[Mne_analysis] cwt and visualization

[Nico Adelhöfer]

Hello Jean-Rémi,

thanks a lot! The code for cwt_morlet you provided worked. However,  
the y-axis labeling doesn't show the frequencies but the position of  
the analyzed frequency in the array. For example:

when freqs = [0, 20, 60], then the y-axis will be labeled 0, 1, 2  
instead of 0, 20, 60.

Is there a way around it? While at this issue, the x-axis shows  
seconds*sfreq, but I'd like to be labeled as seconds.

In other words: Is there a way to change the axis labeling without  
changing the content?

I hope you can help me with this one.

Thanks,
Nico



Quoting JR KING <jeanremi.king at gmail.com>:

> Hi Nico,
>
> You can check how to apply and plot time frequency analyses in this example:
> http://martinos.org/mne/stable/auto_examples/time_frequency/plot_time_frequency_simulated.html
>
> The main function boils down to:
>
> import numpy as np
> from mne.time_frequency import tfr_morlet
> freqs = np.linspace(5, 45, 20)  # an array of floats
> power = tfr_morlet(epochs, freqs=freqs, n_cycles=5, return_itc=False)
> power.plot([0])
>
>
> If you wish to use arrays directly, instead of mne `Epochs` objects as
> above, you can indeed use cwt_morlet:
>
> import numpy as np
> import matplotlib.pyplot as plt
> from mne.time_frequency import cwt_morlet
> n_signal, n_time = 10, 10000
> X = np.random.rand(n_signal, n_time)
> tfr = cwt_morlet(X, sfreq=1000, freqs = np.linspace(5, 45, 20), decim=10)
> power = np.abs(tfr)
> channel = 5
> plt.matshow(power[channel], origin='lower', cmap='viridis', aspect='auto')
> plt.show()
>
> Hope that helps,
>
> Best,
>
> Jean-Rémi
>
>
> On 13 July 2016 at 13:36, Nico Adelhöfer <nico.adelhoefer at st.ovgu.de> wrote:
>
>> Hello,
>>
>> I'm new to this mailing list and to MNE. I think so far it is really great!
>>
>> I have a few questions concerning the usage of the cwt_morlet
>> function; I want to plot a continuous wavelet transform from a single
>> EEG channel. I have a raw multi-channel .fif file, approximately 300s
>> long with a sampling frequency of 512 Hz. I'm interested in a
>> frequency range of approximately 0-45 Hz. How can I achieve this in
>> the simplest way possible? Specifically,
>>
>> 1. what datatype is the first parameter (X)? I tried the variable from
>> read_raw_fif, but that gives me "'tuple' object has no attribute
>> 'shape'". I also tried raw[4][0], which seems to work. But is this
>> really the correct approach?
>> 2. is freqs simply a list of integers with the frequencies of
>> interest? If the length is > 1, I get a Value Error ("Maximum allowed
>> size exceeded"). Does this mean I have to resample my raw data until
>> it works?
>> 3. when it worked, it created an np.ndarray with numbers with complex
>> parts. Do I see it correctly that the complex parts show the phase
>> while the real part shows the power value?
>> 4. how can I visualize the result?
>>
>> Sorry for these basic questions. Help would be much appreciated!
>>
>> Nico
>>
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