Spectral Python Git
A python module for hyperspectral image processing
Status: Beta
Brought to you by:
tboggs
Menu
▾
▴
Tree [d3966e] python3 / History
| File | Date | Author | Commit |
|---|---|---|---|
| spectral | 2015-11-11 |
Thomas Boggs
|
[d3966e] Updated version to 0.17 |
| .gitignore | 2014-08-22 |
Thomas Boggs
|
[4fbac5] Handle changes in python-opengl API. |
| .travis.yml | 2015-10-01 |
Thomas Boggs
|
[15a39e] Migrate to container-based infrastucture |
| LICENSE.txt | 2013-09-07 |
Thomas Boggs
|
[aa413a] Move text files to top level. |
| MANIFEST.in | 2013-09-07 |
Thomas Boggs
|
[ca899b] Updated version to 0.12. |
| README.rst | 2015-06-14 |
Thomas Boggs
|
[dea653] Change download link from Sourceforge to GitHub. |
| VERSIONS.txt | 2015-11-11 |
Thomas Boggs
|
[d3966e] Updated version to 0.17 |
| setup.py | 2015-06-14 |
Thomas Boggs
|
[dea653] Change download link from Sourceforge to GitHub. |
Read Me
Spectral Python (SPy)
Spectral Python (SPy) is a pure Python module for processing hyperspectral image data (imaging spectroscopy data). It has functions for reading, displaying, manipulating, and classifying hyperspectral imagery. Full details about the package are on the web site.
Installation Instructions
The latest release is always hosted on PyPI, so if you have pip installed, you can install SPy from the command line with
pip install spectral
Packaged distributions are also hosted at PyPI and GitHub so you can download and unpack the latest zip/tarball, then type
python setup.py install
To install the latest development version, download or clone the git repository and install as above. No explicit installation is required so you can simply access (or symlink) the spectral module within the source tree.
Unit Tests
To run the suite of unit tests, you must have numpy installed and you must have the sample data files downloaded to the current directory (or one specified by the SPECTRAL_DATA environment variable). To run the unit tests, type
python -m spectral.tests.run
Dependencies
Using SPy interactively with its visualization capabilities requires IPython and several other packages (depending on the features used). See the web site for details.
