python disable path length_Python networkx.shortest_path_length方法代码示例

本文整理汇总了Python中networkx.shortest_path_length方法的典型用法代码示例。如果您正苦于以下问题：Python networkx.shortest_path_length方法的具体用法？Python networkx.shortest_path_length怎么用？Python networkx.shortest_path_length使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在模块networkx的用法示例。

在下文中一共展示了networkx.shortest_path_length方法的30个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Python代码示例。

示例1: calculate_max_depth_over_max_width

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def calculate_max_depth_over_max_width(comment_tree):

comment_tree_nx = nx.from_scipy_sparse_matrix(comment_tree, create_using=nx.Graph())

if len(comment_tree_nx) == 0:

max_depth_over_max_width = 0.0

else:

node_to_depth = nx.shortest_path_length(comment_tree_nx, 0)

depth_to_nodecount = collections.defaultdict(int)

for k, v in node_to_depth.items():

depth_to_nodecount[v] += 1

max_depth = max(node_to_depth.values())

max_width = max(depth_to_nodecount.values())

max_depth_over_max_width = max_depth/max_width

return max_depth_over_max_width

开发者ID:MKLab-ITI，项目名称:news-popularity-prediction，代码行数:20，

示例2: calculate_comment_tree_hirsch

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def calculate_comment_tree_hirsch(comment_tree):

comment_tree_nx = nx.from_scipy_sparse_matrix(comment_tree, create_using=nx.Graph())

if len(comment_tree_nx) == 0:

comment_tree_hirsch = 0.0

else:

node_to_depth = nx.shortest_path_length(comment_tree_nx, 0)

depth_to_nodecount = collections.defaultdict(int)

for k, v in node_to_depth.items():

depth_to_nodecount[v] += 1

comment_tree_hirsch = max(node_to_depth.values())

while True:

if depth_to_nodecount[comment_tree_hirsch] >= comment_tree_hirsch:

break

else:

comment_tree_hirsch -= 1

return comment_tree_hirsch

开发者ID:MKLab-ITI，项目名称:news-popularity-prediction，代码行数:23，

示例3: get_topic_distance

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def get_topic_distance(self, sg, topic):

"""

:param sg: an egocentric subgraph in networkx format

:param topic: a networkx graph of nodes representing the topic

:return: a dictionary of key node name and value distance as integer

"""

distances = dict()

# get all the distances

for tnode in topic.nodes():

if tnode in sg.nodes():

distances[tnode] = nx.shortest_path_length(sg, source=tnode)

# get the smallest distance per key

min_dist = dict()

for key in distances:

for node in distances[key]:

if node not in min_dist:

min_dist[node] = distances[key][node]

elif distances[key][node] < min_dist[node]:

min_dist[node] = distances[key][node]

# Return the dict

return min_dist

开发者ID:vz-risk，项目名称:Verum，代码行数:27，

示例4: add_cycle_edges_by_path

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def add_cycle_edges_by_path(g,number_of_edges,path_length = 5):

number = 0

num_nodes = g.number_of_nodes()

nodes = g.nodes()

extra_edges = []

while number < number_of_edges:

u,v = np.random.randint(0,num_nodes,2)

u = nodes[u]

v = nodes[v]

if nx.has_path(g,u,v):

length = nx.shortest_path_length(g,source = u,target = v)

if length <= path_length:

extra_edges.append((v,u))

number += 1

if nx.has_path(g,v,u):

length = nx.shortest_path_length(g,source = v,target = u)

if length <= path_length:

extra_edges.append((u,v))

number += 1

print("# extra edges added with path length <= %d: %d" % (path_length,len(extra_edges)))

return extra_edges

开发者ID:zhenv5，项目名称:breaking_cycles_in_noisy_hierarchies，代码行数:23，

示例5: distance

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def distance(self, type, node1, node2):

if node1 in self.Dual[type].nodes() and node2 in self.Dual[type].nodes():

return nx.shortest_path_length(self.Dual[type], node1, node2)

elif node1 in self.Dual[type].nodes() and node2 not in self.Dual[type].nodes():

node2 = self.External[type][node2]['measure']

return nx.shortest_path_length(self.Dual[type], node1, node2) + 1

elif node1 not in self.Dual[type].nodes() and node2 in self.Dual[type].nodes():

node1 = self.External[type][node1]['measure']

return nx.shortest_path_length(self.Dual[type], node1, node2) + 1

else:

node1 = self.External[type][node1]['measure']

node2 = self.External[type][node2]['measure']

return nx.shortest_path_length(self.Dual[type], node1, node2) + 2

# Re-initializes Measurement qubits

开发者ID:jacobmarks，项目名称:QTop，代码行数:18，

示例6: dendritic_graph

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def dendritic_graph(self):

