[Mne_analysis] TFR plot

[Jérémy Giroud]

thank you !


2017-11-10 16:04 GMT+01:00 JR KING <jeanremi.king at gmail.com>:

> 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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