Useful matplotlib snippets, plotting routines and template scripts. The examples herein illustrate many advanced matplotlib features by using them in a concrete context. This repository collects such examples, to provide them for easy reusability and as interesting showcases with the hope that they might prove to be useful for other interested parties. This repository consist of many examples which can also be understood as template plot scripts for different plotting scenarios. In particular, many of these are meant to illustrate how much potential matplotlib has if one goes beyond the defaults.
For some cases both a full and minimal version of the same plotting example is provided. The full versions are often heavily customized, whilst the minimal versions are meant to be minimal requirement python scripts that focus on a single issue, without further ado.
The python scripts which produce the above example are placed in
/mpl_correlation2d_with_marginals
The python script which produces the above two figures can be found under
/mpl_heatmap_log_xy-scale/demo
For visualizing small 2d matrices, this pcolormesh assay illustrates a nice way how to create fixed size figures with constant relative margins between data and figure borders. In this way the created panels can be nicely integrated into larger arrays and appear all homogeneously in terms of figure size, margins, borders and figure labels. This approach seems suitable for rather small matrices (around n < 64). For full image viewing matplotlib's imshow command seems more appropriate and up to the task.
The script which produces the shown panels is located in
/mpl_pcolormesh_with_fixed_size_and_relative_border_margins
The example below shows how to create a scatter plot with data lables using nice power of ten string formatting both for the data labels and for the scientific y-axis scaling.
The script which produces the above figure is located in
/mpl_scatter_plot_with_data_labels
All shown examples have been tested with Python 3 (version 3.7.6) and matplotlib version 3.4.1. Update to matplotlib 3.4.2 in progress. Support for Python 2 is dropped. However copying some snippets from the scripts will most likely also (still) work with Python 2.7, as they were originally developed using Python 2.7 starting with matplotlib 2.2.3.
For some modules unit tests are provided in the
/unit-tests
directory which can be run using the unittest module or via pytest. All tests were done using pytest version 6.1.2.
For changes made to this repository see the provided changelog.md file in root.