aind-smartspim-classification

Code for classifying the cell candidate outputs from aind-smartspim-segmentation within the smartspim pipeline. It uses the aind-large-scale-prediction package to efficiently process large amounts of image data. This repository takes as input the cell proposals that will be classified by the CellFinder model. The output is a CSV with the following columns:

• Cell Counts: Number of positive cells.
• Cell Likelihood Mean: Mean of the probabilities of a cell being a cell.
• Cell Likelihood STD: Standard deviation of the probability of a cell being a cell.
• Noncell Counts: Number of negative cells.
• Noncell Likelihood Mean: Mean of the probabilities of negative cells.
• Noncell Likelihood STD; Standard deviation of the probabilities of negative cells.

Installation

To use the software, in the root directory, run

pip install -e .

To develop the code, 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 unittest discover && 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

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.