def data_tooltip(self, x, y):
row = int(y)
if row >= 0 and row < len(self.raw_data):
all_raw_data = self.raw_data
data_idx = self.sort_idcs[row]
lag_diff = np.abs(x - self.raw_lags)
nearest_lag_idx = np.argmin(lag_diff)
nearest_lag = self.raw_lags[nearest_lag_idx]
value = all_raw_data[data_idx, nearest_lag_idx]
return ('%.2f - lag: %.2fms (template similarity: %.2f '
'CC metric %.2f)') % (value, nearest_lag,
self.score_x[data_idx],
self.score_y[data_idx])
else:
return ''
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