本文整理汇总了Python中networkx.readwrite.json_graph.tree_data方法的典型用法代码示例。如果您正苦于以下问题：Python json_graph.tree_data方法的具体用法？Python json_graph.tree_data怎么用？Python json_graph.tree_data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类networkx.readwrite.json_graph的用法示例。
在下文中一共展示了json_graph.tree_data方法的6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，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: create_html
# 需要导入模块: from networkx.readwrite import json_graph [as 别名]
# 或者: from networkx.readwrite.json_graph import tree_data [as 别名]
def create_html(predicted_ids, parent_ids, scores, labels_ids, vocab, filename, output_dir):
graph = create_graph(
predicted_ids=predicted_ids,
parent_ids=parent_ids,
scores=scores,
vocab=vocab)
json_str = json.dumps(json_graph.tree_data(graph, (0, 0)), ensure_ascii=True)
transcript = [vocab[sym] for sym in labels_ids]
transcript.remove('EOS')
transcript = ''.join(transcript)
output_fname = path.join(output_dir, filename + '.html')
num_subdirs = filename.count('/') # too hacky ?
makedirs(path.dirname(output_fname), exist_ok=True)
html_str = HTML_TEMPLATE.substitute(DATA=json_str, WALK='../'*num_subdirs, transcript=transcript)
with open(output_fname, 'w') as f:
f.write(html_str) 示例2: as_tree
# 需要导入模块: from networkx.readwrite import json_graph [as 别名]
# 或者: from networkx.readwrite.json_graph import tree_data [as 别名]
def as_tree(graph, root=OPENSTACK_CLUSTER, reverse=False):
if nx.__version__ >= '2.0':
linked_graph = json_graph.node_link_graph(
graph, attrs={'name': 'graph_index'})
else:
linked_graph = json_graph.node_link_graph(graph)
if 0 == nx.number_of_nodes(linked_graph):
return {}
if reverse:
linked_graph = linked_graph.reverse()
if nx.__version__ >= '2.0':
return json_graph.tree_data(
linked_graph,
root=root,
attrs={'id': 'graph_index', 'children': 'children'})
else:
return json_graph.tree_data(linked_graph, root=root) 示例3: generate
# 需要导入模块: from networkx.readwrite import json_graph [as 别名]
# 或者: from networkx.readwrite.json_graph import tree_data [as 别名]
def generate(input_data, output_dir, include_pad=False):
path_base = os.path.dirname(os.path.realpath(__file__))
if not os.path.exists(output_dir):
os.makedirs(output_dir)
# Copy required files
shutil.copy2(path_base+"/templates/tree.css", output_dir)
shutil.copy2(path_base+"/templates/tree.js", output_dir)
with open(input_data) as beams:
for i, line in enumerate(beams):
beam = json.loads(line)
graph = create_graph(predicted_ids=beam["predicted_tokens"],
parent_ids=beam["parent_ids"],
scores=beam["scores"],
normalized_scores=beam["normalized_scores"],
include_pad=include_pad)
json_str = json.dumps(
json_graph.tree_data(graph, (0, 0)),
ensure_ascii=True)
html_str = HTML_TEMPLATE.substitute(DATA=json_str, SENT=str(i))
output_path = os.path.join(output_dir, "{:06d}.html".format(i))
with open(output_path, "w", encoding="utf-8") as out:
out.write(html_str)
print("Output beams written to: {}".format(output_dir)) 示例4: draw_graph
# 需要导入模块: from networkx.readwrite import json_graph [as 别名]
# 或者: from networkx.readwrite.json_graph import tree_data [as 别名]
def draw_graph(graph):
from string import Template
import shutil
from networkx.readwrite import json_graph
import json
HTML_TEMPLATE = Template("""
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Beam Search</title>
