CODEWITHSUNDEEP
pythonmatplotlib
Eigenvalue
Eigenvalue

Reputation: 1133

Making a contour plot with solutions from systems of differential equations with pylab

So, I'm solving a system of differential equations numerically i have x,y,z each a solution. Each array is one dimensional and and for example x[0],y[0],z[0] goes with a point in space. i want to graph these in a contour like the usual x y z coordinates, it says i need z to be a 2d array, i know how to make a mesh from x and y, but how do i do this to z? I have made a mesh out of the x,y, but for z i don't know what to do.

if someone could give me insight it would be much appreciated.

Upvotes: 1

Views: 1817

Answers (2)

berna1111
berna1111

Reputation: 1861

It looks like you are looking for line or scatter plots instead of contour.

Upvotes: 0

ebarr
ebarr

Reputation: 7842

It is not enough to just mesh in x and y, you need to grid your data on a regular grid to be able to do a contour plot. To do this you should look into matplotlib.mlab.griddata (http://matplotlib.org/examples/pylab_examples/griddata_demo.html).

I'll paste the example code from the link below with some extra comments:

from numpy.random import uniform, seed
from matplotlib.mlab import griddata
import matplotlib.pyplot as plt
import numpy as np

# Here the code generates some x and y coordinates and some corresponding z values.
seed(0)
npts = 200
x = uniform(-2,2,npts)
y = uniform(-2,2,npts)
z = x*np.exp(-x**2-y**2)

# Here you define a grid (of arbitrary dimensions, but equal spacing) onto which your data will be mapped
xi = np.linspace(-2.1,2.1,100)
yi = np.linspace(-2.1,2.1,200)

# Map the data to the grid to get a 2D array of remapped z values
zi = griddata(x,y,z,xi,yi,interp='linear')

# contour the gridded data, plotting dots at the nonuniform data points.
CS = plt.contour(xi,yi,zi,15,linewidths=0.5,colors='k')
CS = plt.contourf(xi,yi,zi,15,cmap=plt.cm.rainbow,
                  vmax=abs(zi).max(), vmin=-abs(zi).max())

plt.colorbar() # draw colorbar

# Plot the original sampling
plt.scatter(x,y,marker='o',c='b',s=5,zorder=10)
plt.xlim(-2,2)
plt.ylim(-2,2)
plt.title('griddata test (%d points)' % npts)
plt.show()

Upvotes: 1

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