[Mne_analysis] Mask-enabled plot_topomap for TFR's and plot_compare_evoked for TFR's

[Alexandre Gramfort]

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hi Pooja,

I am trying to apply spatio-temporal clustering to the averaged TFR values.
> I am following the same steps as shown in the example:
> https://mne.tools/stable/auto_tutorials/stats-sensor-space/plot_stats_spatio_temporal_cluster_sensors.html,
> only difference is i am trying the steps on TFR's instead of evoked.
> I faced two difficulties during execution:
> 1.  When we do the plot_topomap for TFR's, there is no "mask" parameter,
> because of which I was unable to display the significant sensors only (like
> shown in the MNE example). Is there any way to plot only the significant
> sensors using plot_topomap when used on TFR's?
>

I am not sure what you expect to see.


> 2.  To plot the power (TFR's) pertaining to different conditions I used
> plot_compare-evoked, for which I created a dummy EvokedArray (using
> mne.EvokedArray) and placed the power data for each condition. Plot showed
> up the values in 1e15 range whereas the actual power values are in 1e-1
> range. Is there any way we can plot the power like we plot the evoked using
> the single function? Or am I doing something wrong?
>

mne plot functions use the channel types to scale the data during plotting.

maybe you can write your own plotting function using just matplotlib?

Alex



>
> It will be of great help, if you can suggest to me the solution.
> Thank You
>
> --
> Thank You
> Pooja Prabhu
>
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