Commit 5d5f626d authored by Alex Henrie's avatar Alex Henrie

Turn off escape sequences in docstrings

parent 12bdfb90
...@@ -119,7 +119,7 @@ def minimize_blockmodel_dl(g, B_min=None, B_max=None, b_min=None, b_max=None, ...@@ -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_args={}, anneal_args={},
mcmc_equilibrate_args={}, shrink_args={}, mcmc_equilibrate_args={}, shrink_args={},
mcmc_multilevel_args={}, verbose=False): 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. agglomerative heuristic.
Parameters Parameters
...@@ -286,7 +286,7 @@ def minimize_nested_blockmodel_dl(g, B_min=None, B_max=None, b_min=None, ...@@ -286,7 +286,7 @@ def minimize_nested_blockmodel_dl(g, B_min=None, B_max=None, b_min=None,
mcmc_args={}, anneal_args={}, mcmc_args={}, anneal_args={},
mcmc_equilibrate_args={}, shrink_args={}, mcmc_equilibrate_args={}, shrink_args={},
mcmc_multilevel_args={}, verbose=False): 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. using an agglomerative heuristic.
Parameters Parameters
...@@ -479,4 +479,4 @@ def minimize_nested_blockmodel_dl(g, B_min=None, B_max=None, b_min=None, ...@@ -479,4 +479,4 @@ def minimize_nested_blockmodel_dl(g, B_min=None, B_max=None, b_min=None,
**dmask(hierarchy_minimize_args, **dmask(hierarchy_minimize_args,
["B_max", "B_min", "bisection_args", "verbose"])) ["B_max", "B_min", "bisection_args", "verbose"]))
return state return state
\ No newline at end of file
...@@ -999,7 +999,7 @@ class NestedBlockState(object): ...@@ -999,7 +999,7 @@ class NestedBlockState(object):
def hierarchy_minimize(state, B_min=None, B_max=None, b_min=None, b_max=None, def hierarchy_minimize(state, B_min=None, B_max=None, b_min=None, b_max=None,
frozen_levels=None, bisection_args={}, frozen_levels=None, bisection_args={},
epsilon=1e-8, verbose=False): 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. description length.
Parameters Parameters
......
...@@ -849,7 +849,7 @@ def max_cliques(g): ...@@ -849,7 +849,7 @@ def max_cliques(g):
yield c yield c
def min_spanning_tree(g, weights=None, root=None, tree_map=None): def min_spanning_tree(g, weights=None, root=None, tree_map=None):
""" r"""
Return the minimum spanning tree of a given graph. Return the minimum spanning tree of a given graph.
Parameters Parameters
...@@ -1043,7 +1043,7 @@ def random_spanning_tree(g, weights=None, root=None, tree_map=None): ...@@ -1043,7 +1043,7 @@ def random_spanning_tree(g, weights=None, root=None, tree_map=None):
def dominator_tree(g, root, dom_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 Parameters
---------- ----------
...@@ -1777,7 +1777,7 @@ def shortest_distance(g, source=None, target=None, weights=None, ...@@ -1777,7 +1777,7 @@ def shortest_distance(g, source=None, target=None, weights=None,
negative_weights=False, max_dist=None, directed=None, negative_weights=False, max_dist=None, directed=None,
dense=False, dist_map=None, pred_map=False, dense=False, dist_map=None, pred_map=False,
return_reached=False, dag=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 vertices from a given source, or the all pairs shortest paths, if the source
is not specified. is not specified.
...@@ -2034,7 +2034,7 @@ def shortest_distance(g, source=None, target=None, weights=None, ...@@ -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, def shortest_path(g, source, target, weights=None, negative_weights=False,
pred_map=None, dag=False): pred_map=None, dag=False):
"""Return the shortest path from ``source`` to ``target``. r"""Return the shortest path from ``source`` to ``target``.
Parameters Parameters
---------- ----------
...@@ -2552,7 +2552,7 @@ def all_circuits(g, unique=False): ...@@ -2552,7 +2552,7 @@ def all_circuits(g, unique=False):
def pseudo_diameter(g, source=None, weights=None): def pseudo_diameter(g, source=None, weights=None):
""" r"""
Compute the pseudo-diameter of the graph. Compute the pseudo-diameter of the graph.
Parameters Parameters
...@@ -3180,7 +3180,7 @@ def edge_reciprocity(g): ...@@ -3180,7 +3180,7 @@ def edge_reciprocity(g):
def tsp_tour(g, src, weight=None): 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. twice as long as the optimal tour in the worst case.
Parameters Parameters
...@@ -3277,4 +3277,4 @@ def sequential_vertex_coloring(g, order=None, color=None): ...@@ -3277,4 +3277,4 @@ def sequential_vertex_coloring(g, order=None, color=None):
return color return color
from .. flow import libgraph_tool_flow from .. flow import libgraph_tool_flow
\ No newline at end of file
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