For Kendall-tau maximization for now average ranks
@@ -73,7 +73,9 @@ def pool_rdm(rdms, method='cosine'):
rdm_vec = np.array([rankdata(v) for v in rdm_vec])
rdm_vec = np.mean(rdm_vec, axis=0, keepdims=True)
elif method == 'kendall':
- raise NotImplementedError('pooling for ranks not yet implemented!')
+ Warning('Noise ceiling for tau based on averaged ranks!')
+ rdm_vec = np.array([rankdata(v) for v in rdm_vec])
+ rdm_vec = np.mean(rdm_vec, axis=0, keepdims=True)
else:
raise ValueError('Unknown RDM comparison method requested!')
return RDMs(rdm_vec,
