ -841,7 +848,9 @@ def __init__( self._save_spikes_per_cluster() # Create the ClusterMeta instance. - self.cluster_meta = create_cluster_meta(cluster_groups or {}, self.cluster_labels) + self.cluster_meta = (cluster_meta_factory or create_cluster_meta)( + cluster_groups or {}, self.cluster_labels + ) # Create the GlobalHistory instance. self._global_history = GlobalHistory( From cc91f6558c8f5b94a7f311e12c74d95cb45ac650 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 11:39:56 +0200 Subject: [PATCH 10/53] Guard semantic capabilities and serialize concurrent checkpoint saves --- phy/apps/large_recording/curation.py | 176 ++++++++++++++++-- .../large_recording/tests/test_curation.py | 171 +++++++++++++++++ 2 files changed, 336 insertions(+), 11 deletions(-) diff --git a/phy/apps/large_recording/curation.py b/phy/apps/large_recording/curation.py index a37e01456..52babbad6 100644 --- a/phy/apps/large_recording/curation.py +++ b/phy/apps/large_recording/curation.py @@ -6,6 +6,7 @@ import os import shutil import uuid +from contextlib import contextmanager from pathlib import Path import numpy as np @@ -14,6 +15,14 @@ MANIFEST = '_phy_curation_manifest.json' BASE_ASSIGNMENTS = '_phy_spike_clusters_base.npy' +BOOLEAN_CAPABILITIES = ( + 'merge', + 'label', + 'split', + 'stored_waveforms', + 'raw_traces', + 'normalized_correlograms', +) def _json_bytes(value): @@ -64,12 +73,85 @@ def _safe_file(root, name): return path +@contextmanager +def _commit_lock(root): + """Hold a process-safe OS lock; process exit releases it automatically.""" + with _safe_file(root, 'commit.lock').open('a+b') as stream: + if os.name == 'nt': + import msvcrt + + # Windows byte-range locking requires at least one byte in the file. + stream.seek(0, os.SEEK_END) + if stream.tell() == 0: + stream.write(b'\0') + stream.flush() + stream.seek(0) + msvcrt.locking(stream.fileno(), msvcrt.LK_LOCK, 1) + try: + yield + finally: + stream.seek(0) + msvcrt.locking(stream.fileno(), msvcrt.LK_UNLCK, 1) + else: + import fcntl + + fcntl.flock(stream.fileno(), fcntl.LOCK_EX) + try: + yield + finally: + fcntl.flock(stream.fileno(), fcntl.LOCK_UN) + + +def _current_pointer(root): + try: + return _read_json(root / 'current.json') + except FileNotFoundError: + return None + + def _integer(value, name): if isinstance(value, bool) or not isinstance(value, (int, np.integer)) or value < 0: raise ValueError(f'{name} must be a nonnegative integer.') return int(value) +def _validate_capabilities(manifest): + capabilities = manifest.get('capabilities', {}) + if not isinstance(capabilities, dict): + raise ValueError('Bounded capabilities must be a mapping.') + if ( + set(capabilities) + - set(BOOLEAN_CAPABILITIES) + - { + 'full_attributes', + 'predicate_split_attributes', + } + ): + raise ValueError('Unsupported bounded capability declaration.') + result = {} + for name in BOOLEAN_CAPABILITIES: + value = capabilities.get(name, False) + if type(value) is not bool: + raise ValueError(f'Bounded capability {name!r} must be a boolean.') + result[name] = value + if result['split']: + raise ValueError('General selected-row splits are unsupported in bounded mode.') + for name in ('full_attributes', 'predicate_split_attributes'): + values = capabilities.get(name, []) + if ( + not isinstance(values, list) + or any(not isinstance(value, str) for value in values) + or len(set(values)) != len(values) + ): + raise ValueError(f'Bounded capability {name!r} must be a unique string list.') + result[name] = list(values) + if set(result['predicate_split_attributes']) - {'amplitudes.npy'}: + raise ValueError( + 'Unsupported bounded predicate attribute; only raw amplitudes are supported.' + ) + return result + + def _field_name(field): if ( not isinstance(field, str) @@ -152,6 +234,8 @@ def interpret_events(unit_ids, metadata, events): raise ValueError('Malformed merge event.') parents = [_integer(i, 'Parent ID') for i in event['parents']] target = _integer(event['target'], 'Target ID') + if target > np.iinfo(np.int32).max: + raise ValueError('Target cluster ID exceeds the current Phy loader namespace.') if len(parents) < 2 or len(set(parents)) != len(parents): raise ValueError('Merge requires at least two distinct complete units.') if not set(parents) <= active or target in allocated or target < next_id: @@ -195,6 +279,8 @@ def interpret_events(unit_ids, metadata, events): raise ValueError('Malformed threshold split event.') parent = _integer(event['parent'], 'Parent ID') children = [_integer(i, 'Child ID') for i in event['children']] + if any(child > np.iinfo(np.int32).max for child in children): + raise ValueError('Child cluster ID exceeds the current Phy loader namespace.') validate_predicate(event['predicate']) if parent not in active or len(children) != 2 or len(set(children)) != 2: raise ValueError('Threshold split requires an active parent and two children.') @@ -247,6 +333,16 @@ class BoundedSession: """ def __init__(self, dataset_path): + self.global_ids = None + self.base_assignments = None + self.attributes = {} + try: + self._initialize(dataset_path) + except BaseException: + self.close() + raise + + def _initialize(self, dataset_path): self.path = Path(dataset_path) if self.path.is_file(): self.path = self.path.parent @@ -300,7 +396,10 @@ def __init__(self, dataset_path): 'valid_intervals': manifest['valid_intervals'], }: raise ValueError('Bounded time base disagrees with immutable source identity.') + self.capabilities = _validate_capabilities(manifest) self.unit_ids = [_integer(i, 'Unit ID') for i in manifest['unit_ids']] + if any(unit > np.iinfo(np.int32).max for unit in self.unit_ids): + raise ValueError('Unit IDs exceed the current Phy loader namespace.') if not self.unit_ids or len(set(self.unit_ids)) != len(self.unit_ids): raise ValueError('Full unit catalog must contain distinct unit IDs.') counts = np.asarray(manifest['counts']) @@ -395,17 +494,31 @@ def __init__(self, dataset_path): for name in ('amplitudes.npy', 'spike_templates.npy'): if (self.path / name).exists(): self.attributes[name] = np.load(self.path / name, mmap_mode='r') + for name in self.capabilities['predicate_split_attributes']: + array = self.attributes.get(name) + if ( + array is None + or name not in identity['arrays'] + or not (array.ndim == 1 or array.shape[1:] == (1,)) + or len(array) != n + or array.dtype.kind not in 'iuf' + ): + raise ValueError( + f'Bounded predicate attribute is not available as a source scalar: {name}.' + ) self.assignments = np.asarray(self.base_assignments, dtype=np.int64).copy() self.metadata = copy.deepcopy(self.base_metadata) self.events = [] self.extra_documents = {} self.next_cluster_id = self.base_next_cluster_id self.checkpoint_path = None + self._expected_pointer = None pointer_path = self.path / '.phy-curation' / 'current.json' if pointer_path.exists(): self._load_checkpoint(pointer_path) def _validated_state(self, assignments, metadata, events, next_cluster_id): + self._validate_event_capabilities(events) _, projected_metadata, minimum = interpret_events( self.unit_ids, self.base_metadata, events ) @@ -451,6 +564,7 @@ def _load_checkpoint(self, pointer_path): self.events = events self.next_cluster_id = next_id self.checkpoint_path = generation + self._expected_pointer = copy.deepcopy(pointer) self.extra_documents = { name: _read_json(generation / name) for name in descriptor.get('extra_documents', []) } @@ -474,6 +588,7 @@ def journal_state(self): def restore_journal(self, state): """Restore an active history prefix while preserving allocator high-water.""" events = list(state['events']) + self._validate_event_capabilities(events) _, metadata, minimum = interpret_events(self.unit_ids, self.base_metadata, events) next_id = _integer(state['next_cluster_id'], 'Next cluster ID') if next_id < max(minimum, self.base_next_cluster_id): @@ -496,6 +611,7 @@ def restore(self, snapshot): self.next_cluster_id = next_id def _append(self, event): + self._validate_event_capabilities([event]) events = self.events + [event] _, metadata, next_id = interpret_events(self.unit_ids, self.base_metadata, events) assignments = project_assignments(self.base_assignments, events, self.attributes) @@ -503,7 +619,27 @@ def _append(self, event): self.next_cluster_id = max(self.next_cluster_id, next_id) return copy.deepcopy(event) + def _require_capability(self, operation, predicate=None): + if operation == 'threshold_split': + predicate = validate_predicate(predicate) + if predicate['attribute'] not in self.capabilities['predicate_split_attributes']: + raise ValueError( + 'Predicate split capability is unavailable in this bounded package.' + ) + elif not self.capabilities.get(operation, False): + raise ValueError( + f'{operation.capitalize()} capability is disabled in this bounded package.' + ) + + def _validate_event_capabilities(self, events): + for event in events: + if isinstance(event, dict): + operation = event.get('operation') + if operation in ('merge', 'label', 'threshold_split'): + self._require_capability(operation, event.get('predicate')) + def preflight_merge(self, parents, target, metadata=None): + self._require_capability('merge') event = { 'version': 1, 'operation': 'merge', @@ -519,19 +655,24 @@ def preflight_merge(self, parents, target, metadata=None): def record_merge(self, parents, target, metadata=None): return self._append(self.preflight_merge(parents, target, metadata)) + def preflight_label(self, field, ids, value): + self._require_capability('label') + event = { + 'version': 1, + 'operation': 'label', + 'field': field, + 'ids': [int(i) for i in ids], + 'value': copy.deepcopy(value), + } + interpret_events(self.unit_ids, self.base_metadata, self.events + [event]) + return event + def record_label(self, field, ids, value): - return self._append( - { - 'version': 1, - 'operation': 'label', - 'field': field, - 'ids': [int(i) for i in ids], - 'value': copy.deepcopy(value), - } - ) + return self._append(self.preflight_label(field, ids, value)) def record_threshold_split(self, parent, children, predicate, metadata=None): - """Pure replay service; the bounded GUI currently keeps splits disabled.""" + """Apply an explicitly enabled full-source scalar predicate.""" + self._require_capability('threshold_split', predicate) children = [int(i) for i in children] if any(i < self.next_cluster_id for i in children): raise ValueError('Threshold children collide with the complete catalog allocator.') @@ -547,6 +688,7 @@ def record_threshold_split(self, parent, children, predicate, metadata=None): ) def preflight_split(self, parent, selected_id, remainder_id, predicate, metadata=None): + self._require_capability('threshold_split', predicate) children = [int(remainder_id), int(selected_id)] if any(i < self.next_cluster_id for i in children): raise ValueError('Threshold children collide with the complete catalog allocator.') @@ -598,6 +740,16 @@ def save( generations.mkdir(parents=True, exist_ok=True) _fsync_directory(root) _fsync_directory(self.path) + with _commit_lock(root): + if _current_pointer(root) != self._expected_pointer: + raise ValueError( + 'Bounded curation checkpoint changed in another session; ' + 'reopen the dataset before saving to avoid losing its changes.' + ) + return self._save_generation(generations, values, metadata, events, next_id, documents) + + def _save_generation(self, generations, values, metadata, events, next_id, documents): + root = generations.parent identifier = uuid.uuid4().hex stage = generations / f'.{identifier}.tmp' final = generations / identifier @@ -625,7 +777,8 @@ def save( _fsync_directory(stage) os.replace(stage, final) _fsync_directory(generations) - _write_json(pointer_tmp, {'generation': identifier, 'sha256': _digest(descriptor)}) + pointer = {'generation': identifier, 'sha256': _digest(descriptor)} + _write_json(pointer_tmp, pointer) os.replace(pointer_tmp, root / 'current.json') _fsync_directory(root) except BaseException: @@ -635,4 +788,5 @@ def save( self.assignments, self.metadata, self.events = values, metadata, copy.deepcopy(events) self.next_cluster_id, self.checkpoint_path = next_id, final self.extra_documents = documents + self._expected_pointer = pointer return final diff --git a/phy/apps/large_recording/tests/test_curation.py b/phy/apps/large_recording/tests/test_curation.py index 5de69f1f7..2aa748a6d 100644 --- a/phy/apps/large_recording/tests/test_curation.py +++ b/phy/apps/large_recording/tests/test_curation.py @@ -44,6 +44,12 @@ def make_session(tmp_path): 'global_spike_ids_file': '_phy_spike_global_ids.npy', 'windows_file': 'windows.npy', 'base_metadata': source.metadata, + 'capabilities': { + 'merge': True, + 'label': True, + 'split': False, + 'predicate_split_attributes': ['amplitudes.npy'], + }, 'bounded_files': { name: hash_file(fixture.bounded / name) for name in ( @@ -253,3 +259,168 @@ def test_session_close_releases_own_file_mappings(tmp_path): session.close() assert all(mapping.closed for mapping in mappings) session.close() + + +def test_stale_session_save_rejected_without_losing_first_commit(tmp_path): + _, first = make_session(tmp_path) + second = BoundedSession(first.path) + first.record_merge([0, 1], 100, {'group': 'good'}) + second.record_merge([1, 2], 100, {'group': 'noise'}) + first.save(extra_documents={'curation_review.json': {'accepted': [100]}}) + with pytest.raises(ValueError, match='reopen'): + second.save(extra_documents={'curation_review.json': {'rejected': [100]}}) + reopened = BoundedSession(first.path) + assert reopened.events == first.events + assert reopened.extra_documents == first.extra_documents + assert second.events != reopened.events + # The winning session can commit again without reopening. + first.record_label('group', [100], 'mua') + first.save() + assert BoundedSession(first.path).metadata['group'][100] == 'mua' + + +def test_failed_save_releases_commit_lock(tmp_path, monkeypatch): + from phy.apps.large_recording import curation + + _, session = make_session(tmp_path) + session.save() + other = BoundedSession(session.path) + original = curation._write_json + + def fail(path, value): + if path.name == 'journal.json': + raise OSError('injected locked save failure') + return original(path, value) + + with monkeypatch.context() as patch: + patch.setattr(curation, '_write_json', fail) + with pytest.raises(OSError, match='locked'): + session.save() + other.record_label('group', [0], 'mua') + other.save() + assert BoundedSession(session.path).metadata['group'][0] == 'mua' + + +def _concurrent_save_worker(path, barrier, results, label): + session = BoundedSession(path) + try: + session.record_label('group', [0], label) + barrier.wait(timeout=20) + try: + session.save() + except ValueError as error: + results.put(('conflict', str(error))) + else: + results.put(('saved', label)) + finally: + session.close() + + +def test_concurrent_process_saves_compare_generation_under_lock(tmp_path): + import multiprocessing + + _, session = make_session(tmp_path) + session.save() + context = multiprocessing.get_context('spawn') + barrier = context.Barrier(2) + results = context.Queue() + processes = [ + context.Process( + target=_concurrent_save_worker, + args=(str(session.path), barrier, results, label), + ) + for label in ('good', 'noise') + ] + for process in processes: + process.start() + try: + outcomes = [results.get(timeout=30) for _ in processes] + for process in processes: + process.join(timeout=10) + assert process.exitcode == 0 + assert sorted(status for status, _ in outcomes) == ['conflict', 'saved'] + winner = next(value for status, value in outcomes if status == 'saved') + assert 'reopen' in next(value for status, value in outcomes if status == 'conflict') + assert BoundedSession(session.path).metadata['group'][0] == winner + finally: + for process in processes: + if process.is_alive(): + process.terminate() + process.join(timeout=5) + results.close() + + +def _replace_capabilities(session, capabilities): + session.close() + path = session.path / '_phy_curation_manifest.json' + manifest = json.loads(path.read_text()) + if capabilities is None: + manifest.pop('capabilities', None) + else: + manifest['capabilities'] = capabilities + path.write_text(json.dumps(manifest)) + return BoundedSession(session.path) + + +@pytest.mark.parametrize( + 'capabilities', [None, {}, {'merge': False, 'label': False, 'split': False}] +) +def test_readonly_capabilities_reject_public_mutations_without_state_changes( + tmp_path, capabilities +): + _, session = make_session(tmp_path) + session = _replace_capabilities(session, capabilities) + before = session.snapshot() + predicate = { + 'attribute': 'amplitudes.npy', + 'operator': '<', + 'threshold': 15.0, + 'nonfinite': 'keep', + } + commands = [ + lambda: session.preflight_merge([0, 1], 100), + lambda: session.record_merge([0, 1], 100), + lambda: session.preflight_label('group', [0], 'good'), + lambda: session.record_label('group', [0], 'good'), + lambda: session.preflight_split(2, 100, 101, predicate), + lambda: session.record_split(2, 100, 101, predicate), + lambda: session.record_threshold_split(2, [101, 100], predicate), + ] + for command in commands: + with pytest.raises(ValueError, match='capability'): + command() + assert session.events == before['events'] + assert session.metadata == before['metadata'] + assert session.next_cluster_id == before['next_cluster_id'] + assert np.array_equal(session.assignments, before['assignments']) + + +@pytest.mark.parametrize( + 'capabilities', + [ + {'merge': 'true'}, + {'label': 'false'}, + {'stored_waveforms': 1}, + {'raw_traces': None}, + {'split': True}, + {'predicate_split_attributes': 'amplitudes.npy'}, + {'predicate_split_attributes': ['amplitudes.npy', 'amplitudes.npy']}, + {'predicate_split_attributes': ['spike_templates.npy']}, + {'predicate_split_attributes': ['waveform_peak']}, + {'predicate_split_attributes': [True]}, + {'full_attributes': 'amplitude'}, + ], +) +def test_malformed_or_unsupported_capabilities_fail_validation(tmp_path, capabilities): + _, session = make_session(tmp_path) + with pytest.raises(ValueError, match='capability|capabilities|unsupported|Unsupported'): + _replace_capabilities(session, capabilities) + + +def test_predicate_capability_requires_an_available_scalar_source_attribute(tmp_path): + _, session = make_session(tmp_path) + session.close() + values = np.load(session.path / 'amplitudes.npy') + np.save(session.path / 'amplitudes.npy', np.column_stack([values, values])) + with pytest.raises(ValueError, match='source scalar'): + BoundedSession(session.path) From 551ab4b13ae374932e3086134f4f94c124c4976e Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 11:39:56 +0200 Subject: [PATCH 11/53] Harden evidence provenance, publication, and acquisition boundaries --- phy/apps/large_recording/prepare.py | 33 ++++++++++++-- phy/apps/large_recording/replay.py | 11 +++++ phy/apps/large_recording/source.py | 44 ++++++++++++++++--- .../large_recording/tests/test_prepare.py | 42 ++++++++++++++++++ phy/apps/large_recording/tests/test_source.py | 42 ++++++++++++++++++ 5 files changed, 163 insertions(+), 9 deletions(-) diff --git a/phy/apps/large_recording/prepare.py b/phy/apps/large_recording/prepare.py index 15920b1ef..308fca6b2 100644 --- a/phy/apps/large_recording/prepare.py +++ b/phy/apps/large_recording/prepare.py @@ -32,10 +32,12 @@ def _row_bounds(times, windows): ] -def _union(windows): +def _union(windows, block_starts=()): result = [] for start, end in sorted(windows): - if result and start <= result[-1][1]: + if result and ( + start < result[-1][1] or (start == result[-1][1] and start not in block_starts) + ): result[-1][1] = max(result[-1][1], int(end)) else: result.append([int(start), int(end)]) @@ -180,7 +182,7 @@ def _prepare_source( rng = np.random.default_rng(seed) def accept(start, end, kind, segment, stratum_id): - candidate = _union([*windows, [start, end]]) + candidate = _union([*windows, [start, end]], set(source.valid_intervals[:, 0])) n = sum(stop - first for first, stop in _row_bounds(times, candidate)) n_waveforms = _selected_waveform_count(source, candidate) size = fixed_bytes + n * row_bytes + n_waveforms * waveform_bytes + len(candidate) * 256 @@ -241,6 +243,17 @@ def accept(start, end, kind, segment, stratum_id): 'or shorten window_seconds (tied spikes remain together).' ) output_dir.parent.mkdir(parents=True, exist_ok=True) + estimated_bytes = ( + fixed_bytes + + n_bounded * row_bytes + + _selected_waveform_count(source, windows) * waveform_bytes + + len(windows) * 256 + ) + free = shutil.disk_usage(output_dir.parent).free + if free < estimated_bytes: + raise OSError( + f'Insufficient disk space for bounded preparation: estimated {estimated_bytes:,} bytes, {free:,} available.' + ) temporary = Path( tempfile.mkdtemp(prefix=f'.{output_dir.name}.prepare-', dir=output_dir.parent) ) @@ -280,6 +293,17 @@ def accept(start, end, kind, segment, stratum_id): shutil.copyfile(source.path / name, temporary / name) if source.arrays.keys() >= WAVEFORMS: _copy_waveforms(source, temporary, global_ids, row_bounds) + waveform_counts = {int(unit): 0 for unit in source.unit_ids} + waveform_ids_path = temporary / '_phy_spikes_subset.spikes.npy' + if waveform_ids_path.exists(): + waveform_ids = np.load(waveform_ids_path, mmap_mode='r') + for start in range(0, len(waveform_ids), batch_size): + ids, counts = np.unique( + base[waveform_ids[start : start + batch_size]], return_counts=True + ) + for unit, count in zip(ids, counts): + waveform_counts[int(unit)] += int(count) + waveform_ids._mmap.close() np.save(temporary / '_phy_curation_windows.npy', np.asarray(windows, dtype=np.int64)) _write_metadata(temporary, source.metadata) (temporary / '_phy_cluster_metadata.json').write_text( @@ -350,6 +374,7 @@ def accept(start, end, kind, segment, stratum_id): 'unit_ids': source.unit_ids.tolist(), 'counts': source.counts.tolist(), 'bounded_counts': [bounded_counts[int(unit)] for unit in source.unit_ids], + 'waveform_counts': [waveform_counts[int(unit)] for unit in source.unit_ids], 'next_cluster_id': source.next_cluster_id, 'global_spike_ids_file': '_phy_spike_global_ids.npy', 'base_assignments_file': '_phy_spike_clusters_base.npy', @@ -387,7 +412,7 @@ def accept(start, end, kind, segment, stratum_id): 'predicate_split_attributes': ( ['amplitudes.npy'] if 'amplitude' in scalar_attributes(source) else [] ), - 'stored_waveforms': source.arrays.keys() >= WAVEFORMS, + 'stored_waveforms': bool(sum(waveform_counts.values())), 'raw_traces': False, 'normalized_correlograms': False, }, diff --git a/phy/apps/large_recording/replay.py b/phy/apps/large_recording/replay.py index 0fa3355ec..965fde0f7 100644 --- a/phy/apps/large_recording/replay.py +++ b/phy/apps/large_recording/replay.py @@ -119,6 +119,17 @@ def _apply_curation(source, session, output_dir, batch_size): if output == source.path or source.path in output.parents: raise ValueError('Curated output must be outside the immutable source directory.') output.parent.mkdir(parents=True, exist_ok=True) + estimated_bytes = sum( + (source.path / name).stat().st_size + for name in source.arrays + if name != 'spike_clusters.npy' + ) + estimated_bytes += source.n_spikes * 8 + 1024 * 1024 + free = shutil.disk_usage(output.parent).free + if free < estimated_bytes: + raise OSError( + f'Insufficient disk space for full replay: estimated at least {estimated_bytes:,} bytes, {free:,} available.' + ) stage = Path(tempfile.mkdtemp(prefix=f'.{output.name}-', dir=output.parent)) curated = None assignments = None diff --git a/phy/apps/large_recording/source.py b/phy/apps/large_recording/source.py index 89fd2c48c..9d86c7b31 100644 --- a/phy/apps/large_recording/source.py +++ b/phy/apps/large_recording/source.py @@ -28,6 +28,7 @@ ( 'templates.npy', 'templates_ind.npy', + 'template_ind.npy', 'channel_map.npy', 'channel_positions.npy', 'channel_shanks.npy', @@ -181,6 +182,16 @@ class Source: def __init__( self, params_path, duration_seconds=None, valid_intervals=None, batch_size=100000 + ): + self.arrays = {} + try: + self._initialize(params_path, duration_seconds, valid_intervals, batch_size) + except BaseException: + self.close() + raise + + def _initialize( + self, params_path, duration_seconds=None, valid_intervals=None, batch_size=100000 ): self.params_path = Path(params_path).resolve() self.path = self.params_path.parent @@ -204,6 +215,7 @@ def __init__( raise ValueError('A positive finite sample_rate is required.') upstream = self.path / '_phy_spikes_subset.manifest.json' recording = {} + info = {} if upstream.exists(): info = json.loads(upstream.read_text(encoding='utf-8')) if info.get('format') != 'phy_spikes_subset' or info.get('format_version') != 1: @@ -318,6 +330,10 @@ def __init__( if not isinstance(unit, int) or unit < 0: raise ValueError('Lineage unit IDs must be nonnegative integers.') counts.setdefault(unit, 0) + if any(unit < 0 or unit > np.iinfo(np.int32).max for unit in counts): + raise ValueError( + 'Unit IDs must fit nonnegative int32 for the current Phy loader; spike sample/row coordinates remain int64.' + ) self.unit_ids = np.array(sorted(counts), dtype=np.int64) minimum_next = int(self.unit_ids[-1]) + 1 if len(self.unit_ids) else 0 self.next_cluster_id = lineage.get('next_cluster_id', minimum_next) @@ -355,6 +371,19 @@ def __init__( 'arrays': {name: hash_file(self.path / name) for name in immutable}, } self.identity['sha256'] = hash_json(self.identity) + declared_source = info.get('source_sorting', {}) + if not isinstance(declared_source, dict): + raise ValueError('Waveform manifest source_sorting must be a mapping.') + if declared_source.get('num_spikes', self.n_spikes) != self.n_spikes: + raise ValueError('Waveform reservoir source spike count does not match this sorting.') + declared_times = declared_source.get('spike_times_sha256') + if ( + declared_times is not None + and declared_times != self.identity['arrays']['spike_times.npy'] + ): + raise ValueError( + 'Waveform reservoir source coordinate fingerprint does not match this sorting.' + ) self.revision = assignment_revision(self.path, self.metadata) if lineage: if ( @@ -489,18 +518,23 @@ def validate(self): raise ValueError(f'{name} must contain a model-channel square matrix.') templates = self.arrays.get('templates.npy') if templates is not None: - sparse = self.arrays.get('templates_ind.npy') + # phylib uses singular template_ind; KS2's plural sidecar does + # not turn a dense tensor into a sparse tensor in the loader. + sparse = self.arrays.get('template_ind.npy') if templates.ndim != 3: raise ValueError('templates.npy must be a template/sample/channel tensor.') if sparse is None and templates.shape[2] != len(channels): raise ValueError('Dense templates must align with model channels.') - if sparse is not None: + for index_name in ('template_ind.npy', 'templates_ind.npy'): + sparse = self.arrays.get(index_name) + if sparse is None: + continue if sparse.shape != (len(templates), templates.shape[2]): - raise ValueError('templates_ind.npy must align with sparse templates.') + raise ValueError(f'{index_name} must align with sparse templates.') if not np.issubdtype(sparse.dtype, np.integer): - raise ValueError('templates_ind.npy must contain integer channel indices.') + raise ValueError(f'{index_name} must contain integer channel indices.') if np.any((sparse < -1) | (sparse >= len(channels))): - raise ValueError('templates_ind.npy contains invalid model channel IDs.') + raise ValueError(f'{index_name} contains invalid model channel IDs.') positions = self.arrays.get('channel_positions.npy') if positions is not None and (positions.ndim != 2 or len(positions) != len(channels)): raise ValueError('channel_positions.npy must align with model channels.') diff --git a/phy/apps/large_recording/tests/test_prepare.py b/phy/apps/large_recording/tests/test_prepare.py index 7b5b0bcb9..7dacb519b 100644 --- a/phy/apps/large_recording/tests/test_prepare.py +++ b/phy/apps/large_recording/tests/test_prepare.py @@ -136,6 +136,48 @@ def test_prepare_missing_waveforms_is_explicit(tmp_path): assert not (output / '_phy_spikes_subset.waveforms.npy').exists() +def test_spikeinterface_singular_sparse_template_indices(tmp_path): + params = make_sorting(tmp_path / 'full') + templates = np.load(params.parent / 'templates.npy')[:, :, :2] + templates[1, :, 1] = 0 + np.save(params.parent / 'templates.npy', templates) + indices = np.array([[0, 2], [1, -1], [2, 0]], dtype=np.int32) + np.save(params.parent / 'template_ind.npy', indices) + output = prepare_large(params, tmp_path / 'bounded', window_seconds=20, stratum_seconds=20) + model = load_model(output / 'params.py') + try: + np.testing.assert_array_equal(model.sparse_templates.cols, indices) + finally: + model.close() + + +def test_adjacent_acquisition_blocks_retain_observation_boundaries(tmp_path): + params = make_sorting(tmp_path / 'full') + output = prepare_large( + params, + tmp_path / 'bounded', + valid_intervals=[[0, 10], [10, 20]], + window_seconds=10, + stratum_seconds=10, + ) + manifest = json.loads((output / '_phy_curation_manifest.json').read_text()) + np.testing.assert_array_equal(np.load(output / manifest['windows_file']), [[0, 10], [10, 20]]) + assert manifest['windows'][0]['block'] != manifest['windows'][1]['block'] + + +def test_disk_preflight_rejects_before_writing_package(tmp_path, monkeypatch): + from types import SimpleNamespace + + from phy.apps.large_recording import prepare + + params = make_sorting(tmp_path / 'full') + monkeypatch.setattr(prepare.shutil, 'disk_usage', lambda path: SimpleNamespace(free=0)) + with pytest.raises(OSError, match='Insufficient disk'): + prepare_large(params, tmp_path / 'bounded', window_seconds=20, stratum_seconds=20) + assert not (tmp_path / 'bounded').exists() + assert not list(tmp_path.glob('.bounded.prepare-*')) + + def test_final_windows_records_match_retained_samples_and_gaps(tmp_path): params = make_sorting(tmp_path / 'full') output = prepare_large( diff --git a/phy/apps/large_recording/tests/test_source.py b/phy/apps/large_recording/tests/test_source.py index 0781ca843..b3c1c45ee 100644 --- a/phy/apps/large_recording/tests/test_source.py +++ b/phy/apps/large_recording/tests/test_source.py @@ -59,6 +59,48 @@ def test_source_batches_ties_counts_columns(tmp_path, columns): assert source.metadata['group'][99] == 'noise' +def test_declared_waveform_source_identity_is_checked(tmp_path): + params = make_sorting(tmp_path / 'full') + manifest = { + 'format': 'phy_spikes_subset', + 'format_version': 1, + 'recording': {'num_samples': 20, 'sampling_frequency_hz': 1}, + 'source_sorting': {'num_spikes': 12, 'spike_times_sha256': '0' * 64}, + } + path = params.parent / '_phy_spikes_subset.manifest.json' + path.write_text(json.dumps(manifest)) + with pytest.raises(ValueError, match='fingerprint'): + Source(params) + manifest['source_sorting']['spike_times_sha256'] = hash_file(params.parent / 'spike_times.npy') + path.write_text(json.dumps(manifest)) + Source(params).close() + manifest['source_sorting']['num_spikes'] = 13 + path.write_text(json.dumps(manifest)) + with pytest.raises(ValueError, match='spike count'): + Source(params) + + +def test_failed_source_validation_closes_readers_and_rejects_unsupported_ids( + tmp_path, monkeypatch +): + params = make_sorting(tmp_path / 'full') + labels = np.load(params.parent / 'spike_clusters.npy').astype(np.int64) + labels[-1] = 2**31 + np.save(params.parent / 'spike_clusters.npy', labels) + original = np.load + readers = [] + + def read(*args, **kwargs): + array = original(*args, **kwargs) + readers.append(array) + return array + + monkeypatch.setattr(np, 'load', read) + with pytest.raises(ValueError, match='int32'): + Source(params) + assert all(array._mmap.closed for array in readers) + + def test_identity_assignment_and_feature_layers(tmp_path): params = make_sorting(tmp_path / 'full') source = Source(params) From 28b510a59051cfe63cc4ffa32035a9bbbed9c884 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 11:40:09 +0200 Subject: [PATCH 12/53] Compute sampled timing statistics within acquisition windows --- phy/apps/large_recording/statistics.py | 67 +++++++++++++++++++ .../large_recording/tests/test_statistics.py | 43 ++++++++++++ 2 files changed, 110 insertions(+) create mode 100644 phy/apps/large_recording/statistics.py create mode 100644 phy/apps/large_recording/tests/test_statistics.py diff --git a/phy/apps/large_recording/statistics.py b/phy/apps/large_recording/statistics.py new file mode 100644 index 000000000..04742de84 --- /dev/null +++ b/phy/apps/large_recording/statistics.py @@ -0,0 +1,67 @@ +"""Descriptive statistics restricted to retained contiguous observation windows.""" + +import numpy as np +from phylib.stats import correlograms + + +def window_isi(samples, windows, sample_rate): + intervals = [] + for start, end in windows: + first, last = np.searchsorted(samples, [start, end]) + intervals.append(np.diff(samples[first:last]) / sample_rate) + return np.concatenate(intervals) if intervals else np.array([], dtype=np.float64) + + +def window_correlograms( + samples, clusters, windows, cluster_ids, sample_rate, bin_size, window_size +): + """Exact window-local pair counts, without a full-duration rate baseline. + + Positive/negative lag bins follow phylib's floor-to-bin convention. The + central bin counts unordered within-unit pairs and cross-unit pairs with + absolute delays below one bin. Cross-unit central counts sum both temporal + orientations, making them independent of equal-time source row order. + """ + selected = np.isin(clusters, cluster_ids) + order = np.argsort(cluster_ids) + sorted_ids = np.asarray(cluster_ids)[order] + result = None + for start, end in windows: + first, last = np.searchsorted(samples, [start, end]) + mask = selected[first:last] + ticks = samples[first:last][mask] - start + if len(ticks) and ticks.max() >= 2**50: + raise ValueError( + 'Observation window is too long for exact correlogram sample conversion.' + ) + # phylib truncates float times * rate to integer samples. A common + # quarter-sample offset preserves every integer tick after conversion + # without changing any pair delay, including late-clock recordings. + times = (ticks.astype(np.float64) + 0.25) / sample_rate + # Avoid phylib's lookup allocation indexed by absolute cluster ID. + labels = order[np.searchsorted(sorted_ids, clusters[first:last][mask])] + if np.any(np.bincount(labels, minlength=len(cluster_ids)) > 46340): + raise ValueError( + 'Evidence window has too many spikes for exact correlogram counts; prepare shorter windows.' + ) + positive = correlograms( + times, + labels, + sample_rate=sample_rate, + cluster_ids=np.arange(len(cluster_ids)), + bin_size=bin_size, + window_size=window_size, + symmetrize=False, + ).astype(np.int64) + # Accumulate before symmetrization to preserve exact central counts and + # int64 totals across many windows. Self-spike pairs are never counted. + if result is None: + result = positive + else: + result += positive + if result is None: + raise ValueError('Correlograms require at least one observation window.') + center = result[..., 0] + result[..., 0].T + np.fill_diagonal(center, np.diag(result[..., 0])) + result[..., 0] = center + return np.dstack((result[..., 1:][..., ::-1].transpose(1, 0, 2), result)) diff --git a/phy/apps/large_recording/tests/test_statistics.py b/phy/apps/large_recording/tests/test_statistics.py new file mode 100644 index 000000000..1bee50516 --- /dev/null +++ b/phy/apps/large_recording/tests/test_statistics.py @@ -0,0 +1,43 @@ +"""Independent pair-count oracle and observation-boundary regressions.""" + +import numpy as np + +from phy.apps.large_recording.statistics import window_correlograms, window_isi + + +def test_window_isi_excludes_missing_observation_periods_and_preserves_ties(): + samples = np.array([0, 1, 1, 2, 1000, 1002], dtype=np.int64) + windows = np.array([[0, 3], [1000, 1003]], dtype=np.int64) + np.testing.assert_array_equal(window_isi(samples, windows, 1), [1, 0, 1, 2]) + + +def test_late_sample_ccg_matches_all_pairs_oracle_with_sparse_ids(): + origin = 1000 * 3600 * 30000 + samples = origin + np.array([0, 1, 30, 30, 31, 60, 300, 301, 330], dtype=np.int64) + clusters = np.array([2_000_000_000, 2, 2, 2_000_000_000, 2, 2, 2, 2_000_000_000, 2]) + windows = np.array([[origin, origin + 100], [origin + 300, origin + 400]], dtype=np.int64) + ids = [2_000_000_000, 2] + actual = window_correlograms(samples, clusters, windows, ids, 30000, 0.001, 0.004) + expected = np.zeros((2, 2, 5), dtype=np.int64) + lookup = {cluster: index for index, cluster in enumerate(ids)} + for start, end in windows: + rows = [i for i, tick in enumerate(samples) if start <= tick < end] + for index, left in enumerate(rows): + for right in rows[index + 1 :]: + delay = int(samples[right] - samples[left]) // 30 + if delay > 2: + continue + a, b = lookup[clusters[left]], lookup[clusters[right]] + expected[a, b, 2 + delay] += 1 + if a != b or delay != 0: + expected[b, a, 2 - delay] += 1 + np.testing.assert_array_equal(actual, expected) + + +def test_cross_unit_central_pairs_do_not_depend_on_tied_row_order(): + samples = np.array([0, 0, 10, 10], dtype=np.int64) + windows = np.array([[0, 20]], dtype=np.int64) + a = window_correlograms(samples, np.array([0, 1, 1, 0]), windows, [0, 1], 30000, 0.001, 0.004) + b = window_correlograms(samples, np.array([1, 0, 1, 0]), windows, [0, 1], 30000, 0.001, 0.004) + np.testing.assert_array_equal(a, b) + assert a[0, 1, 2] == 4 From 2ad713b2025db386a5a6f113c76343ce0cbb231c Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 11:40:09 +0200 Subject: [PATCH 13/53] Integrate bounded curation GUI with transactional history and evidence views --- phy/apps/large_recording/adapter.py | 364 ++++++++++++++ phy/apps/large_recording/model.py | 53 ++ phy/apps/large_recording/stability.py | 176 +++++++ phy/apps/large_recording/supervisor.py | 459 ++++++++++++++++++ .../large_recording/tests/test_adapter.py | 447 +++++++++++++++++ .../tests/test_gui_lifecycle.py | 150 ++++++ phy/apps/large_recording/views.py | 23 + phy/apps/template/gui.py | 40 +- 8 files changed, 1710 insertions(+), 2 deletions(-) create mode 100644 phy/apps/large_recording/adapter.py create mode 100644 phy/apps/large_recording/model.py create mode 100644 phy/apps/large_recording/stability.py create mode 100644 phy/apps/large_recording/supervisor.py create mode 100644 phy/apps/large_recording/tests/test_adapter.py create mode 100644 phy/apps/large_recording/tests/test_gui_lifecycle.py create mode 100644 phy/apps/large_recording/views.py diff --git a/phy/apps/large_recording/adapter.py b/phy/apps/large_recording/adapter.py new file mode 100644 index 000000000..e4d332008 --- /dev/null +++ b/phy/apps/large_recording/adapter.py @@ -0,0 +1,364 @@ +"""Manifest-gated template controller for bounded recording evidence.""" + +from copy import deepcopy +from pathlib import Path + +import numpy as np +from phylib.io.model import get_template_params +from phylib.utils import Bunch + +from phy.cluster._propositions import MergePropositionController, decode_review_mapping + +from ..base import _allocate_spike_counts, _sample_spikes_evenly +from ..template.gui import TemplateController +from .curation import BoundedSession +from .model import BoundedTemplateModel +from .statistics import window_correlograms, window_isi +from .supervisor import BoundedSupervisor +from .views import EvidenceAmplitudeView, SampledCorrelogramView, SampledISIView + + +class BoundedTemplateController(TemplateController): + gui_name = 'BoundedTemplateGUI' + # Bounded mode has its own state namespace and initial view list. Importing + # ordinary saved dock geometry would suppress the new evidence views. + default_state_path = None + default_views = ( + 'UnitStabilityView', + 'WaveformView', + 'EvidenceAmplitudeView', + 'FeatureView', + 'ProbeView', + 'SampledISIView', + 'SampledCorrelogramView', + ) + + def __init__(self, dir_path=None, model=None, **kwargs): + if model is not None: + raise ValueError( + 'Open bounded packages from their directory, without a supplied model.' + ) + self.bounded_session = BoundedSession(dir_path) + self.evidence_window_index = 0 + kwargs['enable_threading'] = False + kwargs.update(get_template_params(Path(dir_path) / 'params.py')) + kwargs.pop('dir_path', None) + super().__init__(dir_path=dir_path, **kwargs) + + def _create_model(self, dir_path=None, **kwargs): + model = BoundedTemplateModel(dir_path=dir_path, session=self.bounded_session, **kwargs) + if model.sample_rate != self.bounded_session.manifest['sample_rate']: + model.close() + raise ValueError('Bounded params sampling rate disagrees with the manifest.') + model.spike_clusters = self.bounded_session.assignments.copy() + model.metadata = deepcopy(self.bounded_session.metadata) + model.duration = self.bounded_session.manifest['num_samples'] / model.sample_rate + + def reject_save(*args, **kwargs): + raise ValueError('Save bounded curation through supervisor.save() as one transaction.') + + model.save_spike_clusters = reject_save + model.save_metadata = reject_save + model.save_spikes_subset_waveforms = reject_save + model.freeze_source() + return model + + def _cache_methods(self): + # Ordinary persistent feature caches omit the current evidence window. + # Bounded queries are already capped; evaluate them against live state. + return + + def close(self, close_model=True): + super().close(close_model=close_model) + if close_model: + self.bounded_session.close() + + def _set_supervisor(self): + session = self.bounded_session + propositions = self._load_merge_propositions() + self.supervisor = BoundedSupervisor( + spike_clusters=self.model.spike_clusters.copy(), + cluster_groups=self.model.metadata.get('group', {}), + cluster_metrics=self.cluster_metrics, + cluster_labels=self.model.metadata, + similarity=self.similarity_functions[self.similarity], + session=session, + merge_propositions=propositions, + ) + self.supervisor._validate_native() + + def _load_merge_propositions(self): + controller = super()._load_merge_propositions() + reviews = self.bounded_session.extra_documents.get('curation_review.json') + if controller is not None and reviews is not None: + source, mapping = decode_review_mapping(reviews) + if source.get('sha256') != self._merge_proposition_sha256: + raise ValueError('Committed reviews belong to different merge propositions.') + controller = MergePropositionController(controller.catalog._replace(reviews=mapping)) + return controller + + def _set_cluster_metrics(self): + super()._set_cluster_metrics() + self.cluster_metrics['full_count'] = self.get_full_count + self.cluster_metrics['evidence_count'] = lambda c: self.supervisor.n_spikes(c) + self.cluster_metrics['waveform_count'] = self.get_waveform_count + self.cluster_metrics['evidence'] = lambda c: ( + 'pending replay' if self.get_full_count(c) is None else 'sampled windows' + ) + + def _set_view_creator(self): + super()._set_view_creator() + for name in ( + 'ISIView', + 'CorrelogramView', + 'FiringRateView', + 'TraceView', + 'TraceImageView', + ): + self.view_creator.pop(name, None) + self.view_creator.pop('AmplitudeView', None) + self.view_creator['EvidenceAmplitudeView'] = self.create_evidence_amplitude_view + self.view_creator['UnitStabilityView'] = self.create_unit_stability_view + self.view_creator['SampledISIView'] = lambda: SampledISIView(cluster_stat=self._get_isi) + self.view_creator['SampledCorrelogramView'] = lambda: SampledCorrelogramView( + correlograms=self._window_correlograms, sample_rate=self.model.sample_rate + ) + + def _get_waveforms_dict(self): + functions = super()._get_waveforms_dict() + if not self.bounded_session.manifest['capabilities']['stored_waveforms']: + functions.pop('waveforms', None) + functions.pop('mean_waveforms', None) + return functions + + def create_feature_view(self): + if ( + self.model.features is None + and not self.bounded_session.manifest['capabilities']['stored_waveforms'] + ): + return + view = super().create_feature_view() + if view is not None: + view.ex_status = self._window_status() + return view + + def _source_units(self, cluster_id): + version = self.bounded_session.events + cached = getattr(self, '_lineage_cache', None) + if cached is not None and cached[0] is version: + return cached[1].get(int(cluster_id)) + units = {int(c): {int(c)} for c in self.bounded_session.unit_ids} + for event in self.bounded_session.events: + if event['operation'] == 'merge': + parents = [units.pop(c) for c in event['parents']] + units[event['target']] = ( + None if any(p is None for p in parents) else set.union(*parents) + ) + elif event['operation'] == 'threshold_split': + units.pop(event['parent']) + units.update(dict.fromkeys(event['children'])) + self._lineage_cache = version, units + return units.get(int(cluster_id)) + + def get_full_count(self, cluster_id): + units = self._source_units(cluster_id) + if units is None: + return None + if not hasattr(self, '_full_counts'): + self._full_counts = dict( + zip(self.bounded_session.unit_ids, self.bounded_session.manifest['counts']) + ) + counts = self._full_counts + return sum(int(counts[c]) for c in units) + + def get_waveform_count(self, cluster_id): + stored = self.model.spike_waveforms + if stored is None: + return 0 + if ( + not hasattr(self, '_waveform_membership_cache') + or self._waveform_membership_cache[0] is not self.bounded_session.events + ): + labels = self.supervisor.clustering.spike_clusters[stored.spike_ids] + ids, counts = np.unique(labels, return_counts=True) + self._waveform_membership_cache = self.bounded_session.events, dict(zip(ids, counts)) + return int(self._waveform_membership_cache[1].get(cluster_id, 0)) + + def get_mean_firing_rate(self, cluster_id): + count = self.get_full_count(cluster_id) + if count is None: + return None + intervals = np.asarray(self.bounded_session.manifest['valid_intervals']) + exposure = np.sum(intervals[:, 1] - intervals[:, 0]) / self.model.sample_rate + return count / exposure + + @property + def evidence_windows(self): + if not hasattr(self, '_evidence_windows'): + self._evidence_windows = np.load( + self.dir_path / self.bounded_session.manifest['windows_file'] + ) + return self._evidence_windows + + def _get_isi(self, cluster_id): + ids = self.supervisor.clustering.spikes_per_cluster.get(cluster_id, []) + samples = self.model.spike_samples[ids] + return Bunch(data=window_isi(samples, self.evidence_windows, self.model.sample_rate)) + + def _window_correlograms(self, cluster_ids, bin_size, window_size): + return window_correlograms( + self.model.spike_samples, + self.supervisor.clustering.spike_clusters, + self.evidence_windows, + cluster_ids, + self.model.sample_rate, + bin_size, + window_size, + ) + + def create_unit_stability_view(self): + from .stability import UnitStabilityView + + return UnitStabilityView(self) + + @property + def current_evidence_window(self): + return self.evidence_windows[self.evidence_window_index] + + def _window_ids(self, cluster_id=None): + start, end = self.current_evidence_window + if cluster_id is None: + first, last = np.searchsorted(self.model.spike_samples, [start, end]) + return np.arange(first, last, dtype=np.int64) + ids = self.supervisor.clustering.spikes_per_cluster.get( + cluster_id, np.array([], dtype=np.int64) + ) + times = self.model.spike_samples[ids] + first, last = np.searchsorted(times, [start, end]) + return ids[first:last] + + def _window_time(self, ids): + # Subtract int64 samples before floating conversion, even at hour 1000. + return ( + self.model.spike_samples[ids] - self.current_evidence_window[0] + ) / self.model.sample_rate + + def _get_feature_view_spike_ids(self, cluster_id=None, load_all=False): + ids = self._window_ids(cluster_id) + if self.model.features is None: + if self.model.spike_waveforms is None: + return np.array([], dtype=np.int64) + ids = np.intersect1d(ids, self.model.spike_waveforms.spike_ids) + if getattr(self.model, 'features_rows', None) is not None: + ids = np.intersect1d(ids, self.model.features_rows) + limit = self.n_spikes_features_background if cluster_id is None else self.n_spikes_features + return ids if load_all else _sample_spikes_evenly(ids, limit) + + def _get_feature_view_spike_times(self, cluster_id=None, load_all=False): + ids = self._get_feature_view_spike_ids(cluster_id, load_all=load_all) + if not len(ids): + return + start, end = self.current_evidence_window + return Bunch( + data=self._window_time(ids), + spike_ids=ids, + lim=(0.0, (end - start) / self.model.sample_rate), + ) + + def _evidence_amplitudes(self, cluster_ids, load_all=False): + active = [c for c in cluster_ids if c is not None] + eligible = [self._window_ids(c) for c in active] + counts = _allocate_spike_counts( + [len(ids) for ids in eligible], + per_cluster=None if load_all else self.n_spikes_amplitudes, + total=None if load_all else self.n_spikes_amplitudes_total, + ) + values = self.bounded_session.attributes['amplitudes.npy'].reshape(-1) + output = [] + if None in cluster_ids: + ids = self._window_ids() + ids = ids[~np.isin(self.supervisor.clustering.spike_clusters[ids], active)] + ids = _sample_spikes_evenly(ids, self.n_spikes_amplitudes_background) + ids = ids[np.isfinite(values[ids])] + output.append( + Bunch(amplitudes=values[ids], spike_ids=ids, spike_times=self._window_time(ids)) + ) + for ids, count in zip(eligible, counts): + ids = _sample_spikes_evenly(ids, int(count)) + ids = ids[np.isfinite(values[ids])] + output.append( + Bunch(amplitudes=values[ids], spike_ids=ids, spike_times=self._window_time(ids)) + ) + return output + + def create_evidence_amplitude_view(self): + array = self.bounded_session.attributes.get('amplitudes.npy') + if array is None or (array.ndim != 1 and array.shape[1:] != (1,)): + return + start, end = self.current_evidence_window + view = EvidenceAmplitudeView( + amplitudes={'source': self._evidence_amplitudes}, + amplitudes_type='source', + duration=(end - start) / self.model.sample_rate, + split_is_eligible=lambda: False, + ) + view.ex_status = self._window_status() + return view + + def _window_status(self): + start, end = self.current_evidence_window + return ( + f'Evidence window {self.evidence_window_index}: {start / self.model.sample_rate:.3f}–' + f'{end / self.model.sample_rate:.3f} s; time axis is seconds from window start; nonfinite amplitudes omitted.' + ) + + def inspect_evidence_window(self, index): + index = int(index) + if not 0 <= index < len(self.evidence_windows): + raise ValueError('Evidence window index is outside the retained plan.') + self.evidence_window_index = index + gui = getattr(self.supervisor, 'gui', None) + if gui is not None: + start, end = self.current_evidence_window + for view in gui.list_views('EvidenceAmplitudeView', 'FeatureView'): + view.ex_status = self._window_status() + if isinstance(view, EvidenceAmplitudeView): + view.duration = (end - start) / self.model.sample_rate + view.canvas.panzoom.reset() + if view.cluster_ids: + view.plot() + view.update_status() + + def create_gui(self, *args, **kwargs): + gui = super().create_gui(*args, **kwargs) + gui.setWindowTitle( + f'phy — Bounded evidence ({self.model.n_spikes:,} / ' + f'{self.bounded_session.manifest["num_spikes"]:,} spikes)' + ) + + @self.supervisor.actions.add(prompt=True, name='Split by source amplitude') + def split_by_source_amplitude(threshold): + """Split one selected unit below a source amplitude threshold (source units).""" + ids = self.supervisor.selected + if len(ids) != 1: + raise ValueError('Select one unit for a source-amplitude threshold split.') + return self.supervisor.split_source_amplitude(ids[0], float(threshold)) + + @gui.view_actions.add(prompt=True, prompt_default=lambda: self.evidence_window_index) + def inspect_evidence_window(index): + """Inspect a retained evidence window by its zero-based index.""" + self.inspect_evidence_window(index) + + split_action = self.supervisor.actions.get('split') + if split_action is not None: + split_action.setEnabled(False) + split_action.setToolTip( + 'Selected-row splits cannot assign unseen source spikes; use a source-amplitude predicate.' + ) + predicate_action = self.supervisor.actions.get('Split by source amplitude') + if predicate_action is not None: + predicate_action.setEnabled( + 'amplitudes.npy' in self.bounded_session.capabilities['predicate_split_attributes'] + ) + + return gui diff --git a/phy/apps/large_recording/model.py b/phy/apps/large_recording/model.py new file mode 100644 index 000000000..cc0bf62b3 --- /dev/null +++ b/phy/apps/large_recording/model.py @@ -0,0 +1,53 @@ +"""Bounded template loading without dense caches indexed by cluster namespace.""" + +from types import MappingProxyType + +import numpy as np +from phylib.io.model import TemplateModel + + +class BoundedTemplateModel(TemplateModel): + """Load committed assignments and original templates as separate concepts. + + The controller derives live unit evidence from Supervisor assignments. + phylib's eager merged-cluster waveform cache allocates by the maximum + absolute ID and does not track subsequent GUI edits; bounded mode does not + expose that cache as current scientific evidence. + """ + + def __init__(self, *args, session, **kwargs): + self._bounded_session = session + super().__init__(*args, **kwargs) + self.sparse_clusters = None + + def freeze_source(self): + """Prevent public model edits from bypassing semantic curation.""" + names = set() + for name, value in vars(self).items(): + if not name.startswith('_') and isinstance(value, np.ndarray): + value.flags.writeable = False + names.add(name) + self.metadata = MappingProxyType( + {name: MappingProxyType(values) for name, values in self.metadata.items()} + ) + names.update( + ('metadata', 'save_spike_clusters', 'save_metadata', 'save_spikes_subset_waveforms') + ) + self._protected_source_names = frozenset(names) + + def __setattr__(self, name, value): + if name in getattr(self, '_protected_source_names', ()): + raise ValueError('Bounded model source is read-only; use semantic curation commands.') + super().__setattr__(name, value) + + def _load_spike_clusters(self): + return self._bounded_session.assignments.copy() + + def get_merge_map(self): + return {}, np.array([], dtype=np.int64) + + def cluster_waveforms(self): + return None + + def get_cluster_mean_waveforms(self, *args, **kwargs): + raise ValueError('Use the controller waveform/template providers for live bounded units.') diff --git a/phy/apps/large_recording/stability.py b/phy/apps/large_recording/stability.py new file mode 100644 index 000000000..131268fd1 --- /dev/null +++ b/phy/apps/large_recording/stability.py @@ -0,0 +1,176 @@ +"""Selected-unit full-duration evidence with explicit acquisition exposure.""" + +import numpy as np +from phylib.utils import Bunch, connect, unconnect + +from phy.cluster.views import ManualClusteringView +from phy.plot.plot import PlotCanvasMpl + + +class UnitStabilityView(ManualClusteringView): + """Full counts/rates, available source trends, gaps and retained evidence windows.""" + + plot_canvas_class = PlotCanvasMpl + max_n_clusters = 1 + _default_position = 'right' + ex_status = 'Full-duration evidence; sampling cannot establish chronic unit identity.' + + def __init__(self, controller): + super().__init__() + self.controller = controller + self.canvas.subplots(3, 1, sharex=True) + self._summary_arrays = {} + + def _array(self, name): + if name not in self._summary_arrays: + self._summary_arrays[name] = np.load(self.controller.dir_path / name, mmap_mode='r') + return self._summary_arrays[name] + + def get_data(self, cluster_id): + controller = self.controller + session = getattr(controller, 'bounded_session', None) + if session is None: + # Optional ordinary-data view: only the selected cluster is evaluated. + times = controller.get_spike_times(cluster_id) + edges = np.linspace(0, controller.model.duration, 101) + counts, _ = np.histogram(times, edges) + exposure = np.diff(edges) + return Bunch( + edges=edges, + counts=counts, + exposure=exposure, + windows=[], + intervals=[[0, controller.model.duration]], + trends={}, + provenance='Loaded recording; continuous acquisition assumed.', + ) + manifest = session.manifest + summary = manifest.get('summaries', manifest) + edges = self._array(summary['edges_file']) / controller.model.sample_rate + exposure = self._array(summary['exposure_file']) + units = controller._source_units(cluster_id) + if units is None: + return Bunch( + edges=edges, + counts=None, + exposure=exposure, + windows=[], + intervals=[], + trends={}, + provenance='Split evidence pending full-data replay.', + ) + lookup = {int(c): i for i, c in enumerate(session.unit_ids)} + rows = [lookup[c] for c in units] + # Bound temporaries by one unit's summary row, including merged units. + count_grid = self._array(summary['counts_file']) + counts = np.zeros(len(exposure), dtype=np.int64) + for row in rows: + counts += count_grid[row] + trends = {} + for attribute in ('amplitude', 'depth'): + sum_file, count_file = f'{attribute}_sum_file', f'{attribute}_count_file' + if sum_file not in summary: + continue + total, valid = np.zeros(len(exposure)), np.zeros(len(exposure), dtype=np.int64) + for row in rows: + total += self._array(summary[sum_file])[row] + valid += self._array(summary[count_file])[row] + mean = np.full(len(exposure), np.nan) + np.divide(total, valid, out=mean, where=valid > 0) + trends[attribute] = mean + return Bunch( + edges=edges, + counts=counts, + exposure=exposure, + trends=trends, + windows=controller.evidence_windows / controller.model.sample_rate, + intervals=np.asarray(manifest['valid_intervals']) / controller.model.sample_rate, + provenance='Complete source sorting; exact counts and finite-value means.', + ) + + def plot(self, **kwargs): + axes = list(self.canvas.iter_ax()) + for ax in axes: + ax.clear() + session = getattr(self.controller, 'bounded_session', None) + if not self.cluster_ids: + axes[0].text( + 0.02, + 0.6, + 'Select a unit to inspect full-duration evidence.', + transform=axes[0].transAxes, + ) + else: + cluster_id = self.cluster_ids[0] + data = self.get_data(cluster_id) + if data.counts is None: + axes[0].text(0.02, 0.6, data.provenance, transform=axes[0].transAxes) + else: + rates = np.full(len(data.exposure), np.nan) + np.divide(data.counts, data.exposure, out=rates, where=data.exposure > 0) + x = (data.edges[:-1] + data.edges[1:]) / 7200 + axes[0].plot(x, rates) + for ax, attribute in zip(axes[1:], ('amplitude', 'depth')): + if attribute in data.trends: + ax.plot(x, data.trends[attribute]) + else: + ax.text( + 0.02, + 0.6, + f'{attribute.title()} measurement unavailable.', + transform=ax.transAxes, + ) + for ax in axes: + for start, end in data.windows: + ax.axvspan(start / 3600, end / 3600, color='cyan', alpha=0.15) + previous = 0 + for start, end in data.intervals: + if start > previous: + ax.axvspan(previous / 3600, start / 3600, color='gray', alpha=0.4) + previous = end + if previous < data.edges[-1]: + ax.axvspan(previous / 3600, data.edges[-1] / 3600, color='gray', alpha=0.4) + axes[0].set_title(f'Unit {cluster_id} — {data.provenance}', fontsize=9) + axes[0].set_ylabel('Rate (Hz)') + axes[1].set_ylabel('Mean amplitude\n(source units)') + axes[2].set_ylabel('Mean depth\n(source units)') + axes[2].set_xlabel('Elapsed acquisition clock (hours)') + if session is not None: + missing = [ + c for c, n in zip(session.unit_ids, session.manifest['bounded_counts']) if not n + ] + if missing: + axes[2].text( + 0.02, + -0.42, + f'{len(missing)} source units without evidence: ' + f'{", ".join(map(str, missing[:12]))}' + (' …' if len(missing) > 12 else ''), + transform=axes[2].transAxes, + fontsize=8, + ) + self.canvas.figure.tight_layout() + self.canvas.update() + + def on_select(self, cluster_ids=None, **kwargs): + self.cluster_ids = tuple(cluster_ids or ())[:1] + self.plot(**kwargs) + + def attach(self, gui): + super().attach(gui) + + @self.actions.add(prompt=True) + def show_source_unit(cluster_id): + """Inspect a full source unit, including one without sampled evidence.""" + session = getattr(self.controller, 'bounded_session', None) + if session is not None and int(cluster_id) not in session.unit_ids: + raise ValueError('Unknown source unit ID.') + self.on_select([int(cluster_id)]) + + @connect(event='bounded_state_changed', sender=self.controller.supervisor) + def on_state(sender): + self.plot() + + @connect(event='close_view', sender=self) + def on_close(sender, *args): + unconnect(on_state, on_close) + self._summary_arrays.clear() diff --git a/phy/apps/large_recording/supervisor.py b/phy/apps/large_recording/supervisor.py new file mode 100644 index 000000000..a5765232f --- /dev/null +++ b/phy/apps/large_recording/supervisor.py @@ -0,0 +1,459 @@ +"""Guarded native commands paired with semantic state, history and checkpoints.""" + +from contextlib import contextmanager +from copy import deepcopy +from functools import wraps +from types import MappingProxyType + +import numpy as np +from phylib.utils import emit + +from phy.cluster._history import History +from phy.cluster._utils import ClusterMeta +from phy.cluster.clustering import Clustering +from phy.cluster.supervisor import Supervisor + +from .curation import evaluate_predicate, interpret_events + + +class MutationPolicy: + """Only semantic commands may mutate native bounded state.""" + + def __init__(self): + self.depth = 0 + + def require(self): + if not self.depth: + raise ValueError( + 'Bounded curation requires a semantic command. Use supervisor.merge(), ' + 'supervisor.label(), or split_source_amplitude(); arbitrary splits are unavailable.' + ) + + @contextmanager + def command(self): + self.depth += 1 + try: + yield + finally: + self.depth -= 1 + + +class GuardedClustering(Clustering): + def __init__(self, *args, policy, **kwargs): + self.policy = policy + super().__init__(*args, **kwargs) + + @property + def spike_clusters(self): + result = self._spike_clusters.view() + result.flags.writeable = bool(self.policy.depth) + return result + + @property + def cluster_ids(self): + result = self._cluster_ids.view() + result.flags.writeable = False + return result + + @property + def spikes_per_cluster(self): + return MappingProxyType(self._spikes_per_cluster) + + def _update_cluster_ids(self, *args, **kwargs): + super()._update_cluster_ids(*args, **kwargs) + for ids in self._spikes_per_cluster.values(): + ids.flags.writeable = False + + def merge(self, *args, **kwargs): + self.policy.require() + return super().merge(*args, **kwargs) + + def assign(self, *args, **kwargs): + self.policy.require() + return super().assign(*args, **kwargs) + + def reset(self): + self.policy.require() + return super().reset() + + def undo(self): + self.policy.require() + return super().undo() + + def redo(self): + self.policy.require() + return super().redo() + + +class GuardedMeta(ClusterMeta): + def __init__(self, policy): + self.policy = policy + super().__init__() + + def set(self, *args, **kwargs): + self.policy.require() + return super().set(*args, **kwargs) + + def add_field(self, *args, **kwargs): + self.policy.require() + return super().add_field(*args, **kwargs) + + def from_dict(self, *args, **kwargs): + self.policy.require() + return super().from_dict(*args, **kwargs) + + def undo(self): + self.policy.require() + return super().undo() + + def redo(self): + self.policy.require() + return super().redo() + + +class SessionHistory(History): + def __init__(self, session): + self.session = session + super().__init__(session.journal_state()) + + def capture(self): + self.add(self.session.journal_state()) + + def undo(self): + self.back() + self.session.restore_journal(self.current_item) + + def redo(self): + self.forward() + self.session.restore_journal(self.current_item) + + +def semantic_command(method): + @wraps(method) + def execute(self, *args, **kwargs): + with self._transaction(): + return method(self, *args, **kwargs) + + return execute + + +class BoundedSupervisor(Supervisor): + """Native UI/history operations paired with a validated semantic journal.""" + + def __init__(self, *args, session, **kwargs): + self.session = session + self.policy = MutationPolicy() + self.select_actions = None + self.cluster_view = None + self.similarity_view = None + + def clustering_factory(*args, **kwargs): + return GuardedClustering(*args, policy=self.policy, **kwargs) + + def meta_factory(groups, labels): + meta = GuardedMeta(self.policy) + data = {} + for field, values in labels.items(): + for cluster, value in values.items(): + data.setdefault(cluster, {})[field] = value + with self.policy.command(): + meta.add_field('group') + meta.from_dict(data) + return meta + + # Generation state supersedes disposable clustering caches. + kwargs['context'] = None + kwargs['new_cluster_id'] = session.next_cluster_id + kwargs['clustering_factory'] = clustering_factory + kwargs['cluster_meta_factory'] = meta_factory + super().