Archive paper Figures 2–4 and S3–S6 for private review
Browse files- README.md +63 -0
- RIGHTS.md +3 -0
- archive_index.json +62 -0
- archives/S3.tar.gz +3 -0
- archives/S4.tar.gz +3 -0
- archives/S5.tar.gz +3 -0
- archives/S6.tar.gz +3 -0
- archives/figure2.tar.gz +3 -0
- archives/figure3.tar.gz +3 -0
- archives/figure4.tar.gz +3 -0
- extract_data.py +52 -0
- figure_map.csv +8 -0
- main_figure_plot_inputs.json +193 -0
- manifests/S3.jsonl +4 -0
- manifests/S4.jsonl +249 -0
- manifests/S5.jsonl +103 -0
- manifests/S6.jsonl +0 -0
- manifests/figure2.jsonl +0 -0
- manifests/figure3.jsonl +0 -0
- manifests/figure4.jsonl +0 -0
- source_aliases.jsonl +0 -0
- validation.json +51 -0
README.md
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| 1 |
+
---
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| 2 |
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language:
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- en
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tags:
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- neuroscience
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- reinforcement-learning
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- drosophila
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- simulation
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pretty_name: FlyControl paper records — Figures 2–4 and S3–S6
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---
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# FlyControl — paper data and provenance
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This is a private, author-review snapshot for **A Drosophila connectome prior enables adaptable embodied control**. It covers Figure 2, Figure 3, Figure 4, and Supplementary Figures S3–S6 from the final manuscript supplied on 2026-11-02. Figure 5 and Figure 6 are outside this snapshot.
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The manuscript identity is SHA-256 `cb7dac9a2c20305f6228c98766d7d0f361ce59c058e1e13b88bee59d38152a30`. The manuscript itself is not distributed here. The corresponding code is [FlyControl](https://github.com/THU-NeuroML/FlyControl/tree/1a49c33bf1e6eab17cb2953123e02ecc2549a5f4), revision `1a49c33bf1e6eab17cb2953123e02ecc2549a5f4`.
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Seven figure-specific archives contain numerical source tables, included episode results and traces, mechanism-analysis records, exact derived graphs, effective protocols, and the visual source assets needed by the main-figure panels. Large collections of small files are bundled without changing their contents. Checkpoints and loading instructions are in [FlyControl-models](https://huggingface.co/UncleStrawberryBear/FlyControl-models).
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| Paper item | Evidence / task | Checkpoint files |
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|---|---|---:|
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| Figure 2 | Terrain; Adult, MLP and ER, 20 seeds each | 60 |
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| Figure 3 | Turning; Adult/MLP, 24 seeds each, plus 24 Adult initial states | 72 |
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| Figure 4 | Speed; Adult/MLP, 20 seeds each | 40 |
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| S3 | Developmental direction; Adult/Larva, 6 seeds each | 12 |
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| S4 | Developmental speed; Adult/Larva, 6 seeds each | 12 |
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| S5 | BANC descending/motor readouts, 6 seeds each, initial and final | 24 |
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| S6 | BANC regional recovery, 3 seeds per readout | 6 |
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`archive_index.json` records each archive's size, SHA-256 and member count. `manifests/<figure>.jsonl` records every extracted path, size, SHA-256 and original local source. `figure_map.csv` maps the final paper numbering to historical directories: final S5/S6 correspond to historical `s06`/`s07`. No standalone S1/S2 archive is included in this requested snapshot.
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## Contents and statistical units
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- Figures 2–4 retain the plot inputs, episode/seed tables, full comparison-family summaries, perturbation grids and selected mechanism histories. Figure 2 also includes the final corrected axis/surface and ER comparison tables. Figure 3 preserves the broader registered comparison data while checkpoint coverage is restricted to the plotted Adult/MLP cohort and the necessary initial Adult states.
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- S3 contains direction episodes and the full 22-comparison seed-level inference family, including the jointly corrected terrain endpoints. These supplemental policies are distinct from the main Figure 3 cohort.
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- S4 contains the full speed endpoint/seed tables and all 240 stored step/sine traces used by the displayed developmental analyses. Other rows in the endpoint table can reference historical trajectories outside this selected trace subset; `plot_trace_manifest.csv` enumerates the included traces.
