def get_type_data(model):
number = model.number
categories = [opts.GraphCategory(name='类型')]
nodes = [
opts.GraphNode(name=str(model),
symbol_size=100,
category=0,
value=number)
]
links = []
# 事件总数量
set_number_node(model, categories, nodes, links)
# 事件最多社区
set_max_community_node('Type', model, categories, nodes, links)
# 类型下所有大类
maintypes = MainType.objects.filter(type=model)
name = '大类'
categories.append(opts.GraphCategory(name=name))
index = len(categories) - 1
for maintype in maintypes:
value = str(maintype)
number = maintype.number
if value == str(model):
value = value + '（问题大类）'
nodes.append(
opts.GraphNode(name=value,
symbol_size=50,
category=index,
value=number))
links.append(
opts.GraphLink(source=str(model), target=value, value='下属大类'))
return categories, nodes, links
def get_district_data(model_name, model):
categories = [opts.GraphCategory(name='区域')]
number_d = model.number
nodes = [
opts.GraphNode(name=str(model),
symbol_size=80,
category=0,
value=number_d)
]
links = []
streets = Street.objects.filter(district=model)
for street in streets:
name_s = Street.name
number_s = street.number
if name_s == 'name' or name_s == 'id':
continue
value_s = str(street)
categories.append(opts.GraphCategory(name='街道'))
index_s = len(categories) - 1
nodes.append(
opts.GraphNode(name=value_s,
symbol_size=60,
category=index_s,
value=number_s))
links.append(
opts.GraphLink(source=str(model), target=value_s, value='下属街道'))
return categories, nodes, links
def get_maintype_data(model):
number = model.number
categories = [opts.GraphCategory(name='大类')]
nodes = [
opts.GraphNode(name=str(model),
symbol_size=100,
category=0,
value=number)
]
links = []
# 事件数量
set_number_node(model, categories, nodes, links)
# 所属类型
set_type_node('MainType', model, categories, nodes, links)
# 事件最多社区
set_max_community_node('MainType', model, categories, nodes, links)
subtypes = SubType.objects.filter(main_type=model)
name = '小类'
categories.append(opts.GraphCategory(name=name))
index = len(categories) - 1
for subtype in subtypes:
value = str(subtype)
sub_number = subtype.number
if value == str(model) or value == str(model.type):
value = value + '（问题小类）'
nodes.append(
opts.GraphNode(name=value,
symbol_size=50,
category=index,
value=sub_number))
links.append(
opts.GraphLink(source=str(model), target=value, value='下属小类'))
return categories, nodes, links
def _get_categories():
try:
_categories ={nodes[node]['color'] for node in nodes}
categories = [opts.GraphCategory(name='level_'+str(category)) for category in _categories]
except:
categories = [
opts.GraphCategory(name='c_'+ str(index)) for index in range(len(nodes))
]
finally:
return categories
def get_street_data(model_name, model):
categories = [opts.GraphCategory(name='街道')]
str_number = model.number
nodes = [
opts.GraphNode(name=str(model),
symbol_size=80,
category=0,
value=str_number)
]
links = []
# 街道所属区域
districts = District.objects.all()
for district in districts:
number_c = district.number
name_c = district.name
if name_c == 'name' or name_c == 'id':
continue
value_c = str(district)
categories.append(opts.GraphCategory(name='区域'))
index_c = len(categories) - 1
nodes.append(
opts.GraphNode(name=value_c,
symbol_size=60,
category=index_c,
value=number_c))
links.append(
opts.GraphLink(source=str(model), target=value_c, value='所属区域'))
# 街道下所有社区及其数量
communities = Community.objects.filter(street=model)
for community in communities:
name_c = Community.name
number_c = community.number
# ratio_c = str((round(number_c*100/str_number,2)))+'%'
if name_c == 'name' or name_c == 'id':
continue
value_c = str(community)
categories.append(opts.GraphCategory(name='社区'))
index_c = len(categories) - 1
nodes.append(
opts.GraphNode(name=value_c,
symbol_size=40,
category=index_c,
value=number_c))
links.append(
opts.GraphLink(source=str(model), target=value_c, value='下属社区'))
return categories, nodes, links
def get_disposeunit_data(model_name, model):
number_dis = str(model.number)
categories = [opts.GraphCategory(name='执行部门')]
nodes = [
opts.GraphNode(name=str(model),
symbol_size=100,
category=0,
value=number_dis)
]
links = []
id = DisposeUnit.objects.filter(name=str(model)).values("id")[0]['id']
dis_model = DisposeUnit.objects.filter(id=id)[0]
try:
# 事件总数
node_name = str(dis_model.number)
print(node_name)
cate_name = '数量'
link_name = '事件总数'
source_node = str(dis_model)
create_node(source_node, categories, cate_name, nodes, node_name,
links, link_name)