__init__(*args, **kwargs) + self.session_history = SessionHistory(session) + + @contextmanager + def _transaction(self): + """Roll native and semantic state back if an observer or command fails.""" + clustering = self.clustering + arrays = ( + clustering._spike_clusters.copy(), + dict(clustering._spikes_per_cluster), + clustering._cluster_ids.copy(), + ) + data, fields = deepcopy(self.cluster_meta._data), dict(self.cluster_meta._fields) + histories = [ + clustering._undo_stack, + self.cluster_meta._undo_stack, + self._global_history, + self.session_history, + ] + if self.merge_propositions is not None: + histories.append(self.merge_propositions._history) + history_states = [(list(h._history), h._index) for h in histories] + journal, selection, dirty = ( + self.session.journal_state(), + self.selection.snapshot(), + self._is_dirty, + ) + propositions = ( + self.merge_propositions.snapshot() if self.merge_propositions is not None else None + ) + workflow, columns = self._workflow_context(), list(self.columns) + try: + yield + except Exception: + clustering._spike_clusters, clustering._spikes_per_cluster, clustering._cluster_ids = ( + arrays + ) + self.cluster_meta._data, self.cluster_meta._fields = data, fields + for history, (items, index) in zip(histories, history_states): + history._history, history._index = items, index + self.session.restore_journal(journal) + self.session.next_cluster_id = max( + self.session.next_cluster_id, clustering.new_cluster_id() + ) + self.selection.restore(selection) + if propositions is not None: + self.merge_propositions.restore(propositions) + self._is_dirty = dirty + self.columns = columns + self._lineage_cache = None + if self.gui is not None: + self._reset_cluster_view() + self._restore_history_context( + selection, + { + 'mode': 'merge' if selection.is_merge_mode else 'post_merge', + 'tables': workflow, + }, + 'undo', + ) + self._refresh_bounded() + self._update_save_feedback() + raise + + def _require_capability(self, name): + if not self.session.manifest.get('capabilities', {}).get(name, False): + raise ValueError(f'This bounded package does not allow {name} operations.') + + def get_cluster_info(self, cluster_id, exclude=()): + info = super().get_cluster_info(cluster_id, exclude=exclude) + # Producer TSV labels may use metric names. They must not overwrite + # authoritative complete-sorting counts/rates with inherited values. + for name in ( + 'n_spikes', + 'fr', + 'full_count', + 'evidence_count', + 'waveform_count', + 'evidence', + ): + if name not in exclude and name in self.cluster_metrics: + info[name] = self.cluster_metrics[name](cluster_id) + return info + + def _select_after_merge(self, *args, **kwargs): + if self.gui is not None: + return super()._select_after_merge(*args, **kwargs) + + def _select_after_split(self, *args, **kwargs): + if self.gui is not None: + return super()._select_after_split(*args, **kwargs) + + def _restore_history_context(self, *args, **kwargs): + if self.gui is not None: + return super()._restore_history_context(*args, **kwargs) + + def _reset_cluster_view(self, *args, **kwargs): + if self.gui is not None: + return super()._reset_cluster_view(*args, **kwargs) + + def _workflow_context(self): + return super()._workflow_context() if self.gui is not None else {} + + def _validate_native(self, metadata=True): + if not np.array_equal(self.clustering.spike_clusters, self.session.assignments): + raise ValueError('Native assignments disagree with the bounded semantic command.') + if metadata: + active, expected, _ = interpret_events( + self.session.unit_ids, self.session.base_metadata, self.session.events + ) + for field in set(self.cluster_meta.fields) | set(expected): + for cluster in active: + actual = ( + self.cluster_meta.get(field, cluster) + if field in self.cluster_meta.fields + else None + ) + if actual != expected.get(field, {}).get(cluster): + raise ValueError( + 'Native metadata disagrees with the bounded semantic command.' + ) + + def _synchronize_metadata(self): + # Native ClusterMeta.undo does not retain nonstacked inherited merge + # labels. The semantic projection is authoritative in bounded mode. + data = {} + for field, values in self.session.metadata.items(): + if field not in self.cluster_meta.fields: + with self.policy.command(): + self.cluster_meta.add_field(field) + for cluster, value in values.items(): + data.setdefault(cluster, {})[field] = value + self.cluster_meta._data = data + + def _refresh_bounded(self): + if self.gui is not None: + data = self.cluster_info + self.cluster_view.change(data) + self.similarity_view.change(data) + if self.merge_view is not None: + self.merge_view.change(data) + emit('bounded_state_changed', self) + + def _capture(self): + self._validate_native() + self.session_history.capture() + self._global_history.add_to_current_action(self.session_history) + self._is_dirty = True + self._update_save_feedback() + self._synchronize_metadata() + self._refresh_bounded() + + @semantic_command + def merge(self, cluster_ids=None, to=None): + self._require_capability('merge') + parents = list(self.selected if cluster_ids is None else cluster_ids) + if len(parents) < 2: + return + target = max(self.clustering.new_cluster_id(), self.session.next_cluster_id) + target = target if to is None else int(to) + self.session.preflight_merge(parents, target) + with self.policy.command(): + out = super().merge(cluster_ids=cluster_ids, to=target) + if out is None: + return + resolved = { + field: self.cluster_meta.get(field, target) for field in self.cluster_meta.fields + } + self.session.record_merge(parents, target, metadata=resolved) + self._capture() + return out + + @semantic_command + def label(self, name, value, cluster_ids=None): + self._require_capability('label') + if name in ( + 'n_spikes', + 'fr', + 'full_count', + 'evidence_count', + 'waveform_count', + 'evidence', + ): + raise ValueError('Bounded count/rate/evidence columns are read-only metrics.') + ids = list(self.selected if cluster_ids is None else np.atleast_1d(cluster_ids)) + if not ids or self.selection.state.is_merge_mode: + return + # Preflight against a copy before touching native metadata. + before = self.session.snapshot() + self.session.record_label(name, ids, value) + self.session.restore(before) + with self.policy.command(): + super().label(name, value, cluster_ids=ids) + self.session.record_label(name, ids, value) + self._capture() + + def split(self, *args, **kwargs): + raise ValueError( + 'Lasso, feature and waveform splits cannot be replayed on unseen spikes. ' + 'Use Split by source amplitude for a full-source scalar predicate.' + ) + + @semantic_command + def split_source_amplitude(self, cluster_id, threshold): + if 'amplitudes.npy' not in self.session.manifest.get('capabilities', {}).get( + 'predicate_split_attributes', [] + ): + raise ValueError('This package does not support source-amplitude predicate splits.') + if self.selection.state.is_merge_mode: + raise ValueError('Leave Merge mode before splitting by source amplitude.') + if 'amplitudes.npy' not in self.session.attributes: + raise ValueError('The source has no scalar per-spike amplitudes.') + predicate = { + 'attribute': 'amplitudes.npy', + 'operator': '<', + 'threshold': float(threshold), + 'nonfinite': 'keep', + } + ids = self.clustering.spikes_per_cluster.get(int(cluster_id), np.array([], dtype=np.int64)) + selected = ids[ + evaluate_predicate(self.session.attributes['amplitudes.npy'][ids], predicate) + ] + if not len(selected) or len(selected) == len(ids): + raise ValueError('Both sides of the threshold must have evidence spikes.') + selected_id = max(self.clustering.new_cluster_id(), self.session.next_cluster_id) + remainder_id = selected_id + 1 + self.clustering._new_cluster_id = selected_id + metadata = { + field: { + child: self.cluster_meta.get(field, cluster_id) + for child in (selected_id, remainder_id) + } + for field in self.cluster_meta.fields + } + before = self.session.snapshot() + self.session.record_threshold_split( + int(cluster_id), [remainder_id, selected_id], predicate, metadata=metadata + ) + self.session.restore(before) + with self.policy.command(): + out = Supervisor.split(self, selected) + self.session.record_threshold_split( + int(cluster_id), [remainder_id, selected_id], predicate, metadata=metadata + ) + self._capture() + return out + + @semantic_command + def undo(self): + with self.policy.command(): + super().undo() + self._after_history() + + @semantic_command + def redo(self): + with self.policy.command(): + super().redo() + self._after_history() + + def _after_history(self): + self._validate_native(metadata=False) + # Never reuse allocated IDs after branching or restoring a snapshot. + self.session.next_cluster_id = max( + self.session.next_cluster_id, self.clustering.new_cluster_id() + ) + self._is_dirty = True + self._update_save_feedback() + self._synchronize_metadata() + self._refresh_bounded() + + def save(self): + self._validate_native() + documents = None + if self.merge_propositions is not None: + from .source import hash_file + + documents = { + 'curation_review.json': self.merge_propositions.catalog.review_mapping( + source_sha256=hash_file(self.session.path / 'curation.json') + ) + } + self.session.save( + assignments=self.clustering.spike_clusters, + metadata=self.session.metadata, + next_cluster_id=max(self.session.next_cluster_id, self.clustering.new_cluster_id()), + extra_documents=documents, + ) + if self.merge_propositions is not None: + self.merge_propositions.mark_saved() + self._is_dirty = False + self._update_save_feedback(saved=True) diff --git a/phy/apps/large_recording/tests/test_adapter.py b/phy/apps/large_recording/tests/test_adapter.py new file mode 100644 index 000000000..937d45433 --- /dev/null +++ b/phy/apps/large_recording/tests/test_adapter.py @@ -0,0 +1,447 @@ +"""Bounded GUI correctness and ordinary-controller isolation.""" + +import json + +import numpy as np +import pytest +from click.testing import CliRunner +from phylib.utils import connect, unconnect + +from phy.apps import phycli +from phy.apps.large_recording.adapter import BoundedTemplateController +from phy.apps.large_recording.curation import BoundedSession +from phy.apps.large_recording.prepare import prepare_large +from phy.apps.large_recording.replay import apply_curation +from phy.apps.large_recording.tests.test_source import make_sorting +from phy.apps.template.gui import TemplateController + + +def make_controller(tmp_path, sparse=False): + params = make_gui_sorting(tmp_path / 'source') + output = prepare_large( + params, + tmp_path / 'bounded', + window_seconds=3 if sparse else 20, + stratum_seconds=20, + max_spikes=5 if sparse else 100, + bin_seconds=5, + batch_size=2, + ) + controller = TemplateController( + dir_path=output, + config_dir=tmp_path / 'config', + plugins=[], + enable_threading=False, + clear_cache=True, + ) + return params, controller + + +def make_gui_sorting(path): + params = make_sorting(path) + times = np.load(path / 'spike_times.npy') + np.save(path / 'spike_times.npy', times * 30000) + params.write_text( + params.read_text() + .replace('sample_rate = 1.0', 'sample_rate = 30000.0') + .replace('num_samples = 20', 'num_samples = 600000') + ) + return params + + +def test_manifest_factory_reserves_complete_ids_and_guards_mutations(tmp_path): + _, controller = make_controller(tmp_path, sparse=True) + try: + assert isinstance(controller, BoundedTemplateController) + with pytest.raises(ValueError): + controller.model.spike_clusters[0] = 123 + with pytest.raises(ValueError): + controller.model.spike_clusters = np.array([123]) + with pytest.raises(TypeError): + controller.model.metadata['group'][0] = 'noise' + supervisor = controller.supervisor + assert 99 not in supervisor.clustering.cluster_ids + assert supervisor.clustering.new_cluster_id() == 100 + assert controller.get_full_count(0) == 4 + assert controller.get_mean_firing_rate(0) == 0.2 + for operation in ( + lambda: supervisor.clustering.merge([0, 1]), + lambda: supervisor.clustering.assign([0]), + lambda: supervisor.clustering.split([0]), + supervisor.clustering.undo, + supervisor.clustering.redo, + supervisor.clustering.reset, + lambda: supervisor.cluster_meta.set('group', [0], 'noise', add_to_stack=False), + lambda: supervisor.cluster_meta.from_dict({0: {'group': 'noise'}}), + lambda: controller.model.save_spike_clusters(supervisor.clustering.spike_clusters), + lambda: controller.model.save_metadata('group', {0: 'noise'}), + lambda: supervisor.split([0]), + ): + with pytest.raises(ValueError): + operation() + with pytest.raises(ValueError): + supervisor.clustering.spike_clusters[0] = 8 + assert not controller.bounded_session.events + with pytest.raises(ValueError): + supervisor.cluster_meta.add_field('group', 'noise') + with pytest.raises(TypeError): + supervisor.clustering.spikes_per_cluster[0] = np.array([0]) + with pytest.raises(ValueError): + supervisor.clustering.spikes_per_cluster[0][0] = 1 + assert 'CorrelogramView' not in controller.view_creator + assert 'FiringRateView' not in controller.view_creator + finally: + controller.close() + + +def test_loader_and_native_history_do_not_allocate_by_sparse_unit_id(qtbot, tmp_path): + params = make_gui_sorting(tmp_path / 'source') + labels = np.load(params.parent / 'spike_clusters.npy').astype(np.int64) + labels[labels == 99] = 2_000_000_000 + np.save(params.parent / 'spike_clusters.npy', labels) + (params.parent / 'cluster_group.tsv').write_text( + 'cluster_id\tgroup\n0\tgood\n1\tmua\n2\tgood\n2000000000\tnoise\n' + ) + output = prepare_large(params, tmp_path / 'bounded', window_seconds=20, stratum_seconds=20) + controller = TemplateController(dir_path=output, config_dir=tmp_path / 'config', plugins=[]) + try: + assert controller.model.sparse_clusters is None + first = controller.supervisor.merge([0, 1]) + assert first.added == [2_000_000_001] + controller.supervisor.merge([2, 2_000_000_001]) + controller.supervisor.undo() + assert 2_000_000_001 in controller.supervisor.clustering.cluster_ids + values = controller._window_correlograms([2, 2_000_000_001], 0.001, 0.004) + assert values.shape == (2, 2, 5) + controller.supervisor.save() + finally: + controller.close() + reopened = TemplateController(dir_path=output, config_dir=tmp_path / 'config', plugins=[]) + try: + assert 2_000_000_001 in reopened.model.cluster_ids + assert reopened.model.sparse_clusters is None + finally: + reopened.close() + + +def test_merge_label_history_save_reopen_replay_regenerate(tmp_path): + params, controller = make_controller(tmp_path) + path = controller.dir_path + try: + supervisor = controller.supervisor + original_file = (path / 'spike_clusters.npy').read_bytes() + up = supervisor.merge([0, 1]) + assert up.added == [100] + assert controller.get_full_count(100) == 7 + supervisor.label('group', 'noise', [100]) + supervisor.undo() + assert controller.bounded_session.metadata['group'][100] == 'good' + assert supervisor.cluster_meta.get('group', 100) == 'good' + supervisor.redo() + assert controller.bounded_session.metadata['group'][100] == 'noise' + supervisor.undo() + supervisor.undo() + np.testing.assert_array_equal( + supervisor.clustering.spike_clusters, controller.bounded_session.base_assignments + ) + supervisor.merge([1, 2]) + assert supervisor.clustering.new_cluster_id() == 102 + supervisor.label('quality', 'reviewed', [101]) + supervisor.save() + assert not supervisor.is_dirty() + assert (path / 'spike_clusters.npy').read_bytes() == original_file + expected = supervisor.clustering.spike_clusters.copy() + finally: + controller.close() + reopened = TemplateController( + dir_path=path, config_dir=tmp_path / 'config', plugins=[], enable_threading=False + ) + try: + np.testing.assert_array_equal(reopened.supervisor.clustering.spike_clusters, expected) + assert reopened.supervisor.clustering.new_cluster_id() == 102 + assert reopened.supervisor.cluster_meta.get('quality', 101) == 'reviewed' + assert reopened.supervisor._global_history.current_position == 0 + finally: + reopened.close() + output = apply_curation(params, path, tmp_path / 'curated', batch_size=2) + source = np.load(params.parent / 'spike_clusters.npy') + oracle = source.copy() + oracle[np.isin(source, [1, 2])] = 101 + np.testing.assert_array_equal(np.load(output / 'spike_clusters.npy'), oracle) + regenerated = prepare_large( + output / 'params.py', + tmp_path / 'regenerated', + window_seconds=20, + stratum_seconds=20, + bin_seconds=5, + ) + assert BoundedSession(regenerated).unit_ids == [0, 99, 101] + + +def test_source_threshold_replays_every_spike_and_full_metrics_pending(tmp_path): + params, controller = make_controller(tmp_path) + try: + supervisor = controller.supervisor + up = supervisor.split_source_amplitude(0, 4) + assert set(up.added) == {100, 101} + assert controller.get_full_count(100) is None + assert controller.get_mean_firing_rate(101) is None + supervisor.undo() + assert controller.get_full_count(0) == 4 + supervisor.redo() + supervisor.save() + output = apply_curation(params, controller.dir_path, tmp_path / 'curated', batch_size=2) + source = np.load(params.parent / 'spike_clusters.npy') + amplitudes = np.load(params.parent / 'amplitudes.npy') + oracle = source.copy() + oracle[(source == 0) & (amplitudes < 4)] = 100 + oracle[(source == 0) & ~(amplitudes < 4)] = 101 + np.testing.assert_array_equal(np.load(output / 'spike_clusters.npy'), oracle) + finally: + controller.close() + + +def test_failed_save_leaves_dirty_previous_checkpoint(tmp_path, monkeypatch): + _, controller = make_controller(tmp_path) + try: + supervisor = controller.supervisor + supervisor.merge([0, 1]) + supervisor.save() + supervisor.label('group', 'noise', [100]) + from phy.apps.large_recording import curation + + original = curation._write_json + + def fail(path, value): + if path.name == 'journal.json': + raise OSError('interrupted') + return original(path, value) + + monkeypatch.setattr(curation, '_write_json', fail) + with pytest.raises(OSError, match='interrupted'): + supervisor.save() + assert supervisor.is_dirty() + assert BoundedSession(controller.dir_path).metadata['group'][100] == 'good' + finally: + controller.close() + + +def test_standard_controller_retains_existing_path_and_save_format(qtbot, tmp_path): + params = make_gui_sorting(tmp_path / 'ordinary') + controller = TemplateController( + dir_path=params.parent, + config_dir=tmp_path / 'config', + plugins=[], + enable_threading=False, + sample_rate=30000, + n_channels_dat=3, + dtype='int16', + ) + gui = controller.create_gui(default_views=[], do_prompt_save=False) + try: + assert type(controller) is TemplateController + assert controller.gui_name == 'TemplateGUI' + assert controller.default_views[0] == 'WaveformView' + assert 'FiringRateView' in controller.view_creator + up = controller.supervisor.merge([0, 1]) + controller.supervisor.save() + assert up.added == [100] + assert not (params.parent / '.phy-curation').exists() + assert not (params.parent / '_phy_curation_manifest.json').exists() + assert 100 in np.load(params.parent / 'spike_clusters.npy') + finally: + gui.close() + controller.close() + + +def test_malformed_manifest_fails_before_model_loading(tmp_path): + params = make_sorting(tmp_path / 'ordinary') + (params.parent / '_phy_curation_manifest.json').write_text(json.dumps({'format_version': 99})) + with pytest.raises(ValueError, match='Unsupported'): + TemplateController(dir_path=params.parent, plugins=[]) + + +def test_cli_preparation_and_replay(tmp_path): + params = make_sorting(tmp_path / 'source') + runner = CliRunner() + output = tmp_path / 'bounded' + result = runner.invoke( + phycli, + [ + 'prepare-large', + str(params), + str(output), + '--window-seconds', + '20', + '--stratum-seconds', + '20', + '--bin-seconds', + '5', + '--batch-size', + '2', + ], + ) + assert result.exit_code == 0, result.output + session = BoundedSession(output) + session.record_merge([0, 1], 100, {'group': 'good'}) + session.save() + result = runner.invoke( + phycli, + [ + 'apply-curation', + str(params), + str(output), + str(tmp_path / 'curated'), + '--batch-size', + '2', + ], + ) + assert result.exit_code == 0, result.output + + +def test_stability_gui_and_exact_trends(qtbot, tmp_path): + _, controller = make_controller(tmp_path, sparse=True) + gui = controller.create_gui(default_views=['UnitStabilityView'], do_prompt_save=False) + try: + assert 'Bounded evidence' in gui.windowTitle() + view = gui.list_views('UnitStabilityView')[0] + data = view.get_data(0) + assert data.counts.sum() == 4 + np.testing.assert_allclose(data.trends['amplitude'], [1.5, np.nan, 6, 9], equal_nan=True) + view.on_select([99]) # Unit absent from evidence still has full-duration counts. + assert view.get_data(99).counts.sum() == 2 + controller.supervisor.merge([0, 1]) + controller.supervisor.block() + assert view.get_data(100).counts.sum() == 7 + finally: + gui.close() + controller.close() + + +def test_observer_mutation_rolls_back_native_and_semantic_state(tmp_path): + _, controller = make_controller(tmp_path) + supervisor = controller.supervisor + once = [] + + @connect(event='cluster', sender=supervisor.clustering) + def mutate(sender, up): + if not once: + once.append(True) + sender.assign([0]) + + try: + with pytest.raises(ValueError, match='Native assignments'): + supervisor.merge([0, 1]) + np.testing.assert_array_equal( + supervisor.clustering.spike_clusters, controller.bounded_session.base_assignments + ) + assert not controller.bounded_session.events + assert supervisor._global_history.current_position == 0 + assert not supervisor.is_dirty() + finally: + unconnect(mutate) + controller.close() + + +def test_evidence_navigation_never_reuses_old_feature_cache(tmp_path): + _, controller = make_controller(tmp_path, sparse=True) + try: + first = controller._get_features(0, channel_ids=[0, 1], load_all=True) + assert first.spike_ids.tolist() == [0, 3] + controller.inspect_evidence_window(1) + assert not controller._get_feature_view_spike_ids(0, load_all=True).size + assert not controller._get_features(0, channel_ids=[0, 1], load_all=True) + finally: + controller.close() + + +def test_late_clock_evidence_preserves_submillisecond_positions(tmp_path): + params = make_gui_sorting(tmp_path / 'source') + origin = 1000 * 3600 * 30000 + times = np.load(params.parent / 'spike_times.npy') + origin + times[1:4] = origin + np.array([30, 31, 60]) + np.save(params.parent / 'spike_times.npy', times) + params.write_text( + params.read_text().replace('num_samples = 600000', f'num_samples = {origin + 600000}') + + f'valid_intervals = [[{origin}, {origin + 600000}]]\n' + ) + output = prepare_large( + params, tmp_path / 'bounded', window_seconds=20, stratum_seconds=20, bin_seconds=3600 + ) + controller = TemplateController(dir_path=output, config_dir=tmp_path / 'config', plugins=[]) + try: + positions = controller._window_time(np.array([1, 2])) + assert positions[1] - positions[0] == pytest.approx(1 / 30000) + assert np.float32(positions[0]) != np.float32(positions[1]) + finally: + controller.close() + + +def test_empty_window_and_nonfinite_amplitude_measurements(qtbot, tmp_path): + _, controller = make_controller(tmp_path, sparse=True) + view = controller.create_evidence_amplitude_view() + try: + controller.inspect_evidence_window(1) + view.on_select([0]) + assert view.data_bounds == (0, 0, view.duration, 1) + assert all(not len(b.amplitudes) for b in view._displayed_bunchs) + finally: + view.canvas.close() + controller.close() + + +def test_proposition_reviews_checkpoint_and_failed_review_history(tmp_path): + from phy.cluster._propositions import MergePropositionController, decode_curation_mapping + + _, controller = make_controller(tmp_path) + supervisor = controller.supervisor + mapping = {'format_version': '2', 'unit_ids': [0, 1, 2, 99], 'merges': [{'unit_ids': [0, 1]}]} + producer = controller.dir_path / 'curation.json' + producer.write_text(json.dumps(mapping)) + supervisor.merge_propositions = MergePropositionController(decode_curation_mapping(mapping)) + key = supervisor.merge_propositions.catalog.propositions[0].key + try: + with pytest.raises(RuntimeError, match='observer'), supervisor._transaction(): + supervisor.merge_propositions.accept(key, [0, 1], 100) + raise RuntimeError('observer') + assert supervisor.merge_propositions._history.current_position == 0 + assert not supervisor.merge_propositions.catalog.reviews + supervisor.merge_propositions.reject(key) + supervisor.save() + controller.close() + reopened = TemplateController( + dir_path=producer.parent, config_dir=tmp_path / 'config', plugins=[] + ) + try: + assert ( + reopened.supervisor.merge_propositions.catalog.status_for(key).value == 'rejected' + ) + assert not reopened.supervisor.is_dirty() + finally: + reopened.close() + finally: + controller.close() + + +def test_nonfinite_source_amplitudes_are_omitted_from_plots_and_kept_in_replay(qtbot, tmp_path): + params = make_gui_sorting(tmp_path / 'source') + amplitudes = np.load(params.parent / 'amplitudes.npy') + amplitudes[3] = np.inf + amplitudes[6] = np.nan + np.save(params.parent / 'amplitudes.npy', amplitudes) + output = prepare_large(params, tmp_path / 'bounded', window_seconds=20, stratum_seconds=20) + controller = TemplateController(dir_path=output, config_dir=tmp_path / 'config', plugins=[]) + view = controller.create_evidence_amplitude_view() + try: + view.on_select([0]) + assert np.all(np.isfinite(view.data_bounds)) + assert all(np.all(np.isfinite(b.amplitudes)) for b in view._displayed_bunchs) + controller.supervisor.split_source_amplitude(0, 4) + controller.supervisor.save() + curated = apply_curation(params, output, tmp_path / 'curated') + labels = np.load(curated / 'spike_clusters.npy') + assert labels[0] == 100 + assert labels[3] == labels[6] == 101 + finally: + view.canvas.close() + controller.close() diff --git a/phy/apps/large_recording/tests/test_gui_lifecycle.py b/phy/apps/large_recording/tests/test_gui_lifecycle.py new file mode 100644 index 000000000..c6d951b38 --- /dev/null +++ b/phy/apps/large_recording/tests/test_gui_lifecycle.py @@ -0,0 +1,150 @@ +"""GUI transaction, proposition review, and pending-metric regressions.""" + +import json + +import numpy as np +import pytest +from phylib.utils import connect, unconnect + +from phy.apps.large_recording.prepare import prepare_large +from phy.apps.large_recording.tests.test_adapter import make_controller, make_gui_sorting +from phy.apps.template.gui import TemplateController + + +def test_gui_observer_mutation_rolls_back_views_selection_and_journal(qtbot, tmp_path): + _, controller = make_controller(tmp_path) + gui = controller.create_gui(default_views=[], do_prompt_save=False) + supervisor = controller.supervisor + once = [] + + try: + supervisor.select([0]) + supervisor.block() + assignments = supervisor.clustering.spike_clusters.copy() + events = list(controller.bounded_session.events) + selection = supervisor.selection.snapshot() + cluster_ids = supervisor.cluster_view.get_ids() + similarity_ids = supervisor.similarity_view.get_ids() + histories = tuple( + (history._index, len(history._history)) + for history in ( + supervisor.clustering._undo_stack, + supervisor.cluster_meta._undo_stack, + supervisor._global_history, + supervisor.session_history, + ) + ) + dirty = supervisor.is_dirty() + + @connect(event='cluster', sender=supervisor.clustering) + def mutate(sender, up): + if not once: + once.append(True) + sender.assign([0]) + + with pytest.raises((ValueError, KeyError)): + supervisor.merge([0, 1]) + supervisor.block() + + np.testing.assert_array_equal(supervisor.clustering.spike_clusters, assignments) + assert controller.bounded_session.events == events + assert supervisor.selection.snapshot() == selection + assert supervisor.cluster_view.get_ids() == cluster_ids + assert supervisor.similarity_view.get_ids() == similarity_ids + assert ( + tuple( + (history._index, len(history._history)) + for history in ( + supervisor.clustering._undo_stack, + supervisor.cluster_meta._undo_stack, + supervisor._global_history, + supervisor.session_history, + ) + ) + == histories + ) + assert supervisor.is_dirty() == dirty + finally: + if 'mutate' in locals(): + unconnect(mutate) + gui.close() + controller.close() + + +def test_gui_proposition_review_undo_redo_and_checkpoint_reopen(qtbot, tmp_path): + params = make_gui_sorting(tmp_path / 'source') + proposal = { + 'format_version': '2', + 'unit_ids': [0, 1, 2, 99], + 'merges': [{'unit_ids': [0, 1]}], + } + (params.parent / 'curation.json').write_text(json.dumps(proposal), encoding='utf-8') + bounded = prepare_large( + params, + tmp_path / 'bounded', + window_seconds=20, + stratum_seconds=20, + bin_seconds=5, + batch_size=2, + ) + config = tmp_path / 'config' + controller = TemplateController( + dir_path=bounded, config_dir=config, plugins=[], enable_threading=False + ) + gui = controller.create_gui(default_views=[], do_prompt_save=False) + supervisor = controller.supervisor + proposition = supervisor.merge_propositions.catalog.propositions[0] + key = proposition.key + + try: + supervisor._review_merge_proposition(supervisor.merge_propositions_view, key) + assert supervisor.selection.state.is_merge_mode + assert supervisor.selected_merge == [0, 1] + + merged = supervisor.merge() + supervisor.block() + assert merged.added == [100] + assert supervisor.merge_propositions.catalog.status_for(key).value == 'accepted' + assert controller.bounded_session.events[-1]['target'] == 100 + + supervisor.undo() + supervisor.block() + assert supervisor.merge_propositions.catalog.status_for(key).value == 'pending' + assert controller.bounded_session.events == [] + + supervisor.redo() + supervisor.block() + assert supervisor.merge_propositions.catalog.status_for(key).value == 'accepted' + assert controller.bounded_session.events[-1]['target'] == 100 + supervisor.save() + finally: + gui.close() + controller.close() + + reopened = TemplateController( + dir_path=bounded, config_dir=config, plugins=[], enable_threading=False + ) + try: + key = reopened.supervisor.merge_propositions.catalog.propositions[0].key + assert reopened.supervisor.merge_propositions.catalog.status_for(key).value == 'accepted' + assert reopened.bounded_session.events[-1]['target'] == 100 + finally: + reopened.close() + + +def test_default_bounded_views_handle_threshold_children_with_pending_metrics(qtbot, tmp_path): + _, controller = make_controller(tmp_path) + gui = controller.create_gui(do_prompt_save=False) + try: + supervisor = controller.supervisor + update = supervisor.split_source_amplitude(0, 4) + supervisor.block() + assert set(update.added) == {100, 101} + for cluster_id in update.added: + row = supervisor.cluster_view._model.row_by_id(cluster_id) + assert row['fr'] is None + assert row['full_count'] is None + assert row['evidence'] == 'pending replay' + finally: + gui.close() + controller.close() diff --git a/phy/apps/large_recording/views.py b/phy/apps/large_recording/views.py new file mode 100644 index 000000000..d19d5190e --- /dev/null +++ b/phy/apps/large_recording/views.py @@ -0,0 +1,23 @@ +"""Explicitly sampled statistics and window-relative amplitude views.""" + +from phy.cluster.views import AmplitudeView, CorrelogramView, ISIView + + +class SampledISIView(ISIView): + ex_status = 'Selected windows only; intervals crossing window boundaries excluded.' + + +class SampledCorrelogramView(CorrelogramView): + ex_status = 'Selected windows only; raw pair counts, no full-recording rate baseline.' + + +class EvidenceAmplitudeView(AmplitudeView): + """Raw source amplitude in an explicitly rebased evidence window.""" + + def _get_data_bounds(self, bunchs): + if not any(len(bunch.amplitudes) for bunch in bunchs): + return (0, 0, self.duration, 1) + xmin, ymin, xmax, ymax = super()._get_data_bounds(bunchs) + if ymin == ymax: + ymin, ymax = ymin - 0.5, ymax + 0.5 + return xmin, ymin, xmax, ymax diff --git a/phy/apps/template/gui.py b/phy/apps/template/gui.py index bda606c42..d8c1db3ba 100644 --- a/phy/apps/template/gui.py +++ b/phy/apps/template/gui.py @@ -81,6 +81,14 @@ class TemplateController(WaveformMixin, FeatureMixin, TemplateMixin, TraceMixin, # Internal methods # ------------------------------------------------------------------------- + def __new__(cls, dir_path=None, *args, **kwargs): + if cls is TemplateController and dir_path is not None: + if (Path(dir_path) / '_phy_curation_manifest.json').exists(): + from ..large_recording.adapter import BoundedTemplateController + + return object.__new__(BoundedTemplateController) + return object.__new__(cls) + def _get_waveforms_dict(self): waveforms_dict = super()._get_waveforms_dict() # Remove waveforms and mean_waveforms if there is no raw data file. @@ -142,6 +150,7 @@ def _get_template_features(self, cluster_ids, load_all=False): def _set_view_creator(self): super()._set_view_creator() self.view_creator['TemplateFeatureView'] = self.create_template_feature_view + self.view_creator['UnitStabilityView'] = self.create_unit_stability_view # Public methods # ------------------------------------------------------------------------- @@ -255,6 +264,12 @@ def create_template_feature_view(self): return return TemplateFeatureView(coords=self._get_template_features) + def create_unit_stability_view(self): + """Optionally inspect selected-unit activity over the loaded recording.""" + from ..large_recording.stability import UnitStabilityView + + return UnitStabilityView(self) + # ------------------------------------------------------------------------------ # Template commands @@ -268,9 +283,14 @@ def template_gui(params_path, **kwargs): # pragma: no cover dir_path = p.parent _add_log_file(dir_path / 'phy.log') - model = load_model(params_path) + bounded = (dir_path / '_phy_curation_manifest.json').exists() + model = None if bounded else load_model(params_path) # Automatically export spike waveforms when using compressed raw ephys. - if model.spike_waveforms is None and isinstance(model.traces, MtscompEphysReader): + if ( + model is not None + and model.spike_waveforms is None + and isinstance(model.traces, MtscompEphysReader) + ): # TODO: customizable values below. model.save_spikes_subset_waveforms(max_n_spikes_per_template=500, max_n_channels=16) @@ -285,6 +305,22 @@ def template_gui(params_path, **kwargs): # pragma: no cover def template_describe(params_path): """Describe a template dataset.""" + if (Path(params_path).parent / '_phy_curation_manifest.json').exists(): + from ..large_recording.curation import BoundedSession + + session = BoundedSession(Path(params_path).parent) + try: + print(f'Bounded evidence: {len(session.assignments):,} spikes') + print( + f'Complete source: {session.manifest["num_spikes"]:,} spikes, {len(session.unit_ids):,} units' + ) + print( + f'Duration: {session.manifest["num_samples"] / session.manifest["sample_rate"]:.3f} s' + ) + print(f'Committed curation: {len(session.events)} semantic operations') + finally: + session.close() + return model = load_model(params_path) model.describe() model.close() From 983a23d6ce0639bdd63b68b6230bb7999463290f Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 11:40:09 +0200 Subject: [PATCH 14/53] Expose preparation and replay commands with reproducible capacity benchmark --- phy/apps/__init__.py | 61 +++++ tools/benchmark_long_recording.py | 398 ++++++++++++++++++++++++++++++ 2 files changed, 459 insertions(+) create mode 100644 tools/benchmark_long_recording.py diff --git a/phy/apps/__init__.py b/phy/apps/__init__.py index db51602ea..c6767d88c 100644 --- a/phy/apps/__init__.py +++ b/phy/apps/__init__.py @@ -174,6 +174,57 @@ def cli_template_describe(ctx, params_path): template_describe(params_path) +# ------------------------------------------------------------------------------ +# Long-recording batch commands +# ------------------------------------------------------------------------------ + + +@phycli.command('prepare-large') +@click.argument('params-path', type=click.Path(exists=True, dir_okay=False, path_type=Path)) +@click.argument('output-dir', type=click.Path(path_type=Path)) +@click.option('--duration', 'duration_seconds', type=click.FloatRange(min=0, min_open=True)) +@click.option('--valid-intervals', type=click.Path(exists=True, dir_okay=False, path_type=Path)) +@click.option('--max-spikes', type=click.IntRange(min=1), default=2000000, show_default=True) +@click.option('--max-bytes', type=click.IntRange(min=1), default=536870912, show_default=True) +@click.option('--window-seconds', type=click.FloatRange(min=0, min_open=True), default=30.0) +@click.option('--stratum-seconds', type=click.FloatRange(min=0, min_open=True), default=3600.0) +@click.option('--seed', type=click.IntRange(min=0), default=0) +@click.option('--bin-seconds', type=click.FloatRange(min=0, min_open=True), default=3600.0) +@click.option('--batch-size', type=click.IntRange(min=1), default=100000) +def cli_prepare_large(params_path, output_dir, valid_intervals=None, **kwargs): + """Prepare bounded shared-window evidence and complete-sorting summaries. + + VALID_INTERVALS is an optional int64 .npy array of acquisition sample [start, end) pairs. + Duration/exposure must be authoritative; it is never inferred from spike silence. + """ + import numpy as np + + from .large_recording.prepare import prepare_large + + try: + intervals = np.load(valid_intervals, allow_pickle=False) if valid_intervals else None + output = prepare_large(params_path, output_dir, valid_intervals=intervals, **kwargs) + except (ValueError, OSError) as error: + raise click.ClickException(str(error)) from error + click.echo(f'Prepared bounded evidence: {output}') + + +@phycli.command('apply-curation') +@click.argument('source-params', type=click.Path(exists=True, dir_okay=False, path_type=Path)) +@click.argument('bounded-dir', type=click.Path(exists=True, file_okay=False, path_type=Path)) +@click.argument('output-dir', type=click.Path(path_type=Path)) +@click.option('--batch-size', type=click.IntRange(min=1), default=100000) +def cli_apply_curation(source_params, bounded_dir, output_dir, batch_size): + """Replay committed bounded curation into a new complete sorting.""" + from .large_recording.replay import apply_curation + + try: + output = apply_curation(source_params, bounded_dir, output_dir, batch_size=batch_size) + except (ValueError, OSError) as error: + raise click.ClickException(str(error)) from error + click.echo(f'Published complete curated sorting: {output}') + + # ------------------------------------------------------------------------------ # Kwik GUI # ------------------------------------------------------------------------------ @@ -224,6 +275,11 @@ def cli_alf_convert(ctx, subdirs, out_dir): from phylib.io.merge import Merger from phylib.io.model import load_model + if any((Path(path) / '_phy_curation_manifest.json').exists() for path in subdirs): + raise click.ClickException( + 'Apply bounded curation to the complete sorting before ALF conversion.' + ) + out_dir = Path(out_dir) if len(subdirs) >= 2: @@ -253,6 +309,11 @@ def template_extract_waveforms( """Extract spike waveforms.""" from phylib.io.model import load_model + if (Path(params_path).parent / '_phy_curation_manifest.json').exists(): + raise click.ClickException( + 'Extract waveforms on the original source and regenerate bounded evidence; bounded package assets are immutable.' + ) + model = load_model(params_path) model.save_spikes_subset_waveforms( max_n_spikes_per_template=n_spikes_per_cluster, max_n_channels=nc diff --git a/tools/benchmark_long_recording.py b/tools/benchmark_long_recording.py new file mode 100644 index 000000000..b6bfabeef --- /dev/null +++ b/tools/benchmark_long_recording.py @@ -0,0 +1,398 @@ +"""Reproducible, file-backed capacity benchmark for long-recording services. + +Run from a development environment, for example:: + + uv run python tools/benchmark_long_recording.py --spikes 1000000 + +The benchmark creates synthetic Phy arrays without raw traces, times preparation +and replay in separate child processes, and checks replay against an independent +streamed oracle. It is intentionally capped at two million source spikes. +""" + +import argparse +import json +import os +import platform +import subprocess +import sys +import tempfile +import threading +import time +from pathlib import Path + +import numpy as np + +REPOSITORY = Path(__file__).resolve().parents[1] +if str(REPOSITORY) not in sys.path: + sys.path.insert(0, str(REPOSITORY)) + + +def _file_bytes(path): + path = Path(path) + return sum(item.stat().st_size for item in path.rglob('*') if item.is_file()) + + +def _make_source(path, spikes, units, duration_hours, batch_size): + """Write canonical arrays in bounded chunks, without allocating full vectors.""" + path.mkdir(parents=True) + duration_seconds = duration_hours * 3600 + sample_rate = 30_000 + num_samples = round(duration_seconds * sample_rate) + if num_samples <= 0 or num_samples > np.iinfo(np.int64).max: + raise ValueError('duration-hours produces an invalid int64 sample axis.') + + arrays = { + 'spike_times.npy': np.lib.format.open_memmap( + path / 'spike_times.npy', mode='w+', dtype=np.int64, shape=(spikes,) + ), + 'spike_clusters.npy': np.lib.format.open_memmap( + path / 'spike_clusters.npy', mode='w+', dtype=np.int32, shape=(spikes,) + ), + 'spike_templates.npy': np.lib.format.open_memmap( + path / 'spike_templates.npy', mode='w+', dtype=np.int32, shape=(spikes,) + ), + } + for start in range(0, spikes, batch_size): + stop = min(start + batch_size, spikes) + rows = np.arange(start, stop, dtype=np.int64) + arrays['spike_times.npy'][start:stop] = rows * (num_samples - 1) // spikes + assignments = (rows % units).astype(np.int32) + arrays['spike_clusters.npy'][start:stop] = assignments + arrays['spike_templates.npy'][start:stop] = assignments + for array in arrays.values(): + array.flush() + array._mmap.close() + + templates = np.lib.format.open_memmap( + path / 'templates.npy', mode='w+', dtype=np.float32, shape=(units, 4, 2) + ) + templates[:] = 0 + templates.flush() + templates._mmap.close() + np.save(path / 'channel_map.npy', np.array([0, 1], dtype=np.int32)) + np.save(path / 'channel_positions.npy', np.array([[0.0, 0.0], [20.0, 0.0]], dtype=np.float32)) + (path / 'params.py').write_text( + f'sample_rate = {sample_rate}.0\n' + f'num_samples = {num_samples}\n' + 'n_channels_dat = 2\n' + "dtype = 'int16'\n" + 'dat_path = None\n', + encoding='utf-8', + ) + return duration_seconds + + +def _peak_rss_bytes(): + """Return process peak RSS, or an explicit unavailable result.""" + if os.name != 'nt': + try: + import resource + + value = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss + # Linux and the BSDs report KiB; macOS reports bytes. + return int(value if sys.platform == 'darwin' else value * 1024), 'resource.ru_maxrss' + except (ImportError, AttributeError, OSError): + pass + + try: + import psutil + except ImportError: + return None, 'unavailable (install psutil for sampled peak RSS on Windows)' + + process = psutil.Process() + peak = [process.memory_info().rss] + stopped = threading.Event() + + def sample(): + while not stopped.wait(0.02): + try: + peak[0] = max(peak[0], process.memory_info().rss) + except psutil.Error: + return + + sampler = threading.Thread(target=sample, daemon=True) + sampler.start() + return _SampledRSS(stopped, sampler, peak) + + +class _SampledRSS: + def __init__(self, stopped, sampler, peak): + self.stopped = stopped + self.sampler = sampler + self.peak = peak + + def finish(self): + self.stopped.set() + self.sampler.join() + return int(self.peak[0]), 'psutil sampled every 20 ms' + + +def _measure_rss_start(): + value = _peak_rss_bytes() + return value if isinstance(value, _SampledRSS) else value + + +def _rss_result(handle): + return handle.finish() if isinstance(handle, _SampledRSS) else handle + + +def _phase_prepare(args): + from phy.apps.large_recording.prepare import prepare_large + + rss = _measure_rss_start() + started = time.perf_counter() + bounded = prepare_large( + args.params, + args.bounded_path, + duration_seconds=args.duration_seconds, + max_spikes=args.max_spikes, + max_bytes=args.max_bytes, + window_seconds=args.window_seconds, + stratum_seconds=args.stratum_seconds, + seed=args.seed, + batch_size=args.batch_size, + bin_seconds=args.bin_seconds, + ) + elapsed = time.perf_counter() - started + peak, method = _rss_result(rss) + print( + json.dumps( + { + 'phase': 'prepare', + 'wall_seconds': elapsed, + 'peak_rss_bytes': peak, + 'peak_rss_method': method, + 'bounded_path': str(bounded), + } + ) + ) + + +def _phase_curate(args): + from phy.apps.large_recording.curation import BoundedSession + + session = BoundedSession(args.bounded_path) + try: + if 0 not in session.unit_ids or 1 not in session.unit_ids: + raise ValueError('Synthetic source must contain units 0 and 1.') + session.record_merge([0, 1], session.next_cluster_id) + session.save() + finally: + session.close() + print(json.dumps({'phase': 'curate', 'saved': True})) + + +def _phase_replay(args): + from phy.apps.large_recording.replay import apply_curation + + rss = _measure_rss_start() + started = time.perf_counter() + output = apply_curation( + args.params, args.bounded_path, args.curated_path, batch_size=args.batch_size + ) + elapsed = time.perf_counter() - started + peak, method = _rss_result(rss) + print( + json.dumps( + { + 'phase': 'replay', + 'wall_seconds': elapsed, + 'peak_rss_bytes': peak, + 'peak_rss_method': method, + 'curated_path': str(output), + } + ) + ) + + +def _oracle(source_path, curated_path, spikes, units, batch_size): + """Independent streamed oracle for the benchmark's one known merge.""" + source = np.load(source_path / 'spike_clusters.npy', mmap_mode='r', allow_pickle=False) + output = np.load(curated_path / 'spike_clusters.npy', mmap_mode='r', allow_pickle=False) + expected_target = units + checked = 0 + matches = source.shape == output.shape == (spikes,) + for start in range(0, spikes, batch_size): + stop = min(start + batch_size, spikes) + expected = np.array(source[start:stop], copy=True) + expected[(expected == 0) | (expected == 1)] = expected_target + matches &= np.array_equal(expected, output[start:stop]) + checked += stop - start + source._mmap.close() + output._mmap.close() + return {'matches': bool(matches), 'rows_checked': checked, 'merge_target': expected_target} + + +def _run_phase( + script, + phase, + params, + bounded, + curated, + duration_seconds, + max_spikes, + max_bytes, + window_seconds, + stratum_seconds, + seed, + batch_size, + bin_seconds, +): + command = [ + sys.executable, + str(script), + '--_phase', + phase, + '--params', + str(params), + '--bounded-path', + str(bounded), + '--curated-path', + str(curated), + '--duration-seconds', + str(duration_seconds), + '--max-spikes', + str(max_spikes), + '--max-bytes', + str(max_bytes), + '--window-seconds', + str(window_seconds), + '--stratum-seconds', + str(stratum_seconds), + '--seed', + str(seed), + '--batch-size', + str(batch_size), + '--bin-seconds', + str(bin_seconds), + ] + try: + completed = subprocess.run( + command, cwd=REPOSITORY, check=True, capture_output=True, text=True + ) + except subprocess.CalledProcessError as error: + raise RuntimeError(error.stderr.strip() or error.stdout.strip()) from error + return json.loads(completed.stdout.strip().splitlines()[-1]) + + +def _run(args): + if args.spikes <= 0 or args.spikes > 2_000_000: + raise ValueError('--spikes must be between 1 and 2,000,000.') + if args.units < 2 or args.units > args.spikes: + raise ValueError('--units must be at least 2 and no greater than --spikes.') + if args.batch_size <= 0 or args.duration_hours <= 0: + raise ValueError('--batch-size and --duration-hours must be positive.') + + temporary = None + if args.output_dir: + root = Path(args.output_dir).resolve() + root.mkdir(parents=True, exist_ok=True) + else: + temporary = tempfile.TemporaryDirectory(prefix='phy-long-recording-benchmark-') + root = Path(temporary.name) + source_dir, bounded_dir, curated_dir = ( + root / name for name in ('source', 'bounded', 'curated') + ) + duration_seconds = _make_source( + source_dir, args.spikes, args.units, args.duration_hours, args.batch_size + ) + source_bytes = _file_bytes(source_dir) + common = { + 'params': source_dir / 'params.py', + 'bounded': bounded_dir, + 'curated': curated_dir, + 'duration_seconds': duration_seconds, + 'max_spikes': args.max_spikes, + 'max_bytes': args.max_bytes, + 'window_seconds': args.window_seconds, + 'stratum_seconds': args.stratum_seconds, + 'seed': args.seed, + 'batch_size': args.batch_size, + 'bin_seconds': args.bin_seconds, + } + prepare = _run_phase(Path(__file__).resolve(), 'prepare', **common) + _run_phase(Path(__file__).resolve(), 'curate', **common) + replay = _run_phase(Path(__file__).resolve(), 'replay', **common) + oracle = _oracle(source_dir, curated_dir, args.spikes, args.units, args.batch_size) + if not oracle['matches']: + raise RuntimeError('Independent streamed replay oracle did not match curated assignments.') + + result = { + 'benchmark': 'phy_long_recording_v1', + 'machine': { + 'platform': platform.platform(), + 'machine': platform.machine(), + 'processor': platform.processor(), + 'python': platform.python_version(), + 'numpy': np.__version__, + 'cpu_count': os.cpu_count(), + }, + 'parameters': { + 'spikes': args.spikes, + 'units': args.units, + 'duration_hours': args.duration_hours, + 'sample_rate_hz': 30000, + 'batch_size': args.batch_size, + 'max_spikes': args.max_spikes, + 'max_bytes': args.max_bytes, + 'window_seconds': args.window_seconds, + 'stratum_seconds': args.stratum_seconds, + 'seed': args.seed, + 'bin_seconds': args.bin_seconds, + }, + 'source_file_bytes': source_bytes, + 'bounded_file_bytes': _file_bytes(bounded_dir), + 'curated_file_bytes': _file_bytes(curated_dir), + 'bounded_spikes': int( + json.loads((bounded_dir / '_phy_curation_manifest.json').read_text(encoding='utf-8'))[ + 'bounded_num_spikes' + ] + ), + 'preparation': prepare, + 'replay': replay, + 'independent_streamed_replay_oracle': oracle, + 'output_dir': str(root), + 'output_dir_retained': temporary is None, + } + print(json.dumps(result, indent=2, sort_keys=True)) + if temporary is not None: + temporary.cleanup() + + +def _parser(): + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument('--spikes', type=int, default=1_000_000) + parser.add_argument('--units', type=int, default=1000) + parser.add_argument('--duration-hours', type=float, default=1000) + parser.add_argument('--batch-size', type=int, default=100_000) + parser.add_argument('--max-spikes', type=int, default=100_000) + parser.add_argument('--max-bytes', type=int, default=536_870_912) + parser.add_argument('--window-seconds', type=float, default=30) + parser.add_argument('--stratum-seconds', type=float, default=3600) + parser.add_argument('--seed', type=int, default=0) + parser.add_argument('--bin-seconds', type=float, default=3600) + parser.add_argument('--output-dir', type=Path) + parser.add_argument( + '--_phase', choices=('prepare', 'curate', 'replay'), help=argparse.SUPPRESS + ) + parser.add_argument('--params', type=Path, help=argparse.SUPPRESS) + parser.add_argument('--bounded-path', type=Path, help=argparse.SUPPRESS) + parser.add_argument('--curated-path', type=Path, help=argparse.SUPPRESS) + parser.add_argument('--duration-seconds', type=float, help=argparse.SUPPRESS) + return parser + + +def main(): + args = _parser().parse_args() + if args._phase == 'prepare': + _phase_prepare(args) + elif args._phase == 'curate': + _phase_curate(args) + elif args._phase == 'replay': + _phase_replay(args) + else: + _run(args) + + +if __name__ == '__main__': + main() From f212f069e5b5b19469cfa73781dac08de093d9a1 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 11:40:53 +0200 Subject: [PATCH 15/53] Protect bounded source clock and channel schema from plugin mutation --- phy/apps/large_recording/model.py | 14 +++++++++++++- phy/apps/large_recording/tests/test_adapter.py | 2 ++ 2 files changed, 15 insertions(+), 1 deletion(-) diff --git a/phy/apps/large_recording/model.py b/phy/apps/large_recording/model.py index cc0bf62b3..9f0de0389 100644 --- a/phy/apps/large_recording/model.py +++ b/phy/apps/large_recording/model.py @@ -31,7 +31,19 @@ def freeze_source(self): {name: MappingProxyType(values) for name, values in self.metadata.items()} ) names.update( - ('metadata', 'save_spike_clusters', 'save_metadata', 'save_spikes_subset_waveforms') + ( + 'metadata', + 'save_spike_clusters', + 'save_metadata', + 'save_spikes_subset_waveforms', + 'sample_rate', + 'duration', + 'n_channels', + 'n_channels_dat', + 'n_samples_waveforms', + 'dtype', + 'offset', + ) ) self._protected_source_names = frozenset(names) diff --git a/phy/apps/large_recording/tests/test_adapter.py b/phy/apps/large_recording/tests/test_adapter.py index 937d45433..76d4dda47 100644 --- a/phy/apps/large_recording/tests/test_adapter.py +++ b/phy/apps/large_recording/tests/test_adapter.py @@ -57,6 +57,8 @@ def test_manifest_factory_reserves_complete_ids_and_guards_mutations(tmp_path): controller.model.spike_clusters[0] = 123 with pytest.raises(ValueError): controller.model.spike_clusters = np.array([123]) + with pytest.raises(ValueError): + controller.model.sample_rate = 1.0 with pytest.raises(TypeError): controller.model.metadata['group'][0] = 'noise' supervisor = controller.supervisor From 7526e483907fcf5da2f493b754302888d276fbc1 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 11:42:58 +0200 Subject: [PATCH 16/53] Validate GUI channel geometry and nonidentity waveform mappings --- phy/apps/large_recording/source.py | 8 ++++++-- phy/apps/large_recording/tests/test_prepare.py | 4 +++- phy/apps/large_recording/tests/test_source.py | 10 ++++++++++ 3 files changed, 19 insertions(+), 3 deletions(-) diff --git a/phy/apps/large_recording/source.py b/phy/apps/large_recording/source.py index 9d86c7b31..07bacf21f 100644 --- a/phy/apps/large_recording/source.py +++ b/phy/apps/large_recording/source.py @@ -536,8 +536,12 @@ def validate(self): if np.any((sparse < -1) | (sparse >= len(channels))): raise ValueError(f'{index_name} contains invalid model channel IDs.') positions = self.arrays.get('channel_positions.npy') - if positions is not None and (positions.ndim != 2 or len(positions) != len(channels)): - raise ValueError('channel_positions.npy must align with model channels.') + if positions is not None and ( + positions.shape != (len(channels), 2) or not np.all(np.isfinite(positions)) + ): + raise ValueError( + 'channel_positions.npy must contain finite x/y model channel coordinates.' + ) for feature, indices in ( ('pc_features.npy', 'pc_feature_ind.npy'), ('template_features.npy', 'template_feature_ind.npy'), diff --git a/phy/apps/large_recording/tests/test_prepare.py b/phy/apps/large_recording/tests/test_prepare.py index 7dacb519b..a3688fd8c 100644 --- a/phy/apps/large_recording/tests/test_prepare.py +++ b/phy/apps/large_recording/tests/test_prepare.py @@ -11,8 +11,10 @@ from phy.apps.large_recording.tests.test_source import make_sorting -def test_prepare_exact_arrays_waveforms_and_source_unchanged(tmp_path): +@pytest.mark.parametrize('channel_map', [[0, 1, 2], [2, 0, 1]]) +def test_prepare_exact_arrays_waveforms_and_source_unchanged(tmp_path, channel_map): params = make_sorting(tmp_path / 'full', columns=True) + np.save(params.parent / 'channel_map.npy', np.asarray(channel_map, dtype=np.int32)) before = {p.name: hash_file(p) for p in params.parent.iterdir()} output = prepare_large( params, diff --git a/phy/apps/large_recording/tests/test_source.py b/phy/apps/large_recording/tests/test_source.py index b3c1c45ee..1dfe30e7f 100644 --- a/phy/apps/large_recording/tests/test_source.py +++ b/phy/apps/large_recording/tests/test_source.py @@ -264,6 +264,16 @@ def test_exporter_channel_sidecars_and_raw_map_validation(tmp_path): Source(params) +@pytest.mark.parametrize( + 'positions', [np.zeros((3, 1)), np.zeros((3, 3)), np.full((3, 2), np.nan)] +) +def test_channel_geometry_must_match_gui_contract(tmp_path, positions): + params = make_sorting(tmp_path / 'source') + np.save(params.parent / 'channel_positions.npy', positions) + with pytest.raises(ValueError, match='finite x/y'): + Source(params) + + def test_exclusive_publish_preserves_racing_empty_destination(tmp_path): from phy.apps.large_recording.source import publish_directory From 064e71cf0c5ec956de6ff4a05119b5e3d08a5844 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 11:43:49 +0200 Subject: [PATCH 17/53] Document bounded workflow, validation evidence, and scientific acceptance limits --- design/large-recording-curation.md | 11 +- design/large-recording-integration-plan.md | 26 ++-- design/large-recording-validation.md | 77 ++++++++++ docs/api.md | 16 +++ docs/changelog.md | 15 ++ docs/cli.md | 29 ++++ docs/long-recordings.md | 160 +++++++++++++++++++++ mkdocs.yml | 1 + 8 files changed, 321 insertions(+), 14 deletions(-) create mode 100644 design/large-recording-validation.md create mode 100644 docs/long-recordings.md diff --git a/design/large-recording-curation.md b/design/large-recording-curation.md index 7e9b11388..87707863a 100644 --- a/design/large-recording-curation.md +++ b/design/large-recording-curation.md @@ -1,9 +1,12 @@ # Long-recording curation in Phy 2.x: Phy-side design contract -**Status:** proposed; implementation sequence and file contracts for review. This -specification is for Phy-side development; it does not authorize changes to the -AIND/Code Ocean export pipeline. Current Phy behavior remains unchanged until -the implementation is complete and validated. +**Status:** implementation present; acceptance validation is ongoing. This +specification is for Phy-side behavior; it does not authorize changes to the +AIND/Code Ocean export pipeline. The current branch implements the bounded +workflow behind an explicit manifest while retaining standard behavior for +ordinary datasets. See the [integration plan](large-recording-integration-plan.md) +and [validation record](large-recording-validation.md) for implementation scope, +checks, and remaining acceptance work. The [integration audit and plan](large-recording-integration-plan.md) refines this proposal with assignment revisions, transactional persistence, capability diff --git a/design/large-recording-integration-plan.md b/design/large-recording-integration-plan.md index ee6270afa..de9e7043d 100644 --- a/design/large-recording-integration-plan.md +++ b/design/large-recording-integration-plan.md @@ -265,13 +265,19 @@ supports one segment and distinguishes Phy channel indices from exported origina channel IDs. Do not assume that arbitrary multi-session inputs already satisfy this contract or that a deployed exporter matches this inspected revision. -## Validation of this design branch - -On 2026-10-13, the locked development environment with phylib 2.7.1 passed -all ten reference tests, including the loader and returned waveform values. -`make test-apps format-check` passed all 165 application tests, lint and -formatting checks. Patch whitespace validation also passed. The test process -reported pending ipykernel tasks during shutdown after successful completion. -This branch changes design documents and reference tests only; it does not -implement preparation, replay, transactional saves or a stability view, and -does not establish realistic long-recording capacity. +## Implementation and validation status + +The branch now includes batched source validation and preparation, full-source +summaries, bounded GUI curation and checkpoints, semantic replay, Unit Stability, +and dedicated long-recording tests. The feature is implemented, but its +acceptance remains incomplete: this test and synthetic benchmark evidence does +not replace real chronic-recording review by domain curators. + +On 2026-10-13, `make test-full` completed with 745 passed and 1 skipped. Three +additional bounded GUI lifecycle regressions pass in +`phy/apps/large_recording/tests/test_gui_lifecycle.py`. +[`design/large-recording-validation.md`](large-recording-validation.md) records +the synthetic capacity runs and their limits. The separate 32-spike, 1000-hour +fixture verifies sample-coordinate handling and file mapping; it is not a +billion-spike capacity test or evidence of chronic biological identity. Curator +acceptance on real chronic recordings remains outstanding. diff --git a/design/large-recording-validation.md b/design/large-recording-validation.md new file mode 100644 index 000000000..2dcd3e761 --- /dev/null +++ b/design/large-recording-validation.md @@ -0,0 +1,77 @@ +# Long-recording implementation validation + +This record summarizes the current implementation checks and their limits. The +results validate the measured code paths and fixtures described here. They do +not establish capacity for every source layout or scientific suitability for +chronic curation. + +## Automated checks + +On 2026-10-13, `make test-full` completed with **756 passed and 1 +skipped** (496 non-application tests and 260 application tests). Final channel +geometry and nonidentity waveform-mapping additions passed a further focused +source/preparation run of **33 tests**. Lint, format checking, package build, +and the strict documentation build also passed. The dedicated bounded GUI lifecycle file passed all three +regressions: reentrant observer rollback with the GUI attached, merge-proposal +review through undo/redo/save/reopen, and pending full metrics for threshold +children in the default bounded views. + +The reference long-recording fixture is deliberately sparse: 32 spikes spread +over a 1000-hour sample clock. It checks long `int64` coordinates, tied times, +source-row mapping, waveform remapping, and loader compatibility. It is not a +billion-spike capacity test, a realistic chronic recording, or evidence of +biological identity across a recording. + +## Synthetic preparation and replay runs + +The reproducible benchmark is `uv run python +tools/benchmark_long_recording.py`. It writes synthetic source arrays in +batches, with no raw voltage data, and runs preparation and replay in separate +processes. Both runs below used Python 3.13.3, NumPy 2.4.3, Linux +`x86_64`/glibc 2.39, 30 kHz sampling, 1000 units, a 1000-hour sample axis, +100,000-row batches, 30-second windows, 3600-second strata, a 100,000-spike +budget, a 512 MiB output budget, seed 0, and 3600-second summary bins. The +oracle independently streamed every source and output assignment row and +matched the expected merge in both cases. + +| Synthetic source spikes | Source files | Bounded package | Bounded spikes | Curated output | Prepare time / peak RSS | Replay time / peak RSS | Oracle rows | +| ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: | +| 250,000 | 4,032,892 B | 8,625,460 B | 2,389 | 5,038,086 B | 1.902 s / 215,773,184 B | 0.114 s / 214,847,488 B | 250,000 | +| 2,000,000 | 32,032,892 B | 9,157,120 B | 16,676 | 40,038,086 B | 1.227 s / 214,433,792 B | 0.292 s / 215,285,760 B | 2,000,000 | + +Each measurement is a single run, not a throughput curve. Preparation and +replay durations exclude child-process startup; peak RSS is the process high +water mark. The source is a regular synthetic distribution with tiny templates +and no stored waveforms, raw data, irregular acquisition gaps, or real feature +loads. These figures therefore do not predict every preparation cost or GUI +interaction on a chronic dataset. The full JSON reports are retained at +`/tmp/phy-long-recording-benchmark-250k.json` and +`/tmp/phy-long-recording-benchmark-2m.json` on the validation workstation. + +## Ordinary-dataset smoke comparison + +A separate three-run comparison used fresh subprocesses, configs, and caches in +the same Python environment. It compared baseline `a30d5c65` with current +`f212f069e5b5b19469cfa73781dac08de093d9a1` on a 12,000-spike, two-cluster +dataset with 1,024 stored waveform rows of shape `[40, 4]` and dense template +features. Counts and output dimensions matched exactly. + +| Measure (median of 3) | Baseline | Current | +| --- | ---: | ---: | +| Controller startup | 0.03879 s | 0.02822 s | +| Waveform provider | 0.00353 s | 0.00293 s | +| Feature provider | 0.00372 s | 0.00302 s | + +This small case showed no regression; the apparent gains are within the range +where run-to-run noise matters. The comparison did not measure Qt rendering, +raw-voltage I/O, or large-dataset selection churn. Its report is retained at +`/tmp/phy-standard-recording-comparison.json` on the validation workstation. + +## Remaining acceptance work + +Real chronic-recording review by domain curators remains outstanding. It must +cover drift, rare and bursting units, artifacts, gaps, waveform coverage, +intentionally incorrect merges, withheld contiguous windows, and full-data +diagnostics where available. Software integrity checks and synthetic throughput +do not establish that the evidence is scientifically sufficient or that a +cluster represents one biological unit throughout 1000 hours. diff --git a/docs/api.md b/docs/api.md index a5f0f2506..52733d154 100644 --- a/docs/api.md +++ b/docs/api.md @@ -10117,6 +10117,13 @@ Component that brings manual clustering facilities to a GUI: Whether automatic navigation and similar-cluster selection skip noise and MUA clusters. The default is True. +* `clustering_factory : callable, optional` + Construct the clustering model. Defaults to Clustering; bounded curation + supplies a guarded implementation with the same constructor interface. + +* `cluster_meta_factory : callable, optional` + Construct metadata from groups and labels. Defaults to create_cluster_meta. + **Events** When this component is attached to a GUI, the following events are emitted: @@ -13197,6 +13204,15 @@ Create a trace view. --- +#### TemplateController.create_unit_stability_view + + +**`TemplateController.create_unit_stability_view(self)`** + +Optionally inspect selected-unit activity over the loaded recording. + +--- + #### TemplateController.create_waveform_view diff --git a/docs/changelog.md b/docs/changelog.md index 2842a69f3..1fadb9629 100644 --- a/docs/changelog.md +++ b/docs/changelog.md @@ -11,10 +11,25 @@ been included in a stable release. The current entries cover all user-visible changes committed since 23 July 2026; test-only commits are represented by the behavior they verify rather than listed separately. +### Long recordings + +- Added `prepare-large` and `apply-curation` for bounded shared-window evidence, + full-duration exposure-aware summaries, semantic merges/labels/source-amplitude + splits, and replay into a new complete sorting. +- Added Unit Stability, precise window-relative amplitude/feature inspection, + sampled interval/correlogram views, and explicit full-versus-evidence counts. + Standard datasets retain their existing curation workflow and default layout. +- Bounded saves use validated atomic generations and reject conflicting saves + from stale sessions. Unsupported selected-row splits are blocked. +- Sparse cluster IDs no longer require dense allocations during clustering. + ### Documentation - Documented uv-first installation of exact previous phy releases in separate environments, including how to intentionally replace a tool installation. +- Added a long-recording workflow guide covering bounded evidence preparation, + supported curation, full-sorting replay, and