Windowed time lagged cross correlations

synchrony04.py

# 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),int(seconds*fps+1))]
    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=[0,301], xlabel='Offset',ylabel='Window epochs')
ax.set_xticks([0, 50, 100, 151, 201, 251, 301])
ax.set_xticklabels([-150, -100, -50, 0, 50, 100, 150]);

# 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),int(seconds*fps+1))]
    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=[0,301], xlabel='Offset',ylabel='Epochs')
ax.set_xticks([0, 50, 100, 151, 201, 251, 301])
ax.set_xticklabels([-150, -100, -50, 0, 50, 100, 150]);