Installing HyperSpy¶

HyperSpy Bundle for Microsoft Windows¶

The easiest way to install HyperSpy in Windows is installing the HyperSpy Bundle. This is a customised WinPython distribution that includes HyperSpy, all its dependencies and many other scientific Python packages. HyperSpy Bundle does not interact with any other Python installation in your system, so it can be safely installed alongside other Python distributions. Moreover it is portable, so it can be installed to a USB key. When installing it with administrator rights for all users it adds context (right-click) menu entries to start the Jupyter Notebook and Juypter QtConsole inside the folder being clicked. See start_jupyter_cm for details.

Quick instructions to install HyperSpy using Anaconda (Linux, MacOs, Windows)¶

Anaconda is recommended for the best performance (it is compiled using Intel MKL libraries) and the easiest installation. The academic license is free.

1. Download and install Anaconda. If you are not familiar with Anaconda please refer to their User Guide for details.

2. Then install HyperSpy executing the following conda commands in the Anaconda Prompt, Linux/Mac Terminal or Microsoft Windows Command Prompt. (This depends on your OS and how you have installed Anaconda, see the Anaconda User Guide) for details.

   $ conda config --add channels conda-forge
   $ conda install hyperspy
   

$ conda install traitsui
$ pip install --upgrade hyperspy==0.8.3-1

To enable context-menu (right-click) startup in a chosen folder, install start_jupyter_cm. (Currently only available for Gnome and Windows, not MacOS.)

For more options and details read the rest of the documentation.

Install using Python installers¶

HyperSpy is listed in the Python Package Index. Therefore, it can be automatically downloaded and installed pip. You may need to install pip for the following commands to run.

Install using pip:

$ pip install hyperspy

$ pip install --upgrade hyperspy==0.8.3-1

pip installs automatically the strictly required libraries. However, for full functionality you may need to install some other dependencies, see Installing the required libraries. Also, be aware that HyperSpy depends on a number of libraries that usually need to be compiled and therefore installing HyperSpy may require development tools. If the above does not work for you remember that the easiest way to install HyperSpy is using Anaconda.

Creating Conda environment for HyperSpy¶

Anaconda Python distribution can be easily set up using environment files. The two required steps are:

1. Download HyperSpy environment file.
2. Create and activate HyperSpy environment according to instructions here. For Unix, the following should work:

$ conda config --add channels conda-forge
$ conda env create -f anaconda_hyperspy_environment.yml
$ source activate hyperspy

Install from a binary¶

We provide binary distributions for Windows (see the Downloads section of the website). To install easily in other platforms see Install using Python installers

Install from source¶

$ tar -xzf hyperspy.tar.gz
$ cd hyperspy
$ python setup.py install

$ pip install hyperspy.tar.gz

$ git clone https://github.com/hyperspy/hyperspy.git

$ cd hyperspy
$ pip install -e ./

$ cd hyperspy
$ sudo pip install -e ./

$ ./release_debian

Installing the required libraries¶

When installing HyperSpy using Python installers or from source the Python programming language and the following libraries must be installed in the system: numpy, scipy, matplotlib (>= 1.2), ipython, natsort, tqdm, ipyparallel, python-dateutil, traits and traitsui. For full functionality it is recommended to also install h5py, scikit-image, scikit-learn and lxml. If HyperSpy is going to be installed from source, cython is also required.In addition, since version 0.7.2 the lowess filter requires statsmodels. In Windows HyperSpy uses the Ipython’s QtConsole and therefore Qt and PyQt or PySide are also required.

In Debian/Ubuntu you can install the libraries as follows:

$ sudo apt-get install python-numpy python-matplotlib ipython
ipython-notebook python-traits python-traitsui python-h5py
python-scikit-learn python-scikit-image python-nose
python-statsmodels python3-tqdm

Known issues¶