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 reading SPEC file format, histogramming, curves and image plot widget with a set of associated tools (See changelog file).
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.edna-site.org/pub/debian/
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]
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
Most modules and functions dealing with HDF5 input/output depend on the following extra package: * h5py
Supported platforms: Linux, Windows, Mac OS X.
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
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
The source code of silx is licensed under the MIT and LGPL licenses. See the copyright file for details.