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scikit-learn is an open source Python module for machine learning built on NumPy, SciPy and matplotlib. It offers simple and efficient tools for predictive data analysis and is reusable in various contexts.
PyNanoLab contains a variety of tools to complete the data analysis, statistics, curve fitting, and basic machine learning application. Visualization in pynanolab is based on matplotlib. The setup tools is desinged to control and set-up all the details of the figure with a GUI.
Installable / Portable Python Distribution for Everyone.
PySchool is a free and open-source Python distribution intended primarily for students who learn Python and data analysis, but it can also used by scientists, engineering, and data scientists.
It includes more than 150 Python packages (full edition) including numpy, pandas, scipy, sympy, keras, scikit-learn, matplotlib, seaborn, beautifulsoup4...
Data Processing and Analysis for X-ray Spectroscopy and More
...Larch has been primarily developed for dealing with x-ray spectroscopic and scattering data, especially the kind of data collected at modern synchrotrons and x-ray sources.
Larch is written in Python and relies heavily on the standard tools for scientific computing with Python (numpy, scipy, matplotlib, and h5py).
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Python API for the GOLEM Tokamak discharge database
This simple Python API aims to provide a simple and easy to understand access to the discharge database of the GOLEM Tokamak.
The scipy, numpy and matplotlib Python libraries are used for data analysis and plotting.
QME-DEV Workbench (wxScipy) is a data analysis workbench based on Python, SciPy, Numpy and MatPlotLib(PyLab) and uses wxPython for the GUI. It can be used for non-linear analysis with a large set of experimental or generated data. Load/Acquire / Save/ Gr