Skip to main content

General python code for analysis pipeline

Project description

Inflow

Core package for analysis, and pipelining utilities in the Haiss Lab
Find the documentation for the functions of this package in a searchable website here : https://haisslab.pages.pasteur.fr/analysis-packages/Inflow/

Requirements

Inflow requires python 3.7 or later, and is tested on Windows 10.

Installing

Installing the package via pip typically takes a few seconds. To install, activate your developpement environment :

conda activate <myenvironment>

If you don't have an environment or conda installed, follow these instructions
Then run the Inflow install using :

pip install git+https://gitlab.pasteur.fr/haisslab/analysis-packages/Inflow.git

NB:
This package is still under active development, for the best experience please regularly update the package by running :

pip install --force-reinstall --no-deps -U git+https://gitlab.pasteur.fr/haisslab/analysis-packages/Inflow.git

For dev environment (expect bugs), use this one :

pip install --force-reinstall --no-deps git+https://gitlab.pasteur.fr/haisslab/analysis-packages/Inflow.git@dev

This will force the reinstallation of the package, without the need to do a pip uninstall Inflow first, and without reinstalling the dependancies like numpy etc (hence faster).

For pre-realeases environment (dev after minimal testing, please don't hesitate to report bugs), use this one :

pip install --force-reinstall --no-deps -U git+https://gitlab.pasteur.fr/haisslab/analysis-packages/Inflow.git@pre-releases

Usage

import Inflow
Inflow.load.tdms("mytdmsfile.tdms").

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

inflow_haisslab-1.2.29.tar.gz (154.4 kB view details)

Uploaded Source

Built Distribution

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

inflow_haisslab-1.2.29-py3-none-any.whl (168.1 kB view details)

Uploaded Python 3

File details

Details for the file inflow_haisslab-1.2.29.tar.gz.

File metadata

  • Download URL: inflow_haisslab-1.2.29.tar.gz
  • Upload date:
  • Size: 154.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for inflow_haisslab-1.2.29.tar.gz
Algorithm Hash digest
SHA256 5d98048d430ec93a7984f447f1d3b92e69e71e300b51456d030b5f51b2d1e86d
MD5 09f4c384c5b6341f01a6553324aacf58
BLAKE2b-256 04d63678beabea7c2753bca575dc6cd60c1d1ded2662ed2718c9c5eb3e7a8f3f

See more details on using hashes here.

File details

Details for the file inflow_haisslab-1.2.29-py3-none-any.whl.

File metadata

File hashes

Hashes for inflow_haisslab-1.2.29-py3-none-any.whl
Algorithm Hash digest
SHA256 f58f1a0a03e5289743efc32fef0712aa8a127e3f36937562577a1d62871b7665
MD5 f4933f57084c8e8d9b64f352a7c00f8c
BLAKE2b-256 b2dc349c6ccea6b2c5cecc6aa2ab8b6b99193174244d7b59db2a51bdb7bc44d6

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