CODEWITHSUNDEEP
pythonnumpymatplotlib
Nicolas Martin
Nicolas Martin

Reputation: 595

Time series plotted with imshow

I tried to make the title as clear as possible although I am not sure it is completely limpid. I have three series of data (number of events along time). I would like to do a subplots were the three time series are represented. You will find attached the best I could come up with. The last time series is significantly shorter and that's why it is not visible on here.

I'm also adding the corresponding code so you can maybe understand better why I'm trying to do and advice me on the proper/smart way to do so. 

import numpy as np
import matplotlib.pyplot as plt

x=np.genfromtxt('nbr_lig_bound1.dat')
x1=np.genfromtxt('nbr_lig_bound2.dat')
x2=np.genfromtxt('nbr_lig_bound3.dat')
# doing so because imshow requieres a 2D array
# best way I found and probably not the proper way to get it done
x=np.expand_dims(x, axis=0)
x=np.vstack((x,x))
x1=np.expand_dims(x1, axis=0)
x1=np.vstack((x1,x1))
x2=np.expand_dims(x2, axis=0)
x2=np.vstack((x2,x2))
# hoping that this would compensate for sharex shrinking my X range to 
# the shortest array 
ax[0].set_xlim(1,24)
ax[1].set_xlim(1,24)
ax[2].set_xlim(1,24)


fig, ax = plt.subplots(nrows=3, ncols=1, figsize=(6,6), sharex=True)
fig.subplots_adjust(hspace=0.001) # this seem to have no effect 

p1=ax[0].imshow(x1[:,::10000], cmap='autumn_r')
p2=ax[1].imshow(x2[:,::10000], cmap='autumn_r')
p3=ax[2].imshow(x[:,::10000], cmap='autumn')

Here is what I could reach so far: Actual results

and here is a scheme of what I wish to have since I could not find it on the web. In short, I would like to remove the blank spaces around the plotted data in the two upper graphs. And as a more general question I would like to know if imshow is the best way of obtaining such plot (cf intended results below).

enter image description here

Upvotes: 3

Views: 1319

Answers (1)

wflynny
wflynny

Reputation: 18521

Using fig.subplots_adjust(hspace=0) sets the vertical (height) space between subplots to zero but doesn't adjust the vertical space within each subplot. By default, plt.imshow has a default aspect ratio (rc image.aspect) usually set such that pixels are squares so that you can accurately recreate images. To change this use aspect='auto' and adjust the ylim of your axes accordingly.

For example:

# you don't need all the `expand_dims` and `vstack`ing.  Use `reshape`
x0 = np.linspace(5, 0, 25).reshape(1, -1)
x1 = x0**6
x2 = x0**2

fig, axes = plt.subplots(3, 1, sharex=True)
fig.subplots_adjust(hspace=0)

for ax, x in zip(axes, (x0, x1, x2)):
    ax.imshow(x, cmap='autumn_r', aspect='auto') 
    ax.set_ylim(-0.5, 0.5) # alternatively pass extent=[0, 1, 0, 24] to imshow
    ax.set_xticks([]) # remove all xticks
    ax.set_yticks([]) # remove all yticks

plt.show()

yields

enter image description here

To add a colorbar, I recommend looking at this answer which uses fig.add_axes() or looking at the documentation for AxesDivider (which I personally like better).

Upvotes: 2

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