Remove superuser privileges from pip and install packages in ~/.local. This also
prevents hiding pip's packages by system packages, since user packages have
precedence.

Install numpy, scipy and matplotlib via the pip3 command and not via ubuntu's
package manager, since this would install older versions.

Fix the write/append operations, such that the proper X11 setup is written to
decay.py

Add a preliminary version, i.e. without proof reading, of the section describing
how to read, plot and fit data.

Add a section about the prerequisites needed for this tutorial and how the
tutorial and the repository is structured.

Adding a new section explain how to plot data points on top of the expected
cropped parabola.

Two minor changes:
 - Add eps and png images to the gitignore file
 - Fix a typo in the plotting function f(x)

Add the *.png pattern to the list of artifacts.

Create also a png version of the cropped parabola plot and use this version in
the README.

Embed the plot of the cropped parabola from the artifacts of the CI.

Prevent the second operation in func_plot.py to overwrite the first one, which
set up the Agg backend.

Add matplotlib.use('Agg') to the code examples, which is necessary when run in
an environment without X11 sever, such as the CI pipeline.

Add a chapter showing and example how to plot a simple function with
matplotlib. This commit add eps-files to the artifacts of the CI.

Use CI_REGISTRY_IMAGE instead of a combination of CI_REGISTRY and
CI_PROJECT_PATH_SLUG to fix registry image path.

Use CI_PROJECT_PATH_SLUG instead of CI_PROJECT_PATH in docker image path, since
the registry path must be lowercase.

Fix the gitlab-ci configuration by adding quotes to the artifacts path with
wildcards.

Add the gitignore file. Temporary vim file should be ignored, as well as
python script generated by doxec.

Add a CI pipeline with a single doxec task. The created python code examples are
packaged and can be downloaded on success.

This commit adds a chapter about the installation of python3, numpy, scipy and
matplotlib and a chapter with a first 'Hello World'-like example.