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-0.1.1.tar.gz (14.9 kB view details)

Uploaded Source

Built Distribution

CalSciPy-0.1.1-py3-none-any.whl (16.9 kB view details)

Uploaded Python 3

File details

Details for the file CalSciPy-0.1.1.tar.gz.

File metadata

  • Download URL: CalSciPy-0.1.1.tar.gz
  • Upload date:
  • Size: 14.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.12

File hashes

Hashes for CalSciPy-0.1.1.tar.gz
Algorithm Hash digest
SHA256 280897ce556f8dd6821ea71a678a426e1f9e7279d02e4929feafedfbaf91b591
MD5 c6f7d7555701d80aee59435c32eb244f
BLAKE2b-256 d9b00ad1d78a6ad80bf32ad80dc18a275ca970a83e69da008733344f085fddfe

See more details on using hashes here.

File details

Details for the file CalSciPy-0.1.1-py3-none-any.whl.

File metadata

  • Download URL: CalSciPy-0.1.1-py3-none-any.whl
  • Upload date:
  • Size: 16.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.12

File hashes

Hashes for CalSciPy-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 947c8e10400900ab2e020d3c31d5b41923fba1a3ff090d5b4a082455dc249b54
MD5 0f1db21895716047020986d41fd66f33
BLAKE2b-256 259d658f9a10069db848ed61c28d0b4e91e555d9df5e1241cb6b222cbc876a03

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