在不更改图的情况下重新缩放y轴

Question

What I have

I am trying to create a 'heatmap' of values using python 3 .
I'm stuck on the spacing between the y-ticks, and several SO questions could not help me out...

The code that I have so far is the following:

data = np.load('path\to\data\datafile.npy')

# plot using imshow (and use interpolation)
plt.imshow(data,
           cmap          = 'RdBu_r', 
           aspect        = 'auto', 
           vmin          = -.4,
           vmax          =  .4,
           origin        = 'lower',
           extent        = [-1000, 4500, 2, 48], 
           interpolation = 'hanning')

# plt parameters
plt.xlim(-750, 4250)
plt.colorbar()
plt.vlines(0, 
           frequencies[0], 
           frequencies[-1], 
           colors = 'black',
           label = 'Stimulus onset',
           linewidth = 2.5)
plt.legend(loc=(1,1.04))
plt.title('Time-frequency using Morlet wavelets\nSubject: {}'.format(SUB_ID))
plt.ylabel('Frequency (in Hz)')
plt.xlabel('Time (in ms)')
plt.show()

This gives me the following plot:

Plot with wrong y-axis scaling

What I want

The labels on the y-axis are wrong.
Specifically, the y-axis should have the following labels (which are spaced in a logarithmic fashion):

In [15]:
# parameters
min_freq = 2;
max_freq = 48;
num_frex = 20;

# define frequencies of interest
frequencies = np.logspace(np.log10(min_freq), 
                          np.log10(max_freq), 
                          num_frex)
frequencies

Out[15]: 
array([ 2.        ,  2.36413729,  2.79457255,  3.30337659,  3.90481788,
        4.61576277,  5.45614844,  6.44954198,  7.62380134,  9.01185651,
       10.652633  , 12.59214343, 14.8847779 , 17.59482922, 20.7982959 ,
       24.58501342, 29.06117345, 34.35230187, 40.60677887, 48.        ])

The resulting plot should look like this (when focusing on the y-axis):

Plot with correct y-label spacing

So:

• The plot should not be altered
• The y-axis labels should be converted from linear to log
• The spacing between the labels should be as in the latter plot

datafile.npy can be found here

Answer 1

You just need to provide the plot with a custom ytick list:

# parameters
min_freq = 2;
max_freq = 48;
num_frex = 20;

# define frequencies of interest
frequencies = np.logspace(np.log10(min_freq), 
                      np.log10(max_freq), 
                      num_frex)

plt.yticks(frequencies)

see https://matplotlib.org/3.1.0/api/_as_gen/matplotlib.pyplot.yticks.html#matplotlib.pyplot.yticks for more