Skip to main content

No project description provided

Project description

tnbs_stim_clean

Description

tnbs_stim_clean provides functionality to clean EEG, MEG, and other time-series data from mne-python by removing unwanted stimuli using the tnbs_stim_clean function. This is especially useful in preprocessing to remove noise or artifacts from signals caused by stimuli events.

Installation

You can install the package via pip from PyPI:

pip install tnbs_stim_clean

Example use

import tnbs_stim_clean

# Example parameters
raw  # Raw time series data in MNE's raw object format
half_win = 100  # Half window size around each stimulus (in samples) that will be chopped away from the artifact peak point
threshold = 0.0001  # Threshold above which stimulus is considered significant

# Apply stimulus cleaning 
raw_cleaned = stim_clean(raw, half_win, threshold)

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

tnbs_stim_clean-0.1.5.tar.gz (1.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

tnbs_stim_clean-0.1.5-py3-none-any.whl (1.6 kB view details)

Uploaded Python 3

File details

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

File metadata

  • Download URL: tnbs_stim_clean-0.1.5.tar.gz
  • Upload date:
  • Size: 1.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.2

File hashes

Hashes for tnbs_stim_clean-0.1.5.tar.gz
Algorithm Hash digest
SHA256 d80fb96de31533cfc79f17f3d85473ac79c31c3a3b9b7574224588cfebf30adc
MD5 84d89655340331f060111b5ab9f7381c
BLAKE2b-256 fe211716f362b027e38ff75f201fb52f3387f8d6c6581cb95e5f3fa43e84c78a

See more details on using hashes here.

File details

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

File metadata

File hashes

Hashes for tnbs_stim_clean-0.1.5-py3-none-any.whl
Algorithm Hash digest
SHA256 0184e8cf9c025b489069bc1b9a7d8756708b8f620c84e7926f8d47ce0bc88088
MD5 0bd600d08ba1da45cf528f30d1ff97df
BLAKE2b-256 6ec1d9b8d1e324c1f9c8ac9bb9a9840bfb6a579a4a510e84a764c09794f44a2d

See more details on using hashes here.

Supported by

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