Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Root | 2,296 | 20 | 7 hours ago | 16 | October 24, 2022 | 885 | other | C++ | ||
The official repository for ROOT: analyzing, storing and visualizing big data, scientifically | ||||||||||
Cellpy | 61 | 2 | a month ago | 117 | October 27, 2023 | 21 | mit | Python | ||
extract and tweak data from electrochemical tests of cells | ||||||||||
Machinelearningect | 46 | 3 years ago | 3 | cc0-1.0 | ||||||
For better displaying html files and course material use this link | ||||||||||
Plottr | 35 | 4 months ago | 19 | March 28, 2022 | 57 | mit | Python | |||
A flexible plotting and data analysis tool. | ||||||||||
Nptool | 27 | 4 years ago | 3 | other | C++ | |||||
NPTool, a ROOT/Geant4 based framework for Nuclear Physics | ||||||||||
Amptools | 18 | 7 days ago | 11 | C++ | ||||||
A utility library for performing amplitude analysis on particle physics data. | ||||||||||
Arpes | 14 | 2 years ago | 4 | other | Python | |||||
Mirror of PyARPES (gitlab/lanzara-group/python-arpes) the open source ARPES analysis framework | ||||||||||
Qtplot | 10 | 5 years ago | 36 | November 07, 2018 | 3 | mit | Python | |||
Data visualization application for data taken with qtlab or QCoDeS | ||||||||||
Mlerasmus | 10 | 4 days ago | 2 | |||||||
This site contains all document relevant for the Machine Learning courses of the Erasmus+ network. Jupyter-book link at https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/intro.html. | ||||||||||
Qexpy | 10 | 3 | a year ago | 35 | January 19, 2021 | 2 | gpl-3.0 | Python | ||
Python-3 package for data-analysis in undergraduate laboratories. |
This Python Package was developed to help the researchers at IFE, Norway, in their cumbersome task of interpreting and handling data from cycling tests of batteries and cells.
The documentation for cellpy
is hosted on Read the docs.
The easiest way to install cellpy
is to install with conda or pip.
With conda:
conda install -c conda-forge cellpy
Or if you prefer installing using pip:
python -m pip install cellpy
Have a look at the documentation for more detailed installation procedures, especially with respect to "difficult" dependencies when installing with pip.
cellpy
is free software made available under the MIT License.