Installation#

To install pyIBA follow one of the methods below.

For an online installation using pip tools:

$ pip3 install pyIBA

Alternatively, you can install from the source:

  1. Clone the repository from GitHub.

  2. Navigate to the project directory where setup.py is located.

  3. Install the project:

    $ pip3 install .

Note

If you’re actively developing, you might want to install in “editable” mode using pip3 install -e .. This ensures changes made to the source code immediately reflect in the installed package.

Alternatively, to avoid installing pyIBA system-wide or using a virtual environment:

  1. Download the source files from GitHub.

  2. Add the following Python commands in your python code before importing pyIBA:

    $ import sys
$ sys.path.insert(0, '/path/to/pyIBA/')
$ from pyIBA import IDF

Note

Usually, pip3 is used to install Python3 packages while pip is used to install Python2 libraries. However, in some environments, the command pip may point to pip3, just as python may point to Python3. You can use which pip or pip --version to check this.

Examples#

Below is a series of examples/tutorials showcasing the use of pyIBA. All of them are made using jupyter Notebooks and thus can be downloaded, edited and tested on your computer. They can be found in the project’s documentation folder (pyIBA).

Note

Any contribution is welcome!

Basic Examples#

1 - Creating a blank IDF
2 - Reading an IDF file
3 - Editing an IDF file
4 - Adding multiple spectra to a single IDF file
5 - IDF files with other techniques

Advanced Examples#

A1 - Large IDF file with experimental and NDF fitted RBS-NRA-PIXE-SIMS data
A2 - Opening IBA Studio from jupyter
A3 - NDF and IDF files
A4 - pyIBA and Tensorflow: Machine Learning demo
A5 - Creating IDF files from NDF files