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- S5 contains before/after BANC class sensitivity, per-window/per-state records, neuron annotations, and the 32 exact observed common histories. It does not require publishing all policies that originally generated those histories.
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- S6 contains all 1,890 analyzed stable recovery branch traces, 54 matched branch snapshots, unpushed neural references, the probe records, regional masks/edge fractions, and recorded quality-control summaries. The six recovery policies are supplied in the model repository.
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Training seed identifies the policy-level unit; evaluation seed identifies a repeated rollout or reset. Do not treat repeated trajectories as independent trained models. Preserve failure flags, partial durations and missing windows. Original raw and multiplicity-adjusted statistics are retained; use the stated family rather than recomputing correction over only significant/displayed rows.
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Column names retain the original units: `_s` seconds, `_mm` millimetres, `_mm_s` millimetres per second, `_rad` radians, `_deg` degrees, and `_hz` hertz. Statistics tables may contain an explicit `unit` field that takes precedence. Blank/NaN fields can mean unavailable or inapplicable measurements and must not be replaced by zero. NPZ contents and protocol JSON files retain the original task-specific variable names; this is a research archive, not a uniform supervised-learning table.
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## Download and extract
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```python
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| 46 |
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from huggingface_hub import snapshot_download
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data = snapshot_download(
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| 48 |
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'UncleStrawberryBear/FlyControl-data', repo_type='dataset',
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| 49 |
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allow_patterns=['README.md', 'archive_index.json', 'manifests/figure2.jsonl',
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| 50 |
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'archives/figure2.tar.gz', 'extract_data.py'])
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| 51 |
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```
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```bash
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| 54 |
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python /path/to/data-snapshot/extract_data.py --figure figure2 --output ./paper-data
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| 55 |
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```
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The extractor verifies the archive and every member checksum, rejects unsafe members, and preserves the recorded relative layout. Multiple figure archives can be extracted into the same directory. See `data/figure2/source_data`, `data/figure3/source_data`, and `data/figure4/source_data` for main-figure source tables. Supplemental locations appear in `figure_map.csv`; additional raw S5/S6 records live under `research/outputs/nmi_unified/`.
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Historical absolute paths inside original CSV/JSON records are provenance, not required machine locations. Use manifest paths after extraction; match trajectories or models by their SHA-256 identities. `source_aliases.jsonl` maps additional known original supplementary paths to included archive members. `plot_trace_manifest.csv` supplies the portable S4 trace paths. A historical path to an omitted exploratory run does not imply that run belongs in this snapshot.
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The archives retain exact FlyWire/Larva/BANC derived inputs; the upstream version manifests under `external_inputs/` identify their public sources. Use BANC release 626, as verified by the code's reproduction notes, rather than inferring a release from historical folder names. See `RIGHTS.md`.
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This is a private archival upload. Hash and coverage checks do not constitute a new full simulator reproduction of the paper. No DOI or public-release claim is made.
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RIGHTS.md
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This snapshot is private and is prepared for author review. A public redistribution license for the authors' research data and weights has not yet been selected; the code repository's Apache-2.0 license does not automatically apply to these files.
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Derived connectome material retains the upstream FlyWire FAFB v783, larval Drosophila, and BANC v626 attribution and terms. Exact upstream input manifests are included under `external_inputs/` in the data archives. FlyGym/NeuroMechFly assets and numerical engines retain their upstream attribution; see the pinned code repository's THIRD_PARTY_NOTICES.md. This snapshot does not relicense upstream material.
