Metadata-Version: 2.1
Name: sciplot
Version: 0.8.1
Summary: Format Matplotlib scientific plots
Home-page: https://github.com/andreasfuhr/sciplot
Author: Andreas Führ
Author-email: andreas.fuhr@outlook.com
License: MIT
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Classifier: Natural Language :: English
Classifier: Framework :: Matplotlib
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE.txt

# Sciplot
[<img src='https://img.shields.io/pypi/v/sciplot/0.8.1'>](https://pypi.org/project/sciplot) 
[<img src='https://img.shields.io/static/v1?label=repo&color=blue&style=flat&logo=github&message=v.0.8.1'>](https://github.com/andreasfuhr/sciplot)

*Format Matplotlib scientific plots*


*Sciplot* is a Python package that formats scientific plots created with Matplotlib in a 
user-friendly, yet highly customizable way.
It makes typesetting in LaTeX possible and comes with several methods that makes plotting more 
straightforward and less cluttered, without sacrificing full control over plot settings.

Two examples of plots created with Sciplot:

<img src='https://github.com/andreasfuhr/sciplot/raw/7a1b143b5101a5e9b19f03cf654a1060a7f3a489/example_plots/Line_plot_2021-05-23T13.37.png' alt="example_plot" width="500"/>
<img src="https://github.com/andreasfuhr/sciplot/raw/7a1b143b5101a5e9b19f03cf654a1060a7f3a489/example_plots/Histogram_plot_2021-05-23T13.38.png" alt="example_plot" width="800"/>


The Sciplot package was developed by [Andreas Führ](https://www.linkedin.com/in/fuhrandreas/) in May 2021.

## Installation and getting started
To install the latest release from PyPI, use the following command:
```
pip install sciplot
```
To install the latest commit, please use:
```
pip install git+https://github.com/andreasfuhr/sciplot.git
```

<br/><br/>
Formatting plots in Matplotlib is based on a functional `with`-statement context. A MWE can be demonstrated as follows:
```python
import matplotlib.pyplot as plt
import numpy as np
import sciplot

x = np.arange(0, 2 * np.pi, 1e-2)
y1 = np.sin(2 * x + np.pi)
y2 = np.cos(2 * x + np.pi)

sciplot.set_size_cm(5)  # Alternatively, set figure size with Matplotlib directly

with sciplot.style():
    plt.plot(x, y1, x, y2)
    plt.xticks(
        np.linspace(0, 2 * np.pi, 5),
        ['$0$', r'$\frac{\pi}{2}$', r'$\pi$', r'$\frac{3\pi}{2}$', r'$2\pi$']
    )
    plt.show()
```
This produces the following output:

<img src='https://github.com/andreasfuhr/sciplot/raw/7a1b143b5101a5e9b19f03cf654a1060a7f3a489/example_plots/MWE_plot_2021-05-23T13.33.png' alt="example_plot" width="300"/>


## Overview

### Key Features:
* User-friendly. A *style context manager* is used for all Matplotlib related user code and can be passed several 
themes and arguments to alter the look of the plot, such as:
    * LaTeX typesetting
    * serif or sans serif font
    * dark mode
    * [locale](https://docs.oracle.com/cd/E23824_01/html/E26033/glset.html) string (for correct decimal 
    separator etc.)
* Implements LaTeX kernel for typesetting plots. A versatile LaTeX preamble is included that is specifically 
created and optionally editable for mathematics- and physics-oriented papers, theses and presentations. Both the 
[siunitx](https://ctan.org/pkg/siunitx) and [physics](https://www.ctan.org/pkg/physics) LaTeX packages are included by 
default in the parameter settings.
* Easy customization. Most settings have been moved to parameters files, which are imported to the context manager and 
configured with `matplotlibrc`. The **user is encouraged to edit** these accessible and highly readable YAML parameters
files, or **create new theme-associated parameter files**, whom are found with the `sciplot.get_paramters_dir()`
method.
* Includes a set of useful methods relevant during plotting:
    * `sciplot.set_size_cm()` for setting figure sizes in centimeters
    * `sciplot.set_legend()` for customizing the content and position of plot legends
    * `sciplot.get_color_lst()` for extracting a list of colors of specified length and from a given Seaborn colormap
    * `sciplot.save_time_stamped_figure` for saving plots in an easy manner with time stamped file names


### Disadvantages:
* Slow. LaTeX typesetting, turned on by default, can take quite some time to compile. Loading the parameters is however
not known from experience to be time consuming.
* Only compatible with Python 3.7 and later. The 3.3.4 version of Matplotlib fixes several bugs that directly solves 
some earlier issues with this package. 


It should be noted that although this package is in many ways similar to [[1]](#1), which is a recommended 
alternative approach, Sciplot has been independently developed and has a multitude of structural and functional 
differences.


