log xaxis for contourf

Hi to all,

I spent about 3 hours trying to fix a plotting problem I have with
matplotlib.pyplot...unfortunately without any sucess.

I want to have a logarithmic xaxis in my contourf plot. Since this is not
directly possible, I took the log10 of the axis and simply used them. Doing
so, I get some white space inside the plot for some reason. Can someone give
me a hint why this is happening? I use the following fraction of code:

#without log scale
plt.figure(11), plt.cla()
cf1 = plt.contourf(f_psd_welch, traverseCoord,
10*np.log10(psd_hotwire_FS_welch),cmap='viridis')
cbar1 = plt.colorbar(cf1)
plt.xlim([min(f_psd_welch), max(f_psd_welch)]), plt.ylim([-50, 50])

<http://matplotlib.1069221.n5.nabble.com/file/t5112/normalX.png>

#with logscale
plt.figure(11), plt.cla()
cf1 = plt.contourf(np.log10(f_psd_welch), traverseCoord,
10*np.log10(psd_hotwire_FS_welch),cmap='viridis')
cbar1 = plt.colorbar(cf1)
plt.xlim([min(np.log10(f_psd_welch[1:])), max(np.log10(f_psd_welch[1:]))]),
plt.ylim([-50, 50])

<http://matplotlib.1069221.n5.nabble.com/file/t5112/logX.png>

The output is attached.
I would be happy about any help!

Thanks,
Dimitri

···

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You are giving contour very irregularly spaced data in x. Its trying to come up w/ those last few contours with very little data and I guess its misbehaving.

If it were me, I?d interpolate onto a regular log10 grid first and then send to contour. Then you have control over how the interpolation takes place...

You may also want to consider just using pcolormesh.

Cheers, Jody

···

On Nov 23, 2017, at 18:42 PM, dimitrif <df388 at cam.ac.uk> wrote:

Hi to all,

I spent about 3 hours trying to fix a plotting problem I have with
matplotlib.pyplot...unfortunately without any sucess.

I want to have a logarithmic xaxis in my contourf plot. Since this is not
directly possible, I took the log10 of the axis and simply used them. Doing
so, I get some white space inside the plot for some reason. Can someone give
me a hint why this is happening? I use the following fraction of code:

#without log scale
plt.figure(11), plt.cla()
cf1 = plt.contourf(f_psd_welch, traverseCoord,
10*np.log10(psd_hotwire_FS_welch),cmap='viridis')
cbar1 = plt.colorbar(cf1)
plt.xlim([min(f_psd_welch), max(f_psd_welch)]), plt.ylim([-50, 50])

<http://matplotlib.1069221.n5.nabble.com/file/t5112/normalX.png>

#with logscale
plt.figure(11), plt.cla()
cf1 = plt.contourf(np.log10(f_psd_welch), traverseCoord,
10*np.log10(psd_hotwire_FS_welch),cmap='viridis')
cbar1 = plt.colorbar(cf1)
plt.xlim([min(np.log10(f_psd_welch[1:])), max(np.log10(f_psd_welch[1:]))]),
plt.ylim([-50, 50])

<http://matplotlib.1069221.n5.nabble.com/file/t5112/logX.png>

The output is attached.
I would be happy about any help!

Thanks,
Dimitri

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Dimitri,

If you send me your data (f_psd_welch, traverseCoord and
psd_hotwire_FS_welch) I will take a look at the problem.

Ian

···

On 24 November 2017 at 02:42, dimitrif <df388 at cam.ac.uk> wrote:

Hi to all,

I spent about 3 hours trying to fix a plotting problem I have with
matplotlib.pyplot...unfortunately without any sucess.

