This is a library intended to produce ready to publish (and not so heavy) plots.

Prerequisites

• Python 2.7
• matplotlib
• numpy
• scipy
• h5py
• colorcet (optional)
• imgtops

All packages can be installed via pip

$ pip install <package-name>

except imgtops, which is a tool not in the PyPI.

imgtops can be downloaded from here. In order to have imgtops properly installed I did the following:

* Install python package `pillow`
* Modify the `setup.py`. Change PIL for pillow

Examples

Linear plot

import numpy as np
import PypersPlots as pp
pp.latexify()
x = np.linspace(0.0, 2.0*np.pi, 50)
fig,ax = pp.initPlot()
ax.plot(x,np.sin(x))
ax.plot(x,np.cos(x))
pp.decor(ax,xlim=(0.0,2.0*np.pi),ylim=(-1.0,1.0),ylabel=r"$\mathcal{L}$",xlabel=r"$\mathcal{X}$")
pp.printer(fig,'sin')

Contours plot

import numpy as np
import PypersPlots as pp
pp.latexify()
x, y = np.meshgrid(*(np.linspace(-0.6,0.6,500),)*2)
z = np.sin(20*x**2)*np.cos(30*y)
fig,ax = pp.initPlot()
CS = pp.theContours(ax,x,y,z)
pp.decor(ax,ylabel=r"$\mathcal{Y}$",xlabel=r"$\mathcal{X}$")
pp.printer(fig,'contours')

Gradient plot

import numpy as np
import PypersPlots as pp
import extractor as ext
import colorcet as cc
N = 150
data = "temperature.dat"
fname = 'gradient'
x, y, T = ext.dataExtract3col(data, N)
fig, ax = pp.initPlot()
fig.canvas.draw_idle()
CM = pp.theGradient(ax,x,y,T, (0.0, 1.e2),cmap=cc.cm['inferno'])
pp.decor(ax,xlabel=r"$\mathcal{X}$",ylabel=r"$\mathcal{Y}$")
CB = pp.setColorBar(CM,fig,ax,cblabel=r"$\mathcal{L}$",pad=0.05)
pp.printer(fig,'gradient')

More elaborate example examples

Streams and fields

Temperature profiles from internal shocks simulations

Magnetobremsstrahlung

To see how these examples were produced go to the wiki. I will be placing more elaborated stuff there.

Recomendations and observations

Interacting with Python

For a good interactive plotting I suggest using IPython (v2.7). Once in the command line call the magic command %matplotlib osx, if you are using macOS:

%matplotlib osx

To see the backends available for matplotlib just type:

%matplotlib -l

For your benefit

This module is under development. Please if you have any issue, comment or upgrades they are most welcome.