python - How do I set limits on ticks, colors, and labels for colorbar contourf matplotlib -

i've spatial field of values i'm outputting on regular interval on course of day. i'm plotting contourf , following on course of day's data:

• limit colors on colobar values represent min , max of day's data
• hold color bar static on 24 hourly plots @ max , min of days data
• hold labels static on course of 24 hours

for example:

data = np.random.uniform(0, 5, size=(24,30,30)) data[3,:,:]=np.random.uniform(1,3,size=(30,30))  # example of bad plot fgsize=(12,4) numrecs = np.size(data,axis=0) cbar_min = np.min(data) cbar_max = np.max(data) cbarlabels = np.linspace(np.floor(cbar_min), np.ceil(cbar_max), num=5, endpoint=true)   tt in range(0, numrecs):     plt.figure(figsize=fgsize, dpi=80)     plt.title('this title')     plt.contourf(data[tt, :, :], 35, vmin=cbar_min, vmax=cbar_max, cmap='coolwarm')     cbar =plt.colorbar()     cbar.set_ticks(cbarlabels)     cbar.set_ticklabels(cbarlabels)     cbar.set_label('my data has units')     plt.show()     plt.close() 

here , example of bad plot. colors seem limited, color bar changes color/label limits. how fix this?

here example of good plot.

it turns out contourf bit tricky in setting levels colormap, see this answer. can proper limits , colours normalising contours, follows:

import numpy np import matplotlib.pyplot plt  data = np.random.uniform(0, 5, size=(24,30,30)) data[3,:,:]=np.random.uniform(1,3,size=(30,30))  # example of bad plot fgsize=(12,4) numrecs = np.size(data,axis=0) cbar_min = np.min(data) cbar_max = np.max(data) cbarlabels = np.linspace(np.floor(cbar_min), np.ceil(cbar_max), num=5, endpoint=true)  # set normalisation 35 levels (as in example) import matplotlib.colors mc levels = np.linspace(np.floor(cbar_min), np.ceil(cbar_max), 35) # draw 35 levels norm = mc.boundarynorm(levels, 256)  tt in range(0, numrecs):     print cbar_min, cbar_max     plt.figure(figsize=fgsize, dpi=80)     plt.title('this title')      # draw levels, proper normalisation, here:     plt.contourf(data[tt, :, :], levels, vmin=cbar_min, vmax=cbar_max, cmap='coolwarm', levels=levels, norm=norm)      cbar = plt.colorbar()     cbar.set_ticks(cbarlabels)     cbar.set_ticklabels(cbarlabels)     cbar.set_label('my data has units')     plt.show()