I want to have a logarithmic xaxis in my contourf plot. Since this is not
directly possible, I took the log10 of the axis and simply used them. Doing
so, I get some white space inside the plot for some reason. Can someone
give
me a hint why this is happening? I use the following fraction of code:

#without log scale
plt.figure(11), plt.cla()
cf1 = plt.contourf(f_psd_welch, traverseCoord,
10*np.log10(psd_hotwire_FS_welch),cmap='viridis')
cbar1 = plt.colorbar(cf1)
plt.xlim([min(f_psd_welch), max(f_psd_welch)]), plt.ylim([-50, 50])

<http://matplotlib.1069221.n5.nabble.com/file/t5112/normalX.png>

#with logscale
plt.figure(11), plt.cla()
cf1 = plt.contourf(np.log10(f_psd_welch), traverseCoord,
10*np.log10(psd_hotwire_FS_welch),cmap='viridis')
cbar1 = plt.colorbar(cf1)
plt.xlim([min(np.log10(f_psd_welch[1:])), max(np.log10(f_psd_welch[1:]))
]),
plt.ylim([-50, 50])

<http://matplotlib.1069221.n5.nabble.com/file/t5112/logX.png>

The output is attached.
I would be happy about any help!

Thanks,
Dimitri

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Hi Jody,

I have tried pcolormesh but it 'smears' the data too much due to
interpolation.

Maybe there is no other way than interpolating manually to have full
control. I just wonder, it seems like it works in Matlab without any issues
but matpotlib struggles with log axis for contourf.

Dimitri

···

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Hi Ian,

I sent you an email.

Dimitir

···

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Hi Dimitri,

The problem is that your x data (f_psd_welch) begins at zero. Log10 of zero
is minus infinity. Some of the contour x-values will be exactly zero and
hence log10 of them is -inf; most will be larger than zero and hence log10
of them will be finite. Drawing polygons between finite and infinite values
is bound to look messy.

There is usually a numpy warning when you try np.log10(0.0), but it depends
on some python settings so you may not have seen it.

You had nearly solved the problem yourself as when you are calculating the
minimum x-value to limit the contour plot axis you use
np.min(np.log10(f_psd_welch[1:])) which excludes the first value which is
log10(0.0) = -inf.

There are 2 possible solutions:

1) Exclude the x=0 values from the plot, i.e. use
cf1 = plt.contourf(np.log10(f_psd_welch[1:]), traverseCoord,
10*np.log10(psd_hotwire_FS_welch[:,1:]),cmap='viridis')

2) Add a very small amount to all x-values, i.e.
cf1 = plt.contourf(np.log10(f_psd_welch + 1e-10), traverseCoord,
10*np.log10(psd_hotwire_FS_welch),cmap='viridis')

We could add an explicit check to ensure that all arrays that are passed to
contour contain only finite values, but then we would have to have a policy
of doing that across all matplotlib functions which would be a major impact
to the library and (arguably) unnecessarily affect the performance of 99.9%
of mpl calls that don't need the check. The existing numpy log10 warning
should suffice.

Ian

···

On 24 November 2017 at 12:53, dimitrif <df388 at cam.ac.uk> wrote:

Hi Ian,

I sent you an email.

Dimitir

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Hi Ian,

Amazing, thank you very much for your help! Now, it works as expected.

I actually got the following warning 'RuntimeWarning: divide by zero
encountered in log10' when running the script but I couldn't connect it to
the outcome. Sometimes a new pair of eyes and a fresh mind helps to solve
the issue in a few seconds.

Sounds logically for me that changing the library would not be necessary. I
wonder why contourf does not have the option to switch the axes to log
similar to loglog or semilogx? That would look much nicer and save a lot of
time adjusting the axes of contourf.

Dimitri

···

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Dimitri,

Although there is no explicit 'log axis' argument that contour accepts, you
can use this:

plt.contourf(f_psd_welch, traverseCoord, 10*np.log10(psd_hotwire_FS_welch))
plt.gca().set_xscale('log')
plt.xlim([np.min(f_psd_welch[1:]), np.max(f_psd_welch[1:])])

Ian

···

On 24 November 2017 at 20:03, dimitrif <df388 at cam.ac.uk> wrote:

Hi Ian,

Amazing, thank you very much for your help! Now, it works as expected.

I actually got the following warning 'RuntimeWarning: divide by zero
encountered in log10' when running the script but I couldn't connect it to
the outcome. Sometimes a new pair of eyes and a fresh mind helps to solve
the issue in a few seconds.

Sounds logically for me that changing the library would not be necessary. I
wonder why contourf does not have the option to switch the axes to log
similar to loglog or semilogx? That would look much nicer and save a lot of
time adjusting the axes of contourf.

Dimitri

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Hi Ian,

I didn't know how to do that. That is actuaclly exactly what I want. Thank
you very much once again.

Dimitri

···

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