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src='https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/andreasfuhr/38e0946c4456d70028d4482fe18dcc45/raw/Sciplot-pypi-version.json'\u003e](https://pypi.org/project/sciplot)\n[\u003cimg src='https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/andreasfuhr/ae1a5002566bdc7d8d143aab72331657/raw/Sciplot-github-version.json'\u003e](https://github.com/andreasfuhr/sciplot)\n\n*Format Matplotlib scientific plots*\n\n*Sciplot* is a Python package that formats scientific plots created with Matplotlib in a\nuser-friendly, yet highly customizable way.\nIt makes typesetting in LaTeX possible and comes with several methods that makes plotting more\nstraightforward and less cluttered, without sacrificing full control over plot settings.\n\nTwo examples of plots created with Sciplot:\n\n\u003cimg src='https://github.com/andreasfuhr/sciplot/raw/7a1b143b5101a5e9b19f03cf654a1060a7f3a489/example_plots/Line_plot_2021-05-23T13.37.png' alt=\"example_plot\" width=\"500\"/\u003e\n\u003cimg src=\"https://github.com/andreasfuhr/sciplot/raw/7a1b143b5101a5e9b19f03cf654a1060a7f3a489/example_plots/Histogram_plot_2021-05-23T13.38.png\" alt=\"example_plot\" width=\"800\"/\u003e\n\nThe Sciplot package was developed by [Andreas Führ](https://www.linkedin.com/in/fuhrandreas/) in May 2021.\n\n## Installation and getting started\n\nTo install the latest release from PyPI, use the following command:\n\n```bash\npip install sciplot\n```\n\nTo install the latest commit, please use:\n\n```bash\npip install git+https://github.com/andreasfuhr/sciplot.git\n```\n\n\u003cbr/\u003e\u003cbr/\u003e\nFormatting plots in Matplotlib is based on a functional `with`-statement context. A MWE can be demonstrated as follows:\n\n```python\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport sciplot\n\nx = np.arange(0, 2 * np.pi, 1e-2)\ny1 = np.sin(2 * x + np.pi)\ny2 = np.cos(2 * x + np.pi)\n\nsciplot.set_size_cm(5)  # Alternatively, set figure size with Matplotlib directly\n\nwith sciplot.style():\n    plt.plot(x, y1, x, y2)\n    plt.xticks(\n        np.linspace(0, 2 * np.pi, 5),\n        ['$0$', r'$\\frac{\\pi}{2}$', r'$\\pi$', r'$\\frac{3\\pi}{2}$', r'$2\\pi$']\n    )\n    plt.show()\n```\n\nThis produces the following output:\n\n\u003cimg src='https://github.com/andreasfuhr/sciplot/raw/7a1b143b5101a5e9b19f03cf654a1060a7f3a489/example_plots/MWE_plot_2021-05-23T13.33.png' alt=\"example_plot\" width=\"300\"/\u003e\n\n## Overview\n\n### Key Features\n\n* User-friendly. A *style context manager* is used for all Matplotlib related user code and can be passed several\nthemes and arguments to alter the look of the plot, such as:\n  * LaTeX typesetting\n  * serif or sans serif font\n  * dark mode\n  * [locale](https://docs.oracle.com/cd/E23824_01/html/E26033/glset.html) string (for correct decimal\n    separator etc.)\n* Implements LaTeX kernel for typesetting plots. A versatile LaTeX preamble is included that is specifically\ncreated and optionally editable for mathematics- and physics-oriented papers, theses and presentations. Both the\n[siunitx](https://ctan.org/pkg/siunitx) and [physics](https://www.ctan.org/pkg/physics) LaTeX packages are included by\ndefault in the parameter settings.\n* Easy customization. Most settings have been moved to parameters files, which are imported to the context manager and\nconfigured with `matplotlibrc`. The **user is encouraged to edit** these accessible and highly readable YAML parameters\nfiles, or **create new theme-associated parameter files**, whom are found with the `sciplot.get_paramters_dir()`\nmethod.\n* Includes a set of useful methods relevant during plotting:\n  * `sciplot.set_size_cm()` for setting figure sizes in centimeters\n  * `sciplot.set_legend()` for customizing the content and position of plot legends\n  * `sciplot.get_color_lst()` for extracting a list of colors of specified length and from a given Seaborn colormap\n  * `sciplot.save_time_stamped_figure` for saving plots in an easy manner with time stamped file names\n\n### Disadvantages\n\n* Slow. LaTeX typesetting, turned on by default, can take quite some time to compile. Loading the parameters is however\nnot known from experience to be time consuming.\n* Only compatible with Python 3.7 and later. The 3.3.4 version of Matplotlib fixes several bugs that directly solves\nsome earlier issues with this package.\n\nIt should be noted that although this package is in many ways similar to [[1]](#1), which is a recommended\nalternative approach, Sciplot has been independently developed and has a multitude of structural and functional\ndifferences.\n\n## How to use Sciplot\n\n### The style context and themes\n\nThe `sciplot.style()` context manager is the core feature of Sciplot. It is a powerful and versetile tool for a\ncomplete control of the looks of plots created with Matplotlib. The context manager operates with two input arguments:\n`theme` and `locale_setting`. By default, creating plots within the style context\n\n```python\nwith sciplot.style():\n    ...\n```\n\nis equivalent to the following style context:\n\n```python\nwith sciplot.style(theme='default', locale_setting='sv_SE.UTF-8'):\n    ...