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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/
Inflow requires python 3.7 or later, and is tested on Windows 10.
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
import Inflow
Inflow.load.tdms("mytdmsfile.tdms").
FAQs
General python code for analysis pipeline
We found that inflow-haisslab demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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