"""

Builds skeleton of the topological representation (used internally)

"""

diam = networkx.diameter(self.gl)

g3 = networkx.Graph()

dicdend = {}

for n in range(diam-1):

nodedist = []

for k in self.pl:

dil = networkx.shortest_path_length(self.gl, self.root, k)

if dil == n:

nodedist.append(str(k))

g2 = self.gl.subgraph(nodedist)

dicdend[n] = sorted(networkx.connected_components(g2))

for n2, yu in enumerate(dicdend[n]):

g3.add_node(str(n) + '_' + str(n2))

if n > 0:

for n3, yu2 in enumerate(dicdend[n-1]):

if networkx.is_connected(self.gl.subgraph(list(yu)+list(yu2))):

g3.add_edge(str(n) + '_' + str(n2), str(n-1) + '_' + str(n3))

return g3, dicdend

开发者ID:CamaraLab，项目名称:scTDA，代码行数:24，

示例7: node_distance

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def node_distance(G):

"""

Return an NxN matrix that consists of histograms of shortest path

lengths between nodes i and j. This is useful for eventually taking

information theoretic distances between the nodes.

Parameters

----------

G (nx.Graph): the graph in question.

Returns

-------

out (np.ndarray): a matrix of binned node distance values.

"""

N = G.number_of_nodes()

a = np.zeros((N, N))

dists = nx.shortest_path_length(G)

for idx, row in enumerate(dists):

counts = Counter(row[1].values())

a[idx] = [counts[l] for l in range(1, N + 1)]

return a / (N - 1)

开发者ID:netsiphd，项目名称:netrd，代码行数:27，

示例8: furtherest_node_miles

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def furtherest_node_miles(self, *args):

"""

Returns the maximum eccentricity from the source, in miles.

.. warning:: Not working....

"""

if args:

if len(args) == 1:

_net = args[0]

_src = self.source

elif len(args) == 2:

_net, _src = args

else:

_net = self.G.graph

_src = self.source

dist = {}

_net = _net.copy()

if not _net.has_node(_src):

_sp = nx.shortest_path(self.G.graph, _src, list(_net.nodes())[0])

for n1, n2 in zip(_sp[:-1], _sp[1:]):

_net.add_edge(n1, n2, length=self.G.graph[n1][n2]["length"])

for node in _net.nodes():

dist[node] = nx.shortest_path_length(_net, _src, node, weight="length")

return np.max(list(dist.values())) * 0.000621371 # Convert length to miles

开发者ID:NREL，项目名称:ditto，代码行数:26，

示例9: bell_reweighting

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def bell_reweighting(tree, root, sublinear=False):

# convert the hierarchy to a tree if make_bfs_tree is true

distance_by_target = nx.shortest_path_length(tree, source=root)

level_count = defaultdict(int)

for val in distance_by_target.values():

level_count[val] += 1

for edge in tree.edges():

parent, child = edge

if sublinear:

# use smoothed logarithm

tree[parent][child]['weight'] = 1.0 / log(1 + level_count[distance_by_target[child]], 10)

else:

tree[parent][child]['weight'] = 1.0 / level_count[distance_by_target[child]]

return tree

开发者ID:quadflor，项目名称:Quadflor，代码行数:20，

示例10: find_best_mapping

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def find_best_mapping(alignments, query_length, parent, coords_to_exclude, children_dict, previous_gene_start, copy_tag):

children = children_dict[parent.id]

children_coords = liftoff_utils.merge_children_intervals(children)

node_dict, aln_graph = intialize_graph()

head_nodes = add_single_alignments(node_dict, aln_graph, alignments, children_coords, parent, coords_to_exclude,

previous_gene_start)

chain_alignments(head_nodes, node_dict, aln_graph, coords_to_exclude, parent, children_coords)

