diff --git a/src/graph_tool/inference/minimize.py b/src/graph_tool/inference/minimize.py index fbca5ede503f5c9c7c582c53564f2eba276733e8..13bfca42a51b342a66403b4102dbc893c2a4fce5 100644 --- a/src/graph_tool/inference/minimize.py +++ b/src/graph_tool/inference/minimize.py @@ -119,7 +119,7 @@ def minimize_blockmodel_dl(g, B_min=None, B_max=None, b_min=None, b_max=None, mcmc_args={}, anneal_args={}, mcmc_equilibrate_args={}, shrink_args={}, mcmc_multilevel_args={}, verbose=False): - """Fit the stochastic block model, by minimizing its description length using an + r"""Fit the stochastic block model, by minimizing its description length using an agglomerative heuristic. Parameters @@ -286,7 +286,7 @@ def minimize_nested_blockmodel_dl(g, B_min=None, B_max=None, b_min=None, mcmc_args={}, anneal_args={}, mcmc_equilibrate_args={}, shrink_args={}, mcmc_multilevel_args={}, verbose=False): - """Fit the nested stochastic block model, by minimizing its description length + r"""Fit the nested stochastic block model, by minimizing its description length using an agglomerative heuristic. Parameters @@ -479,4 +479,4 @@ def minimize_nested_blockmodel_dl(g, B_min=None, B_max=None, b_min=None, **dmask(hierarchy_minimize_args, ["B_max", "B_min", "bisection_args", "verbose"])) - return state \ No newline at end of file + return state diff --git a/src/graph_tool/inference/nested_blockmodel.py b/src/graph_tool/inference/nested_blockmodel.py index dd6525dbd2622bee95539aaab3885bc85579b822..7a831f33f4196a5cc051a544ec89c1a9b73fa1fc 100644 --- a/src/graph_tool/inference/nested_blockmodel.py +++ b/src/graph_tool/inference/nested_blockmodel.py @@ -999,7 +999,7 @@ class NestedBlockState(object): def hierarchy_minimize(state, B_min=None, B_max=None, b_min=None, b_max=None, frozen_levels=None, bisection_args={}, epsilon=1e-8, verbose=False): - """Attempt to find a fit of the nested stochastic block model that minimizes the + r"""Attempt to find a fit of the nested stochastic block model that minimizes the description length. Parameters diff --git a/src/graph_tool/topology/__init__.py b/src/graph_tool/topology/__init__.py index 87ea69a3ca7b4cea10613589b1eaaa4d4df47460..16b0b2cd089ae4f769513d9ba1db2f15a1e36207 100644 --- a/src/graph_tool/topology/__init__.py +++ b/src/graph_tool/topology/__init__.py @@ -849,7 +849,7 @@ def max_cliques(g): yield c def min_spanning_tree(g, weights=None, root=None, tree_map=None): - """ + r""" Return the minimum spanning tree of a given graph. Parameters @@ -1043,7 +1043,7 @@ def random_spanning_tree(g, weights=None, root=None, tree_map=None): def dominator_tree(g, root, dom_map=None): - """Return a vertex property map the dominator vertices for each vertex. + r"""Return a vertex property map the dominator vertices for each vertex. Parameters ---------- @@ -1777,7 +1777,7 @@ def shortest_distance(g, source=None, target=None, weights=None, negative_weights=False, max_dist=None, directed=None, dense=False, dist_map=None, pred_map=False, return_reached=False, dag=False): - """Calculate the distance from a source to a target vertex, or to of all + r"""Calculate the distance from a source to a target vertex, or to of all vertices from a given source, or the all pairs shortest paths, if the source is not specified. @@ -2034,7 +2034,7 @@ def shortest_distance(g, source=None, target=None, weights=None, def shortest_path(g, source, target, weights=None, negative_weights=False, pred_map=None, dag=False): - """Return the shortest path from ``source`` to ``target``. + r"""Return the shortest path from ``source`` to ``target``. Parameters ---------- @@ -2552,7 +2552,7 @@ def all_circuits(g, unique=False): def pseudo_diameter(g, source=None, weights=None): - """ + r""" Compute the pseudo-diameter of the graph. Parameters @@ -3180,7 +3180,7 @@ def edge_reciprocity(g): def tsp_tour(g, src, weight=None): - """Return a traveling salesman tour of the graph, which is guaranteed to be + r"""Return a traveling salesman tour of the graph, which is guaranteed to be twice as long as the optimal tour in the worst case. Parameters @@ -3277,4 +3277,4 @@ def sequential_vertex_coloring(g, order=None, color=None): return color -from .. flow import libgraph_tool_flow \ No newline at end of file +from .. flow import libgraph_tool_flow