How do I plot 3 dimensionally in a domain specified by a function in Python?

Question

So I am trying to plot 3 dimensionally with matplotlib.pyplot, but only in a specific domain whose boundary is set by a function. Here is the code

import numpy
from scipy.integrate import quad
import matplotlib.pyplot
import matplotlib.ticker
from mpl_toolkits.mplot3d import Axes3D

def get_x1min(pT, eta, rS):
    return (pT * numpy.exp(eta)) / (rS - pT * numpy.exp(- eta))

def get_x2(x1, pT, eta, rS):
    return (x1 * pT * numpy.exp(- eta)) / (x1 * rS - pT * numpy.exp(eta))

rS = 1960.0
eta = 0.0
pT = [66.0, 77.5, 89.5, 92.0, 94.0, 96.0, 98.0, 100.0, 103.0, 105.0, 107.0, 109.0, 111.0, 113.0, 118.5, 136.5, 157.5, 182.0, 200.0, 209.5, 241.5, 278.5, 321.0, 370.0, 426.5, 492.0]

fig = matplotlib.pyplot.figure()
ax = Axes3D(fig)
x1_test = numpy.linspace(0.1, 1.0, 20)
x1_test, pT = numpy.meshgrid(x1_test, pT)
x2_test = get_x2(x1_test, pT, eta, rS)
ax.plot_surface(x1_test, pT, x2_test, rstride=1, cstride=1, cmap=matplotlib.pyplot.get_cmap('rainbow'))
matplotlib.pyplot.show()

This works fine BUT the domain is a rectangle, and the only change needed is to have x1_test just start from a minimum that can be obtained from function get_x1min. Is there any method of doing it?

Thanks in advance!

Thomas Kühn · Accepted Answer · 2018-12-17 07:29:30Z

3

You can set the unwanted values to np.nan, then they will not be plotted. Note though that there seems to be some problems with the colormapping. You can get around this using the vmin and vmax keywords:

mask = x1_test< get_x1min(pT, eta, rS)
x2_test[mask] = numpy.nan

ax.plot_surface(
    x1_test, pT, x2_test, rstride=1, cstride=1,
    cmap=matplotlib.pyplot.get_cmap('rainbow'),
    vmin = numpy.nanmin(x2_test),
    vmax = numpy.nanmax(x2_test),    
    )

matplotlib.pyplot.show()

The rest of the code would stay the same. The result looks something like this:

edited Dec 17, 2018 at 7:29

answered Dec 17, 2018 at 7:22

Thomas Kühn

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