add_target_node(aln_graph, node_dict, query_length, children_coords, parent)

shortest_path = nx.shortest_path(aln_graph, source=0, target=len(node_dict) - 1,

weight=lambda u, v, d: get_weight(u, v, d, aln_graph))

shortest_path_weight = nx.shortest_path_length(aln_graph, source=0, target=len(node_dict) - 1,

weight=lambda u, v, d: get_weight(u, v, d, aln_graph))

shortest_path_nodes = []

for i in range (1,len(shortest_path)-1):

node_name = shortest_path[i]

shortest_path_nodes.append(node_dict[node_name])

if len(shortest_path_nodes) == 0:

return {}, shortest_path_weight, 0,0

mapped_children, alignment_coverage, seq_id = convert_all_children_coords(shortest_path_nodes, children, parent, copy_tag)

return mapped_children, shortest_path_weight, alignment_coverage, seq_id

开发者ID:agshumate，项目名称:Liftoff，代码行数:24，

示例11: descendants

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def descendants(G, source):

"""Return all nodes reachable from `source` in G.

Parameters

----------

G : NetworkX DiGraph

source : node in G

Returns

-------

des : set()

The descendants of source in G

"""

if not G.has_node(source):

raise nx.NetworkXError("The node %s is not in the graph." % source)

des = set(nx.shortest_path_length(G, source=source).keys()) - set([source])

return des

开发者ID:SpaceGroupUCL，项目名称:qgisSpaceSyntaxToolkit，代码行数:19，

示例12: ancestors

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def ancestors(G, source):

"""Return all nodes having a path to `source` in G.

Parameters

----------

G : NetworkX DiGraph

source : node in G

Returns

-------

ancestors : set()

The ancestors of source in G

"""

if not G.has_node(source):

raise nx.NetworkXError("The node %s is not in the graph." % source)

anc = set(nx.shortest_path_length(G, target=source).keys()) - set([source])

return anc

开发者ID:SpaceGroupUCL，项目名称:qgisSpaceSyntaxToolkit，代码行数:19，

示例13: test_eccentricity

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def test_eccentricity(self):

assert_equal(networkx.eccentricity(self.G,1),6)

e=networkx.eccentricity(self.G)

assert_equal(e[1],6)

sp=networkx.shortest_path_length(self.G)

e=networkx.eccentricity(self.G,sp=sp)

assert_equal(e[1],6)

e=networkx.eccentricity(self.G,v=1)

assert_equal(e,6)

e=networkx.eccentricity(self.G,v=[1,1]) #This behavior changed in version 1.8 (ticket #739)

assert_equal(e[1],6)

e=networkx.eccentricity(self.G,v=[1,2])

assert_equal(e[1],6)

# test against graph with one node

G=networkx.path_graph(1)

e=networkx.eccentricity(G)

assert_equal(e[0],0)

e=networkx.eccentricity(G,v=0)

assert_equal(e,0)

assert_raises(networkx.NetworkXError, networkx.eccentricity, G, 1)

# test against empty graph

G=networkx.empty_graph()

e=networkx.eccentricity(G)

assert_equal(e,{})

开发者ID:SpaceGroupUCL，项目名称:qgisSpaceSyntaxToolkit，代码行数:26，

示例14: descendants

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def descendants(G, source):

"""Returns all nodes reachable from `source` in `G`.

Parameters

----------

G : NetworkX DiGraph

A directed acyclic graph (DAG)

source : node in `G`

Returns

-------

set()

The descendants of `source` in `G`

"""

if not G.has_node(source):

raise nx.NetworkXError("The node %s is not in the graph." % source)

des = set(n for n, d in nx.shortest_path_length(G, source=source).items())

return des - {source}

开发者ID:holzschu，项目名称:Carnets，代码行数:20，

示例15: ancestors

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def ancestors(G, source):

"""Returns all nodes having a path to `source` in `G`.

