Additional network formats¶
This module provides additional temporal network classes only available in the Python implementation.
-
class
tacoma.network_formats.
adjacency_matrices
(temporal_network, dtype=<class 'float'>)[source]¶ Bases:
object
Construct a temporal network as a list of adjacency matrices (
numpy.array
).Parameters: - temporal_network (
_tacoma.edge_changes
,_tacoma.edge_lists
,_tacoma.edge_changes_with_histograms
, or_tacoma.edge_lists_with_histograms
) – An instance of a temporal network. - dtype (numpy.dtype, default=float) – Data type of the matrix entries.
- temporal_network (
-
class
tacoma.network_formats.
sparse_adjacency_matrices
(temporal_network, sparse_generator=<Mock id='4380274448'>, dtype=<class 'float'>)[source]¶ Bases:
object
Construct a temporal network as a list of sparse adjacency matrices.
Parameters: - temporal_network (
_tacoma.edge_changes
,_tacoma.edge_lists
,_tacoma.edge_changes_with_histograms
, or_tacoma.edge_lists_with_histograms
) – An instance of a temporal network. - sparse_generator (instance of
scipy.sparse
matrix, default :scipy.sparse.csc_matrix
) – The sparse matrix class with which to construct all adjacency matrices. - dtype (numpy.dtype, default=float) – Data type of the matrix entries.
- temporal_network (