# [Mne_analysis] TFR plot

JR KING jeanremi.king at gmail.com
Fri Nov 10 10:04:31 EST 2017
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```If the aim is to clearly see low frequencies while ranging up to high
frequencies, it is probably better to use a logarithmic frequency scale.

You can do this by simply changing the axis: e.g.

plt.gca().set_yscale('log')

Better, you can do this when you compute the time frequency decomposition.
For example in this tutorial (
https://martinos.org/mne/stable/auto_examples/time_frequency/plot_time_frequency_simulated.html),
change

freqs = np.arange
<https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.arange.html#numpy.arange>(5.,
100., 3.)

by

freqs = np.l <https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.arange.html#numpy.arange>ogspace(np.log10(5.),
np.log10(100.), 32)

HTH
JR

On 10 November 2017 at 09:37, Chris Holdgraf <choldgraf at berkeley.edu> wrote:

> Yeah I usually do this by creating *two* separate pcolor plots, and then
> arranging the axes so that it *looks* like they're part of the same axis w/
> a break in the middle
> --
>
> On Fri, Nov 10, 2017 at 3:24 AM Jérémy Giroud <jeremy.giroud at gmail.com>
> wrote:
>
>> thanks !
>>
>>
>>
>> 2017-11-09 21:07 GMT+01:00 Alexandre Gramfort <
>> alexandre.gramfort at inria.fr>:
>>
>>> hi,
>>>
>>> you can use pcolor eg
>>> https://matplotlib.org/examples/pylab_examples/pcolor_demo.html
>>> but a simpler option would be to put np.nan in values you don't want
>>> to plot and matplotlib
>>> with mask it.
>>>
>>> HTH
>>> Alex
>>>
>>> On Thu, Nov 9, 2017 at 6:58 PM, Jérémy Giroud <jeremy.giroud at gmail.com>
>>> wrote:
>>> > Hello all,
>>> >
>>> > Do you know if it is possible to crop a tfr plot like in the attached
>>> > picture to get rid of unwanted frequency bands. Thanks in advance.
>>> >
>>> > Jeremy
>>> >
>>> >
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