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Merge pull request #104 from catalystneuro/leifer
Add 001075 example figure
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name: leifer_notebooks_created_8_29_2024 | ||
channels: | ||
- defaults | ||
dependencies: | ||
- bzip2=1.0.8=h2bbff1b_6 | ||
- ca-certificates=2024.7.2=haa95532_0 | ||
- expat=2.6.2=hd77b12b_0 | ||
- libffi=3.4.4=hd77b12b_1 | ||
- openssl=3.0.14=h827c3e9_0 | ||
- pip=24.2=py312haa95532_0 | ||
- python=3.12.4=h14ffc60_1 | ||
- setuptools=72.1.0=py312haa95532_0 | ||
- sqlite=3.45.3=h2bbff1b_0 | ||
- tk=8.6.14=h0416ee5_0 | ||
- vc=14.40=h2eaa2aa_0 | ||
- vs2015_runtime=14.40.33807=h98bb1dd_0 | ||
- wheel=0.43.0=py312haa95532_0 | ||
- xz=5.4.6=h8cc25b3_1 | ||
- zlib=1.2.13=h8cc25b3_1 | ||
- pip: | ||
- aiobotocore==2.14.0 | ||
- aiohappyeyeballs==2.4.0 | ||
- aiohttp==3.10.5 | ||
- aioitertools==0.11.0 | ||
- aiosignal==1.3.1 | ||
- annotated-types==0.7.0 | ||
- anyio==4.4.0 | ||
- argon2-cffi==23.1.0 | ||
- argon2-cffi-bindings==21.2.0 | ||
- arrow==1.3.0 | ||
- asciitree==0.3.3 | ||
- asttokens==2.4.1 | ||
- async-lru==2.0.4 | ||
- attrs==24.2.0 | ||
- babel==2.16.0 | ||
- beautifulsoup4==4.12.3 | ||
- bidsschematools==0.7.2 | ||
- bleach==6.1.0 | ||
- botocore==1.35.7 | ||
- certifi==2024.8.30 | ||
- cffi==1.17.0 | ||
- charset-normalizer==3.3.2 | ||
- ci-info==0.3.0 | ||
- click==8.1.7 | ||
- click-didyoumean==0.3.1 | ||
- colorama==0.4.6 | ||
- comm==0.2.2 | ||
- contourpy==1.3.0 | ||
- cycler==0.12.1 | ||
- dandi==0.63.1 | ||
- dandischema==0.10.3 | ||
- debugpy==1.8.5 | ||
- decorator==5.1.1 | ||
- defusedxml==0.7.1 | ||
- dnspython==2.6.1 | ||
- email-validator==2.2.0 | ||
- etelemetry==0.3.1 | ||
- executing==2.0.1 | ||
- fasteners==0.19 | ||
- fastjsonschema==2.20.0 | ||
- fonttools==4.53.1 | ||
- fqdn==1.5.1 | ||
- frozenlist==1.4.1 | ||
- fscacher==0.4.1 | ||
- fsspec==2024.6.1 | ||
- h11==0.14.0 | ||
- h5py==3.11.0 | ||
- hdmf==3.14.3 | ||
- hdmf-zarr==0.8.0 | ||
- httpcore==1.0.5 | ||
- httpx==0.27.2 | ||
- humanize==4.10.0 | ||
- idna==3.8 | ||
- interleave==0.2.1 | ||
- ipykernel==6.29.5 | ||
- ipython==8.26.0 | ||
- ipywidgets==8.1.5 | ||
- isodate==0.6.1 | ||
- isoduration==20.11.0 | ||
- jaraco-classes==3.4.0 | ||
- jaraco-context==6.0.1 | ||
- jaraco-functools==4.0.2 | ||
- jedi==0.19.1 | ||
- jinja2==3.1.4 | ||
- jmespath==1.0.1 | ||
- joblib==1.4.2 | ||
- json5==0.9.25 | ||
- jsonpointer==3.0.0 | ||
- jsonschema==4.23.0 | ||
- jsonschema-specifications==2023.12.1 | ||
- jupyter==1.1.0 | ||
- jupyter-client==8.6.2 | ||
- jupyter-console==6.6.3 | ||
- jupyter-core==5.7.2 | ||
- jupyter-events==0.10.0 | ||
- jupyter-lsp==2.2.5 | ||
- jupyter-server==2.14.2 | ||
- jupyter-server-terminals==0.5.3 | ||
- jupyterlab==4.2.5 | ||
- jupyterlab-pygments==0.3.0 | ||
- jupyterlab-server==2.27.3 | ||
- jupyterlab-widgets==3.0.13 | ||
- keyring==25.3.0 | ||
- keyrings-alt==5.0.2 | ||
- kiwisolver==1.4.5 | ||
- markupsafe==2.1.5 | ||
- matplotlib==3.9.2 | ||
- matplotlib-inline==0.1.7 | ||
- mistune==3.0.2 | ||
- more-itertools==10.4.0 | ||
- multidict==6.0.5 | ||
- natsort==8.4.0 | ||
- nbclient==0.10.0 | ||
- nbconvert==7.16.4 | ||
- nbformat==5.10.4 | ||
- nest-asyncio==1.6.0 | ||
- notebook==7.2.2 | ||
