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prettypyplot

Publication-ready figures made easy

https://github.com/braniii/prettypyplot

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 3 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (13.0%) to scientific vocabulary

Keywords

matplotlib scientific-visualization

Keywords from Contributors

interactive molecule mesh interpretability profiles sequences generic projection standardization optim
Last synced: 6 months ago · JSON representation

Repository

Publication-ready figures made easy

Basic Info
Statistics
  • Stars: 8
  • Watchers: 2
  • Forks: 3
  • Open Issues: 1
  • Releases: 4
Topics
matplotlib scientific-visualization
Created almost 5 years ago · Last pushed 7 months ago
Metadata Files
Readme Changelog Contributing License Zenodo

README.md

DOI

Docs • Features • Installation • Gallery

prettypyplot

The documentation including an gallery can be found here.

This is a wrapper package for matplotlib to achieve more easily pretty figures. If you are looking for something complete, this project is nothing for you but maybe seaborn. The main aspect of this project is to help me syncing my rcParams files and to stop copy-pasting so much code.

The aim of this project is to simplify the generation of some simple pre-defined figures. Almost all code is inspired or taken from the matplotlib gallery. If you are a power user or interested in generating complex figures, this packages is not ment for you and you should better take a look in the matplotlib gallery directly.

This project is in an alpha stage, hence it is neither stable nor ready for production.

CAUTION: Starting from version 1.0.0 (which is far in the future) API-breaking changes will be made only in major releases. Until then, it can be changed in every minor release (see changelog).

Features

The most notable features are:

  • Tested with matplotlib 3.3-3.10
  • figsize specifies size of canvas. So labels, ticks or colorbars are not counted.
  • Nice top-aligned outter legends
  • New colors

Usage

This package uses an syntax very close to matplotlib. Hence, it should be straight forward to use it. Instead of calling a function on the axes itself, one needs to pass here the axes as an argument (args or kwargs).

Installation

python python3 -m pip install --upgrade prettypyplot or python conda install -c conda-forge prettypyplot or for the latest dev version python python3 -m pip install git+https://github.com/braniii/prettypyplot.git

Usage

```python import matplotlib.pyplot as plt import prettypyplot as pplt

pplt.use_style() fig, ax = plt.subplots() ... pplt.plot(ax=ax, x, y) pplt.savefig(output) ```

Known Bugs

  • plt.subplots_adjust() does not work with pplt.savefig(use_canvas_size=True) If you find one, please open an issue.
  • pplt.savefig(use_canvas_size=True) is not compatible with a grid of subplots

Known Workarounds

The method pyplot.subplots_adjust() is not compatible with the option use_canvas_size in prettypyplot.plot.savefig, use instead: ```python

this doesn't work, use instead gridspec

fig.subplots_adjust(hspace=0)

use this instead

fig, axs = plt.subplots(..., gridspec_kw={'hspace': 0.000}) ```

Comparison to matplotlib

matplotlib.pyplot.plot
 prettypyplot.plot
matplotlib.pyplot.legend
 prettypyplot.legend
matplotlib.pyplot.imshow
 prettypyplot.imshow
matplotlib.pyplot.colorbar
 prettypyplot.colorbar

Roadmap:

The following list is sorted from near future to hopefully ever.

  • [x] add pytest
  • [x] add search functionality in doc
  • [x] refactoring code to improve readabilty
  • [x] add package to conda_forge
  • [x] add gallery page
  • [x] improve plt.suplots() behaviour together with pplt.savefig()
  • [ ] add more colorpalettes
  • [ ] add countour line plot
  • [ ] add axes_grid examples
  • [ ] setup widths and scaling factors for beamer and poster mode
  • [ ] tweak all function to enable STYLE='minimal'
  • [ ] implement tufte style

Building Documentation:

The doc is based on mkdocs and can be created by ```bash

installing all dependencies

python -m pip install -e .[docs]

serve interactively

python -m mkdocs serve ```

Similar Projects

Citing Prettypyplot

If you want to cite prettypyplot in scientific work please use:

Prettypyplot: publication ready matplotlib figures made simple
D. Nagel, 2022. Zenodo: 10.5281/zenodo.7278312

Credits:

In alphabetical order:

Owner

  • Name: Daniel Nagel
  • Login: braniii
  • Kind: user
  • Location: Freiburg, Germany

GitHub Events

Total
  • Watch event: 2
  • Delete event: 11
  • Issue comment event: 3
  • Push event: 30
  • Pull request event: 27
  • Create event: 14
Last Year
  • Watch event: 2
  • Delete event: 11
  • Issue comment event: 3
  • Push event: 30
  • Pull request event: 27
  • Create event: 14

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 372
  • Total Committers: 5
  • Avg Commits per committer: 74.4
  • Development Distribution Score (DDS): 0.035
Past Year
  • Commits: 17
  • Committers: 2
  • Avg Commits per committer: 8.5
  • Development Distribution Score (DDS): 0.471
Top Committers
Name Email Commits
braniii d****l@p****m 359
dependabot[bot] 4****] 8
Georg Diez 5****o 3
taenzel 6****l 1
Patrick Binder p****l@p****m 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 3
  • Total pull requests: 31
  • Average time to close issues: 4 months
  • Average time to close pull requests: 6 days
  • Total issue authors: 3
  • Total pull request authors: 4
  • Average comments per issue: 0.33
  • Average comments per pull request: 0.45
  • Merged pull requests: 22
  • Bot issues: 0
  • Bot pull requests: 17
Past Year
  • Issues: 1
  • Pull requests: 24
  • Average time to close issues: N/A
  • Average time to close pull requests: 3 days
  • Issue authors: 1
  • Pull request authors: 2
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.42
  • Merged pull requests: 16
  • Bot issues: 0
  • Bot pull requests: 17
View more stats
Top Authors
Issue Authors
  • gegabo (1)
  • farudolf (1)
  • braniii (1)
Pull Request Authors
  • dependabot[bot] (23)
  • braniii (12)
  • gegabo (6)
  • taenzel (2)
Top Labels
Issue Labels
bug (1)
Pull Request Labels
dependencies (23) github_actions (7)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 318 last-month
  • Total dependent packages: 2
  • Total dependent repositories: 1
  • Total versions: 16
  • Total maintainers: 1
pypi.org: prettypyplot

Wrapper for matplotlib to generate pretty plots.

  • Versions: 16
  • Dependent Packages: 2
  • Dependent Repositories: 1
  • Downloads: 318 Last month
Rankings
Dependent packages count: 3.1%
Downloads: 13.3%
Average: 17.1%
Dependent repos count: 21.7%
Forks count: 22.6%
Stargazers count: 25.0%
Maintainers (1)
braniii
Last synced: 6 months ago

Dependencies

.github/workflows/pages.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
extra-requirements.txt pypi
  • coverage *
  • flake8 *
  • mkdocs-gen-files *
  • mkdocs-literate-nav *
  • mkdocs-material *
  • mkdocstrings *
  • mkdocstrings-python *
  • pytest *
  • pytest-cov *
  • pytest-mpl *
  • pytest-rerunfailures *
requirements.txt pypi
  • decorit >=0.2.0
  • matplotlib >=3.0.0
  • numpy *
setup.py pypi
  • decorit >=0.2.0
  • matplotlib *
  • numpy *
.github/workflows/pytest.yml actions
  • actions/checkout v4 composite
  • actions/setup-python v5 composite
.github/workflows/python-publish.yml actions
  • actions/checkout v4 composite
  • actions/setup-python v5 composite
  • pypa/gh-action-pypi-publish release/v1 composite