# LovelyPlots
  [](
http://doi.org/10.5281/zenodo.6903937) 
> **Warning**
> : As of version 1.0.0, you need to add ``import lovelyplots`` before setting the style (``plt.style.use('ipynb')``).
LovelyPlots is a repository containing ``matplotlib`` style sheets to nicely format figures for scientific papers, thesis and presentations while keeping them fully editable in ``Adobe Illustrator``. Additonaly, ``.svg`` exports options allows figures to automatically adapt their font to your document's font. For example, ``.svg`` figures imported in a ``.tex`` file will automatically be generated with the text font used in your ``.tex`` file.
<p align="center" width="50%">
<img width="70%" src="figs/plots/ipynb+use_mathtext.svg">
</p>
# Installation
```bash
# to install latest PyPI release
pip install LovelyPlots
# to install latest GitHub commit
pip install --upgrade git+https://github.com/killiansheriff/LovelyPlots.git
```
The pip installation will move all of the ``matplotlib`` style files ``*.mplstyle`` into the appropriate ``matplotlib`` directory.
# Usage
LovelyPlots main style is called ``ipynb``. To use it, add the following lines to the begining of your python scripts:
```python
import lovelyplots
import matplotlib.pyplot as plt
plt.style.use('ipynb')
```
Styles can be combined:
```python
import lovelyplots
import matplotlib.pyplot as plt
plt.style.use(['ipynb','colorsblind34'])
```
In the above case, the ``ipynb`` default color cycle will be overwritten by a 34 colors colorblind safe color cycle called ``colorsblind34``.
If you only wish to apply a style on a specific plot, this can be achieved using:
```python
import lovelyplots
import matplotlib.pyplot as plt
with plt.style.context('ipynb'):
fig, ax = plt.subplots()
ax.plot(x, y)
```
# Examples
A few styles are presented here, please see [Styles](#Styles) for a list of all implemented styles. The script used to generate these plots can be found [here](examples/plot.py).
:warning: If you use the ``use_mathtext`` style, ``Adobe Illustrator`` might fail to nicely detect text objects. Please see [here](#Tips-and-Tricks) for work arounds.
The ``['ipynb', 'use_mathtext']`` style:
The ``['ipynb', 'use_mathtext','colors10-markers']`` style:
The ``['ipynb', 'use_mathtext','colors5-light']`` style:
The ``['ipynb', 'use_mathtext', 'colors10-ls']`` style:
The ``['ipynb']`` style:
The ``['paper', 'use_mathtext']`` style:
# Styles
LovelyPlots main style is called ``ipynb``. The latter by default sets the figure size to ``(4.5, 3.46) inches``, uses the default ``matplotlib`` font, activate scientific notation and makes sure your ``matplotlib`` exports will be editable in ``Adobe Illustrator``. Its default color cycle was set to ``colors10``.
## Color cycles
A multitude of color cycles were implemented:
``colors5-light``
``colors5``
``colors10``
``colorsblind10``
``colorsblind34``
Can be seen [here](figs/colors/colorsblind34.png).
## Lines styles, markers and combinations styles
Line styles, markers styles and combinations can be set using the following styles: `ls5`, `marker7`, `colors10-ls`, `colors10-markers`.
## Color maps
Default ``matplotlib`` colormaps were implemented and can be used by adding the following styles: ``cmap-viridis``, ``cmap-inferno``, ``cmap-cividis``, ``cmap-magma``, ``cmap-plasma``.
## Utils
Specific ``matplotlibrc`` parameters can be turned ``on/off`` using the following utilities styles: ``svg_no_fonttype``, ``use_mathtex``, ``use_tex``.
## Fonts
By default the ``ipynb`` style uses the default ``matplotlib`` font. However, one can set its favorite font from a TIFF file:
```python
import lovelyplots as lp
import matplotlib.pyplot as plt
plt.style.use('ipynb')
lp.utils.set_font('my_font.tiff')
```
# Tips and Tricks
## Adobe Illustrator
Unfortunately, ``mathtext`` (and thus nicely formated scientific notation) will mess up ``Adobe illustrator`` ability to detect text objects, and is thus not activated by default. If you wish to use it, please add the style ``use_mathtext``.