- notebook-shim==0.2.4 | ||
- numcodecs==0.13.0 | ||
- numpy==1.26.4 | ||
- nwbinspector==0.5.1 | ||
- overrides==7.7.0 | ||
- packaging==24.1 | ||
- pandas==2.2.2 | ||
- pandocfilters==1.5.1 | ||
- parso==0.8.4 | ||
- pillow==10.4.0 | ||
- platformdirs==4.2.2 | ||
- prometheus-client==0.20.0 | ||
- prompt-toolkit==3.0.47 | ||
- psutil==6.0.0 | ||
- pure-eval==0.2.3 | ||
- pycparser==2.22 | ||
- pycryptodomex==3.20.0 | ||
- pydantic==2.8.2 | ||
- pydantic-core==2.20.1 | ||
- pygments==2.18.0 | ||
- pynwb==2.8.1 | ||
- pyout==0.7.3 | ||
- pyparsing==3.1.4 | ||
- python-dateutil==2.9.0.post0 | ||
- python-json-logger==2.0.7 | ||
- pytz==2024.1 | ||
- pywin32==306 | ||
- pywin32-ctypes==0.2.3 | ||
- pywinpty==2.0.13 | ||
- pyyaml==6.0.2 | ||
- pyzmq==26.2.0 | ||
- referencing==0.35.1 | ||
- remfile==0.1.13 | ||
- requests==2.32.3 | ||
- rfc3339-validator==0.1.4 | ||
- rfc3986-validator==0.1.1 | ||
- rfc3987==1.3.8 | ||
- rpds-py==0.20.0 | ||
- ruamel-yaml==0.18.6 | ||
- ruamel-yaml-clib==0.2.8 | ||
- s3fs==2024.6.1 | ||
- scipy==1.14.1 | ||
- semantic-version==2.10.0 | ||
- send2trash==1.8.3 | ||
- six==1.16.0 | ||
- sniffio==1.3.1 | ||
- soupsieve==2.6 | ||
- stack-data==0.6.3 | ||
- tenacity==9.0.0 | ||
- terminado==0.18.1 | ||
- threadpoolctl==3.5.0 | ||
- tinycss2==1.3.0 | ||
- tornado==6.4.1 | ||
- tqdm==4.66.5 | ||
- traitlets==5.14.3 | ||
- types-python-dateutil==2.9.0.20240821 | ||
- typing-extensions==4.12.2 | ||
- tzdata==2024.1 | ||
- uri-template==1.3.0 | ||
- urllib3==2.2.2 | ||
- wcwidth==0.2.13 | ||
- webcolors==24.8.0 | ||
- webencodings==0.5.1 | ||
- websocket-client==1.8.0 | ||
- widgetsnbextension==4.0.13 | ||
- wrapt==1.16.0 | ||
- yarl==1.9.4 | ||
- zarr==2.18.2 | ||
- zarr-checksum==0.4.2 | ||
prefix: C:\Users\theac\anaconda3\envs\leifer_notebooks_created_8_29_2024 |
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# 001075 - Neural signal propagation atlas of Caenorhabditis elegans | ||
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## How to cite | ||
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Randi, Francesco; Sharma, Anuj; Dvali, Sophie; Leifer, Andrew M. (2024) Neural signal propagation atlas of Caenorhabditis elegans (Version 0.240930.1859) [Data set]. DANDI archive. https://doi.org/10.48324/dandi.001075/0.240930.1859 | ||
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## Setup | ||
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Install [Conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html) on your machine. | ||
Install `git` and clone the example notebook repository: | ||
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```bash | ||
conda install git | ||
git clone https://github.com/dandi/example-notebooks.git | ||
``` | ||
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Then create a specific environment for this notebook using: | ||
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```bash | ||
conda env create --file example-notebooks/001075/001075_notebook_environment.yml | ||
``` | ||
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Then activate the environment: | ||
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```bash | ||
conda activate leifer_notebooks_created_8_29_2024 | ||
``` | ||