<link rel="stylesheet" type="text/css" href="tree.css">
<script src="http://d3js.org/d3.v3.min.js"></script>
</head>
<body>
<script>
var treeData = $DATA
</script>
<script src="tree.js"></script>
</body>
</html>""")
seq2seq_path = '/scratch/make_build/gram_as_foreight_lang/seq2seq'
vis_path = base_path+'/vis/graph_beam/'
os.makedirs(base_path+'/vis/graph_beam/', exist_ok=True)
shutil.copy2(seq2seq_path+"/bin/tools/beam_search_viz/tree.css", vis_path)
shutil.copy2(seq2seq_path+"/bin/tools/beam_search_viz/tree.js", vis_path)
json_str = json.dumps(json_graph.tree_data(graph, (0, 0)), ensure_ascii=False)
html_str = HTML_TEMPLATE.substitute(DATA=json_str)
output_path = os.path.join(vis_path, "graph.html")
with open(output_path, "w") as file:
file.write(html_str)
print(output_path) 示例5: main
# 需要导入模块: from networkx.readwrite import json_graph [as 别名]
# 或者: from networkx.readwrite.json_graph import tree_data [as 别名]
def main():
beam_data = np.load(ARGS.data)
# Optionally load vocabulary data
vocab = None
if ARGS.vocab:
with open(ARGS.vocab) as file:
vocab = file.readlines()
vocab = [_.strip() for _ in vocab]
vocab += ["UNK", "SEQUENCE_START", "SEQUENCE_END"]
if not os.path.exists(ARGS.output_dir):
os.makedirs(ARGS.output_dir)
# Copy required files
shutil.copy2("/home/bowen/pycharm_deployment_directory/synthesis/prototype_models/google_seq2seq/bin/tools/beam_search_viz/tree.css", ARGS.output_dir)
shutil.copy2("/home/bowen/pycharm_deployment_directory/synthesis/prototype_models/google_seq2seq/bin/tools/beam_search_viz/tree.js", ARGS.output_dir)
for idx in range(len(beam_data["predicted_ids"])):
predicted_ids = beam_data["predicted_ids"][idx]
parent_ids = beam_data["beam_parent_ids"][idx]
scores = beam_data["scores"][idx]
graph = create_graph(
predicted_ids=predicted_ids,
parent_ids=parent_ids,
scores=scores,
vocab=vocab)
json_str = json.dumps(
json_graph.tree_data(graph, (0, 0)),
ensure_ascii=False)
html_str = HTML_TEMPLATE.substitute(DATA=json_str)
output_path = os.path.join(ARGS.output_dir, "{:06d}.html".format(idx))
with open(output_path, "w") as file:
file.write(html_str)
print(output_path) 示例6: main
# 需要导入模块: from networkx.readwrite import json_graph [as 别名]
# 或者: from networkx.readwrite.json_graph import tree_data [as 别名]
def main():
beam_data = np.load(ARGS.data)
# Optionally load vocabulary data
vocab = None
if ARGS.vocab:
with open(ARGS.vocab) as file:
vocab = file.readlines()
vocab = [_.strip() for _ in vocab]
vocab += ["UNK", "SEQUENCE_START", "SEQUENCE_END"]
if not os.path.exists(ARGS.output_dir):
os.makedirs(ARGS.output_dir)
# Copy required files
shutil.copy2("./bin/tools/beam_search_viz/tree.css", ARGS.output_dir)
shutil.copy2("./bin/tools/beam_search_viz/tree.js", ARGS.output_dir)
for idx in range(len(beam_data["predicted_ids"])):
predicted_ids = beam_data["predicted_ids"][idx]
parent_ids = beam_data["beam_parent_ids"][idx]
scores = beam_data["scores"][idx]
graph = create_graph(
predicted_ids=predicted_ids,
parent_ids=parent_ids,
scores=scores,
vocab=vocab)
json_str = json.dumps(
json_graph.tree_data(graph, (0, 0)),
ensure_ascii=False)
html_str = HTML_TEMPLATE.substitute(DATA=json_str)
output_path = os.path.join(ARGS.output_dir, "{:06d}.html".format(idx))
with open(output_path, "w") as file:
file.write(html_str)
print(output_path)