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pythonarraysnumpymatplotlibimshow

Imshow heatmap with array of arrays - problem with final plot/image

I'd like to plot imshow heatmap but the final image looks very small and disproportional. My data represent a distance measured between atoms (cca 10 atoms of one molecule to cca 30 atoms of other molecule) - the result is array of arrays. I prepared similar output for illustration, however my original dataset is bigger:

import numpy as np
array1 = np.random.randint(20, size=30)
array2 = np.random.randint(20, size=30)
array3 = np.random.randint(20, size=30)
array4 = np.random.randint(20, size=30)
array5 = np.random.randint(20, size=30)
array6 = np.random.randint(20, size=30)
array7 = np.random.randint(20, size=30)
array8 = np.random.randint(20, size=30)
array9 = np.random.randint(20, size=30)
arrayOfArrays = np.array([array1, array2, array3, array4, array5, array6, array7, array8, array9])

Then I wanted to make heatmap to see distances between the atoms, so this is my code:

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
im = ax.imshow(arrayOfArrays, origin='upper')

#this is here because I use this approach to define xticks and yticks in my original plot  - here I modified the code with "len(range(0,30))" but in my original plot there is number of atoms for which I measured the distances (something like n_atoms=len(dataset1))
n_1=len(range(0,30))
n_2=len(range(0,9))
tick_interval = 1
ax.set_yticks(np.arange(n_2)[::tick_interval])
ax.set_xticks(np.arange(n_1)[::tick_interval])

# colorbar
cbar = fig.colorbar(im)

The final image created with this particular plot looks already small but the image with my original data is even smaller and I can't see the colors inside at all.

For illustration:this is how it looks with original measured data

I'd really appreciate any suggestions where the problem is or which part of the code should be edited? I tried to edit size of picture, add "interpolation", "ascpect"...

Solution

  • I like the answer from TomiOck, but I believe that JohanC is right is you have a dataset for which you have many more columns than rows. This can be fixed by adding aspect='auto' to the imshow command.

    Here is my attempt:

    import numpy as np
nrows = 9
ncols = 30
minv = 0 # inclusive
maxv = 20 # exclusive
arrayofArrays = np.random.randint(low=minv, high=maxv, size=(nrows,ncols))

    You can generate the random data in one numpy line.

    import matplotlib.pyplot as plt

fig, ax = plt.subplots(figsize=(14,8)) # width and height in inches
im = ax.imshow(arrayOfArrays, origin='upper', aspect='auto', interpolation='None')

n_1 = np.arange(ncols)
n_2 = np.arange(nrows)
tick_interval = 1
ax.set_yticks(n_2[::tick_interval])
ax.set_xticks(n_1[::tick_interval])

# colourbar
cbar = fig.colorbar(im)

    The aspect='auto' stretches your image such that it fill the figure. I also recommend using interpolation='None' to be absolutely sure that matplotlib does not change the colours much (https://matplotlib.org/stable/gallery/images_contours_and_fields/interpolation_methods.html). outcome