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Finally, start Jupyter: | ||
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```bash | ||
jupyter notebook | ||
``` | ||
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And select the notebook `001075_paper_figure_1d.ipynb` from the file explorer in the browser. | ||
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If interested in creating your own plots, refer to the code in `utils_001075` for how to handle the data streams. | ||
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Note that all timing information is aligned to the NeuroPAL imaging system. | ||
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## Help | ||
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- Dataset: https://dandiarchive.org/dandiset/001075/0.240930.1859 | ||
- Original publication: [Neural signal propagation atlas of Caenorhabditis elegans](https://www.nature.com/articles/s41586-023-06683-4) | ||
- [Visualize (Neurosift)](https://neurosift.app/?p=/dandiset&dandisetId=001075&dandisetVersion=0.240930.1859) | ||
- Note: the files are split by 'imaging' (raw) and 'segmentation' (processed). To view both, select a combined | ||
view for the same session: [example](https://neurosift.app/?p=/nwb&url=https://api.dandiarchive.org/api/assets/5feda038-0c84-494a-a0e0-c3ef8ec194d1/download/&url=https://api.dandiarchive.org/api/assets/40a6799b-4835-4170-89bb-9a866082e503/download/&dandisetId=001075&dandisetVersion=draft). | ||
- [NWB file basics](https://pynwb.readthedocs.io/en/stable/tutorials/general/plot_file.html#sphx-glr-tutorials-general-plot-file-py) | ||
- [How to read NWB files](https://pynwb.readthedocs.io/en/stable/tutorials/general/scratch.html#sphx-glr-tutorials-general-scratch-py) | ||
- [Data analysis with NWB files](https://pynwb.readthedocs.io/en/stable/tutorials/general/scratch.html#sphx-glr-tutorials-general-scratch-py) |
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from ._waterfall import plot_waterfall | ||
from ._stream_nwbfile import stream_nwbfile | ||
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__all__ = ["plot_waterfall", "stream_nwbfile"] |
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from typing import Literal | ||
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import dandi.dandiapi | ||
import h5py | ||
import pynwb | ||
import remfile | ||
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def stream_nwbfile(subject_id: str, session_id: str, session_type: Literal["imaging", "segmentation"]) -> pynwb.NWBFile: | ||
dandiset_id = "001075" | ||
dandifile_path = f"sub-{subject_id}/sub-{subject_id}_ses-{session_id}_desc-{session_type}_ophys+ogen.nwb" | ||
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dandi_client = dandi.dandiapi.DandiAPIClient() | ||
dandiset = dandi_client.get_dandiset(dandiset_id=dandiset_id) | ||
dandifile = dandiset.get_asset_by_path(path=dandifile_path) | ||
s3_url = dandifile.get_content_url() | ||
byte_stream = remfile.File(url=s3_url) | ||
file = h5py.File(name=byte_stream) | ||
io = pynwb.NWBHDF5IO(file=file) | ||
nwbfile = io.read() | ||
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return nwbfile |
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