crippledlambda crippledlambda - 3 months ago 32
Python Question

matplotlib: overlay plots with different scales?

So far I have the following code:

colors = ('k','r','b')
ax = []
for i in range(3):
ax.append(plt.axes())
plt.plot(datamatrix[:,0],datamatrix[:,i],colors[i]+'o')
ax[i].set(autoscale_on=True)


With the
autoscale_on=True
option for each axis, I thought each plot should have its own y-axis limits, but it appears they all share the same value (even if they share different axes). How do I set them to scale to show the range of each
datamatrix[:,i]
(just an explicit call to
.set_ylim()
?) And also, how can I create an offset y-axis for the third variable (
datamatrix[:,2]
) that might be required above? Thanks all.

Answer

It sounds like what you're wanting is subplots... What you're doing now doesn't make much sense (Or I'm very confused by your code snippet, at any rate...).

Try something more like this:

import matplotlib.pyplot as plt
import numpy as np

fig, axes = plt.subplots(nrows=3)

colors = ('k', 'r', 'b')
for ax, color in zip(axes, colors):
    data = np.random.random(1) * np.random.random(10)
    ax.plot(data, marker='o', linestyle='none', color=color)

plt.show()

enter image description here

Edit:

If you don't want subplots, your code snippet makes a lot more sense.

You're trying to add three axes right on top of each other. Matplotlib is recognizing that there's already a subplot in that exactly size and location on the figure, and so it's returning the same axes object each time. In other words, if you look at your list ax, you'll see that they're all the same object.

If you really want to do that, you'll need to reset fig._seen to an empty dict each time you add an axes. You probably don't really want to do that, however.

Instead of putting three independent plots over each other, have a look at using twinx instead.

E.g.

import matplotlib.pyplot as plt
import numpy as np
# To make things reproducible...
np.random.seed(1977)

fig, ax = plt.subplots()

# Twin the x-axis twice to make independent y-axes.
axes = [ax, ax.twinx(), ax.twinx()]

# Make some space on the right side for the extra y-axis.
fig.subplots_adjust(right=0.75)

# Move the last y-axis spine over to the right by 20% of the width of the axes
axes[-1].spines['right'].set_position(('axes', 1.2))

# To make the border of the right-most axis visible, we need to turn the frame
# on. This hides the other plots, however, so we need to turn its fill off.
axes[-1].set_frame_on(True)
axes[-1].patch.set_visible(False)

# And finally we get to plot things...
colors = ('Green', 'Red', 'Blue')
for ax, color in zip(axes, colors):
    data = np.random.random(1) * np.random.random(10)
    ax.plot(data, marker='o', linestyle='none', color=color)
    ax.set_ylabel('%s Thing' % color, color=color)
    ax.tick_params(axis='y', colors=color)
axes[0].set_xlabel('X-axis')

plt.show()

enter image description here