## Latex and SVG files
By default, the ``ipynb`` style sets ``svg.fonttype: none``. This allows for plots saved as ``.svg`` not to carry font information. Consequently, when opened in another environement, the plot will be generated with the default system font.
For example, this allows ``.svg`` plots imported inside a ``Latex`` file to directly be generated with the proper document font, without you having to manually edit the fonts to match your document's font. Additonally, you can open the ``.svg`` file as text file, find the ugly ``1e10`` scientific notation and replace it with ``$10^10$`` so that it is nicely formated when included in your ``.tex`` file.
An example of how to show an svg in a ``.tex`` file:
```tex
\usepackage{svg}
\begin{figure}[htbp]
\centering
\includesvg{myfig.svg}
\end{figure}
```
## Retina displays
For those using ``IPython`` notebooks, you can set retina display support by adding the following lines to the begining on your python script:
```python
import lovelyplots as lp
lp.utils.set_retina()
```
## Useth in Google Colab
To use on Google Colab, you will need to run the following code:
```python
!pip install lovelyplots
import lovelyplots
plt.style.reload_library()
plt.style.use('ipynb')
```
# Acknowledgements
This reprository was inspired by [SciencePlots](https://github.com/garrettj403/SciencePlots), but adds different styles and crucial functionalities for useth in ``.tex`` files and ``Adobe Illustrator``.
# Citing
If you use LovelyPlots, please consider citing:
@software{killian_sheriff_2022_6916993,
author = {Killian Sheriff},
title = {{LovelyPlots, a collection of matplotlib
stylesheets for scientific figures}},
month = jul,
year = 2022,
publisher = {Zenodo},
version = {v0.0.26\_LovelyPlots},
doi = {10.5281/zenodo.6916993},
url = {https://doi.org/10.5281/zenodo.6916993}
}
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"description": "# LovelyPlots\n  [](\nhttp://doi.org/10.5281/zenodo.6903937) \n\n> **Warning**\n> : As of version 1.0.0, you need to add ``import lovelyplots`` before setting the style (``plt.style.use('ipynb')``).\n\nLovelyPlots is a repository containing ``matplotlib`` style sheets to nicely format figures for scientific papers, thesis and presentations while keeping them fully editable in ``Adobe Illustrator``. Additonaly, ``.svg`` exports options allows figures to automatically adapt their font to your document's font. For example, ``.svg`` figures imported in a ``.tex`` file will automatically be generated with the text font used in your ``.tex`` file.\n\n<p align=\"center\" width=\"50%\">\n <img width=\"70%\" src=\"figs/plots/ipynb+use_mathtext.svg\">\n</p>\n\n# Installation\n\n```bash\n# to install latest PyPI release\npip install LovelyPlots\n\n# to install latest GitHub commit\npip install --upgrade git+https://github.com/killiansheriff/LovelyPlots.git\n```\n\nThe pip installation will move all of the ``matplotlib`` style files ``*.mplstyle`` into the appropriate ``matplotlib`` directory.\n\n# Usage\n\nLovelyPlots main style is called ``ipynb``. To use it, add the following lines to the begining of your python scripts:\n\n```python\nimport lovelyplots\nimport matplotlib.pyplot as plt\nplt.style.use('ipynb')\n```\n\nStyles can be combined:\n\n```python\nimport lovelyplots\nimport matplotlib.pyplot as plt\nplt.style.use(['ipynb','colorsblind34'])\n```\n\nIn the above case, the ``ipynb`` default color cycle will be overwritten by a 34 colors colorblind safe color cycle called ``colorsblind34``.\n\nIf you only wish to apply a style on a specific plot, this can be achieved using:\n\n```python\nimport lovelyplots\nimport matplotlib.pyplot as plt\n\nwith plt.style.context('ipynb'):\n fig, ax = plt.subplots()\n ax.plot(x, y)\n```\n\n# Examples\n\nA few styles are presented here, please see [Styles](#Styles) for a list of all implemented styles. The script used to generate these plots can be found [here](examples/plot.py).\n\n:warning: If you use the ``use_mathtext`` style, ``Adobe Illustrator`` might fail to nicely detect text objects. Please see [here](#Tips-and-Tricks) for work arounds.