python - Matplotlib so log axis only has minor tick mark labels at specified points. Also change size of tick labels in colorbar

Question

I am trying to create a plot but I just want the ticklabels to show as shown where the log scale is shown as above. I only want the minor ticklabel for 50, 500 and 2000 to show. Is there anyway to specify the minor tick labels to show?? I have been trying to figure this out for a bit but haven't found a good solution. All I can think of is to get the minorticklabels() and set the fontsize to 0. This is shown below the first snippet of code. I was hoping there was a more clean solution.

The other thing is changing the size of the ticklabels in the colorbar which I haven't figured out. If anyone knows of a way to do this please let me know because I don't see a method in colorbar that easily does this.

First code:

fig = figure(figto)
ax = fig.add_subplot(111)
actShape = activationTrace.shape
semitones = arange(actShape[1])
freqArray = arange(actShape[0])
X,Y = meshgrid(self.testFreqArray,self.testFreqArray)
Z = sum(activationTrace[:,:,beg:end],axis=2)
surf = ax.contourf(X,Y,Z, 8, cmap=cm.jet)
ax.set_position([0.12,0.15,.8,.8])
ax.set_ylabel('Log Frequency (Hz)')
ax.set_xlabel('Log Frequency (Hz)')
ax.set_xscale('log')
ax.set_yscale('log')
ax.xaxis.set_minor_formatter(FormatStrFormatter('%d'))
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
ax.tick_params(axis='both',reset=False,which='both',length=8,width=2)
self.plotSetAxisLabels(ax,22)
self.plotSetAxisTickLabels(ax,18)
cbar = fig.colorbar(surf, shrink=0.5, aspect=20, fraction=.12,pad=.02)
cbar.set_label('Activation',size=18)
return ax, cbar

Second Code:

fig = figure(figto)
ax = fig.add_subplot(111)
actShape = activationTrace.shape
semitones = arange(actShape[1])
freqArray = arange(actShape[0])
X,Y = meshgrid(self.testFreqArray,self.testFreqArray)
Z = sum(activationTrace[:,:,beg:end],axis=2)
surf = ax.contourf(X,Y,Z, 8, cmap=cm.jet)
ax.set_position([0.12,0.15,.8,.8])
ax.set_ylabel('Log Frequency (Hz)')
ax.set_xlabel('Log Frequency (Hz)')
ax.set_xscale('log')
ax.set_yscale('log')
ax.xaxis.set_minor_formatter(FormatStrFormatter('%d'))
ax.yaxis.set_minor_formatter(FormatStrFormatter('%d'))
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
ax.tick_params(axis='both',reset=False,which='both',length=8,width=2)
self.plotSetAxisLabels(ax,22)
self.plotSetAxisTickLabels(ax,18)
cbar = fig.colorbar(surf, shrink=0.5, aspect=20, fraction=.12,pad=.02)
cbar.set_label('Activation',size=18)
count = 0
for i in ax.xaxis.get_minorticklabels():
    if (count%4 == 0):
        i.set_fontsize(12)
    else:
        i.set_fontsize(0)
    count+=1
for i in ax.yaxis.get_minorticklabels():
    if (count%4 == 0):
        i.set_fontsize(12)
    else:
        i.set_fontsize(0)
    count+=1
return ax, cbar

For the colorbar: Another quick question if you don't mind because trying to figure it out but not entirely sure. I want to use scientific notation which I can get with ScalarFormatter. How do I set the number of decimal places and the multiplier?? I'd like it to be like 8x10^8 or .8x10^9 to save space instead of putting all those zeros. I figure there is multiple ways to do this inside the axes object but what do you reckon is the best way. I can't figure out how to change the notation when changing to the ScalarFormatter.

For the chart: Also, my data has points starting at 46 and then at successive multiplies of that multiplied by 2^(1/12) so 46,49,50,55,58,61...3132. These are all rounded but lie close to the 2^(1/12). I decided it better to place major tickers close to these numbers. Is the best way to use the fixed formatter and use a ticker every 15 or so in the freqArray. Then use a minor ticker at every other frequency. Can I do this and still maintain a log axis??

Answer 1

1) Use FixedLocator to statically define explicit tick locations.

2) Colorbar cbar will have an ax attribute that will provide access to the usual axis methods including tick formatting.

import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure()
ax = fig.add_subplot(111)
x = np.arange(10,3000,100)
y = np.arange(10,3000,100)
X,Y = np.meshgrid(x,y)
Z = np.random.random(X.shape)*8000000
surf = ax.contourf(X,Y,Z, 8, cmap=plt.cm.jet)
ax.set_ylabel('Log Frequency (Hz)')
ax.set_xlabel('Log Frequency (Hz)')
ax.set_xscale('log')
ax.set_yscale('log')
ax.xaxis.set_minor_formatter(plt.FormatStrFormatter('%d'))
# defining custom minor tick locations:
ax.xaxis.set_minor_locator(plt.FixedLocator([50,500,2000]))
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
ax.tick_params(axis='both',reset=False,which='both',length=8,width=2)
cbar = fig.colorbar(surf, shrink=0.5, aspect=20, fraction=.12,pad=.02)
cbar.set_label('Activation',size=18)
# access to cbar tick labels:
cbar.ax.tick_params(labelsize=5) 
plt.show()

Edit

If you want the tick marls, but you want to selectively show the labels, I see nothing wrong with your iteration, except I might use set_visible instead of making the fontsize zero.

You might enjoy finer control using a FuncFormatter where you can use the value or position of the tick to decide whether it gets shown:

def show_only_some(x, pos):
    s = str(int(x))
    if s[0] in ('2','5'):
        return s
    return ''

ax.xaxis.set_minor_formatter(plt.FuncFormatter(show_only_some))