CalSciPy 0.8.3

CalSciPy

CalSciPy is a utility toolbox for calcium imaging experiments. It contains a variety of useful features, from interactive visualization of data to computer-generated holography for "read/write" experiments, and everything in-between. Essentially, it's a collection of code written for my imaging experiments that might be considered useful to others. I was inspired to upload my own code to solve some of the issues outlined in the motivation section of the docs or at least create a neat package my friends and I could use to easily analyze data across various environments and computers.

Active Development

As of version 0.9.8, the current implementation is unstable, partially untested, partially finished, and should be considered an open alpha/beta. Please be patient, refactoring my code for public use is a pet-project. I have to graduate at some point and I have a newborn.

Until things are more stable, I'll explicitly note which subpackages are stable, have >90% test coverage, and are ready-to-use.

Stable & Tested Modules

• The main module is ready to use as of 0.7.5. New features will be demarcated by a label indicating the version added in the docs.

Experimental

• The organization module is untested but incorporated into the distributed pypi version
• The bruker module is untested but incorporated into the distributed pypi version
• The optogenetics module is untested but incorporated into the distributed pypi version

Unstable

• The interactive module is unstable but partially incorporated into the distributed pypi version
• The optics module is unstable and not incorporated into the distributed pypi version

Installation

Eventually I will break things up into sub-packages so you don't have to install everything together...
pip install CalSciPy

Roadmap

My current focus is on refactoring tools for holographic optogenetics and circumventing PrairieView's writing of data to proprietary RAW format. I also plan on breaking up this repo because its many of its contents are too decoupled (e.g., bruker prairieview tricks / helpers vs experiment organization)

Contributions

Save me from myself, contributions welcome :)

Documentation

Hosted at ReadtheDocs. Available locally as HTML, LATEX and PDF.