Parameters

----------

G : NetworkX DiGraph

A directed acyclic graph (DAG)

source : node in `G`

Returns

-------

set()

The ancestors of source in G

"""

if not G.has_node(source):

raise nx.NetworkXError("The node %s is not in the graph." % source)

anc = set(n for n, d in nx.shortest_path_length(G, target=source).items())

return anc - {source}

开发者ID:holzschu，项目名称:Carnets，代码行数:20，

示例16: test_all_pairs_shortest_path_length

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def test_all_pairs_shortest_path_length(self):

ans = dict(nx.shortest_path_length(self.cycle))

assert_equal(ans[0], {0: 0, 1: 1, 2: 2, 3: 3, 4: 3, 5: 2, 6: 1})

assert_equal(ans, dict(nx.all_pairs_shortest_path_length(self.cycle)))

ans = dict(nx.shortest_path_length(self.grid))

assert_equal(ans[1][16], 6)

# now with weights

ans = dict(nx.shortest_path_length(self.cycle, weight='weight'))

assert_equal(ans[0], {0: 0, 1: 1, 2: 2, 3: 3, 4: 3, 5: 2, 6: 1})

assert_equal(ans, dict(nx.all_pairs_dijkstra_path_length(self.cycle)))

ans = dict(nx.shortest_path_length(self.grid, weight='weight'))

assert_equal(ans[1][16], 6)

# weights and method specified

ans = dict(nx.shortest_path_length(self.cycle, weight='weight',

method='dijkstra'))

assert_equal(ans[0], {0: 0, 1: 1, 2: 2, 3: 3, 4: 3, 5: 2, 6: 1})

assert_equal(ans, dict(nx.all_pairs_dijkstra_path_length(self.cycle)))

ans = dict(nx.shortest_path_length(self.cycle, weight='weight',

method='bellman-ford'))

assert_equal(ans[0], {0: 0, 1: 1, 2: 2, 3: 3, 4: 3, 5: 2, 6: 1})

assert_equal(ans,

dict(nx.all_pairs_bellman_ford_path_length(self.cycle)))

开发者ID:holzschu，项目名称:Carnets，代码行数:24，

示例17: test_eccentricity

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def test_eccentricity(self):

assert_equal(networkx.eccentricity(self.G, 1), 6)

e = networkx.eccentricity(self.G)

assert_equal(e[1], 6)

sp = dict(networkx.shortest_path_length(self.G))

e = networkx.eccentricity(self.G, sp=sp)

assert_equal(e[1], 6)

e = networkx.eccentricity(self.G, v=1)

assert_equal(e, 6)

# This behavior changed in version 1.8 (ticket #739)

e = networkx.eccentricity(self.G, v=[1, 1])

assert_equal(e[1], 6)

e = networkx.eccentricity(self.G, v=[1, 2])

assert_equal(e[1], 6)

# test against graph with one node

G = networkx.path_graph(1)

e = networkx.eccentricity(G)

assert_equal(e[0], 0)

e = networkx.eccentricity(G, v=0)

assert_equal(e, 0)

assert_raises(networkx.NetworkXError, networkx.eccentricity, G, 1)

# test against empty graph

G = networkx.empty_graph()

e = networkx.eccentricity(G)

assert_equal(e, {})

开发者ID:holzschu，项目名称:Carnets，代码行数:27，

示例18: descendants

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def descendants(G, source):

"""Return all nodes reachable from `source` in `G`.

Parameters

----------

G : NetworkX DiGraph

A directed acyclic graph (DAG)

source : node in `G`

Returns

-------

set()

The descendants of `source` in `G`

"""

if not G.has_node(source):

raise nx.NetworkXError("The node %s is not in the graph." % source)

spl = nx.shortest_path_length(G, source=source)

des = set(spl) - set([source])

return des

开发者ID:aws-samples，项目名称:aws-kube-codesuite，代码行数:21，

示例19: ancestors

​点赞 6

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def ancestors(G, source):

"""Return all nodes having a path to `source` in `G`.

