Installation

PyXRF is supported for Python 3.9-3.11 in Linux/Mac/Windows systems. The easiest way to install PyXRF is to load it into a Conda environment from conda-forge Anaconda channel. Installation instructions are identical for all supported OS.

Note

If you experience problems using Conda, in particular if Conda gets stuck trying to resolve the environment, use Mamba, which is designed as a drop-in replacement for Conda. Mamba is included in the Miniforge distribution. It can also be installed in the base environment of an existing installation of Miniconda or Anaconda:

$ conda install -n base --override-channels -c conda-forge mamba 'python_abi=*=*cp*'

See Mamba installation instructions for more details.

How to use `mamba`: Simply replace conda with mamba when you create an environment, install or remove packages, etc. For example

$ mamba create -n pyxrf-env python=3.11 pip -c conda-forge
$ mamba activate pyxrf-env
$ mamba install pyxrf -c conda-forge

  1. Install Miniconda3 or Anaconda. Select the latest version. Miniconda is sufficient for running PyXRF and contains the minimum number of packages. Anaconda is much larger download, which also installs GUI applications for more convenient management of Conda environments.

    If Conda is already installed on your computer, proceed to the next step.

  2. Open a terminal (Linux/Mac) or start Anaconda Prompt from Windows Start Menu (Windows).

  3. If you are using existing Conda installation, update Conda:

    $ conda update -n base -c defaults conda

    If you are installing PyXRF on a Windows platform, close and restart Anaconda Prompt.

  1. Install PyXRF from conda-forge Anaconda channels.

    Create new Conda environment with the desired version of Python (e.g. v3.11):

    $ conda create -n pyxrf-env python=3.11 pip -c conda-forge

    Activate the new environment:

    $ conda activate pyxrf-env

    Install PyXRF:

    $ conda install pyxrf -c conda-forge

  2. Install PyXRF from PyPI:

    Create new Conda environment with the desired version of Python (e.g. v3.11), xraylib and scikit-beam packages (recommended):

    $ conda create -n pyxrf-env python=3.11 pip xraylib scikit-beam -c conda-forge

    The scikit-beam package may be installed may be installed from PyPI if necessary. Third party distribution of xraylib package also exists on PyPI.

    Activate the new environment:

    $ conda activate pyxrf-env

    Install PyXRF from PyPI:

    $ pip install pyxrf PyQt5

    or from source (editable installation):

    $ cd <root-directory-of-the-repository>
$ pip install PyQt5
$ pip install -e .

Starting PyXRF

  1. Open a terminal (Linux/Mac) or start Anaconda Prompt from Windows Start Menu (Windows).

  2. Activate Conda environment that contains PyXRF installation (in our example pyxrf-env):

    $ conda activate pyxrf-env

  3. Start PyXRF by typing:

    $ pyxrf

Updating PyXRF

  1. Open a terminal (Linux/Mac) or start Anaconda Prompt from Windows Start Menu (Windows)

  2. Activate Conda environment that contains PyXRF installation (in our example pyxrf-env):

    $ conda activate pyxrf-env

  3. Update Conda installation of PyXRF:

    $ conda update pyxrf scikit-beam -c conda-forge

  4. Update PyPI installation of PyXRF:

    $ conda update scikit-beam -c conda-forge
$ pip install --upgrade pyxrf -c conda-forge

    if scikit-beam was installed using Conda or

    $ pip install --upgrade scikit-beam pyxrf -c conda-forge

    if scikit-beam was installed from PyPI.

Deactivating Conda environment

$ conda deactivate