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archive_index.json
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{
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| 2 |
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"scope": [
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| 3 |
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"figure2",
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| 4 |
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"figure3",
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| 5 |
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"figure4",
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| 6 |
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"S3",
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| 7 |
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"S4",
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| 8 |
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"S5",
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| 9 |
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"S6"
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| 10 |
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],
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| 11 |
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"archives": [
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| 12 |
+
{
|
| 13 |
+
"paper_item": "figure2",
|
| 14 |
+
"path": "archives/figure2.tar.gz",
|
| 15 |
+
"bytes": 2383654154,
|
| 16 |
+
"sha256": "df2fef83bdfeb5f2bfe1e5d0becda6f2c61ad5293fc194fa713a4e81d217512a",
|
| 17 |
+
"members": 26823
|
| 18 |
+
},
|
| 19 |
+
{
|
| 20 |
+
"paper_item": "figure3",
|
| 21 |
+
"path": "archives/figure3.tar.gz",
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| 22 |
+
"bytes": 1218275395,
|
| 23 |
+
"sha256": "95c520d5f0c03829d0060a895f88304a2e5495f98044f9dc70b2807234732e68",
|
| 24 |
+
"members": 18233
|
| 25 |
+
},
|
| 26 |
+
{
|
| 27 |
+
"paper_item": "figure4",
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| 28 |
+
"path": "archives/figure4.tar.gz",
|
| 29 |
+
"bytes": 552260900,
|
| 30 |
+
"sha256": "47130a992a76ebbbabf9803c7e3c2904000656ed3dec6f14d10defa0b1e41b58",
|
| 31 |
+
"members": 1608
|
| 32 |
+
},
|
| 33 |
+
{
|
| 34 |
+
"paper_item": "S3",
|
| 35 |
+
"path": "archives/S3.tar.gz",
|
| 36 |
+
"bytes": 89798,
|
| 37 |
+
"sha256": "9817eebfa4259cde2e4b4d3557b4d1e45a67f0995d58d1117984268fc50408a2",
|
| 38 |
+
"members": 4
|
| 39 |
+
},
|
| 40 |
+
{
|
| 41 |
+
"paper_item": "S4",
|
| 42 |
+
"path": "archives/S4.tar.gz",
|
| 43 |
+
"bytes": 17260654,
|
| 44 |
+
"sha256": "65c45efc93c175ec95a644a07ae2a6b2078868fe6e300eb4454f4c9b0da8fc12",
|
| 45 |
+
"members": 249
|
| 46 |
+
},
|
| 47 |
+
{
|
| 48 |
+
"paper_item": "S5",
|
| 49 |
+
"path": "archives/S5.tar.gz",
|
| 50 |
+
"bytes": 124029882,
|
| 51 |
+
"sha256": "e4def942d533b7922993b6b0a92e9c47447e175bdb2d584c05d69d80d14d075c",
|
| 52 |
+
"members": 103
|
| 53 |
+
},
|
| 54 |
+
{
|
| 55 |
+
"paper_item": "S6",
|
| 56 |
+
"path": "archives/S6.tar.gz",
|
| 57 |
+
"bytes": 3406429927,
|
| 58 |
+
"sha256": "7717995396c90d3da544aa0c510a46b918a8846ed834c006e2b06147ce6d8ab0",
|
| 59 |
+
"members": 2092
|
| 60 |
+
}
|
| 61 |
+
]
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| 62 |
+
}
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archives/S3.tar.gz
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+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9817eebfa4259cde2e4b4d3557b4d1e45a67f0995d58d1117984268fc50408a2
|
| 3 |
+
size 89798
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archives/S4.tar.gz
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| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:65c45efc93c175ec95a644a07ae2a6b2078868fe6e300eb4454f4c9b0da8fc12
|
| 3 |
+
size 17260654
|
archives/S5.tar.gz
ADDED
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@@ -0,0 +1,3 @@
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e4def942d533b7922993b6b0a92e9c47447e175bdb2d584c05d69d80d14d075c
|
| 3 |
+
size 124029882
|
archives/S6.tar.gz
ADDED
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@@ -0,0 +1,3 @@
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7717995396c90d3da544aa0c510a46b918a8846ed834c006e2b06147ce6d8ab0
|
| 3 |
+
size 3406429927
|
archives/figure2.tar.gz
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:df2fef83bdfeb5f2bfe1e5d0becda6f2c61ad5293fc194fa713a4e81d217512a
|
| 3 |
+
size 2383654154
|
archives/figure3.tar.gz
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:95c520d5f0c03829d0060a895f88304a2e5495f98044f9dc70b2807234732e68
|
| 3 |
+
size 1218275395
|
archives/figure4.tar.gz
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@@ -0,0 +1,3 @@
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| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:47130a992a76ebbbabf9803c7e3c2904000656ed3dec6f14d10defa0b1e41b58
|
| 3 |
+
size 552260900
|
extract_data.py
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| 1 |
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"""Verify and extract an individual FlyControl figure archive."""