## How to use Sciplot


### The style context and themes

The `sciplot.style()` context manager is the core feature of Sciplot. It is a powerful and versetile tool for a 
complete control of the looks of plots created with Matplotlib. The context manager operates with two input arguments:
`theme` and `locale_setting`. By default, creating plots within the style context 
```Python
with sciplot.style():
    ...
```
is equivalent to the following style context:
```Python
with sciplot.style(theme='default', locale_setting='sv_SE.UTF-8'):
    ...
```


#### Themes

A handful of themes are bundled with Sciplot. The `theme` argument can be passed either a single theme as a *string* or
a *list of theme strings*. Since all themes are not mutually exclusive w.r.t. Matplotlib settings, the themes are 
segmented such that Sciplot distinguishes which style settings are more important and becomes prioritized (higher 
number means lower priority):

Priority | Theme            | Description
:------- | :--------------- | :----------
0        | *Custom theme*   | A theme entirely made by the user. This is done by creating a parameter file in the `sciplot.parameter` directory. A theme named **my_fabulous_theme** will for example extract parameter settings from a file named `my_fabulous_theme.yml`.
1        | ***alpha***      | Predefined, contentless user theme. Intended for editing by user.
2        | ***beta***       | Predefined, contentless user theme. Intended for editing by user.
3        | ***gamma***      | Predefined, contentless user theme. Intended for editing by user.
4        | ***no-latex***   | No local LaTeX kernel is used for typesetting.
5        | ***serif***      | *Computer Modern Roman* used as text and math font, with typesetting in LaTeX.
6        | ***sans-serif*** | *Computer Modern Roman Sans Serif* used as text and math font, with typesetting in LaTeX.
7        | ***dark***       | Uses Matplotlib's `dark_background` style and comes with a set of colours suitable for plotting against a black background.
8        | ***default***    | The default theme. Always active unless the ***clean*** "theme" is used. Uses LaTeX typesetting and *Computer Modern Roman Sans Serif* as text and math font. Initialises basic figure settings for linewidths, ticks, legends, font sizes, dpi, margins, etc. Also comes with the *cubehelix* colourmap [[2]](#2) as well as basic plot colours and styles.
–        | ***clean***      | Not technically a theme. Simpy inactivates the ***default*** theme.


#### Locales

The `locale_setting` argument lets the user determine the *locale* to be used in a plot, thereby determining a set of
parameters that defines the user's language, region and other regionally based settings and whom are used by Matplotlib
to alter the appearance of a plot. To see all available locales, one can call the `sciplot.get_available_locals` 
method for a console printout.


#### Code example

If a plot style with dark theme, LaTeX, a serif font (Computer Modern Roman) and local settings for the United States
is requested, the style context should be initiated with
```Python
with sciplot.style(['dark', 'serif'], 'en_US'):
    ...
```


## Future improvements

The package is still in its infancy and is planned to be expanded in features and configurability. Here is a list of 
what is in the pipeline:
* Documentation of source code
* Instructions on how to install a local LaTeX distribution
* Making it possible to choose LaTeX fonts. As of currently, *Computer Modern Roman* and *Computer Modern Roman Sans 
Serif* are the only two font options for both text and mathematical notation.
* Include more example plots in documentation
* Write instructions on how to use the package
* Address potential issues with user defined themes and updating sciplot
* Move sciplot methods not used by the user outside of `sciplot.main`


### Table of proposed themes not yet implemented:

Name of theme                            | Priority | Background color | Font                         | Seaborn colormap | Figure size
:--------------------------------------- | :------- | :--------------- | :--------------------------- | :--------------- | :----------
***antique***                            | low      | white            | Garamond                     | *TBD*            | -
***ieee_column***                        | medium   | white            | ?<sup id="a1">[1](#f1)</sup> | *TBD*            | 88 mm<sup id="a1">[2](#f2)</sup>
***ieee_page***                          | low      | white            | ?<sup id="a1">[1](#f1)</sup> | *TBD*            | 181 mm<sup id="a1">[2](#f2)</sup>
***grid***                               | high

<b id="f1">1</b>: One of the following Open Type fonts are suggested to be used: Times New Roman, Helvetica, Arial, 
Cambria or Symbol [[3]](#3).

<b id="f2">2</b>: See [[3]](#3) for a description of sizes that graphics should be.


## Citing Sciplot

To cite this Python package, please use the following BibTeX citation:

```
@article{Sciplot,
  author       = {Andreas H. Führ},
  title        = {{andreasfuhr/sciplot}},
  month        = May,
  year         = 2021,
  version      = {0.8.1},
  url          = {https://github.com/andreasfuhr/sciplot}
}
```
Note that under the current license, citing this package is not necessary. The creator will however be happy and 
thankful for any recognition.


## References

<a id="1">[1]</a>
J.D. Garrett and H. Peng,
*garrettj403/SciencePlots*,
ver. 1.0.7.
Zenodo,
Feb. 2021.
\[Online].
doi: [10.5281/zenodo.4106649](http://doi.org/10.5281/zenodo.4106649)

<a id="1">[2]</a>
D.A. Green,
"A colour scheme for the display of astronomical intensity images,"
in *Bulletin of the Astronomical Society of India*, vol. 39, pp. 289–295, 2011.
\[Online].
Available: [arXiv:1108.5083](https://arxiv.org/abs/1108.5083).

<a id="2">[3]</a>
"Preparation of papers for IEEE Transactions and Journals (December 2013),"
in IEEE Transactions on Consumer Electronics,
vol. 63,
no. 1,
pp. c3-c3,
February 2017,
doi: [10.1109/TCE.2017.7932035](http://doi.org/10.1109/TCE.2017.7932035)

