Generated from aind-library-template
Project description
Welcome to aind-ophys-utils
Python utility library for processing calcium imaging (optical physiology) data. All interfaces are array-based (NumPy / h5py) with no project-specific data structures, making the modules easy to integrate into any pipeline.
Modules
| Module | Description |
|---|---|
baseline_fitting |
Robust parametric baseline fitting: M-estimator norms (Tukey biweight variants), IRLS nonlinear fitting with JAX autodiff, robust LOWESS smoother, and a high-level fit_baseline orchestrator that chains bleach-trend fitting with local fluctuation estimation. |
dff |
ΔF/F computation from fluorescence traces. Inactive-frame masking baseline, parallelised across ROIs, with a plot_dff helper for QA visualisation. |
signal_utils |
Signal processing primitives: running percentile filter, nanmedian filter, robust noise standard deviation (MAD / FFT / Welch), and a fast noise estimator using GPU-accelerated FFTs via PyTorch. |
summary_images |
GPU-accelerated summary images for calcium imaging movies: mean, max-correlation (Cn), and peak-to-noise ratio (PNR). |
array_utils |
Array downsampling and subsampling utilities with flexible strategies (mean, max, median, first, last, mid) and optional NaN-skipping. |
video_utils |
H5 video downsampling and VP9 video encoding via imageio-ffmpeg. |
motion_border_utils |
Compute motion borders from frame-shift correction outputs. |
Installation
pip install aind-ophys-utils
GPU / CPU note.
aind-ophys-utilsdepends on PyTorch, which pulls in CUDA libraries by default from PyPI (~2 GB). To install a CPU-only build instead, install PyTorch first using the official CPU index, then install this package:pip install torch --index-url https://download.pytorch.org/whl/cpu pip install aind-ophys-utilsAlternatively, pass
--extra-index-urlin a single command:pip install aind-ophys-utils --extra-index-url https://download.pytorch.org/whl/cpu
To use the software from source, clone the repository and in the root directory run
pip install -e .
To develop the code in place, run
pip install -e .[dev]
Contributing
Linters and testing
There are several libraries used to run linters, check documentation, and run tests.
- Please test your changes using the coverage library, which will run the tests and log a coverage report:
coverage run -m pytest && coverage report
- Use interrogate to check that modules, methods, etc. have been documented thoroughly:
interrogate .
- Use flake8 to check that code is up to standards (no unused imports, etc.):
flake8 .
- Use black to automatically format the code into PEP standards:
black .
- Use isort to automatically sort import statements:
isort .
Pull requests
For internal members, please create a branch. For external members, please fork the repository and open a pull request from the fork. We'll primarily use Angular style for commit messages. Roughly, they should follow the pattern:
<type>(<scope>): <short summary>
where scope (optional) describes the packages affected by the code changes and type (mandatory) is one of:
- build: Changes that affect build tools or external dependencies (example scopes: pyproject.toml, setup.py)
- ci: Changes to our CI configuration files and scripts (examples: .github/workflows/ci.yml)
- docs: Documentation only changes
- feat: A new feature
- fix: A bugfix
- perf: A code change that improves performance
- refactor: A code change that neither fixes a bug nor adds a feature
- test: Adding missing tests or correcting existing tests
Semantic Release
The table below, from semantic release, shows which commit message gets you which release type when semantic-release runs (using the default configuration):
| Commit message | Release type |
|---|---|
fix(pencil): stop graphite breaking when too much pressure applied |
|
feat(pencil): add 'graphiteWidth' option |
|
perf(pencil): remove graphiteWidth optionBREAKING CHANGE: The graphiteWidth option has been removed.The default graphite width of 10mm is always used for performance reasons. |
(Note that the BREAKING CHANGE: token must be in the footer of the commit) |
Documentation
To generate the rst files source files for documentation, run
sphinx-apidoc -o doc_template/source/ src
Then to create the documentation HTML files, run
sphinx-build -b html doc_template/source/ doc_template/build/html
More info on sphinx installation can be found here.
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