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| 2 |
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import argparse, hashlib, json, tarfile
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| 3 |
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from pathlib import Path
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| 4 |
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| 5 |
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def sha(path):
|
| 6 |
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h=hashlib.sha256()
|
| 7 |
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with Path(path).open('rb') as f:
|
| 8 |
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for block in iter(lambda:f.read(8*1024*1024),b''):h.update(block)
|
| 9 |
+
return h.hexdigest()
|
| 10 |
+
|
| 11 |
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def extract(figure, root, output):
|
| 12 |
+
root,output=Path(root).resolve(),Path(output).resolve()
|
| 13 |
+
index=json.loads((root/'archive_index.json').read_text())['archives']
|
| 14 |
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item=next(x for x in index if x['paper_item']==figure)
|
| 15 |
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archive=root/item['path']
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| 16 |
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assert archive.stat().st_size==item['bytes'] and sha(archive)==item['sha256'], 'Archive integrity failure'
|
| 17 |
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manifest={x['path']:x for x in map(json.loads,(root/'manifests'/f'{figure}.jsonl').open())}
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| 18 |
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assert len(manifest)==item['members']
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| 19 |
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output.mkdir(parents=True,exist_ok=True)
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| 20 |
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seen=set()
|
| 21 |
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with tarfile.open(archive,'r|gz') as tar:
|
| 22 |
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for member in tar:
|
| 23 |
+
if not member.isfile() or member.name not in manifest or member.name in seen:
|
| 24 |
+
raise ValueError('Unexpected archive member: '+member.name)
|
| 25 |
+
dest=(output/member.name).resolve()
|
| 26 |
+
if not dest.is_relative_to(output):raise ValueError('Unsafe member path')
|
| 27 |
+
expected=manifest[member.name]
|
| 28 |
+
assert member.size==expected['bytes']
|
| 29 |
+
dest.parent.mkdir(parents=True,exist_ok=True)
|
| 30 |
+
if dest.exists():
|
| 31 |
+
assert dest.stat().st_size==expected['bytes'] and sha(dest)==expected['sha256'], str(dest)
|
| 32 |
+
else:
|
| 33 |
+
stream=tar.extractfile(member)
|
| 34 |
+
hasher=hashlib.sha256()
|
| 35 |
+
try:
|
| 36 |
+
with dest.open('xb') as f:
|
| 37 |
+
for block in iter(lambda:stream.read(8*1024*1024),b''):
|
| 38 |
+
f.write(block);hasher.update(block)
|
| 39 |