\n```\n\n#### Themes\n\nA handful of themes are bundled with Sciplot. The `theme` argument can be passed either a single theme as a *string* or\na *list of theme strings*. Since all themes are not mutually exclusive w.r.t. Matplotlib settings, the themes are\nsegmented such that Sciplot distinguishes which style settings are more important and becomes prioritized (higher\nnumber means lower priority):\n\nPriority | Theme            | Description\n:------- | :--------------- | :----------\n0        | *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`.\n1        | ***alpha***      | Predefined, contentless user theme. Intended for editing by user.\n2        | ***beta***       | Predefined, contentless user theme. Intended for editing by user.\n3        | ***gamma***      | Predefined, contentless user theme. Intended for editing by user.\n4        | ***no-latex***   | No local LaTeX kernel is used for typesetting.\n5        | ***serif***      | *Computer Modern Roman* used as text and math font, with typesetting in LaTeX.\n6        | ***sans-serif*** | *Computer Modern Roman Sans Serif* used as text and math font, with typesetting in LaTeX.\n7        | ***dark***       | Uses Matplotlib's `dark_background` style and comes with a set of colours suitable for plotting against a black background.\n8        | ***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.\n–        | ***clean***      | Not technically a theme. Simpy inactivates the ***default*** theme.\n\n#### Locales\n\nThe `locale_setting` argument lets the user determine the *locale* to be used in a plot, thereby determining a set of\nparameters that defines the user's language, region and other regionally based settings and whom are used by Matplotlib\nto alter the appearance of a plot. To see all available locales, one can call the `sciplot.get_available_locals`\nmethod for a console printout.\n\n#### Code example\n\nIf a plot style with dark theme, LaTeX, a serif font (Computer Modern Roman) and local settings for the United States\nis requested, the style context should be initiated with\n\n```python\nwith sciplot.style(['dark', 'serif'], 'en_US'):\n    ...\n```\n\n## Future improvements\n\nThe package is still in its infancy and is planned to be expanded in features and configurability. Here is a list of\nwhat is in the pipeline:\n* Documentation of source code\n* Instructions on how to install a local LaTeX distribution\n* Making it possible to choose LaTeX fonts. As of currently, *Computer Modern Roman* and *Computer Modern Roman Sans\nSerif* are the only two font options for both text and mathematical notation.\n* Include more example plots in documentation\n* Write instructions on how to use the package\n* Address potential issues with user defined themes and updating sciplot\n* Move sciplot methods not used by the user outside of `sciplot.main`\n\n### Table of proposed themes not yet implemented\n\nName of theme                            | Priority | Background color | Font                         | Seaborn colormap | Figure size\n:--------------------------------------- | :------- | :--------------- | :--------------------------- | :--------------- | :--------------------------------\n***antique***                            | low      | white            | Garamond                     | *TBD*            | -\n***ieee_column***                        | medium   | white            | ?\u003csup id=\"a1\"\u003e[1](#f1)\u003c/sup\u003e | *TBD*            | 88 mm\u003csup id=\"a1\"\u003e[2](#f2)\u003c/sup\u003e\n***ieee_page***                          | low      | white            | ?\u003csup id=\"a1\"\u003e[1](#f1)\u003c/sup\u003e | *TBD*            | 181 mm\u003csup id=\"a1\"\u003e[2](#f2)\u003c/sup\u003e\n***grid***                               | high\n\n\u003cb id=\"f1\"\u003e1\u003c/b\u003e: One of the following Open Type fonts are suggested to be used: Times New Roman, Helvetica, Arial,\nCambria or Symbol [[3]](#3).\n\n\u003cb id=\"f2\"\u003e2\u003c/b\u003e: See [[3]](#3) for a description of sizes that graphics should be.\n\n## Citing Sciplot\n\nTo cite this Python package, please use the following BibTeX citation:\n\n```tex\n@article{Sciplot,\n  author       = {Andreas H. Führ},\n  title        = {{andreasfuhr/sciplot}},\n  month        = May,\n  year         = 2021,\n  version      = {0.8.1},\n  url          = {https://github.com/andreasfuhr/sciplot}\n}\n```\n\nNote that under the current license, citing this package is not necessary. The creator will however be happy and\nthankful for any recognition.\n\n## References\n\n\u003ca id=\"1\"\u003e[1]\u003c/a\u003e\nJ.D. Garrett and H. Peng,\n*garrettj403/SciencePlots*,\nver. 1.0.7.\nZenodo,\nFeb. 2021.\n\\[Online].\ndoi: [10.5281/zenodo.4106649](http://doi.org/10.5281/zenodo.4106649)\n\n\u003ca id=\"1\"\u003e[2]\u003c/a\u003e\nD.A. Green,\n\"A colour scheme for the display of astronomical intensity images,\"\nin *Bulletin of the Astronomical Society of India*, vol. 39, pp. 289–295, 2011.\n\\[Online].\nAvailable: [arXiv:1108.5083](https://arxiv.org/abs/1108.5083).\n\n\u003ca id=\"2\"\u003e[3]\u003c/a\u003e\n\"Preparation of papers for IEEE Transactions and Journals (December 2013),\"\nin IEEE Transactions on Consumer Electronics,\nvol. 63,\nno. 1,\npp. c3-c3,\nFebruary 2017,\ndoi: [10.1109/TCE.2017.7932035](http://doi.org/10.1109/TCE.2017.7932035)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandreasfuhr%2Fsciplot","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fandreasfuhr%2Fsciplot","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandreasfuhr%2Fsciplot/lists"}