limits on interpreting sampled + measurements. ### Added diff --git a/docs/cli.md b/docs/cli.md index 0bb61a764..16b554a1f 100644 --- a/docs/cli.md +++ b/docs/cli.md @@ -25,6 +25,35 @@ GUI commands accept: --clear-cache remove and rebuild the dataset .phy cache ``` +## Long recordings + +Prepare bounded evidence, curate it with `template-gui`, then replay supported +actions into a new full sorting. See the [long-recording guide](long-recordings.md) +for input requirements, interpretation limits, and the complete workflow. + +```bash +phy prepare-large /data/recording/params.py /data/recording-bounded \ + --duration 3600000 \ + --valid-intervals /data/recording/valid-intervals.npy \ + --max-spikes 2000000 \ + --max-bytes 536870912 \ + --window-seconds 30 \ + --stratum-seconds 3600 \ + --seed 0 \ + --bin-seconds 3600 \ + --batch-size 100000 + +phy template-gui /data/recording-bounded/params.py + +phy apply-curation /data/recording/params.py /data/recording-bounded \ + /data/recording-curated --batch-size 100000 +``` + +`--duration` is acquisition duration in seconds. `--valid-intervals` reads an +integer `.npy` array of `[start, end)` sample pairs. `--max-bytes` caps the +prepared package size, not process memory. The output directories must be new; +the original sorting remains the replay parent. + ## Raw trace viewer ```bash diff --git a/docs/long-recordings.md b/docs/long-recordings.md new file mode 100644 index 000000000..abff49b5e --- /dev/null +++ b/docs/long-recordings.md @@ -0,0 +1,160 @@ +# Curating long recordings + +Phy's long-recording workflow prepares a bounded evidence dataset for interactive +review, then replays supported curation actions against the complete local +sorting. Preparation reads source arrays in batches; it does not load the full +sorting into the GUI. The source dataset is retained unchanged, and replay +writes a separate output dataset. + +This workflow is intended for a Phy sorting with one fixed-rate, monotonic sample +clock. Multi-segment recordings are not supported. Supply acquisition duration +and valid acquisition intervals when they are not already recorded in the +dataset metadata. Duration describes exposure; Phy cannot infer acquisition +gaps from periods with no spikes. Intervals use half-open sample coordinates +`[start, end)`. + +## Prepare bounded evidence + +Run `prepare-large` with the source `params.py` and a new output directory: + +```bash +phy prepare-large /data/recording/params.py /data/recording-bounded \ + --duration 3600000 \ + --valid-intervals /data/recording/valid-intervals.npy \ + --max-spikes 2000000 \ + --max-bytes 536870912 \ + --window-seconds 30 \ + --stratum-seconds 3600 \ + --seed 0 \ + --bin-seconds 3600 \ + --batch-size 100000 +``` + +`--duration` is in seconds and must agree with declared acquisition metadata. +The `.npy` valid-interval file contains an integer array of shape `[W, 2]` with +ordered, nonoverlapping sample pairs. +Without it, the full declared duration is treated as valid exposure. Do not use +that default when the recording contains acquisition gaps. + +`--max-bytes` limits the bounded output package size, including its summaries and +window plan. It is not a process-memory or peak-RSS limit. The source unit IDs +must fit nonnegative `int32`; sample coordinates and full-source spike row IDs +use `int64`. + +Preparation chooses shared time windows under the spike and byte budgets. The +window length, strata, and seed make the plan reproducible; inspect the saved +window plan in the output package when documenting or repeating an analysis. +Windows that exceed the budget are omitted, so a high-density interval can +reduce retained evidence. Preparation does not shorten an over-budget window or +silently thin spikes inside it. A survey of shared windows is supplemented by +deterministic rescue evidence for units missed by the survey. This improves the +chance of seeing rare units, but makes the evidence selection unequal: rescue +windows must not be treated as a probability sample. + +Preparation records exact full-recording spike counts and rates using valid +acquisition exposure. If source scalar amplitudes or depths are available, it +also records per-bin finite-value means and availability counts. It does not +invent missing measurements or convert source values to physical units. Stored +waveforms are included only where available in the source; raw traces are not +required when stored waveform data are sufficient for the views being used. +Producer-supplied per-unit metrics and annotations remain inherited metadata; +Phy does not recalculate those values for merged or split units. Use the +full-count, rate, amplitude-mean, and depth-mean summaries produced by this +workflow for the measurements they explicitly cover. + +## Review and curate + +Open the bounded output with the normal GUI command: + +```bash +phy template-gui /data/recording-bounded/params.py +``` + +The bounded manifest explicitly selects this mode. Bounded mode has its own +configuration namespace and default view layout; it does not replace the normal +Phy layout or restore ordinary saved dock geometry. The GUI keeps full-recording +counts and rates distinct from counts in selected evidence rows. Unit Stability +shows time-binned counts/rates, available source scalar-amplitude means, +evidence windows, and acquisition gaps. Missing measurements and units without +evidence remain visible as unavailable. + +Evidence Amplitude shows raw source scalar amplitudes from the currently +selected evidence window. The Feature view also uses window-relative seconds; +both views label the current window and reset their time origin when it changes. +To inspect another retained window, choose **View > Inspect evidence window** +and enter its zero-based index. Unit Stability keeps the full-recording time +context visible while you inspect individual windows. + +The Sampled ISI view excludes intervals crossing retained-window boundaries. +The Sampled Correlogram view shows raw pair counts from retained windows; it +does not apply a full-recording rate baseline. Both views are explicitly labeled +as sampled evidence. Its central bin counts unordered within-unit pairs and +combines both temporal orientations for cross-unit pairs whose absolute delay +is less than one bin, so tied sample times do not depend on source row order. +For exact pair counts, each unit may have at most 46,340 spikes in an evidence +window; the view reports an error for a larger per-unit window. Prepare shorter +windows if this limit is reached. + +Bounded curation supports whole-unit merges, cluster labels, and a source +amplitude threshold action. Use the GUI action **Split by source amplitude** +with one unit selected and a threshold in the source amplitude units. The action +uses the source `amplitudes.npy` scalar for every spike during replay; nonfinite +values stay with the remainder. Child units show full-data metrics as pending +until the replayed sorting is re-prepared, because their complete counts and +trends have not yet been calculated. Merge and label actions are journaled with +the bounded assignments and metadata in an atomic checkpoint generation. +Reopening loads the last complete generation. A reopened session starts a new +undo baseline. Each save checks that the checkpoint has not changed since this +session opened. If another session has saved first, the stale save fails; reopen +the bounded dataset before continuing to avoid overwriting that generation. + +Lasso, feature, and waveform splits remain unavailable in bounded mode because +the selected rows do not define how unseen source spikes should be assigned. +Standard, unbounded datasets retain their existing curation behavior. + +## Unit Stability on ordinary recordings + +Unit Stability can also be opened as an optional view for an ordinary dataset. +It evaluates only the selected unit and bins its loaded spikes over the recording +duration. Since ordinary datasets do not supply valid acquisition intervals to +this view, its rate assumes continuous acquisition; the plot labels that +assumption. The ordinary default view layout remains unchanged. Use the bounded +manifest workflow above when known acquisition gaps must be represented +explicitly. + +## Apply to the complete sorting + +After saving the bounded session, replay its journal against the exact source +assignment revision used during preparation: + +```bash +phy apply-curation /data/recording/params.py /data/recording-bounded \ + /data/recording-curated --batch-size 100000 +``` + +Replay checks the source identity and parent assignment revision, streams the +complete assignment array in batches, and writes a new full sorting. It rejects +a journal prepared from a different source revision. Keep the original source +and bounded package; they establish the lineage of the curated output. To review +the curated full sorting with bounded evidence again, run `prepare-large` on +the curated output to produce a fresh package and revision-specific summaries. +This replay and re-preparation step also resolves full-data counts and trends +for threshold-split children. + +## Interpreting evidence + +Full counts and exposure-based rates describe the complete sorting. Window plots, +waveforms, feature scatterplots, and other bounded measurements describe only +the retained evidence. Survey and rescue selection can overrepresent some +periods or units, and waveform availability can vary across units and time. +These views do not establish full-recording quality, contamination, refractory +violations, or continuous biological identity. Use them to guide review, not as +scientific claims about unseen spikes. Long-duration coordinates preserve the +source sample clock; silence alone is never evidence that the acquisition was +inactive. + +For reproducible synthetic capacity measurements, run +`uv run python tools/benchmark_long_recording.py`. The benchmark reports +preparation and replay time and peak memory in separate processes and checks +replay against a streamed oracle. It is capped at two million synthetic spikes; +its results are not a substitute for measurements on real chronic datasets. diff --git a/mkdocs.yml b/mkdocs.yml index bf8a4ad12..f59e59417 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -17,6 +17,7 @@ nav: - How-to and customization: - Configuration and state: configuration.md - Performance and spike sampling: performance.md + - Curating long recordings: long-recordings.md - Change keyboard shortcuts: keyboard_customization.md - Plugin introduction: customization.md - Plugin examples: plugins.md From da93252287770e02026e051a74e232dd2a9f0237 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 13:05:11 +0200 Subject: [PATCH 18/53] Fix Windows durable file flushing and close revision-test readers --- design/README.md | 2 +- design/large-recording-curation.md | 2 +- phy/apps/large_recording/curation.py | 3 ++- phy/apps/large_recording/prepare.py | 3 ++- phy/apps/large_recording/replay.py | 3 ++- phy/apps/large_recording/tests/test_source.py | 3 +++ 6 files changed, 11 insertions(+), 5 deletions(-) diff --git a/design/README.md b/design/README.md index 27af3605f..e52897a7a 100644 --- a/design/README.md +++ b/design/README.md @@ -61,7 +61,7 @@ The implementation and user documentation are complete on the unreleased phy ## Long-recording curation (proposed) The [long-recording curation Phy-side design contract](large-recording-curation.md) -describes bounded local datasets for ~1000-hour sortings, the three spike-index +describes bounded local datasets for ~1000-hour sorting datasets, the three spike-index spaces, optional upstream waveform evidence, full-duration metrics, replay safety, and the implementation stages. The accompanying synthetic 1000-hour fixture and reference tests are in `phy/apps/tests/large_recording_fixtures.py` diff --git a/design/large-recording-curation.md b/design/large-recording-curation.md index 87707863a..26f6d482e 100644 --- a/design/large-recording-curation.md +++ b/design/large-recording-curation.md @@ -15,7 +15,7 @@ over the original implementation sequence in Section 9. ## 1. Objective and boundaries -Curate chronic Neuropixels sortings of roughly 1000 hours without opening hundreds +Curate chronic Neuropixels sorting datasets of roughly 1000 hours without opening hundreds of millions or billions of spikes in the existing in-memory Phy clustering model. The workstation downloads the **complete sorter output once**; downloading the complete raw voltage recording is **not required**. All preparation, interactive diff --git a/phy/apps/large_recording/curation.py b/phy/apps/large_recording/curation.py index 52babbad6..6a45d7f70 100644 --- a/phy/apps/large_recording/curation.py +++ b/phy/apps/large_recording/curation.py @@ -757,7 +757,8 @@ def _save_generation(self, generations, values, metadata, events, next_id, docum pointer_tmp = root / f'.current-{identifier}.tmp' try: np.save(stage / 'spike_clusters.npy', values) - with (stage / 'spike_clusters.npy').open('rb') as stream: + # Windows _commit (os.fsync) requires a writable descriptor. + with (stage / 'spike_clusters.npy').open('r+b') as stream: os.fsync(stream.fileno()) _write_json(stage / 'journal.json', events) _write_json(stage / 'metadata.json', metadata) diff --git a/phy/apps/large_recording/prepare.py b/phy/apps/large_recording/prepare.py index 308fca6b2..4f4b5e3dc 100644 --- a/phy/apps/large_recording/prepare.py +++ b/phy/apps/large_recording/prepare.py @@ -464,7 +464,8 @@ def accept(start, end, kind, segment, stratum_id): close_array(array) for path in temporary.iterdir(): if path.is_file(): - with path.open('rb') as stream: + # Windows _commit (os.fsync) requires a writable descriptor. + with path.open('r+b') as stream: os.fsync(stream.fileno()) _fsync_directory(temporary) if output_dir.exists(): diff --git a/phy/apps/large_recording/replay.py b/phy/apps/large_recording/replay.py index 965fde0f7..96c39ba8c 100644 --- a/phy/apps/large_recording/replay.py +++ b/phy/apps/large_recording/replay.py @@ -211,7 +211,8 @@ def _apply_curation(source, session, output_dir, batch_size): curated.close() for path in stage.iterdir(): if path.is_file(): - with path.open('rb') as stream: + # Windows _commit (os.fsync) requires a writable descriptor. + with path.open('r+b') as stream: os.fsync(stream.fileno()) _fsync_directory(stage) # Refuse replacement even when a racing caller creates the target. diff --git a/phy/apps/large_recording/tests/test_source.py b/phy/apps/large_recording/tests/test_source.py index 1dfe30e7f..05578bf9d 100644 --- a/phy/apps/large_recording/tests/test_source.py +++ b/phy/apps/large_recording/tests/test_source.py @@ -104,16 +104,19 @@ def read(*args, **kwargs): def test_identity_assignment_and_feature_layers(tmp_path): params = make_sorting(tmp_path / 'full') source = Source(params) + source.close() clusters = np.load(params.parent / 'spike_clusters.npy') clusters[clusters == 1] = 0 np.save(params.parent / 'spike_clusters.npy', clusters) merged = Source(params) + merged.close() assert merged.identity == source.identity assert merged.revision != source.revision values = np.load(params.parent / 'amplitudes.npy') values[0] = 99 np.save(params.parent / 'amplitudes.npy', values) altered = Source(params) + altered.close() assert altered.identity != merged.identity assert altered.revision == merged.revision assert ( From 8d2e13de4deea7fd418a456c1827fc09edbd5a4e Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 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Duration describes exposure; Phy cannot infer acquisition gaps from periods with no spikes. Intervals use half-open sample coordinates `[start, end)`. +The screenshots below show the actual bounded GUI views using a deterministic +synthetic eight-hour sorting. The overview plots full-duration rates and +available source means; gray marks the synthetic acquisition gap and cyan marks +the inspected evidence window. The evidence view places windowed amplitudes at +top left, sampled ISI at top right, sampled correlograms at middle right, and +features below. They illustrate the interface and its sampling context; they +are not biological data or scientific examples. + +![Full-duration Unit Stability with a synthetic acquisition gap](images/long-recording-overview.png) + +![Windowed source amplitudes, features, sampled ISI and correlogram](images/long-recording-evidence.png) + +Recreate these images from source with Qt's X11 platform and software OpenGL +(the script writes a temporary synthetic source and bounded package): + +```bash +QT_QPA_PLATFORM=xcb LIBGL_ALWAYS_SOFTWARE=1 \ + xvfb-run -a -s '-screen 0 2400x1600x24 +extension GLX' \ + uv run python tools/capture_long_recording_views.py +``` + ## Prepare bounded evidence Run `prepare-large` with the source `params.py` and a new output directory: diff --git a/tools/capture_long_recording_views.py b/tools/capture_long_recording_views.py new file mode 100644 index 000000000..1c40089c8 --- /dev/null +++ b/tools/capture_long_recording_views.py @@ -0,0 +1,254 @@ +"""Capture reproducible screenshots of the bounded-evidence Qt views. + +The script builds a temporary synthetic Phy sorting, prepares it with the real +long-recording workflow, opens the real GUI, and saves two screenshots. It does +not download or modify a recording. + +Run with a display, or under a virtual X server:: + + QT_QPA_PLATFORM=xcb LIBGL_ALWAYS_SOFTWARE=1 \ + xvfb-run -a -s '-screen 0 2400x1600x24 +extension GLX' \ + uv run python tools/capture_long_recording_views.py +""" + +import argparse +import sys +import tempfile +from pathlib import Path + +import numpy as np +from PyQt5.QtTest import QTest + +from phy.apps.large_recording.prepare import prepare_large +from phy.apps.template.gui import TemplateController +from phy.gui.qt import QApplication, Qt + +REPOSITORY = Path(__file__).resolve().parents[1] +DEFAULT_OUTPUT = REPOSITORY / 'docs' / 'images' +SAMPLE_RATE = 30_000 +HOURS = 8 +CLUSTER_IDS = np.array([0, 2, 7, 99], dtype=np.int32) + + +def _make_source(path): + """Write a varied but deterministic synthetic source sorting.""" + path.mkdir(parents=True) + rng = np.random.default_rng(20261013) + samples = SAMPLE_RATE * 3600 * HOURS + intervals = np.array( + [[0, 3 * 3600 * SAMPLE_RATE], [int(3.5 * 3600 * SAMPLE_RATE), samples]], + dtype=np.int64, + ) + valid = intervals[:, 1] - intervals[:, 0] + cumulative = np.cumsum(valid) + offsets = rng.integers(0, cumulative[-1], size=120_000, dtype=np.int64) + interval_index = np.searchsorted(cumulative, offsets, side='right') + previous = np.where(interval_index == 0, 0, cumulative[np.maximum(interval_index - 1, 0)]) + spike_times = intervals[interval_index, 0] + offsets - previous + order = np.argsort(spike_times, kind='stable') + spike_times = spike_times[order] + + unit_index = np.arange(len(spike_times), dtype=np.int64) % len(CLUSTER_IDS) + unit_index = unit_index[order] + elapsed = spike_times / SAMPLE_RATE + hour_phase = elapsed / 3600 + amplitudes = ( + 35 + + unit_index * 9 + + 5 * np.sin(hour_phase * np.pi / 3) + + 2 * hour_phase + + rng.normal(0, 2.5, len(spike_times)) + ).astype(np.float32) + depths = ( + 250 + + unit_index * 180 + + 20 * np.sin(hour_phase * np.pi / 2) + + rng.normal(0, 8, len(spike_times)) + ).astype(np.float32) + templates_for_spike = unit_index.astype(np.int32) + + np.save(path / 'spike_times.npy', spike_times.astype(np.int64)) + np.save(path / 'spike_clusters.npy', CLUSTER_IDS[unit_index]) + np.save(path / 'spike_templates.npy', templates_for_spike) + np.save(path / 'amplitudes.npy', amplitudes) + np.save(path / 'spike_depths.npy', depths) + + channel_map = np.arange(4, dtype=np.int32) + channel_positions = np.array([[0, 0], [20, 100], [0, 200], [20, 300]], dtype=np.float32) + np.save(path / 'channel_map.npy', channel_map) + np.save(path / 'channel_positions.npy', channel_positions) + + templates = np.zeros((len(CLUSTER_IDS), 40, len(channel_map)), dtype=np.float32) + time = np.arange(40, dtype=np.float32) + for unit in range(len(CLUSTER_IDS)): + center = 13 + unit * 3 + pulse = -np.exp(-0.5 * ((time - center) / 3.5) ** 2) * (35 + 8 * unit) + for channel in range(len(channel_map)): + templates[unit, :, channel] = pulse * np.exp(-0.7 * abs(channel - unit)) + np.save(path / 'templates.npy', templates) + + pc_feature_ind = np.array( + [ + [unit, (unit + 1) % len(channel_map), (unit + 2) % len(channel_map)] + for unit in range(len(CLUSTER_IDS)) + ], + dtype=np.int32, + ) + np.save(path / 'pc_feature_ind.npy', pc_feature_ind) + features = np.empty((len(spike_times), 3, 3), dtype=np.float32) + features[:, 0, :] = unit_index[:, None] * 3.5 + rng.normal(0, 0.65, (len(spike_times), 3)) + features[:, 1, :] = np.sin(hour_phase[:, None] * np.pi / 2) + rng.normal( + 0, 0.7, (len(spike_times), 3) + ) + features[:, 2, :] = np.cos(hour_phase[:, None] * np.pi / 3) + rng.normal( + 0, 0.6, (len(spike_times), 3) + ) + np.save(path / 'pc_features.npy', features) + + # Stored waveforms are a display reservoir, aligned to sorted source rows. + waveform_ids = np.arange(0, len(spike_times), 8, dtype=np.int64) + waveform_channels = np.tile( + np.arange(len(channel_map), dtype=np.int32), (len(waveform_ids), 1) + ) + waveforms = templates[unit_index[waveform_ids]].copy() + waveforms += rng.normal(0, 2.2, waveforms.shape).astype(np.float32) + stem = '_phy_spikes_subset' + np.save(path / f'{stem}.spikes.npy', waveform_ids) + np.save(path / f'{stem}.channels.npy', waveform_channels) + np.save(path / f'{stem}.waveforms.npy', waveforms) + + with (path / 'cluster_group.tsv').open('w', encoding='utf-8') as stream: + stream.write('cluster_id\tgroup\n0\tgood\n2\tgood\n7\tmua\n99\tgood\n') + (path / 'params.py').write_text( + f'sample_rate = {SAMPLE_RATE}.0\n' + f'num_samples = {samples}\n' + 'n_channels_dat = 4\n' + "dtype = 'int16'\n" + 'dat_path = None\n' + f'valid_intervals = {intervals.tolist()!r}\n', + encoding='utf-8', + ) + return path / 'params.py', intervals + + +def _wait_for_render(): + QApplication.processEvents() + QTest.qWait(1200) + QApplication.processEvents() + + +def _capture(gui, destination): + _wait_for_render() + # Phy's OpenGL canvases are native child windows. QWidget.grab() omits + # those children on some Qt/X11 combinations, so grab the rendered screen + # and crop to the application window instead. + screen = QApplication.primaryScreen() + frame = gui.frameGeometry() + pixmap = screen.grabWindow(0).copy(frame.x(), frame.y(), frame.width(), frame.height()) + if not pixmap.save(str(destination), 'PNG'): + raise OSError(f'Could not save screenshot: {destination}') + + +def _capture_views(bounded, config_dir, output_dir, stability): + views = ( + ['UnitStabilityView'] + if stability + else [ + 'EvidenceAmplitudeView', + 'FeatureView', + 'SampledISIView', + 'SampledCorrelogramView', + ] + ) + controller = TemplateController( + dir_path=bounded, + config_dir=config_dir, + plugins=[], + enable_threading=False, + ) + gui = controller.create_gui(default_views=views, do_prompt_save=False) + try: + gui.resize(2100, 1200) + gui.show() + _wait_for_render() + # Focus the captures on the plotted evidence rather than the GUI tables. + similarity = gui.get_view('SimilarityView') + if similarity is not None: + similarity.dock.hide() + cluster_table = gui.get_view('ClusterView') + if cluster_table is not None: + cluster_table.dock.hide() + if not stability: + amplitude, feature, isi, correlogram = ( + gui.get_view(name) + for name in ( + 'EvidenceAmplitudeView', + 'FeatureView', + 'SampledISIView', + 'SampledCorrelogramView', + ) + ) + gui.splitDockWidget(amplitude.dock, feature.dock, Qt.Vertical) + gui.splitDockWidget(amplitude.dock, isi.dock, Qt.Horizontal) + gui.splitDockWidget(isi.dock, correlogram.dock, Qt.Vertical) + gui.resizeDocks([amplitude.dock, isi.dock], [1000, 1000], Qt.Horizontal) + gui.resizeDocks([amplitude.dock, feature.dock], [550, 550], Qt.Vertical) + gui.resizeDocks([isi.dock, correlogram.dock], [550, 550], Qt.Vertical) + _wait_for_render() + windows = controller.evidence_windows + times = controller.model.spike_samples + counts = [ + int(np.searchsorted(times, end) - np.searchsorted(times, start)) + for start, end in windows + ] + best_window = int(np.argmax(counts)) + controller.inspect_evidence_window(best_window) + selected = [0] if stability else [0, 2] + controller.supervisor.select(selected) + controller.supervisor.block() + _wait_for_render() + if stability: + filename = 'long-recording-overview.png' + else: + filename = 'long-recording-evidence.png' + destination = output_dir / filename + _capture(gui, destination) + print( + f'{destination} ({gui.width()}x{gui.height()}, window {best_window}, ' + f'{counts[best_window]} evidence spikes)' + ) + finally: + gui.close() + controller.close() + + +def main(): + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument('--output-dir', type=Path, default=DEFAULT_OUTPUT) + args = parser.parse_args() + args.output_dir.mkdir(parents=True, exist_ok=True) + app = QApplication.instance() or QApplication(sys.argv[:1]) + + with tempfile.TemporaryDirectory(prefix='phy-long-recording-screenshots-') as temporary: + root = Path(temporary) + params, intervals = _make_source(root / 'source') + bounded = prepare_large( + params, + root / 'bounded', + duration_seconds=SAMPLE_RATE * 3600 * HOURS / SAMPLE_RATE, + valid_intervals=intervals, + max_spikes=20_000, + max_bytes=268_435_456, + window_seconds=30, + stratum_seconds=3600, + seed=0, + batch_size=50_000, + bin_seconds=1800, + ) + _capture_views(bounded, root / 'config-stability', args.output_dir, stability=True) + _capture_views(bounded, root / 'config-evidence', args.output_dir, stability=False) + app.quit() + + +if __name__ == '__main__': + main() From e189567852ce71a4647f1b74dd153e0cd05e8624 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 13:12:01 +0200 Subject: [PATCH 20/53] Release mapped readers before intentional corruption in Windows tests --- phy/apps/large_recording/tests/test_curation.py | 1 + phy/apps/large_recording/tests/test_replay.py | 4 +++- 2 files changed, 4 insertions(+), 1 deletion(-) diff --git a/phy/apps/large_recording/tests/test_curation.py b/phy/apps/large_recording/tests/test_curation.py index 2aa748a6d..9997bc9cf 100644 --- a/phy/apps/large_recording/tests/test_curation.py +++ b/phy/apps/large_recording/tests/test_curation.py @@ -144,6 +144,7 @@ def test_checkpoint_corruption_is_rejected(tmp_path): def test_bound_base_corruption_is_rejected(tmp_path): _, session = make_session(tmp_path) + session.close() shutil.copyfile(session.path / 'spike_times.npy', session.path / BASE_ASSIGNMENTS) with pytest.raises(ValueError, match='integrity'): BoundedSession(session.path) diff --git a/phy/apps/large_recording/tests/test_replay.py b/phy/apps/large_recording/tests/test_replay.py index fefeb52ab..408f536fd 100644 --- a/phy/apps/large_recording/tests/test_replay.py +++ b/phy/apps/large_recording/tests/test_replay.py @@ -45,11 +45,12 @@ def test_source_revision_and_feature_identity_are_independently_bound(tmp_path): source, session = make_session(tmp_path) session.save() clusters = source.arrays['spike_clusters.npy'].copy() + amplitudes = source.arrays['amplitudes.npy'].copy() + source.close() clusters[0] = 2 np.save(source.path / 'spike_clusters.npy', clusters) with pytest.raises(ValueError, match='revision'): apply_curation(source.params_path, session.path, tmp_path / 'wrong_revision') - amplitudes = source.arrays['amplitudes.npy'].copy() amplitudes[0] += 1 np.save(source.path / 'amplitudes.npy', amplitudes) with pytest.raises(ValueError, match='identity'): @@ -132,6 +133,7 @@ def test_replay_preserves_empty_split_children_and_allocator_lineage(tmp_path): def test_bounded_threshold_attribute_must_match_exact_source_rows(tmp_path): source, session = make_session(tmp_path) session.save() + session.close() # Even a manifest that does not hash this optional attribute must not allow # evidence values different from those used by the full-data predicate. values = np.load(session.path / 'amplitudes.npy') From 94adf85227d94d19a2b295503653df1cf8414016 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 13:12:35 +0200 Subject: [PATCH 21/53] Clarify stability screenshot marks all retained evidence windows --- docs/long-recordings.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/long-recordings.md b/docs/long-recordings.md index 03596d771..454a372db 100644 --- a/docs/long-recordings.md +++ b/docs/long-recordings.md @@ -16,7 +16,7 @@ gaps from periods with no spikes. Intervals use half-open sample coordinates The screenshots below show the actual bounded GUI views using a deterministic synthetic eight-hour sorting. The overview plots full-duration rates and available source means; gray marks the synthetic acquisition gap and cyan marks -the inspected evidence window. The evidence view places windowed amplitudes at +the retained evidence windows. The evidence view places windowed amplitudes at top left, sampled ISI at top right, sampled correlograms at middle right, and features below. They illustrate the interface and its sampling context; they are not biological data or scientific examples. From 4c8e74f3627486679e87aec8302ad351d1b77516 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Tue, 13 Oct 2026 14:13:46 +0200 Subject: [PATCH 22/53] Label evidence-window time axes and display absolute recording range --- docs/changelog.md | 2 ++ docs/images/long-recording-evidence.png | Bin 211062 -> 217430 bytes docs/long-recordings.md | 6 +++-- phy/apps/large_recording/adapter.py | 8 +++++++ .../tests/test_gui_lifecycle.py | 19 +++++++++++++++ phy/apps/large_recording/views.py | 22 ++++++++++++++++++ 6 files changed, 55 insertions(+), 2 deletions(-) diff --git a/docs/changelog.md b/docs/changelog.md index 1fadb9629..f18f7b05f 100644 --- a/docs/changelog.md +++ b/docs/changelog.md @@ -22,6 +22,8 @@ behavior they verify rather than listed separately. - Bounded saves use validated atomic generations and reject conflicting saves from stale sessions. Unsupported selected-row splits are blocked. - Sparse cluster IDs no longer require dense allocations during clustering. +- Bounded amplitude plots label seconds from window start and display the + window's recording-time range above the plot. ### Documentation diff --git a/docs/images/long-recording-evidence.png b/docs/images/long-recording-evidence.png index f7649941ce5c4ed8c950553bf6f723dda51d0abc..294d03924c4f24cab645ea6c6af1ae6cd311d969 100644 GIT binary patch literal 217430 zcmb5V1yq%5*ENiKlo08VmJR{wF6r)0>F$yiC1g|5CEeX!N_Tg6cQ@bVInSf#eZMjO zZ~XT-N8PaZy{}knt~uwm?f_Y7kymioa8OWCuf#+J<)NTpn4qBkDuHXqNB?^0r0vgGLja|?m8J2@vhOr z2M78b%aT^ijw+vbcy{biw37{|UFIdkq&lDcx$)zwxP&wvrDuAuV-w?EBk||h3ym6A zS4_M-apExHy)Da}p@?IXX0)t~U`nl7to+T(!d^n3udVMA-NWTpvczF{lQfoxGD~yA zQfaQk!S;A@b)B`gs*go^!M1o{7D6WNu!2p4`rpCoj10TCGK1{Tazou~OCW$N1KJ zKLG{OLfgpGi>{WRmW6#Z*v_v@PxuvmCtTCuE(Br1NEfD=ipm}DUqlz)^mCqX&pJFM zn_nDu7+NTHA=JRtydz4s!k@}BoIUn$iX_({3Vy`S9=77Mwx>Z?+UE$igmz?Ejojw* 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zyQ7a52=z&9b?rgJavx#srm~cv0Rll>8yox?!tiEN%vmzc$U>X!yd&4#S?GiyA!%St z%y|kpEPuafV*n)hkdNAKad?Dt@sTCE^Uqn(7L_gvSG0dUb@NS`FD_nOK^L-$<{0w& zI_0X;z<`{Bhp3XnN@SZ+pmi+hiHzI%G|LZjV17O>-*<;wT;FiY{nw?xcn-lnist_e*Z!Jy1Br7M`T-S}{?o#r z?*I2iP45Io*5B6un=_tNR(U@L&Tjn|1Ju#~rr}3%o~zD(9fJKIhxmWvZiJcN2TQ%4 RFZhcH4HX^bDn*-!{{g_|pojnf diff --git a/docs/long-recordings.md b/docs/long-recordings.md index 454a372db..b5bf8d424 100644 --- a/docs/long-recordings.md +++ b/docs/long-recordings.md @@ -100,8 +100,10 @@ evidence windows, and acquisition gaps. Missing measurements and units without evidence remain visible as unavailable. Evidence Amplitude shows raw source scalar amplitudes from the currently -selected evidence window. The Feature view also uses window-relative seconds; -both views label the current window and reset their time origin when it changes. +selected evidence window. The Feature view also uses window-relative seconds. +The amplitude plot labels this axis as **Seconds from window start** and shows +the window's recording-time range above the plot. +Both views label the current window and reset their time origin when it changes. To inspect another retained window, choose **View > Inspect evidence window** and enter its zero-based index. Unit Stability keeps the full-recording time context visible while you inspect individual windows. diff --git a/phy/apps/large_recording/adapter.py b/phy/apps/large_recording/adapter.py index e4d332008..cc5a351ac 100644 --- a/phy/apps/large_recording/adapter.py +++ b/phy/apps/large_recording/adapter.py @@ -303,6 +303,11 @@ def create_evidence_amplitude_view(self): split_is_eligible=lambda: False, ) view.ex_status = self._window_status() + view.set_window_context( + self.evidence_window_index, + start / self.model.sample_rate, + end / self.model.sample_rate, + ) return view def _window_status(self): @@ -324,6 +329,9 @@ def inspect_evidence_window(self, index): view.ex_status = self._window_status() if isinstance(view, EvidenceAmplitudeView): view.duration = (end - start) / self.model.sample_rate + view.set_window_context( + index, start / self.model.sample_rate, end / self.model.sample_rate + ) view.canvas.panzoom.reset() if view.cluster_ids: view.plot() diff --git a/phy/apps/large_recording/tests/test_gui_lifecycle.py b/phy/apps/large_recording/tests/test_gui_lifecycle.py index c6d951b38..d2286b9eb 100644 --- a/phy/apps/large_recording/tests/test_gui_lifecycle.py +++ b/phy/apps/large_recording/tests/test_gui_lifecycle.py @@ -11,6 +11,25 @@ from phy.apps.template.gui import TemplateController +def test_window_time_labels_follow_navigation(qtbot, tmp_path): + _, controller = make_controller(tmp_path, sparse=True) + gui = controller.create_gui(default_views=['EvidenceAmplitudeView'], do_prompt_save=False) + try: + view = gui.get_view('EvidenceAmplitudeView') + assert view.time_axis_label.text() == 'Seconds from window start' + initial = view.window_label.text() + controller.inspect_evidence_window(1) + start, end = controller.current_evidence_window / controller.model.sample_rate + assert view.window_label.text() == ( + f'Evidence window 1 | Recording time: {start:.3f}–{end:.3f} s' + ) + assert view.window_label.text() != initial + assert view.duration == end - start + finally: + gui.close() + controller.close() + + def test_gui_observer_mutation_rolls_back_views_selection_and_journal(qtbot, tmp_path): _, controller = make_controller(tmp_path) gui = controller.create_gui(default_views=[], do_prompt_save=False) diff --git a/phy/apps/large_recording/views.py b/phy/apps/large_recording/views.py index d19d5190e..c96fabf09 100644 --- a/phy/apps/large_recording/views.py +++ b/phy/apps/large_recording/views.py @@ -1,6 +1,7 @@ """Explicitly sampled statistics and window-relative amplitude views.""" from phy.cluster.views import AmplitudeView, CorrelogramView, ISIView +from phy.gui.qt import QLabel, Qt class SampledISIView(ISIView): @@ -14,6 +15,27 @@ class SampledCorrelogramView(CorrelogramView): class EvidenceAmplitudeView(AmplitudeView): """Raw source amplitude in an explicitly rebased evidence window.""" + window_caption = 'Recording time unavailable' + + def set_window_context(self, index, start_seconds, end_seconds): + self.window_caption = ( + f'Evidence window {index} | Recording time: {start_seconds:.3f}–{end_seconds:.3f} s' + ) + if hasattr(self, 'window_label'): + self.window_label.setText(self.window_caption) + + def attach(self, gui): + super().attach(gui) + layout = self.dock.widget().layout() + self.window_label = QLabel(self.window_caption) + self.window_label.setWordWrap(True) + self.time_axis_label = QLabel('Seconds from window start') + for label in (self.window_label, self.time_axis_label): + label.setAlignment(Qt.AlignCenter) + label.setStyleSheet('color: white; background-color: black; padding: 4px;') + layout.insertWidget(0, self.window_label) + layout.insertWidget(layout.count() - 1, self.time_axis_label) + def _get_data_bounds(self, bunchs): if not any(len(bunch.amplitudes) for bunch in bunchs): return (0, 0, self.duration, 1) From 0f204af5b344456adbf2a8cf71c13c88f6b30cf9 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 17:54:53 +0200 Subject: [PATCH 23/53] docs: define explicit large-recording time coordinates --- design/large-recording-time-coordinates.md | 240 +++++++++++++++++++++ 1 file changed, 240 insertions(+) create mode 100644 design/large-recording-time-coordinates.md diff --git a/design/large-recording-time-coordinates.md b/design/large-recording-time-coordinates.md new file mode 100644 index 000000000..451790679 --- /dev/null +++ b/design/large-recording-time-coordinates.md @@ -0,0 +1,240 @@ +# Event coordinates and acquisition exposure + +This document defines the narrow time-coordinate extension for the AIND export +reported against PR #1428. It supplements the +[large-recording contract](large-recording-curation.md) and its +[integration plan](large-recording-integration-plan.md). It does not authorize +changes to an upstream export or establish that this particular chronic +recording is ready for curation. + +## Supported coordinates + +Phy-facing event times are nonnegative integer coordinates on one monotonic +axis. Two explicitly distinguished meanings are supported: + +- `acquisition_samples`: sample indices on the acquisition axis supported by the + original contract. +- `elapsed_ticks`: elapsed seconds from the source recording's time origin, + multiplied by a declared tick frequency and quantized to integers. Gaps remain + visible on this axis. A tick is a time coordinate, not a recorded voltage + sample. + +The optional producer declaration is a Python dictionary in `params.py`: + +```python +sample_rate = 30000.0 +waveform_sample_rate = 30000.0 +time_base = {'kind': 'elapsed_ticks', 'ticks_per_second': 30000.0} +num_samples = 12188787510 +# Illustrative values only; the producer must supply authoritative exposure. +valid_intervals = [[0, 100000], [200000, 12188787510]] +``` + +The same declaration can occur as `recording.time_base` in +`_phy_spikes_subset.manifest.json`. If both locations declare it, they must +agree. `kind` is one of the two strings above; `ticks_per_second` is positive +and finite. Unknown kinds and conflicting declarations are errors. + +For this implementation, `ticks_per_second`, `params.py`'s `sample_rate`, +`waveform_sample_rate` when declared, and the waveform manifest's +`recording.sampling_frequency_hz` when declared must be equal. This keeps the +existing loader and waveform time axes correct for the reported 30 kHz export. +Supporting unequal event tick and physical waveform sample frequencies requires +separate waveform-axis plumbing and is outside this extension. + +The physical and event frequencies nevertheless have different meanings. In +elapsed mode, `sample_rate` converts event ticks to seconds; the waveform +frequency describes the spacing between samples inside each stored waveform. +Clock drift or a piecewise clock map must not stretch the waveform's local +sample axis. + +Without an explicit declaration, retain the original acquisition-sample +behavior and identity representation for existing sources. A source containing +`timestamps.json` must provide an explicit time-base declaration before this +bounded workflow accepts it. This is an intentional conservative admission +rule: the file's presence signals acquisition metadata whose exposure semantics +have not been established by the legacy defaults. It is not proof that every +such source actually has mixed coordinates. The error must explain how to +declare authoritative coordinates and exposure; it must not parse the JSON and +guess a conversion. + +## Bounds and exposure + +For both kinds, the legacy names `num_samples` and `valid_intervals` describe +the canonical event axis: + +- `num_samples` is its exclusive positive integer upper bound. In elapsed mode + it is a tick extent, not the number of acquired frames. +- `valid_intervals` contains ordered, disjoint, nonempty integer `[start, end)` + intervals inside that extent. They declare valid acquisition exposure on the + same event axis. +- Every spike belongs to a valid interval. Time ties and original source row + order remain allowed and preserved. +- Exposure in seconds is the sum of interval lengths divided by the tick + frequency, counted once across units. Gaps and filler are not zero firing. + +An explicit elapsed-time source needs authoritative exposure rather than a +silent `[0, num_samples)` default. The producer must exclude missing acquisition +time and filler that does not contain usable recording data. If sorting spikes +remain in excluded intervals, reject the source with an actionable error. Do +not silently drop, move or relabel them: these actions change source row +identity or scientific interpretation. A future flagged-spike policy needs its +own full-data counting, selection and replay contract. + +The upper bound must include the producer's final representable event tick. +An endpoint mapping may describe the last sample rather than an exclusive end; +do not blindly substitute its rounded clock span for `num_samples`. A physical +pipeline frame count can be retained as separately named producer provenance, +for example `recording.num_frames`, but cannot also define the elapsed extent. +`--duration` remains a consistency check and does not override conflicting +producer metadata. + +Reject a first or last source spike outside the declared extent before a full +validation/hash scan. Still perform the complete batched validation for internal +reversals, out-of-range rows and invalid exposure membership. The early check +is a diagnostic improvement, not a replacement for validation. + +## Waveform and window sidecars + +In explicit elapsed mode, the waveform manifest must declare the coordinates of +each present time-bearing sidecar: + +```json +{ + "format": "phy_spikes_subset", + "format_version": 1, + "recording": { + "sampling_frequency_hz": 30000.0, + "num_samples": 12188787510, + "time_base": {"kind": "elapsed_ticks", "ticks_per_second": 30000.0}, + "window_bounds_coordinates": "elapsed_ticks", + "sample_index_coordinates": "elapsed_ticks" + } +} +``` + +The example omits `valid_intervals`; a real elapsed export must declare the +authoritative intervals in `params.py` or `recording`, with agreement when both +declare them. `window_bounds_coordinates` is required when window bounds are +present; `sample_index_coordinates` is required when sample indices are +present. Their values equal `time_base.kind`. A contradictory +`recording.frame_coordinates` declaration is an error, not an invitation to +reinterpret an array. Existing producer prose describing frames before +clock conversion must be corrected explicitly for an elapsed export. + +The sidecars have these meanings and validation obligations: + +- `_phy_spikes_subset.window_bounds.npy`: `int64[W, 2]` event-coordinate + `[start, end)` intervals, ordered and nonoverlapping, within the declared + extent and valid exposure. A window cannot bridge an unsupported interruption. +- `_phy_spikes_subset.window_types.npy`: `uint8[W]`, with `0` survey and `1` + rescue. +- `_phy_spikes_subset.window_strata.npy`: `int32[W]`, nonnegative survey + stratum IDs and `-1` for rescue. The three window arrays are aligned. +- Optional `_phy_spikes_subset.sample_index.npy`: `int64[N_waveforms]`, aligned + with waveform rows, containing canonical event-center coordinates. For every + waveform row `w`, it equals + `spike_times[subset_spikes[w]]`. It is not a source spike row ID or a raw-file + sample offset. + +The established waveform triplet remains authoritative for actual waveform +availability. A window denotes potential evidence, not a waveform for every +spike in it. When sidecars are supplied as producer evidence, waveform centers +must lie in the declared window union. Reject malformed sidecars rather than +falling back to an independently generated plan that hides the error. + +The existing row spaces remain unchanged: full spike row `g`, bounded spike row +`b`, waveform row `w`. Remap waveform row IDs through the selected full-to-bounded +mapping, and gather sample-index, waveform and channel rows together. Replay +preserves the original full arrays byte for byte. Supporting a sample-index +sidecar that intentionally remains in pipeline-frame coordinates is a separate +future provenance extension; this implementation does not infer its mapping. + +Preparation should prefer validated producer evidence windows while keeping +whole windows, the configured spike/byte budgets, and deterministic omission +reporting. Do not enlarge memory or disk budgets merely because many waveforms +were exported. Report the source, retained and omitted waveform counts so a +small bounded package cannot appear to preserve the complete reservoir. + +## Raw voltage access + +Elapsed event ticks must never flow into raw voltage indexing. This first +extension rejects an elapsed source with a real raw-data path until a separate +explicit event-to-raw-frame mapping and its validation exist. Absent raw paths, +including an export's literal `None` sentinel, must be recognized consistently. +The bounded package continues to use stored waveforms without raw data. + +Do not replace raw indices with elapsed ticks in an exporter and then claim +ordinary raw-trace loading works. Converting waveform centers for this contract +does not convert the physical voltage stream or establish a reversible map. + +## Identity, replay and metadata preservation + +Explicit time-base metadata participates in coordinate identity alongside the +canonical extent, exposure, immutable arrays, channel geometry and existing +acquisition provenance. Changing the coordinate kind, tick frequency or +exposure must invalidate a bounded package prepared against different metadata. +Keep the legacy identity shape unchanged for sources without a declaration. + +Carry explicit metadata into bounded `params.py` and the bounded manifest. +Validate it when reopening and replaying, rather than trusting a free-form field +that is never consumed. Preserve it in complete replay outputs and their +lineage. Repreparing a replay output must produce the same coordinate identity. +Assignment revisions remain distinct from that identity. Coordinate changes +cannot be repaired by retaining a journal against an obsolete source identity. + +Optional upstream sampling-policy windows do not by themselves change immutable +spike identity, but their validation and package hashes must bind the exact +evidence that the GUI uses. A waveform-aligned sample-index array does carry +immutable row provenance and must be included in the corresponding hashes and +copy/gather paths. + +## Why Phy does not convert the supplied timestamps JSON + +The supplied file contains 420 frame/clock endpoints for 210 pieces. Frame +endpoints increase strictly; clock endpoints are nondecreasing with 15 equal +adjacent pairs. Its metadata additionally reports underlying backward timestamp +steps that are not represented by those endpoint pairs. Consequently, the +endpoint map does not establish an invertible or sample-accurate raw clock. + +Interpolation can reproduce the reported exported spike ticks without proving +the exposure between endpoints. Piecewise dropped samples, filler and true +gaps need producer knowledge. Mapping just the endpoints of a window that +crosses a gap would incorrectly declare the gap observed. The reported +`total_dropped_within_pieces_s` also does not locate every unsupported interval. +Neither the apparent 30 kHz unit nor monotonic exported spikes makes elapsed +ticks equivalent to physical acquisition samples. + +The producer owns clock conversion and the final validity mask. Phy validates +the resulting explicit contract. Acquisition logs remain necessary to resolve +the reported interruptions and the 35 sorting spikes inside filler before +declaring this export suitable for exposure-aware statistics. + +## Regression and acceptance gates + +Before considering the extension complete, require concrete checks for: + +1. Unchanged legacy preparation, identity, summaries, GUI behavior and replay; + explicit acquisition-sample sources also round-trip. +2. Explicit elapsed data with tied spikes, long `int64` coordinates, gaps and + endpoint boundaries; exact independently calculated full counts and exposure. +3. Missing/conflicting time declarations, unsupported rates, raw paths, + contradictory frame metadata, and first/last out-of-bounds spikes; errors + identify the conflicting coordinate meanings before the expensive scan. +4. Spikes in filler/excluded exposure, internal reversals and invalid interval + boundaries; none are silently dropped or accepted as valid exposure. +5. Malformed or partially supplied producer sidecars, invalid dtypes/lengths, + overlapping windows, windows crossing gaps, waveform centers outside windows, + and sample-index values inconsistent with their source spike rows. +6. Budget-constrained producer-window selection with exact retained/omitted + waveform reporting and deterministic complete-window selection. +7. Prepare, merge/label, save/reopen, replay and reprepare preserving explicit + metadata, immutable rows and waveform alignment. Mutating time metadata or + sample-index provenance must invalidate the appropriate identity/checksum. +8. Window-local ISI/CCG calculations excluding unsupported cross-boundary pairs, + physical waveform sample spacing, and no elapsed-coordinate raw indexing. + +These establish software behavior. They do not establish that endpoint-derived +exposure is scientifically precise or that the finite waveform evidence is +sufficient for chronic unit identity. Domain-curator acceptance remains required +by the existing validation plan. From acc18c95273ef8c0fd0ad2a9308c4c4d31675bb2 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 17:53:25 +0200 Subject: [PATCH 24/53] Fail early on source clock endpoint mismatches --- phy/apps/large_recording/source.py | 11 +++++++++++ phy/apps/large_recording/tests/test_source.py | 17 +++++++++++++++++ 2 files changed, 28 insertions(+) diff --git a/phy/apps/large_recording/source.py b/phy/apps/large_recording/source.py index 07bacf21f..237596175 100644 --- a/phy/apps/large_recording/source.py +++ b/phy/apps/large_recording/source.py @@ -427,6 +427,17 @@ def validate(self): array = _vector(self.arrays[name], name) if not np.issubdtype(array.dtype, np.integer): raise ValueError(f'{name} must contain integer coordinates.') + times = _vector(self.arrays['spike_times.npy'], 'spike_times.npy') + # Monotonic sources expose a clock mismatch at their endpoints. Check + # these before scanning hundreds of millions of rows or hashing assets; + # the complete monotonicity and bounds validation below remains required. + if len(times) and (times[0] < 0 or times[-1] >= self.num_samples): + raise ValueError( + 'Spike time endpoints fall outside declared num_samples; check that ' + 'spike_times.npy, num_samples, valid_intervals and waveform sidecars ' + 'use the same time base. Convert producer metadata to canonical ' + 'coordinates before preparing this sorting.' + ) previous = -1 for batch in self.iter_batches(): times = batch['spike_times.npy'] diff --git a/phy/apps/large_recording/tests/test_source.py b/phy/apps/large_recording/tests/test_source.py index 05578bf9d..e2ccf0ab6 100644 --- a/phy/apps/large_recording/tests/test_source.py +++ b/phy/apps/large_recording/tests/test_source.py @@ -293,3 +293,20 @@ def test_exclusive_publish_preserves_racing_empty_destination(tmp_path): publish_directory(staged, destination) assert not staged.exists() assert (destination / 'payload').read_text() == 'complete' + + +def test_clock_endpoint_mismatch_fails_before_full_scan_or_hash(tmp_path, monkeypatch): + from phy.apps.large_recording import source as module + + params = make_sorting(tmp_path / 'source') + times = np.load(params.parent / 'spike_times.npy') + times[-1] = 100 + np.save(params.parent / 'spike_times.npy', times) + + def unexpected(*args, **kwargs): + pytest.fail('Clock endpoint mismatch must fail before scans or hashing.') + + monkeypatch.setattr(Source, 'iter_batches', unexpected) + monkeypatch.setattr(module, 'hash_file', unexpected) + with pytest.raises(ValueError, match='same time base'): + Source(params) From 92c5421f65580d787f3066546006331b039f1fb0 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 17:55:50 +0200 Subject: [PATCH 25/53] Require explicit canonical timing contracts for elapsed exports --- phy/apps/large_recording/replay.py | 11 +- phy/apps/large_recording/source.py | 103 +++++++++++- phy/apps/large_recording/tests/test_replay.py | 46 ++++++ phy/apps/large_recording/tests/test_source.py | 156 ++++++++++++++++++ 4 files changed, 312 insertions(+), 4 deletions(-) diff --git a/phy/apps/large_recording/replay.py b/phy/apps/large_recording/replay.py index 96c39ba8c..7d821ec9a 100644 --- a/phy/apps/large_recording/replay.py +++ b/phy/apps/large_recording/replay.py @@ -16,7 +16,7 @@ interpret_events, project_assignments, ) -from .source import PER_SPIKE, Source, close_array, publish_directory +from .source import PER_SPIKE, Source, _has_raw_paths, close_array, publish_directory def _merge_mapping(unit_ids, events): @@ -142,12 +142,17 @@ def _apply_curation(source, session, output_dir, batch_size): upstream_manifest = source.path / '_phy_spikes_subset.manifest.json' if upstream_manifest.exists(): shutil.copyfile(upstream_manifest, stage / upstream_manifest.name) + if source.time_base is not None and source.timestamps_path.exists(): + shutil.copyfile(source.timestamps_path, stage / 'timestamps.json') # Preserve source params semantics and make external raw paths absolute. # The full export can contain no raw traces; immutable array rows suffice. dat_path = source.params.get('dat_path') - if dat_path: + if _has_raw_paths(dat_path): raw_paths = dat_path if isinstance(dat_path, (list, tuple)) else [dat_path] - resolved = [str((source.path / raw).resolve()) for raw in raw_paths] + resolved = [ + str((source.path / raw).resolve()) if _has_raw_paths(raw) else raw + for raw in raw_paths + ] dat_path = resolved if isinstance(dat_path, (list, tuple)) else resolved[0] with (stage / 'params.py').open('a', encoding='utf8') as stream: stream.write(f'\nnum_samples = {source.num_samples!r}\n') diff --git a/phy/apps/large_recording/source.py b/phy/apps/large_recording/source.py index 237596175..fe3389c40 100644 --- a/phy/apps/large_recording/source.py +++ b/phy/apps/large_recording/source.py @@ -48,6 +48,7 @@ '_phy_spikes_subset.waveforms.npy', ) ) +WAVEFORM_SIDECARS = frozenset(('_phy_spikes_subset.sample_index.npy',)) WINDOW_SIDECARS = frozenset( ( '_phy_spikes_subset.window_bounds.npy', @@ -173,6 +174,26 @@ def _metadata(path): return result +def _time_base(value): + """Normalize an explicit producer clock without inferring conversions.""" + if not isinstance(value, dict) or set(value) != {'kind', 'ticks_per_second'}: + raise ValueError('time_base must declare kind and ticks_per_second.') + if value['kind'] not in ('acquisition_samples', 'elapsed_ticks'): + raise ValueError('time_base.kind must be acquisition_samples or elapsed_ticks.') + rate = value['ticks_per_second'] + if isinstance(rate, bool) or not isinstance(rate, (int, float)): + raise ValueError('time_base.ticks_per_second must be positive and finite.') + rate = float(rate) + if not np.isfinite(rate) or rate <= 0: + raise ValueError('time_base.ticks_per_second must be positive and finite.') + return {'kind': value['kind'], 'ticks_per_second': rate} + + +def _has_raw_paths(dat_path): + paths = dat_path if isinstance(dat_path, (list, tuple)) else [dat_path] + return any(path is not None and str(path).strip() not in ('', 'None') for path in paths) + + class Source: """Read source arrays in batches without constructing a GUI model. @@ -224,6 +245,43 @@ def _initialize( upstream_rate = recording.get('sampling_frequency_hz', self.sample_rate) if upstream_rate != self.sample_rate: raise ValueError('Waveform manifest sampling rate disagrees with params.py.') + self.upstream_recording = recording + declared_clocks = [ + _time_base(container['time_base']) + for container in (self.params, recording) + if 'time_base' in container + ] + if len(declared_clocks) == 2 and declared_clocks[0] != declared_clocks[1]: + raise ValueError('time_base disagrees between params and waveform manifest.') + self.time_base = declared_clocks[0] if declared_clocks else None + self.timestamps_path = self.path / 'timestamps.json' + if self.time_base is None and self.timestamps_path.exists(): + raise ValueError( + 'timestamps.json requires an explicit time_base in params.py or manifest ' + 'recording. Convert num_samples, valid_intervals and waveform sidecars ' + 'to the spike_times.npy coordinates; automatic timestamp mapping is unsupported.' + ) + if self.time_base is not None: + if self.time_base['ticks_per_second'] != self.sample_rate: + raise ValueError('time_base ticks_per_second must equal sample_rate.') + for container in (self.params, recording): + if container.get('waveform_sample_rate', self.sample_rate) != self.sample_rate: + raise ValueError('waveform_sample_rate must equal sample_rate.') + kind = self.time_base['kind'] + if recording.get('frame_coordinates', kind) != kind: + raise ValueError('recording.frame_coordinates must equal time_base.kind.') + for suffix, field in ( + ('window_bounds', 'window_bounds_coordinates'), + ('sample_index', 'sample_index_coordinates'), + ): + if (self.path / f'_phy_spikes_subset.{suffix}.npy').exists(): + coordinates = recording.get(field) + if coordinates is None and kind == 'acquisition_samples': + coordinates = kind + if coordinates != kind: + raise ValueError(f'recording.{field} must equal time_base.kind.') + if kind == 'elapsed_ticks' and _has_raw_paths(self.params.get('dat_path')): + raise ValueError('elapsed_ticks cannot reference raw dat_path traces.') if self.params.get('num_segments', recording.get('num_segments', 1)) != 1: raise ValueError('Only a single monotonic acquisition segment is supported.') duration_samples = None @@ -278,6 +336,12 @@ def _initialize( raise ValueError('Explicit valid_intervals disagree with acquisition metadata.') if valid_intervals is None: valid_intervals = declared_intervals + if ( + self.time_base is not None + and self.time_base['kind'] == 'elapsed_ticks' + and valid_intervals is None + ): + raise ValueError('elapsed_ticks requires explicit authoritative valid_intervals.') intervals = [[0, self.num_samples]] if valid_intervals is None else valid_intervals raw_intervals = np.asarray(intervals) if raw_intervals.ndim != 2 or raw_intervals.shape[1] != 2 or not len(raw_intervals): @@ -293,8 +357,19 @@ def _initialize( raise ValueError( 'valid_intervals must be ordered, disjoint integer acquisition samples.' ) + sample_index_path = self.path / '_phy_spikes_subset.sample_index.npy' + if ( + self.time_base is None + and sample_index_path.exists() + and recording.get('sample_index_coordinates', 'acquisition_samples') + != 'acquisition_samples' + ): + raise ValueError( + 'Legacy waveform sample_index coordinates must be acquisition_samples; ' + 'declare an explicit time_base for elapsed_ticks.' + ) names = {p.name for p in self.path.glob('*.npy')} - unknown = names - PER_SPIKE - STATIC - WAVEFORMS - WINDOW_SIDECARS + unknown = names - PER_SPIKE - STATIC - WAVEFORMS - WAVEFORM_SIDECARS - WINDOW_SIDECARS # Replay lineage and original optional sidecars are retained; bounded # outputs deliberately cannot be used as full-source sorting inputs. if unknown: @@ -370,6 +445,10 @@ def _initialize( }, 'arrays': {name: hash_file(self.path / name) for name in immutable}, } + if self.time_base is not None: + self.identity['time_base']['contract'] = self.time_base.copy() + if self.timestamps_path.exists(): + self.identity['time_base']['timestamps_sha256'] = hash_file(self.timestamps_path) self.identity['sha256'] = hash_json(self.identity) declared_source = info.get('source_sorting', {}) if not isinstance(declared_source, dict): @@ -464,6 +543,9 @@ def validate(self): waveforms = self.arrays.keys() & WAVEFORMS if waveforms and waveforms != WAVEFORMS: raise ValueError('Stored waveforms require spikes, channels, and waveforms together.') + sample_index = self.arrays.get('_phy_spikes_subset.sample_index.npy') + if sample_index is not None and not waveforms: + raise ValueError('Stored waveform sample_index requires the waveform triplet.') if waveforms: ids = self.arrays['_phy_spikes_subset.spikes.npy'] if ids.ndim != 1 or ids.dtype != np.dtype('int64'): @@ -478,6 +560,12 @@ def validate(self): or not np.issubdtype(channels.dtype, np.integer) ): raise ValueError('Stored waveform tensors and channels are not aligned.') + if sample_index is not None and ( + sample_index.ndim != 1 + or not np.issubdtype(sample_index.dtype, np.integer) + or len(sample_index) != len(ids) + ): + raise ValueError('Stored waveform sample_index must be an aligned integer vector.') last = -1 # Sparse-padding checks create temporary boolean arrays and gathers; # cap their tensor bytes independently of the source row batch size. @@ -493,6 +581,19 @@ def validate(self): or np.any(rows >= self.n_spikes) ): raise ValueError('Stored waveform row IDs must be sorted, unique source rows.') + if sample_index is not None: + coordinates = sample_index[start : start + waveform_batch] + if ( + np.any(coordinates < 0) + or np.any(coordinates >= self.num_samples) + or not np.array_equal( + coordinates, self.arrays['spike_times.npy'].reshape(-1)[rows] + ) + ): + raise ValueError( + 'Stored waveform sample_index must equal spike_times.npy at waveform ' + 'row IDs in canonical time-base coordinates.' + ) if len(rows): last = int(rows[-1]) if np.any((slots < -1) | (slots >= n_channels)): diff --git a/phy/apps/large_recording/tests/test_replay.py b/phy/apps/large_recording/tests/test_replay.py index 408f536fd..cc595e94b 100644 --- a/phy/apps/large_recording/tests/test_replay.py +++ b/phy/apps/large_recording/tests/test_replay.py @@ -142,3 +142,49 @@ def test_bounded_threshold_attribute_must_match_exact_source_rows(tmp_path): with pytest.raises(ValueError, match='does not match source rows'): apply_curation(source.params_path, session.path, tmp_path / 'bad_evidence') assert not (tmp_path / 'bad_evidence').exists() + + +@pytest.mark.parametrize('kind', ['acquisition_samples', 'elapsed_ticks']) +def test_replay_preserves_explicit_clock_metadata_and_timestamp_bytes(tmp_path, kind): + source, session = make_session(tmp_path) + params = source.params_path + intervals = source.valid_intervals.tolist() + rate = source.sample_rate + source.close() + session.close() + contract = {'kind': kind, 'ticks_per_second': rate} + params.write_text( + params.read_text() + + f'\ntime_base = {contract!r}\nvalid_intervals = {intervals!r}\ndat_path = "None"\n' + ) + timestamps = params.parent / 'timestamps.json' + timestamps.write_bytes(b'{"producer": "clock mapping", "gaps": [4, 8]}\n') + upstream_path = params.parent / '_phy_spikes_subset.manifest.json' + upstream = json.loads(upstream_path.read_text()) + upstream['recording'].update( + { + 'time_base': contract, + 'frame_coordinates': kind, + 'window_bounds_coordinates': kind, + 'sample_index_coordinates': kind, + } + ) + upstream_path.write_text(json.dumps(upstream)) + source = Source(params) + manifest_path = session.path / '_phy_curation_manifest.json' + manifest = json.loads(manifest_path.read_text()) + manifest['source']['identity'] = source.identity + manifest_path.write_text(json.dumps(manifest)) + from phy.apps.large_recording.curation import BoundedSession + + session = BoundedSession(session.path) + session.record_merge([0, 1], 100) + session.save() + output = apply_curation(params, session.path, tmp_path / 'curated') + assert (output / 'timestamps.json').read_bytes() == timestamps.read_bytes() + with Source(output / 'params.py') as curated: + assert curated.identity == source.identity + assert curated.time_base == contract + assert curated.params['dat_path'] == 'None' + session.close() + source.close() diff --git a/phy/apps/large_recording/tests/test_source.py b/phy/apps/large_recording/tests/test_source.py index e2ccf0ab6..d576c2e9f 100644 --- a/phy/apps/large_recording/tests/test_source.py +++ b/phy/apps/large_recording/tests/test_source.py @@ -310,3 +310,159 @@ def unexpected(*args, **kwargs): monkeypatch.setattr(module, 'hash_file', unexpected) with pytest.raises(ValueError, match='same time base'): Source(params) + + +def clock_manifest(params, recording): + path = params.parent / '_phy_spikes_subset.manifest.json' + path.write_text( + json.dumps( + { + 'format': 'phy_spikes_subset', + 'format_version': 1, + 'recording': recording, + } + ) + ) + return path + + +def test_explicit_clocks_and_legacy_identity(tmp_path): + params = make_sorting(tmp_path / 'source') + with Source(params) as source: + legacy = source.identity + assert source.time_base is None + # Existing exports preserve their exact identity schema. + assert set(legacy['time_base']) == {'sample_rate', 'num_samples', 'valid_intervals'} + contract = {'kind': 'acquisition_samples', 'ticks_per_second': 1} + params.write_text(params.read_text() + f'time_base = {contract!r}\n') + clock_manifest(params, {'time_base': contract}) + with Source(params) as source: + assert source.time_base == contract + assert source.identity != legacy + explicit = source.identity + timestamps = params.parent / 'timestamps.json' + timestamps.write_text('{"mapping": "producer-owned"}') + with Source(params) as source: + assert source.identity != explicit + assert source.identity['time_base']['timestamps_sha256'] == hash_file(timestamps) + timestamps.write_text('{"mapping": "changed"}') + with Source(params) as source: + assert source.identity['time_base']['timestamps_sha256'] == hash_file(timestamps) + + +@pytest.mark.parametrize( + 'contract', + [ + None, + {}, + {'kind': 'clock', 'ticks_per_second': 1}, + {'kind': 'elapsed_ticks', 'ticks_per_second': 0}, + {'kind': 'elapsed_ticks', 'ticks_per_second': float('inf')}, + {'kind': 'elapsed_ticks', 'ticks_per_second': True}, + {'kind': 'elapsed_ticks', 'ticks_per_second': '1'}, + ], +) +def test_invalid_explicit_clock_contract(tmp_path, contract): + params = make_sorting(tmp_path / 'source') + clock_manifest(params, {'time_base': contract}) + with pytest.raises(ValueError, match='time_base'): + Source(params) + + +def test_timestamps_without_contract_fail_before_arrays(tmp_path, monkeypatch): + params = make_sorting(tmp_path / 'source') + (params.parent / 'timestamps.json').write_text('{}') + monkeypatch.setattr(np, 'load', lambda *a, **kw: pytest.fail('Unexpected array read')) + with pytest.raises(ValueError, match='explicit time_base'): + Source(params) + + +@pytest.mark.parametrize( + 'failure', + [ + 'clock', + 'ticks', + 'waveform_rate', + 'manifest_rate', + 'frame_coordinates', + 'missing_intervals', + 'raw', + 'window_coordinates', + 'sample_coordinates', + ], +) +def test_explicit_elapsed_clock_rejects_ambiguous_producer_metadata(tmp_path, failure): + params = make_sorting(tmp_path / 'source') + contract = {'kind': 'elapsed_ticks', 'ticks_per_second': 1} + recording = {'time_base': contract, 'valid_intervals': [[0, 20]]} + if failure == 'clock': + params.write_text( + params.read_text() + + "time_base = {'kind': 'acquisition_samples', 'ticks_per_second': 1}\n" + ) + elif failure == 'ticks': + recording['time_base'] = {**contract, 'ticks_per_second': 2} + elif failure == 'waveform_rate': + params.write_text(params.read_text() + 'waveform_sample_rate = 2\n') + elif failure == 'manifest_rate': + recording['sampling_frequency_hz'] = 2 + elif failure == 'frame_coordinates': + recording['frame_coordinates'] = 'before any clock-time conversion' + elif failure == 'missing_intervals': + recording.pop('valid_intervals') + elif failure == 'raw': + params.write_text(params.read_text() + "dat_path = ['None', 'raw.bin']\n") + elif failure == 'window_coordinates': + np.save(params.parent / '_phy_spikes_subset.window_bounds.npy', [[0, 20]]) + else: + np.save(params.parent / '_phy_spikes_subset.sample_index.npy', [0, 1, 2, 14, 19]) + recording['sample_index_coordinates'] = 'acquisition_samples' + clock_manifest(params, recording) + with pytest.raises(ValueError): + Source(params) + + +@pytest.mark.parametrize('raw', [None, 'None', '', [], [None, 'None', '']]) +def test_elapsed_clock_canonical_sidecars_and_no_raw_sentinels(tmp_path, raw): + params = make_sorting(tmp_path / 'source') + contract = {'kind': 'elapsed_ticks', 'ticks_per_second': 1} + params.write_text(params.read_text() + f'dat_path = {raw!r}\n') + recording = { + 'time_base': contract, + 'valid_intervals': [[0, 7], [10, 20]], + 'frame_coordinates': 'elapsed_ticks', + 'window_bounds_coordinates': 'elapsed_ticks', + 'sample_index_coordinates': 'elapsed_ticks', + } + clock_manifest(params, recording) + np.save(params.parent / '_phy_spikes_subset.window_bounds.npy', [[0, 7], [10, 20]]) + np.save(params.parent / '_phy_spikes_subset.sample_index.npy', [0, 1, 2, 14, 19]) + with Source(params) as source: + assert source.time_base == contract + assert source.upstream_recording == recording + assert source.valid_intervals.tolist() == [[0, 7], [10, 20]] + + +@pytest.mark.parametrize( + 'values', + [ + [0, 1, 2, 14], + [[0], [1], [2], [14], [19]], + [0.0, 1.0, 2.0, 14.0, 19.0], + [-1, 1, 2, 14, 19], + [0, 1, 2, 14, 20], + [0, 1, 2, 13, 19], + ], +) +def test_waveform_sample_index_requires_exact_canonical_alignment(tmp_path, values): + params = make_sorting(tmp_path / 'source') + np.save(params.parent / '_phy_spikes_subset.sample_index.npy', values) + with pytest.raises(ValueError, match='sample_index'): + Source(params) + + +def test_waveform_sample_index_legacy_default_is_acquisition_samples(tmp_path): + params = make_sorting(tmp_path / 'source', columns=True) + np.save(params.parent / '_phy_spikes_subset.sample_index.npy', [0, 1, 2, 14, 19]) + with Source(params) as source: + assert '_phy_spikes_subset.sample_index.npy' in source.identity['arrays'] From 37a27656066403c2ce696371d21a47957192efb0 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 17:56:02 +0200 Subject: [PATCH 26/53] Declare replay fixture clock in bounded manifest --- phy/apps/large_recording/tests/test_replay.py | 1 + 1 file changed, 1 insertion(+) diff --git a/phy/apps/large_recording/tests/test_replay.py b/phy/apps/large_recording/tests/test_replay.py index cc595e94b..5910bdc82 100644 --- a/phy/apps/large_recording/tests/test_replay.py +++ b/phy/apps/large_recording/tests/test_replay.py @@ -174,6 +174,7 @@ def test_replay_preserves_explicit_clock_metadata_and_timestamp_bytes(tmp_path, manifest_path = session.path / '_phy_curation_manifest.json' manifest = json.loads(manifest_path.read_text()) manifest['source']['identity'] = source.identity + manifest['time_base'] = contract manifest_path.write_text(json.dumps(manifest)) from phy.apps.large_recording.curation import BoundedSession From 2fb9336fb4bfbf4e714e27f25ab48ca37a813e7c Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 17:56:38 +0200 Subject: [PATCH 27/53] Document elapsed tick export handoff --- design/aind-export-handoff.md | 90 +++++++++++++++++++++++++++++++++++ docs/changelog.md | 3 ++ docs/long-recordings.md | 79 ++++++++++++++++++++++-------- 3 files changed, 153 insertions(+), 19 deletions(-) create mode 100644 design/aind-export-handoff.md diff --git a/design/aind-export-handoff.md b/design/aind-export-handoff.md new file mode 100644 index 000000000..924c823f4 --- /dev/null +++ b/design/aind-export-handoff.md @@ -0,0 +1,90 @@ +# AIND export handoff for elapsed-time coordinates + +This note describes the producer work needed before an AIND export can use +Phy's explicit elapsed-tick contract. It is a handoff, not evidence that an +exporter change has been implemented or that a real export has passed +acceptance. The exporter source repository was not available in this worktree; +the steps below are proposed commit-sized changes, with no repository or branch +assumed. + +## Proposed exporter changes + +1. **Establish authoritative acquisition truth.