Parameters

----------

G : NetworkX DiGraph

A directed acyclic graph (DAG)

source : node in `G`

Returns

-------

set()

The ancestors of source in G

"""

if not G.has_node(source):

raise nx.NetworkXError("The node %s is not in the graph." % source)

spl = nx.shortest_path_length(G, target=source)

anc = set(spl) - set([source])

return anc

开发者ID:aws-samples，项目名称:aws-kube-codesuite，代码行数:21，

示例20: calculate_max_depth

​点赞 5

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def calculate_max_depth(comment_tree):

comment_tree_nx = nx.from_scipy_sparse_matrix(comment_tree, create_using=nx.Graph())

if len(comment_tree_nx) == 0:

max_depth = 0.0

else:

node_to_depth = nx.shortest_path_length(comment_tree_nx, 0)

max_depth = max(node_to_depth.values())

return max_depth

开发者ID:MKLab-ITI，项目名称:news-popularity-prediction，代码行数:12，

示例21: calculate_avg_depth

​点赞 5

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def calculate_avg_depth(comment_tree):

comment_tree_nx = nx.from_scipy_sparse_matrix(comment_tree, create_using=nx.Graph())

if len(comment_tree_nx) == 0:

avg_depth = 0.0

else:

node_to_depth = nx.shortest_path_length(comment_tree_nx, 0)

avg_depth = statistics.mean(node_to_depth.values())

return avg_depth

开发者ID:MKLab-ITI，项目名称:news-popularity-prediction，代码行数:12，

示例22: calculate_max_width

​点赞 5

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def calculate_max_width(comment_tree):

comment_tree_nx = nx.from_scipy_sparse_matrix(comment_tree, create_using=nx.Graph())

if len(comment_tree_nx) == 0:

max_width = 1.0

else:

node_to_depth = nx.shortest_path_length(comment_tree_nx, 0)

depth_to_nodecount = collections.defaultdict(int)

for k, v in node_to_depth.items():

depth_to_nodecount[v] += 1

max_width = max(depth_to_nodecount.values())

return max_width

开发者ID:MKLab-ITI，项目名称:news-popularity-prediction，代码行数:17，

示例23: calculate_avg_width

​点赞 5

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def calculate_avg_width(comment_tree):

comment_tree_nx = nx.from_scipy_sparse_matrix(comment_tree, create_using=nx.Graph())

if len(comment_tree_nx) == 0:

avg_width = 1.0

else:

node_to_depth = nx.shortest_path_length(comment_tree_nx, 0)

depth_to_nodecount = collections.defaultdict(int)

for k, v in node_to_depth.items():

depth_to_nodecount[v] += 1

avg_width = statistics.mean(depth_to_nodecount.values())

return avg_width

开发者ID:MKLab-ITI，项目名称:news-popularity-prediction，代码行数:17，

示例24: create_profile_graph

​点赞 5

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def create_profile_graph(self, y_values):

self.regenerate_network(load_names=False, gen_names=False)

swing_bus = self.swing_bus

bus_distance_matrix_df = pd.DataFrame(nx.shortest_path_length(self.graph))

pos = dict()

for k, v in bus_distance_matrix_df.loc[swing_bus].sort_values().to_dict().items():

pos[k] = (v, y_values[k])

self.positions = pos

开发者ID:power-system-simulation-toolbox，项目名称:psst，代码行数:13，

示例25: get_syntactical_distance_from_graph

​点赞 5

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def get_syntactical_distance_from_graph(graph, token_a, token_b, debug=False):

return nx.shortest_path_length(graph,

source='{}-{}'.format(token_a.word if hasattr(token_a, 'word') else token_a.text, token_a.i),

target='{}-{}'.format(token_b.word if hasattr(token_b, 'word') else token_b.text, token_b.i))

开发者ID:sattree，项目名称:gap，代码行数:6，

示例26: get_topic_distance

​点赞 5

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def get_topic_distance(sg, topic):

"""

:param sg: an egocentric subgraph in networkx format

:param topic: a networkx graph of nodes representing the topic

:return: a dictionary of key node name and value distance as integer

"""

distances = dict()

# get all the distances

for tnode in topic.nodes():

if tnode in sg.nodes():

distances[tnode] = nx.shortest_path_length(sg, source=tnode)

# get the smallest distance per key

min_dist = dict()

for key in distances:

for node in distances[key]:

if node not in min_dist:

min_dist[node] = distances[key][node]

elif distances[key][node] < min_dist[node]:

min_dist[node] = distances[key][node]

# Return the dict

return min_dist

开发者ID:vz-risk，项目名称:Verum，代码行数:28，

示例27: _lowest_common_anscestor

​点赞 5

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def _lowest_common_anscestor(T, u, v, root):