+
assert hasher.hexdigest()==expected['sha256'], str(dest)
|
| 40 |
+
except BaseException:
|
| 41 |
+
dest.unlink(missing_ok=True)
|
| 42 |
+
raise
|
| 43 |
+
seen.add(member.name)
|
| 44 |
+
assert seen==set(manifest)
|
| 45 |
+
print(json.dumps(dict(figure=figure,members=len(seen),verified=True,output=str(output))))
|
| 46 |
+
|
| 47 |
+
if __name__=='__main__':
|
| 48 |
+
p=argparse.ArgumentParser(description=__doc__)
|
| 49 |
+
p.add_argument('--figure',required=True)
|
| 50 |
+
p.add_argument('--dataset-dir',default=str(Path(__file__).parent))
|
| 51 |
+
p.add_argument('--output',required=True)
|
| 52 |
+
a=p.parse_args();extract(a.figure,a.dataset_dir,a.output)
|
figure_map.csv
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
paper_item,data_archive,model_id_prefix,checkpoint_files,historical_data_location
|
| 2 |
+
figure2,archives/figure2.tar.gz,figure2/,60,data/figure2
|
| 3 |
+
figure3,archives/figure3.tar.gz,figure3/,72,data/figure3
|
| 4 |
+
figure4,archives/figure4.tar.gz,figure4/,40,data/figure4
|
| 5 |
+
S3,archives/S3.tar.gz,S3/,12,data/supplementary/development
|
| 6 |
+
S4,archives/S4.tar.gz,S4/,12,data/supplementary/development
|
| 7 |
+
S5,archives/S5.tar.gz,S5/,24,data/supplementary/s06
|
| 8 |
+
S6,archives/S6.tar.gz,S6/,6,data/supplementary/s07
|
main_figure_plot_inputs.json
ADDED
|
@@ -0,0 +1,193 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"2": {
|
| 3 |
+
"direct_plot_inputs": [
|
| 4 |
+
"assets/figure2/block_scene.png",
|
| 5 |
+
"assets/figure2/demo/frames/connectome_0.17.png",
|
| 6 |
+
"assets/figure2/demo/frames/connectome_0.33.png",
|
| 7 |
+
"assets/figure2/demo/frames/connectome_0.50.png",
|
| 8 |
+
"assets/figure2/demo/frames/connectome_1.20.png",
|
| 9 |
+
"assets/figure2/demo/frames/mlp_0.17.png",
|
| 10 |
+
"assets/figure2/demo/frames/mlp_0.33.png",
|
| 11 |
+
"assets/figure2/demo/frames/mlp_0.50.png",
|
| 12 |
+
"assets/figure2/demo/frames/mlp_1.20.png",
|
| 13 |
+
"data/figure2/source_data/ADDITIONAL_SEEDS.csv",
|
| 14 |
+
"data/figure2/source_data/ALL_ENDPOINT_STATISTICS.csv",
|
| 15 |
+
"data/figure2/source_data/BEHAVIOR_SEEDS.csv",
|
| 16 |
+
"data/figure2/source_data/BEHAVIOR_STATISTICS.csv",
|
| 17 |
+
"data/figure2/source_data/CIRCUIT_MEANS.csv",
|
| 18 |
+
"data/figure2/source_data/CIRCUIT_STATISTICS.csv",
|
| 19 |
+
"data/figure2/source_data/DEMO_FRAME_INDEX.csv",
|
| 20 |
+
"data/figure2/source_data/DEMO_TRAJECTORY.csv",
|
| 21 |
+
"data/figure2/source_data/DENSE_SURFACE_MEANS.csv",
|
| 22 |
+
"data/figure2/source_data/DENSE_TIME_STATISTICS.csv",
|
| 23 |
+
"data/figure2/source_data/EARLY_ATLAS_MEANS.csv",
|
| 24 |
+
"data/figure2/source_data/MATCHED_ER_ATLAS_MEANS.csv"
|
| 25 |
+
],
|
| 26 |
+
"panel_map": [
|
| 27 |
+
[
|
| 28 |
+
"a",
|
| 29 |
+
"`assets/figure2/block_scene.png`",
|
| 30 |
+
"原模拟场景示意"
|
| 31 |
+
],
|
| 32 |
+
[
|
| 33 |
+
"b–d",
|
| 34 |
+
"`BEHAVIOR_SEEDS.csv`、`ADDITIONAL_SEEDS.csv`、对应完整统计族",
|
| 35 |
+
"`data/figure2/evaluation/`；`fig2.current.behavior`、`trace_metrics`"
|
| 36 |
+
],
|
| 37 |
+
[
|
| 38 |
+
"e",
|
| 39 |
+
"`EARLY_ATLAS_MEANS.csv`、`MATCHED_ER_ATLAS_MEANS.csv`",
