Modifying axes on matplotlib colorbar plot of 2D array
10,510
You want to look at the imshow options "origin" and "extent", I think.
import matplotlib.pyplot as plt
import numpy as np
x,y = np.mgrid[-2:2:0.1, -2:2:0.1]
data = np.sin(x)*(y+1.05**(x*np.floor(y))) + 1/(abs(x-y)+0.01)*0.03
fig = plt.figure()
ax = fig.add_subplot(111)
ticks_at = [-abs(data).max(), 0, abs(data).max()]
cax = ax.imshow(data, interpolation='nearest',
origin='lower', extent=[0.0, 0.1, 0.0, 0.1],
vmin=ticks_at[0], vmax=ticks_at[-1])
cbar = fig.colorbar(cax,ticks=ticks_at,format='%1.2g')
fig.savefig('out.png')
Author by
Doa
Updated on July 22, 2022Comments
-
Doa almost 2 years
I have a 2D numpy array that I want to plot in a colorbar. I am having trouble changing the axis so that they display my dataset. The vertical axis goes 'down' from 0 to 100, whereas I want it to go 'up' from 0.0 to 0.1. So I need to do two things:
- Flip the array using np.flipud() and then 'flip' the axis as well
- Change the labels to go from 0.0 to 0.1, instead of 0 to 100
Here is an example of what my colorbar plot currently looks like:
And here is the code:
data = np.load('scorr.npy') (x,y) = np.unravel_index(data.argmax(), data.shape) max=data[x][y] fig = plt.figure() ax = fig.add_subplot(111) cax = ax.imshow(data, interpolation='nearest') cbar = fig.colorbar(cax, ticks=[-max, 0, max]) cbar.ax.set_yticklabels([str(-max), '0', str(max)]) plt.show()
Does anybody have any suggestions? Thanks in advance!