** Obtain acquisition logs or + equivalent source records for clock origin, piece boundaries, dropped or + invalid spans, filler, and the physical recording extent. Resolve the + reported interruptions and the 35 sorting spikes reported inside filler. + Do not infer validity solely from spike times or endpoint interpolation. +2. **Emit a canonical event time axis.** For each sorting spike, emit a + nonnegative integer elapsed tick from the source time origin. Declare + `time_base = {'kind': 'elapsed_ticks', 'ticks_per_second': ...}`. Set + `num_samples` to the exclusive bound that includes the last representable + event tick; retain a physical frame count separately (for example as + `recording.num_frames`). Do not call a tick bound a frame count. +3. **Emit authoritative exposure.** Emit ordered, disjoint integer + `valid_intervals` in the same elapsed-tick coordinates, excluding missing + acquisition time and unusable filler. Ensure every emitted sorting spike + belongs to a valid interval. If any sorting rows fall outside exposure, + resolve them using acquisition truth upstream; never silently drop, move, or + relabel rows. +4. **Emit aligned waveform and window evidence.** Store + `_phy_spikes_subset.sample_index.npy` in canonical elapsed ticks, with each + value equal to `spike_times[subset_spikes[w]]`. Emit producer windows in + elapsed ticks, with boundaries that do not bridge unsupported intervals. + If the windows overlap, retain their original boundaries and ensure their + union accurately represents potential evidence. Add + `recording.sample_index_coordinates: "elapsed_ticks"` and + `recording.window_bounds_coordinates: "elapsed_ticks"` to the manifest when + those sidecars are present. Add `recording.time_base` and authoritative + `valid_intervals`; if `params.py` also declares them, keep the declarations + identical. +5. **Keep raw voltage semantics explicit.** Do not put elapsed ticks into raw + frame-index fields or claim ordinary raw-trace loading works. An export with + a real raw-data path is outside this contract until an explicit validated + event-to-frame mapping is supported. Stored waveform data can be exported + without a raw path. + +## Report evidence separately from verification + +The supplied export report describes 420 frame/clock endpoints for 210 pieces, +with strictly increasing frame endpoints, nondecreasing clock endpoints, and +15 equal adjacent clock pairs. It also reports backward timestamp steps that +are not represented by those endpoints. These are reported properties of the +export metadata, not independent verification of the corresponding acquisition +events. + +The reported `total_dropped_within_pieces_s` was not independently confirmed +against acquisition truth. Endpoint interpolation does not establish the exact +valid-time mask, a sample-accurate raw clock, or reversibility: equal clock +endpoints make the endpoint map non-invertible. The reported 35 spikes inside +filler likewise require independent confirmation and resolution. A 30 kHz +label, monotonic spike times, or a plausible endpoint-derived extent cannot +replace those checks. + +Changing Phy's sampling seed (including setting it to `42`) does not make an +export interoperable. The seed only selects among windows already defined in +Phy's coordinate system; it cannot recover producer acquisition boundaries, +map clock coordinates to frames, or determine which spans contain valid data. +Use compatible producer windows and an explicit coordinate and exposure +contract. + +## Acceptance evidence to return with an export + +Provide the exporter commit or reviewable diff, a short provenance note naming +the authoritative source for boundaries and filler, and machine-checkable +checks showing: + +- every exported spike's elapsed tick and valid-interval membership; +- the exclusive event-axis bound and separately named physical frame count; +- waveform-row alignment of sample indices to `spike_times[subset_spikes]`; +- producer windows' coordinate kind, valid exposure, and source waveform + coverage; +- exact source, retained, and omitted waveform counts under Phy's unchanged + 512 MiB package and 2,000,000-spike budgets. + +If the exporter removes spike rows, it must apply the identical row selection to +every spike-aligned array and rewrite any row-reference arrays such as +`subset_spikes` consistently. Silent removal leaves waveform and metadata rows +misaligned and is not acceptable. Phy can validate the explicit contract and +the exported arrays; only the exporter and acquisition evidence can establish +that the chosen exposure is scientifically authoritative. A local older +recording is not acceptance evidence for a new export. diff --git a/docs/changelog.md b/docs/changelog.md index f18f7b05f..487ee4e40 100644 --- a/docs/changelog.md +++ b/docs/changelog.md @@ -24,6 +24,9 @@ behavior they verify rather than listed separately. - Sparse cluster IDs no longer require dense allocations during clustering. - Bounded amplitude plots label seconds from window start and display the window's recording-time range above the plot. +- Long-recording preparation accepts explicitly declared elapsed-tick + coordinates and can select whole validated producer evidence windows, while + keeping the existing spike and output-byte budgets. ### Documentation diff --git a/docs/long-recordings.md b/docs/long-recordings.md index b5bf8d424..de67eac00 100644 --- a/docs/long-recordings.md +++ b/docs/long-recordings.md @@ -6,12 +6,39 @@ sorting. Preparation reads source arrays in batches; it does not load the full sorting into the GUI. The source dataset is retained unchanged, and replay writes a separate output dataset. -This workflow is intended for a Phy sorting with one fixed-rate, monotonic sample -clock. Multi-segment recordings are not supported. Supply acquisition duration -and valid acquisition intervals when they are not already recorded in the -dataset metadata. Duration describes exposure; Phy cannot infer acquisition -gaps from periods with no spikes. Intervals use half-open sample coordinates -`[start, end)`. +This workflow supports a single monotonic event axis. Existing sources without +an explicit time-base declaration use `acquisition_samples`, the legacy +fixed-rate sample-coordinate contract. Sources with `time_base` may instead +declare `elapsed_ticks`: nonnegative integer elapsed-time coordinates with a +declared `ticks_per_second`. In either case, `num_samples` is the exclusive +upper bound of the canonical coordinate axis, and `valid_intervals` are +half-open `[start, end)` intervals on that same axis. For elapsed ticks, +`num_samples` is a tick bound, not a physical frame count. Explicit elapsed +sources must provide authoritative valid intervals; Phy cannot infer +acquisition gaps or filler from periods with no spikes. Multi-segment recordings +are not supported. + +The `time_base` declaration is a dictionary such as +`{'kind': 'elapsed_ticks', 'ticks_per_second': 30000.0}` in `params.py` (or +`recording.time_base` in the waveform manifest). For this workflow, +`ticks_per_second`, `sample_rate`, and the physical waveform sample rate must +be equal. Unequal event and waveform rates need separate waveform-axis support. +A source containing `timestamps.json` must declare its coordinate contract +explicitly; Phy does not parse that file to guess a conversion. Elapsed ticks +cannot index raw voltage, so an elapsed source with a real `dat_path` is not +supported. Stored waveforms can be used without raw data. + +For explicit elapsed exports, the waveform manifest must declare +`recording.sample_index_coordinates` and +`recording.window_bounds_coordinates` as `elapsed_ticks` when those sidecars are +present. The waveform-aligned `sample_index[w]` must equal +`spike_times[subset_spikes[w]]`; it is neither a source row ID nor a raw frame +offset. The manifest's `sample_index_coordinates` and +`window_bounds_coordinates` must each equal the declared `time_base.kind`. +Producer window bounds describe canonical elapsed coordinates and must not +cross unsupported gaps. The 512 MiB output cap applies to package bytes, not +process RSS; waveform source, retained, and omitted counts are reported in the +CLI and manifest. The screenshots below show the actual bounded GUI views using a deterministic synthetic eight-hour sorting. The overview plots full-duration rates and @@ -53,31 +80,45 @@ phy prepare-large /data/recording/params.py /data/recording-bounded \ `--duration` is in seconds and must agree with declared acquisition metadata. The `.npy` valid-interval file contains an integer array of shape `[W, 2]` with -ordered, nonoverlapping sample pairs. -Without it, the full declared duration is treated as valid exposure. Do not use -that default when the recording contains acquisition gaps. +ordered, nonoverlapping coordinate pairs. Without it, legacy acquisition-sample +sources treat the full declared extent as valid exposure. Explicit elapsed +sources require producer-declared `valid_intervals`; there is no full-extent +default for them. `--max-bytes` limits the bounded output package size, including its summaries and window plan. It is not a process-memory or peak-RSS limit. The source unit IDs must fit nonnegative `int32`; sample coordinates and full-source spike row IDs use `int64`. -Preparation chooses shared time windows under the spike and byte budgets. The -window length, strata, and seed make the plan reproducible; inspect the saved -window plan in the output package when documenting or repeating an analysis. +Preparation uses `--window-policy auto` by default. When validated producer +windows are available, it selects among those whole windows and preserves their +acquisition boundaries. Producer-window mode requires valid producer windows; +it does not generate rescue windows to compensate for missing or malformed +producer evidence. Without producer windows, the original shared-window planner +uses the configured window length, strata, and seed. Inspect the saved window +plan in the output package when documenting or repeating an analysis. Windows that exceed the budget are omitted, so a high-density interval can reduce retained evidence. Preparation does not shorten an over-budget window or -silently thin spikes inside it. A survey of shared windows is supplemented by -deterministic rescue evidence for units missed by the survey. This improves the -chance of seeing rare units, but makes the evidence selection unequal: rescue -windows must not be treated as a probability sample. - -Preparation records exact full-recording spike counts and rates using valid -acquisition exposure. If source scalar amplitudes or depths are available, it +silently thin spikes inside it. The generated planner supplements its survey of +shared windows with deterministic rescue evidence for units missed by the +survey. This improves the chance of seeing rare units, but makes the evidence +selection unequal: rescue windows must not be treated as a probability sample. +Producer-window selection uses only the producer windows and does not generate +rescue windows. + +Overlapping producer windows are allowed; selection uses their union while +retaining their acquisition boundaries. Preparation records exact +full-recording spike counts and rates using valid exposure. If source scalar +amplitudes or depths are available, it also records per-bin finite-value means and availability counts. It does not invent missing measurements or convert source values to physical units. Stored waveforms are included only where available in the source; raw traces are not required when stored waveform data are sufficient for the views being used. +The default spike and byte budgets remain 2,000,000 spikes and 512 MiB. Output +byte budgets describe package bytes, not resident memory. Waveform availability +can exceed the bounded output budget: preparation reports waveform counts +retained, omitted, and available in the source on the CLI, and stores the counts +in the manifest so truncation is visible. Producer-supplied per-unit metrics and annotations remain inherited metadata; Phy does not recalculate those values for merged or split units. Use the full-count, rate, amplitude-mean, and depth-mean summaries produced by this From c894e816b7e291940ce6e550b805227bc04dc44c Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 17:56:59 +0200 Subject: [PATCH 28/53] Prefer validated producer windows and report waveform coverage --- phy/apps/large_recording/prepare.py | 197 ++++++++++++++++-- .../tests/test_producer_windows.py | 161 ++++++++++++++ 2 files changed, 339 insertions(+), 19 deletions(-) create mode 100644 phy/apps/large_recording/tests/test_producer_windows.py diff --git a/phy/apps/large_recording/prepare.py b/phy/apps/large_recording/prepare.py index 4f4b5e3dc..2c2637353 100644 --- a/phy/apps/large_recording/prepare.py +++ b/phy/apps/large_recording/prepare.py @@ -34,7 +34,7 @@ def _row_bounds(times, windows): def _union(windows, block_starts=()): result = [] - for start, end in sorted(windows): + for start, end in sorted(windows, key=lambda row: (int(row[0]), int(row[1]))): if result and ( start < result[-1][1] or (start == result[-1][1] and start not in block_starts) ): @@ -70,6 +70,86 @@ def _selected_waveform_count(source, windows): ) +def _producer_windows(source): + """Validate optional producer plans without loading waveform tensors.""" + stem = '_phy_spikes_subset.' + bounds = source.arrays.get(stem + 'window_bounds.npy') + types = source.arrays.get(stem + 'window_types.npy') + strata = source.arrays.get(stem + 'window_strata.npy') + if bounds is None: + if types is not None or strata is not None: + raise ValueError('Producer window types/strata require window_bounds.') + return None, None + if bounds.ndim != 2 or bounds.shape[1] != 2 or bounds.dtype.kind not in 'iu': + raise ValueError('Producer window_bounds must be an integer (W, 2) array.') + for label, values in (('types', types), ('strata', strata)): + if values is not None and ( + values.ndim != 1 or len(values) != len(bounds) or values.dtype.kind not in 'iu' + ): + raise ValueError(f'Producer window_{label} must be an aligned integer vector.') + manifest_path = source.path / (stem + 'manifest.json') + info = json.loads(manifest_path.read_text()) if manifest_path.exists() else {} + coordinates = info.get('recording', {}).get('window_bounds_coordinates') + clock = getattr(source, 'time_base', None) + kind = clock['kind'] if clock else 'samples' + if coordinates is not None and coordinates != kind: + raise ValueError('Producer window_bounds_coordinates disagrees with the source time_base.') + if kind == 'elapsed_ticks' and coordinates is None: + raise ValueError('Elapsed-tick producer windows require window_bounds_coordinates.') + previous = -1 + for index, (first, last) in enumerate(bounds): + first, last = int(first), int(last) + block = int(np.searchsorted(source.valid_intervals[:, 0], first, side='right') - 1) + if first < previous or first < 0 or last <= first or last > source.num_samples: + raise ValueError( + 'Producer window bounds must be sorted, positive, and inside recording.' + ) + if block < 0 or last > source.valid_intervals[block, 1]: + raise ValueError('Producer window crosses an acquisition block or gap.') + previous = first + code = int(types[index]) if types is not None else 0 + stratum = int(strata[index]) if strata is not None else (-1 if code == 1 else 0) + if code not in (0, 1): + raise ValueError('Producer window_types codes must be 0 (survey) or 1 (rescue).') + if stratum < -1 or (code == 1 and stratum != -1) or (code == 0 and stratum < 0): + raise ValueError( + 'Producer window_strata must be nonnegative for survey and -1 for rescue.' + ) + provenance = { + 'sha256': hash_json( + { + 'files': { + name: hash_file(source.path / name) + for name in ( + stem + 'window_bounds.npy', + stem + 'window_types.npy', + stem + 'window_strata.npy', + ) + if name in source.arrays + }, + 'coordinates': coordinates, + } + ), + 'window_bounds_coordinates': coordinates, + 'num_windows': len(bounds), + } + return (bounds, types, strata), provenance + + +def _distributed_indices(count): + """Visit sorted windows in a reproducible dyadic spread, using constant memory.""" + if not count: + return + bits = (count - 1).bit_length() + for value in range(1 << bits): + index, remainder = 0, value + for _ in range(bits): + index = (index << 1) | (remainder & 1) + remainder >>= 1 + if index < count: + yield index + + def prepare_large( params_path, output_dir, @@ -82,6 +162,7 @@ def prepare_large( seed=0, batch_size=100000, bin_seconds=3600, + window_policy='auto', ): """Choose complete shared windows, write bounded arrays, and publish atomically. @@ -101,6 +182,7 @@ def prepare_large( seed, batch_size, bin_seconds, + window_policy, ) @@ -114,7 +196,19 @@ def _prepare_source( seed, batch_size, bin_seconds, + window_policy, ): + if window_policy not in ('auto', 'producer', 'generated'): + raise ValueError('window_policy must be auto, producer, or generated.') + producer, producer_provenance = _producer_windows(source) + available = ( + producer is not None and bool(len(producer[0])) and source.arrays.keys() >= WAVEFORMS + ) + if window_policy == 'producer' and not available: + raise ValueError( + 'Producer policy requires nonempty window bounds and stored waveform data.' + ) + resolved_policy = 'producer' if available and window_policy != 'generated' else 'generated' output_dir = Path(output_dir).resolve() missing_static = { 'templates.npy', @@ -164,13 +258,18 @@ def _prepare_source( ) overhead = 32768 + metadata_bytes + 1024 * len(source.arrays) fixed_bytes += overhead + # Candidate records remain present even when rejected. Reserve them before + # selection so an omission cannot silently exceed the byte budget. + if resolved_policy == 'producer': + fixed_bytes += len(producer[0]) * 512 row_bytes = 16 # int64 global row mapping and baseline assignment for name in source.arrays.keys() & PER_SPIKE: array = source.arrays[name] row_bytes += array.dtype.itemsize * int(np.prod(array.shape[1:], dtype=np.int64)) + waveform_sidecars = source.arrays.keys() & {'_phy_spikes_subset.sample_index.npy'} waveform_bytes = 0 if source.arrays.keys() >= WAVEFORMS: - for name in WAVEFORMS: + for name in WAVEFORMS | waveform_sidecars: array = source.arrays[name] waveform_bytes += array.dtype.itemsize * int(np.prod(array.shape[1:], dtype=np.int64)) if fixed_bytes > max_bytes: @@ -185,7 +284,12 @@ def accept(start, end, kind, segment, stratum_id): candidate = _union([*windows, [start, end]], set(source.valid_intervals[:, 0])) n = sum(stop - first for first, stop in _row_bounds(times, candidate)) n_waveforms = _selected_waveform_count(source, candidate) - size = fixed_bytes + n * row_bytes + n_waveforms * waveform_bytes + len(candidate) * 256 + size = ( + fixed_bytes + + n * row_bytes + + n_waveforms * waveform_bytes + + (len(candidate) + len(plan) + len(omitted) + 1) * 256 + ) record = { 'start': int(start), 'end': int(end), @@ -194,6 +298,8 @@ def accept(start, end, kind, segment, stratum_id): 'block': int(segment), 'stratum': int(stratum_id), } + if (len(plan) + len(omitted) + 1) * 256 + fixed_bytes > max_bytes: + raise ValueError('Window plan metadata exceeds max_bytes; increase max_bytes.') if n > max_spikes or size > max_bytes: omitted.append( {**record, 'reason': 'spike_budget' if n > max_spikes else 'byte_budget'} @@ -203,24 +309,54 @@ def accept(start, end, kind, segment, stratum_id): plan.append(record) return True - # Candidate enumeration is scalar and bounded by output-window metadata, - # rather than constructing recording-length arrays. - for segment, (first, last) in enumerate(source.valid_intervals): - for start in range(int(first), int(last), stratum): - end = min(start + stratum, int(last)) - length = min(width, end - start) - offset = int(rng.integers(0, end - start - length + 1)) - accept(start + offset, start + offset + length, 'survey', segment, start // stratum) - if (len(plan) + len(omitted)) * 256 + fixed_bytes > max_bytes: - raise ValueError( - 'Window plan metadata exceeds max_bytes; increase stratum_seconds.' + producer_estimate = None + if resolved_policy == 'producer': + bounds, types, strata = producer + # Counting intersections uses sparse ID binary searches, never waveform data. + union = _union(bounds, set(source.valid_intervals[:, 0])) + all_spikes = sum(stop - first for first, stop in _row_bounds(times, union)) + all_waveforms = _selected_waveform_count(source, union) + if all_waveforms != len(source.arrays['_phy_spikes_subset.spikes.npy']): + raise ValueError('Stored waveform rows fall outside the producer window plan.') + producer_estimate = { + 'spikes': all_spikes, + 'waveform_rows': all_waveforms, + 'bytes': fixed_bytes + + all_spikes * row_bytes + + all_waveforms * waveform_bytes + + (len(bounds) + len(union)) * 256, + } + del union + for index in _distributed_indices(len(bounds)): + first, last = map(int, bounds[index]) + block = int(np.searchsorted(source.valid_intervals[:, 0], first, side='right') - 1) + code = int(types[index]) if types is not None else 0 + kind = 'survey' if code == 0 else 'rescue' + stratum_id = int(strata[index]) if strata is not None else (-1 if code else index) + accept(first, last, kind, block, stratum_id) + else: + # Candidate enumeration is scalar and bounded by output-window metadata, + # rather than constructing recording-length arrays. + for segment, (first, last) in enumerate(source.valid_intervals): + for start in range(int(first), int(last), stratum): + end = min(start + stratum, int(last)) + length = min(width, end - start) + offset = int(rng.integers(0, end - start - length + 1)) + accept( + start + offset, start + offset + length, 'survey', segment, start // stratum ) + if (len(plan) + len(omitted)) * 256 + fixed_bytes > max_bytes: + raise ValueError( + 'Window plan metadata exceeds max_bytes; increase stratum_seconds.' + ) evidence = set() for first, stop in _row_bounds(times, windows): for start in range(first, stop, batch_size): evidence.update(np.unique(assignments[start : min(start + batch_size, stop)]).tolist()) missing = set(source.unit_ids.tolist()) - evidence for batch in source.iter_batches(): + if window_policy == 'producer': + break if not missing: break units, positions = np.unique(batch['spike_clusters.npy'], return_index=True) @@ -247,7 +383,7 @@ def accept(start, end, kind, segment, stratum_id): fixed_bytes + n_bounded * row_bytes + _selected_waveform_count(source, windows) * waveform_bytes - + len(windows) * 256 + + (len(windows) + len(plan) + len(omitted)) * 256 ) free = shutil.disk_usage(output_dir.parent).free if free < estimated_bytes: @@ -333,6 +469,8 @@ def accept(start, end, kind, segment, stratum_id): num_samples=source.num_samples, valid_intervals=source.valid_intervals.tolist(), ) + if getattr(source, 'time_base', None) is not None: + params['time_base'] = source.time_base params.setdefault('dtype', 'int16') params.setdefault('n_channels_dat', len(source.arrays.get('channel_map.npy', []))) (temporary / 'params.py').write_text( @@ -375,6 +513,20 @@ def accept(start, end, kind, segment, stratum_id): 'counts': source.counts.tolist(), 'bounded_counts': [bounded_counts[int(unit)] for unit in source.unit_ids], 'waveform_counts': [waveform_counts[int(unit)] for unit in source.unit_ids], + 'waveform_coverage': { + 'source_rows': len(source.arrays['_phy_spikes_subset.spikes.npy']) + if source.arrays.keys() >= WAVEFORMS + else 0, + 'retained_rows': sum(waveform_counts.values()), + 'dropped_rows': ( + len(source.arrays['_phy_spikes_subset.spikes.npy']) + if source.arrays.keys() >= WAVEFORMS + else 0 + ) + - sum(waveform_counts.values()), + }, + 'producer_window_plan': producer_provenance, + 'producer_window_estimate': producer_estimate, 'next_cluster_id': source.next_cluster_id, 'global_spike_ids_file': '_phy_spike_global_ids.npy', 'base_assignments_file': '_phy_spike_clusters_base.npy', @@ -388,6 +540,8 @@ def accept(start, end, kind, segment, stratum_id): **{key: value for key, value in summaries.items() if key.endswith('_file')}, 'selection': { 'algorithm': 'shared_windows_v1', + 'window_policy': window_policy, + 'resolved_window_policy': resolved_policy, 'seed': int(seed), 'window_seconds': window_seconds, 'stratum_seconds': stratum_seconds, @@ -401,7 +555,7 @@ def accept(start, end, kind, segment, stratum_id): fixed_bytes + n_bounded * row_bytes + _selected_waveform_count(source, windows) * waveform_bytes - + len(windows) * 256 + + (len(windows) + len(plan) + len(omitted)) * 256 ), }, 'capabilities': { @@ -422,6 +576,8 @@ def accept(start, end, kind, segment, stratum_id): if name in PER_SPIKE else 'stored_waveform' if name in WAVEFORMS + else 'waveform_sidecar' + if name in waveform_sidecars else 'static' if name in STATIC else 'excluded_window_sidecar', @@ -434,7 +590,7 @@ def accept(start, end, kind, segment, stratum_id): 'excluded_files': sorted( p.name for p in source.path.iterdir() - if p.name not in (PER_SPIKE | STATIC | WAVEFORMS) + if p.name not in (PER_SPIKE | STATIC | WAVEFORMS | waveform_sidecars) and p.name not in ( 'params.py', @@ -445,6 +601,8 @@ def accept(start, end, kind, segment, stratum_id): and (not p.name.startswith('cluster_') or p.stem == 'cluster_info') ), } + if getattr(source, 'time_base', None) is not None: + manifest['time_base'] = source.time_base for document in producer_documents: shutil.copyfile(document, temporary / document.name) bound_paths = [ @@ -502,8 +660,9 @@ def _copy_waveforms(source, output, global_ids, row_bounds): ] n = sum(stop - first for first, stop in spans) targets = {} + waveform_names = WAVEFORMS | (source.arrays.keys() & {'_phy_spikes_subset.sample_index.npy'}) try: - for name in WAVEFORMS: + for name in waveform_names: original = source.arrays[name] targets[name] = np.lib.format.open_memmap( output / name, mode='w+', dtype=original.dtype, shape=(n, *original.shape[1:]) @@ -516,7 +675,7 @@ def _copy_waveforms(source, output, global_ids, row_bounds): targets['_phy_spikes_subset.spikes.npy'][cursor : cursor + length] = ( np.searchsorted(global_ids, upstream_ids[start:end]) ) - for name in WAVEFORMS - {'_phy_spikes_subset.spikes.npy'}: + for name in waveform_names - {'_phy_spikes_subset.spikes.npy'}: targets[name][cursor : cursor + length] = source.arrays[name][start:end] cursor += length for array in targets.values(): diff --git a/phy/apps/large_recording/tests/test_producer_windows.py b/phy/apps/large_recording/tests/test_producer_windows.py new file mode 100644 index 000000000..41ae7699c --- /dev/null +++ b/phy/apps/large_recording/tests/test_producer_windows.py @@ -0,0 +1,161 @@ +"""Producer plans retain complete windows and preserve sparse waveform row alignment.""" + +import json + +import numpy as np +import pytest + +from phy.apps.large_recording.prepare import prepare_large +from phy.apps.large_recording.tests.test_source import make_sorting + +STEM = '_phy_spikes_subset.' + + +def producer_sorting(path): + params = make_sorting(path) + bounds = np.array([[0, 3], [5, 7], [10, 12], [14, 15], [18, 20]]) + np.save(path / (STEM + 'window_bounds.npy'), bounds) + np.save(path / (STEM + 'window_types.npy'), np.zeros(5, dtype=np.uint8)) + np.save(path / (STEM + 'window_strata.npy'), np.arange(5, dtype=np.int32)) + return params + + +def read_manifest(path): + return json.loads((path / '_phy_curation_manifest.json').read_text()) + + +def test_auto_prefers_producer_and_exact_waveform_remapping(tmp_path): + params = producer_sorting(tmp_path / 'source') + output = prepare_large(params, tmp_path / 'bounded', window_policy='producer', batch_size=2) + manifest = read_manifest(output) + assert manifest['selection']['resolved_window_policy'] == 'producer' + assert manifest['waveform_coverage'] == { + 'source_rows': 5, + 'retained_rows': 5, + 'dropped_rows': 0, + } + np.testing.assert_array_equal( + np.load(output / manifest['windows_file']), + np.load(params.parent / (STEM + 'window_bounds.npy')), + ) + ids = np.load(output / manifest['global_spike_ids_file']) + upstream_ids = np.load(params.parent / (STEM + 'spikes.npy')) + np.testing.assert_array_equal(ids[np.load(output / (STEM + 'spikes.npy'))], upstream_ids) + for suffix in ('waveforms.npy', 'channels.npy'): + np.testing.assert_array_equal( + np.load(output / (STEM + suffix)), np.load(params.parent / (STEM + suffix)) + ) + assert manifest['producer_window_plan']['sha256'] + assert manifest['producer_window_estimate']['spikes'] == 12 + auto = prepare_large(params, tmp_path / 'auto') + assert read_manifest(auto)['selection']['resolved_window_policy'] == 'producer' + + +def test_budget_distributes_complete_windows_across_recording(tmp_path): + params = producer_sorting(tmp_path / 'source') + output = prepare_large(params, tmp_path / 'bounded', window_policy='producer', max_spikes=7) + manifest = read_manifest(output) + # Dyadic traversal takes the first and last windows before exhausting budget. + assert manifest['bounded_num_spikes'] == 7 + assert [(r['start'], r['end']) for r in manifest['accepted_window_candidates']] == [ + (0, 3), + (18, 20), + ] + assert manifest['omitted_windows'] + assert all(r['reason'] == 'spike_budget' for r in manifest['omitted_windows']) + assert manifest['waveform_coverage']['dropped_rows'] > 0 + + +def test_generated_override_and_missing_producer(tmp_path): + params = producer_sorting(tmp_path / 'source') + output = prepare_large( + params, + tmp_path / 'bounded', + window_policy='generated', + window_seconds=20, + stratum_seconds=20, + ) + assert read_manifest(output)['selection']['resolved_window_policy'] == 'generated' + params = make_sorting(tmp_path / 'legacy') + with pytest.raises(ValueError, match='requires nonempty'): + prepare_large(params, tmp_path / 'missing', window_policy='producer') + with pytest.raises(ValueError, match='window_policy'): + prepare_large(params, tmp_path / 'bad', window_policy='invalid') + + +@pytest.mark.parametrize( + 'name,value,match', + [ + ('window_bounds.npy', np.array([0, 3]), 'integer'), + ('window_bounds.npy', np.array([[0.0, 3.0]]), 'integer'), + ('window_bounds.npy', np.array([[3, 2]]), 'bounds'), + ('window_bounds.npy', np.array([[0, 21]]), 'bounds'), + ('window_bounds.npy', np.array([[5, 6], [0, 3]]), 'sorted'), + ('window_types.npy', np.zeros(4, dtype=np.uint8), 'aligned'), + ('window_types.npy', np.full(5, 2, dtype=np.uint8), 'codes'), + ('window_strata.npy', np.full(5, -2), 'strata'), + ], +) +def test_invalid_sidecars_rejected_even_for_generated(tmp_path, name, value, match): + params = producer_sorting(tmp_path / 'source') + np.save(params.parent / (STEM + name), value) + if name == 'window_bounds.npy': + for suffix in ('window_types.npy', 'window_strata.npy'): + (params.parent / (STEM + suffix)).unlink() + with pytest.raises(ValueError, match=match): + prepare_large(params, tmp_path / 'bounded', window_policy='generated') + + +@pytest.mark.parametrize('intervals', [[[0, 10], [10, 20]], [[0, 9], [10, 20]]]) +def test_producer_window_cannot_cross_block_or_gap(tmp_path, intervals): + params = producer_sorting(tmp_path / 'source') + with params.open('a') as stream: + stream.write(f'valid_intervals = {intervals!r}\n') + np.save(params.parent / (STEM + 'window_bounds.npy'), np.array([[0, 11]])) + for suffix in ('window_types.npy', 'window_strata.npy'): + (params.parent / (STEM + suffix)).unlink() + with pytest.raises(ValueError, match='block|gap'): + prepare_large(params, tmp_path / 'bounded') + + +def test_overlaps_union_without_duplicate_spikes(tmp_path): + params = producer_sorting(tmp_path / 'source') + np.save(params.parent / (STEM + 'window_bounds.npy'), np.array([[0, 12], [10, 20]])) + for suffix in ('window_types.npy', 'window_strata.npy'): + (params.parent / (STEM + suffix)).unlink() + output = prepare_large(params, tmp_path / 'bounded', window_policy='producer') + manifest = read_manifest(output) + assert manifest['bounded_num_spikes'] == 12 + np.testing.assert_array_equal(np.load(output / manifest['windows_file']), [[0, 20]]) + + +def test_waveforms_outside_producer_windows_rejected(tmp_path): + params = producer_sorting(tmp_path / 'source') + np.save(params.parent / (STEM + 'window_bounds.npy'), np.array([[0, 3]])) + for suffix in ('window_types.npy', 'window_strata.npy'): + (params.parent / (STEM + suffix)).unlink() + with pytest.raises(ValueError, match='outside'): + prepare_large(params, tmp_path / 'bounded', window_policy='producer') + + +def test_wrong_window_coordinates_rejected_for_generated(tmp_path): + params = producer_sorting(tmp_path / 'source') + (params.parent / (STEM + 'manifest.json')).write_text( + json.dumps( + { + 'format': 'phy_spikes_subset', + 'format_version': 1, + 'recording': {'window_bounds_coordinates': 'elapsed_ticks'}, + } + ) + ) + with pytest.raises(ValueError, match='coordinates|time_base'): + prepare_large(params, tmp_path / 'bounded', window_policy='generated') + + +def test_producer_policy_requires_waveform_triplet(tmp_path): + params = producer_sorting(tmp_path / 'source') + for suffix in ('spikes.npy', 'channels.npy', 'waveforms.npy'): + (params.parent / (STEM + suffix)).unlink() + with pytest.raises(ValueError, match='requires nonempty'): + prepare_large(params, tmp_path / 'bounded', window_policy='producer') From 0bfa26baa870d2169b968bc9e593598eeb0a770c Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 17:59:16 +0200 Subject: [PATCH 29/53] Validate elapsed sessions and producer evidence through replay --- design/large-recording-time-coordinates.md | 24 +++--- docs/long-recordings.md | 5 +- phy/apps/large_recording/curation.py | 21 ++++- phy/apps/large_recording/prepare.py | 8 +- phy/apps/large_recording/source.py | 2 +- .../tests/test_elapsed_workflow.py | 82 +++++++++++++++++++ .../tests/test_producer_windows.py | 20 ++++- 7 files changed, 141 insertions(+), 21 deletions(-) create mode 100644 phy/apps/large_recording/tests/test_elapsed_workflow.py diff --git a/design/large-recording-time-coordinates.md b/design/large-recording-time-coordinates.md index 451790679..3c04bc9bf 100644 --- a/design/large-recording-time-coordinates.md +++ b/design/large-recording-time-coordinates.md @@ -125,13 +125,16 @@ clock conversion must be corrected explicitly for an elapsed export. The sidecars have these meanings and validation obligations: - `_phy_spikes_subset.window_bounds.npy`: `int64[W, 2]` event-coordinate - `[start, end)` intervals, ordered and nonoverlapping, within the declared - extent and valid exposure. A window cannot bridge an unsupported interruption. -- `_phy_spikes_subset.window_types.npy`: `uint8[W]`, with `0` survey and `1` - rescue. -- `_phy_spikes_subset.window_strata.npy`: `int32[W]`, nonnegative survey - stratum IDs and `-1` for rescue. The three window arrays are aligned. -- Optional `_phy_spikes_subset.sample_index.npy`: `int64[N_waveforms]`, aligned + `[start, end)` intervals, ordered by start, within the declared extent and + valid exposure. Overlapping windows are unioned without double counting; + acquisition block boundaries remain distinct. A window cannot bridge an + unsupported interruption. +- Optional `_phy_spikes_subset.window_types.npy`: integer `[W]`, conventionally + `uint8`, with `0` survey and `1` rescue; absent types default to survey. +- Optional `_phy_spikes_subset.window_strata.npy`: integer `[W]`, conventionally + `int32`, nonnegative survey stratum IDs and `-1` for rescue. Supplied arrays + align with the window bounds; absent strata receive deterministic defaults. +- Optional `_phy_spikes_subset.sample_index.npy`: integer `[N_waveforms]`, aligned with waveform rows, containing canonical event-center coordinates. For every waveform row `w`, it equals `spike_times[subset_spikes[w]]`. It is not a source spike row ID or a raw-file @@ -223,9 +226,10 @@ Before considering the extension complete, require concrete checks for: identify the conflicting coordinate meanings before the expensive scan. 4. Spikes in filler/excluded exposure, internal reversals and invalid interval boundaries; none are silently dropped or accepted as valid exposure. -5. Malformed or partially supplied producer sidecars, invalid dtypes/lengths, - overlapping windows, windows crossing gaps, waveform centers outside windows, - and sample-index values inconsistent with their source spike rows. +5. Malformed producer sidecars, policy labels without bounds, invalid + dtypes/lengths, overlapping-window union without double counting, windows + crossing gaps, waveform centers outside windows, and sample-index values + inconsistent with their source spike rows. 6. Budget-constrained producer-window selection with exact retained/omitted waveform reporting and deterministic complete-window selection. 7. Prepare, merge/label, save/reopen, replay and reprepare preserving explicit diff --git a/docs/long-recordings.md b/docs/long-recordings.md index de67eac00..b957f8b9b 100644 --- a/docs/long-recordings.md +++ b/docs/long-recordings.md @@ -103,8 +103,9 @@ silently thin spikes inside it. The generated planner supplements its survey of shared windows with deterministic rescue evidence for units missed by the survey. This improves the chance of seeing rare units, but makes the evidence selection unequal: rescue windows must not be treated as a probability sample. -Producer-window selection uses only the producer windows and does not generate -rescue windows. +The explicit `producer` policy uses only producer windows. The `auto` policy +can supplement producer windows with generated rescue evidence for units still +missing from the selected evidence. Overlapping producer windows are allowed; selection uses their union while retaining their acquisition boundaries. Preparation records exact diff --git a/phy/apps/large_recording/curation.py b/phy/apps/large_recording/curation.py index 6a45d7f70..036dfea08 100644 --- a/phy/apps/large_recording/curation.py +++ b/phy/apps/large_recording/curation.py @@ -11,7 +11,7 @@ import numpy as np -from .source import hash_json +from .source import _time_base, hash_json MANIFEST = '_phy_curation_manifest.json' BASE_ASSIGNMENTS = '_phy_spike_clusters_base.npy' @@ -390,11 +390,26 @@ def _initialize(self, dataset_path): raise ValueError('Invalid bounded counts or recording duration.') if manifest['sample_rate'] <= 0: raise ValueError('Sampling rate must be positive.') - if identity['time_base'] != { + expected_time_base = { 'sample_rate': manifest['sample_rate'], 'num_samples': samples, 'valid_intervals': manifest['valid_intervals'], - }: + } + if manifest.get('time_base') is not None: + contract = _time_base(manifest['time_base']) + if contract['ticks_per_second'] != manifest['sample_rate']: + raise ValueError('Bounded tick frequency disagrees with sampling rate.') + expected_time_base['contract'] = contract + timestamps_hash = identity['time_base'].get('timestamps_sha256') + if timestamps_hash is not None: + if ( + not isinstance(timestamps_hash, str) + or len(timestamps_hash) != 64 + or any(c not in '0123456789abcdef' for c in timestamps_hash) + ): + raise ValueError('Invalid source timestamps digest.') + expected_time_base['timestamps_sha256'] = timestamps_hash + if identity['time_base'] != expected_time_base: raise ValueError('Bounded time base disagrees with immutable source identity.') self.capabilities = _validate_capabilities(manifest) self.unit_ids = [_integer(i, 'Unit ID') for i in manifest['unit_ids']] diff --git a/phy/apps/large_recording/prepare.py b/phy/apps/large_recording/prepare.py index 2c2637353..31edc85e3 100644 --- a/phy/apps/large_recording/prepare.py +++ b/phy/apps/large_recording/prepare.py @@ -91,7 +91,7 @@ def _producer_windows(source): info = json.loads(manifest_path.read_text()) if manifest_path.exists() else {} coordinates = info.get('recording', {}).get('window_bounds_coordinates') clock = getattr(source, 'time_base', None) - kind = clock['kind'] if clock else 'samples' + kind = clock['kind'] if clock else 'acquisition_samples' if coordinates is not None and coordinates != kind: raise ValueError('Producer window_bounds_coordinates disagrees with the source time_base.') if kind == 'elapsed_ticks' and coordinates is None: @@ -115,6 +115,10 @@ def _producer_windows(source): raise ValueError( 'Producer window_strata must be nonnegative for survey and -1 for rescue.' ) + if source.arrays.keys() >= WAVEFORMS: + union = _union(bounds, set(source.valid_intervals[:, 0])) + if _selected_waveform_count(source, union) != len(source.arrays[stem + 'spikes.npy']): + raise ValueError('Stored waveform rows fall outside the producer window plan.') provenance = { 'sha256': hash_json( { @@ -316,8 +320,6 @@ def accept(start, end, kind, segment, stratum_id): union = _union(bounds, set(source.valid_intervals[:, 0])) all_spikes = sum(stop - first for first, stop in _row_bounds(times, union)) all_waveforms = _selected_waveform_count(source, union) - if all_waveforms != len(source.arrays['_phy_spikes_subset.spikes.npy']): - raise ValueError('Stored waveform rows fall outside the producer window plan.') producer_estimate = { 'spikes': all_spikes, 'waveform_rows': all_waveforms, diff --git a/phy/apps/large_recording/source.py b/phy/apps/large_recording/source.py index fe3389c40..321c6db6c 100644 --- a/phy/apps/large_recording/source.py +++ b/phy/apps/large_recording/source.py @@ -1,4 +1,4 @@ -"""Validated, file-backed source sorting on one monotonic sample clock.""" +"""Validated, file-backed source sorting on one monotonic integer time axis.""" import csv import ctypes diff --git a/phy/apps/large_recording/tests/test_elapsed_workflow.py b/phy/apps/large_recording/tests/test_elapsed_workflow.py new file mode 100644 index 000000000..aeba29650 --- /dev/null +++ b/phy/apps/large_recording/tests/test_elapsed_workflow.py @@ -0,0 +1,82 @@ +"""Independent discontinuous-clock preparation and replay oracle.""" + +import json +from contextlib import closing + +import numpy as np +import pytest + +from phy.apps.large_recording.curation import BoundedSession +from phy.apps.large_recording.prepare import prepare_large +from phy.apps.large_recording.replay import apply_curation +from phy.apps.large_recording.source import Source, hash_file +from phy.apps.large_recording.tests.test_source import make_sorting + + +def test_elapsed_producer_evidence_replay_and_exposure(tmp_path): + params = make_sorting(tmp_path / 'source') + contract = {'kind': 'elapsed_ticks', 'ticks_per_second': 1.0} + intervals = [[0, 7], [10, 20]] + params.write_text( + params.read_text() + f'time_base = {contract!r}\nvalid_intervals = {intervals!r}\n' + ) + source_path = params.parent + samples = np.load(source_path / 'spike_times.npy') + labels = np.load(source_path / 'spike_clusters.npy') + waveform_ids = np.load(source_path / '_phy_spikes_subset.spikes.npy') + np.save(source_path / '_phy_spikes_subset.sample_index.npy', samples[waveform_ids]) + np.save(source_path / '_phy_spikes_subset.window_bounds.npy', np.array(intervals, 'int64')) + (source_path / 'timestamps.json').write_text('{"provenance": "producer-owned clock"}\n') + (source_path / '_phy_spikes_subset.manifest.json').write_text( + json.dumps( + { + 'format': 'phy_spikes_subset', + 'format_version': 1, + 'recording': { + 'time_base': contract, + 'window_bounds_coordinates': 'elapsed_ticks', + 'sample_index_coordinates': 'elapsed_ticks', + }, + } + ) + ) + original = {p.name: hash_file(p) for p in source_path.iterdir() if p.is_file()} + bounded = prepare_large(params, tmp_path / 'bounded', bin_seconds=5) + manifest = json.loads((bounded / '_phy_curation_manifest.json').read_text()) + assert manifest['time_base'] == contract + assert manifest['selection']['resolved_window_policy'] == 'producer' + np.testing.assert_array_equal(np.load(bounded / '_phy_spike_global_ids.npy'), np.arange(12)) + np.testing.assert_array_equal( + np.load(bounded / '_phy_spikes_subset.sample_index.npy'), samples[waveform_ids] + ) + # Independent exposure oracle, including the partial bin before the gap. + np.testing.assert_array_equal(np.load(bounded / manifest['exposure_file']), [5, 2, 5, 5]) + counts = np.load(bounded / manifest['counts_file']) + for row, unit in enumerate(manifest['unit_ids']): + expected, _ = np.histogram(samples[labels == unit], bins=[0, 5, 10, 15, 20]) + np.testing.assert_array_equal(counts[row], expected) + with closing(BoundedSession(bounded)) as session: + session.record_merge([0, 1], 100) + session.save() + with closing(BoundedSession(bounded)) as reopened: + np.testing.assert_array_equal(reopened.assignments, np.where(labels < 2, 100, labels)) + output = apply_curation(params, bounded, tmp_path / 'curated') + np.testing.assert_array_equal( + np.load(output / 'spike_clusters.npy'), np.where(labels < 2, 100, labels) + ) + assert (output / 'timestamps.json').read_bytes() == ( + source_path / 'timestamps.json' + ).read_bytes() + with Source(params) as source, Source(output / 'params.py') as curated: + assert source.identity == curated.identity + again = prepare_large(output / 'params.py', tmp_path / 'again', bin_seconds=5) + with closing(BoundedSession(again)) as session: + assert session.manifest['time_base'] == contract + assert original == {p.name: hash_file(p) for p in source_path.iterdir() if p.is_file()} + # A metadata edit cannot change the coordinate interpretation of saved evidence. + path = again / '_phy_curation_manifest.json' + altered = json.loads(path.read_text()) + altered['time_base']['kind'] = 'acquisition_samples' + path.write_text(json.dumps(altered)) + with pytest.raises(ValueError, match='time base'): + BoundedSession(again) diff --git a/phy/apps/large_recording/tests/test_producer_windows.py b/phy/apps/large_recording/tests/test_producer_windows.py index 41ae7699c..9c071d5e1 100644 --- a/phy/apps/large_recording/tests/test_producer_windows.py +++ b/phy/apps/large_recording/tests/test_producer_windows.py @@ -129,13 +129,29 @@ def test_overlaps_union_without_duplicate_spikes(tmp_path): np.testing.assert_array_equal(np.load(output / manifest['windows_file']), [[0, 20]]) -def test_waveforms_outside_producer_windows_rejected(tmp_path): +@pytest.mark.parametrize('policy', ['auto', 'producer', 'generated']) +def test_waveforms_outside_producer_windows_rejected(tmp_path, policy): params = producer_sorting(tmp_path / 'source') np.save(params.parent / (STEM + 'window_bounds.npy'), np.array([[0, 3]])) for suffix in ('window_types.npy', 'window_strata.npy'): (params.parent / (STEM + suffix)).unlink() with pytest.raises(ValueError, match='outside'): - prepare_large(params, tmp_path / 'bounded', window_policy='producer') + prepare_large(params, tmp_path / 'bounded', window_policy=policy) + + +def test_legacy_acquisition_coordinate_declaration(tmp_path): + params = producer_sorting(tmp_path / 'source') + (params.parent / (STEM + 'manifest.json')).write_text( + json.dumps( + { + 'format': 'phy_spikes_subset', + 'format_version': 1, + 'recording': {'window_bounds_coordinates': 'acquisition_samples'}, + } + ) + ) + output = prepare_large(params, tmp_path / 'bounded', window_policy='producer') + assert read_manifest(output)['waveform_coverage']['retained_rows'] == 5 def test_wrong_window_coordinates_rejected_for_generated(tmp_path): From 1533ff52654d0a7d34df790d60e641506e5dab8c Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 17:59:16 +0200 Subject: [PATCH 30/53] Expose producer window policy and waveform coverage in the CLI --- phy/apps/__init__.py | 17 ++++++++- phy/apps/large_recording/tests/test_cli.py | 43 ++++++++++++++++++++++ 2 files changed, 59 insertions(+), 1 deletion(-) create mode 100644 phy/apps/large_recording/tests/test_cli.py diff --git a/phy/apps/__init__.py b/phy/apps/__init__.py index c6767d88c..a74019d0d 100644 --- a/phy/apps/__init__.py +++ b/phy/apps/__init__.py @@ -191,12 +191,21 @@ def cli_template_describe(ctx, params_path): @click.option('--seed', type=click.IntRange(min=0), default=0) @click.option('--bin-seconds', type=click.FloatRange(min=0, min_open=True), default=3600.0) @click.option('--batch-size', type=click.IntRange(min=1), default=100000) +@click.option( + '--window-policy', + type=click.Choice(['auto', 'producer', 'generated']), + default='auto', + show_default=True, + help='Prefer producer waveform windows, require them, or generate new windows.', +) def cli_prepare_large(params_path, output_dir, valid_intervals=None, **kwargs): """Prepare bounded shared-window evidence and complete-sorting summaries. - VALID_INTERVALS is an optional int64 .npy array of acquisition sample [start, end) pairs. + VALID_INTERVALS is an optional int64 .npy array of acquisition [start, end) tick pairs. Duration/exposure must be authoritative; it is never inferred from spike silence. """ + import json + import numpy as np from .large_recording.prepare import prepare_large @@ -207,6 +216,12 @@ def cli_prepare_large(params_path, output_dir, valid_intervals=None, **kwargs): except (ValueError, OSError) as error: raise click.ClickException(str(error)) from error click.echo(f'Prepared bounded evidence: {output}') + manifest = json.loads((output / '_phy_curation_manifest.json').read_text(encoding='utf-8')) + coverage = manifest['waveform_coverage'] + click.echo( + f'Stored waveforms: {coverage["retained_rows"]:,} retained / ' + f'{coverage["source_rows"]:,} source; {coverage["dropped_rows"]:,} omitted.' + ) @phycli.command('apply-curation') diff --git a/phy/apps/large_recording/tests/test_cli.py b/phy/apps/large_recording/tests/test_cli.py new file mode 100644 index 000000000..573e95fc3 --- /dev/null +++ b/phy/apps/large_recording/tests/test_cli.py @@ -0,0 +1,43 @@ +"""Batch CLI coverage and window-policy regressions.""" + +import json + +from click.testing import CliRunner + +from phy.apps import phycli +from phy.apps.large_recording.tests.test_source import make_sorting + + +def test_prepare_cli_reports_waveform_coverage_and_window_policy(tmp_path): + params = make_sorting(tmp_path / 'source') + output = tmp_path / 'bounded' + result = CliRunner().invoke( + phycli, + [ + 'prepare-large', + str(params), + str(output), + '--window-policy', + 'generated', + '--window-seconds', + '20', + '--stratum-seconds', + '20', + ], + ) + assert result.exit_code == 0, result.output + assert '5 retained / 5 source; 0 omitted' in result.output + manifest = json.loads((output / '_phy_curation_manifest.json').read_text()) + assert manifest['selection']['window_policy'] == 'generated' + + +def test_prepare_cli_explains_missing_producer_windows(tmp_path): + params = make_sorting(tmp_path / 'source') + output = tmp_path / 'bounded' + result = CliRunner().invoke( + phycli, + ['prepare-large', str(params), str(output), '--window-policy', 'producer'], + ) + assert result.exit_code == 1 + assert 'producer' in result.output.lower() + assert not output.exists() From 28af2ed7ac55ea639792bd5976cd45c78a30ff79 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 18:02:49 +0200 Subject: [PATCH 31/53] Verify elapsed GUI behavior and record audited validation --- design/large-recording-validation.md | 30 ++++++++++++++ docs/long-recordings.md | 5 ++- .../tests/test_gui_lifecycle.py | 39 +++++++++++++++++++ 3 files changed, 72 insertions(+), 2 deletions(-) diff --git a/design/large-recording-validation.md b/design/large-recording-validation.md index 2dcd3e761..527de3ab9 100644 --- a/design/large-recording-validation.md +++ b/design/large-recording-validation.md @@ -7,6 +7,36 @@ chronic curation. ## Automated checks +On 2026-10-24, the AIND time-coordinate follow-up passed `make test-full`: +**818 passed, 1 existing benchmark skip** (496 core tests and 322 application +tests). The environment used Python 3.12.3, released phylib 2.7.1, Linux, +Xvfb, software OpenGL, and Qt's offscreen platform. The target included lint +and formatting checks. The strict documentation check and `uv build` also +passed; the wheel contains all 12 long-recording runtime modules. + +The follow-up has a 96-test focused source/preparation/replay run and an +additional GUI regression for explicit elapsed clocks. Its independent +discontinuous-clock oracle verifies per-bin exposure and unit counts, exact +waveform sample-index alignment, merge assignments, save/reopen, replay, +repreparation, timestamp provenance, and unchanged source bytes. The GUI test +opens all default bounded views, checks exposure-based firing rate and window +navigation, and confirms that elapsed ticks do not enable raw traces. All of +these tests are included in the full-suite result above. + +Separate architecture, correctness, and final audit reviews used Sol at high +reasoning effort. The correctness review found a legacy coordinate-name +mismatch and a generated-policy bypass of producer waveform-window membership +validation; both received regression coverage and were corrected. The final +independent audit found no remaining blocking defect in the reviewed changes. + +These results validate the [explicit coordinate contract](large-recording-time-coordinates.md), +not the supplied export's acquisition truth. The complete new Code Ocean export +and its acquisition logs were unavailable. The supplied `timestamps.json` was +inspected directly; spike-array counts and filler-spike claims remain attributed +to Carl's report. No exporter repository was identified or modified. The +[exporter handoff](aind-export-handoff.md) records the upstream work and real-data +acceptance evidence still needed. + On 2026-10-13, `make test-full` completed with **756 passed and 1 skipped** (496 non-application tests and 260 application tests). Final channel geometry and nonidentity waveform-mapping additions passed a further focused diff --git a/docs/long-recordings.md b/docs/long-recordings.md index b957f8b9b..9a841b391 100644 --- a/docs/long-recordings.md +++ b/docs/long-recordings.md @@ -82,7 +82,8 @@ phy prepare-large /data/recording/params.py /data/recording-bounded \ The `.npy` valid-interval file contains an integer array of shape `[W, 2]` with ordered, nonoverlapping coordinate pairs. Without it, legacy acquisition-sample sources treat the full declared extent as valid exposure. Explicit elapsed -sources require producer-declared `valid_intervals`; there is no full-extent +sources require authoritative `valid_intervals` in metadata or supplied +explicitly through the CLI/API; there is no full-extent default for them. `--max-bytes` limits the bounded output package size, including its summaries and @@ -215,7 +216,7 @@ periods or units, and waveform availability can vary across units and time. These views do not establish full-recording quality, contamination, refractory violations, or continuous biological identity. Use them to guide review, not as scientific claims about unseen spikes. Long-duration coordinates preserve the -source sample clock; silence alone is never evidence that the acquisition was +declared source time axis; silence alone is never evidence that the acquisition was inactive. For reproducible synthetic capacity measurements, run diff --git a/phy/apps/large_recording/tests/test_gui_lifecycle.py b/phy/apps/large_recording/tests/test_gui_lifecycle.py index d2286b9eb..a57ccc243 100644 --- a/phy/apps/large_recording/tests/test_gui_lifecycle.py +++ b/phy/apps/large_recording/tests/test_gui_lifecycle.py @@ -11,6 +11,45 @@ from phy.apps.template.gui import TemplateController +def test_elapsed_producer_windows_open_and_navigate_in_gui(qtbot, tmp_path): + params = make_gui_sorting(tmp_path / 'source') + intervals = [[0, 210000], [300000, 600000]] + contract = {'kind': 'elapsed_ticks', 'ticks_per_second': 30000.0} + params.write_text( + params.read_text() + f'time_base = {contract!r}\nvalid_intervals = {intervals!r}\n' + ) + np.save(params.parent / '_phy_spikes_subset.window_bounds.npy', np.array(intervals, 'int64')) + (params.parent / '_phy_spikes_subset.manifest.json').write_text( + json.dumps( + { + 'format': 'phy_spikes_subset', + 'format_version': 1, + 'recording': {'window_bounds_coordinates': 'elapsed_ticks'}, + } + ) + ) + output = prepare_large(params, tmp_path / 'bounded', window_policy='producer', bin_seconds=5) + controller = TemplateController( + dir_path=output, config_dir=tmp_path / 'config', plugins=[], enable_threading=False + ) + gui = None + try: + gui = controller.create_gui(do_prompt_save=False) + controller.supervisor.select([0, 1]) + controller.supervisor.block() + controller.inspect_evidence_window(1) + assert controller.model.sample_rate == 30000.0 + assert controller.model.traces is None + assert controller.get_mean_firing_rate(0) == pytest.approx(4 / 17) + view = gui.get_view('EvidenceAmplitudeView') + assert view.duration == 10 + assert view.window_label.text() == ('Evidence window 1 | Recording time: 10.000–20.000 s') + finally: + if gui is not None: + gui.close() + controller.close() + + def test_window_time_labels_follow_navigation(qtbot, tmp_path): _, controller = make_controller(tmp_path, sparse=True) gui = controller.create_gui(default_views=['EvidenceAmplitudeView'], do_prompt_save=False) From d809e5b90177185ee3e090e6c5b17b22a9241d19 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 20:01:10 +0200 Subject: [PATCH 32/53] Normalize bounded split journal metadata before saving --- docs/changelog.md | 2 ++ phy/apps/large_recording/curation.py | 4 +-- .../large_recording/tests/test_curation.py | 31 +++++++++++++++++++ .../tests/test_gui_lifecycle.py | 31 +++++++++++++++++++ 4 files changed, 66 insertions(+), 2 deletions(-) diff --git a/docs/changelog.md b/docs/changelog.md index 487ee4e40..abe54d6e9 100644 --- a/docs/changelog.md +++ b/docs/changelog.md @@ -13,6 +13,8 @@ behavior they verify rather than listed separately. ### Long recordings +- Fixed saving bounded amplitude splits after merge undo/redo when NumPy cluster + IDs appear in journal metadata. - Added `prepare-large` and `apply-curation` for bounded shared-window evidence, full-duration exposure-aware summaries, semantic merges/labels/source-amplitude splits, and replay into a new complete sorting. diff --git a/phy/apps/large_recording/curation.py b/phy/apps/large_recording/curation.py index 036dfea08..2827ad1b9 100644 --- a/phy/apps/large_recording/curation.py +++ b/phy/apps/large_recording/curation.py @@ -698,7 +698,7 @@ def record_threshold_split(self, parent, children, predicate, metadata=None): 'parent': int(parent), 'children': children, 'predicate': validate_predicate(predicate), - 'metadata': copy.deepcopy(metadata or {}), + 'metadata': normalize_metadata(metadata or {}), } ) @@ -713,7 +713,7 @@ def preflight_split(self, parent, selected_id, remainder_id, predicate, metadata 'parent': int(parent), 'children': children, 'predicate': validate_predicate(predicate), - 'metadata': copy.deepcopy(metadata or {}), + 'metadata': normalize_metadata(metadata or {}), } interpret_events(self.unit_ids, self.base_metadata, self.events + [event]) project_assignments(self.base_assignments, self.events + [event], self.attributes) diff --git a/phy/apps/large_recording/tests/test_curation.py b/phy/apps/large_recording/tests/test_curation.py index 9997bc9cf..a0f5258e2 100644 --- a/phy/apps/large_recording/tests/test_curation.py +++ b/phy/apps/large_recording/tests/test_curation.py @@ -64,6 +64,37 @@ def make_session(tmp_path): return source, BoundedSession(fixture.bounded) +@pytest.mark.parametrize('command', ['record_threshold_split', 'record_split']) +def test_split_numpy_metadata_keys_save_and_reopen(tmp_path, command): + source, session = make_session(tmp_path) + predicate = { + 'attribute': 'amplitudes.npy', + 'operator': '<', + 'threshold': 0.5, + 'nonfinite': 'keep', + } + children = [np.int64(100), np.int64(101)] + metadata = {'group': {children[0]: 'good', children[1]: 'noise'}} + try: + if command == 'record_threshold_split': + session.record_threshold_split(0, children, predicate, metadata) + else: + session.record_split(0, *children, predicate, metadata) + session.save() + with_metadata = session.events[-1]['metadata']['group'] + assert all(type(key) is int for key in with_metadata) + reopened = BoundedSession(session.path) + try: + np.testing.assert_array_equal(reopened.assignments, session.assignments) + assert reopened.metadata['group'][100] == 'good' + assert reopened.metadata['group'][101] == 'noise' + finally: + reopened.close() + finally: + session.close() + source.close() + + def test_merge_label_snapshot_branch_reopen(tmp_path): source, session = make_session(tmp_path) baseline = session.snapshot() diff --git a/phy/apps/large_recording/tests/test_gui_lifecycle.py b/phy/apps/large_recording/tests/test_gui_lifecycle.py index a57ccc243..308dc5e9d 100644 --- a/phy/apps/large_recording/tests/test_gui_lifecycle.py +++ b/phy/apps/large_recording/tests/test_gui_lifecycle.py @@ -206,3 +206,34 @@ def test_default_bounded_views_handle_threshold_children_with_pending_metrics(qt finally: gui.close() controller.close() + + +def test_merge_redo_then_amplitude_split_saves_and_reopens(qtbot, tmp_path): + _, controller = make_controller(tmp_path) + bounded = controller.dir_path + gui = controller.create_gui(default_views=[], do_prompt_save=False) + supervisor = controller.supervisor + try: + supervisor.merge([0, 1]) + supervisor.block() + supervisor.undo() + supervisor.block() + supervisor.redo() + supervisor.block() + split = supervisor.split_source_amplitude(2, 6.0) + supervisor.block() + assignments = supervisor.clustering.spike_clusters.copy() + supervisor.save() + children = list(split.added) + finally: + gui.close() + controller.close() + reopened = TemplateController( + dir_path=bounded, config_dir=tmp_path / 'config', plugins=[], enable_threading=False + ) + try: + np.testing.assert_array_equal(reopened.bounded_session.assignments, assignments) + assert set(reopened.bounded_session.events[-1]['children']) == set(children) + assert len(reopened.bounded_session.events) == 2 + finally: + reopened.close() From 592938d85451da9403ea71361d2956c7c9141ea0 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 20:06:58 +0200 Subject: [PATCH 33/53] Record full-size AIND diagnostic validation and acceptance limits --- design/aind-real-data-validation.md | 137 +++++++++++++++++++++++++++ design/large-recording-validation.md | 15 ++- 2 files changed, 148 insertions(+), 4 deletions(-) create mode 100644 design/aind-real-data-validation.md diff --git a/design/aind-real-data-validation.md b/design/aind-real-data-validation.md new file mode 100644 index 000000000..2edf9d868 --- /dev/null +++ b/design/aind-real-data-validation.md @@ -0,0 +1,137 @@ +# Real AIND software diagnostic + +## Conclusion + +The downloaded export does **not** work unchanged with PR #1428: its time +coordinates and exposure declarations still need upstream correction. A +separately labeled diagnostic derivative exercised the complete Phy workflow +over 469,725,534 rows and exposed one additional Phy defect. That defect is +fixed, with portable regression coverage. Preparation, GUI curation, +save/reopen, full replay, independent verification, and repreparation now pass +on the derivative. + +This is software integration evidence, not scientific acceptance of the +original export. The derivative's exposure is inferred from the JSON endpoint +map, and 33 filler-region spikes were explicitly quarantined. Those choices +require acquisition evidence and producer review before use for curation. + +## Source and unchanged-export checks + +The supplied download script selected computation +`b1b0782a-b3ea-4f34-81d7-b3c6e36452b3`, rather than the earlier reported +`85640506-601d-4826-aa61-d3b822e53c84`. Its recording is +`experiment1_AmplifierData_recording1_group0` from session +`854393_2026-06-09_19-34-26`. + +All 67 downloaded files matched the server's listed sizes, totaling +15,381,599,263 bytes. NumPy headers and payload sizes were checked. The export +contains 469,725,567 spikes, 705 declared units, 140,240 stored waveforms and +177 producer windows. Spike times are monotonic across the complete array. + +The unchanged source fails `prepare-large` with the intended early +`timestamps.json requires an explicit time_base` diagnostic. It declares +10,800,000,000 pipeline frames, while its last spike is elapsed tick +12,188,787,421. Exactly 54,808,765 spikes are beyond the declared extent. +`params.py` and the waveform manifest lack an explicit elapsed-time contract +and valid acquisition intervals. + +All 140,240 waveform centers match the JSON's frame-to-clock conversion within +0.5 tick, while their stored sample indices remain pipeline frames. This +reproduces producer interpolation; it does not establish sample-accurate +acquisition timestamps or exposure. Under that same map, filler regions contain +23, 4 and 6 spikes. These 33 rows differ from the 35 reported for the other +computation. Neither explicit large gap contains spikes. + +## Diagnostic derivative and limits + +The original export was retained unchanged. A separate source was constructed +solely to isolate software behavior: + +- Declare the elapsed-tick contract at 30 kHz, an exclusive extent of + 12,188,787,510 ticks, and canonical sidecar coordinates. +- Copy exact `spike_times[waveform_ids]` into the waveform sample-index sidecar. + Convert each producer `[a, b)` window to + `[round(map(a)), round(map(b - 1)) + 1)` on the elapsed axis. +- Infer diagnostic exposure by excluding only the mapped explicit large gaps + and filler regions. This does not locate unknown dropped frames within + pieces or establish acquisition truth. +- Confirm that coordinate normalization alone still rejects the 33 filler + spikes through the strict exposure-membership check. +- Quarantine those source rows explicitly, apply the identical row selection + to every spike-aligned array, and remap waveform row references. No stored + waveform references a quarantined row. Keep a provenance file listing every + excluded source row and spike tick. + +No conversion or filtering behavior was added to the production importer. +The diagnostic source, outputs, SHA-256 inventory, assumptions and one-off +reproduction scripts are retained beneath the downloaded computation's +`diagnostic-validation/` directory on the validation workstation. + +## Observed Phy defect and fix + +With the actual bounded data, merge, undo/redo, amplitude split and undo/redo +left NumPy integer child IDs as keys in split-event metadata. Projected session +metadata had been normalized, but the retained event had not. Saving failed +while serializing `journal.json` with `TypeError: keys must be str, int, float, +bool or None, not numpy.int64`. + +Both split-event construction paths now normalize metadata before retaining +the event. This preserves IDs and the remainder/selected child order. Two +session API regressions reproduced the failure before the fix; a GUI regression +also exercises merge undo/redo, split, save and reopen. The focused +curation/lifecycle run passed 43 tests. Independent Sol-high review confirmed +the root cause and semantics of the fix. + +## Full workflow results + +Default preparation retained 1,486,361 spikes in 36 windows and 27,865 of +140,240 waveforms. Every unit has spike evidence; 702 of 705 have stored +waveform evidence. The package occupies 532,625,401 bytes, within the +536,870,912-byte cap. The complete producer-window plan is estimated at +2,554,394,546 bytes and 7,298,318 spikes, exceeding both default budgets. + +All default bounded views opened, including waveform-derived features without +exported PCs. Selection included units 574, 578 and 579, which have no retained +stored waveforms. Navigation covered the beginning, middle and final retained +windows. Artificial merge and amplitude-split actions passed undo/redo, an +independent bounded assignment comparison, save and reopen, without logged +application errors. These actions are test operations, not biological curation. + +Full replay wrote a separate output. An independent streamed oracle compared +**all 469,725,534 assignments**, using explicit merge masks and amplitude +comparisons rather than the production replay functions. Edge searches and +weighted/unweighted histograms independently checked the original per-bin +counts, finite amplitude counts and amplitude sums. Exposure arithmetic was +checked against the declared diagnostic intervals, without claiming their +scientific validity. + +Every bounded spike row was checked against its source row. All 27,865 bounded +waveform rows, channel lists and center indices matched their mapped source +rows exactly. Replay preserved immutable array bytes and timestamp provenance. +Repreparation's complete unit counts matched the replay oracle. SHA-256 checks +confirmed that every file in the original download remained unchanged. + +## Measurements and acceptance limits + +Single workstation runs used Linux, Python 3.12.3, phylib 2.7.1, 100,000-row +batches, Xvfb/software OpenGL and Qt's offscreen platform. The workstation has +125 GiB RAM; source files were warm in the filesystem cache. Some later phases +ran concurrently with tests or another verification phase. These are observed +integration costs, not controlled throughput benchmarks or laptop predictions. + +| Phase | Wall time | Peak process RSS | +| --- | ---: | ---: | +| Preparation | 50.1 s | 14.2 GiB | +| GUI actions and reopen | 9.1 s | 0.68 GiB | +| Full replay | 37.0 s | 25.0 GiB | +| Repreparation | 51.0 s | 14.1 GiB | + +Offline RSS includes resident memory-mapped source/output pages. It is not +limited by the bounded package's byte budget. These measurements do not prove a +small process-RSS bound on a much longer source. + +The original export remains blocked until its producer supplies consistent +time coordinates, authoritative exposure and a justified filler-spike policy. +See the [exporter handoff](aind-export-handoff.md). No acquisition logs or +verified exporter source repository were available, and this diagnostic does +not resolve timestamp precision within pieces or chronic unit identity. diff --git a/design/large-recording-validation.md b/design/large-recording-validation.md index 527de3ab9..afcee5825 100644 --- a/design/large-recording-validation.md +++ b/design/large-recording-validation.md @@ -7,6 +7,11 @@ chronic curation. ## Automated checks +After the real-data split-journal fix described in the +[AIND diagnostic record](aind-real-data-validation.md), `make test-full` passed +**821 tests with 1 existing benchmark skip** (496 core and 325 application +tests). Lint, formatting, documentation checks, and package build passed. + On 2026-10-24, the AIND time-coordinate follow-up passed `make test-full`: **818 passed, 1 existing benchmark skip** (496 core tests and 322 application tests). The environment used Python 3.12.3, released phylib 2.7.1, Linux, @@ -30,10 +35,12 @@ validation; both received regression coverage and were corrected. The final independent audit found no remaining blocking defect in the reviewed changes. These results validate the [explicit coordinate contract](large-recording-time-coordinates.md), -not the supplied export's acquisition truth. The complete new Code Ocean export -and its acquisition logs were unavailable. The supplied `timestamps.json` was -inspected directly; spike-array counts and filler-spike claims remain attributed -to Carl's report. No exporter repository was identified or modified. The +not the supplied export's acquisition truth. During that initial follow-up the +complete export and its acquisition logs were unavailable; its spike-array and +filler-spike claims were attributed to Carl's report. A different computation +was subsequently downloaded and tested as an explicitly modified engineering +derivative, as recorded in the AIND diagnostic above. No exporter repository +was identified or modified. The [exporter handoff](aind-export-handoff.md) records the upstream work and real-data acceptance evidence still needed. From 4cf93a666e8b3fb53abee6a9d34b564844b705b8 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 21:47:04 +0200 Subject: [PATCH 34/53] Explain stale merge suggestions using cumulative retirement history --- phy/cluster/_propositions.py | 49 +++++++++++++++++++--- phy/cluster/tests/test_propositions.py | 56 ++++++++++++++++++++++++++ 2 files changed, 99 insertions(+), 6 deletions(-) diff --git a/phy/cluster/_propositions.py b/phy/cluster/_propositions.py index dfd1710a9..ffc8f07a6 100644 --- a/phy/cluster/_propositions.py +++ b/phy/cluster/_propositions.py @@ -182,6 +182,7 @@ class MergePropositionCatalog: reviews: Mapping[str, PropositionReview] = field(default_factory=dict) live_unit_ids: tuple[int, ...] | None = None source_mapping: Mapping = field(default_factory=dict) + retired_units: Mapping = field(default_factory=dict) def __post_init__(self): source_ids = _ids(self.source_unit_ids, minimum=0) @@ -208,6 +209,23 @@ def __post_init__(self): object.__setattr__(self, 'reviews', MappingProxyType(reviews)) object.__setattr__(self, 'live_unit_ids', live_ids) object.__setattr__(self, 'source_mapping', source_mapping) + retired = {} + for key, value in _mapping(self.retired_units, name='retired_units').items(): + if not isinstance(key, str) or not key.isdecimal() or str(int(key)) != key: + raise ValueError( + 'retired_units keys must be canonical non-negative integer strings.' + ) + value = _mapping(value, name='retired unit') + operation = value.get('operation') + if operation not in {'merge', 'threshold_split'}: + raise ValueError('Unknown retired-unit operation.') + replacements = _ids(value.get('replacements'), name='replacements', minimum=1) + if any(unit < 0 for unit in replacements) or int(key) in replacements: + raise ValueError( + 'Retired-unit replacements must be distinct non-negative new IDs.' + ) + retired[key] = {'operation': operation, 'replacements': replacements} + object.__setattr__(self, 'retired_units', _freeze(retired)) @property def propositions(self): @@ -259,11 +277,22 @@ def reason_for(self, key): for unit_id in entry.proposition.unit_ids if unit_id not in self.live_unit_ids ) + causes = [] + for unit_id in missing: + retirement = self.retired_units.get(str(unit_id)) + if retirement is not None: + verb = 'merged' if retirement['operation'] == 'merge' else 'split' + causes.append(f'{unit_id} was {verb}') + if causes: + return f'Source clusters no longer exist: {missing}; ' + '; '.join(causes) + '.' return f'One or more source clusters no longer exist: {missing}.' return None - def project_live_ids(self, live_unit_ids): - return self._replace(live_unit_ids=_ids(live_unit_ids, name='live_unit_ids')) + def project_live_ids(self, live_unit_ids, *, retired_units=None): + changes = {'live_unit_ids': _ids(live_unit_ids, name='live_unit_ids')} + if retired_units is not None: + changes['retired_units'] = retired_units + return self._replace(**changes) def snapshot(self): """Return an immutable snapshot suitable for history entries.""" @@ -323,6 +352,7 @@ def _replace(self, **changes): 'reviews': self.reviews, 'live_unit_ids': self.live_unit_ids, 'source_mapping': self.source_mapping, + 'retired_units': self.retired_units, } values.update(changes) return type(self)(**values) @@ -355,8 +385,10 @@ def restore(self, snapshot): self._catalog = self._require_catalog(snapshot) return None - def project_live_ids(self, live_unit_ids): - self._catalog = self._catalog.project_live_ids(tuple(map(int, live_unit_ids))) + def project_live_ids(self, live_unit_ids, *, retired_units=None): + self._catalog = self._catalog.project_live_ids( + tuple(map(int, live_unit_ids)), retired_units=retired_units + ) return None def reject(self, key): @@ -422,7 +454,7 @@ def _review_fingerprint(catalog): ) -def decode_curation_mapping(mapping) -> MergePropositionCatalog: +def decode_curation_mapping(mapping, *, retired_units=None) -> MergePropositionCatalog: """Decode a supported AIND/SpikeInterface v2 curation document. Invalid individual ``merges`` entries become visible invalid catalog entries; @@ -453,7 +485,12 @@ def decode_curation_mapping(mapping) -> MergePropositionCatalog: entries.append(PropositionEntry(index, proposition=proposition, raw_mapping=raw)) except (TypeError, ValueError) as e: entries.append(PropositionEntry(index, invalid_reason=str(e), raw_mapping=raw)) - return MergePropositionCatalog(source_ids, tuple(entries), source_mapping=mapping) + return MergePropositionCatalog( + source_ids, + tuple(entries), + source_mapping=mapping, + retired_units={} if retired_units is None else retired_units, + ) def encode_curation_mapping(catalog: MergePropositionCatalog): diff --git a/phy/cluster/tests/test_propositions.py b/phy/cluster/tests/test_propositions.py index 22caf1194..2bd63ae9d 100644 --- a/phy/cluster/tests/test_propositions.py +++ b/phy/cluster/tests/test_propositions.py @@ -30,6 +30,62 @@ def _source(merges=None): } +def test_retired_units_explain_stale_without_retargeting_or_overwriting_reviews(): + source = _source([{'unit_ids': [41, 56]}, {'unit_ids': [56, 72]}]) + catalog = decode_curation_mapping(source) + accepted, pending = [entry.key for entry in catalog.entries] + catalog = catalog.accept(accepted, [41, 56], 100) + retired = { + '41': {'operation': 'merge', 'replacements': [100]}, + '56': {'operation': 'merge', 'replacements': [100]}, + '72': {'operation': 'threshold_split', 'replacements': [101, 102]}, + } + catalog = catalog.project_live_ids([100, 101, 102], retired_units=retired) + assert catalog.status_for(accepted) is PropositionStatus.ACCEPTED + assert catalog.reason_for(accepted) is None + assert catalog.status_for(pending) is PropositionStatus.STALE + assert '56 was merged' in catalog.reason_for(pending) + assert '72 was split' in catalog.reason_for(pending) + assert encode_curation_mapping(catalog) == source + retired['56']['operation'] = 'threshold_split' + assert '56 was merged' in catalog.reason_for(pending) + controller = MergePropositionController(catalog) + controller.project_live_ids([100, 101, 102]) + assert controller.catalog.reason_for(pending) == catalog.reason_for(pending) + + +def test_retired_unit_validation(): + for retired in ( + [], + False, + {'01': {'operation': 'merge', 'replacements': [100]}}, + {'41': {'operation': 'label', 'replacements': [100]}}, + {'41': {'operation': 'merge', 'replacements': [41]}}, + {'41': {'operation': 'merge', 'replacements': []}}, + {'41': {'operation': 'threshold_split', 'replacements': [-1]}}, + ): + with raises(ValueError): + decode_curation_mapping(_source(), retired_units=retired) + + +def test_retirement_projection_undo_and_durable_modified_review(): + catalog = decode_curation_mapping(_source()) + key = catalog.propositions[0].key + controller = MergePropositionController(catalog) + before = controller.snapshot() + retired = {'41': {'operation': 'threshold_split', 'replacements': [100, 101]}} + controller.project_live_ids([56, 72, 100, 101], retired_units=retired) + assert '41 was split' in controller.catalog.reason_for(key) + controller.restore(before) + assert controller.catalog.status_for(key) is PropositionStatus.PENDING + modified = catalog.accept(key, [41, 72], 100).project_live_ids( + [56, 100], retired_units={'41': {'operation': 'merge', 'replacements': [100]}} + ) + assert modified.status_for(key) is PropositionStatus.ACCEPTED_MODIFIED + rejected = catalog.reject(key).project_live_ids([56, 100], retired_units=retired) + assert rejected.status_for(key) is PropositionStatus.REJECTED + + def test_aind_v2_decode_preserves_source_and_proposition_order(): source = _source([{'unit_ids': [56, 41], 'new_unit_id': 1000}]) From 0306c9cf314edf600ce3e5fe782b2e1dea20ca97 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 21:47:43 +0200 Subject: [PATCH 35/53] Preserve bound SLAY suggestions and reviews across curation rounds --- phy/apps/large_recording/adapter.py | 33 +- phy/apps/large_recording/curation.py | 139 +++++++- phy/apps/large_recording/prepare.py | 25 +- phy/apps/large_recording/replay.py | 20 +- phy/apps/large_recording/source.py | 41 +++ phy/apps/large_recording/supervisor.py | 20 +- .../large_recording/tests/test_adapter.py | 9 +- .../large_recording/tests/test_curation.py | 8 +- .../large_recording/tests/test_prepare.py | 20 +- .../tests/test_proposition_persistence.py | 324 ++++++++++++++++++ 10 files changed, 602 insertions(+), 37 deletions(-) create mode 100644 phy/apps/large_recording/tests/test_proposition_persistence.py diff --git a/phy/apps/large_recording/adapter.py b/phy/apps/large_recording/adapter.py index cc5a351ac..81398d78e 100644 --- a/phy/apps/large_recording/adapter.py +++ b/phy/apps/large_recording/adapter.py @@ -7,7 +7,11 @@ from phylib.io.model import get_template_params from phylib.utils import Bunch -from phy.cluster._propositions import MergePropositionController, decode_review_mapping +from phy.cluster._propositions import ( + MergePropositionController, + decode_curation_mapping, + decode_review_mapping, +) from ..base import _allocate_spike_counts, _sample_spikes_evenly from ..template.gui import TemplateController @@ -88,14 +92,25 @@ def _set_supervisor(self): self.supervisor._validate_native() def _load_merge_propositions(self): - controller = super()._load_merge_propositions() - reviews = self.bounded_session.extra_documents.get('curation_review.json') - if controller is not None and reviews is not None: - source, mapping = decode_review_mapping(reviews) - if source.get('sha256') != self._merge_proposition_sha256: - raise ValueError('Committed reviews belong to different merge propositions.') - controller = MergePropositionController(controller.catalog._replace(reviews=mapping)) - return controller + session = self.bounded_session + session.validate_proposition_documents() + self._merge_proposition_sha256 = None + if not self.enable_merge_propositions: + return None + item = session.proposition_documents.get('curation.json') + if item is None: + return None + from .curation import _read_json + + catalog = decode_curation_mapping( + _read_json(session.path / item['filename']), retired_units=session.retired_units + ) + self._merge_proposition_sha256 = item['sha256'] + reviews = session.extra_documents.get('curation_review.json') + if reviews is not None: + _, mapping = decode_review_mapping(reviews) + catalog = catalog._replace(reviews=mapping) + return MergePropositionController(catalog) def _set_cluster_metrics(self): super()._set_cluster_metrics() diff --git a/phy/apps/large_recording/curation.py b/phy/apps/large_recording/curation.py index 2827ad1b9..e7541504f 100644 --- a/phy/apps/large_recording/curation.py +++ b/phy/apps/large_recording/curation.py @@ -65,7 +65,12 @@ def _fsync_directory(path): def _safe_file(root, name): - if not isinstance(name, str) or Path(name).name != name or name in ('', '.', '..'): + if ( + not isinstance(name, str) + or Path(name).name != name + or name in ('', '.', '..') + or any(c in name for c in ('\\', '\0', '\n', '\r')) + ): raise ValueError('Manifest/checkpoint filename must be a plain local filename.') path = Path(root) / name if path.is_symlink(): @@ -73,6 +78,16 @@ def _safe_file(root, name): return path +def _validate_digest(value): + if ( + not isinstance(value, str) + or len(value) != 64 + or any(c not in '0123456789abcdef' for c in value) + ): + raise ValueError('Invalid SHA-256 digest.') + return value + + @contextmanager def _commit_lock(root): """Hold a process-safe OS lock; process exit releases it automatically.""" @@ -425,6 +440,11 @@ def _initialize(self, dataset_path): or sum(map(int, counts)) != full_n ): raise ValueError('Full unit counts do not match the source spike count/catalog.') + from phy.cluster._propositions import MergePropositionCatalog + + MergePropositionCatalog((), (), retired_units=manifest.get('retired_units', {})) + if set(manifest.get('retired_units', {})) & set(map(str, self.unit_ids)): + raise ValueError('Retired units cannot remain in the active source catalog.') self.base_next_cluster_id = _integer(manifest['next_cluster_id'], 'Next cluster ID') if self.base_next_cluster_id <= max(self.unit_ids): raise ValueError('Cluster allocator collides with the complete source catalog.') @@ -473,6 +493,7 @@ def _initialize(self, dataset_path): if not any(left <= start and stop <= right for left, right in intervals): raise ValueError('Evidence windows cross unsupported acquisition gaps.') for name, digest in manifest.get('bounded_files', {}).items(): + _validate_digest(digest) if _hash_file(_safe_file(self.path, name)) != digest: raise ValueError(f'Bounded package integrity check failed: {name}.') hashed_files = manifest.get('bounded_files', {}) @@ -525,6 +546,45 @@ def _initialize(self, dataset_path): self.metadata = copy.deepcopy(self.base_metadata) self.events = [] self.extra_documents = {} + if 'proposition_documents' not in manifest and any( + (self.path / name).exists() for name in ('curation.json', 'curation_review.json') + ): + raise ValueError( + 'Legacy bounded propositions have no preparation binding; reprepare the source.' + ) + self.proposition_documents = manifest.get('proposition_documents', {}) + if not isinstance(self.proposition_documents, dict) or set(self.proposition_documents) - { + 'curation.json', + 'curation_review.json', + }: + raise ValueError('Invalid bounded proposition document inventory.') + for name, item in self.proposition_documents.items(): + expected_name = ( + '_phy_curation_review_base.json' if name == 'curation_review.json' else name + ) + if ( + not isinstance(item, dict) + or set(item) != {'filename', 'sha256'} + or item['filename'] != expected_name + or hashed_files.get(expected_name) != item['sha256'] + ): + raise ValueError('Proposition documents must have immutable preparation digests.') + _validate_digest(item['sha256']) + value = _read_json(_safe_file(self.path, expected_name)) + if not isinstance(value, dict): + raise ValueError('Proposition documents must contain JSON objects.') + if name == 'curation_review.json': + self.extra_documents[name] = value + if ( + 'curation.json' in self.proposition_documents + and 'curation_review.json' not in self.extra_documents + ): + from phy.cluster._propositions import encode_review_mapping + + self.extra_documents['curation_review.json'] = encode_review_mapping( + {}, source_sha256=self.proposition_documents['curation.json']['sha256'] + ) + self.validate_proposition_documents() self.next_cluster_id = self.base_next_cluster_id self.checkpoint_path = None self._expected_pointer = None @@ -532,6 +592,53 @@ def _initialize(self, dataset_path): if pointer_path.exists(): self._load_checkpoint(pointer_path) + def validate_proposition_documents(self): + """Keep producer input and its inherited ledger bound to preparation.""" + for name, item in self.proposition_documents.items(): + path = _safe_file(self.path, item['filename']) + if not path.is_file() or _hash_file(path) != item['sha256']: + raise ValueError(f'Bounded proposition document changed: {name}.') + if 'proposition_documents' in self.manifest: + for name in ('curation.json',): + if name not in self.proposition_documents and (self.path / name).exists(): + raise ValueError('Unbound bounded proposition document.') + review = self.extra_documents.get('curation_review.json') + has_review = 'curation_review.json' in self.extra_documents + if has_review and 'proposition_documents' not in self.manifest: + raise ValueError( + 'Legacy bounded reviews have no preparation binding; reprepare the source.' + ) + if 'curation.json' in self.proposition_documents and not isinstance(review, dict): + raise ValueError('Bounded proposition checkpoints require a review ledger mapping.') + if has_review: + from phy.cluster._propositions import decode_review_mapping + + source, _ = decode_review_mapping(review) + expected = self.proposition_documents.get('curation.json', {}).get('sha256') + if ( + source.get('filename') != 'curation.json' + or expected is None + or source.get('sha256') != expected + ): + raise ValueError('Bounded review source filename/hash does not match preparation.') + + @property + def retired_units(self): + """Cumulative retirement history, without retargeting source suggestions.""" + result = copy.deepcopy(self.manifest.get('retired_units', {})) + # Events have already passed the complete-unit journal validator. + interpret_events(self.unit_ids, self.base_metadata, self.events) + for event in self.events: + if event['operation'] == 'merge': + for parent in event['parents']: + result[str(parent)] = {'operation': 'merge', 'replacements': [event['target']]} + elif event['operation'] == 'threshold_split': + result[str(event['parent'])] = { + 'operation': 'threshold_split', + 'replacements': list(event['children']), + } + return result + def _validated_state(self, assignments, metadata, events, next_cluster_id): self._validate_event_capabilities(events) _, projected_metadata, minimum = interpret_events( @@ -562,6 +669,7 @@ def _load_checkpoint(self, pointer_path): ): raise ValueError('Checkpoint belongs to a different bounded manifest.') for name, digest in descriptor['files'].items(): + _validate_digest(digest) if _hash_file(_safe_file(generation, name)) != digest: raise ValueError(f'Checkpoint corruption: {name}.') if not {'spike_clusters.npy', 'journal.json', 'metadata.json'} <= set(descriptor['files']): @@ -580,9 +688,20 @@ def _load_checkpoint(self, pointer_path): self.next_cluster_id = next_id self.checkpoint_path = generation self._expected_pointer = copy.deepcopy(pointer) + documents = descriptor.get('extra_documents', []) + if ( + not isinstance(documents, list) + or any(not isinstance(name, str) for name in documents) + or len(set(documents)) != len(documents) + or not set(documents) <= set(descriptor['files']) + or set(documents) + & {'checkpoint.json', 'spike_clusters.npy', 'journal.json', 'metadata.json'} + ): + raise ValueError('Extra checkpoint documents must be in the hash inventory.') self.extra_documents = { - name: _read_json(generation / name) for name in descriptor.get('extra_documents', []) + name: _read_json(_safe_file(generation, name)) for name in documents } + self.validate_proposition_documents() def snapshot(self): return { @@ -733,6 +852,7 @@ def save( extra_documents=None, ): """Validate, flush a generation, then atomically replace its commit pointer.""" + self.validate_proposition_documents() assignments = self.assignments if assignments is None else assignments metadata = self.metadata if metadata is None else metadata events = self.events if events is None else events @@ -740,9 +860,11 @@ def save( values, metadata, next_id = self._validated_state( assignments, metadata, events, next_cluster_id ) - documents = copy.deepcopy( - self.extra_documents if extra_documents is None else extra_documents - ) + if extra_documents is not None and not isinstance(extra_documents, dict): + raise ValueError('Extra checkpoint documents must be a filename-to-JSON mapping.') + documents = copy.deepcopy(self.extra_documents) + if extra_documents is not None: + documents.update(copy.deepcopy(extra_documents)) if not isinstance(documents, dict): raise ValueError('Extra checkpoint documents must be a filename-to-JSON mapping.') for name, value in documents.items(): @@ -750,6 +872,12 @@ def save( if name in ('checkpoint.json', 'spike_clusters.npy', 'journal.json', 'metadata.json'): raise ValueError('Extra document collides with a checkpoint state file.') _json_bytes(value) + previous_documents = self.extra_documents + try: + self.extra_documents = documents + self.validate_proposition_documents() + finally: + self.extra_documents = previous_documents root = self.path / '.phy-curation' generations = root / 'generations' generations.mkdir(parents=True, exist_ok=True) @@ -795,6 +923,7 @@ def _save_generation(self, generations, values, metadata, events, next_id, docum _fsync_directory(generations) pointer = {'generation': identifier, 'sha256': _digest(descriptor)} _write_json(pointer_tmp, pointer) + self.validate_proposition_documents() os.replace(pointer_tmp, root / 'current.json') _fsync_directory(root) except BaseException: diff --git a/phy/apps/large_recording/prepare.py b/phy/apps/large_recording/prepare.py index 31edc85e3..9bc334c0a 100644 --- a/phy/apps/large_recording/prepare.py +++ b/phy/apps/large_recording/prepare.py @@ -249,8 +249,12 @@ def _prepare_source( for name in ('curation.json', 'curation_review.json') if (source.path / name).is_file() ] + producer_hashes = {path.name: hash_file(path) for path in producer_documents} fixed_bytes = ( - sum(path.stat().st_size for path in producer_documents) + sum( + path.stat().st_size * (2 if path.name == 'curation_review.json' else 1) + for path in producer_documents + ) + summary_bytes + sum((source.path / name).stat().st_size for name in source.arrays.keys() & STATIC) ) @@ -605,12 +609,29 @@ def accept(start, end, kind, segment, stratum_id): } if getattr(source, 'time_base', None) is not None: manifest['time_base'] = source.time_base + manifest['retired_units'] = source.retired_units + manifest['proposition_documents'] = {} for document in producer_documents: - shutil.copyfile(document, temporary / document.name) + # Root review is a convenience copy; its inherited baseline is immutable. + name = ( + '_phy_curation_review_base.json' + if document.name == 'curation_review.json' + else document.name + ) + shutil.copyfile(document, temporary / name) + manifest['proposition_documents'][document.name] = { + 'filename': name, + 'sha256': producer_hashes[document.name], + } + if hash_file(temporary / name) != producer_hashes[document.name]: + raise ValueError('Producer proposition document changed during preparation.') + if name != document.name: + shutil.copyfile(document, temporary / document.name) bound_paths = [ *temporary.glob('*.npy'), temporary / 'params.py', temporary / '_phy_cluster_metadata.json', + *(temporary / item['filename'] for item in manifest['proposition_documents'].values()), ] manifest['bounded_files'] = {p.name: hash_file(p) for p in sorted(bound_paths)} manifest['preparation_identity'] = hash_json(manifest) diff --git a/phy/apps/large_recording/replay.py b/phy/apps/large_recording/replay.py index 7d821ec9a..d292a6b59 100644 --- a/phy/apps/large_recording/replay.py +++ b/phy/apps/large_recording/replay.py @@ -16,7 +16,7 @@ interpret_events, project_assignments, ) -from .source import PER_SPIKE, Source, _has_raw_paths, close_array, publish_directory +from .source import PER_SPIKE, Source, _has_raw_paths, close_array, hash_file, publish_directory def _merge_mapping(unit_ids, events): @@ -76,6 +76,7 @@ def apply_curation(source_params, bounded_dir, output_dir, batch_size=100000): def _apply_curation(source, session, output_dir, batch_size): + session.validate_proposition_documents() manifest = session.manifest expected = manifest['source'] if source.identity != expected['identity']: @@ -87,6 +88,9 @@ def _apply_curation(source, session, output_dir, batch_size): or source.n_spikes != manifest['num_spikes'] ): raise ValueError('Source catalog or spike count does not match bounded preparation.') + for name, item in session.proposition_documents.items(): + if hash_file(source.path / name) != item['sha256']: + raise ValueError('Source proposition documents changed since preparation.') # Identity/revision bind the complete source. Validate the actual projection # too, so a tampered bounded base cannot silently replay unrelated evidence. source_assignments = source.arrays['spike_clusters.npy'].reshape(-1) @@ -183,6 +187,17 @@ def _apply_curation(source, session, output_dir, batch_size): assignments = None _write_metadata(stage, metadata) _write_json(stage / '_phy_curation_journal.json', session.events) + proposition_hashes = {} + item = session.proposition_documents.get('curation.json') + if item is not None: + shutil.copyfile(session.path / item['filename'], stage / 'curation.json') + proposition_hashes['curation.json'] = hash_file(stage / 'curation.json') + if proposition_hashes['curation.json'] != item['sha256']: + raise ValueError('Producer propositions changed during replay.') + review = session.extra_documents.get('curation_review.json') + if review is not None and item is not None: + _write_json(stage / 'curation_review.json', review) + proposition_hashes['curation_review.json'] = hash_file(stage / 'curation_review.json') # Re-reading verifies alignment, full catalog and immutable byte digests. curated = Source(stage / 'params.py', batch_size=batch_size) if curated.identity != source.identity or curated.n_spikes != source.n_spikes: @@ -211,6 +226,8 @@ def _apply_curation(source, session, output_dir, batch_size): 'preparation_sha256': _digest(manifest), 'next_cluster_id': session.next_cluster_id, 'unit_ids': sorted(active_units), + 'retired_units': session.retired_units, + 'proposition_documents': proposition_hashes, }, ) curated.close() @@ -223,6 +240,7 @@ def _apply_curation(source, session, output_dir, batch_size): # Refuse replacement even when a racing caller creates the target. if output.exists(): raise FileExistsError(f'Curated output already exists: {output}.') + session.validate_proposition_documents() publish_directory(stage, output) _fsync_directory(output.parent) except BaseException: diff --git a/phy/apps/large_recording/source.py b/phy/apps/large_recording/source.py index 321c6db6c..fb70eccaa 100644 --- a/phy/apps/large_recording/source.py +++ b/phy/apps/large_recording/source.py @@ -405,6 +405,47 @@ def _initialize( if not isinstance(unit, int) or unit < 0: raise ValueError('Lineage unit IDs must be nonnegative integers.') counts.setdefault(unit, 0) + self.retired_units = lineage.get('retired_units', {}) + if not isinstance(self.retired_units, dict): + raise ValueError('Lineage retired_units must be a mapping.') + for unit, record in self.retired_units.items(): + if ( + not isinstance(unit, str) + or not unit.isdecimal() + or str(int(unit)) != unit + or int(unit) > np.iinfo(np.int32).max + or not isinstance(record, dict) + or set(record) != {'operation', 'replacements'} + or record['operation'] not in ('merge', 'threshold_split') + ): + raise ValueError('Invalid lineage retired unit record.') + replacements = record['replacements'] + if ( + not isinstance(replacements, list) + or not replacements + or any( + type(value) is not int or value < 0 or value > np.iinfo(np.int32).max + for value in replacements + ) + or len(set(replacements)) != len(replacements) + or len(replacements) != (1 if record['operation'] == 'merge' else 2) + or int(unit) in replacements + or int(unit) in counts + ): + raise ValueError('Invalid lineage retired unit replacements.') + documents = lineage.get('proposition_documents', {}) + if not isinstance(documents, dict): + raise ValueError('Lineage proposition documents must be a mapping.') + for name, digest in documents.items(): + if ( + name not in ('curation.json', 'curation_review.json') + or not isinstance(digest, str) + or len(digest) != 64 + or any(c not in '0123456789abcdef' for c in digest) + or (self.path / name).is_symlink() + or hash_file(self.path / name) != digest + ): + raise ValueError('Lineage proposition document integrity check failed.') if any(unit < 0 or unit > np.iinfo(np.int32).max for unit in counts): raise ValueError( 'Unit IDs must fit nonnegative int32 for the current Phy loader; spike sample/row coordinates remain int64.' diff --git a/phy/apps/large_recording/supervisor.py b/phy/apps/large_recording/supervisor.py index a5765232f..bcca4c9e4 100644 --- a/phy/apps/large_recording/supervisor.py +++ b/phy/apps/large_recording/supervisor.py @@ -301,6 +301,10 @@ def _synchronize_metadata(self): self.cluster_meta._data = data def _refresh_bounded(self): + if self.merge_propositions is not None: + self.merge_propositions.project_live_ids( + self.clustering.cluster_ids, retired_units=self.session.retired_units + ) if self.gui is not None: data = self.cluster_info self.cluster_view.change(data) @@ -438,15 +442,17 @@ def _after_history(self): def save(self): self._validate_native() + self.session.validate_proposition_documents() documents = None if self.merge_propositions is not None: - from .source import hash_file - - documents = { - 'curation_review.json': self.merge_propositions.catalog.review_mapping( - source_sha256=hash_file(self.session.path / 'curation.json') - ) - } + documents = dict(self.session.extra_documents) + documents.update( + { + 'curation_review.json': self.merge_propositions.catalog.review_mapping( + source_sha256=self.session.proposition_documents['curation.json']['sha256'] + ) + } + ) self.session.save( assignments=self.clustering.spike_clusters, metadata=self.session.metadata, diff --git a/phy/apps/large_recording/tests/test_adapter.py b/phy/apps/large_recording/tests/test_adapter.py index 76d4dda47..94f280941 100644 --- a/phy/apps/large_recording/tests/test_adapter.py +++ b/phy/apps/large_recording/tests/test_adapter.py @@ -16,8 +16,10 @@ from phy.apps.template.gui import TemplateController -def make_controller(tmp_path, sparse=False): +def make_controller(tmp_path, sparse=False, propositions=None): params = make_gui_sorting(tmp_path / 'source') + if propositions is not None: + (params.parent / 'curation.json').write_text(json.dumps(propositions)) output = prepare_large( params, tmp_path / 'bounded', @@ -395,11 +397,10 @@ def test_empty_window_and_nonfinite_amplitude_measurements(qtbot, tmp_path): def test_proposition_reviews_checkpoint_and_failed_review_history(tmp_path): from phy.cluster._propositions import MergePropositionController, decode_curation_mapping - _, controller = make_controller(tmp_path) - supervisor = controller.supervisor mapping = {'format_version': '2', 'unit_ids': [0, 1, 2, 99], 'merges': [{'unit_ids': [0, 1]}]} + _, controller = make_controller(tmp_path, propositions=mapping) + supervisor = controller.supervisor producer = controller.dir_path / 'curation.json' - producer.write_text(json.dumps(mapping)) supervisor.merge_propositions = MergePropositionController(decode_curation_mapping(mapping)) key = supervisor.merge_propositions.catalog.propositions[0].key try: diff --git a/phy/apps/large_recording/tests/test_curation.py b/phy/apps/large_recording/tests/test_curation.py index a0f5258e2..ed667ef8d 100644 --- a/phy/apps/large_recording/tests/test_curation.py +++ b/phy/apps/large_recording/tests/test_curation.py @@ -109,13 +109,13 @@ def test_merge_label_snapshot_branch_reopen(tmp_path): session.restore(baseline) session.record_merge([1, 2], 100, {'group': 'noise'}) session.record_label('custom', [99, 100], 'reviewed') - session.save(extra_documents={'curation_review.json': {'accepted': [100]}}) + session.save(extra_documents={'supplemental.json': {'accepted': [100]}}) reopened = BoundedSession(session.path) assert reopened.next_cluster_id == 101 assert reopened.events == session.events assert reopened.metadata == session.metadata assert np.array_equal(reopened.assignments, session.assignments) - assert reopened.extra_documents == {'curation_review.json': {'accepted': [100]}} + assert reopened.extra_documents == {'supplemental.json': {'accepted': [100]}} assert source.unit_ids.tolist() == [0, 1, 2, 99] assert 99 not in session.base_assignments @@ -298,9 +298,9 @@ def test_stale_session_save_rejected_without_losing_first_commit(tmp_path): second = BoundedSession(first.path) first.record_merge([0, 1], 100, {'group': 'good'}) second.record_merge([1, 2], 100, {'group': 'noise'}) - first.save(extra_documents={'curation_review.json': {'accepted': [100]}}) + first.save(extra_documents={'supplemental.json': {'accepted': [100]}}) with pytest.raises(ValueError, match='reopen'): - second.save(extra_documents={'curation_review.json': {'rejected': [100]}}) + second.save(extra_documents={'supplemental.json': {'rejected': [100]}}) reopened = BoundedSession(first.path) assert reopened.events == first.events assert reopened.extra_documents == first.extra_documents diff --git a/phy/apps/large_recording/tests/test_prepare.py b/phy/apps/large_recording/tests/test_prepare.py index a3688fd8c..51c15d46a 100644 --- a/phy/apps/large_recording/tests/test_prepare.py +++ b/phy/apps/large_recording/tests/test_prepare.py @@ -202,11 +202,21 @@ def test_final_windows_records_match_retained_samples_and_gaps(tmp_path): def test_prepare_protects_loader_and_preserves_producer_documents(tmp_path): params = make_sorting(tmp_path / 'full') - for name, value in ( - ('curation.json', {'merge': [[0, 1]]}), - ('curation_review.json', {'accepted': []}), - ): - (params.parent / name).write_text(json.dumps(value)) + (params.parent / 'curation.json').write_text( + json.dumps({'format_version': '2', 'unit_ids': [0, 1], 'merges': [{'unit_ids': [0, 1]}]}) + ) + (params.parent / 'curation_review.json').write_text( + json.dumps( + { + 'format_version': '1', + 'source': { + 'filename': 'curation.json', + 'sha256': hash_file(params.parent / 'curation.json'), + }, + 'reviews': {}, + } + ) + ) output = prepare_large(params, tmp_path / 'bounded', window_seconds=20, stratum_seconds=20) manifest = json.loads((output / '_phy_curation_manifest.json').read_text()) assert manifest['bounded_files']['params.py'] == hash_file(output / 'params.py') diff --git a/phy/apps/large_recording/tests/test_proposition_persistence.py b/phy/apps/large_recording/tests/test_proposition_persistence.py new file mode 100644 index 000000000..918d4a8a2 --- /dev/null +++ b/phy/apps/large_recording/tests/test_proposition_persistence.py @@ -0,0 +1,324 @@ +"""Producer bytes, durable decisions and retirement survive bounded replay rounds.""" + +import json + +import pytest + +from phy.apps.large_recording.curation import BoundedSession, _digest +from phy.apps.large_recording.prepare import prepare_large +from phy.apps.large_recording.replay import apply_curation +from phy.apps.large_recording.source import Source, hash_file +from phy.apps.large_recording.tests.test_adapter import make_gui_sorting +from phy.apps.template.gui import TemplateController +from phy.cluster._propositions import PropositionReview, encode_review_mapping, proposition_key + + +def prepare(tmp_path): + params = make_gui_sorting(tmp_path / 'source') + producer = b'{"format_version":"2", "unit_ids":[0,1,2,99], "merges":[{"unit_ids":[0,1]},{"unit_ids":[1,2]}], "producer": {"unchanged":true}}\n' + (params.parent / 'curation.json').write_bytes(producer) + review = encode_review_mapping( + { + proposition_key([1, 2]): PropositionReview('rejected'), + proposition_key([77, 78]): PropositionReview('accepted', [77, 78], 90), + }, + source_sha256=hash_file(params.parent / 'curation.json'), + ) + (params.parent / 'curation_review.json').write_text(json.dumps(review)) + bounded = prepare_large(params, tmp_path / 'bounded', window_seconds=20, stratum_seconds=20) + return params, bounded, producer, review + + +@pytest.mark.parametrize('mode', ['direct', 'enabled', 'disabled']) +def test_three_noop_rounds_preserve_exact_source_and_complete_ledger(tmp_path, mode): + params, bounded, producer, review = prepare(tmp_path) + original_reviews = review['reviews'] + for round_index in range(3): + if mode == 'direct': + session = BoundedSession(bounded) + session.save() + session.close() + else: + controller = TemplateController( + dir_path=bounded, + config_dir=tmp_path / 'config', + plugins=[], + enable_merge_propositions=mode == 'enabled', + ) + try: + controller.supervisor.save() + finally: + controller.close() + # A committed generation outranks every loose-root review state. + root_review = bounded / 'curation_review.json' + if round_index == 0: + root_review.write_text('{malformed') + elif round_index == 1: + root_review.write_text(json.dumps(dict(review, reviews={}))) + else: + root_review.unlink(missing_ok=True) + reopened = TemplateController(dir_path=bounded, config_dir=tmp_path / 'config', plugins=[]) + try: + assert ( + reopened.supervisor.merge_propositions.catalog.review_mapping()['reviews'] + == original_reviews + ) + finally: + reopened.close() + output = apply_curation(params, bounded, tmp_path / f'curated-{round_index}') + assert (output / 'curation.json').read_bytes() == producer + assert ( + json.loads((output / 'curation_review.json').read_text())['reviews'] + == original_reviews + ) + lineage = json.loads((output / '_phy_curation_lineage.json').read_text()) + assert lineage['proposition_documents'] == { + name: hash_file(output / name) for name in ('curation.json', 'curation_review.json') + } + params = output / 'params.py' + bounded = prepare_large( + params, tmp_path / f'bounded-{round_index}', window_seconds=20, stratum_seconds=20 + ) + + +def test_accepted_and_rejected_decisions_and_retirements_survive_replay(tmp_path): + params, bounded, producer, review = prepare(tmp_path) + controller = TemplateController(dir_path=bounded, config_dir=tmp_path / 'config', plugins=[]) + try: + supervisor = controller.supervisor + key = proposition_key([0, 1]) + supervisor.merge_propositions.accept(key, [0, 1], 100) + supervisor.merge([0, 1], to=100) + supervisor.save() + expected_reviews = supervisor.merge_propositions.catalog.review_mapping()['reviews'] + finally: + controller.close() + output = apply_curation(params, bounded, tmp_path / 'curated') + assert (output / 'curation.json').read_bytes() == producer + assert json.loads((output / 'curation_review.json').read_text())['reviews'] == expected_reviews + source = Source(output / 'params.py') + try: + assert source.retired_units == { + '0': {'operation': 'merge', 'replacements': [100]}, + '1': {'operation': 'merge', 'replacements': [100]}, + } + finally: + source.close() + second = prepare_large( + output / 'params.py', tmp_path / 'second', window_seconds=20, stratum_seconds=20 + ) + session = BoundedSession(second) + session.record_split( + 100, + 101, + 102, + {'attribute': 'amplitudes.npy', 'operator': '<', 'threshold': 4.0, 'nonfinite': 'keep'}, + ) + session.save() + session.close() + final = apply_curation(output / 'params.py', second, tmp_path / 'final') + lineage = json.loads((final / '_phy_curation_lineage.json').read_text()) + assert lineage['retired_units']['100'] == { + 'operation': 'threshold_split', + 'replacements': [102, 101], + } + assert lineage['retired_units']['0'] == {'operation': 'merge', 'replacements': [100]} + + +@pytest.mark.parametrize('target', ['curation.json', '_phy_curation_review_base.json']) +def test_mutation_after_load_rejects_save_and_replay(tmp_path, target): + params, bounded, _, _ = prepare(tmp_path) + session = BoundedSession(bounded) + session.save() + (bounded / target).write_text('{}') + try: + with pytest.raises(ValueError, match='changed'): + session.save() + with pytest.raises(ValueError, match='integrity'): + apply_curation(params, bounded, tmp_path / 'bad') + assert not (tmp_path / 'bad').exists() + finally: + session.close() + + +def test_generation_extra_document_requires_hash_inventory(tmp_path): + _, bounded, _, _ = prepare(tmp_path) + session = BoundedSession(bounded) + generation = session.save() + session.close() + descriptor = json.loads((generation / 'checkpoint.json').read_text()) + descriptor['files'].pop('curation_review.json') + (generation / 'checkpoint.json').write_text(json.dumps(descriptor)) + pointer = bounded / '.phy-curation/current.json' + data = json.loads(pointer.read_text()) + data['sha256'] = _digest(descriptor) + pointer.write_text(json.dumps(data)) + with pytest.raises(ValueError, match='hash inventory'): + BoundedSession(bounded) + + +@pytest.mark.parametrize('operation', ['prepare', 'replay']) +def test_copy_race_rejects_producer_mutation_without_publication(tmp_path, monkeypatch, operation): + from phy.apps.large_recording import prepare as preparation + from phy.apps.large_recording import replay + + params, bounded, _, _ = prepare(tmp_path) + session = BoundedSession(bounded) + session.save() + session.close() + module = preparation if operation == 'prepare' else replay + original_copy = module.shutil.copyfile + + def mutate_copy(source, destination, *args, **kwargs): + result = original_copy(source, destination, *args, **kwargs) + if str(destination).endswith('/curation.json'): + from pathlib import Path + + Path(destination).write_text('{}') + return result + + monkeypatch.setattr(module.shutil, 'copyfile', mutate_copy) + output = tmp_path / 'bad' + with pytest.raises(ValueError, match='changed'): + if operation == 'prepare': + prepare_large(params, output, window_seconds=20, stratum_seconds=20) + else: + apply_curation(params, bounded, output) + assert not output.exists() + + +@pytest.mark.parametrize( + 'filename, digest', + [ + ('../curation.json', 'valid'), + ('other.json', 'valid'), + ('curation.json', None), + ('curation.json', '0' * 64), + ('curation.json', 'xyz'), + ], +) +def test_bounded_inherited_review_requires_exact_filename_and_hash(tmp_path, filename, digest): + params, _, _, review = prepare(tmp_path) + review['source']['filename'] = filename + if digest is None: + review['source'].pop('sha256') + elif digest != 'valid': + review['source']['sha256'] = digest + (params.parent / 'curation_review.json').write_text(json.dumps(review)) + with pytest.raises(ValueError, match='filename/hash'): + prepare_large(params, tmp_path / 'bad', window_seconds=20, stratum_seconds=20) + assert not (tmp_path / 'bad').exists() + + +def test_gui_save_rejects_producer_mutation_since_load(tmp_path): + _, bounded, _, _ = prepare(tmp_path) + controller = TemplateController(dir_path=bounded, config_dir=tmp_path / 'config', plugins=[]) + try: + (bounded / 'curation.json').write_text('{}') + with pytest.raises(ValueError, match='changed'): + controller.supervisor.save() + assert not (bounded / '.phy-curation/current.json').exists() + finally: + controller.close() + + +def test_replay_rejects_source_producer_mutation(tmp_path): + params, bounded, _, _ = prepare(tmp_path) + session = BoundedSession(bounded) + session.save() + session.close() + (params.parent / 'curation.json').write_text('{}') + with pytest.raises(ValueError, match='changed since preparation'): + apply_curation(params, bounded, tmp_path / 'bad') + assert not (tmp_path / 'bad').exists() + + +def test_legacy_bounded_propositions_require_repreparation(tmp_path): + _, bounded, _, _ = prepare(tmp_path) + path = bounded / '_phy_curation_manifest.json' + manifest = json.loads(path.read_text()) + manifest.pop('proposition_documents') + path.write_text(json.dumps(manifest)) + with pytest.raises(ValueError, match='reprepare'): + BoundedSession(bounded) + + +def test_legacy_checkpoint_review_without_loose_root_requires_repreparation(tmp_path): + from phy.apps.large_recording.curation import _hash_file + from phy.apps.large_recording.tests.test_curation import make_session + + _, session = make_session(tmp_path) + generation = session.save(extra_documents={'supplemental.json': {}}) + session.close() + (generation / 'supplemental.json').rename(generation / 'curation_review.json') + descriptor_path = generation / 'checkpoint.json' + descriptor = json.loads(descriptor_path.read_text()) + descriptor['extra_documents'] = ['curation_review.json'] + descriptor['files'].pop('supplemental.json') + descriptor['files']['curation_review.json'] = _hash_file(generation / 'curation_review.json') + descriptor_path.write_text(json.dumps(descriptor)) + pointer_path = session.path / '.phy-curation/current.json' + pointer = json.loads(pointer_path.read_text()) + pointer['sha256'] = _digest(descriptor) + pointer_path.write_text(json.dumps(pointer)) + with pytest.raises(ValueError, match='reprepare'): + BoundedSession(session.path) + + +@pytest.mark.parametrize('mode', ['direct', 'disabled']) +def test_suggestions_without_reviews_publish_empty_bound_ledger(tmp_path, mode): + params, _, producer, _ = prepare(tmp_path) + (params.parent / 'curation_review.json').unlink() + bounded = prepare_large(params, tmp_path / 'empty', window_seconds=20, stratum_seconds=20) + if mode == 'direct': + session = BoundedSession(bounded) + session.save() + session.close() + else: + controller = TemplateController( + dir_path=bounded, + config_dir=tmp_path / 'config', + plugins=[], + enable_merge_propositions=False, + ) + try: + controller.supervisor.save() + finally: + controller.close() + output = apply_curation(params, bounded, tmp_path / 'curated') + assert (output / 'curation.json').read_bytes() == producer + assert json.loads((output / 'curation_review.json').read_text()) == { + 'format_version': '1', + 'source': {'filename': 'curation.json', 'sha256': hash_file(output / 'curation.json')}, + 'reviews': {}, + } + + +def test_null_review_cannot_remove_inherited_decisions(tmp_path): + _, bounded, _, review = prepare(tmp_path) + session = BoundedSession(bounded) + try: + with pytest.raises(ValueError, match='ledger mapping'): + session.save(extra_documents={'curation_review.json': None}) + assert session.extra_documents['curation_review.json'] == review + assert not (bounded / '.phy-curation/current.json').exists() + finally: + session.close() + + +def test_committed_generation_cannot_omit_required_review_ledger(tmp_path): + _, bounded, _, _ = prepare(tmp_path) + session = BoundedSession(bounded) + generation = session.save() + session.close() + descriptor_path = generation / 'checkpoint.json' + descriptor = json.loads(descriptor_path.read_text()) + descriptor['extra_documents'] = [] + descriptor['files'].pop('curation_review.json') + descriptor_path.write_text(json.dumps(descriptor)) + pointer_path = bounded / '.phy-curation/current.json' + pointer = json.loads(pointer_path.read_text()) + pointer['sha256'] = _digest(descriptor) + pointer_path.write_text(json.dumps(pointer)) + with pytest.raises(ValueError, match='ledger mapping'): + BoundedSession(bounded) From b71514c8cde33d8f212cd92fc259962d9693a209 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 21:47:49 +0200 Subject: [PATCH 36/53] Add a source-preserving AIND export acceptance validator --- .../tests/test_export_validator.py | 207 ++++++++++++++++ tools/validate_aind_export.py | 220 ++++++++++++++++++ 2 files changed, 427 insertions(+) create mode 100644 phy/apps/large_recording/tests/test_export_validator.py create mode 100644 tools/validate_aind_export.py diff --git a/phy/apps/large_recording/tests/test_export_validator.py b/phy/apps/large_recording/tests/test_export_validator.py new file mode 100644 index 000000000..dc4808ee3 --- /dev/null +++ b/phy/apps/large_recording/tests/test_export_validator.py @@ -0,0 +1,207 @@ +"""Focused contract and report tests for the AIND export validator.""" + +import json + +import tools.validate_aind_export as validator +from phy.apps.large_recording.source import hash_file +from phy.apps.large_recording.tests.test_source import make_sorting +from tools.validate_aind_export import main, validate_export + + +def test_validator_reports_engineering_evidence_and_input_hashes(tmp_path): + params = make_sorting(tmp_path / 'source') + params.write_text( + params.read_text() + + "time_base = {'kind': 'elapsed_ticks', 'ticks_per_second': 1.0}\n" + + 'valid_intervals = [[0, 20]]\n' + ) + report = validate_export( + params, + phy_revision='phy-test-revision', + exporter_revision='exporter-test-revision', + batch_size=4, + ) + + assert report['status'] == 'passed' + assert report['failures'] == [] + assert report['engineering_validation_only'] is True + assert report['acquisition_truth_established'] is False + assert report['source']['num_spikes'] == 12 + assert report['source']['num_samples'] == 20 + assert report['source']['exposure']['valid_samples'] == 20 + assert report['source']['input_files']['spike_times.npy']['sha256'] + assert report['phy_revision'] == 'phy-test-revision' + assert report['exporter_revision'] == 'exporter-test-revision' + assert report['timing_seconds']['total'] >= 0 + + +def test_validator_preparation_report_matches_manifest_and_preserves_source(tmp_path): + params = make_sorting(tmp_path / 'source') + params.write_text( + params.read_text().replace('num_samples = 20', 'num_samples = 120') + + "time_base = {'kind': 'elapsed_ticks', 'ticks_per_second': 1.0}\n" + + 'valid_intervals = [[0, 120]]\n' + ) + source_path = params.parent + before_hashes = { + path.name: hash_file(path) for path in source_path.iterdir() if path.is_file() + } + output_dir = tmp_path / 'bounded' + + report = validate_export( + params, + phy_revision='phy-test-revision', + exporter_revision='exporter-test-revision', + output_dir=output_dir, + batch_size=4, + ) + + assert report['status'] == 'passed', report['failures'] + output = report['prepared_output'] + manifest = json.loads((output_dir / '_phy_curation_manifest.json').read_text()) + disk_bytes = sum(path.stat().st_size for path in output_dir.rglob('*') if path.is_file()) + assert output['num_spikes'] == manifest['bounded_num_spikes'] + assert output['num_units'] == len(manifest['unit_ids']) + assert output['waveform_coverage'] == manifest['waveform_coverage'] + assert output['budgets'] == manifest['budgets'] + assert output['output_bytes'] == disk_bytes + assert report['source']['input_files'] == { + name: {'bytes': (source_path / name).stat().st_size, 'sha256': digest} + for name, digest in before_hashes.items() + } + assert { + path.name: hash_file(path) for path in source_path.iterdir() if path.is_file() + } == before_hashes + + +def test_validator_reports_source_rejection_as_json_failure(tmp_path): + params = make_sorting(tmp_path / 'source') + (params.parent / 'timestamps.json').write_text(json.dumps({'frames': []})) + + report = validate_export( + params, + phy_revision='phy-test-revision', + exporter_revision='exporter-test-revision', + ) + + assert report['status'] == 'failed' + assert len(report['failures']) == 1 + assert 'explicit time_base' in report['failures'][0]['message'] + assert report['acquisition_truth_established'] is False + + +def test_validator_requires_explicit_aind_time_and_exposure_contract(tmp_path): + params = make_sorting(tmp_path / 'source') + + report = validate_export( + params, + phy_revision='phy-test-revision', + exporter_revision='exporter-test-revision', + ) + + assert report['status'] == 'failed' + assert ( + report['failures'][0]['message'] == 'AIND export requires an explicit time_base contract.' + ) + + +def test_validator_rejects_nested_preparation_destination(tmp_path): + params = make_sorting(tmp_path / 'source') + params.write_text( + params.read_text() + + "time_base = {'kind': 'elapsed_ticks', 'ticks_per_second': 1.0}\n" + + 'valid_intervals = [[0, 20]]\n' + ) + + report = validate_export( + params, + phy_revision='phy-test-revision', + exporter_revision='exporter-test-revision', + output_dir=params.parent / 'derived', + ) + + assert report['status'] == 'failed' + assert 'outside the immutable source' in report['failures'][0]['message'] + assert not (params.parent / 'derived').exists() + + +def test_cli_report_cannot_overwrite_source_params(tmp_path, capsys): + params = make_sorting(tmp_path / 'source') + original = params.read_bytes() + + result = main( + [ + str(params), + '--phy-revision', + 'phy-test-revision', + '--exporter-revision', + 'exporter-test-revision', + '--report', + str(params), + ] + ) + + assert result == 1 + assert params.read_bytes() == original + report = json.loads(capsys.readouterr().out) + assert report['status'] == 'failed' + assert 'outside the immutable source' in report['failures'][0]['message'] + + +def test_cli_report_cannot_target_future_prepared_output(tmp_path, capsys): + params = make_sorting(tmp_path / 'source') + params.write_text( + params.read_text() + + "time_base = {'kind': 'elapsed_ticks', 'ticks_per_second': 1.0}\n" + + 'valid_intervals = [[0, 20]]\n' + ) + output_dir = tmp_path / 'prepared' + report_path = output_dir / 'params.py' + + result = main( + [ + str(params), + '--phy-revision', + 'phy-test-revision', + '--exporter-revision', + 'exporter-test-revision', + '--output-dir', + str(output_dir), + '--report', + str(report_path), + ] + ) + + assert result == 1 + assert not output_dir.exists() + report = json.loads(capsys.readouterr().out) + assert report['status'] == 'failed' + assert 'prepared output directories' in report['failures'][0]['message'] + + +def test_cli_report_exclusive_create_preserves_racing_file(tmp_path, monkeypatch, capsys): + params = make_sorting(tmp_path / 'source') + report_path = tmp_path / 'report.json' + + def create_report_during_validation(*args, **kwargs): + report_path.write_text('keep me', encoding='utf-8') + return {'status': 'passed'} + + monkeypatch.setattr(validator, 'validate_export', create_report_during_validation) + result = main( + [ + str(params), + '--phy-revision', + 'phy-test-revision', + '--exporter-revision', + 'exporter-test-revision', + '--report', + str(report_path), + ] + ) + + assert result == 1 + assert report_path.read_text(encoding='utf-8') == 'keep me' + report = json.loads(capsys.readouterr().out) + assert report['status'] == 'failed' + assert 'already exists' in report['failures'][0]['message'] diff --git a/tools/validate_aind_export.py b/tools/validate_aind_export.py new file mode 100644 index 000000000..122ddf0d3 --- /dev/null +++ b/tools/validate_aind_export.py @@ -0,0 +1,220 @@ +"""Validate an AIND-produced sorting against Phy's declared source contract. + +This checks software interoperability. It cannot establish acquisition truth; +the exporter revision and authoritative exposure/filler policy must be supplied +and reviewed by the producer. +""" + +import argparse +import json +import sys +import time +from pathlib import Path + +REPOSITORY = Path(__file__).resolve().parents[1] +if str(REPOSITORY) not in sys.path: + sys.path.insert(0, str(REPOSITORY)) + +from phy.apps.large_recording.prepare import prepare_large +from phy.apps.large_recording.source import Source, hash_file + +REPORT_FORMAT = 'phy_aind_export_validation' +REPORT_VERSION = 1 + + +def _failure(error): + return {'type': type(error).