|
| 40 |
+
"`mechanisms/interventions/` 与 `mechanisms/er_atlas/`；`circuit_probe`、`er_probe`、汇总模块"
|
| 41 |
+
],
|
| 42 |
+
[
|
| 43 |
+
"f",
|
| 44 |
+
"`DENSE_TIME_STATISTICS.csv`",
|
| 45 |
+
"`mechanisms/dense_neurons/`；`dense_future` 与 `temporal`"
|
| 46 |
+
],
|
| 47 |
+
[
|
| 48 |
+
"g",
|
| 49 |
+
"`CIRCUIT_MEANS.csv`、`CIRCUIT_STATISTICS.csv`",
|
| 50 |
+
"每种子阻断剂量、随机匹配掩码；`circuit_probe` 与 `circuit`"
|
| 51 |
+
],
|
| 52 |
+
[
|
| 53 |
+
"h",
|
| 54 |
+
"`DEMO_FRAME_INDEX.csv`、`DEMO_TRAJECTORY.csv` 和八张原生帧",
|
| 55 |
+
"`assets/figure2/demo/SELECTION.json`；`render_demo`"
|
| 56 |
+
],
|
| 57 |
+
[
|
| 58 |
+
"i",
|
| 59 |
+
"`DENSE_SURFACE_MEANS.csv`",
|
| 60 |
+
"每模型完整 21 × 21 × 5 高度测量；`input_gain`"
|
| 61 |
+
]
|
| 62 |
+
]
|
| 63 |
+
},
|
| 64 |
+
"3": {
|
| 65 |
+
"direct_plot_inputs": [
|
| 66 |
+
"assets/figure3/demo/contrast_plus60/connectome_+60_0.3.png",
|
| 67 |
+
"assets/figure3/demo/contrast_plus60/connectome_+60_0.9.png",
|
| 68 |
+
"assets/figure3/demo/contrast_plus60/connectome_+60_1.6.png",
|
| 69 |
+
"assets/figure3/demo/contrast_plus60/connectome_+60_2.0.png",
|
| 70 |
+
"assets/figure3/demo/contrast_plus60/mlp_+60_0.3.png",
|
| 71 |
+
"assets/figure3/demo/contrast_plus60/mlp_+60_0.9.png",
|
| 72 |
+
"assets/figure3/demo/contrast_plus60/mlp_+60_1.6.png",
|
| 73 |
+
"assets/figure3/demo/contrast_plus60/mlp_+60_2.0.png",
|
| 74 |
+
"assets/figure3/left_000.png",
|
| 75 |
+
"data/figure3/source_data/activity_unforced_lesion_episodes.csv",
|
| 76 |
+
"data/figure3/source_data/cpg_input_gain_surfaces.npz",
|
| 77 |
+
"data/figure3/source_data/demo_plus60_contrast_trajectories.csv",
|
| 78 |
+
"data/figure3/source_data/enrichment_group_inventory.csv",
|
| 79 |
+
"data/figure3/source_data/enrichment_local_connectome_summary.npz",
|
| 80 |
+
"data/figure3/source_data/full_turn_activity_seed_values.csv",
|
| 81 |
+
"data/figure3/source_data/interface_primary_paired_tests_all9classes.csv",
|
| 82 |
+
"data/figure3/source_data/interface_primary_seed_pairs.csv",
|
| 83 |
+
"data/figure3/source_data/registered_statistics_all_families.csv",
|
| 84 |
+
"data/figure3/source_data/turn_seed_angle_means.csv",
|
| 85 |
+
"data/figure3/source_data/turn_seed_means.csv",
|
| 86 |
+
"data/figure3/source_data/verified_lesion_statistics.csv",
|
| 87 |
+
"data/figure3/source_data/verified_specificity_statistics.csv"
|
| 88 |
+
],
|
| 89 |
+
"panel_map": [
|
| 90 |
+
[
|
| 91 |
+
"a",
|
| 92 |
+
"原生场景帧",
|
| 93 |
+
"`assets/figure3/left_000.png`"
|
| 94 |
+
],
|
| 95 |
+
[
|
| 96 |
+
"b/c",
|
| 97 |
+
"`turn_seed_means.csv`、`registered_statistics_all_families.csv`",
|
| 98 |
+
"`fig3.behavior`；`raw/evaluation/`"
|
| 99 |
+
],
|
| 100 |
+
[
|
| 101 |
+
"d",
|
| 102 |
+
"原始转向方向与每种子终末误差",
|
| 103 |
+
"`fig3.directional`；全部左右转向原始记录"
|
| 104 |
+
],
|
| 105 |
+
[
|
| 106 |
+
"e",
|
| 107 |
+
"`enrichment_local_connectome_summary.npz`",
|
| 108 |
+
"`mechanisms/sensitivity/`；原生稀疏反向传播内核"
|
| 109 |
+
],
|
| 110 |
+
[
|
| 111 |
+
"f",
|
| 112 |
+
"`interface_primary_seed_pairs.csv`、18 项配对比较表",
|
| 113 |
+
"`mechanisms/interface/`；初始／最终输入投影和读出四种交换"
