Software library for X-Ray data analysis
Project description
The silx project aims at providing a collection of Python packages to support the development of data assessment, reduction and analysis applications at synchrotron radiation facilities. It aims at providing reading/writing different file formats, data reduction routines and a set of Qt widgets to browse and visualize data.
The current version provides :
histogramming
fitting
1D and 2D visualization.
image plot widget with a set of associated tools (See changelog file).
Unified browser for HDF5, SPEC and image file formats supporting inspection and visualization of n-dimensional datasets.
OpenGL-based widget to display 3D scalar field with isosurface and cutting plane.
image alignement (sift - OpenCL implementation)
Installation
To install silx, run:
pip install silx
To install silx locally, run:
pip install silx --user
On Linux, to install silx with pip, you must install numpy first.
Unofficial Debian8 packages are available at http://www.silx.org/pub/debian/ CentOS rpm packages are provided by Max IV at the following url: http://pubrepo.maxiv.lu.se/rpm/el7/x86_64/ Arch Linux (AUR) packages are also available: https://aur.archlinux.org/packages/python-silx
On Windows, pre-compiled binaries (aka Python wheels) are available for Python 2.7 and 3.5.
On Mac OS X, pre-compiled binaries (aka Python wheels) are available for Python 2.7.
The latest development version can be obtained from the git repository:
git clone https://github.com/silx-kit/silx.git cd silx pip install . [--user]
Dependencies
The GUI widgets of the silx package depend on the following extra packages:
A Qt binding: PyQt5, PyQt4 (using API version 2) or PySide
matplotlib for the silx.gui.plot package
PyOpenGL for the silx.gui.plot3d package
Most modules and functions dealing with HDF5 input/output depend on the following extra package: * h5py
Supported platforms: Linux, Windows, Mac OS X.
Documentation
Documentation of releases is available at https://pythonhosted.org/silx/
Latest documentation (nightly build) is available at http://www.silx.org/doc/silx/
To build the documentation from the source (requires Sphinx), run:
python setup.py build build_doc
Testing
To run the tests from the python interpreter, run:
>>> import silx.test >>> silx.test.run_tests()
To run the tests, from the source directory, run:
python run_tests.py
Examples
Some examples are available in the source code repository. For example:
python examples/{exampleName.py}
License
The source code of silx is licensed under the MIT and LGPL licenses. See the copyright file for details.
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