__name__, 'message': str(error)} + + +def _cli_failure(error, args): + report = { + 'format': REPORT_FORMAT, + 'format_version': REPORT_VERSION, + 'status': 'failed', + 'failures': [_failure(error)], + 'engineering_validation_only': True, + 'acquisition_truth_established': False, + 'phy_revision': args.phy_revision, + 'exporter_revision': args.exporter_revision, + } + sys.stdout.write(json.dumps(report, indent=2, sort_keys=True) + '\n') + return 1 + + +def _input_inventory(source_path): + """Hash regular files in the source without interpreting their contents.""" + return { + path.name: {'bytes': path.stat().st_size, 'sha256': hash_file(path)} + for path in sorted(source_path.iterdir()) + if path.is_file() + } + + +def validate_export( + params_path, + *, + phy_revision, + exporter_revision, + output_dir=None, + max_spikes=2_000_000, + max_bytes=536_870_912, + batch_size=100_000, +): + """Return a JSON-serializable validation report; never edits the source.""" + started = time.perf_counter() + params_path = Path(params_path).resolve() + source_path = params_path.parent + report = { + 'format': REPORT_FORMAT, + 'format_version': REPORT_VERSION, + 'status': 'failed', + 'failures': [], + 'engineering_validation_only': True, + 'acquisition_truth_established': False, + 'requires_authoritative_exposure_and_filler_policy': True, + 'phy_revision': phy_revision, + 'exporter_revision': exporter_revision, + 'source': {'params_path': str(params_path), 'path': str(source_path)}, + 'budgets': {'max_spikes': int(max_spikes), 'max_bytes': int(max_bytes)}, + 'timing_seconds': {}, + } + if not phy_revision or not exporter_revision: + report['failures'].append( + _failure(ValueError('Both Phy and exporter revisions must be supplied.')) + ) + report['timing_seconds']['total'] = time.perf_counter() - started + return report + try: + phase = time.perf_counter() + with Source(params_path, batch_size=batch_size) as source: + report['timing_seconds']['source_validation'] = time.perf_counter() - phase + report['source'].update( + { + 'sha256': source.identity['sha256'], + 'num_spikes': source.n_spikes, + 'num_units': len(source.unit_ids), + 'sample_rate_hz': source.sample_rate, + 'num_samples': source.num_samples, + 'time_base': source.time_base, + 'exposure': { + 'valid_intervals': source.valid_intervals.tolist(), + 'valid_samples': int( + (source.valid_intervals[:, 1] - source.valid_intervals[:, 0]).sum() + ), + 'valid_seconds': float( + (source.valid_intervals[:, 1] - source.valid_intervals[:, 0]).sum() + / source.sample_rate + ), + }, + 'array_counts': { + name: {'rows': int(len(array)), 'shape': list(array.shape)} + for name, array in sorted(source.arrays.items()) + }, + } + ) + source_root = source.path + declared_intervals = ( + 'valid_intervals' in source.params + or 'valid_intervals' in source.upstream_recording + ) + if source.time_base is None: + raise ValueError('AIND export requires an explicit time_base contract.') + if source.time_base['kind'] != 'elapsed_ticks': + raise ValueError('AIND export time_base.kind must be elapsed_ticks.') + if not declared_intervals: + raise ValueError( + 'AIND export requires explicit authoritative valid_intervals in params.py ' + 'or the waveform manifest.' + ) + phase = time.perf_counter() + report['source']['input_files'] = _input_inventory(source_root) + report['timing_seconds']['input_hashing'] = time.perf_counter() - phase + if output_dir is not None: + destination = Path(output_dir).resolve() + if destination == source_root or source_root in destination.parents: + raise ValueError('Prepared output must be outside the immutable source directory.') + if destination.exists(): + raise ValueError(f'Prepared output must be fresh; already exists: {destination}.') + phase = time.perf_counter() + prepared = prepare_large( + params_path, + destination, + max_spikes=max_spikes, + max_bytes=max_bytes, + batch_size=batch_size, + ) + report['timing_seconds']['prepare'] = time.perf_counter() - phase + manifest = json.loads((prepared / '_phy_curation_manifest.json').read_text()) + report['prepared_output'] = { + 'path': str(prepared), + 'num_spikes': manifest['bounded_num_spikes'], + 'num_units': len(manifest['unit_ids']), + 'waveform_coverage': manifest['waveform_coverage'], + 'budgets': manifest['budgets'], + 'output_bytes': sum(p.stat().st_size for p in prepared.rglob('*') if p.is_file()), + } + except Exception as error: + report['failures'].append(_failure(error)) + if not report['failures']: + report['status'] = 'passed' + report['timing_seconds']['total'] = time.perf_counter() - started + return report + + +def main(argv=None): + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument('params', type=Path, help='AIND sorting params.py') + parser.add_argument('--phy-revision', required=True) + parser.add_argument('--exporter-revision', required=True) + parser.add_argument( + '--output-dir', type=Path, help='Optional fresh bounded package destination' + ) + parser.add_argument('--max-spikes', type=int, default=2_000_000) + parser.add_argument('--max-bytes', type=int, default=536_870_912) + parser.add_argument('--batch-size', type=int, default=100_000) + parser.add_argument( + '--report', type=Path, help='Write JSON report to this path (default stdout)' + ) + args = parser.parse_args(argv) + if args.report: + source_root = args.params.resolve().parent + report_path = args.report.resolve() + protected_roots = [source_root] + if args.output_dir is not None: + protected_roots.append(args.output_dir.resolve()) + if any(report_path == root or root in report_path.parents for root in protected_roots): + failure = ValueError( + 'Report path must be outside the immutable source and prepared output directories.' + ) + elif args.report.exists() or args.report.is_symlink(): + failure = ValueError(f'Report path must be fresh; already exists: {args.report}.') + else: + failure = None + if failure is not None: + return _cli_failure(failure, args) + report = validate_export( + args.params, + phy_revision=args.phy_revision, + exporter_revision=args.exporter_revision, + output_dir=args.output_dir, + max_spikes=args.max_spikes, + max_bytes=args.max_bytes, + batch_size=args.batch_size, + ) + payload = json.dumps(report, indent=2, sort_keys=True) + '\n' + if args.report: + try: + with args.report.open('x', encoding='utf-8') as stream: + stream.write(payload) + except FileExistsError: + return _cli_failure( + FileExistsError(f'Report path must be fresh; already exists: {args.report}.'), + args, + ) + else: + sys.stdout.write(payload) + return 0 if report['status'] == 'passed' else 1 + + +if __name__ == '__main__': + raise SystemExit(main()) From d8c4f51809d3cb5a57a54c309073d5b8d01e3942 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 21:49:56 +0200 Subject: [PATCH 37/53] Document SLAY carryforward guarantees and native export acceptance --- design/aind-native-export-acceptance.md | 63 +++++++++++++++++++++++++ design/slay-roundtrip-validation.md | 62 ++++++++++++++++++++++++ docs/changelog.md | 4 ++ docs/long-recordings.md | 22 +++++++++ 4 files changed, 151 insertions(+) create mode 100644 design/aind-native-export-acceptance.md create mode 100644 design/slay-roundtrip-validation.md diff --git a/design/aind-native-export-acceptance.md b/design/aind-native-export-acceptance.md new file mode 100644 index 000000000..b7082c825 --- /dev/null +++ b/design/aind-native-export-acceptance.md @@ -0,0 +1,63 @@ +# Native AIND export acceptance + +This checklist accepts an export for Phy software integration only. Passing +checks do not prove scientific validity. The exporter owner must provide +authoritative acquisition evidence for the clock origin, physical extent, +valid exposure, dropped spans, and filler policy. A Phy run cannot supply that +evidence by inferring or converting timestamps or exposure. + +## Before validation + +- [ ] Record the exact Phy revision and native exporter revision in the report. +- [ ] Attach the reviewable exporter change and provenance for acquisition + boundaries and filler classification. +- [ ] Confirm the exporter declares one explicit time base and emits + `num_samples`, `valid_intervals`, waveform sample indices, and producer + windows in that same coordinate system. +- [ ] Confirm every sorting spike is inside authoritative valid exposure and + every waveform sample index equals `spike_times[subset_spikes]`. +- [ ] Resolve spikes inside filler from acquisition evidence upstream. Any + intentional row removal must use the same row mask for every spike-aligned + array and update row references consistently. +- [ ] Keep elapsed ticks separate from physical frame counts. Do not route + elapsed ticks to raw frame-index fields or claim raw-trace loading is + supported by this contract. + +## Phy engineering validation + +1. Run the native export through `tools/validate_aind_export.py` with the two + revisions above, without an output directory. Retain its JSON report, + including input file hashes, time contract, exposure, array counts, and + timings. Resolve every source validation failure at the exporter. +2. Run optional preparation first with Phy's default budgets: 2,000,000 spikes + and 512 MiB. Use a new destination outside the source directory. Record + retained spike and waveform counts, omitted evidence, output size, and + timings. Confirm the original source file hashes are unchanged. +3. If the complete producer evidence exceeds either default cap, run larger + spike and byte caps as distinct, explicitly labeled runs, each to a fresh + destination. Report each cap and its result independently; never treat a + larger-cap success as a pass under the defaults. +4. Open the default bounded output in the Phy GUI. Exercise navigation at the + beginning, middle, and end of retained windows, select units with and + without retained stored waveforms, and verify displayed waveform/channel + mapping and feature behavior. +5. Exercise the three-round SLAY carryforward workflow on the bounded output: + save each round, carry assignments and labels forward, reopen the result, + and compare final assignments and metadata with an independent expected + result. Preserve the round-by-round artifacts and logs. +6. Recheck the native source hashes after GUI and carryforward work. All curation + products must be separate from the source export. + +## Decision record + +- [ ] Phy contract validation passes with no timestamp or exposure inference. +- [ ] Default-budget preparation and output counts are recorded. +- [ ] Larger-cap runs, if needed, are separately reported. +- [ ] GUI and three-round SLAY carryforward evidence is attached. +- [ ] Acquisition authority has approved the clock, exposure, and filler + policy independently of the software checks. + +Record the outcome as **software integration accepted** only when the Phy +checks pass. Record **acquisition truth accepted** separately and only when the +authoritative producer evidence has been reviewed. The first outcome alone is +not scientific acceptance of the export. diff --git a/design/slay-roundtrip-validation.md b/design/slay-roundtrip-validation.md new file mode 100644 index 000000000..ff8b980da --- /dev/null +++ b/design/slay-roundtrip-validation.md @@ -0,0 +1,62 @@ +# SLAY persistence validation + +The follow-up to PR #1428 preserves producer `curation.json` bytes and the +complete source-bound review ledger through bounded preparation, committed +save, full replay, and re-preparation. Suggestions retain original IDs; pending +suggestions affected by merges or threshold splits become stale. Historical +accept/reject decisions take precedence over that derived status. + +## Integrity and regression coverage + +Preparation hashes the producer document and an immutable inherited review +snapshot. Session loading uses committed checkpoint reviews before loose review +copies. Direct saves and saves with the proposition feature disabled preserve +the ledger; suggestions without decisions receive an empty bound ledger. +Generation extra documents must belong to the checkpoint hash inventory. +Replay stages both documents, checks copied bytes, and publishes hashes and +cumulative merge/split retirement records in lineage. + +Focused regressions cover three no-op rounds in direct, enabled and disabled +modes; accepted, rejected and orphan history; cumulative merge/split retirement; +malformed, conflicting or absent loose copies; mutated bound documents; missing +or null checkpoint ledgers; and mutations during copying. Old bounded packages +with unbound proposition artifacts fail explicitly instead of dropping history. +Ordinary unbounded loading keeps its existing compatibility behavior. + +A separate Sol-high read-only audit identified copy-time mutation, legacy +silent-drop and null-ledger bypasses. Each received a fix and regression; the +final audit reported no remaining blocking findings. + +## Real-data fixture and limits + +The fixture is Carl's converted overlay of computation +`b1b0782a-b3ea-4f34-81d7-b3c6e36452b3`, with 469,725,567 spikes, +705 original units, 140,240 waveform rows and 93 suggestions. It preserves the +33 filler-edge spikes using Carl's test-only exposure intervals. These intervals +have not been established as acquisition truth; this is an engineering test, +not acceptance of Brandon's native exporter. See +`aind-real-data-validation.md` for the original coordinate mismatch and exposure +limitations. + +The roundtrip uses Carl's explicit 8,000,000-spike / 3,000,000,000-byte caps to +retain all waveform rows. Through the ordinary proposition-review and merge +path, it accepts `[40,44,48] -> 705` and `[49,50,51,53] -> 706` and marks both +results good. Subsequent rounds perform no additional curation. + +The acceptance oracle requires two accepted and 91 pending suggestions in each +round, identical suggestion bytes and review records, save/reopen consistency, +and an independent streamed comparison of every full-source assignment against +the two original merge groups. Small regression fixtures provide overlapping +stale-suggestion coverage, because Carl's remaining 91 suggestions are disjoint +from these groups. + +The separate validator run on this same test overlay passed with default +2,000,000-spike / 536,870,912-byte caps: 1,486,361 evidence spikes, 27,865 of +140,240 waveform rows retained, and 532,625,749 output bytes. It records that +the exporter revision is Carl's test conversion and that acquisition truth is +unestablished. A real native export and authoritative gap/filler policy are +still required; see `aind-native-export-acceptance.md`. + +Local reports and reproduction scripts are retained under +`/home/cyrille/GIT/IBL/phy-data/carl/aind-b1b0782a-b3ea-4f34-81d7-b3c6e36452b3/slay-validation`. +Large arrays and access credentials are not repository artifacts. diff --git a/docs/changelog.md b/docs/changelog.md index abe54d6e9..575ce976b 100644 --- a/docs/changelog.md +++ b/docs/changelog.md @@ -13,6 +13,10 @@ behavior they verify rather than listed separately. ### Long recordings +- SLAY merge suggestions and saved accept/reject decisions now survive bounded + curation, full-sorting replay, and subsequent preparation. Suggestions retain + their original IDs; pending suggestions affected by merges or splits become + stale rather than being silently reassigned. - Fixed saving bounded amplitude splits after merge undo/redo when NumPy cluster IDs appear in journal metadata. - Added `prepare-large` and `apply-curation` for bounded shared-window evidence, diff --git a/docs/long-recordings.md b/docs/long-recordings.md index 9a841b391..e496ea7b0 100644 --- a/docs/long-recordings.md +++ b/docs/long-recordings.md @@ -207,6 +207,28 @@ the curated output to produce a fresh package and revision-specific summaries. This replay and re-preparation step also resolves full-data counts and trends for threshold-split children. +When the source includes SLAY suggestions in `curation.json`, preparation and +replay preserve that file exactly, together with saved accept/reject decisions +in `curation_review.json`. Subsequent bounded rounds retain those decisions, +including rounds with no new edits or with the proposition view disabled. +There is no need to copy either file by hand. + +Suggestions keep their original cluster IDs and source order. A saved acceptance +remains part of the review history even if its resulting cluster is later +merged or split. Pending suggestions whose original clusters disappear become +stale; known merge or split causes are shown without assigning the suggestion +to replacement clusters automatically. Legacy outputs without that history can +only report that an original cluster is missing. + +Bounded packages bind suggestions and review history to file hashes. A committed +checkpoint supplies the saved decisions even if a loose review copy is missing +or outdated. Changing the bound suggestion file requires preparing a new +package; incompatible or damaged documents stop saving or replay. +Older bounded packages with unbound suggestion or review documents require +migration before they can be replayed with this integrity check. Retain their +source and saved checkpoints so existing curation can be recovered; preparing +the original source again alone does not transfer those saved edits. + ## Interpreting evidence Full counts and exposure-based rates describe the complete sorting. Window plots, From 38eefa744ca010af011bf20d13a6c963066ac4f0 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 21:52:46 +0200 Subject: [PATCH 38/53] Exercise genuinely disabled proposition controllers in roundtrip tests --- .../tests/test_proposition_persistence.py | 27 ++++++++++++------- 1 file changed, 17 insertions(+), 10 deletions(-) diff --git a/phy/apps/large_recording/tests/test_proposition_persistence.py b/phy/apps/large_recording/tests/test_proposition_persistence.py index 918d4a8a2..0a8844daf 100644 --- a/phy/apps/large_recording/tests/test_proposition_persistence.py +++ b/phy/apps/large_recording/tests/test_proposition_persistence.py @@ -4,6 +4,7 @@ import pytest +from phy.apps.large_recording.adapter import BoundedTemplateController from phy.apps.large_recording.curation import BoundedSession, _digest from phy.apps.large_recording.prepare import prepare_large from phy.apps.large_recording.replay import apply_curation @@ -13,6 +14,10 @@ from phy.cluster._propositions import PropositionReview, encode_review_mapping, proposition_key +class PropositionsDisabledController(BoundedTemplateController): + enable_merge_propositions = False + + def prepare(tmp_path): params = make_gui_sorting(tmp_path / 'source') producer = b'{"format_version":"2", "unit_ids":[0,1,2,99], "merges":[{"unit_ids":[0,1]},{"unit_ids":[1,2]}], "producer": {"unchanged":true}}\n' @@ -39,13 +44,17 @@ def test_three_noop_rounds_preserve_exact_source_and_complete_ledger(tmp_path, m session.save() session.close() else: - controller = TemplateController( - dir_path=bounded, - config_dir=tmp_path / 'config', - plugins=[], - enable_merge_propositions=mode == 'enabled', + controller_class = ( + PropositionsDisabledController if mode == 'disabled' else TemplateController + ) + controller = controller_class( + dir_path=bounded, config_dir=tmp_path / 'config', plugins=[] ) try: + if mode == 'disabled': + assert controller.supervisor.merge_propositions is None + else: + assert controller.supervisor.merge_propositions is not None controller.supervisor.save() finally: controller.close() @@ -275,13 +284,11 @@ def test_suggestions_without_reviews_publish_empty_bound_ledger(tmp_path, mode): session.save() session.close() else: - controller = TemplateController( - dir_path=bounded, - config_dir=tmp_path / 'config', - plugins=[], - enable_merge_propositions=False, + controller = PropositionsDisabledController( + dir_path=bounded, config_dir=tmp_path / 'config', plugins=[] ) try: + assert controller.supervisor.merge_propositions is None controller.supervisor.save() finally: controller.close() From 8c146f89146bcfd5db02b1a1c5cb14c7e76c49c8 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 21:53:24 +0200 Subject: [PATCH 39/53] Record full-size SLAY roundtrip results and shutdown limitation --- design/slay-roundtrip-validation.md | 22 ++++++++++++++++++++++ 1 file changed, 22 insertions(+) diff --git a/design/slay-roundtrip-validation.md b/design/slay-roundtrip-validation.md index ff8b980da..7af25b863 100644 --- a/design/slay-roundtrip-validation.md +++ b/design/slay-roundtrip-validation.md @@ -60,3 +60,25 @@ still required; see `aind-native-export-acceptance.md`. Local reports and reproduction scripts are retained under `/home/cyrille/GIT/IBL/phy-data/carl/aind-b1b0782a-b3ea-4f34-81d7-b3c6e36452b3/slay-validation`. Large arrays and access credentials are not repository artifacts. + +## Results + +- All three rounds retained exactly two accepted and 91 pending suggestions, + identical producer bytes and review records, and matching assignments for + all 469,725,567 source rows. Each bounded package retained all 140,240 + waveform rows and 7,298,318 evidence spikes at Carl's larger caps. +- The independent hash oracle verified all 67 original files were unchanged + and 12 immutable files per full replay matched the converted source. Both + good labels and the seven retired parent records survived every round. +- A separate final-code controller with proposition loading disabled saved and + reopened the real third-round checkpoint with both accepted reviews intact. +- `make test-full` passed: 854 tests (499 core, 355 applications), with one + existing benchmark skip. Lint and formatting passed. The corrected disabled + controller tests subsequently passed all 22 persistence cases. `make doc-check` + passed; packaging was unchanged. +- The combined three-round script completed every functional assertion and + wrote its success report, then exited with signal 11 during process shutdown. + A separate repeated six-controller/three-GUI lifecycle run with event + processing and reference cleanup exited successfully. The combined harness's + shutdown fault is retained as a limitation; its cause is not established as + a product defect or a data-integrity failure. From 6ac9010d532ad3694d430433d4bbaff891fe4c6f Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sat, 24 Oct 2026 21:56:40 +0200 Subject: [PATCH 40/53] Use portable paths in proposition copy-race regressions --- .../large_recording/tests/test_proposition_persistence.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/phy/apps/large_recording/tests/test_proposition_persistence.py b/phy/apps/large_recording/tests/test_proposition_persistence.py index 0a8844daf..2df49f444 100644 --- a/phy/apps/large_recording/tests/test_proposition_persistence.py +++ b/phy/apps/large_recording/tests/test_proposition_persistence.py @@ -1,6 +1,7 @@ """Producer bytes, durable decisions and retirement survive bounded replay rounds.""" import json +from pathlib import Path import pytest @@ -180,9 +181,7 @@ def test_copy_race_rejects_producer_mutation_without_publication(tmp_path, monke def mutate_copy(source, destination, *args, **kwargs): result = original_copy(source, destination, *args, **kwargs) - if str(destination).endswith('/curation.json'): - from pathlib import Path - + if Path(destination).name == 'curation.json': Path(destination).write_text('{}') return result From 8f08bb4178d82376db3022e30743357b9d963711 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sun, 25 Oct 2026 00:03:40 +0200 Subject: [PATCH 41/53] Compare selected units and toggle full-recording stability metrics --- phy/apps/large_recording/stability.py | 388 +++++++++++++----- .../large_recording/tests/test_stability.py | 348 ++++++++++++++++ 2 files changed, 632 insertions(+), 104 deletions(-) create mode 100644 phy/apps/large_recording/tests/test_stability.py diff --git a/phy/apps/large_recording/stability.py b/phy/apps/large_recording/stability.py index 131268fd1..50e2dd2e9 100644 --- a/phy/apps/large_recording/stability.py +++ b/phy/apps/large_recording/stability.py @@ -5,158 +5,320 @@ from phy.cluster.views import ManualClusteringView from phy.plot.plot import PlotCanvasMpl +from phy.utils.color import selected_cluster_color class UnitStabilityView(ManualClusteringView): - """Full counts/rates, available source trends, gaps and retained evidence windows.""" + """Compare exact rates and available source trends for up to eight selected units.""" plot_canvas_class = PlotCanvasMpl - max_n_clusters = 1 + # Apply the display limit locally, retaining the full presentation selection. + max_n_clusters = 0 + display_limit = 8 _default_position = 'right' ex_status = 'Full-duration evidence; sampling cannot establish chronic unit identity.' + _metrics = ('firing_rate', 'amplitude', 'depth') def __init__(self, controller): super().__init__() self.controller = controller self.canvas.subplots(3, 1, sharex=True) + self.show_firing_rate = self.show_amplitude = self.show_depth = True + self.state_attrs += tuple(f'show_{metric}' for metric in self._metrics) self._summary_arrays = {} + self._selected_summaries = {} + self._common_data = None + self._attaching = False + self._footer = self.canvas.figure.text(0.12, 0.025, '', fontsize=8) def _array(self, name): if name not in self._summary_arrays: self._summary_arrays[name] = np.load(self.controller.dir_path / name, mmap_mode='r') return self._summary_arrays[name] - def get_data(self, cluster_id): + def _common(self): + if self._common_data is not None: + return self._common_data controller = self.controller session = getattr(controller, 'bounded_session', None) if session is None: - # Optional ordinary-data view: only the selected cluster is evaluated. - times = controller.get_spike_times(cluster_id) edges = np.linspace(0, controller.model.duration, 101) - counts, _ = np.histogram(times, edges) - exposure = np.diff(edges) - return Bunch( + self._common_data = Bunch( edges=edges, - counts=counts, - exposure=exposure, + exposure=np.diff(edges), windows=[], intervals=[[0, controller.model.duration]], - trends={}, - provenance='Loaded recording; continuous acquisition assumed.', + footer='', ) - manifest = session.manifest - summary = manifest.get('summaries', manifest) - edges = self._array(summary['edges_file']) / controller.model.sample_rate - exposure = self._array(summary['exposure_file']) - units = controller._source_units(cluster_id) - if units is None: - return Bunch( + else: + manifest = session.manifest + summary = manifest.get('summaries', manifest) + edges = self._array(summary['edges_file']) / controller.model.sample_rate + missing = [c for c, n in zip(session.unit_ids, manifest['bounded_counts']) if not n] + footer = '' + if missing: + footer = ( + f'{len(missing)} source units without evidence: ' + f'{", ".join(map(str, missing[:12]))}' + (' …' if len(missing) > 12 else '') + ) + self._common_data = Bunch( edges=edges, - counts=None, - exposure=exposure, - windows=[], - intervals=[], - trends={}, - provenance='Split evidence pending full-data replay.', + exposure=self._array(summary['exposure_file']), + windows=controller.evidence_windows / controller.model.sample_rate, + intervals=np.asarray(manifest['valid_intervals']) / controller.model.sample_rate, + summary=summary, + lookup={int(c): i for i, c in enumerate(session.unit_ids)}, + footer=footer, ) - lookup = {int(c): i for i, c in enumerate(session.unit_ids)} - rows = [lookup[c] for c in units] - # Bound temporaries by one unit's summary row, including merged units. - count_grid = self._array(summary['counts_file']) - counts = np.zeros(len(exposure), dtype=np.int64) - for row in rows: - counts += count_grid[row] - trends = {} - for attribute in ('amplitude', 'depth'): - sum_file, count_file = f'{attribute}_sum_file', f'{attribute}_count_file' - if sum_file not in summary: + return self._common_data + + def get_data(self, cluster_id, metrics=None): + """Load only requested metrics, caching bounded selected-unit summary rows. + + Counts share the manifest's exposure. Trend sums are combined with their + finite-value counts, never averaged as equally weighted unit means. + """ + metrics = self._metrics if metrics is None else metrics + common = self._common() + data = self._selected_summaries.get(cluster_id) + controller = self.controller + session = getattr(controller, 'bounded_session', None) + if data is None: + data = Bunch(common.copy()) + data.update(counts=None, trends={}, loaded=set(), pending=False) + if session is None: + data.provenance = 'Loaded recording; continuous acquisition assumed.' + else: + units = controller._source_units(cluster_id) + data.pending = units is None + data.rows = [] if units is None else [common.lookup[c] for c in units] + data.provenance = ( + 'Split evidence pending full-data replay.' + if data.pending + else 'Complete source sorting; exact counts and finite-value means.' + ) + # Keep at most eight summaries, including direct source-unit inspection. + if len(self._selected_summaries) >= self.display_limit: + self._selected_summaries.pop(next(iter(self._selected_summaries))) + self._selected_summaries[cluster_id] = data + if data.pending: + return data + for metric in metrics: + if metric in data.loaded: continue - total, valid = np.zeros(len(exposure)), np.zeros(len(exposure), dtype=np.int64) - for row in rows: - total += self._array(summary[sum_file])[row] - valid += self._array(summary[count_file])[row] - mean = np.full(len(exposure), np.nan) - np.divide(total, valid, out=mean, where=valid > 0) - trends[attribute] = mean - return Bunch( - edges=edges, - counts=counts, - exposure=exposure, - trends=trends, - windows=controller.evidence_windows / controller.model.sample_rate, - intervals=np.asarray(manifest['valid_intervals']) / controller.model.sample_rate, - provenance='Complete source sorting; exact counts and finite-value means.', + if metric == 'firing_rate': + if session is None: + data.counts = np.histogram(controller.get_spike_times(cluster_id), data.edges)[ + 0 + ] + else: + counts = np.zeros(len(data.exposure), dtype=np.int64) + grid = self._array(common.summary['counts_file']) + for row in data.rows: + counts += grid[row] + data.counts = counts + data.rates = np.full(len(data.exposure), np.nan) + np.divide(data.counts, data.exposure, out=data.rates, where=data.exposure > 0) + elif session is not None: + sum_file, count_file = f'{metric}_sum_file', f'{metric}_count_file' + if sum_file in common.summary and count_file in common.summary: + total = np.zeros(len(data.exposure)) + valid = np.zeros(len(data.exposure), dtype=np.int64) + sums = self._array(common.summary[sum_file]) + counts = self._array(common.summary[count_file]) + for row in data.rows: + total += sums[row] + valid += counts[row] + mean = np.full(len(data.exposure), np.nan) + np.divide(total, valid, out=mean, where=valid > 0) + data.trends[metric] = mean + data.loaded.add(metric) + return data + + @property + def status(self): + n = len(self.cluster_ids) + return ( + f'Showing first {self.display_limit} of {n} selected units.' + if n > self.display_limit + else '' ) - def plot(self, **kwargs): + def _layout_axes(self, visible): axes = list(self.canvas.iter_ax()) - for ax in axes: + for metric, ax in zip(self._metrics, axes): ax.clear() - session = getattr(self.controller, 'bounded_session', None) - if not self.cluster_ids: + ax.set_visible(metric in visible) + for index, metric in enumerate(visible): + ax = axes[self._metrics.index(metric)] + height = 0.76 / len(visible) + ax.set_position( + [ + 0.12, + 0.15 + (len(visible) - 1 - index) * height, + 0.84, + height * (0.84 if len(visible) > 1 else 1), + ] + ) + ax.tick_params(axis='x', labelbottom=index == len(visible) - 1) + if index == len(visible) - 1: + ax.set_xlabel('Elapsed acquisition clock (hours)') + return axes + + def plot(self, **kwargs): + visible = [metric for metric in self._metrics if getattr(self, f'show_{metric}')] + axes = self._layout_axes(visible) + self._footer.set_text('') + # Reuse an existing axis for the explicitly empty panel. + if not visible: + axes[0].set_visible(True) + axes[0].set_position([0.12, 0.15, 0.84, 0.76]) + axes[0].set_axis_off() axes[0].text( 0.02, 0.6, - 'Select a unit to inspect full-duration evidence.', + 'No metrics enabled. Use Show firing rate, amplitude or depth.', transform=axes[0].transAxes, ) else: - cluster_id = self.cluster_ids[0] - data = self.get_data(cluster_id) - if data.counts is None: - axes[0].text(0.02, 0.6, data.provenance, transform=axes[0].transAxes) - else: - rates = np.full(len(data.exposure), np.nan) - np.divide(data.counts, data.exposure, out=rates, where=data.exposure > 0) + common = self._common() + self._footer.set_text(common.footer) + first_ax = axes[self._metrics.index(visible[0])] + notes = [] + unavailable = {metric: [] for metric in visible} + if not self.cluster_ids: + notes.append('Select a unit to inspect full-duration evidence.') + for index, cluster_id in enumerate(self.cluster_ids[: self.display_limit]): + data = self.get_data(cluster_id, visible) + if data.pending: + notes.append(f'Unit {cluster_id}: {data.provenance}') + continue + color = selected_cluster_color(self.cluster_color_index(cluster_id, index)) x = (data.edges[:-1] + data.edges[1:]) / 7200 - axes[0].plot(x, rates) - for ax, attribute in zip(axes[1:], ('amplitude', 'depth')): - if attribute in data.trends: - ax.plot(x, data.trends[attribute]) - else: - ax.text( - 0.02, - 0.6, - f'{attribute.title()} measurement unavailable.', - transform=ax.transAxes, - ) - for ax in axes: - for start, end in data.windows: - ax.axvspan(start / 3600, end / 3600, color='cyan', alpha=0.15) - previous = 0 - for start, end in data.intervals: - if start > previous: - ax.axvspan(previous / 3600, start / 3600, color='gray', alpha=0.4) - previous = end - if previous < data.edges[-1]: - ax.axvspan(previous / 3600, data.edges[-1] / 3600, color='gray', alpha=0.4) - axes[0].set_title(f'Unit {cluster_id} — {data.provenance}', fontsize=9) - axes[0].set_ylabel('Rate (Hz)') - axes[1].set_ylabel('Mean amplitude\n(source units)') - axes[2].set_ylabel('Mean depth\n(source units)') - axes[2].set_xlabel('Elapsed acquisition clock (hours)') - if session is not None: - missing = [ - c for c, n in zip(session.unit_ids, session.manifest['bounded_counts']) if not n - ] - if missing: - axes[2].text( + for metric in visible: + ax = axes[self._metrics.index(metric)] + values = data.rates if metric == 'firing_rate' else data.trends.get(metric) + if values is not None and np.any(np.isfinite(values)): + ax.plot(x, values, color=color, label=str(cluster_id)) + elif metric != 'firing_rate': + unavailable[metric].append(cluster_id) + labels = ('Rate (Hz)', 'Mean amplitude\n(source units)', 'Mean depth\n(source units)') + for metric in visible: + ax = axes[self._metrics.index(metric)] + ax.set_axis_on() + ax.set_ylabel(labels[self._metrics.index(metric)]) + if unavailable[metric]: + missing = ', '.join(map(str, unavailable[metric])) + message = ( + f'{metric.title()} measurement unavailable.' + if not ax.lines + else f'{metric.title()} measurement unavailable for units: {missing}.' + ) + ax.text(0.02, 0.96, message, transform=ax.transAxes, va='top', fontsize=8) + for start, end in common.windows: + ax.axvspan(start / 3600, end / 3600, color='cyan', alpha=0.15) + previous = 0 + for start, end in common.intervals: + if start > previous: + ax.axvspan(previous / 3600, start / 3600, color='gray', alpha=0.4) + previous = end + if previous < common.edges[-1]: + ax.axvspan(previous / 3600, common.edges[-1] / 3600, color='gray', alpha=0.4) + ax.set_xlim(common.edges[0] / 3600, common.edges[-1] / 3600) + if ax.lines: + ax.legend( + title='Unit', fontsize=8, loc='upper right', ncol=min(4, len(ax.lines)) + ) + provenance = ( + 'Complete source sorting; exact counts and finite-value means.' + if getattr(self.controller, 'bounded_session', None) is not None + else 'Loaded recording; continuous acquisition assumed.' + ) + first_ax.set_title(provenance, fontsize=9) + if notes: + first_ax.text( 0.02, - -0.42, - f'{len(missing)} source units without evidence: ' - f'{", ".join(map(str, missing[:12]))}' + (' …' if len(missing) > 12 else ''), - transform=axes[2].transAxes, + 0.96, + '\n'.join(notes), + transform=first_ax.transAxes, + va='top', fontsize=8, ) - self.canvas.figure.tight_layout() + self.update_status() self.canvas.update() def on_select(self, cluster_ids=None, **kwargs): - self.cluster_ids = tuple(cluster_ids or ())[:1] + if self._attaching: + supervisor = self.controller.supervisor + cluster_ids = supervisor.selected + self._update_cluster_color_indices(supervisor, cluster_ids) + self.cluster_ids = tuple(cluster_ids or ()) + selected = set(self.cluster_ids[: self.display_limit]) + self._selected_summaries = { + c: d for c, d in self._selected_summaries.items() if c in selected + } self.plot(**kwargs) + def _update_cluster_color_indices(self, sender, cluster_ids): + # Hidden-view replay already adopted the authoritative palette at receipt. + if sender is not self: + super()._update_cluster_color_indices(sender, cluster_ids) + + def on_select_threaded(self, sender, cluster_ids, gui=None, **kwargs): + # The base intentionally ignores empty selections; this evidence panel must clear. + if not cluster_ids: + if ( + not self.auto_update + or self._closed + or sender.__class__.__name__ in ('ClusterView', 'SimilarityView') + ): + return + self._update_cluster_color_indices(sender, cluster_ids) + if self.defer_hidden_updates and not self._dock_visible: + self.cluster_ids = () + self._pending_selection = ([], dict(kwargs)) + return + self._pending_selection = None + self.on_select([], **kwargs) + return + return super().on_select_threaded(sender, cluster_ids, gui=gui, **kwargs) + + def _toggle_metric(self, metric, checked): + setattr(self, f'show_{metric}', bool(checked)) + if hasattr(self, 'actions'): + self.actions.get(f'toggle_{metric}').setChecked(bool(checked)) + if not self._closed: + self.plot() + + def toggle_firing_rate(self, checked): + """Show firing rate.""" + self._toggle_metric('firing_rate', checked) + + def toggle_amplitude(self, checked): + """Show amplitude.""" + self._toggle_metric('amplitude', checked) + + def toggle_depth(self, checked): + """Show depth.""" + self._toggle_metric('depth', checked) + + def _invalidate(self): + self._selected_summaries.clear() + def attach(self, gui): - super().attach(gui) + self._attaching = True + try: + super().attach(gui) + finally: + self._attaching = False + for metric in self._metrics: + self.actions.add( + getattr(self, f'toggle_{metric}'), + checkable=True, + checked=getattr(self, f'show_{metric}'), + docstring=f'Show {metric.replace("_", " ")}.', + ) + self.actions.get(f'toggle_{metric}').setText(f'Show {metric.replace("_", " ")}') @self.actions.add(prompt=True) def show_source_unit(cluster_id): @@ -164,13 +326,31 @@ def show_source_unit(cluster_id): session = getattr(self.controller, 'bounded_session', None) if session is not None and int(cluster_id) not in session.unit_ids: raise ValueError('Unknown source unit ID.') + self._cluster_color_index_by_id = {} self.on_select([int(cluster_id)]) @connect(event='bounded_state_changed', sender=self.controller.supervisor) def on_state(sender): - self.plot() + self._invalidate() + if not self._closed: + self.plot() + + @connect(event='cluster', sender=self.controller.supervisor) + def on_cluster(sender, up): + self._invalidate() + # Supervisor selection callbacks may precede this listener. Refresh + # ordinary data after invalidation even if the selected IDs stayed put. + if ( + getattr(self.controller, 'bounded_session', None) is None + and self.auto_update + and not self._closed + and not (self.defer_hidden_updates and not self._dock_visible) + ): + self.plot() @connect(event='close_view', sender=self) def on_close(sender, *args): - unconnect(on_state, on_close) + unconnect(on_state, on_cluster, on_close) self._summary_arrays.clear() + self._selected_summaries.clear() + self._common_data = None diff --git a/phy/apps/large_recording/tests/test_stability.py b/phy/apps/large_recording/tests/test_stability.py new file mode 100644 index 000000000..031a17507 --- /dev/null +++ b/phy/apps/large_recording/tests/test_stability.py @@ -0,0 +1,348 @@ +"""Exact selected-unit comparisons and scoped GUI selection behavior.""" + +from itertools import product +from types import MappingProxyType + +import numpy as np +import pytest +from phylib.utils import Bunch + +from phy.apps.large_recording.stability import UnitStabilityView +from phy.apps.large_recording.tests.test_adapter import make_controller +from phy.utils.color import selected_cluster_color + + +@pytest.fixture +def summary_view(qtbot, tmp_path): + arrays = { + 'edges': [0, 10, 20, 25], + 'exposure': [8.0, 0.0, 3.0], + 'counts': [[4, 0, 3], [12, 0, 6], [8, 0, 0]], + 'amplitude_sum': [[4.0, 0.0, 15.0], [30.0, 0.0, 8.0], [0.0, 0.0, 0.0]], + 'amplitude_count': [[2, 0, 3], [3, 0, 1], [0, 0, 0]], + 'depth_sum': [[40.0, 0.0, 150.0], [300.0, 0.0, 80.0], [0.0, 0.0, 0.0]], + 'depth_count': [[2, 0, 3], [3, 0, 1], [0, 0, 0]], + } + summary = {} + for key, values in arrays.items(): + name = f'{key}.npy' + np.save(tmp_path / name, np.asarray(values)) + summary[f'{key}_file'] = name + membership = {1: [1], 2: [2], 3: [3], 4: [1, 2], 5: None} + controller = Bunch( + dir_path=tmp_path, + model=Bunch(sample_rate=1.0, duration=25.0), + evidence_windows=np.array([[0, 2], [22, 24]]), + bounded_session=Bunch( + unit_ids=[1, 2, 3], + manifest={ + 'summaries': summary, + 'bounded_counts': [1, 1, 0], + 'valid_intervals': [[0, 8], [20, 23]], + }, + ), + _source_units=lambda cluster: membership[cluster], + get_spike_times=lambda cluster: pytest.fail('Bounded views must never read spike arrays'), + ) + view = UnitStabilityView(controller) + yield view + view.close() + + +@pytest.mark.parametrize('selected', [[1, 2], [1, 2, 3]]) +def test_exact_overlays_and_shared_exposure(summary_view, selected): + view = summary_view + view.on_select(selected) + axes = list(view.canvas.iter_ax()) + assert len(axes[0].lines) == len(selected) + assert [line.get_label() for line in axes[0].lines] == list(map(str, selected)) + expected = {1: [0.5, np.nan, 1.0], 2: [1.5, np.nan, 2.0], 3: [1.0, np.nan, 0.0]} + for index, (cluster, line) in enumerate(zip(selected, axes[0].lines)): + np.testing.assert_allclose(line.get_ydata(), expected[cluster], equal_nan=True) + np.testing.assert_allclose(line.get_xdata(), np.array([5, 15, 22.5]) / 3600) + np.testing.assert_allclose(line.get_color(), selected_cluster_color(index)) + assert '3' in view._footer.get_text() # Unit without bounded evidence remains inspectable. + assert len(axes[1].lines) == 2 # No fabricated all-NaN trend for unit 3. + assert any( + 'Amplitude measurement unavailable for units: 3' in t.get_text() for t in axes[1].texts + ) == (3 in selected) + + +def test_weighted_merged_trends_and_pending_do_not_hide_valid_units(summary_view): + view = summary_view + merged = view.get_data(4) + np.testing.assert_array_equal(merged.counts, [16, 0, 9]) + np.testing.assert_allclose(merged.rates, [2.0, np.nan, 3.0], equal_nan=True) + np.testing.assert_allclose(merged.trends['amplitude'], [6.8, np.nan, 5.75], equal_nan=True) + np.testing.assert_allclose(merged.trends['depth'], [68.0, np.nan, 57.5], equal_nan=True) + view.on_select([5, 4]) + ax = next(view.canvas.iter_ax()) + assert len(ax.lines) == 1 and ax.lines[0].get_label() == '4' + assert any('Unit 5: Split evidence pending' in t.get_text() for t in ax.texts) + + +def test_lazy_metrics_selected_cache_and_all_toggle_layouts(summary_view, monkeypatch): + view = summary_view + loads = [] + original = view._array + + def load(name): + loads.append(name) + return original(name) + + monkeypatch.setattr(view, '_array', load) + view.show_amplitude = view.show_depth = False + view.on_select([1, 2]) + assert not any('amplitude' in name or 'depth' in name for name in loads) + common = view._common() + lookups = common.lookup + view.toggle_amplitude(True) + assert any('amplitude' in name for name in loads) + assert not any('depth' in name for name in loads) + loads.clear() + view.toggle_amplitude(False) + view.toggle_amplitude(True) + assert not loads + assert view._common() is common and view._common().lookup is lookups + axes = list(view.canvas.iter_ax()) + callback_counts = {k: len(v) for k, v in view.canvas.canvas.callbacks.callbacks.items()} + for _ in range(2): + for combination in product((False, True), repeat=3): + for metric, enabled in zip(view._metrics, combination): + getattr(view, f'toggle_{metric}')(enabled) + assert tuple(view.state[f'show_{metric}'] for metric in view._metrics) == combination + assert list(view.canvas.iter_ax()) == axes + assert { + k: len(v) for k, v in view.canvas.canvas.callbacks.callbacks.items() + } == callback_counts + visible = [ax for ax in axes if ax.get_visible()] + if any(combination): + assert len(visible) == sum(combination) + assert visible[-1].get_xlabel() == 'Elapsed acquisition clock (hours)' + assert all(not ax.get_xlabel() for ax in visible[:-1]) + assert visible[0].get_position().y1 == pytest.approx( + 0.91 if len(visible) == 1 else 0.15 + 0.76 - 0.16 * 0.76 / len(visible) + ) + else: + assert any('No metrics enabled' in t.get_text() for t in visible[0].texts) + assert view.state.show_depth + view.on_select([3]) + assert set(view._selected_summaries) == {3} + + +def test_selection_limit_palette_and_clear_lifecycle(summary_view): + view = summary_view + # Repeat source rows under distinct cluster IDs to test the display bound. + view.controller._source_units = lambda cluster: [1] + selected = list(range(20, 30)) + sender = Bunch( + selection_color_indices=MappingProxyType({c: 9 - i for i, c in enumerate(selected)}) + ) + view.on_select_threaded(sender, selected) + assert view.cluster_ids == tuple(selected) + assert selected == list(range(20, 30)) + assert len(view._selected_summaries) == 8 + ax = next(view.canvas.iter_ax()) + assert len(ax.lines) == 8 + assert view.status == 'Showing first 8 of 10 selected units.' + for i, line in enumerate(ax.lines): + np.testing.assert_allclose(line.get_color(), selected_cluster_color(9 - i)) + view.auto_update = False + view.on_select_threaded(sender, []) + assert view.cluster_ids == tuple(selected) + view.auto_update = True + view.defer_hidden_updates = True + view._dock_visible = False + view.on_select_threaded(sender, selected) + view._dock_visible = True + view._flush_pending_selection() + np.testing.assert_allclose(ax.lines[0].get_color(), selected_cluster_color(9)) + view._dock_visible = False + view.on_select_threaded(sender, []) + assert view.cluster_ids == () and view._pending_selection == ([], {}) + assert len(ax.lines) == 8 + view._dock_visible = True + view._flush_pending_selection() + assert not ax.lines + view.on_select([1]) + view._closed = True + view.on_select_threaded(sender, []) + assert view.cluster_ids == (1,) + view._closed = False + + +def test_ordinary_continuous_assumption_and_invalidation(qtbot): + times = [np.array([0.0, 1.0, 9.0])] + calls = [] + + def get_times(cluster): + calls.append(cluster) + return times[0] + + controller = Bunch(model=Bunch(duration=10.0), get_spike_times=get_times) + view = UnitStabilityView(controller) + try: + view.on_select([7, 8]) + data = view.get_data(7) + assert data.counts.sum() == 3 and not data.trends + assert 'continuous acquisition assumed' in data.provenance + np.testing.assert_allclose(data.exposure, 0.1) + assert calls == [7, 8] + times[0] = np.array([2.0]) + view._invalidate() + assert view.get_data(7).counts.sum() == 1 + finally: + view.close() + + +def test_gui_initial_authoritative_selection_actions_and_curation(qtbot, tmp_path): + _, controller = make_controller(tmp_path, sparse=True) + gui = controller.create_gui(default_views=[], do_prompt_save=False) + supervisor = controller.supervisor + try: + supervisor.select([0]) + supervisor.block() + supervisor.similarity_view.select([1]) + supervisor.block() + view = UnitStabilityView(controller) + view.attach(gui) + assert view.cluster_ids == tuple(supervisor.selected) == (0, 1) + for metric in view._metrics: + assert view.actions.get(f'toggle_{metric}').isChecked() + view.actions.get('toggle_amplitude').trigger() + assert not view.show_amplitude + assert not view.actions.get('toggle_amplitude').isChecked() + view.toggle_depth(False) + assert not view.actions.get('toggle_depth').isChecked() + state = view.state.copy() + supervisor.toggle_merge_mode() + supervisor.block() + supervisor.similarity_view.select([2, 1]) + supervisor.block() + other = UnitStabilityView(controller) + other.attach(gui) + assert other.cluster_ids == tuple(supervisor.selected) + assert other.cluster_ids + supervisor.add_to_merge((2,), insertion=1) + supervisor.block() + assert other.cluster_ids == tuple(supervisor.selected) + assert other.cluster_ids[1] == 2 + supervisor.similarity_view.sort_by('id', 'desc') + supervisor.block() + assert other.cluster_ids == tuple(supervisor.selected) + for index, line in enumerate(next(other.canvas.iter_ax()).lines): + cluster = int(line.get_label()) + np.testing.assert_allclose( + line.get_color(), + selected_cluster_color(supervisor.selection_color_indices[cluster]), + ) + # Save and restore through GUI view state, including QAction checks. + other.close() + view.close() + restored = UnitStabilityView(controller) + restored.attach(gui) + assert restored.show_firing_rate + assert not restored.show_amplitude and not restored.show_depth + assert not restored.actions.get('toggle_amplitude').isChecked() + assert not restored.actions.get('toggle_depth').isChecked() + view = restored + view.set_state(state) + assert not view.show_amplitude and not view.show_depth + supervisor.toggle_merge_mode() + supervisor.block() + supervisor.merge([0, 1]) + supervisor.block() + assert view.get_data(100).counts.sum() == 7 + supervisor.undo() + supervisor.block() + assert view.get_data(0).counts.sum() == 4 + supervisor.redo() + supervisor.block() + assert view.get_data(100).counts.sum() == 7 + supervisor.undo() + supervisor.block() + up = supervisor.split_source_amplitude(0, 2) + supervisor.block() + children = up.added + for cluster in children: + assert view.get_data(cluster).pending + view.on_select([children[0], 1]) + assert [line.get_label() for line in next(view.canvas.iter_ax()).lines] == ['1'] + supervisor.undo() + supervisor.block() + assert view.get_data(0).counts.sum() == 4 + supervisor.redo() + supervisor.block() + assert view.get_data(children[0]).pending + view.close() + assert not view._summary_arrays and not view._selected_summaries + finally: + gui.close() + controller.close() + + +def test_500_hour_500_bin_comparison_stays_bounded(summary_view): + view = summary_view + bins = 500 + view._common_data = Bunch( + edges=np.linspace(0, 500 * 3600, bins + 1), + exposure=np.full(bins, 3600.0), + windows=np.array([[0, 30], [499 * 3600, 499 * 3600 + 30]]), + intervals=[[0, 500 * 3600]], + footer='', + lookup={1: 0, 2: 1, 3: 2}, + summary={'counts_file': 'virtual_counts'}, + ) + view._summary_arrays['virtual_counts'] = np.ones((3, bins), dtype=np.int64) + view.controller._source_units = lambda cluster: [1] + view.on_select(list(range(8))) + assert len(view._selected_summaries) == 8 + assert all(len(line.get_xdata()) == bins for line in next(view.canvas.iter_ax()).lines) + + +def test_summary_aggregation_reads_one_row_at_a_time(summary_view): + view = summary_view + reads = [] + + class RowGrid: + def __init__(self, values): + self.values = values + + def __getitem__(self, row): + assert isinstance(row, (int, np.integer)), 'Never materialize multiple unit rows' + reads.append(row) + return self.values[row] + + for key in ('counts', 'amplitude_sum', 'amplitude_count', 'depth_sum', 'depth_count'): + name = f'{key}.npy' + view._summary_arrays[name] = RowGrid(np.load(view.controller.dir_path / name)) + data = view.get_data(4) + np.testing.assert_array_equal(data.counts, [16, 0, 9]) + assert reads == [0, 1] + [0, 0, 1, 1] * 2 + + +def test_ordinary_gui_cluster_event_refreshes_cached_counts(qtbot, tmp_path): + _, controller = make_controller(tmp_path) + gui = controller.create_gui(default_views=[], do_prompt_save=False) + times = [np.array([0.0, 1.0])] + ordinary = Bunch( + supervisor=controller.supervisor, + model=Bunch(duration=20.0), + get_spike_times=lambda cluster: times[0], + ) + view = UnitStabilityView(ordinary) + try: + controller.supervisor.select([0]) + controller.supervisor.block() + view.attach(gui) + assert view.get_data(0).counts.sum() == 2 + times[0] = np.array([0.0, 1.0, 2.0, 3.0]) + controller.supervisor.label('group', 'noise', cluster_ids=[0]) + controller.supervisor.block() + ax = next(view.canvas.iter_ax()) + assert np.nansum(ax.lines[0].get_ydata() * 0.2) == pytest.approx(4) + assert view.get_data(0).counts.sum() == 4 + finally: + view.close() + gui.close() + controller.close() From 05af2d4afecdae4f068d2f0d56766bce4a656f42 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sun, 25 Oct 2026 00:03:40 +0200 Subject: [PATCH 42/53] Capture reproducible real-data and long-duration stability comparisons --- tools/capture_long_recording_views.py | 147 ++++++++++++++++++++++++-- 1 file changed, 139 insertions(+), 8 deletions(-) diff --git a/tools/capture_long_recording_views.py b/tools/capture_long_recording_views.py index 1c40089c8..3af9a8b8a 100644 --- a/tools/capture_long_recording_views.py +++ b/tools/capture_long_recording_views.py @@ -12,14 +12,20 @@ """ import argparse +import json +import shutil +import subprocess import sys import tempfile +import time from pathlib import Path import numpy as np +from PyQt5.QtCore import QCoreApplication, QEvent from PyQt5.QtTest import QTest from phy.apps.large_recording.prepare import prepare_large +from phy.apps.large_recording.source import hash_file from phy.apps.template.gui import TemplateController from phy.gui.qt import QApplication, Qt @@ -30,11 +36,11 @@ CLUSTER_IDS = np.array([0, 2, 7, 99], dtype=np.int32) -def _make_source(path): +def _make_source(path, hours=HOURS): """Write a varied but deterministic synthetic source sorting.""" path.mkdir(parents=True) rng = np.random.default_rng(20261013) - samples = SAMPLE_RATE * 3600 * HOURS + samples = SAMPLE_RATE * 3600 * hours intervals = np.array( [[0, 3 * 3600 * SAMPLE_RATE], [int(3.5 * 3600 * SAMPLE_RATE), samples]], dtype=np.int64, @@ -149,6 +155,72 @@ def _capture(gui, destination): raise OSError(f'Could not save screenshot: {destination}') +def _close_capture(gui, controller): + gui.close() + controller.close() + gui.deleteLater() + QCoreApplication.sendPostedEvents(None, QEvent.DeferredDelete) + QApplication.processEvents() + + +def _capture_comparison(bounded, config_dir, output_dir, selected, dataset_label): + """Capture actual GUI comparisons on an isolated, disposable package.""" + controller = TemplateController( + dir_path=bounded, config_dir=config_dir, plugins=[], enable_threading=False + ) + gui = controller.create_gui(default_views=['UnitStabilityView'], do_prompt_save=False) + try: + gui.resize(2100, 1200) + gui.show() + _wait_for_render() + supervisor = controller.supervisor + started = time.perf_counter() + supervisor.select(selected) + supervisor.block() + selection_seconds = time.perf_counter() - started + view = gui.get_view('UnitStabilityView') + assert list(view.cluster_ids) == supervisor.selected + assert len(view.cluster_ids) >= 2, 'Select at least two retained clusters.' + _capture(gui, output_dir / 'after-overview.png') + started = time.perf_counter() + view.toggle_amplitude(False) + view.toggle_depth(False) + rate_only_seconds = time.perf_counter() - started + _capture(gui, output_dir / 'after-rate-only.png') + supervisor.toggle_merge_mode() + supervisor.block() + assert supervisor.selection.state.is_merge_mode + assert list(view.cluster_ids) == supervisor.selected + _capture(gui, output_dir / 'after-merge.png') + manifest = controller.bounded_session.manifest + report = { + 'dataset_label': dataset_label, + 'capture_revision': subprocess.check_output( + ['git', 'rev-parse', 'HEAD'], cwd=REPOSITORY, text=True + ).strip(), + 'clock_hours': manifest['num_samples'] / manifest['sample_rate'] / 3600, + 'selected_cluster_ids': selected, + 'displayed_cluster_ids': list(map(int, view.cluster_ids[: view.display_limit])), + 'merge_cluster_ids': supervisor.selected_merge, + 'summary_bins': len(view.get_data(selected[0]).exposure), + 'full_counts': { + str(unit): int(view.get_data(unit).counts.sum()) + for unit in view.cluster_ids[: view.display_limit] + }, + 'timing_seconds': { + 'select_and_block': selection_seconds, + 'rate_only_redraws': rate_only_seconds, + }, + 'gui_size': [gui.width(), gui.height()], + 'screenshots': ['after-overview.png', 'after-rate-only.png', 'after-merge.png'], + 'source_arrays_modified': False, + } + (output_dir / 'capture.json').write_text(json.dumps(report, indent=2) + '\n') + print(json.dumps(report), flush=True) + finally: + _close_capture(gui, controller) + + def _capture_views(bounded, config_dir, output_dir, stability): views = ( ['UnitStabilityView'] @@ -218,24 +290,74 @@ def _capture_views(bounded, config_dir, output_dir, stability): f'{counts[best_window]} evidence spikes)' ) finally: - gui.close() - controller.close() + _close_capture(gui, controller) def main(): parser = argparse.ArgumentParser(description=__doc__) parser.add_argument('--output-dir', type=Path, default=DEFAULT_OUTPUT) + parser.add_argument( + '--bounded-dir', type=Path, help='Existing package; copied before opening.' + ) + parser.add_argument( + '--comparison', action='store_true', help='Capture cluster overlay controls.' + ) + parser.add_argument('--cluster-ids', type=int, nargs='+', help='IDs for comparison captures.') + parser.add_argument('--dataset-label', help='Dataset provenance label stored in capture.json.') + parser.add_argument('--synthetic-hours', type=int, default=HOURS) args = parser.parse_args() + if args.synthetic_hours < 4: + parser.error('--synthetic-hours must be at least 4.') + if args.bounded_dir and not args.comparison: + parser.error('--bounded-dir requires --comparison.') + if args.bounded_dir: + source = args.bounded_dir.resolve() + if not (source / '_phy_curation_manifest.json').is_file(): + parser.error('--bounded-dir must contain a bounded curation manifest.') + if source == args.output_dir.resolve() or source in args.output_dir.resolve().parents: + parser.error('--output-dir must be outside the input bounded package.') + if not args.cluster_ids or len(args.cluster_ids) < 2: + parser.error('--bounded-dir comparisons require at least two --cluster-ids.') args.output_dir.mkdir(parents=True, exist_ok=True) app = QApplication.instance() or QApplication(sys.argv[:1]) with tempfile.TemporaryDirectory(prefix='phy-long-recording-screenshots-') as temporary: root = Path(temporary) - params, intervals = _make_source(root / 'source') + if args.bounded_dir: + bounded = root / 'bounded' + original_hashes = { + str(path.relative_to(source)): hash_file(path) + for path in source.rglob('*') + if path.is_file() + } + shutil.copytree(source, bounded, ignore=shutil.ignore_patterns('.phy', '*.log')) + _capture_comparison( + bounded, + root / 'config', + args.output_dir, + args.cluster_ids, + args.dataset_label + or 'Existing bounded package; acquisition exposure as declared.', + ) + checked_hashes = { + str(path.relative_to(source)): hash_file(path) + for path in source.rglob('*') + if path.is_file() + } + if original_hashes != checked_hashes: + raise RuntimeError('The input bounded package changed during capture.') + report_path = args.output_dir / 'capture.json' + report = json.loads(report_path.read_text()) + report['input_sha256'] = original_hashes + report['input_package_unchanged'] = True + report_path.write_text(json.dumps(report, indent=2) + '\n') + app.quit() + return + params, intervals = _make_source(root / 'source', hours=args.synthetic_hours) bounded = prepare_large( params, root / 'bounded', - duration_seconds=SAMPLE_RATE * 3600 * HOURS / SAMPLE_RATE, + duration_seconds=args.synthetic_hours * 3600, valid_intervals=intervals, max_spikes=20_000, max_bytes=268_435_456, @@ -245,8 +367,17 @@ def main(): batch_size=50_000, bin_seconds=1800, ) - _capture_views(bounded, root / 'config-stability', args.output_dir, stability=True) - _capture_views(bounded, root / 'config-evidence', args.output_dir, stability=False) + if args.comparison: + _capture_comparison( + bounded, + root / 'config', + args.output_dir, + args.cluster_ids or list(map(int, CLUSTER_IDS[:3])), + args.dataset_label or f'Synthetic {args.synthetic_hours}-hour fixture.', + ) + else: + _capture_views(bounded, root / 'config-stability', args.output_dir, stability=True) + _capture_views(bounded, root / 'config-evidence', args.output_dir, stability=False) app.quit() From eaaea9536defa6aa3e0c5495aa99e1d18aa28d8b Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sun, 25 Oct 2026 00:06:38 +0200 Subject: [PATCH 43/53] Document Unit Stability comparisons with matching Carl-data screenshots --- .../unit-stability-comparison-validation.md | 74 +++++++++++++++++ docs/changelog.md | 7 ++ .../unit-stability-comparison/after-merge.png | Bin 0 -> 302206 bytes .../after-overview.png | Bin 0 -> 302734 bytes .../after-rate-only.png | Bin 0 -> 290064 bytes .../before-overview.png | Bin 0 -> 270102 bytes .../synthetic-500h-overview.png | Bin 0 -> 277324 bytes docs/long-recordings.md | 77 +++++++++++++++--- 8 files changed, 145 insertions(+), 13 deletions(-) create mode 100644 design/unit-stability-comparison-validation.md create mode 100644 docs/images/unit-stability-comparison/after-merge.png create mode 100644 docs/images/unit-stability-comparison/after-overview.png create mode 100644 docs/images/unit-stability-comparison/after-rate-only.png create mode 100644 docs/images/unit-stability-comparison/before-overview.png create mode 100644 docs/images/unit-stability-comparison/synthetic-500h-overview.png diff --git a/design/unit-stability-comparison-validation.md b/design/unit-stability-comparison-validation.md new file mode 100644 index 000000000..a08b07fb6 --- /dev/null +++ b/design/unit-stability-comparison-validation.md @@ -0,0 +1,74 @@ +# Unit Stability comparison validation + +Carl's PR #1428 feedback requested independent metric visibility and comparison +of multiple clusters on long recordings. The view now overlays up to eight +selected units using authoritative selection colors, with saved firing-rate, +amplitude and depth toggles. The display limit does not change merge membership. +Existing preparation, export, journal and replay formats are unchanged. + +## Data and screenshots + +The real-data gallery uses the existing converted AIND test export from +computation `b1b0782a-b3ea-4f34-81d7-b3c6e36452b3`. Its clock spans +112.859 hours including gaps, with 113 summary bins and 705 source units. +This is the earlier local export, not Carl's newly mentioned 500-hour recording. +The conversion's acquisition mask remains unverified; these are software +integration checks, not scientific validation of exposure. + +Before and after captures select the same units, 40, 44 and 48, in a +2100 × 1200 Qt window. The baseline at `6ac9010d` displays only unit 40. +The new view displays all three, permits a full-height rate-only panel, and +preserves the same IDs and colors in Merge View. The authoritative table +presentation order is 40, 48, 44; colors follow that shared selection mapping. +Rate and amplitude are present; depth remains explicitly unavailable. + +The screenshot tool opens a disposable copy of the bounded package and checked +all 72 input file hashes remained unchanged. Full counts read from the source +summaries are 612,536 (40), 207,903 (44), and 336,413 (48). + +A separate generated 500-hour fixture contains 120,000 spikes, four units, +rate/amplitude/depth summaries and 1,000 bins. Each selected unit has exactly +30,000 source spikes. It supplies duration and missing-real-depth test coverage; +it must not be presented as Carl's 500-hour recording. + +Both capture processes exited normally after explicitly draining deferred Qt +deletions. Captures use Xvfb, Qt's X11 platform and software Mesa. Single runs, +concurrent with the test suite, measured selection/block at 0.372 s on the AIND +package and 0.623 s on the synthetic fixture. The two rate-only redraws together +took 0.094 s and 0.529 s respectively. These are observations, not benchmark +guarantees or CI timing thresholds. + +The gallery is in `docs/images/unit-stability-comparison/`. Reproduction options +are documented in `docs/long-recordings.md`; local capture manifests, source +hashes, scripts and logs are retained under +`/home/cyrille/GIT/IBL/phy-data/carl/stability-comparison/`. + +## Regression coverage and review + +Focused tests exercise exact per-unit rates with partial/zero exposure and a +short final bin, finite-value weighted merged means, pending split children +beside valid units, units without sampled evidence, row-at-a-time aggregation, +and absence of complete-spike-array reads in bounded mode. Rate-only loading +does not open trend arrays; toggle redraws reuse cached summaries. + +Selection tests cover normal/Similarity and Merge ordering, authoritative +colors, initial attachment during Merge mode, deferred hidden-view updates, +empty selection, frozen updates, display truncation, and merge/split undo/redo. +All eight metric visibility combinations retain stable axes/callback counts; +saved flags and QAction checks survive closing and reopening the view. +Ordinary optional Unit Stability retains its continuous-acquisition assumption +and refreshes cached counts on cluster edits. + +The implementation and existing adapter tests passed 25 focused cases. +An independent Sol 6.1-high audit found and reproduced a hidden-view palette +reset; the scoped fix and regression were included. Final review found no +remaining product blocker. A minimal standalone ordinary-GUI probe completed +all count assertions but exited 139 during interpreter teardown; repeating it +with explicit deferred Qt deletion exited normally. This remains a harness +cleanup limitation consistent with the earlier roundtrip record, not a verified +new product defect. + +Final local validation: `make test-full` passed 864 tests (499 core, 365 +application), with one existing benchmark skip; its lint and formatting checks +passed. `make doc-check` passed, including strict site generation and current +generated documentation. No packaging or dependency changes were made. diff --git a/docs/changelog.md b/docs/changelog.md index 575ce976b..52ecc51c7 100644 --- a/docs/changelog.md +++ b/docs/changelog.md @@ -25,6 +25,13 @@ behavior they verify rather than listed separately. - Added Unit Stability, precise window-relative amplitude/feature inspection, sampled interval/correlogram views, and explicit full-versus-evidence counts. Standard datasets retain their existing curation workflow and default layout. +- Unit Stability now overlays up to eight selected units with consistent colors + and a legend. Its saved **Show firing rate**, **Show amplitude**, and + **Show depth** view-menu toggles default on; turning all three off leaves the + plot empty. The cap is reported in view status and does not affect merge + membership. Full-source rates use acquisition exposure, and amplitude splits + mark only affected children’s metrics as pending. On ordinary recordings, + firing rates identify their continuous-acquisition assumption. - Bounded saves use validated atomic generations and reject conflicting saves from stale sessions. 