Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.

Check out our home page for more information.

Matplotlib produces publication-quality figures in a variety of hardcopy formats and interactive environments across platforms. Matplotlib can be used in Python scripts, Python/IPython shells, web application servers, and various graphical user interface toolkits.

Install

See the install documentation, which is generated from /doc/users/installing/index.rst

Contribute

You've discovered a bug or something else you want to change - excellent!

You've worked out a way to fix it -- even better!

You want to tell us about it -- best of all!

Start at the contributing guide!

Contact

Discourse is the discussion forum for general questions and discussions and our recommended starting point.

Our active mailing lists (which are mirrored on Discourse) are:

• Users mailing list: matplotlib-users@python.org
• Announcement mailing list: matplotlib-announce@python.org
• Development mailing list: matplotlib-devel@python.org

Gitter is for coordinating development and asking questions directly related to contributing to matplotlib.

Citing Matplotlib

If Matplotlib contributes to a project that leads to publication, please acknowledge this by citing Matplotlib.

A ready-made citation entry is available.

DD2480 - Group 24 - Assignment 3

Git Commit Message Template

type: Description #issuenumber

Types

• build: Changes that affect the build system or external dependencies (example scopes: broccoli, npm).
• docs: Documentation only changes.
• feat: A new feature. Can of course also contain tests for the feature.
• fix: Bug fixes. Can of course also contain tests for the feature.
• refactor: A code change that neither fixes a bug nor adds a feature.
• revert: Reverts a previous commit.
• style: Changes that do not affect the meaning of the code (white-space, formatting, missing semi-colons, etc).
• test: Adding missing tests or correcting existing tests.

Detailed installation for Group 24:

Guide originally provided by matplotlib here for cloning the repo and setup of the virtual environment and the dependencies.

Step 1: Clone the repo

Step 2: Step into the root of the directory:

cd matplotlib

Step 3: Create the virtual environment (choose your folder location name and add it to the .gitignore):

python -m venv <file folder location>

Step 4: Activate the virtual environment:

source <file folder location>/bin/activate   # Linux/macOS
<file folder location>\Scripts\activate.bat  # Windows cmd.exe
<file folder location>\Scripts\Activate.ps1  # Windows PowerShell

Step 5: Install Pytest and Coverage in the virtual environment:

1. pip install pytest
2. pip install coverage

Step 6 (Optional): Run the tests with Coverage.py:

From the Coverage.py tutorial avaliable here.
In the root directory run (this will take a while ~15min):
coverage run -m pytest

Step 7 (Optional): Retrieve the coverage report:

Either in the terminal window:
coverage report -m

or as HTML (the generated files are already ignored in the .gitignore):
coverage html