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.

Motivation

While working on my Ph.D. I noticed I was constantly re-writing boilerplate, “one-liners” and copying/pasting more-extensive code between environments. Ever try to use a minimally-documented function written during an exploratory analysis on a different operating system two years later? How much time have you spent debugging hardcoded variables after adapting functions from one study to the next? During some lunchtime reflection, I realized that a lot of my colleagues were simultaneously writing (and re-writing) very similar code to mine. How much time have scientists spent reinventing the wheel? Why did each of us write our own GUI for interacting looking at traces? And why do they all rely unstandardized, idiosyncratic organizations of datasets. I decided to spend a little extra time thoroughly documenting and testing to put together this package so at least my friends and I could easily analyze data across various environments, interpreters and operating systems. While having all your code so well documented and tested takes more time–I found it does wonders for your stress levels (documenting is a relaxing monotonous activity) and people like you more. Plus, all the abstraction and documentation makes your analysis easy to read and follow. As my programming skills and scientific expertise have grown, I’ve started to roadmap the inclusion of some more complex functionality–refactoring my existing code of interest, writing code for my projects with future distribution in mind, and implementing new features the science community could benefit from–because making scientific software open-source and proliferating expertise is simply the right thing to do.

Highlights

• Useful, well-documented functions often used in boilerplate code alongside registration and roi extraction software packages such as Caiman, SIMA, and Suite2P.

• Flexible & extensible system for neatly organizing data, timestamping analysis, & single-step analyses.

• Quality-of-life utilities for Bruker’s PrairieView software

• Interactive data visualization

• Tools for optics & optogenetics