Skip to main content

Package for analysis of single-neuron spike data.

Project description

pylabianca

Python tools for spike analysis.

pylabianca:

  • allows to read, analyse spike rate and statistically compare conditions in just a few steps
  • follows the convenient API of mne-python
  • provides two straightforward objects for storing spiking data: Spikes and SpikeEpochs
  • allow storing trial-level metadata in these object (just like mne-python) and selecting trials based on these metadata
  • returns xarrays (arrays with labeled dimensions and coordinates) as output from operations like cross-correlation, spiking rate calculation or decoding analysis
  • these xarrays inherit all the trial-level metadata and can be visualised splitting by conditions using pylabianca.viz.plot_shaded or native xarray plotting
  • the xarrays can be statistically tested with cluster based permutation test comparing condition metadata

installation

pylabianca can be installed using pip:

pip install pylabianca

To get most up-to-date version you can also install directly from github:

pip install git+https://github.com/labianca/pylabianca

what's new?

See whats_new.md for documentation of recent changes in pylabianca.

docs

Online docs are currently under construction.

Below you can find jupyter notebook examples showcasing pylabianca features.

To better understand the data formats read natively by pylabianca (and how to read other formats) see data formats page.

sample data

You can get example human data that are used in the examples here.
The preprocessed FieldTrip data used in the examples are available here.

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

pylabianca-0.3.0.tar.gz (108.2 kB view details)

Uploaded Source

Built Distribution

pylabianca-0.3.0-py3-none-any.whl (124.2 kB view details)

Uploaded Python 3

File details

Details for the file pylabianca-0.3.0.tar.gz.

File metadata

  • Download URL: pylabianca-0.3.0.tar.gz
  • Upload date:
  • Size: 108.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.4

File hashes

Hashes for pylabianca-0.3.0.tar.gz
Algorithm Hash digest
SHA256 71b3e1fcc480392e5e4659f44fe1b1c457a8c25e2d5fe49dcd019d04aeedb1c5
MD5 c0c4ed8300953037e9c48f9993253099
BLAKE2b-256 4d3dfba36c174ee12c8f29af8c96e7b4847da64469bbef44e28dccdf7ffbd6ed

See more details on using hashes here.

File details

Details for the file pylabianca-0.3.0-py3-none-any.whl.

File metadata

  • Download URL: pylabianca-0.3.0-py3-none-any.whl
  • Upload date:
  • Size: 124.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.4

File hashes

Hashes for pylabianca-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 94b653e899bba4214d647ce287cdacbf300306c5128a0f89fd063e11e0d2aa6c
MD5 7dd4a4d9becdf88c38ca0642957e4ce5
BLAKE2b-256 a23af50e40aa22a877ae3bce4e6a91c2ddf9f985565540fbf759d80b88fa7938

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