Skip to main content

Electrophys Feature Extract Library (eFEL)

Project description

The Electrophys Feature Extract Library (eFEL) allows neuroscientists to automatically extract features from time series data recorded from neurons (both in vitro and in silico). Examples are the action potential width and amplitude in voltage traces recorded during whole-cell patch clamp experiments. The user of the library provides a set of traces and selects the features to be calculated. The library will then extract the requested features and return the values to the user.

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

efel-3.0.73.tar.gz (90.5 kB view details)

Uploaded Source

File details

Details for the file efel-3.0.73.tar.gz.

File metadata

  • Download URL: efel-3.0.73.tar.gz
  • Upload date:
  • Size: 90.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.23.0 setuptools/44.0.0 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/2.7.15

File hashes

Hashes for efel-3.0.73.tar.gz
Algorithm Hash digest
SHA256 cc2700872c3c6f3c8ce9db94d9b793a786dba87bbdedb1ded6d81ee4339a0b2d
MD5 8ab7316588e50a0b8ee765d3fb0baed3
BLAKE2b-256 f16afa55725b553c9b4a9759f32757b245c7b762172e914ef719bbe056857294

See more details on using hashes here.

Provenance

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