|
| 114 |
+
],
|
| 115 |
+
[
|
| 116 |
+
"g",
|
| 117 |
+
"`full_turn_activity_seed_values.csv`",
|
| 118 |
+
"`mechanisms/activity/`；先合并原始能量再计算富集，不能平均已算好的比值"
|
| 119 |
+
],
|
| 120 |
+
[
|
| 121 |
+
"h",
|
| 122 |
+
"未受外力的全部 1,056 条通路干预记录",
|
| 123 |
+
"`mechanisms/interventions/closed_loop/`；全部十项干预和原四项特异性比较族"
|
| 124 |
+
],
|
| 125 |
+
[
|
| 126 |
+
"i",
|
| 127 |
+
"`demo_plus60_contrast_trajectories.csv`、八张帧",
|
| 128 |
+
"原始 +60° 转向示例；候选选择审计随数据保存"
|
| 129 |
+
],
|
| 130 |
+
[
|
| 131 |
+
"j",
|
| 132 |
+
"`cpg_input_gain_surfaces.npz`",
|
| 133 |
+
"`mechanisms/input_gain/`；48 个模型 × 21 × 21 实测网格"
|
| 134 |
+
]
|
| 135 |
+
]
|
| 136 |
+
},
|
| 137 |
+
"4": {
|
| 138 |
+
"direct_plot_inputs": [
|
| 139 |
+
"assets/figure4/demo/MEDIA_PROVENANCE.json",
|
| 140 |
+
"assets/figure4/demo/speed_modulation.mp4",
|
| 141 |
+
"assets/figure4/simulator_original.png",
|
| 142 |
+
"data/figure4/source_data/demo_speed_trace.csv",
|
| 143 |
+
"data/figure4/source_data/latest_event_class_ablation_seed.csv",
|
| 144 |
+
"data/figure4/source_data/latest_neuron_class_seed_times.csv",
|
| 145 |
+
"data/figure4/source_data/latest_parameter_landscapes.npz",
|
| 146 |
+
"data/figure4/source_data/main_flatness_mean_grids.npz",
|
| 147 |
+
"data/figure4/source_data/scatter_MODEL_MECHANISM_SUMMARY.csv",
|
| 148 |
+
"data/figure4/source_data/scatter_performance_associations.csv",
|
| 149 |
+
"data/figure4/source_data/short_budget_primary_fixed_budget.csv",
|
| 150 |
+
"data/figure4/source_data/short_budget_seed_metrics.csv",
|
| 151 |
+
"data/figure4/source_data/v20_acceleration_heatmap.csv",
|
| 152 |
+
"data/figure4/source_data/v24_ramp_increment_summary.csv"
|
| 153 |
+
],
|
| 154 |
+
"panel_map": [
|
| 155 |
+
[
|
| 156 |
+
"a",
|
| 157 |
+
"`assets/figure4/simulator_original.png`"
|
| 158 |
+
],
|
| 159 |
+
[
|
| 160 |
+
"b",
|
| 161 |
+
"`short_budget_seed_metrics.csv`；完整三项固定预算终点校正"
|
| 162 |
+
],
|
| 163 |
+
[
|
| 164 |
+
"c",
|
| 165 |
+
"`v24_ramp_increment_summary.csv`；原始速度轨迹、固定基线和 0.1 s 窗口"
|
| 166 |
+
],
|
| 167 |
+
[
|
| 168 |
+
"d",
|
| 169 |
+
"`latest_neuron_class_seed_times.csv`；`neurons/` 的模型时域灵敏度"
|
| 170 |
+
],
|
| 171 |
+
[
|
| 172 |
+
"e",
|
| 173 |
+
"`v20_acceleration_heatmap.csv`；`signed_replays/` 的有符号响应"
|
| 174 |
+
],
|
| 175 |
+
[
|
| 176 |
+
"f",
|
| 177 |
+
"`latest_event_class_ablation_seed.csv`；`events/` 中完整目标保持／通道干预响应"
|
| 178 |
+
],
|
| 179 |
+
[
|
| 180 |
+
"g",
|
| 181 |
+
"`scatter_MODEL_MECHANISM_SUMMARY.csv`、`scatter_performance_associations.csv`；`probes/`、行为记录和原始模型投影；保留全部 45 项关联"
|
| 182 |
+
],
|
| 183 |
+
[
|
| 184 |
+
"h",
|
| 185 |
+
"`demo_speed_trace.csv`、原生视频及逐帧选择信息；显示平滑规则与来源保留"
|
| 186 |
+
],
|
| 187 |
+
[
|
| 188 |
+
"i",
|
| 189 |
+
"`latest_parameter_landscapes.npz`；`probes/` 中 40 个模型的 21 × 21 参数扰动面"
|
| 190 |
+
]
|
| 191 |
+
]
|
| 192 |
+
}
|
| 193 |
+
}
|
manifests/S3.jsonl
ADDED
|
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{"path": "data/supplementary/development/direction_episodes.csv", "bytes": 479961, "sha256": "7c827e08d9f7dc43a00c98ce43bd3b60fcc661bafb974d8c8e7df52410559e71", "source": "/data2/ysy/github/fly-locomotion/data/supplementary/development/direction_episodes.csv"}
