https://github.com/phyks/replot

An attempt at an easier API to plot graphs using Matplotlib.
https://github.com/phyks/replot

Last synced: 6 months ago
JSON representation

An attempt at an easier API to plot graphs using Matplotlib.

Host: GitHub
URL: https://github.com/phyks/replot
Owner: Phyks
License: mit
Created: 2016-03-01T13:51:51.000Z (almost 10 years ago)
Default Branch: master
Last Pushed: 2016-05-19T15:17:22.000Z (over 9 years ago)
Last Synced: 2025-01-22T12:23:01.886Z (11 months ago)
Language: Jupyter Notebook
Homepage:
Size: 12.3 MB
Stars: 0
Watchers: 3
Forks: 0
Open Issues: 11
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

          Replot

======

This repo is an attempt for a better API to plot graphs with

[Matplotlib](http://matplotlib.org/) in Python.

`Matplotlib` is a wonderful Python modules to plot data series, functions and

so on. However, I think the API is quite verbose. This is an attempt at

providing a better frontend API on top of `matplotlib` for easy and fast

plotting, especially at prototyping time.

## Features

These are the current features. I will extend the module whenever I feel the

need to introduce new functions and methods. Please let me know about any bad

design in the API, or required feature!



    Saner default plots

    Matplotlib plots are quite ugly by default, colors are not really

    suited for optimal black and white print, or ease reading for colorblind

    people. This module defines a clean default colorscheme to solve it (based

    on Colorbrewer Q10 palette). It also provides direct access to the

    Tableau10 and Colorbrewer Q9 palettes.


    
Support with statement

    Ever got tired of having to start any figure with a call to

    matplotlib.pyplot.subplots()? This module abstracts it using

    with statement. New figures are defined by a

    with statement, and are shown automatically (or

    saved) upon leaving the with context.

    

Plot functions

    Ever got annoyed by the fact that matplotlib can only

    plot point series and not evaluate a function à la Mathematica?

    This module let you do things like plot(sin, (-10, 10)) to

    plot a sine function between -10 and 10, using adaptive sampling.

    

Order of call of methods is no longer important

    When calling a method from matplotlib, it is directly

    applied to the figure, and not deferred to the final render call. Then, if

    calling matplotlib.pyplot.legend() before

    having actually plotted anything, it will fail. This is not

    the case with this module, as it abstracts on top of

    matplotlib and do the actual render only when the figure is

    to be shown. Even after having called the show

    method, you can still change everything in your figure!


    
Does not interfere with matplotlib



    You can still use the default matplotlib if you want, as

    matplotlib state and parameters are not directly affected by

    this module, contrary to what seaborn do when you import it

    for instance.


    
Useful aliases

    You think loc="top left" is easier to remember than

    loc="upper left" in a matplotlib.pyplot.legend()

    call? No worry, this module aliases it for you! (same for "bottom" with

    respect to "lower"). Similarly, you can use xrange or

    xlim arguments to specify axes ranges (respectively

    yrange / ylim).


    
Automatic legend

    If any of your plots contains a label keyword, a legend

    will be added automatically on your graph (you can still explicitly tell

    it not to add a legend by setting the legend attribute to

    False).


    
Use LaTeX rendering in matplotlib, if

    available.

    If replot finds LaTeX installed on your

    machine, it will overload matplotlib settings to use

    LaTeX rendering.


    
Handle subplots more easily

    Have you ever struggled with matplotlib to define a subplot

    grid and arrange your plot? replot lets you describe your

    grid visually using ascii art!


    
"Gridify"

    You have some plots that you would like to arrange into a grid, to

    compare them easily, but you do not want to waste time setting up a grid

    and placing your plots at the correct place? replot handles

    it for you out of the box!


    
Easy plotting in log scale, orthonormal axis etc

    

replot defines logplot and

    loglogplot shortcuts functions to plot in log scale

    or loglog scale. Use orthonormal=True on a

    plot command to plot using orthonormal axes.



## Examples

A more up to date doc is still to be written, but you can have a look at the

`Examples.ipynb`

[Jupyter](https://github.com/jupyter/notebook/) notebook for

examples, which should cover most of the use cases.

## License

This Python module is released under MIT license. Feel free to contribute and

reuse. For more details, see `LICENSE.txt` file.

## Thanks

* [Matplotlib](http://matplotlib.org/) for their really good backend.

* [Seaborn](https://github.com/mwaskom/seaborn) and

  [prettyplotlib](http://blog.olgabotvinnik.com/prettyplotlib/) which gave me

  the original idea.

* [This code](http://central.scipy.org/item/53/1/adaptive-sampling-of-1d-functions)

  from scipy central for a base code for adaptive sampling.

* [Palettable](https://jiffyclub.github.io/palettable/) for palettes.

* [Cubehelix](http://www.ifweassume.com/2013/05/cubehelix-or-how-i-learned-to-love.html)

  colorscheme for nice black and white printing and desaturation compatibility.

ecosyste.ms

Data

Tools

Indexes

Applications

Experiments

Awesome

https://github.com/phyks/replot

Awesome Lists containing this project

README