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- # Windowed time lagged cross correlation
- seconds = 5
- fps = 30
- no_splits = 20
- samples_per_split = df.shape[0]/no_splits
- rss=[]
- for t in range(0, no_splits):
- d1 = df['S1_Joy'].loc[(t)*samples_per_split:(t+1)*samples_per_split]
- d2 = df['S2_Joy'].loc[(t)*samples_per_split:(t+1)*samples_per_split]
- rs = [crosscorr(d1,d2, lag) for lag in range(-int(seconds*fps-1),int(seconds*fps))]
- rss.append(rs)
- rss = pd.DataFrame(rss)
- f,ax = plt.subplots(figsize=(10,5))
- sns.heatmap(rss,cmap='RdBu_r',ax=ax)
- ax.set(title=f'Windowed Time Lagged Cross Correlation',xlim=[0,300], xlabel='Offset',ylabel='Window epochs')
- ax.set_xticklabels([int(item-150) for item in ax.get_xticks()]);
- # Rolling window time lagged cross correlation
- seconds = 5
- fps = 30
- window_size = 300 #samples
- t_start = 0
- t_end = t_start + window_size
- step_size = 30
- rss=[]
- while t_end < 5400:
- d1 = df['S1_Joy'].iloc[t_start:t_end]
- d2 = df['S2_Joy'].iloc[t_start:t_end]
- rs = [crosscorr(d1,d2, lag, wrap=False) for lag in range(-int(seconds*fps-1),int(seconds*fps))]
- rss.append(rs)
- t_start = t_start + step_size
- t_end = t_end + step_size
- rss = pd.DataFrame(rss)
- f,ax = plt.subplots(figsize=(10,10))
- sns.heatmap(rss,cmap='RdBu_r',ax=ax)
- ax.set(title=f'Rolling Windowed Time Lagged Cross Correlation',xlim=[0,300], xlabel='Offset',ylabel='Epochs')
- ax.set_xticklabels([int(item-150) for item in ax.get_xticks()]);
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