|
| 2 |
+
{"path": "data/supplementary/development/inference_22_contrasts.csv", "bytes": 5094, "sha256": "de1dba8d81ef21a692d419934b6231999cc8057e8c62305ba5eaf06436adbf9f", "source": "/data2/ysy/github/fly-locomotion/data/supplementary/development/inference_22_contrasts.csv"}
|
| 3 |
+
{"path": "data/supplementary/development/inference_seed_values.csv", "bytes": 13166, "sha256": "cc0aa5535b86d20be31a7a9e051cbcd0612dfa0492c5e2ebc57eff06fce2dc55", "source": "/data2/ysy/github/fly-locomotion/data/supplementary/development/inference_seed_values.csv"}
|
| 4 |
+
{"path": "external_inputs/larva.json", "bytes": 726, "sha256": "883da0b77e8da092ea9f22d6254489ec26d456707b176414cd2432f10719d4e0", "source": "/data2/ysy/github/FlyControl/configs/inputs/larva.json"}
|
manifests/S4.jsonl
ADDED
|
@@ -0,0 +1,249 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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| 1 |
+
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| 21 |
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| 23 |
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| 24 |
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| 27 |
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| 28 |
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| 29 |
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| 30 |
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| 31 |
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| 32 |
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| 34 |
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| 35 |
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| 38 |
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| 40 |
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| 41 |
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{"path": "data/supplementary/s06/atlas_group_inventory.csv", "bytes": 15078, "sha256": "6637f91138033991783dc47f8f53aabc6446d37ac7c845b9fd694b27f9cd07e1", "source": "/data2/ysy/github/fly-locomotion/data/supplementary/s06/atlas_group_inventory.csv"}
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{"path": "data/supplementary/s06/history_manifest.json", "bytes": 14617, "sha256": "4de5f714158a425ddb6cb3b719eab8664ccc50252ec71e4c246dda75a1651b46", "source": "/data2/ysy/github/fly-locomotion/data/supplementary/s06/history_manifest.json"}
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{"path": "data/supplementary/s06/numerical_checks.csv.gz", "bytes": 4579, "sha256": "4bc4f61e4fb6ba1399d777e0c57cf5910a336b6df4aad2578826b057b1b90d9c", "source": "/data2/ysy/github/fly-locomotion/data/supplementary/s06/numerical_checks.csv.gz"}
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{"path": "data/supplementary/s06/window_manifest.csv", "bytes": 19998, "sha256": "7b98a0e768d43222f4b602aca0ad16e927e28cfa733827315802388b403467f2", "source": "/data2/ysy/github/fly-locomotion/data/supplementary/s06/window_manifest.csv"}
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