Skip to main content

A collection

Project description

CalSciPy

GitHub license Maintenance Documentation Status PyPi

This python packages contains a variety of useful methods for handling, processing, and visualizing calcium imaging data. It's intended to be a collection of useful, well-documented functions often used in boilerplate code alongside software packages such as Caiman, SIMA, and Suite2P.

Highlights

  • Assign unique colormaps to subsets of ROIs to generate rich, informative videos
  • Perona-Malik diffusion for edge-preserving denoising
  • Methods for handling Bruker's PrairieView data
  • Interactive visualization

Installation

pip install CalSciPy or pip install CalSciPy-<subpackage>

Subpackages

  • Bruker
  • Coloring
  • Event Processing
  • Input/Output (I/O)
  • Image Processing
  • Interactive Visuals
  • Reorganization
  • Signal Processing
  • Static Visuals

Documentation

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

CalSciPy-0.1.5.tar.gz (23.3 kB view details)

Uploaded Source

Built Distribution

CalSciPy-0.1.5-py3-none-any.whl (22.5 kB view details)

Uploaded Python 3

File details

Details for the file CalSciPy-0.1.5.tar.gz.

File metadata

  • Download URL: CalSciPy-0.1.5.tar.gz
  • Upload date:
  • Size: 23.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.16

File hashes

Hashes for CalSciPy-0.1.5.tar.gz
Algorithm Hash digest
SHA256 6c349469a874535210707a48c1763a371fb6067981ee4011879c66a89aca616e
MD5 d7bcb1374085a655f62644c772b89b0b
BLAKE2b-256 15fdf100715dcc5397c99c7ee3e72f86c25953d13f3e1e962d0525c267c21e6d

See more details on using hashes here.

File details

Details for the file CalSciPy-0.1.5-py3-none-any.whl.

File metadata

  • Download URL: CalSciPy-0.1.5-py3-none-any.whl
  • Upload date:
  • Size: 22.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.16

File hashes

Hashes for CalSciPy-0.1.5-py3-none-any.whl
Algorithm Hash digest
SHA256 7d43da86adec080475f0e049ef344d980591bf59078dd01401804b8415973693
MD5 7727826738c1a9516d4990fdcc66a9ed
BLAKE2b-256 0114678ad5d34649937b897a491b7691d176bf47201a2096708adad51d3e0449

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page