\n\n\nThe ``['ipynb', 'use_mathtext']`` style:\n\n\n\nThe ``['ipynb', 'use_mathtext','colors10-markers']`` style:\n\n\n\nThe ``['ipynb', 'use_mathtext','colors5-light']`` style:\n\n\n\nThe ``['ipynb', 'use_mathtext', 'colors10-ls']`` style:\n\n\n\nThe ``['ipynb']`` style:\n\n\n\nThe ``['paper', 'use_mathtext']`` style:\n\n\n\n# Styles\n\nLovelyPlots main style is called ``ipynb``. The latter by default sets the figure size to ``(4.5, 3.46) inches``, uses the default ``matplotlib`` font, activate scientific notation and makes sure your ``matplotlib`` exports will be editable in ``Adobe Illustrator``. Its default color cycle was set to ``colors10``.\n\n## Color cycles\n\nA multitude of color cycles were implemented:\n\n``colors5-light``\n\n\n\n``colors5``\n\n\n\n``colors10``\n\n\n\n``colorsblind10``\n\n\n\n``colorsblind34``\n\nCan be seen [here](figs/colors/colorsblind34.png).\n\n\n## Lines styles, markers and combinations styles\n\nLine styles, markers styles and combinations can be set using the following styles: `ls5`, `marker7`, `colors10-ls`, `colors10-markers`.\n\n## Color maps\nDefault ``matplotlib`` colormaps were implemented and can be used by adding the following styles: ``cmap-viridis``, ``cmap-inferno``, ``cmap-cividis``, ``cmap-magma``, ``cmap-plasma``.\n\n## Utils\n\nSpecific ``matplotlibrc`` parameters can be turned ``on/off`` using the following utilities styles: ``svg_no_fonttype``, ``use_mathtex``, ``use_tex``.\n\n## Fonts\n\nBy default the ``ipynb`` style uses the default ``matplotlib`` font. However, one can set its favorite font from a TIFF file:\n\n```python\nimport lovelyplots as lp\nimport matplotlib.pyplot as plt\n\nplt.style.use('ipynb')\nlp.utils.set_font('my_font.tiff')\n```\n\n\n\n\n# Tips and Tricks\n\n## Adobe Illustrator\n\nUnfortunately, ``mathtext`` (and thus nicely formated scientific notation) will mess up ``Adobe illustrator`` ability to detect text objects, and is thus not activated by default. If you wish to use it, please add the style ``use_mathtext``.\n\n## Latex and SVG files\nBy default, the ``ipynb`` style sets ``svg.fonttype: none``. This allows for plots saved as ``.svg`` not to carry font information. Consequently, when opened in another environement, the plot will be generated with the default system font.\n\nFor example, this allows ``.svg`` plots imported inside a ``Latex`` file to directly be generated with the proper document font, without you having to manually edit the fonts to match your document's font. Additonally, you can open the ``.svg`` file as text file, find the ugly ``1e10`` scientific notation and replace it with ``$10^10$`` so that it is nicely formated when included in your ``.tex`` file.\n\nAn example of how to show an svg in a ``.tex`` file:\n\n```tex\n\\usepackage{svg}\n\n\\begin{figure}[htbp]\n \\centering\n \\includesvg{myfig.svg}\n\\end{figure}\n```\n## Retina displays\n\nFor those using ``IPython`` notebooks, you can set retina display support by adding the following lines to the begining on your python script:\n\n\n```python\nimport lovelyplots as lp\nlp.utils.set_retina()\n```\n## Useth in Google Colab\nTo use on Google Colab, you will need to run the following code:\n```python\n!pip install lovelyplots\nimport lovelyplots\nplt.style.reload_library()\nplt.style.use('ipynb')\n```\n\n# Acknowledgements\n\nThis reprository was inspired by [SciencePlots](https://github.com/garrettj403/SciencePlots), but adds different styles and crucial functionalities for useth in ``.tex`` files and ``Adobe Illustrator``.\n\n\n# Citing \n\nIf you use LovelyPlots, please consider citing: \n\n @software{killian_sheriff_2022_6916993,\n author = {Killian Sheriff},\n title = {{LovelyPlots, a collection of matplotlib \n stylesheets for scientific figures}},\n month = jul,\n year = 2022,\n publisher = {Zenodo},\n version = {v0.0.26\\_LovelyPlots},\n doi = {10.5281/zenodo.6916993},\n url = {https://doi.org/10.5281/zenodo.6916993}\n }\n",
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