# Find a least common anscestors

v_branch = nx.ancestors(T, v).union({v})

u_branch = nx.ancestors(T, u).union({u})

common = v_branch & u_branch

if len(common) == 0:

lca = None

else:

lca = max(

(nx.shortest_path_length(T, root, c), c)

for c in common

)[1]

return lca

开发者ID:Erotemic，项目名称:ibeis，代码行数:15，

示例28: create_length_dict

​点赞 5

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def create_length_dict(points_on_line, tranches):

G_complete = nx.Graph()

for idx, node in points_on_line.iterrows():

node_type = node['Type']

G_complete.add_node(idx, type=node_type)

for idx, tranch in tranches.iterrows():

start_node_index = tranch['Startnode'][4::]

end_node_index = tranch['Endnode'][4::]

tranch_length = tranch['Length']

G_complete.add_edge(int(start_node_index), int(end_node_index),

weight=tranch_length,

gene=idx,

startnode=start_node_index,

endnode=end_node_index)

idx_nodes_sub = points_on_line[points_on_line['Type'] == 'PLANT'].index

idx_nodes_consum = points_on_line[points_on_line['Type'] == 'CONSUMER'].index

idx_nodes = idx_nodes_sub.append(idx_nodes_consum)

dict_length = {}

dict_path = {}

for idx_node1 in idx_nodes:

dict_length[idx_node1] = {}

dict_path[idx_node1] = {}

for idx_node2 in idx_nodes:

if idx_node1 == idx_node2:

dict_length[idx_node1][idx_node2] = 0.0

else:

nx.shortest_path(G_complete, 0, 1)

dict_path[idx_node1][idx_node2] = nx.shortest_path(G_complete,

source=idx_node1,

target=idx_node2,

weight='weight')

dict_length[idx_node1][idx_node2] = nx.shortest_path_length(G_complete,

source=idx_node1,

target=idx_node2,

weight='weight')

return dict_length, dict_path

开发者ID:architecture-building-systems，项目名称:CityEnergyAnalyst，代码行数:42，

示例29: create_length_complete_dict

​点赞 5

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def create_length_complete_dict(points_on_line, tranches):

G_complete = nx.Graph()

for idx, node in points_on_line.iterrows():

node_type = node['Type']

G_complete.add_node(idx, type=node_type)

for idx, tranch in tranches.iterrows():

start_node_index = tranch['Startnode'][4::]

end_node_index = tranch['Endnode'][4::]

tranch_length = tranch['Length']

G_complete.add_edge(int(start_node_index), int(end_node_index),

weight=tranch_length,

gene=idx,

startnode=start_node_index,

endnode=end_node_index)

# idx_nodes_sub = points_on_line[points_on_line['Type'] == 'PLANT'].index

# idx_nodes_consum = points_on_line[points_on_line['Type'] == 'CONSUMER'].index

idx_nodes = points_on_line.index

dict_length = {}

dict_path = {}

for idx_node1 in idx_nodes:

dict_length[idx_node1] = {}

dict_path[idx_node1] = {}

for idx_node2 in idx_nodes:

if idx_node1 == idx_node2:

dict_length[idx_node1][idx_node2] = 0.0

else:

nx.shortest_path(G_complete, 0, 1)

dict_path[idx_node1][idx_node2] = nx.shortest_path(G_complete,

source=idx_node1,

target=idx_node2,

weight='weight')

dict_length[idx_node1][idx_node2] = nx.shortest_path_length(G_complete,

source=idx_node1,

target=idx_node2,

weight='weight')

return dict_length, dict_path

开发者ID:architecture-building-systems，项目名称:CityEnergyAnalyst，代码行数:42，

示例30: compute_distance

​点赞 5

​

# 需要导入模块: import networkx [as 别名]

# 或者: from networkx import shortest_path_length [as 别名]

def compute_distance(k):

return nx.shortest_path_length(G,str(k[0]),str(k[1]))

开发者ID:acsicuib，项目名称:YAFS，代码行数:4，

注：本文中的networkx.shortest_path_length方法示例整理自Github/MSDocs等源码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。

本文来自互联网用户投稿，文章观点仅代表作者本人，不代表本站立场，不承担相关法律责任。如若转载，请注明出处。 如若内容造成侵权/违法违规/事实不符，请点击【内容举报】进行投诉反馈！