Use df onset and duration, not var
@@ -54,8 +54,8 @@ class Convolve(Transformation):
elif model != 'fir':
raise ValueError("Model must be one of 'spm', 'glover', or 'fir'.")
- min_interval = min(np.ediff1d(np.sort(var.onset)).min(),
- var.duration.min())
+ min_interval = min(np.ediff1d(np.sort(df.onset)).min(),
+ df.duration.min())
oversampling = np.ceil(1 / (min_interval * sampling_rate))
convolved = hrf.compute_regressor(