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07:33:06 +0100 Subject: [PATCH 44/53] Refine stability display controls, exact rebinning and camera capture --- phy/apps/large_recording/stability.py | 226 +++++++++++++++-- .../large_recording/tests/test_stability.py | 230 +++++++++++++++++- 2 files changed, 430 insertions(+), 26 deletions(-) diff --git a/phy/apps/large_recording/stability.py b/phy/apps/large_recording/stability.py index 50e2dd2e9..9ea1b8109 100644 --- a/phy/apps/large_recording/stability.py +++ b/phy/apps/large_recording/stability.py @@ -1,20 +1,27 @@ """Selected-unit full-duration evidence with explicit acquisition exposure.""" +from collections import OrderedDict +from sys import getsizeof + import numpy as np from phylib.utils import Bunch, connect, unconnect from phy.cluster.views import ManualClusteringView +from phy.gui.qt import screenshot, screenshot_default_path from phy.plot.plot import PlotCanvasMpl from phy.utils.color import selected_cluster_color class UnitStabilityView(ManualClusteringView): - """Compare exact rates and available source trends for up to eight selected units.""" + """Compare exact rates and available source trends for selected units.""" plot_canvas_class = PlotCanvasMpl # Apply the display limit locally, retaining the full presentation selection. max_n_clusters = 0 - display_limit = 8 + display_limit = 32 + rate_line_width = 0.6 + display_bin_seconds = 0.0 + summary_cache_bytes = 64 * 1024 * 1024 _default_position = 'right' ex_status = 'Full-duration evidence; sampling cannot establish chronic unit identity.' _metrics = ('firing_rate', 'amplitude', 'depth') @@ -25,8 +32,10 @@ def __init__(self, controller): self.canvas.subplots(3, 1, sharex=True) self.show_firing_rate = self.show_amplitude = self.show_depth = True self.state_attrs += tuple(f'show_{metric}' for metric in self._metrics) + self.state_attrs += ('display_limit', 'rate_line_width') + self.local_state_attrs += ('display_bin_seconds',) self._summary_arrays = {} - self._selected_summaries = {} + self._selected_summaries = OrderedDict() self._common_data = None self._attaching = False self._footer = self.canvas.figure.text(0.12, 0.025, '', fontsize=8) @@ -85,7 +94,15 @@ def get_data(self, cluster_id, metrics=None): session = getattr(controller, 'bounded_session', None) if data is None: data = Bunch(common.copy()) - data.update(counts=None, trends={}, loaded=set(), pending=False) + data.update( + counts=None, + trends={}, + trend_sums={}, + trend_counts={}, + loaded=set(), + pending=False, + display=None, + ) if session is None: data.provenance = 'Loaded recording; continuous acquisition assumed.' else: @@ -97,11 +114,11 @@ def get_data(self, cluster_id, metrics=None): if data.pending else 'Complete source sorting; exact counts and finite-value means.' ) - # Keep at most eight summaries, including direct source-unit inspection. - if len(self._selected_summaries) >= self.display_limit: - self._selected_summaries.pop(next(iter(self._selected_summaries))) self._selected_summaries[cluster_id] = data + else: + self._selected_summaries.move_to_end(cluster_id) if data.pending: + self._trim_cache() return data for metric in metrics: if metric in data.loaded: @@ -130,17 +147,160 @@ def get_data(self, cluster_id, metrics=None): total += sums[row] valid += counts[row] mean = np.full(len(data.exposure), np.nan) - np.divide(total, valid, out=mean, where=valid > 0) + np.divide(total, valid, out=mean, where=(valid > 0) & (data.exposure > 0)) + data.trend_sums[metric] = total + data.trend_counts[metric] = valid data.trends[metric] = mean data.loaded.add(metric) + data.display = None + self._trim_cache() return data + @property + def displayed_ids(self): + """Presentation subset; the supervisor selection remains authoritative.""" + return self.cluster_ids[: self.display_limit] if self.display_limit else self.cluster_ids + + @staticmethod + def _data_bytes(data): + # Common arrays are shared/mapped, and are deliberately outside the row cache. + overhead = getsizeof(data) + getsizeof(data.loaded) + rows = data.get('rows', []) + overhead += getsizeof(rows) + sum(map(getsizeof, rows)) + arrays = [data.get('counts'), data.get('rates')] + for key in ('trends', 'trend_sums', 'trend_counts'): + overhead += getsizeof(data.get(key, {})) + arrays.extend(data.get(key, {}).values()) + display = data.get('display') + if display is not None: + overhead += getsizeof(display) + getsizeof(display.trends) + arrays.extend([display.edges, display.exposure, display.counts, display.rates]) + arrays.extend(display.trends.values()) + return overhead + sum( + a.nbytes + getsizeof(a) - (a.nbytes if a.flags.owndata else 0) + for a in arrays + if isinstance(a, np.ndarray) + ) + + def _trim_cache(self): + total = sum(self._data_bytes(data) for data in self._selected_summaries.values()) + while self._selected_summaries and total > self.summary_cache_bytes: + _, data = self._selected_summaries.popitem(last=False) + total -= self._data_bytes(data) + + def _display_factor(self, seconds=None): + seconds = self.display_bin_seconds if seconds is None else float(seconds) + if not np.isfinite(seconds) or seconds < 0: + raise ValueError('Display bin size must be zero (native) or finite and positive.') + if seconds == 0: + return 1 + native = np.diff(self._common().edges)[0] + factor = seconds / native + if ( + not np.isfinite(factor) + or factor < 1 + or not np.isclose(factor, round(factor), rtol=1e-10, atol=1e-10) + ): + raise ValueError( + 'Display bin size must be an integer multiple of the native bin size.' + ) + return int(round(factor)) + + def get_display_data(self, cluster_id, metrics=None): + """Group adjacent native bins using additive evidence, without accessing spikes.""" + data = self.get_data(cluster_id, metrics) + factor = self._display_factor() + if data.pending or factor == 1: + return data + if data.display is None or data.display.factor != factor: + starts = np.arange(0, len(data.exposure), min(factor, len(data.exposure))) + exposure = np.add.reduceat(data.exposure, starts) + counts = None if data.counts is None else np.add.reduceat(data.counts, starts) + rates = np.full(len(starts), np.nan) + if counts is not None: + np.divide(counts, exposure, out=rates, where=exposure > 0) + trends = {} + for metric, total in data.trend_sums.items(): + sums = np.add.reduceat(total, starts) + valid = np.add.reduceat(data.trend_counts[metric], starts) + mean = np.full(len(starts), np.nan) + np.divide(sums, valid, out=mean, where=(valid > 0) & (exposure > 0)) + trends[metric] = mean + data.display = Bunch( + factor=factor, + edges=np.r_[data.edges[starts], data.edges[-1]], + exposure=exposure, + counts=counts, + rates=rates, + trends=trends, + pending=False, + provenance=data.provenance, + ) + display = data.display + self._trim_cache() + return display + + def set_display_limit(self, value): + """Set maximum displayed units (0 for all; otherwise a positive integer).""" + number = float(value) + if not np.isfinite(number) or number != int(number) or number < 0: + raise ValueError('Display limit must be an nonnegative integer (0 shows all).') + self.display_limit = int(number) + self.plot() + + def set_rate_line_width(self, value): + """Set rate line width in points (finite and positive).""" + number = float(value) + if not np.isfinite(number) or number <= 0: + raise ValueError('Rate line width must be finite and positive.') + self.rate_line_width = number + self.plot() + + def set_display_bin_seconds(self, value): + """Set display bin size in seconds (0 uses native prepared bins).""" + self._display_factor(value) + self.display_bin_seconds = float(value) + for data in self._selected_summaries.values(): + data.display = None + self.plot() + + def set_state(self, state): + state = dict(state) + for key, default in ( + ('display_limit', 32), + ('rate_line_width', 0.6), + ('display_bin_seconds', 0.0), + ): + if key not in state: + continue + try: + number = float(state[key]) + valid = np.isfinite(number) + if key == 'display_limit': + valid = valid and number.is_integer() and number >= 0 + elif key == 'rate_line_width': + valid = valid and number > 0 + else: + self._display_factor(number) + state[key] = int(number) if key == 'display_limit' and valid else number + if not valid: + state[key] = default + except (ValueError, TypeError, OverflowError): + state[key] = default + super().set_state(state) + + def screenshot(self, dir=None): + """Save the actual Matplotlib Qt canvas using normal screenshot naming.""" + path = screenshot_default_path(self, dir=dir) + return screenshot(self.canvas.canvas, path=path) + @property def status(self): n = len(self.cluster_ids) return ( - f'Showing first {self.display_limit} of {n} selected units.' - if n > self.display_limit + f'Showing first {self.display_limit} of {n} selected units; ' + 'display truncation does not change the selection or merge operation.' + if self.display_limit and n > self.display_limit else '' ) @@ -188,8 +348,8 @@ def plot(self, **kwargs): unavailable = {metric: [] for metric in visible} if not self.cluster_ids: notes.append('Select a unit to inspect full-duration evidence.') - for index, cluster_id in enumerate(self.cluster_ids[: self.display_limit]): - data = self.get_data(cluster_id, visible) + for index, cluster_id in enumerate(self.displayed_ids): + data = self.get_display_data(cluster_id, visible) if data.pending: notes.append(f'Unit {cluster_id}: {data.provenance}') continue @@ -199,7 +359,13 @@ def plot(self, **kwargs): ax = axes[self._metrics.index(metric)] values = data.rates if metric == 'firing_rate' else data.trends.get(metric) if values is not None and np.any(np.isfinite(values)): - ax.plot(x, values, color=color, label=str(cluster_id)) + ax.plot( + x, + values, + color=color, + label=str(cluster_id), + linewidth=self.rate_line_width if metric == 'firing_rate' else 1.5, + ) elif metric != 'firing_rate': unavailable[metric].append(cluster_id) labels = ('Rate (Hz)', 'Mean amplitude\n(source units)', 'Mean depth\n(source units)') @@ -225,10 +391,6 @@ def plot(self, **kwargs): if previous < common.edges[-1]: ax.axvspan(previous / 3600, common.edges[-1] / 3600, color='gray', alpha=0.4) ax.set_xlim(common.edges[0] / 3600, common.edges[-1] / 3600) - if ax.lines: - ax.legend( - title='Unit', fontsize=8, loc='upper right', ncol=min(4, len(ax.lines)) - ) provenance = ( 'Complete source sorting; exact counts and finite-value means.' if getattr(self.controller, 'bounded_session', None) is not None @@ -253,10 +415,10 @@ def on_select(self, cluster_ids=None, **kwargs): cluster_ids = supervisor.selected self._update_cluster_color_indices(supervisor, cluster_ids) self.cluster_ids = tuple(cluster_ids or ()) - selected = set(self.cluster_ids[: self.display_limit]) - self._selected_summaries = { - c: d for c, d in self._selected_summaries.items() if c in selected - } + selected = set(self.displayed_ids) + self._selected_summaries = OrderedDict( + (c, d) for c, d in self._selected_summaries.items() if c in selected + ) self.plot(**kwargs) def _update_cluster_color_indices(self, sender, cluster_ids): @@ -305,6 +467,17 @@ def toggle_depth(self, checked): def _invalidate(self): self._selected_summaries.clear() + def _release_cache(self): + self._summary_arrays.clear() + self._selected_summaries.clear() + self._common_data = None + + def close(self): + """Release mapped summary references and cached rows, including unattached views.""" + result = super().close() + self._release_cache() + return result + def attach(self, gui): self._attaching = True try: @@ -320,6 +493,13 @@ def attach(self, gui): ) self.actions.get(f'toggle_{metric}').setText(f'Show {metric.replace("_", " ")}') + for action in ( + self.set_display_limit, + self.set_rate_line_width, + self.set_display_bin_seconds, + ): + self.actions.add(action, prompt=True) + @self.actions.add(prompt=True) def show_source_unit(cluster_id): """Inspect a full source unit, including one without sampled evidence.""" @@ -351,6 +531,4 @@ def on_cluster(sender, up): @connect(event='close_view', sender=self) def on_close(sender, *args): unconnect(on_state, on_cluster, on_close) - self._summary_arrays.clear() - self._selected_summaries.clear() - self._common_data = None + self._release_cache() diff --git a/phy/apps/large_recording/tests/test_stability.py b/phy/apps/large_recording/tests/test_stability.py index 031a17507..451dea3a9 100644 --- a/phy/apps/large_recording/tests/test_stability.py +++ b/phy/apps/large_recording/tests/test_stability.py @@ -132,6 +132,7 @@ def load(name): def test_selection_limit_palette_and_clear_lifecycle(summary_view): view = summary_view + view.display_limit = 8 # Repeat source rows under distinct cluster IDs to test the display bound. view.controller._source_units = lambda cluster: [1] selected = list(range(20, 30)) @@ -144,7 +145,8 @@ def test_selection_limit_palette_and_clear_lifecycle(summary_view): assert len(view._selected_summaries) == 8 ax = next(view.canvas.iter_ax()) assert len(ax.lines) == 8 - assert view.status == 'Showing first 8 of 10 selected units.' + assert 'Showing first 8 of 10 selected units' in view.status + assert 'does not change the selection or merge operation' in view.status for i, line in enumerate(ax.lines): np.testing.assert_allclose(line.get_color(), selected_cluster_color(9 - i)) view.auto_update = False @@ -195,7 +197,7 @@ def get_times(cluster): view.close() -def test_gui_initial_authoritative_selection_actions_and_curation(qtbot, tmp_path): +def test_gui_initial_authoritative_selection_actions_and_curation(qtbot, tmp_path, monkeypatch): _, controller = make_controller(tmp_path, sparse=True) gui = controller.create_gui(default_views=[], do_prompt_save=False) supervisor = controller.supervisor @@ -214,6 +216,27 @@ def test_gui_initial_authoritative_selection_actions_and_curation(qtbot, tmp_pat assert not view.actions.get('toggle_amplitude').isChecked() view.toggle_depth(False) assert not view.actions.get('toggle_depth').isChecked() + # Exercise the real dock camera callback with the Matplotlib Qt widget. + from phy.apps.large_recording import stability + + default_path = stability.screenshot_default_path + paths = [] + + def screenshot_path(widget, dir=None): + path = default_path(widget, dir=tmp_path) + paths.append(path) + return path + + monkeypatch.setattr(stability, 'screenshot_default_path', screenshot_path) + view.dock._dock_widgets['screenshot'].click() + assert paths[-1].read_bytes().startswith(b'\x89PNG\r\n\x1a\n') + assert paths[-1].name.endswith('_UnitStabilityView.png') + assert view.screenshot(tmp_path) == paths[-1] + view.actions.run('set_rate_line_width', 0.75) + view.actions.run('set_display_limit', 64) + view.actions.run('set_display_bin_seconds', 20) + assert 'display_bin_seconds' in view.local_state_attrs + assert 'display_bin_seconds' not in view.state_attrs state = view.state.copy() supervisor.toggle_merge_mode() supervisor.block() @@ -241,6 +264,9 @@ def test_gui_initial_authoritative_selection_actions_and_curation(qtbot, tmp_pat view.close() restored = UnitStabilityView(controller) restored.attach(gui) + assert restored.rate_line_width == 0.75 + assert restored.display_limit == 64 + assert restored.display_bin_seconds == 20 assert restored.show_firing_rate assert not restored.show_amplitude and not restored.show_depth assert not restored.actions.get('toggle_amplitude').isChecked() @@ -253,12 +279,15 @@ def test_gui_initial_authoritative_selection_actions_and_curation(qtbot, tmp_pat supervisor.merge([0, 1]) supervisor.block() assert view.get_data(100).counts.sum() == 7 + assert view.get_display_data(100).counts.sum() == 7 supervisor.undo() supervisor.block() assert view.get_data(0).counts.sum() == 4 + assert view.get_display_data(0).counts.sum() == 4 supervisor.redo() supervisor.block() assert view.get_data(100).counts.sum() == 7 + assert view.get_display_data(100).counts.sum() == 7 supervisor.undo() supervisor.block() up = supervisor.split_source_amplitude(0, 2) @@ -271,6 +300,7 @@ def test_gui_initial_authoritative_selection_actions_and_curation(qtbot, tmp_pat supervisor.undo() supervisor.block() assert view.get_data(0).counts.sum() == 4 + assert view.get_display_data(0).counts.sum() == 4 supervisor.redo() supervisor.block() assert view.get_data(children[0]).pending @@ -342,7 +372,203 @@ def test_ordinary_gui_cluster_event_refreshes_cached_counts(qtbot, tmp_path): ax = next(view.canvas.iter_ax()) assert np.nansum(ax.lines[0].get_ydata() * 0.2) == pytest.approx(4) assert view.get_data(0).counts.sum() == 4 + assert view.get_display_data(0).counts.sum() == 4 finally: view.close() gui.close() controller.close() + + +def test_display_limit_all_and_large_values_preserve_selection(summary_view): + view = summary_view + assert view.display_limit == 32 + view.controller._source_units = lambda cluster: [1] + selected = list(range(40)) + view.on_select(selected) + assert view.cluster_ids == tuple(selected) + assert len(view.displayed_ids) == len(next(view.canvas.iter_ax()).lines) == 32 + assert 'merge operation' in view.status + for limit in (0, 64, 128): + view.set_display_limit(limit) + assert view.displayed_ids == tuple(selected) + assert len(next(view.canvas.iter_ax()).lines) == 40 + assert not view.status + assert view.cluster_ids == tuple(selected) + for ax in view.canvas.iter_ax(): + assert ax.get_legend() is None + assert all(line.get_linewidth() == 0.6 for line in next(view.canvas.iter_ax()).lines) + view.set_rate_line_width(0.7) + assert all(line.get_linewidth() == 0.7 for line in next(view.canvas.iter_ax()).lines) + + +@pytest.mark.parametrize('value', [None, 'bad', np.nan, np.inf, -1, 0]) +def test_invalid_line_width_state_and_action(summary_view, value): + view = summary_view + with pytest.raises((ValueError, TypeError)): + view.set_rate_line_width(value) + view.set_state({'rate_line_width': value}) + assert view.rate_line_width == 0.6 + + +@pytest.mark.parametrize('value', [None, 'bad', np.nan, np.inf, -1, 1.5]) +def test_invalid_display_limit_state_and_action(summary_view, value): + view = summary_view + with pytest.raises((ValueError, TypeError)): + view.set_display_limit(value) + view.set_state({'display_limit': value}) + assert view.display_limit == 32 + + +@pytest.mark.parametrize('value', [None, 'bad', np.nan, np.inf, -1, 5, 15]) +def test_invalid_display_bins_state_and_action(summary_view, value): + view = summary_view + with pytest.raises((ValueError, TypeError)): + view.set_display_bin_seconds(value) + view.set_state({'display_bin_seconds': value}) + assert view.display_bin_seconds == 0 + + +@pytest.mark.parametrize( + 'seconds, expected_edges, counts, exposure, amplitude', + [ + (0, [0, 10, 20, 25], [16, 0, 9], [8, 0, 3], [6.8, np.nan, 5.75]), + (20, [0, 20, 25], [16, 9], [8, 3], [6.8, 5.75]), + (30, [0, 25], [25], [11], [57 / 9]), + (100, [0, 25], [25], [11], [57 / 9]), + ], +) +def test_display_rebin_exact_merged_primitives( + summary_view, seconds, expected_edges, counts, exposure, amplitude +): + view = summary_view + view.set_display_bin_seconds(seconds) + data = view.get_display_data(4) + np.testing.assert_array_equal(data.edges, expected_edges) + np.testing.assert_array_equal(data.counts, counts) + np.testing.assert_array_equal(data.exposure, exposure) + np.testing.assert_allclose(data.trends['amplitude'], amplitude, equal_nan=True) + expected_rates = np.full(len(exposure), np.nan) + np.divide(counts, exposure, out=expected_rates, where=np.asarray(exposure) > 0) + np.testing.assert_allclose(data.rates, expected_rates, equal_nan=True) + view.on_select([4]) + axes = list(view.canvas.iter_ax()) + for ax in axes: + np.testing.assert_allclose( + ax.lines[0].get_xdata(), (data.edges[:-1] + data.edges[1:]) / 7200 + ) + assert all(ax.get_legend() is None for ax in axes) + + +def test_300_second_native_bins_and_weighted_trends(summary_view, monkeypatch): + view = summary_view + common = view._common() + common.edges = np.array([0, 300, 600, 900, 1000]) + common.exposure = np.array([300.0, 0.0, 100.0, 40.0]) + common.intervals = [[0, 300], [600, 700], [900, 940]] + # Means 1 and 9 have different finite counts: their aggregate is 7, not 5. + view._summary_arrays.update( + { + 'counts.npy': np.array([[30, 0, 20, 4]]), + 'amplitude_sum.npy': np.array([[1.0, 0.0, 27.0, 20.0]]), + 'amplitude_count.npy': np.array([[1, 0, 3, 2]]), + 'depth_sum.npy': np.array([[10.0, 0.0, 270.0, 200.0]]), + 'depth_count.npy': np.array([[1, 0, 3, 2]]), + } + ) + source = view.get_data(1) + assert view._display_factor() == 1 + np.testing.assert_allclose(source.rates, [0.1, np.nan, 0.2, 0.1], equal_nan=True) + monkeypatch.setattr(view, '_array', lambda name: pytest.fail('Cached rows need no I/O')) + for seconds, edges, counts, exposures, means in ( + (600, [0, 600, 1000], [30, 24], [300, 140], [1, 47 / 5]), + (900, [0, 900, 1000], [50, 4], [400, 40], [7, 10]), + (1800, [0, 1000], [54], [440], [8]), + ): + view.set_display_bin_seconds(seconds) + data = view.get_display_data(1) + np.testing.assert_array_equal(data.edges, edges) + np.testing.assert_array_equal(data.counts, counts) + np.testing.assert_array_equal(data.exposure, exposures) + np.testing.assert_allclose(data.trends['amplitude'], means) + assert view.get_display_data(1) is data + view.set_display_bin_seconds(0) + assert view.get_display_data(1) is source + + +def test_cache_budget_independent_of_limit_and_released(summary_view): + view = summary_view + view.controller._source_units = lambda cluster: [1] + view.display_limit = 0 + budget = 2 * view._data_bytes(view.get_data(-1)) + view._invalidate() + view.summary_cache_bytes = budget + for cluster in range(20): + data = view.get_display_data(cluster) + assert data.counts.sum() == 7 + assert sum(map(view._data_bytes, view._selected_summaries.values())) <= budget + assert 19 in view._selected_summaries and 0 not in view._selected_summaries + view.summary_cache_bytes = 0 + assert view.get_data(30).counts.sum() == 7 + assert not view._selected_summaries + view._invalidate() + assert not view._selected_summaries + + +def test_6156_bins_many_units_cached_operation_bounds(summary_view, monkeypatch): + view = summary_view + bins = 6156 + common = view._common() + common.edges = np.arange(bins + 1) * 300.0 + common.exposure = np.full(bins, 300.0) + common.summary = {'counts_file': 'virtual_counts'} + common.intervals = [[0, bins * 300]] + rows = [] + + class Grid: + def __getitem__(self, row): + rows.append(row) + return np.ones(bins, dtype=np.int64) + + view._summary_arrays['virtual_counts'] = Grid() + view.controller._source_units = lambda cluster: [1] + view.show_amplitude = view.show_depth = False + view.on_select(list(range(12))) + assert len(rows) == 12 + assert len(next(view.canvas.iter_ax()).lines) == 12 + assert all(len(line.get_ydata()) == bins for line in next(view.canvas.iter_ax()).lines) + monkeypatch.setattr(view, '_array', lambda name: pytest.fail('Must reuse cached source rows')) + view.set_display_bin_seconds(900) + view.plot() + assert len(rows) == 12 + assert all(len(line.get_ydata()) == bins // 3 for line in next(view.canvas.iter_ax()).lines) + view.set_display_bin_seconds(0) + assert len(rows) == 12 + + +def test_display_gap_and_unattached_cache_release(summary_view): + view = summary_view + common = view._common() + common.exposure = np.array([0.0, 0.0, 3.0]) + view.set_display_bin_seconds(20) + data = view.get_display_data(4) + assert data.exposure[0] == 0 + assert np.isnan(data.rates[0]) + assert np.isnan(data.trends['amplitude'][0]) + assert np.isnan(data.trends['depth'][0]) + assert view._selected_summaries and view._summary_arrays + view.close() + assert not view._selected_summaries and not view._summary_arrays + assert view._common_data is None + + +def test_pending_summaries_also_obey_cache_budget(summary_view): + view = summary_view + view.controller._source_units = lambda cluster: None + pending = view.get_data(5) + view.summary_cache_bytes = 2 * view._data_bytes(pending) + for cluster in range(20): + assert view.get_data(cluster).pending + assert len(view._selected_summaries) <= 2 + assert ( + sum(map(view._data_bytes, view._selected_summaries.values())) <= view.summary_cache_bytes + ) From ada9dfb554113e2b14ddccd321098c224bddf4ae Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sun, 25 Oct 2026 07:38:54 +0100 Subject: [PATCH 45/53] Validate display-bin widths against native summary grids --- phy/apps/large_recording/stability.py | 15 ++++++++- .../large_recording/tests/test_stability.py | 31 +++++++++++++++++++ 2 files changed, 45 insertions(+), 1 deletion(-) diff --git a/phy/apps/large_recording/stability.py b/phy/apps/large_recording/stability.py index 9ea1b8109..b7c847ee0 100644 --- a/phy/apps/large_recording/stability.py +++ b/phy/apps/large_recording/stability.py @@ -194,7 +194,20 @@ def _display_factor(self, seconds=None): raise ValueError('Display bin size must be zero (native) or finite and positive.') if seconds == 0: return 1 - native = np.diff(self._common().edges)[0] + widths = np.diff(self._common().edges) + native = widths[0] if len(widths) else np.nan + if ( + not np.all(np.isfinite(widths)) + or not np.isfinite(native) + or native <= 0 + or not np.allclose(widths[:-1], native, rtol=1e-10, atol=1e-10) + or widths[-1] <= 0 + or (widths[-1] > native and not np.isclose(widths[-1], native, rtol=1e-10, atol=1e-10)) + ): + raise ValueError( + 'Display bin size in seconds requires uniform native bins, ' + 'with an optional shorter final bin. Use 0 for native bins.' + ) factor = seconds / native if ( not np.isfinite(factor) diff --git a/phy/apps/large_recording/tests/test_stability.py b/phy/apps/large_recording/tests/test_stability.py index 451dea3a9..50412cae8 100644 --- a/phy/apps/large_recording/tests/test_stability.py +++ b/phy/apps/large_recording/tests/test_stability.py @@ -572,3 +572,34 @@ def test_pending_summaries_also_obey_cache_budget(summary_view): assert ( sum(map(view._data_bytes, view._selected_summaries.values())) <= view.summary_cache_bytes ) + + +@pytest.mark.parametrize( + 'edges', + [ + [0, 10, 25, 30], + [0, 10, 20, 35], + [0, 10, 20, 20], + [0, 10, 20, np.inf], + ], +) +def test_seconds_coarsening_rejects_nonuniform_or_invalid_native_bins(summary_view, edges): + view = summary_view + view._common().edges = np.asarray(edges, dtype=float) + assert view._display_factor(0) == 1 + with pytest.raises(ValueError, match='requires uniform native bins'): + view.set_display_bin_seconds(20) + assert view.display_bin_seconds == 0 + view.set_state({'display_bin_seconds': 20}) + assert view.display_bin_seconds == 0 + + +def test_seconds_coarsening_supports_short_final_native_bin(summary_view): + view = summary_view + # The fixture's native widths are 10, 10, 5 seconds. + assert view._display_factor(20) == 2 + view.set_display_bin_seconds(20) + data = view.get_display_data(1) + np.testing.assert_array_equal(data.edges, [0, 20, 25]) + np.testing.assert_array_equal(data.counts, [4, 3]) + np.testing.assert_array_equal(data.exposure, [8, 3]) From dce597a6d594464c55771dbdeb24ecd6f2112324 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sun, 25 Oct 2026 07:40:38 +0100 Subject: [PATCH 46/53] Keep replay parameter overrides stable without rewriting user code --- phy/apps/large_recording/parameters.py | 113 ++++++++++++++++ phy/apps/large_recording/replay.py | 14 +- .../large_recording/tests/test_parameters.py | 127 ++++++++++++++++++ phy/apps/large_recording/tests/test_replay.py | 2 +- 4 files changed, 251 insertions(+), 5 deletions(-) create mode 100644 phy/apps/large_recording/parameters.py create mode 100644 phy/apps/large_recording/tests/test_parameters.py diff --git a/phy/apps/large_recording/parameters.py b/phy/apps/large_recording/parameters.py new file mode 100644 index 000000000..82349c7e1 --- /dev/null +++ b/phy/apps/large_recording/parameters.py @@ -0,0 +1,113 @@ +"""Maintain replay-owned parameter overrides without rewriting user Python.""" + +import ast +import io +import tokenize + +BEGIN = '# BEGIN PHY CURATION PARAMETERS' +END = '# END PHY CURATION PARAMETERS' +KEYS = ('num_samples', 'valid_intervals', 'dat_path') + + +def _assignments(nodes): + values = {} + for node, key in zip(nodes, KEYS, strict=True): + if ( + not isinstance(node, ast.Assign) + or len(node.targets) != 1 + or not isinstance(node.targets[0], ast.Name) + or node.targets[0].id != key + or node.col_offset != 0 + ): + raise ValueError('Not a generated parameter assignment.') + values[key] = ast.literal_eval(node.value) + return values + + +def _without_managed_block(text): + markers = [] + for token in tokenize.generate_tokens(io.StringIO(text).readline): + if token.type == tokenize.COMMENT and token.start[1] == 0 and token.string in (BEGIN, END): + markers.append((token.string, token.start[0])) + if not markers: + return text + if len(markers) != 2 or [item[0] for item in markers] != [BEGIN, END]: + raise ValueError('Malformed Phy curation parameter block.') + lines = text.splitlines(keepends=True) + first, last = markers[0][1] - 1, markers[1][1] - 1 + if ''.join(lines[last + 1 :]).strip(): + raise ValueError('Phy curation parameter block must be the final content in params.py.') + nodes = ast.parse(''.join(lines[first + 1 : last])).body + if len(nodes) != 3: + raise ValueError('Unexpected code inside Phy curation parameter block.') + try: + _assignments(nodes) + except (ValueError, TypeError) as error: + raise ValueError('Unexpected code inside Phy curation parameter block.') from error + return ''.join(lines[:first]) + + +def _strip_legacy_suffix(text, overrides): + """Remove only recognizable duplicated trailing triples from the old writer.""" + while True: + nodes = ast.parse(text).body + if len(nodes) < 6: + return text + tail = nodes[-3:] + try: + values = _assignments(tail) + except (ValueError, TypeError): + return text + if values != overrides: + return text + previous = { + target.id + for node in nodes[:-3] + if isinstance(node, ast.Assign) + for target in node.targets + if isinstance(target, ast.Name) + } + if not set(KEYS) <= previous: + return text + lines = text.splitlines(keepends=True) + if any(node.lineno != node.end_lineno for node in tail): + return text + if [node.lineno for node in tail] != list(range(tail[0].lineno, tail[0].lineno + 3)): + return text + if any( + lines[node.lineno - 1].rstrip('\r\n') != f'{key} = {values[key]!r}' + for node, key in zip(tail, KEYS, strict=True) + ): + return text + if ''.join(lines[tail[-1].end_lineno :]).strip(): + return text + # The old writer inserted one blank line immediately before every triple. + stop = tail[0].lineno - 1 + if stop and not lines[stop - 1].strip(): + stop -= 1 + text = ''.join(lines[:stop]) + + +def rewrite_replay_params(text, *, num_samples, valid_intervals, dat_path): + """Return source text with one stable, final block of replay-owned values. + + Original assignments may feed later user expressions and therefore remain + intact. Only this marked block and confidently identified legacy generated + suffixes are replaced; imports, comments and executable source are retained. + """ + if not isinstance(text, str): + raise TypeError('Parameter source must be text.') + ast.parse(text) # Validate syntax without executing user source again. + overrides = dict(zip(KEYS, (num_samples, valid_intervals, dat_path), strict=True)) + # Recognize old suffix values before normalizing legacy no-raw-data strings. + prefix = _strip_legacy_suffix(_without_managed_block(text), overrides) + paths = dat_path if isinstance(dat_path, (list, tuple)) else [dat_path] + if all( + path is None or (isinstance(path, str) and path.strip() in ('', 'None')) for path in paths + ): + overrides['dat_path'] = None + newline = '\r\n' if '\r\n' in text else '\n' + if prefix and not prefix.endswith(newline * 2): + prefix += newline if prefix.endswith(newline) else newline * 2 + block = newline.join([BEGIN, *(f'{key} = {overrides[key]!r}' for key in KEYS), END, '']) + return prefix + block diff --git a/phy/apps/large_recording/replay.py b/phy/apps/large_recording/replay.py index d292a6b59..fe0476b38 100644 --- a/phy/apps/large_recording/replay.py +++ b/phy/apps/large_recording/replay.py @@ -16,6 +16,7 @@ interpret_events, project_assignments, ) +from .parameters import rewrite_replay_params from .source import PER_SPIKE, Source, _has_raw_paths, close_array, hash_file, publish_directory @@ -158,10 +159,15 @@ def _apply_curation(source, session, output_dir, batch_size): for raw in raw_paths ] dat_path = resolved if isinstance(dat_path, (list, tuple)) else resolved[0] - with (stage / 'params.py').open('a', encoding='utf8') as stream: - stream.write(f'\nnum_samples = {source.num_samples!r}\n') - stream.write(f'valid_intervals = {source.valid_intervals.tolist()!r}\n') - stream.write(f'dat_path = {dat_path!r}\n') + params_path = stage / 'params.py' + params_path.write_bytes( + rewrite_replay_params( + params_path.read_bytes().decode('utf8'), + num_samples=source.num_samples, + valid_intervals=source.valid_intervals.tolist(), + dat_path=dat_path, + ).encode('utf8') + ) assignments = np.lib.format.open_memmap( stage / 'spike_clusters.npy', mode='w+', diff --git a/phy/apps/large_recording/tests/test_parameters.py b/phy/apps/large_recording/tests/test_parameters.py new file mode 100644 index 000000000..0addfeb2a --- /dev/null +++ b/phy/apps/large_recording/tests/test_parameters.py @@ -0,0 +1,127 @@ +"""Replay parameters retain Python semantics and stop accumulating overrides.""" + +import ast + +import pytest + +from phy.apps.large_recording.parameters import BEGIN, END, rewrite_replay_params + +VALUES = {'num_samples': 20, 'valid_intervals': [[0, 8], [10, 20]], 'dat_path': None} + + +@pytest.mark.parametrize('ending', ['', '\n', '\r\n']) +def test_managed_parameters_are_idempotent_and_keep_user_source(ending): + original = '# User comment\nimport pathlib\nnum_samples = 7\n' + original += 'derived = num_samples * 2\nvalid_intervals = [[0, 7]]\n' + original += 'alias = dat_path = "relative.bin"' + ending + rewritten = rewrite_replay_params(original, **VALUES) + assert rewritten.startswith(original) + for _ in range(3): + assert rewrite_replay_params(rewritten, **VALUES) == rewritten + namespace = {} + exec(rewritten, namespace) + assert namespace['derived'] == 14 and namespace['alias'] == 'relative.bin' + assert {key: namespace[key] for key in VALUES} == VALUES + assert rewritten.count(BEGIN) == rewritten.count(END) == 1 + + +def test_legacy_literal_suffixes_collapse_without_deleting_originals(): + original = "num_samples = 20\nvalid_intervals = [[0, 8], [10, 20]]\ndat_path = r'None'\n" + legacy = original + ( + "\nnum_samples = 20\nvalid_intervals = [[0, 8], [10, 20]]\ndat_path = 'None'\n" * 3 + ) + values = dict(VALUES, dat_path='None') + rewritten = rewrite_replay_params(legacy, **values) + assert rewritten.startswith(original) + assert len(rewritten) < len(legacy) + assert rewrite_replay_params(rewritten, **VALUES) == rewritten + assert 'dat_path = None' in rewritten + assert ( + sum( + isinstance(node, ast.Assign) + and isinstance(node.targets[0], ast.Name) + and node.targets[0].id == 'num_samples' + for node in ast.parse(rewritten).body + ) + == 2 + ) + + +def test_nonliteral_chained_conditional_and_commented_assignments_remain(): + original = 'num_samples = 10 + 10\nvalid_intervals = [[0, 20]]\ndat_path = None\n' + original += 'if True:\n num_samples = 19\n' + original += "num_samples = valid_intervals = dat_path = 'keep'\n" + original += 'num_samples = 20 # user annotation\nvalid_intervals = [[0, 8], [10, 20]]\ndat_path = None\n' + assert rewrite_replay_params(original, **VALUES).startswith(original) + + +@pytest.mark.parametrize( + 'source', + [ + BEGIN + '\nnum_samples = 1\n', + END + '\n' + BEGIN + '\n', + BEGIN + '\nprint("keep")\n' + END + '\n', + BEGIN + + '\nnum_samples = 20\nvalid_intervals = []\ndat_path = None\n' + + END + + '\nprint("keep")\n', + ], +) +def test_malformed_or_modified_managed_blocks_fail_without_deleting_code(source): + with pytest.raises(ValueError): + rewrite_replay_params(source, **VALUES) + + +def test_marker_strings_and_quoted_paths_are_safe(): + source = f'documentation = """\n{BEGIN}\n{END}\n"""\n' + path = "a'quote\\folder/\u00e9lectrode.bin" + result = rewrite_replay_params(source, **dict(VALUES, dat_path=path)) + assert result.startswith(source) + namespace = {} + exec(result, namespace) + assert namespace['dat_path'] == path + + +def test_crlf_prefix_is_preserved_byte_for_byte(): + original = '# \u00e9lectrode\r\nnum_samples = 7\r\nderived = num_samples * 2\r\n' + result = rewrite_replay_params(original, **VALUES) + assert result.startswith(original) + assert '\n' not in result.replace('\r\n', '') + assert rewrite_replay_params(result, **VALUES) == result + + +def test_three_replay_rounds_preserve_crlf_and_stable_file_size(tmp_path): + from phy.apps.large_recording.curation import BoundedSession + from phy.apps.large_recording.prepare import prepare_large + from phy.apps.large_recording.replay import apply_curation + from phy.apps.large_recording.tests.test_curation import make_session + + source, session = make_session(tmp_path) + params = source.params_path + original = params.read_text().replace('\n', '\r\n').encode('utf8') + params.write_bytes(original) + source.close() + session.save() + sizes = [] + for index in range(3): + output = apply_curation(params, session.path, tmp_path / f'output-{index}') + session.close() + params = output / 'params.py' + content = params.read_bytes() + assert content.startswith(original) + assert content.count(BEGIN.encode()) == 1 + assert b'\n' not in content.replace(b'\r\n', b'') + sizes.append(len(content)) + if index < 2: + bounded = prepare_large( + params, + tmp_path / f'bounded-{index}', + window_seconds=20, + stratum_seconds=20, + max_spikes=100, + bin_seconds=5, + batch_size=2, + ) + session = BoundedSession(bounded) + session.save() + assert len(set(sizes)) == 1 diff --git a/phy/apps/large_recording/tests/test_replay.py b/phy/apps/large_recording/tests/test_replay.py index 5910bdc82..a0d2aa50e 100644 --- a/phy/apps/large_recording/tests/test_replay.py +++ b/phy/apps/large_recording/tests/test_replay.py @@ -186,6 +186,6 @@ def test_replay_preserves_explicit_clock_metadata_and_timestamp_bytes(tmp_path, with Source(output / 'params.py') as curated: assert curated.identity == source.identity assert curated.time_base == contract - assert curated.params['dat_path'] == 'None' + assert curated.params['dat_path'] is None session.close() source.close() From 9a1eae5d0e39fef5f094923be2c191691bcde3be Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sun, 25 Oct 2026 07:40:38 +0100 Subject: [PATCH 47/53] Preserve metadata layouts and membership-scoped curation provenance --- phy/apps/large_recording/curation.py | 208 ++++++++- phy/apps/large_recording/metadata.py | 192 ++++++++ phy/apps/large_recording/prepare.py | 34 +- phy/apps/large_recording/replay.py | 34 +- phy/apps/large_recording/source.py | 37 +- phy/apps/large_recording/supervisor.py | 2 + .../large_recording/tests/test_adapter.py | 6 +- .../large_recording/tests/test_metadata.py | 424 ++++++++++++++++++ phy/apps/large_recording/tests/test_source.py | 1 + 9 files changed, 852 insertions(+), 86 deletions(-) create mode 100644 phy/apps/large_recording/metadata.py create mode 100644 phy/apps/large_recording/tests/test_metadata.py diff --git a/phy/apps/large_recording/curation.py b/phy/apps/large_recording/curation.py index e7541504f..3738cc778 100644 --- a/phy/apps/large_recording/curation.py +++ b/phy/apps/large_recording/curation.py @@ -6,11 +6,13 @@ import os import shutil import uuid +import warnings from contextlib import contextmanager from pathlib import Path import numpy as np +from .metadata import POLICY, complete_schema, validate_schema from .source import _time_base, hash_json MANIFEST = '_phy_curation_manifest.json' @@ -240,11 +242,35 @@ def interpret_events(unit_ids, metadata, events): if not isinstance(events, list): raise ValueError('Semantic journal must be an ordered event list.') next_id = max(active) + 1 - for event in events: - if not isinstance(event, dict) or event.get('version') != 1: + for event_index, event in enumerate(events): + if not isinstance(event, dict) or event.get('version') not in (1, 2): raise ValueError('Unsupported semantic journal event version.') operation = event.get('operation') - if operation == 'merge': + if operation == 'metadata_policy': + if ( + set(event) != {'version', 'operation', 'policy', 'schema'} + or event['version'] != 2 + or event['policy'] != POLICY + ): + raise ValueError('Malformed metadata policy migration event.') + validate_schema(event['schema']) + # Old resolved values have no reliable curator intent. Preserve only + # explicit label events on the current membership scope. + derived = set() + labels = {} + for previous in events[:event_index]: + op = previous['operation'] + if op == 'merge': + derived.add(previous['target']) + elif op == 'threshold_split': + derived.update(previous['children']) + elif op == 'label': + for unit in previous['ids']: + labels[(previous['field'], unit)] = previous['value'] + for field, values in metadata.items(): + for unit in derived & active: + values[unit] = copy.deepcopy(labels.get((field, unit))) + elif operation == 'merge': if set(event) != {'version', 'operation', 'parents', 'target', 'metadata'}: raise ValueError('Malformed merge event.') parents = [_integer(i, 'Parent ID') for i in event['parents']] @@ -258,6 +284,10 @@ def interpret_events(unit_ids, metadata, events): resolved = event['metadata'] if not isinstance(resolved, dict) or any(not isinstance(f, str) for f in resolved): raise ValueError('Merge metadata must contain resolved field values.') + if event['version'] == 2: + expected = dict.fromkeys(set(metadata) | {'group'}) + if resolved != expected: + raise ValueError('New membership must clear producer metadata and quality.') _json_bytes(resolved) for field in resolved: _field_name(field) @@ -302,6 +332,10 @@ def interpret_events(unit_ids, metadata, events): if any(i in allocated or i < next_id for i in children): raise ValueError('Threshold split child ID collision.') resolved = normalize_metadata(event['metadata']) + if event['version'] == 2: + expected = {field: dict.fromkeys(children) for field in set(metadata) | {'group'}} + if resolved != expected: + raise ValueError('New membership must clear producer metadata and quality.') if any(not set(v) <= set(children) for v in resolved.values()): raise ValueError('Split metadata must refer only to explicit children.') active.remove(parent) @@ -511,6 +545,11 @@ def _initialize(self, dataset_path): or not set(np.unique(self.base_assignments)) <= set(self.unit_ids) ): raise ValueError('Immutable bounded assignments do not match the full catalog.') + self.metadata_schema = validate_schema( + manifest.get('metadata_schema', {'version': 1, 'tables': []}) + ) + if manifest.get('metadata_policy') not in (None, POLICY): + raise ValueError('Unsupported bounded metadata policy.') self.base_metadata = normalize_metadata( manifest.get('base_metadata', manifest.get('metadata', {})) ) @@ -591,6 +630,13 @@ def _initialize(self, dataset_path): pointer_path = self.path / '.phy-curation' / 'current.json' if pointer_path.exists(): self._load_checkpoint(pointer_path) + if self.metadata_policy is None: + warnings.warn( + 'Legacy bounded metadata preserves inherited values; use ' + 'migrate_metadata() to adopt membership-scoped metadata.', + UserWarning, + stacklevel=2, + ) def validate_proposition_documents(self): """Keep producer input and its inherited ledger bound to preparation.""" @@ -685,6 +731,14 @@ def _load_checkpoint(self, pointer_path): ) self.assignments, self.metadata = values, metadata self.events = events + if 'metadata_policy' in descriptor and ( + descriptor['metadata_policy'] != self.metadata_policy + or descriptor.get('metadata_schema') != self.effective_metadata_schema + or descriptor.get('metadata_provenance') != self.metadata_provenance + ): + raise ValueError( + 'Checkpoint metadata policy/schema/provenance disagrees with journal.' + ) self.next_cluster_id = next_id self.checkpoint_path = generation self._expected_pointer = copy.deepcopy(pointer) @@ -745,8 +799,8 @@ def restore(self, snapshot): self.next_cluster_id = next_id def _append(self, event): - self._validate_event_capabilities([event]) events = self.events + [event] + self._validate_event_capabilities(events) _, metadata, next_id = interpret_events(self.unit_ids, self.base_metadata, events) assignments = project_assignments(self.base_assignments, events, self.attributes) self.assignments, self.metadata, self.events = assignments, metadata, events @@ -766,20 +820,138 @@ def _require_capability(self, operation, predicate=None): ) def _validate_event_capabilities(self, events): + policy = self.manifest.get('metadata_policy') == POLICY for event in events: if isinstance(event, dict): operation = event.get('operation') - if operation in ('merge', 'label', 'threshold_split'): + if operation == 'metadata_policy': + if policy: + raise ValueError('Metadata policy migration has already been applied.') + policy = True + elif operation in ('merge', 'label', 'threshold_split'): + if event.get('version') != (2 if policy else 1): + raise ValueError('Semantic event version disagrees with metadata policy.') self._require_capability(operation, event.get('predicate')) + @property + def metadata_policy(self): + return self._metadata_policy(self.events) + + def _metadata_policy(self, events): + return ( + POLICY + if ( + self.manifest.get('metadata_policy') == POLICY + or any(e['operation'] == 'metadata_policy' for e in events) + ) + else None + ) + + @property + def effective_metadata_schema(self): + return self._metadata_schema(self.events, self.metadata) + + def _metadata_schema(self, events, metadata): + schema = self.metadata_schema + for event in events: + if event['operation'] == 'metadata_policy': + schema = event['schema'] + return complete_schema(schema, metadata) + + @property + def metadata_provenance(self): + return self._metadata_provenance(self.events) + + def _metadata_provenance(self, events): + result = copy.deepcopy(self.manifest.get('metadata_provenance', {'history': []})) + metadata = copy.deepcopy(self.base_metadata) + for index, event in enumerate(events): + operation = event['operation'] + if operation in ('merge', 'threshold_split'): + parents = event['parents'] if operation == 'merge' else [event['parent']] + children = [event['target']] if operation == 'merge' else event['children'] + result.setdefault('history', []).append( + { + 'operation': operation, + 'source_revision': self.manifest['source']['revision'], + 'event_index': index, + **( + {'predicate': copy.deepcopy(event['predicate'])} + if operation == 'threshold_split' + else {} + ), + 'parents': parents, + 'children': children, + 'parent_metadata': { + field: {str(unit): values.get(unit) for unit in parents} + for field, values in metadata.items() + }, + 'policy': POLICY if event['version'] == 2 else 'legacy_inherited', + } + ) + elif operation == 'label' or operation == 'metadata_policy': + result.setdefault('history', []).append(copy.deepcopy(event)) + # Event metadata is already resolved and validated. Scan it once + # instead of replaying every prefix of a potentially long journal. + if operation in ('merge', 'threshold_split'): + for values in metadata.values(): + for parent in parents: + values.pop(parent, None) + for field, resolved in event['metadata'].items(): + values = {event['target']: resolved} if operation == 'merge' else resolved + metadata.setdefault(field, {}).update(copy.deepcopy(values)) + elif operation == 'label': + values = metadata.setdefault(event['field'], {}) + for unit in event['ids']: + values[unit] = copy.deepcopy(event['value']) + elif operation == 'metadata_policy': + _, metadata, _ = interpret_events( + self.unit_ids, self.base_metadata, events[: index + 1] + ) + return result + + def migrate_metadata(self, source_params=None): + """Explicitly clear ambiguous inherited values; retain label journal intent. + + The original manifest and generations remain immutable. Saving commits a + policy transition and schema in the same atomic generation as assignments. + Reopen a supervisor after migrating an already-open GUI session. + """ + if self.metadata_policy == POLICY: + return None + from .source import Source + + source_params = source_params or self.manifest.get('source', {}).get('path') + if not source_params: + raise ValueError('Migration requires source_params to recover original table names.') + with Source( + source_params, + duration_seconds=self.manifest['num_samples'] / self.manifest['sample_rate'], + valid_intervals=self.manifest['valid_intervals'], + ) as source: + if source.identity != self.manifest['source']['identity']: + raise ValueError('Migration source identity does not match preparation.') + if source.revision != self.manifest['source']['revision']: + raise ValueError('Migration source revision does not match preparation.') + if source.metadata != self.base_metadata: + raise ValueError('Migration base metadata does not match source metadata.') + schema = source.metadata_schema + return self._append( + {'version': 2, 'operation': 'metadata_policy', 'policy': POLICY, 'schema': schema} + ) + def preflight_merge(self, parents, target, metadata=None): self._require_capability('merge') event = { - 'version': 1, + 'version': 2 if self.metadata_policy else 1, 'operation': 'merge', 'parents': [int(i) for i in parents], 'target': _integer(target, 'Target ID'), - 'metadata': copy.deepcopy(metadata or {}), + 'metadata': ( + dict.fromkeys(set(self.metadata) | {'group'}) + if self.metadata_policy + else copy.deepcopy(metadata or {}) + ), } if event['target'] < self.next_cluster_id: raise ValueError('Merge target is below the complete catalog allocator.') @@ -791,8 +963,9 @@ def record_merge(self, parents, target, metadata=None): def preflight_label(self, field, ids, value): self._require_capability('label') + complete_schema(self.effective_metadata_schema, {**self.metadata, field: {}}) event = { - 'version': 1, + 'version': 2 if self.metadata_policy else 1, 'operation': 'label', 'field': field, 'ids': [int(i) for i in ids], @@ -812,12 +985,16 @@ def record_threshold_split(self, parent, children, predicate, metadata=None): raise ValueError('Threshold children collide with the complete catalog allocator.') return self._append( { - 'version': 1, + 'version': 2 if self.metadata_policy else 1, 'operation': 'threshold_split', 'parent': int(parent), 'children': children, 'predicate': validate_predicate(predicate), - 'metadata': normalize_metadata(metadata or {}), + 'metadata': ( + {field: dict.fromkeys(children) for field in set(self.metadata) | {'group'}} + if self.metadata_policy + else normalize_metadata(metadata or {}) + ), } ) @@ -827,12 +1004,16 @@ def preflight_split(self, parent, selected_id, remainder_id, predicate, metadata if any(i < self.next_cluster_id for i in children): raise ValueError('Threshold children collide with the complete catalog allocator.') event = { - 'version': 1, + 'version': 2 if self.metadata_policy else 1, 'operation': 'threshold_split', 'parent': int(parent), 'children': children, 'predicate': validate_predicate(predicate), - 'metadata': normalize_metadata(metadata or {}), + 'metadata': ( + {field: dict.fromkeys(children) for field in set(self.metadata) | {'group'}} + if self.metadata_policy + else normalize_metadata(metadata or {}) + ), } interpret_events(self.unit_ids, self.base_metadata, self.events + [event]) project_assignments(self.base_assignments, self.events + [event], self.attributes) @@ -911,6 +1092,9 @@ def _save_generation(self, generations, values, metadata, events, next_id, docum 'version': 1, 'manifest_sha256': _digest(self.manifest), 'next_cluster_id': next_id, + 'metadata_policy': self._metadata_policy(events), + 'metadata_schema': self._metadata_schema(events, metadata), + 'metadata_provenance': self._metadata_provenance(events), 'files': { name: _hash_file(stage / name) for name in ('spike_clusters.npy', 'journal.json', 'metadata.json', *documents) diff --git a/phy/apps/large_recording/metadata.py b/phy/apps/large_recording/metadata.py new file mode 100644 index 000000000..9ae6f671d --- /dev/null +++ b/phy/apps/large_recording/metadata.py @@ -0,0 +1,192 @@ +"""Lossless producer table layout and typed canonical unit metadata.""" + +import csv +import json +from pathlib import Path + +SCHEMA_FILE = '_phy_cluster_metadata_schema.json' +POLICY = 'membership_v1' + + +def normalize_value(value): + """Empty table cells represent missing values, including in typed JSON.""" + return None if value == '' else value + + +def cell(value): + if value is None: + return '' + if isinstance(value, (dict, list, bool)): + return json.dumps(value, sort_keys=True, separators=(',', ':'), allow_nan=False) + return str(value) + + +def validate_schema(schema): + if ( + not isinstance(schema, dict) + or set(schema) != {'version', 'tables'} + or schema['version'] != 1 + ): + raise ValueError('Unsupported metadata table schema.') + if not isinstance(schema['tables'], list): + raise ValueError('Metadata schema tables must be an ordered list.') + names, fields = set(), set() + for table in schema['tables']: + if not isinstance(table, dict) or set(table) != {'filename', 'delimiter', 'columns'}: + raise ValueError('Invalid metadata table descriptor.') + name, columns = table['filename'], table['columns'] + if ( + not isinstance(name, str) + or Path(name).name != name + or '\\' in name + or any(c in name for c in '\0\n\r') + or not name.startswith('cluster_') + or Path(name).suffix not in ('.tsv', '.csv') + or Path(name).stem.casefold() == 'cluster_info' + or name.casefold() in names + ): + raise ValueError(f'Unsafe, reserved or colliding metadata filename: {name!r}.') + if table['delimiter'] != ('\t' if name.endswith('.tsv') else ','): + raise ValueError(f'Invalid metadata delimiter: {name}.') + if ( + not isinstance(columns, list) + or len(columns) < 2 + or columns.count('cluster_id') != 1 + or any( + not isinstance(f, str) or not f or any(c in f for c in '/\\\0\n\r\t') + for f in columns + ) + or len(set(columns)) != len(columns) + ): + raise ValueError(f'Invalid or duplicate metadata columns: {name}.') + for field in columns: + if field != 'cluster_id': + if field in fields: + raise ValueError(f'Duplicate metadata field {field!r} in {name}.') + fields.add(field) + names.add(name.casefold()) + return {'version': 1, 'tables': sorted(schema['tables'], key=lambda t: t['filename'])} + + +def complete_schema(schema, metadata): + if 'cluster_id' in metadata: + raise ValueError('cluster_id is reserved for the metadata unit index.') + schema = json.loads(json.dumps(validate_schema(schema))) + fields = {f for t in schema['tables'] for f in t['columns']} + for field in sorted(set(metadata) - fields): + schema['tables'].append( + { + 'filename': f'cluster_{field}.tsv', + 'delimiter': '\t', + 'columns': ['cluster_id', field], + } + ) + return validate_schema(schema) + + +def read_metadata(path): + path = Path(path) + schema_path = path / SCHEMA_FILE + declared = json.loads(schema_path.read_text()) if schema_path.exists() else None + tables, parsed = [], {} + filenames = sorted([*path.glob('cluster_*.tsv'), *path.glob('cluster_*.csv')]) + for filename in filenames: + if filename.stem == 'cluster_info': + continue + if filename.is_symlink(): + raise ValueError(f'Metadata table must not be a symbolic link: {filename.name}.') + with filename.open(encoding='utf-8', newline='') as stream: + reader = csv.reader(stream, delimiter='\t' if filename.suffix == '.tsv' else ',') + columns = next(reader, []) + table = { + 'filename': filename.name, + 'delimiter': '\t' if filename.suffix == '.tsv' else ',', + 'columns': columns, + } + tables.append(table) + validate_schema({'version': 1, 'tables': tables}) + for field in columns: + if field != 'cluster_id': + parsed.setdefault(field, {}) + seen = set() + for row in reader: + if len(row) != len(columns): + raise ValueError(f'Malformed metadata row in {filename.name}.') + raw_id = row[columns.index('cluster_id')] + try: + unit = int(raw_id) + except ValueError as error: + raise ValueError(f'Invalid unit ID in {filename.name}: {raw_id!r}.') from error + if unit < 0 or unit in seen: + raise ValueError(f'Duplicate or negative unit {unit} in {filename.name}.') + seen.add(unit) + for field, value in zip(columns, row): + if field != 'cluster_id': + parsed.setdefault(field, {})[unit] = ( + value if declared is None else normalize_value(value) + ) + schema = validate_schema({'version': 1, 'tables': tables}) + if declared is not None and validate_schema(declared) != schema: + raise ValueError('Metadata table files or columns disagree with metadata schema.') + sidecar = path / '_phy_cluster_metadata.json' + if not sidecar.exists(): + if declared is not None: + raise ValueError('Metadata schema requires the canonical typed JSON sidecar.') + return parsed, schema + raw = json.loads(sidecar.read_text(encoding='utf-8')) + if not isinstance(raw, dict): + raise ValueError('Cluster metadata JSON must be a field mapping.') + canonical = {} + for field, values in raw.items(): + if not isinstance(values, dict): + raise ValueError('Cluster metadata fields must map integer cluster IDs to values.') + canonical[field] = {} + for key, value in values.items(): + unit = int(key) + if str(unit) != key or unit < 0: + raise ValueError('Cluster metadata IDs must be nonnegative canonical integers.') + canonical[field][unit] = value + complete_schema(schema, canonical) # Validate field-derived filenames as well. + for table in tables: + for field in table['columns']: + if field == 'cluster_id': + continue + left, right = parsed.get(field, {}), canonical.get(field, {}) + for unit in set(left) | set(right): + if declared is None and unit not in left and right.get(unit) is None: + continue # Legacy writer omitted rows for JSON null values. + if ( + declared is None + and unit in left + and unit in right + and left[unit] == str(right[unit]) + ): + continue # Legacy csv.writer used Python representations for typed values. + if unit not in left or unit not in right or cell(left[unit]) != cell(right[unit]): + raise ValueError( + f'Metadata conflict in {table["filename"]}, field {field}, unit {unit}.' + ) + if declared is not None and set(canonical) != set(parsed): + raise ValueError('Canonical metadata fields disagree with table schema.') + return canonical, complete_schema(schema, canonical) + + +def write_metadata(path, metadata, schema): + """Keep source basenames, delimiters and column order, including blank rows.""" + schema = complete_schema(schema, metadata) + for table in schema['tables']: + fields = [f for f in table['columns'] if f != 'cluster_id'] + units = sorted({u for f in fields for u in metadata.get(f, {})}) + with (path / table['filename']).open('w', encoding='utf-8', newline='') as stream: + writer = csv.writer(stream, delimiter=table['delimiter']) + writer.writerow(table['columns']) + for unit in units: + writer.writerow( + [ + unit if f == 'cluster_id' else cell(metadata.get(f, {}).get(unit)) + for f in table['columns'] + ] + ) + (path / '_phy_cluster_metadata.json').write_text(json.dumps(metadata, sort_keys=True) + '\n') + (path / SCHEMA_FILE).write_text(json.dumps(schema, sort_keys=True) + '\n') + return schema diff --git a/phy/apps/large_recording/prepare.py b/phy/apps/large_recording/prepare.py index 9bc334c0a..eddbea5eb 100644 --- a/phy/apps/large_recording/prepare.py +++ b/phy/apps/large_recording/prepare.py @@ -1,6 +1,5 @@ """Publish a self-contained bounded evidence package from a full sorting.""" -import csv import json import os import shutil @@ -9,6 +8,7 @@ import numpy as np +from .metadata import POLICY, SCHEMA_FILE, write_metadata from .source import ( PER_SPIKE, STATIC, @@ -44,22 +44,6 @@ def _union(windows, block_starts=()): return result -def _write_metadata(path, metadata): - for field, values in metadata.items(): - if ( - not isinstance(field, str) - or not field - or '/' in field - or '\\' in field - or field in ('.', '..') - ): - raise ValueError('Metadata field names must be safe filenames.') - with (path / f'cluster_{field}.tsv').open('w', encoding='utf-8', newline='') as stream: - writer = csv.writer(stream, delimiter='\t') - writer.writerow(['cluster_id', field]) - writer.writerows(sorted(values.items())) - - def _selected_waveform_count(source, windows): ids = source.arrays.get('_phy_spikes_subset.spikes.npy') if ids is None: @@ -447,10 +431,8 @@ def accept(start, end, kind, segment, stratum_id): waveform_counts[int(unit)] += int(count) waveform_ids._mmap.close() np.save(temporary / '_phy_curation_windows.npy', np.asarray(windows, dtype=np.int64)) - _write_metadata(temporary, source.metadata) - (temporary / '_phy_cluster_metadata.json').write_text( - json.dumps(source.metadata, sort_keys=True) + '\n', encoding='utf-8' - ) + metadata = source.metadata + write_metadata(temporary, metadata, source.metadata_schema) # Standard loader stays self-contained; no original raw path is referenced. params = { key: source.params[key] @@ -540,8 +522,11 @@ def accept(start, end, kind, segment, stratum_id): 'windows': final_windows, 'accepted_window_candidates': plan, 'omitted_windows': omitted, - 'metadata': source.metadata, - 'base_metadata': source.metadata, + 'metadata': metadata, + 'base_metadata': metadata, + 'metadata_schema': source.metadata_schema, + 'metadata_policy': POLICY, + 'metadata_provenance': source.metadata_provenance, 'summaries': summaries, **{key: value for key, value in summaries.items() if key.endswith('_file')}, 'selection': { @@ -601,6 +586,7 @@ def accept(start, end, kind, segment, stratum_id): not in ( 'params.py', '_phy_cluster_metadata.json', + SCHEMA_FILE, 'curation.json', 'curation_review.json', ) @@ -631,6 +617,8 @@ def accept(start, end, kind, segment, stratum_id): *temporary.glob('*.npy'), temporary / 'params.py', temporary / '_phy_cluster_metadata.json', + temporary / SCHEMA_FILE, + *(temporary / table['filename'] for table in source.metadata_schema['tables']), *(temporary / item['filename'] for item in manifest['proposition_documents'].values()), ] manifest['bounded_files'] = {p.name: hash_file(p) for p in sorted(bound_paths)} diff --git a/phy/apps/large_recording/replay.py b/phy/apps/large_recording/replay.py index fe0476b38..f1a5fe6a2 100644 --- a/phy/apps/large_recording/replay.py +++ b/phy/apps/large_recording/replay.py @@ -1,6 +1,5 @@ """Stream semantic curation into a new complete sorting, never the source.""" -import csv import os import shutil import tempfile @@ -16,6 +15,7 @@ interpret_events, project_assignments, ) +from .metadata import complete_schema, write_metadata from .parameters import rewrite_replay_params from .source import PER_SPIKE, Source, _has_raw_paths, close_array, hash_file, publish_directory @@ -35,19 +35,8 @@ def _merge_mapping(unit_ids, events): return keys, targets -def _write_metadata(path, metadata): - for field, values in sorted(metadata.items()): - if not field or any(char in field for char in ('/', '\\', '\0')): - raise ValueError('Metadata fields must be safe local filenames.') - with (path / f'cluster_{field}.tsv').open('w', encoding='utf8', newline='') as stream: - writer = csv.writer(stream, delimiter='\t') - writer.writerow(['cluster_id', field]) - for cluster, value in sorted(values.items()): - if value is not None: - writer.writerow([cluster, value]) - stream.flush() - os.fsync(stream.fileno()) - _write_json(path / '_phy_cluster_metadata.json', metadata) +def _write_metadata(path, metadata, schema=None): + return write_metadata(path, metadata, schema or {'version': 1, 'tables': []}) def apply_curation(source_params, bounded_dir, output_dir, batch_size=100000): @@ -79,11 +68,20 @@ def apply_curation(source_params, bounded_dir, output_dir, batch_size=100000): def _apply_curation(source, session, output_dir, batch_size): session.validate_proposition_documents() manifest = session.manifest + if 'metadata_schema' in manifest and source.metadata_schema != manifest['metadata_schema']: + raise ValueError('Source metadata schema changed since bounded preparation.') + if ( + 'metadata_provenance' in manifest + and source.metadata_provenance != manifest['metadata_provenance'] + ): + raise ValueError('Source metadata provenance changed since bounded preparation.') expected = manifest['source'] if source.identity != expected['identity']: raise ValueError('Source coordinate/feature identity does not match bounded preparation.') if source.revision != expected['revision']: raise ValueError('Source assignment revision does not match journal parent revision.') + if source.metadata != session.base_metadata: + raise ValueError('Bounded base metadata does not match the source metadata revision.') if ( source.unit_ids.tolist() != manifest['unit_ids'] or source.n_spikes != manifest['num_spikes'] @@ -117,7 +115,9 @@ def _apply_curation(source, session, output_dir, batch_size): raise ValueError(f'Bounded attribute does not match source rows: {name}.') finally: close_array(bounded) - active_units, metadata, _ = interpret_events(source.unit_ids, source.metadata, session.events) + active_units, metadata, _ = interpret_events( + source.unit_ids, session.base_metadata, session.events + ) output = Path(output_dir).resolve() if output.exists(): raise FileExistsError(f'Curated output already exists: {output}.') @@ -191,7 +191,7 @@ def _apply_curation(source, session, output_dir, batch_size): assignments._mmap.close() del flat, assignments assignments = None - _write_metadata(stage, metadata) + _write_metadata(stage, metadata, complete_schema(source.metadata_schema, metadata)) _write_json(stage / '_phy_curation_journal.json', session.events) proposition_hashes = {} item = session.proposition_documents.get('curation.json') @@ -234,6 +234,8 @@ def _apply_curation(source, session, output_dir, batch_size): 'unit_ids': sorted(active_units), 'retired_units': session.retired_units, 'proposition_documents': proposition_hashes, + 'metadata_provenance': session.metadata_provenance, + 'metadata_policy': session.metadata_policy, }, ) curated.close() diff --git a/phy/apps/large_recording/source.py b/phy/apps/large_recording/source.py index fb70eccaa..ee7534735 100644 --- a/phy/apps/large_recording/source.py +++ b/phy/apps/large_recording/source.py @@ -1,6 +1,5 @@ """Validated, file-backed source sorting on one monotonic integer time axis.""" -import csv import ctypes import errno import hashlib @@ -12,6 +11,8 @@ import numpy as np +from .metadata import read_metadata + PER_SPIKE = frozenset( ( 'spike_times.npy', @@ -142,36 +143,7 @@ def _vector(array, name): def _metadata(path): - sidecar = path / '_phy_cluster_metadata.json' - if sidecar.exists(): - metadata = json.loads(sidecar.read_text(encoding='utf-8')) - if not isinstance(metadata, dict): - raise ValueError('Cluster metadata JSON must be a field mapping.') - result = {} - for field, values in metadata.items(): - if not isinstance(values, dict): - raise ValueError('Cluster metadata fields must map integer cluster IDs to values.') - result[field] = {int(key): value for key, value in values.items()} - if any(key < 0 for key in result[field]): - raise ValueError('Cluster metadata IDs must be nonnegative.') - return result - result = {} - for filename in sorted([*path.glob('cluster_*.tsv'), *path.glob('cluster_*.csv')]): - # cluster_info is generated GUI metrics, not a source label table. - if filename.stem == 'cluster_info': - continue - with filename.open(encoding='utf-8', newline='') as stream: - reader = csv.DictReader(stream, delimiter='\t' if filename.suffix == '.tsv' else ',') - if not reader.fieldnames or 'cluster_id' not in reader.fieldnames: - raise ValueError(f'{filename.name} requires a cluster_id column.') - for row in reader: - cluster_id = int(row['cluster_id']) - if cluster_id < 0: - raise ValueError('Cluster metadata IDs must be nonnegative.') - for field, value in row.items(): - if field != 'cluster_id': - result.setdefault(field, {})[cluster_id] = value - return result + return read_metadata(path)[0] def _time_base(value): @@ -382,7 +354,7 @@ def _initialize( if required not in self.arrays: raise ValueError(f'Missing required source array {required}.') self.n_spikes = len(_vector(self.arrays['spike_times.npy'], 'spike_times.npy')) - self.metadata = _metadata(self.path) + self.metadata, self.metadata_schema = read_metadata(self.path) self.validate() counts = {} for batch in self.iter_batches(): @@ -405,6 +377,7 @@ def _initialize( if not isinstance(unit, int) or unit < 0: raise ValueError('Lineage unit IDs must be nonnegative integers.') counts.setdefault(unit, 0) + self.metadata_provenance = lineage.get('metadata_provenance', {'history': []}) self.retired_units = lineage.get('retired_units', {}) if not isinstance(self.retired_units, dict): raise ValueError('Lineage retired_units must be a mapping.') diff --git a/phy/apps/large_recording/supervisor.py b/phy/apps/large_recording/supervisor.py index bcca4c9e4..78603a399 100644 --- a/phy/apps/large_recording/supervisor.py +++ b/phy/apps/large_recording/supervisor.py @@ -314,6 +314,8 @@ def _refresh_bounded(self): emit('bounded_state_changed', self) def _capture(self): + if self.session.metadata_policy: + self._synchronize_metadata() self._validate_native() self.session_history.capture() self._global_history.add_to_current_action(self.session_history) diff --git a/phy/apps/large_recording/tests/test_adapter.py b/phy/apps/large_recording/tests/test_adapter.py index 94f280941..0c44051ac 100644 --- a/phy/apps/large_recording/tests/test_adapter.py +++ b/phy/apps/large_recording/tests/test_adapter.py @@ -139,8 +139,8 @@ def test_merge_label_history_save_reopen_replay_regenerate(tmp_path): assert controller.get_full_count(100) == 7 supervisor.label('group', 'noise', [100]) supervisor.undo() - assert controller.bounded_session.metadata['group'][100] == 'good' - assert supervisor.cluster_meta.get('group', 100) == 'good' + assert controller.bounded_session.metadata['group'][100] is None + assert supervisor.cluster_meta.get('group', 100) is None supervisor.redo() assert controller.bounded_session.metadata['group'][100] == 'noise' supervisor.undo() @@ -225,7 +225,7 @@ def fail(path, value): with pytest.raises(OSError, match='interrupted'): supervisor.save() assert supervisor.is_dirty() - assert BoundedSession(controller.dir_path).metadata['group'][100] == 'good' + assert BoundedSession(controller.dir_path).metadata['group'][100] is None finally: controller.close() diff --git a/phy/apps/large_recording/tests/test_metadata.py b/phy/apps/large_recording/tests/test_metadata.py new file mode 100644 index 000000000..22ce28c2b --- /dev/null +++ b/phy/apps/large_recording/tests/test_metadata.py @@ -0,0 +1,424 @@ +"""Membership-scoped metadata, source layouts and explicit legacy migration.""" + +import csv +import json + +import numpy as np +import pytest + +from phy.apps.large_recording.curation import BoundedSession, interpret_events +from phy.apps.large_recording.metadata import ( + POLICY, + SCHEMA_FILE, + complete_schema, + read_metadata, + validate_schema, + write_metadata, +) +from phy.apps.large_recording.prepare import prepare_large +from phy.apps.large_recording.replay import apply_curation +from phy.apps.large_recording.source import Source, hash_file +from phy.apps.large_recording.tests.test_curation import make_session +from phy.apps.large_recording.tests.test_source import make_sorting + + +def prepared(params, destination): + prepare_large( + params, + destination, + window_seconds=20, + stratum_seconds=20, + max_spikes=100, + bin_seconds=5, + batch_size=2, + ) + return BoundedSession(destination) + + +def metadata_sorting(tmp_path): + params = make_sorting(tmp_path / 'source') + (params.parent / 'cluster_si_unit_ids.tsv').write_text( + 'cluster_id\tsi_unit_id\n0\t40\n1\t44\n2\t48\n88\tempty\n99\t99\n' + ) + (params.parent / 'cluster_producer.csv').write_text( + 'unknown,cluster_id,bombcell,snr\nsua,0,good,12.26\nsua,1,good,12.92\n' + 'sua,2,mua,12.16\n,88,,\nunchanged,99,noise,3\n' + ) + return params + + +def test_three_round_membership_and_noop_export(tmp_path): + params = metadata_sorting(tmp_path) + original = Source(params) + expected_unchanged = {field: values.get(99) for field, values in original.metadata.items()} + expected_empty = {field: values.get(88) for field, values in original.metadata.items()} + original.close() + predicate = { + 'attribute': 'amplitudes.npy', + 'operator': '<', + 'threshold': 4.0, + 'nonfinite': 'keep', + } + previous_history = 0 + for round_id in range(3): + session = prepared(params, tmp_path / f'bounded-{round_id}') + assert session.metadata_policy == POLICY + if round_id == 0: + session.record_label('group', [0], 'good') + session.record_merge([0, 1], 100, {'group': 'good', 'snr': 12.26}) + children = [100] + elif round_id == 1: + assert session.metadata['group'][100] == 'good' + session.record_threshold_split( + 100, [101, 102], predicate, {'group': {101: 'good', 102: 'good'}} + ) + children = [101, 102] + else: + session.record_merge([101, 102, 2], 103, {'group': 'good'}) + children = [103] + for values in session.metadata.values(): + assert all(values[unit] is None for unit in children) + for field, value in expected_unchanged.items(): + assert session.metadata[field].get(99) == value + for field, value in expected_empty.items(): + assert session.metadata[field].get(88) == value + session.record_label('group', children, 'good') + session.save() + output = apply_curation(params, session.path, tmp_path / f'round-{round_id}') + assert (output / 'cluster_si_unit_ids.tsv').exists() + assert not (output / 'cluster_si_unit_id.tsv').exists() + with (output / 'cluster_producer.csv').open(newline='') as stream: + rows = list(csv.reader(stream)) + assert rows[0] == ['unknown', 'cluster_id', 'bombcell', 'snr'] + for unit in children: + assert next(row for row in rows[1:] if row[1] == str(unit)) == ['', str(unit), '', ''] + current = Source(output / 'params.py') + assert current.metadata == session.metadata + history = current.metadata_provenance['history'] + membership = [ + record for record in history if record['operation'] in ('merge', 'threshold_split') + ] + latest = membership[-1] + assert latest['parent_metadata']['group'][str(latest['parents'][0])] == 'good' + if round_id == 0: + assert latest['parent_metadata']['group']['1'] == 'mua' + assert len(history) > previous_history + previous_history = len(history) + current.close() + session.close() + # A full no-op round retains the explicit label on this membership. + noop = prepared(output / 'params.py', tmp_path / f'noop-bounded-{round_id}') + assert all(noop.metadata['group'][unit] == 'good' for unit in children) + noop.save() + noop_output = apply_curation( + output / 'params.py', noop.path, tmp_path / f'noop-output-{round_id}' + ) + noop.close() + params = noop_output / 'params.py' + + +def test_typed_tables_roundtrip_and_conflicts(tmp_path): + schema = { + 'version': 1, + 'tables': [ + { + 'filename': 'cluster_si_unit_ids.tsv', + 'delimiter': '\t', + 'columns': ['cluster_id', 'si_unit_id'], + }, + { + 'filename': 'cluster_metrics.csv', + 'delimiter': ',', + 'columns': ['snr', 'cluster_id', 'flag', 'details'], + }, + ], + } + metadata = { + 'si_unit_id': {0: 40, 1: None}, + 'snr': {0: 12.26, 1: None}, + 'flag': {0: True, 1: False}, + 'details': {0: ['a', 1], 1: {'x': 2}}, + 'group': {0: 'good', 1: None}, + } + write_metadata(tmp_path, metadata, schema) + assert read_metadata(tmp_path)[0] == metadata + assert read_metadata(tmp_path)[1] == complete_schema(schema, metadata) + metric = tmp_path / 'cluster_metrics.csv' + metric.write_text(metric.read_text().replace('12.26', '99.0')) + with pytest.raises(ValueError, match='cluster_metrics.csv, field snr, unit 0'): + read_metadata(tmp_path) + + +@pytest.mark.parametrize( + 'filename', ['../cluster_metric.tsv', 'cluster_info.tsv', 'cluster_bad\\evil.tsv', 'params.py'] +) +def test_unsafe_or_reserved_filenames(filename): + with pytest.raises(ValueError, match='filename'): + validate_schema( + { + 'version': 1, + 'tables': [ + {'filename': filename, 'delimiter': '\t', 'columns': ['cluster_id', 'metric']} + ], + } + ) + + +def test_duplicate_fields_and_casefold_collisions(tmp_path): + (tmp_path / 'cluster_a.tsv').write_text('cluster_id\tsnr\n0\t1\n') + (tmp_path / 'cluster_b.csv').write_text('cluster_id,snr\n0,1\n') + with pytest.raises(ValueError, match='Duplicate metadata field'): + read_metadata(tmp_path) + with pytest.raises(ValueError, match='colliding'): + validate_schema( + { + 'version': 1, + 'tables': [ + { + 'filename': 'cluster_A.tsv', + 'delimiter': '\t', + 'columns': ['cluster_id', 'a'], + }, + { + 'filename': 'cluster_a.tsv', + 'delimiter': '\t', + 'columns': ['cluster_id', 'b'], + }, + ], + } + ) + + +def test_legacy_blank_omitted_rows_and_conflicting_edit(tmp_path): + (tmp_path / 'cluster_metric.tsv').write_text('cluster_id\tmetric\n0\t4\n2\t\n') + (tmp_path / '_phy_cluster_metadata.json').write_text( + json.dumps({'metric': {'0': 4, '1': None, '2': ''}}) + ) + metadata, schema = read_metadata(tmp_path) + assert metadata['metric'] == {0: 4, 1: None, 2: ''} + write_metadata(tmp_path, metadata, schema) + assert read_metadata(tmp_path)[0] == metadata + assert '1\t\n' in (tmp_path / 'cluster_metric.tsv').read_text() + (tmp_path / 'cluster_metric.tsv').write_text('cluster_id\tmetric\n0\t9\n1\t\n2\t\n') + with pytest.raises(ValueError, match='field metric, unit 0'): + read_metadata(tmp_path) + + +def test_legacy_migration_atomic_reopen_history_and_reviews(tmp_path): + source, session = make_session(tmp_path) + session.record_merge([0, 1], 100, {'group': 'good', 'producer': 9}) + session.record_label('group', [100], 'good') + session.record_merge([100, 2], 101, {'group': 'good', 'producer': 9}) + session.record_label('comment', [101], 'explicit decision') + review = {'opaque_review': ['unchanged']} + legacy_generation = session.save(extra_documents={'review.json': review}) + manifest_hash = hash_file(session.path / '_phy_curation_manifest.json') + old_hash = hash_file(legacy_generation / 'metadata.json') + before = session.snapshot() + event = session.migrate_metadata() + assert event['operation'] == 'metadata_policy' + assert session.metadata['group'][101] is None # Parent's explicit label expires. + assert session.metadata['producer'][101] is None + assert session.metadata['comment'][101] == 'explicit decision' + migrated = session.snapshot() + session.restore(before) + assert session.metadata['group'][101] == 'good' + session.restore(migrated) + assert session.metadata['group'][101] is None + np.testing.assert_array_equal(session.assignments, before['assignments']) + assert session.next_cluster_id == before['next_cluster_id'] + session.save() + reopened = BoundedSession(session.path) + assert reopened.metadata_policy == POLICY + assert reopened.metadata == session.metadata + assert reopened.extra_documents['review.json'] == review + assert hash_file(session.path / '_phy_curation_manifest.json') == manifest_hash + assert hash_file(legacy_generation / 'metadata.json') == old_hash + reopened.record_label('group', [101], 'good') + assert reopened.metadata['group'][101] == 'good' + reopened.record_merge([101, 99], 102, {'group': 'good'}) + assert reopened.metadata['group'][102] is None + source.close() + session.close() + reopened.close() + + +def test_legacy_interpretation_is_unchanged(): + events = [ + { + 'version': 1, + 'operation': 'merge', + 'parents': [0, 1], + 'target': 2, + 'metadata': {'group': 'good', 'snr': 12.26}, + } + ] + _, metadata, _ = interpret_events([0, 1], {'snr': {0: 12.26, 1: 8}}, events) + assert metadata == {'group': {2: 'good'}, 'snr': {2: 12.26}} + + +def test_blank_legacy_metadata_preserves_revision_and_v1_values(tmp_path): + from phy.apps.large_recording.source import assignment_revision + + params = make_sorting(tmp_path / 'full') + (params.parent / 'cluster_metric.tsv').write_text('cluster_id\tmetric\n0\t\n') + with Source(params) as source: + legacy = {'group': {0: 'good', 1: 'mua', 2: 'good', 99: 'noise'}, 'metric': {0: ''}} + assert source.metadata == legacy + assert source.revision == assignment_revision(params.parent, legacy) + _, projected, _ = interpret_events([0, 1], {'metric': {0: ''}}, []) + assert projected == {'metric': {0: ''}} + + +def test_save_snapshot_policy_schema_and_provenance_use_supplied_state(tmp_path): + source, session = make_session(tmp_path) + session.record_merge([0, 1], 100, {'group': 'good'}) + legacy = session.snapshot() + session.migrate_metadata() + session.record_label('group', [100], 'good') + # Save an earlier valid history prefix, as undo/history clients can do. + session.save(**legacy) + reopened = BoundedSession(session.path) + assert reopened.events == legacy['events'] + assert reopened.metadata == legacy['metadata'] + assert reopened.metadata_policy is None + assert len(reopened.metadata_provenance['history']) == 1 + source.close() + session.close() + reopened.close() + + +def test_migration_rejects_same_metadata_with_changed_source_coordinates(tmp_path): + source, session = make_session(tmp_path) + source.close() + amplitudes = np.load(source.path / 'amplitudes.npy') + amplitudes[0] += 1 + np.save(source.path / 'amplitudes.npy', amplitudes) + with pytest.raises(ValueError, match='identity'): + session.migrate_metadata() + assert not session.events + session.close() + + +def test_gui_membership_quality_metadata_and_history(tmp_path): + from phy.apps.large_recording.tests.test_adapter import make_controller + + _, controller = make_controller(tmp_path) + try: + supervisor = controller.supervisor + supervisor.label('producer_metric', 42, [0, 1]) + supervisor.label('classification', 'sua', [0, 1]) + supervisor.merge([0, 1]) + session = controller.bounded_session + for field in ('producer_metric', 'classification', 'group'): + assert session.metadata[field][100] is None + assert supervisor.cluster_meta.get(field, 100) is None + assert supervisor.cluster_meta.get('group', 2) == 'good' + supervisor.label('group', 'good', [100]) + supervisor.undo() + assert supervisor.cluster_meta.get('group', 100) is None + supervisor.redo() + assert supervisor.cluster_meta.get('group', 100) == 'good' + supervisor.split_source_amplitude(100, 4) + children = session.events[-1]['children'] + for field in ('producer_metric', 'classification', 'group'): + assert all(supervisor.cluster_meta.get(field, child) is None for child in children) + supervisor.undo() + assert supervisor.cluster_meta.get('group', 100) == 'good' + supervisor.redo() + assert all(supervisor.cluster_meta.get('group', child) is None for child in children) + supervisor.save() + finally: + controller.close() + + +def test_migration_keeps_explicit_target_quality_and_old_generation_reopens(tmp_path): + source, session = make_session(tmp_path) + # The original spelling cannot be inferred from the group header alone. + (source.path / 'cluster_group.tsv').rename(source.path / 'cluster_quality_archive.tsv') + session.record_merge([0, 1], 100, {'group': 'noise'}) + session.record_label('group', [100], 'good') + session.save() + pointer_path = session.path / '.phy-curation' / 'current.json' + legacy_pointer = pointer_path.read_bytes() + legacy_metadata = session.snapshot()['metadata'] + session.migrate_metadata() + assert session.metadata['group'][100] == 'good' + assert ( + session.effective_metadata_schema['tables'][0]['filename'] == 'cluster_quality_archive.tsv' + ) + session.save() + migrated_pointer = pointer_path.read_bytes() + pointer_path.write_bytes(legacy_pointer) + with pytest.warns(UserWarning, match='Legacy bounded metadata'): + old = BoundedSession(session.path) + assert old.metadata == legacy_metadata + assert old.metadata_policy is None + old.close() + pointer_path.write_bytes(migrated_pointer) + migrated = BoundedSession(session.path) + assert migrated.metadata['group'][100] == 'good' + assert migrated.metadata_policy == POLICY + migrated.close() + source.close() + session.close() + + +def test_v2_resolved_metadata_cannot_smuggle_parent_measurements(): + event = { + 'version': 2, + 'operation': 'merge', + 'parents': [0, 1], + 'target': 2, + 'metadata': {'group': 'good', 'snr': 12.26}, + } + with pytest.raises(ValueError, match='clear producer metadata'): + interpret_events([0, 1], {'snr': {0: 12.26, 1: 8}}, [event]) + + +def test_legacy_typed_python_table_representations(tmp_path): + metadata = {'flag': {'0': True}, 'details': {'0': ['a', 1]}} + (tmp_path / '_phy_cluster_metadata.json').write_text(json.dumps(metadata)) + (tmp_path / 'cluster_flag.tsv').write_text('cluster_id\tflag\n0\tTrue\n') + (tmp_path / 'cluster_details.tsv').write_text("cluster_id\tdetails\n0\t['a', 1]\n") + assert read_metadata(tmp_path)[0] == {'flag': {0: True}, 'details': {0: ['a', 1]}} + + +def test_merge_empty_catalog_unit_does_not_inherit_identity(tmp_path): + params = metadata_sorting(tmp_path) + session = prepared(params, tmp_path / 'bounded') + session.record_merge([0, 88], 100) + assert session.metadata['si_unit_id'][100] is None + session.save() + output = apply_curation(params, session.path, tmp_path / 'out') + with Source(output / 'params.py') as curated: + assert 88 not in curated.unit_ids + assert curated.metadata['si_unit_id'][100] is None + assert curated.counts[curated.unit_ids.tolist().index(100)] == 4 + session.close() + + +def test_replay_rejects_unsourced_manifest_metadata(tmp_path): + source, session = make_session(tmp_path) + session.close() + manifest_path = session.path / '_phy_curation_manifest.json' + manifest = json.loads(manifest_path.read_text()) + manifest['base_metadata']['group']['0'] = 'fabricated' + manifest_path.write_text(json.dumps(manifest)) + session = BoundedSession(session.path) + session.save() + with pytest.raises(ValueError, match='base metadata does not match'): + apply_curation(source.params_path, session.path, tmp_path / 'out') + assert not (tmp_path / 'out').exists() + source.close() + session.close() + + +def test_replay_rejects_changed_original_table_basename(tmp_path): + params = metadata_sorting(tmp_path) + session = prepared(params, tmp_path / 'bounded') + session.save() + (params.parent / 'cluster_si_unit_ids.tsv').rename(params.parent / 'cluster_si_unit_id.tsv') + with pytest.raises(ValueError, match='metadata schema changed'): + apply_curation(params, session.path, tmp_path / 'out') + session.close() diff --git a/phy/apps/large_recording/tests/test_source.py b/phy/apps/large_recording/tests/test_source.py index d576c2e9f..a0642ffe7 100644 --- a/phy/apps/large_recording/tests/test_source.py +++ b/phy/apps/large_recording/tests/test_source.py @@ -162,6 +162,7 @@ def test_reject_ambiguous_or_misaligned_sources(tmp_path, failure): def test_metadata_json_preserves_typed_values(tmp_path): params = make_sorting(tmp_path / 'full') + (params.parent / 'cluster_group.tsv').write_text('cluster_id\tgroup\n0\tgood\n') metadata = {'group': {'0': 'good'}, 'custom': {'99': None, '2': 4}} (params.parent / '_phy_cluster_metadata.json').write_text(json.dumps(metadata)) assert Source(params).metadata == {'group': {0: 'good'}, 'custom': {99: None, 2: 4}} From 2887f925bec812d757447d2c3d2c8307fa050a7e Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sun, 25 Oct 2026 07:44:52 +0100 Subject: [PATCH 48/53] Preserve read-only metadata symlink inputs without unsafe output writes --- phy/apps/large_recording/metadata.py | 6 ++- .../large_recording/tests/test_metadata.py | 45 +++++++++++++++++++ 2 files changed, 49 insertions(+), 2 deletions(-) diff --git a/phy/apps/large_recording/metadata.py b/phy/apps/large_recording/metadata.py index 9ae6f671d..7b6a6bb26 100644 --- a/phy/apps/large_recording/metadata.py +++ b/phy/apps/large_recording/metadata.py @@ -93,8 +93,6 @@ def read_metadata(path): for filename in filenames: if filename.stem == 'cluster_info': continue - if filename.is_symlink(): - raise ValueError(f'Metadata table must not be a symbolic link: {filename.name}.') with filename.open(encoding='utf-8', newline='') as stream: reader = csv.reader(stream, delimiter='\t' if filename.suffix == '.tsv' else ',') columns = next(reader, []) @@ -174,6 +172,10 @@ def read_metadata(path): def write_metadata(path, metadata, schema): """Keep source basenames, delimiters and column order, including blank rows.""" schema = complete_schema(schema, metadata) + filenames = [table['filename'] for table in schema['tables']] + for filename in [*filenames, '_phy_cluster_metadata.json', SCHEMA_FILE]: + if (path / filename).is_symlink(): + raise ValueError(f'Metadata output must not overwrite a symbolic link: {filename}.') for table in schema['tables']: fields = [f for f in table['columns'] if f != 'cluster_id'] units = sorted({u for f in fields for u in metadata.get(f, {})}) diff --git a/phy/apps/large_recording/tests/test_metadata.py b/phy/apps/large_recording/tests/test_metadata.py index 22ce28c2b..55d61c26d 100644 --- a/phy/apps/large_recording/tests/test_metadata.py +++ b/phy/apps/large_recording/tests/test_metadata.py @@ -422,3 +422,48 @@ def test_replay_rejects_changed_original_table_basename(tmp_path): with pytest.raises(ValueError, match='metadata schema changed'): apply_curation(params, session.path, tmp_path / 'out') session.close() + + +def test_readonly_source_symlink_preserves_table_alias_and_target(tmp_path): + params = make_sorting(tmp_path / 'source') + producer = tmp_path / 'immutable-producer-si.tsv' + producer.write_text('cluster_id\tsi_unit_id\n0\t40\n1\t44\n2\t48\n99\t99\n') + alias = params.parent / 'cluster_si_unit_ids.tsv' + alias.symlink_to(producer) + original_hash = hash_file(producer) + with Source(params) as source: + assert source.metadata['si_unit_id'][0] == '40' + descriptor = next( + table for table in source.metadata_schema['tables'] if 'si_unit_id' in table['columns'] + ) + assert descriptor['filename'] == 'cluster_si_unit_ids.tsv' + session = prepared(params, tmp_path / 'bounded') + session.save() + output = apply_curation(params, session.path, tmp_path / 'out') + assert (output / 'cluster_si_unit_ids.tsv').is_file() + assert not (output / 'cluster_si_unit_ids.tsv').is_symlink() + assert alias.is_symlink() + assert hash_file(producer) == original_hash + session.close() + + +def test_metadata_output_refuses_existing_symlink_without_mutating_target(tmp_path): + producer = tmp_path / 'producer.tsv' + producer.write_text('immutable producer data') + destination = tmp_path / 'out' + destination.mkdir() + (destination / 'cluster_si_unit_ids.tsv').symlink_to(producer) + schema = { + 'version': 1, + 'tables': [ + { + 'filename': 'cluster_si_unit_ids.tsv', + 'delimiter': '\t', + 'columns': ['cluster_id', 'si_unit_id'], + } + ], + } + original_hash = hash_file(producer) + with pytest.raises(ValueError, match='output must not overwrite a symbolic link'): + write_metadata(destination, {'si_unit_id': {0: '40'}}, schema) + assert hash_file(producer) == original_hash From 87b8069b5da7a9c2e5425668ed477039c139efff Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sun, 25 Oct 2026 07:45:22 +0100 Subject: [PATCH 49/53] Capture native and coarsened stability traces with the camera action --- tools/capture_long_recording_views.py | 65 ++++++++++++++++++++------- 1 file changed, 48 insertions(+), 17 deletions(-) diff --git a/tools/capture_long_recording_views.py b/tools/capture_long_recording_views.py index 3af9a8b8a..579ecb1fd 100644 --- a/tools/capture_long_recording_views.py +++ b/tools/capture_long_recording_views.py @@ -36,10 +36,11 @@ CLUSTER_IDS = np.array([0, 2, 7, 99], dtype=np.int32) -def _make_source(path, hours=HOURS): +def _make_source(path, hours=HOURS, unit_count=4): """Write a varied but deterministic synthetic source sorting.""" path.mkdir(parents=True) rng = np.random.default_rng(20261013) + cluster_ids = CLUSTER_IDS if unit_count == 4 else np.arange(unit_count, dtype=np.int32) samples = SAMPLE_RATE * 3600 * hours intervals = np.array( [[0, 3 * 3600 * SAMPLE_RATE], [int(3.5 * 3600 * SAMPLE_RATE), samples]], @@ -54,7 +55,7 @@ def _make_source(path, hours=HOURS): order = np.argsort(spike_times, kind='stable') spike_times = spike_times[order] - unit_index = np.arange(len(spike_times), dtype=np.int64) % len(CLUSTER_IDS) + unit_index = np.arange(len(spike_times), dtype=np.int64) % len(cluster_ids) unit_index = unit_index[order] elapsed = spike_times / SAMPLE_RATE hour_phase = elapsed / 3600 @@ -74,7 +75,7 @@ def _make_source(path, hours=HOURS): templates_for_spike = unit_index.astype(np.int32) np.save(path / 'spike_times.npy', spike_times.astype(np.int64)) - np.save(path / 'spike_clusters.npy', CLUSTER_IDS[unit_index]) + np.save(path / 'spike_clusters.npy', cluster_ids[unit_index]) np.save(path / 'spike_templates.npy', templates_for_spike) np.save(path / 'amplitudes.npy', amplitudes) np.save(path / 'spike_depths.npy', depths) @@ -84,19 +85,21 @@ def _make_source(path, hours=HOURS): np.save(path / 'channel_map.npy', channel_map) np.save(path / 'channel_positions.npy', channel_positions) - templates = np.zeros((len(CLUSTER_IDS), 40, len(channel_map)), dtype=np.float32) + templates = np.zeros((len(cluster_ids), 40, len(channel_map)), dtype=np.float32) time = np.arange(40, dtype=np.float32) - for unit in range(len(CLUSTER_IDS)): - center = 13 + unit * 3 + for unit in range(len(cluster_ids)): + center = 13 + (unit % len(channel_map)) * 3 pulse = -np.exp(-0.5 * ((time - center) / 3.5) ** 2) * (35 + 8 * unit) for channel in range(len(channel_map)): - templates[unit, :, channel] = pulse * np.exp(-0.7 * abs(channel - unit)) + templates[unit, :, channel] = pulse * np.exp( + -0.7 * abs(channel - unit % len(channel_map)) + ) np.save(path / 'templates.npy', templates) pc_feature_ind = np.array( [ - [unit, (unit + 1) % len(channel_map), (unit + 2) % len(channel_map)] - for unit in range(len(CLUSTER_IDS)) + [unit % len(channel_map), (unit + 1) % len(channel_map), (unit + 2) % len(channel_map)] + for unit in range(len(cluster_ids)) ], dtype=np.int32, ) @@ -124,7 +127,9 @@ def _make_source(path, hours=HOURS): np.save(path / f'{stem}.waveforms.npy', waveforms) with (path / 'cluster_group.tsv').open('w', encoding='utf-8') as stream: - stream.write('cluster_id\tgroup\n0\tgood\n2\tgood\n7\tmua\n99\tgood\n') + stream.write('cluster_id\tgroup\n') + for unit in cluster_ids: + stream.write(f'{unit}\t{"mua" if unit == 7 else "good"}\n') (path / 'params.py').write_text( f'sample_rate = {SAMPLE_RATE}.0\n' f'num_samples = {samples}\n' @@ -181,12 +186,18 @@ def _capture_comparison(bounded, config_dir, output_dir, selected, dataset_label view = gui.get_view('UnitStabilityView') assert list(view.cluster_ids) == supervisor.selected assert len(view.cluster_ids) >= 2, 'Select at least two retained clusters.' + assert all(ax.get_legend() is None for ax in view.canvas.iter_ax()) _capture(gui, output_dir / 'after-overview.png') started = time.perf_counter() view.toggle_amplitude(False) view.toggle_depth(False) rate_only_seconds = time.perf_counter() - started _capture(gui, output_dir / 'after-rate-only.png') + camera = view.screenshot(dir=output_dir / 'camera') + shutil.copyfile(camera, output_dir / 'camera-rate-only.png') + native = float(np.diff(view.get_data(selected[0]).edges)[0]) + view.set_display_bin_seconds(2 * native) + _capture(gui, output_dir / 'after-rate-coarsened.png') supervisor.toggle_merge_mode() supervisor.block() assert supervisor.selection.state.is_merge_mode @@ -200,19 +211,28 @@ def _capture_comparison(bounded, config_dir, output_dir, selected, dataset_label ).strip(), 'clock_hours': manifest['num_samples'] / manifest['sample_rate'] / 3600, 'selected_cluster_ids': selected, - 'displayed_cluster_ids': list(map(int, view.cluster_ids[: view.display_limit])), + 'displayed_cluster_ids': list(map(int, view.displayed_ids)), 'merge_cluster_ids': supervisor.selected_merge, 'summary_bins': len(view.get_data(selected[0]).exposure), 'full_counts': { - str(unit): int(view.get_data(unit).counts.sum()) - for unit in view.cluster_ids[: view.display_limit] + str(unit): int(view.get_data(unit).counts.sum()) for unit in view.displayed_ids }, 'timing_seconds': { 'select_and_block': selection_seconds, 'rate_only_redraws': rate_only_seconds, }, 'gui_size': [gui.width(), gui.height()], - 'screenshots': ['after-overview.png', 'after-rate-only.png', 'after-merge.png'], + 'display_bins': len(view.get_display_data(selected[0]).exposure), + 'rate_line_width': view.rate_line_width, + 'display_limit': view.display_limit, + 'display_bin_seconds': view.display_bin_seconds, + 'screenshots': [ + 'after-overview.png', + 'after-rate-only.png', + 'after-merge.png', + 'after-rate-coarsened.png', + 'camera-rate-only.png', + ], 'source_arrays_modified': False, } (output_dir / 'capture.json').write_text(json.dumps(report, indent=2) + '\n') @@ -305,9 +325,13 @@ def main(): parser.add_argument('--cluster-ids', type=int, nargs='+', help='IDs for comparison captures.') parser.add_argument('--dataset-label', help='Dataset provenance label stored in capture.json.') parser.add_argument('--synthetic-hours', type=int, default=HOURS) + parser.add_argument('--synthetic-units', type=int, default=4) + parser.add_argument('--summary-bin-seconds', type=float, default=1800) args = parser.parse_args() if args.synthetic_hours < 4: parser.error('--synthetic-hours must be at least 4.') + if args.synthetic_units < 2: + parser.error('--synthetic-units must be at least 2.') if args.bounded_dir and not args.comparison: parser.error('--bounded-dir requires --comparison.') if args.bounded_dir: @@ -353,7 +377,9 @@ def main(): report_path.write_text(json.dumps(report, indent=2) + '\n') app.quit() return - params, intervals = _make_source(root / 'source', hours=args.synthetic_hours) + params, intervals = _make_source( + root / 'source', hours=args.synthetic_hours, unit_count=args.synthetic_units + ) bounded = prepare_large( params, root / 'bounded', @@ -365,14 +391,19 @@ def main(): stratum_seconds=3600, seed=0, batch_size=50_000, - bin_seconds=1800, + bin_seconds=args.summary_bin_seconds, ) if args.comparison: _capture_comparison( bounded, root / 'config', args.output_dir, - args.cluster_ids or list(map(int, CLUSTER_IDS[:3])), + args.cluster_ids + or ( + list(map(int, CLUSTER_IDS[:3])) + if args.synthetic_units == 4 + else list(range(min(12, args.synthetic_units))) + ), args.dataset_label or f'Synthetic {args.synthetic_hours}-hour fixture.', ) else: From 54c2f8b888c2f4203d0e30a64801c7a2c55d3578 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sun, 25 Oct 2026 07:52:07 +0100 Subject: [PATCH 50/53] Preserve parameter encodings and BOMs during replay --- phy/apps/large_recording/parameters.py | 8 +++++++- phy/apps/large_recording/replay.py | 8 ++++---- .../large_recording/tests/test_parameters.py | 20 ++++++++++++++++++- 3 files changed, 30 insertions(+), 6 deletions(-) diff --git a/phy/apps/large_recording/parameters.py b/phy/apps/large_recording/parameters.py index 82349c7e1..b76a300ca 100644 --- a/phy/apps/large_recording/parameters.py +++ b/phy/apps/large_recording/parameters.py @@ -109,5 +109,11 @@ def rewrite_replay_params(text, *, num_samples, valid_intervals, dat_path): newline = '\r\n' if '\r\n' in text else '\n' if prefix and not prefix.endswith(newline * 2): prefix += newline if prefix.endswith(newline) else newline * 2 - block = newline.join([BEGIN, *(f'{key} = {overrides[key]!r}' for key in KEYS), END, '']) + block = newline.join([BEGIN, *(f'{key} = {ascii(overrides[key])}' for key in KEYS), END, '']) return prefix + block + + +def rewrite_replay_params_bytes(contents, **overrides): + """Preserve a Python encoding cookie/BOM as well as original line endings.""" + encoding, _ = tokenize.detect_encoding(io.BytesIO(contents).readline) + return rewrite_replay_params(contents.decode(encoding), **overrides).encode(encoding) diff --git a/phy/apps/large_recording/replay.py b/phy/apps/large_recording/replay.py index f1a5fe6a2..ec6fdfda8 100644 --- a/phy/apps/large_recording/replay.py +++ b/phy/apps/large_recording/replay.py @@ -16,7 +16,7 @@ project_assignments, ) from .metadata import complete_schema, write_metadata -from .parameters import rewrite_replay_params +from .parameters import rewrite_replay_params_bytes from .source import PER_SPIKE, Source, _has_raw_paths, close_array, hash_file, publish_directory @@ -161,12 +161,12 @@ def _apply_curation(source, session, output_dir, batch_size): dat_path = resolved if isinstance(dat_path, (list, tuple)) else resolved[0] params_path = stage / 'params.py' params_path.write_bytes( - rewrite_replay_params( - params_path.read_bytes().decode('utf8'), + rewrite_replay_params_bytes( + params_path.read_bytes(), num_samples=source.num_samples, valid_intervals=source.valid_intervals.tolist(), dat_path=dat_path, - ).encode('utf8') + ) ) assignments = np.lib.format.open_memmap( stage / 'spike_clusters.npy', diff --git a/phy/apps/large_recording/tests/test_parameters.py b/phy/apps/large_recording/tests/test_parameters.py index 0addfeb2a..68db02648 100644 --- a/phy/apps/large_recording/tests/test_parameters.py +++ b/phy/apps/large_recording/tests/test_parameters.py @@ -4,7 +4,12 @@ import pytest -from phy.apps.large_recording.parameters import BEGIN, END, rewrite_replay_params +from phy.apps.large_recording.parameters import ( + BEGIN, + END, + rewrite_replay_params, + rewrite_replay_params_bytes, +) VALUES = {'num_samples': 20, 'valid_intervals': [[0, 8], [10, 20]], 'dat_path': None} @@ -90,6 +95,19 @@ def test_crlf_prefix_is_preserved_byte_for_byte(): assert rewrite_replay_params(result, **VALUES) == result +@pytest.mark.parametrize('encoding', ['utf-8-sig', 'cp1252']) +def test_python_encoding_and_bom_survive_with_unicode_generated_paths(encoding): + text = f'# coding: {encoding}\r\n# \u00e9lectrode\r\nnum_samples = 7\r\n' + original = text.encode(encoding) + values = dict(VALUES, dat_path='\u00e9lectrode/\u4e2d\u6587.bin') + result = rewrite_replay_params_bytes(original, **values) + assert result.startswith(original) + assert rewrite_replay_params_bytes(result, **values) == result + namespace = {} + exec(result, namespace) + assert namespace['dat_path'] == values['dat_path'] + + def test_three_replay_rounds_preserve_crlf_and_stable_file_size(tmp_path): from phy.apps.large_recording.curation import BoundedSession from phy.apps.large_recording.prepare import prepare_large From 7b452a327f90a7e5520b895d508d7f722c3bc301 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sun, 25 Oct 2026 08:02:37 +0100 Subject: [PATCH 51/53] Document metadata migration and all seven PDF acceptance checks --- design/unit-metadata-roundtrip-validation.md | 105 ++++++++++++++++ docs/changelog.md | 25 ++-- .../unit-metadata-refinements/carl-camera.png | Bin 0 -> 110117 bytes .../carl-coarsened-rate.png | Bin 0 -> 275151 bytes .../carl-native-rate.png | Bin 0 -> 296437 bytes .../synthetic-513h-coarsened.png | Bin 0 -> 269628 bytes .../synthetic-513h-native.png | Bin 0 -> 157713 bytes docs/long-recordings.md | 112 +++++++++++++++--- 8 files changed, 218 insertions(+), 24 deletions(-) create mode 100644 design/unit-metadata-roundtrip-validation.md create mode 100644 docs/images/unit-metadata-refinements/carl-camera.png create mode 100644 docs/images/unit-metadata-refinements/carl-coarsened-rate.png create mode 100644 docs/images/unit-metadata-refinements/carl-native-rate.png create mode 100644 docs/images/unit-metadata-refinements/synthetic-513h-coarsened.png create mode 100644 docs/images/unit-metadata-refinements/synthetic-513h-native.png diff --git a/design/unit-metadata-roundtrip-validation.md b/design/unit-metadata-roundtrip-validation.md new file mode 100644 index 000000000..735b1bf37 --- /dev/null +++ b/design/unit-metadata-roundtrip-validation.md @@ -0,0 +1,105 @@ +# Unit metadata and display feedback: seven-item acceptance + +This follow-up implements Carl's three-page **PR1428 - unit metadata across +curation rounds.pdf**, received 25 October 2026. Changes remain in PR #1428's +`feature/long-recording-curation` branch. No phylib or exporter change is needed. + +| PDF item | Behavior and evidence | +| --- | --- | +| 1. Source IDs and filenames | Schema descriptors preserve source basenames, CSV/TSV delimiters and column ordering. `cluster_si_unit_ids.tsv` remains plural with header `si_unit_id`; new merge/split IDs have blank scalar source IDs. Complete parent metadata is retained in history. | +| 2. Stale pipeline metrics/classifications | Membership-policy events clear imported fields and quality on new membership. Explicit new-unit labels survive unchanged rounds; prior decisions remain historical. GUI, journal, checkpoint and export use the same projection. | +| 3. Parameter-file growth | One final managed override block replaces itself; only recognizable old generated suffixes are removed. Original Python code, comments, CRLF, encoding cookies and BOMs survive. Raw-data sentinel strings normalize to Python `None`. | +| 4. Eight-unit cap | Default 32, saved nonnegative setting; zero shows all and any positive integer is accepted. Display IDs and cache capacity are independent; truncation never changes merge membership. | +| 5. Legend | Removed outright from every metric axis. Authoritative cluster/Merge colors are retained. | +| 6. Camera action | Unit Stability captures its actual Qt FigureCanvas, retaining the usual screenshot path/naming/return contract. Regression tests trigger the screenshot action and inspect the PNG. Real capture also calls that same view method. | +| 7. Rate readability | Default saved width 0.6 points. Dataset-local display bins default to native resolution and permit aligned coarsening. Counts/exposure and finite measurement sums/counts add before division; zero exposure remains unavailable and final short edges are retained. | + +## Metadata compatibility and policy + +Imported values remain unchanged for untouched units, including legacy empty +strings and typed JSON values. New producer values are blank even when parent +values agree. New memberships are unreviewed; an explicit `705 = good` applies +to unit 705 until it is transformed again. No producer SNR, classifier, or +violation metric is recomputed or copied from a preferred parent. + +Layout descriptors validate filenames, columns, duplicate fields and collisions. +Typed JSON/table disagreement fails with file, field and unit context. Read-only +source aliases may be symlinks; output writes refuse symlink targets. Legacy +omitted-null rows and Python scalar representations remain readable, and old +blank values retain their canonical revision hashes. + +Version-1 event meaning is preserved. `BoundedSession.migrate_metadata()` records +an explicit policy transition, recovering source names from the exact original +source identity and revision. Saving creates a new immutable generation without +changing the base manifest, assignments, allocation IDs or review ledger. It +clears ambiguous resolved values on active derived units while retaining explicit +label journal intent. Already exported values without their earlier journal +cannot establish curator intent; they remain imported values rather than being +retroactively called explicit decisions. The guide includes migration usage. + +## Real-data acceptance + +The fixture is Carl's earlier converted engineering test export, computation +`b1b0782a-b3ea-4f34-81d7-b3c6e36452b3`: 469,725,567 spikes, 705 original +units and a 112.859-hour elapsed clock. Its exposure declaration remains a test +conversion, not independently verified acquisition truth. Carl's newly mentioned +500-hour export was not available locally. + +Fresh outputs exercise: + +1. Accept `[40,44,48] -> 705` and `[49,50,51,53] -> 706` through the GUI + proposition workflow; assert producer fields and quality clear before explicit + good labels and a custom curator note are recorded. +2. Re-prepare, split 705 into 707/708 by a source-amplitude predicate, assert new + membership values clear, then explicitly label both children. +3. Re-prepare, merge 707/708 into 709, assert clearing again, then label 709. + +The independent Qt-free oracle checked every one of the 469,725,567 assignments +in **each round**, all unchanged source metadata cells, blank producer cells, +explicit group labels, and the two accepted review records. All 45 original +table filenames survive. The 91 remaining propositions remain pending. Params +are exactly **892 bytes in all three outputs**, with one managed block. +History grows from 5 to 8 to 11 records rather than losing parent decisions. + +The same oracle verified all **67 original download files** were unchanged and +**12 immutable files per output** matched the converted source. A separate copy +of the earlier reviewed bounded package was migrated: its manifest, assignments +and accepted reviews were unchanged; ambiguous producer values became blank and +explicit good labels on 705/706 survived. The data-only process exited zero. + +The combined GUI/data harness completed all assertions and printed PASS, then +exited 143 (SIGTERM). The signal's source is unknown; no traceback or verified +product termination path was found. This is retained as a combined-harness +limitation, not described as a clean process exit. Independent data verification, +the test suites, and both standalone capture processes exited normally. The +original independent checker also needed a harness-only fix to flatten column +cluster arrays before combining them with scalar amplitude masks; saved outputs +were unchanged and all rows were subsequently rechecked. + +## Display and regression checks + +Refreshed real captures use units 24, 26, 27 and 32, with no legend and 0.6-point +rate lines. The actual camera image is included in +`docs/images/unit-metadata-refinements/`. A generated **513-hour, twelve-unit** +fixture uses 6156 native five-minute bins and exact ten-minute display coarsening +to 3078 bins. It is synthetic stress coverage, not Carl's 500-hour data. + +Focused coverage includes metadata aliases/multi-column CSVs, typed values, +safe names and conflicts, blank legacy revisions, immutable old generation +reopen, migration identity, snapshot saves, policy event versions, provenance, +undo/redo, encoding/BOM/CRLF preservation, all display settings, actual camera +capture, cache limits, nonuniform-grid rejection, zero-exposure groups, merged +weighted means and final partial bins. + +Local verification ran `make test-full` (499 core + 431 application tests, one +existing benchmark skip), then the application target after two added symlink +regressions (433 passed). The final parameter/replay run passed 23 cases, +including two added encoding regressions. This covers 934 distinct current +tests; full CI runs the final tree together. Lint and format checks passed. +Documentation and wheel checks are recorded with the final handoff. + +Local reports/scripts are under +`/home/cyrille/GIT/IBL/phy-data/carl/aind-b1b0782a-b3ea-4f34-81d7-b3c6e36452b3/pdf-metadata-validation/`. +Captures are in sibling `pdf-refinements-screenshots` and +`pdf-refinements-synthetic-513h` directories. Arrays and credentials are not +repository artifacts. diff --git a/docs/changelog.md b/docs/changelog.md index 52ecc51c7..bcfa5dddf 100644 --- a/docs/changelog.md +++ b/docs/changelog.md @@ -25,13 +25,24 @@ behavior they verify rather than listed separately. - Added Unit Stability, precise window-relative amplitude/feature inspection, sampled interval/correlogram views, and explicit full-versus-evidence counts. Standard datasets retain their existing curation workflow and default layout. -- Unit Stability now overlays up to eight selected units with consistent colors - and a legend. Its saved **Show firing rate**, **Show amplitude**, and - **Show depth** view-menu toggles default on; turning all three off leaves the - plot empty. The cap is reported in view status and does not affect merge - membership. Full-source rates use acquisition exposure, and amplitude splits - mark only affected children’s metrics as pending. On ordinary recordings, - firing rates identify their continuous-acquisition assumption. +- Unit Stability overlays up to 32 selected units by default, with consistent + colors and no legend. Its saved display limit accepts zero to show all selected + units, without a hard positive upper limit. Saved view settings include the + positive rate-line width (0.6 points by default) and the **Show firing rate**, + **Show amplitude**, and **Show depth** toggles, which default on. Its + dataset-local display-bin setting defaults to native resolution and permits + exact coarsening by integer multiples of the native bin width. The screenshot + action captures the Matplotlib Qt canvas. Full-source rates use acquisition + exposure, and amplitude splits mark only affected children’s metrics as + pending. On ordinary recordings, firing rates identify their + continuous-acquisition assumption. +- Bounded replay preserves producer metadata table filenames, delimiters, and + column layouts. New merge and split memberships clear producer values and + source IDs; quality labels are membership-scoped and start unreviewed until + assigned. Legacy journals retain inherited-metadata behavior until explicitly + migrated with the bounded session `migrate_metadata()` API. Replay parameter + overrides are kept in one managed final block while original source code + remains intact. - Bounded saves use validated atomic generations and reject conflicting saves from stale sessions. 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z$RcYpTroi6*J{>K?$BW-htv;W=Ly*;kFY~FR%lSLUJn}1V@Y1 z>EU5`#fFCy>H>VpOV<=C1G+Vx$R9_1eiZr@%%d_snioGcH1L#V2Ns?}%00 zR*z0ZKoY*Vx6NT}NwpuS)fk0m3SWwr+aH1OT>}07*}Jyg(81olv(CpYtZ{K}PeNwj zcGAZmk5NVHg0>D6hsO)0KRGd$NKxzS1;3OzrITvEVIEWQ5cfgo#Zm^Zh%iIu_@$7Sc*%Cnwb8)d+*&m@9Cw_Ch2l9hr_yuWR2wwOr92>JB zO#fGd*xyGymGZCn>c7L>!Vz7|)DhI}#kI13g)N!l{}mgsFpfBA%!qG|Lb=p aF3K@6so~8n+b9Bcyq3D|?P9e@ul@r&=1Up? literal 0 HcmV?d00001 diff --git a/docs/long-recordings.md b/docs/long-recordings.md index 1a409ab8d..566fd386a 100644 --- a/docs/long-recordings.md +++ b/docs/long-recordings.md @@ -41,7 +41,9 @@ process RSS; waveform source, retained, and omitted counts are reported in the CLI and manifest. The screenshots below show the bounded GUI views using a deterministic -synthetic eight-hour sorting. The overview plots full-duration rates and +synthetic eight-hour sorting. These captures document the interface before +the latest Unit Stability display refinements; their unit cap and legend are +historical. The overview plots full-duration rates and available source means; gray marks the synthetic acquisition gap and cyan marks the retained evidence windows. The evidence view places windowed amplitudes at top left, sampled ISI at top right, sampled correlograms at middle right, and @@ -77,7 +79,10 @@ Turning off **Show amplitude** and **Show depth** expands the rate comparison: ![Rate-only comparison of units 40, 44 and 48](images/unit-stability-comparison/after-rate-only.png) -The same colors and cluster IDs follow the staged Merge candidates: +These captures predate the current Unit Stability display refinements; the +overlaid rates remain representative, while any legend or unit-display limit +visible in them is historical. The same colors and cluster IDs follow the staged +Merge candidates: ![Merge View candidates match the firing-rate curves](images/unit-stability-comparison/after-merge.png) @@ -98,6 +103,31 @@ test data, not Carl's 500-hour recording. Reproduce it with `--comparison --synthetic-hours 500 --output-dir /tmp/stability-500h` instead of `--bounded-dir` and `--cluster-ids`. +### Latest display refinements + +The following captures show the current controls on Carl's earlier converted +112.9-hour test export, with units **24, 26, 27, and 32**. The camera image was +saved through Unit Stability's own screenshot action. Legends are removed and +native rate lines use the new 0.6-point default. Declared exposure remains the +conversion's test mask, not independent acquisition verification. + +![Camera capture with no legend and thin rate lines](images/unit-metadata-refinements/carl-camera.png) + +A separate generated 513-hour fixture displays twelve selected units with +6156 native five-minute bins. Selecting ten-minute display bins groups these +into 3078 bins by adding counts/exposure and measurement sums/counts; prepared +files remain unchanged. This is generated test data, not Carl's 500-hour export. + +| Native five-minute bins | Ten-minute display bins | +| --- | --- | +| ![Twelve synthetic units at native resolution](images/unit-metadata-refinements/synthetic-513h-native.png) | ![The same units with exact display coarsening](images/unit-metadata-refinements/synthetic-513h-coarsened.png) | + +Reproduce the generated stress captures with `--comparison --synthetic-hours +513 --synthetic-units 12 --summary-bin-seconds 300 --output-dir +/tmp/stability-513h`. The capture script also exercises the view's camera action +and writes `camera-rate-only.png`. Display coarsening starts at the native +prepared resolution; it never changes preparation's default bin size. + ## Prepare bounded evidence Run `prepare-large` with the source `params.py` and a new output directory: @@ -158,10 +188,48 @@ byte budgets describe package bytes, not resident memory. Waveform availability can exceed the bounded output budget: preparation reports waveform counts retained, omitted, and available in the source on the CLI, and stores the counts in the manifest so truncation is visible. -Producer-supplied per-unit metrics and annotations remain inherited metadata; -Phy does not recalculate those values for merged or split units. Use the -full-count, rate, amplitude-mean, and depth-mean summaries produced by this -workflow for the measurements they explicitly cover. +Producer metadata tables retain their source filenames, delimiters, and column +order, including multi-column CSV files. For a new merge or split membership, +producer values and source-unit IDs are blank; imported custom fields are also +cleared. Quality labels belong to the current unit +membership: a new membership starts unreviewed until explicitly labeled. +Untouched memberships keep their labels, and label history remains in the +curation journal. Existing legacy journals keep their inherited-metadata +behavior until explicitly migrated with the bounded session's +`migrate_metadata()` API. This migration preserves label intent while adopting +membership-scoped metadata. Use the full-count, rate, amplitude-mean, and +depth-mean summaries for the measurements they explicitly cover; producer +metrics are not recomputed during merge or split. + +For an already saved legacy bounded session, close the GUI and explicitly +migrate before applying its curation. Supply the original producer params if +the source has moved; this also recovers its original metadata filenames: + +```python +from phy.apps.large_recording.curation import BoundedSession + +session = BoundedSession('/data/recording-bounded') +try: + session.migrate_metadata('/data/original-recording/params.py') + session.save() +finally: + session.close() +``` + +Migration publishes a new save generation and retains the older generations, +assignments, review decisions, and explicit label events. A legacy session +remains readable under its old rules until migrated. Already exported values +alone cannot reveal whether a label was inherited or explicitly assigned; keep +the original source and saved bounded journal to recover that distinction. +The same applies to metadata filenames already changed by an older export. +Conflicting JSON/table metadata is reported with the filename, field, and unit; +reconcile the input representations rather than relying on silent precedence. + +Replay keeps source parameter code intact and maintains one final marked block +for its `num_samples`, `valid_intervals`, and `dat_path` overrides. Original +assignments can remain in the file because they may be used by other user +expressions; the managed block, rather than every declaration in the file, is +the stable replay override. ## Review and curate @@ -179,15 +247,24 @@ shows time-binned counts/rates, available source scalar-amplitude means, evidence windows, and acquisition gaps. Missing measurements and units without evidence remain visible as unavailable. -Unit Stability can overlay up to eight selected clusters. Multiple-cluster -overlays use consistent colors and include a legend; the eight-cluster cap is -reported in the view status and does not alter cluster selection or merge -membership. Use the Unit Stability view menu's **Show firing rate**, -**Show amplitude**, and **Show depth** toggles to choose the plotted -measurements. These choices are saved across sessions and require no export or -re-preparation. All three are on by default; turning all three off leaves the -view empty. The full-source counts and rates use acquisition exposure, including -declared gaps. Source amplitude and depth summaries appear only when available. +Unit Stability overlays up to 32 selected clusters by default for responsiveness, +using the same +colors as the cluster and Merge views and no legend. The view menu's display +limit can be changed; zero displays all selected units, with no hard positive +upper limit. A nonzero limit affects only the displayed curves, not cluster +selection or merge membership. Use the **Show firing rate**, **Show amplitude**, +and **Show depth** toggles to choose plotted measurements. These choices are +saved across sessions; all three are on by default, and turning all three off +leaves the view empty. The default rate-line width is 0.6 points; its positive +width setting is saved with the view. The display-bin setting is local to the +dataset: zero uses the prepared native bins (or the view's native bins on an +ordinary recording), while a coarser bin groups adjacent bins by adding counts +and exposure, and additive trend summaries, exactly. It accepts only integer +multiples of the native bin width, so it cannot display finer bins. The default +is native resolution, preserving the prepared bin size (for example, 300 or +3600 seconds). The screenshot action captures the Matplotlib Qt canvas. The +full-source counts and rates use acquisition exposure, including declared gaps; +source amplitude and depth summaries appear only when available. Evidence Amplitude shows raw source scalar amplitudes from the currently selected evidence window. The Feature view also uses window-relative seconds. @@ -233,8 +310,9 @@ It evaluates selected units and bins their loaded spikes over the recording duration. Its firing rate assumes continuous acquisition because ordinary datasets do not supply valid acquisition intervals to the view; the plot labels that assumption. The Unit Stability view menu's **Show firing rate**, -**Show amplitude**, and **Show depth** toggles are saved across sessions, with -all three on by default. The ordinary default view layout remains unchanged. +**Show amplitude**, and **Show depth** toggles and rate-line width are saved +across sessions, with all three toggles on by default. The display-bin setting +is dataset-local. The ordinary default view layout remains unchanged. Use the bounded manifest workflow above when known acquisition gaps must be represented explicitly. From d260c09ca3efab4505b195b81bfb3eccd68879d6 Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sun, 25 Oct 2026 08:05:09 +0100 Subject: [PATCH 52/53] Record final package verification and portable symlink regressions --- design/unit-metadata-roundtrip-validation.md | 6 ++++++ phy/apps/large_recording/tests/test_metadata.py | 13 +++++++++++-- 2 files changed, 17 insertions(+), 2 deletions(-) diff --git a/design/unit-metadata-roundtrip-validation.md b/design/unit-metadata-roundtrip-validation.md index 735b1bf37..aad6ba30e 100644 --- a/design/unit-metadata-roundtrip-validation.md +++ b/design/unit-metadata-roundtrip-validation.md @@ -98,6 +98,12 @@ including two added encoding regressions. This covers 934 distinct current tests; full CI runs the final tree together. Lint and format checks passed. Documentation and wheel checks are recorded with the final handoff. +`make doc-check` and `uv build` passed. The built wheel contains both new +runtime modules (`metadata.py` and `parameters.py`) with bytes matching the +working source. All refreshed image files were visually inspected. Source +symlink regressions skip only the specific Windows missing-privilege condition; +they run normally on systems supporting symlink creation. + Local reports/scripts are under `/home/cyrille/GIT/IBL/phy-data/carl/aind-b1b0782a-b3ea-4f34-81d7-b3c6e36452b3/pdf-metadata-validation/`. Captures are in sibling `pdf-refinements-screenshots` and diff --git a/phy/apps/large_recording/tests/test_metadata.py b/phy/apps/large_recording/tests/test_metadata.py index 55d61c26d..29e562615 100644 --- a/phy/apps/large_recording/tests/test_metadata.py +++ b/phy/apps/large_recording/tests/test_metadata.py @@ -429,7 +429,7 @@ def test_readonly_source_symlink_preserves_table_alias_and_target(tmp_path): producer = tmp_path / 'immutable-producer-si.tsv' producer.write_text('cluster_id\tsi_unit_id\n0\t40\n1\t44\n2\t48\n99\t99\n') alias = params.parent / 'cluster_si_unit_ids.tsv' - alias.symlink_to(producer) + _symlink_or_skip(alias, producer) original_hash = hash_file(producer) with Source(params) as source: assert source.metadata['si_unit_id'][0] == '40' @@ -452,7 +452,7 @@ def test_metadata_output_refuses_existing_symlink_without_mutating_target(tmp_pa producer.write_text('immutable producer data') destination = tmp_path / 'out' destination.mkdir() - (destination / 'cluster_si_unit_ids.tsv').symlink_to(producer) + _symlink_or_skip(destination / 'cluster_si_unit_ids.tsv', producer) schema = { 'version': 1, 'tables': [ @@ -467,3 +467,12 @@ def test_metadata_output_refuses_existing_symlink_without_mutating_target(tmp_pa with pytest.raises(ValueError, match='output must not overwrite a symbolic link'): write_metadata(destination, {'si_unit_id': {0: '40'}}, schema) assert hash_file(producer) == original_hash + + +def _symlink_or_skip(path, target): + try: + path.symlink_to(target) + except OSError as error: + if getattr(error, 'winerror', None) == 1314: + pytest.skip('This Windows account has no symbolic-link privilege.') + raise From ab8d7887f8e12dcd0edd8fd9738e8370db261c6f Mon Sep 17 00:00:00 2001 From: Cyrille Rossant Date: Sun, 25 Oct 2026 08:14:12 +0100 Subject: [PATCH 53/53] Accept unchanged legacy structured labels while preserving typed conflicts --- design/unit-metadata-roundtrip-validation.md | 4 ++-- phy/apps/large_recording/metadata.py | 19 ++++++++++++++++++- .../large_recording/tests/test_metadata.py | 18 ++++++++++++++++++ 3 files changed, 38 insertions(+), 3 deletions(-) diff --git a/design/unit-metadata-roundtrip-validation.md b/design/unit-metadata-roundtrip-validation.md index aad6ba30e..140d25256 100644 --- a/design/unit-metadata-roundtrip-validation.md +++ b/design/unit-metadata-roundtrip-validation.md @@ -94,8 +94,8 @@ weighted means and final partial bins. Local verification ran `make test-full` (499 core + 431 application tests, one existing benchmark skip), then the application target after two added symlink regressions (433 passed). The final parameter/replay run passed 23 cases, -including two added encoding regressions. This covers 934 distinct current -tests; full CI runs the final tree together. Lint and format checks passed. +including two added encoding regressions. The final metadata run passed 24 cases, including two added structured-label +serialization regressions. This covers 936 distinct current tests; full CI runs the final tree together. Lint and format checks passed. Documentation and wheel checks are recorded with the final handoff. `make doc-check` and `uv build` passed. The built wheel contains both new diff --git a/phy/apps/large_recording/metadata.py b/phy/apps/large_recording/metadata.py index 7b6a6bb26..446a3e018 100644 --- a/phy/apps/large_recording/metadata.py +++ b/phy/apps/large_recording/metadata.py @@ -1,5 +1,6 @@ """Lossless producer table layout and typed canonical unit metadata.""" +import ast import csv import json from pathlib import Path @@ -21,6 +22,22 @@ def cell(value): return str(value) +def _legacy_cell_matches(text, value): + if text == str(value): + return True + if not isinstance(value, (dict, list)): + return False + try: + # Old csv.writer used Python repr, while the JSON sidecar sorted keys + # and converted tuples to lists. Compare JSON meaning without exec or + # Python's bool/int equality conflating true with 1. + candidate = json.loads(json.dumps(ast.literal_eval(text), allow_nan=False)) + options = {'sort_keys': True, 'separators': (',', ':'), 'allow_nan': False} + return json.dumps(candidate, **options) == json.dumps(value, **options) + except (SyntaxError, TypeError, ValueError): + return False + + def validate_schema(schema): if ( not isinstance(schema, dict) @@ -157,7 +174,7 @@ def read_metadata(path): declared is None and unit in left and unit in right - and left[unit] == str(right[unit]) + and _legacy_cell_matches(left[unit], right[unit]) ): continue # Legacy csv.writer used Python representations for typed values. if unit not in left or unit not in right or cell(left[unit]) != cell(right[unit]): diff --git a/phy/apps/large_recording/tests/test_metadata.py b/phy/apps/large_recording/tests/test_metadata.py index 29e562615..6ded32f26 100644 --- a/phy/apps/large_recording/tests/test_metadata.py +++ b/phy/apps/large_recording/tests/test_metadata.py @@ -476,3 +476,21 @@ def _symlink_or_skip(path, target): if getattr(error, 'winerror', None) == 1314: pytest.skip('This Windows account has no symbolic-link privilege.') raise + + +@pytest.mark.parametrize('value', [{'z': (1, 2), 'a': True}, [{'z': 2, 'a': True}]]) +def test_legacy_structured_label_key_order_and_tuple_json_equivalence(tmp_path, value): + metadata = {'details': {0: value}} + table = tmp_path / 'cluster_details.tsv' + with table.open('w', newline='') as stream: + writer = csv.writer(stream, delimiter='\t') + writer.writerow(['cluster_id', 'details']) + writer.writerow([0, value]) + sidecar = tmp_path / '_phy_cluster_metadata.json' + sidecar.write_text(json.dumps(metadata, sort_keys=True)) + actual, _ = read_metadata(tmp_path) + assert actual['details'][0] == json.loads(json.dumps(value)) + # A changed boolean is a real conflict, not legacy serialization variance. + table.write_text(table.read_text().replace('True', '1')) + with pytest.raises(ValueError, match='field details, unit 0'): + read_metadata(tmp_path)

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