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from my_settings import *


    

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import mne
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
import os
    
%matplotlib qt
# change \"qt\" to \"inline\" for the figures to be place in the notebook"


    

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from tf_analyses_functions import calc_spatial_resolution, calc_wavelet_duration


    

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freqs = np.arange(6,90, 2)
n_cycles_2 = freqs/2.
n_cycles_3 = freqs/3.
n_cycles_33 = freqs/3.3
n_cycles_4 = freqs/4.


    

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wd_2 = calc_wavelet_duration(freqs=freqs, n_cycles=n_cycles_2)
wd_3 = calc_wavelet_duration(freqs=freqs, n_cycles=n_cycles_3)
wd_33 = calc_wavelet_duration(freqs=freqs, n_cycles=n_cycles_33)
wd_4 = calc_wavelet_duration(freqs=freqs, n_cycles=n_cycles_4)


    

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plt.figure()
plt.plot(freqs, wd_2, label="cycles = freqs / 2")
plt.plot(freqs, wd_3, label="cycles = freqs / 3")
plt.plot(freqs, wd_33, label="cycles = freqs / 3.3")
plt.plot(freqs, wd_4, label="cycles = freqs / 4")
plt.legend()
plt.title("Wavelet duration")
plt.show()


    

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sr_2 = calc_spatial_resolution(freqs=freqs, n_cycles=n_cycles_2)
sr_3 = calc_spatial_resolution(freqs=freqs, n_cycles=n_cycles_3)
sr_33 = calc_spatial_resolution(freqs=freqs, n_cycles=n_cycles_33)
sr_4 = calc_spatial_resolution(freqs=freqs, n_cycles=n_cycles_4)


    

In [8]:

    

sr_33


    

    
Out[8]:





array([6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,
       6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6])

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plt.figure()
plt.plot(freqs, sr_2, label="cycles = freqs / 2")
plt.plot(freqs, sr_3, label="cycles = freqs / 3")
plt.plot(freqs, sr_33, label="cycles = freqs / 3.3")
plt.plot(freqs, sr_4, label="cycles = freqs / 4")
plt.legend()
plt.title("Spatial resolution")
plt.show()


    

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In [4]:

    

cd data/tf_data/


    

    




/home/mje/Projects/malthe_alpha_project/data/tf_data

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itc_ctl_left = []

for subject in subjects[-3:]:
    data = np.load("itc_%s_8-12_Brodmann.17-lh_ctl_left_dSPM.npy" % subject)
    itc_ctl_left.append(data.mean(axis=0).mean(axis=0))


    

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itc_ctl_left = np.asarray(itc_ctl_left)


    

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itc_ctl_left.shape


    

    
Out[7]:





(3, 1251)

In [8]:

    

np.save("Foo.npy", itc_ctl_left)


    

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