如何为z = f（x，y）绘制平滑的2D颜色图

Question

I am trying to plot 2D field data using matplotlib. So basically I want something similar to this:

In my actual case I have data stored in a file on my harddrive. However for simplicity consider the function z = f(x, y). I want a smooth 2D plot where z is visualised using color. I managed the plotting with the following lines of code:

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(-1, 1, 21)
y = np.linspace(-1, 1, 21)
z = np.array([i*i+j*j for j in y for i in x])

X, Y = np.meshgrid(x, y)
Z = z.reshape(21, 21)

plt.pcolor(X, Y, Z)
plt.show()

However, the plot I obtain is very coarse. Is there a very simple way to smooth the plot? I know something similar is possible with surface plots, however, those are 3D. I could change the camera angle to obtain a 2D representation, but I am convinced there is an easier way. I also tried imshow but then I have to think in graphic coordinates where the origin is in the upper left corner.

Problem solved

I managed to solve my problem using:

plt.imshow(Z,origin='lower',interpolation='bilinear')

Answer 1

If you can't change your mesh granularity, then try to go with imshow , which will essentially plot any 2D matrix as an image, where the values of each matrix cell represent the color to make that pixel. Using your example values:

In [3]: x = y = np.linspace(-1, 1, 21)
In [4]: z = np.array([i*i+j*j for j in y for i in x])
In [5]: Z = z.reshape(21, 21)
In [7]: plt.imshow(Z, interpolation='bilinear')
Out[7]: <matplotlib.image.AxesImage at 0x7f4864277650>
In [8]: plt.show()

Answer 2

you can use contourf

plt.contourf(X, Y, Z)

EDIT:

For more levels (smoother colour transitions), you can use more levels (contours)

For example:

plt.contourf(X, Y, Z, 100)