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caculateProcess.py
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caculateProcess.py
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from graphviz import Digraph
from graphviz import render
'''
传入的数据结构：
元组中的元素都是串联的，相互之间有依赖关系
列表中的元素都是并联的，相互之间没有依赖关系
并联的节点用圆形的
串联的节点用方框
'''
nodes = ((['incar', 'kpoint', 'potcar'], 'input', 'relax'),
(['incar', 'kpoint', 'potcar'], 'input', 'static'),
(['incar', 'kpoint', 'dos'], 'input', 'band'),
[(['incar', 'kpoint', 'potcar'], 'input', 'relax'),
(['incar', 'kpoint', 'dos'], 'input', 'band'),(['incar', 'kpoint', 'dos'], 'input', 'band')])
# 只要是元组就创建一个子图，这样比较方便
TUPLE_NUMBER = 0
def tuple_subgraph(parent_graph, tuple):
global TUPLE_NUMBER, subgraph_nodes
cluster_name = 'cluster_tuple' + str(TUPLE_NUMBER)
TUPLE_NUMBER += 1
# 接收元组中节点的列表
tuple_nodes = []
with parent_graph.subgraph(name=cluster_name) as A:
A.attr(style='', compound='true')
# 创建节点
for i in tuple:
# 定义一个节点的名称索引，为了防止重复，在名称前面加上其所属子图名
node_name = cluster_name + '_' + str(tuple.index(i))
if type(i) is list:
# 调用列表型的子图
B, list_nodes = list_subgraph(A, i)
tuple_nodes.append(list_nodes)
elif type(i) is str:
A.node(node_name, label=i)
# a = (node_name, cluster_name)
a = (node_name, A.name)
tuple_nodes.append(a)
elif type(i) is tuple:
n = tuple_subgraph(A, i)
tuple_nodes.append(n)
# 连接节点
for i in range(len(tuple)-1):
# 连接元组内部列表和普通节点
if type(tuple[i]) is list:
index = (len(tuple[i]) // 2)
# A.edge(list_nodes[index][0], tuple_nodes[i+1][0], ltail=list_nodes[index][0])
A.edge(list_nodes[index][0], tuple_nodes[i + 1][0], ltail=B.name)
if type(tuple[i]) is str:
A.edge(tuple_nodes[i][0], tuple_nodes[i+1][0])
# subgraph_nodes.append(tuple_nodes)
# print(tuple_nodes)
return tuple_nodes
# 如果是列表也创建一个子图，内部的节点是水平的
LIST_NUMBER = 0
def list_subgraph(parent_graph, l):
global LIST_NUMBER, subgraph_nodes
cluster_name = 'cluster_list' + str(LIST_NUMBER)
LIST_NUMBER += 1
# 暂时保存列表中的节点名
list_nodes = []
with parent_graph.subgraph(name=cluster_name) as B:
B.attr(style='dashed', rank='same', compound='true')
if have_tuple(l):
n_list = []
for i in l:
n = tuple_subgraph(B, i)
n_list.append(n)
subgraph_nodes.append(n_list)
else:
for i in l:
# 定义一个节点的名称索引，为了防止重复，在名称前面加上其所属子图名
node_name = cluster_name + '_' + str(l.index(i))
B.node(node_name, label=i)
# a = (node_name, cluster_name)
a = (node_name, B.name)
list_nodes.append(a)
# print(list_nodes)
return B, list_nodes
# 查看列表中有没有元组，如果全部是字符串，则直接创建节点；如果含有元组，就调用元组函数
def have_tuple(l):
for i in l:
if type(i) is tuple:
return True
return False
# 全局图，连接子图的节点
p = Digraph(filename='test_process.gv')
p.attr(compound='true', size="15", center='true')
subgraph_nodes = [] # 接受子图节点
for item in nodes:
if type(item) is tuple:
n = tuple_subgraph(p, item)
subgraph_nodes.append(n)
elif type(item) is list:
list_subgraph(p, item)
# 根据返回的子图间的连接节点来连接子图，图的开头和结尾不用管
for item in range(len(nodes)-1):
# 每个子图的最后一个元素与下个子图第一个元素连接
if type(nodes[item]) is tuple:
# 下一个元素不是列表才能直接连，否则得连多条线
if type(nodes[item+1]) is not list:
p.edge(subgraph_nodes[item][-1][0], subgraph_nodes[item+1][0][1][0], ltail=subgraph_nodes[item][-1][1], lhead=subgraph_nodes[item+1][0][1][1])
elif type(nodes[item+1]) is list:
for i in range(len(nodes[item+1])):
p.edge(subgraph_nodes[item][-1][0], subgraph_nodes[item+1][i][0][1][0], ltail=subgraph_nodes[item][-1][1], lhead=subgraph_nodes[item+1][i][0][1][1], headport='n', tailport='s')
# elif type(nodes[item]) is list:
# # 列表中每个子图的尾部都和下个元素子图的头部连接
# pass
p.view()