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Description
The layer_likelihood function in tests has a bottleneck the indexing of the transition matrix
pathpy/pathpy/classes/multi_order_model.py
Lines 473 to 480 in595fc2d
| transition_matrix=self.transition_matrices[l] | |
| factor_=paths.paths[k][p][1] | |
| forsinrange(len(nodes)-1): | |
| idx_s1=indexmaps[l][nodes[s+1]] | |
| idx_s0=indexmaps[l][nodes[s]] | |
| trans_mat=transition_matrix[idx_s1,idx_s0] | |
| likelihood+=np.log(trans_mat)*factor_ | |
Some stats changing the type of sparse matrix used:
| dense | lil | csr | csc | |
|---|---|---|---|---|
| layer_likelihood | 2.8 | 3.5 | 10 | 27 |
| estimate_order | 16.8 | 17.6 | 24 | 42 |
| with instantiation | 29.1 | 30 | 41 | 51 |