P = ax.scatter(Vr,Dm,Mo,c=misfits,vmin=0.3,vmax=1,s=2,edgecolor='none',marker='o')įig.colorbar(p, ticks=arange(0.3,1+0.1,0. By default, matplotlib will find the minimum and maximum of your data on both axes and use this as the range to plot your data. fig = figure(2)Īx = fig.add_subplot(111, projection='3d') Any help or advice would be very welcome.
PYPLOT SCATTER AXIS RANGE CODE
This is the entire code for this figure in particular. If I try to set the z-axis as logarithmic (by adding the line ax.set_zscale('log')), the resulting scaling does not seem to work properly, because the ordering of each power is not equally spaced:Īnd finally, If I try to limit the z-axis to the range of values that I'm interested (by simply adding the line ax.set_zlim3d(1e17,1e19)), instead of cutting the dots to the defined range in this axis, they seem to scape from the graph:
This is the original figure with linear axes and without restricting the z-axis: pylab.ylim ( 0,1000) has no effect, unfortunately. 0,1000 The FFT plot of my data (a column in a text file) results in a (inf.) spike so that the actual data is not visible. Maybe there is a bug in Matplotlib, or I'm not using the commands correctly. 291 How can I set the y axis range of the second subplot to e.g. I tried different options that I saw in other forums, but the plot does not work properly.
I'm plotting the parameter ( Mo) in the z-axis, and would be great to set only this axis to be logarithmic with the range of values that matters. One of those parameters ( Mo) has a variability of values between 10^15 and 10^20 approximately, and I'm interested in plotting the good solutions (blue dots), which vary from 10^17 to 10^19. I performed a Monte Carlo inversion of three parameters, and now I'm trying to plot them in a 3-D figure using Matplotlib.
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