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# Installing PySptools

From version 0.12.1, PySptools can run under Python 2.7 and 3.3. It has been tested for these versions but can probably run under others Python versions.

Note

The HSI cubes are, in general, large and the 64 bits version of Python is recommended.

The latest release is available at these download sites:

> - pypi
> - sourceforge

## Manual installation

To install download the sources, expand it in a directory and add the path of the pysptools-0.xx.x directory to the PYTHONPATH system variable.

## Distutils installation

You can use Distutils. Expand the sources in a directory, go to the pysptools-0.xx.x directory and at the command prompt type ‘python setup.py install’. To uninstall the library, you have to do it manually. Go to your python installation. In the Lib/site-packages folder simply removes the associated pysptools folder and files.

## Using the faster version of NFINDR

The algorithm NFINDR have a cython version. This cython version run two times faster than the pure Python version. It is compiled for Windows 7 (maybe it work for vista and 8), 64 bits and the official Python 2.7 64 bits release. If it is your case, download NFINDR_win_amd64-py2.7.zip, unzip and copy the nfindr.pyd file to your installation in the endmembers extraction algorithms folder, something like lib\site-packages\pysptools\eea You can find this file on the sourceforge download site. To have more information on nfindr.pyd read the eea module documentation.

## Dependencies

> - Python 2.7 or 3.3
> - Numpy, required
> - Scipy, required
> - scikit-learn, required
> - SPy, required (for Python 2.7)
> - Matplotlib, required
> - CVXOPT, optional, to run FCLS
> - IPython, optional, if you want to use the display feature

The development environment is a follow:

- For Python 2.7, the library is developed on the Windows platform, with: Python 2.7.5, 64 bits, numpy 1.8.2, scipy 0.12.0, SPy 0.11, Matplotlib 1.3.1, scikit-learn 0.13.1, CVXOPT 1.1.6 and IPython 2.2.0.
- For Python 3.3, the library is developed on the Windows platform, with: Python 3.3.5, 64 bits, numpy 1.8.1, scipy 0.13.3, Matplotlib 1.3.1, scikit-learn 0.15, CVXOPT 1.1.7 and IPython 2.2.0.

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