# 完成事件百分比
is_achieve_count = Event.objects.filter(
dispose_unit=id).values('achieve').annotate(
count=Count('achieve')).values('achieve',
'count').order_by('-count')
is_achieve_count = list(is_achieve_count)
print(is_achieve_count)
y = is_achieve_count[0]['count']
n = is_achieve_count[1]['count']
percent = round(y * 100 / (y + n), 2)
node_name = str(percent) + '%'
cate_name = '百分比'
link_name = '完成事件百分比'
create_node(source_node, categories, cate_name, nodes, node_name,
links, link_name)
# 部门编号
aid = dis_model.aID
node_name = str(aid)
cate_name = '编号'
link_name = '部门编号'
create_node(source_node, categories, cate_name, nodes, node_name,
links, link_name)
except Exception as e:
print(e)
return categories, nodes, links
def set_number_node(model, categories, nodes, links):
value = str(getattr(model, 'number'))
categories.append(opts.GraphCategory(name='数量'))
index = len(categories) - 1
nodes.append(opts.GraphNode(name=value, symbol_size=50, category=index))
links.append(opts.GraphLink(source=str(model), target=value,
value='事件总数量'))
return 0
def get_achive_data(model_name, model):
events = model.event.get_queryset()
ratio = '{:.2f}%'.format(model.number / Event.objects.count() * 100)
unit_list = {}
for event in events:
unit = event.dispose_unit.name
if unit in unit_list:
unit_list[unit] += 1
else:
unit_list.update({unit: 1})
number_max = 0
for key in unit_list:
if unit_list[key] > number_max:
unit = key
number_max = unit_list[key]
categories = [
opts.GraphCategory(name="执行情况"),
opts.GraphCategory(name="数量"),
opts.GraphCategory(name="处置部门"),
opts.GraphCategory(name="百分比"),
]
nodes = [
opts.GraphNode(name=str(model.name), symbol_size=80, category=0),
opts.GraphNode(name=str(model.number), symbol_size=50, category=1),
opts.GraphNode(name=unit, symbol_size=50, category=2),
opts.GraphNode(name=ratio, symbol_size=50, category=3),
]
links = [
opts.GraphLink(source=str(model.name),
target=str(model.number),
value="事件数量"),
opts.GraphLink(source=str(model.name),
target=unit,
value="最多 " + str(model.name) + " 处置机构"),
opts.GraphLink(source=str(model.name), target=ratio, value="事件占比"),
]
return categories, nodes, links
def get_source_data(model_name, model):
events = model.event.get_queryset()
# 对应性质
property_list = {}
for event in events:
proper = event.property.name
if proper in property_list.keys():
property_list[proper] += 1
else:
property_list.update({proper: 1})
# 占事件总数百分比
ratio = '{:.2f}%'.format(model.number / Event.objects.count() * 100)
number_max = 0
for key in property_list:
if property_list[key] > number_max:
proper = key
number_max = property_list[key]
categories = [
opts.GraphCategory(name="来源"),
opts.GraphCategory(name="数量"),
opts.GraphCategory(name="性质"),
opts.GraphCategory(name="百分比"),
]
nodes = [
opts.GraphNode(name=str(model), symbol_size=80, category=0),
opts.GraphNode(name=str(model.number), symbol_size=50, category=1),
opts.GraphNode(name=proper, symbol_size=50, category=2),
opts.GraphNode(name=ratio, symbol_size=50, category=3),
]
links = [
opts.GraphLink(source=str(model),
target=str(model.number),
value="事件总数量"),
opts.GraphLink(source=str(model), target=proper, value="对应性质"),
opts.GraphLink(source=str(model), target=ratio, value="占事件总数百分比"),
]
return categories, nodes, links
def set_max_community_node(model_name, model, categories, nodes, links):
max_num = 0
communities = Community.objects.all()
if model_name == 'MainType':
subtypes = SubType.objects.filter(main_type=model)
for community in communities:
events = Event.objects.filter(sub_type__in=subtypes,
community=community)
now_num = len(events)
if now_num > max_num:
max_num = now_num
max_community = community
if model_name == 'SubType':
for community in communities:
events = Event.objects.filter(sub_type=model, community=community)
now_num = len(events)
if now_num > max_num:
max_num = now_num
max_community = community
if model_name == 'Type':
maintypes = MainType.objects.filter(type=model)
subtypes = SubType.objects.filter(main_type__in=maintypes)
for community in communities:
events = Event.objects.filter(sub_type__in=subtypes,
community=community)
now_num = len(events)
if now_num > max_num:
max_num = now_num
max_community = community
name = '社区'
categories.append(opts.GraphCategory(name=name))
index = len(categories) - 1
value = str(max_community)
nodes.append(
opts.GraphNode(name=value,
value=str(max_num),
symbol_size=50,
category=index))
links.append(
opts.GraphLink(source=str(model), target=value, value='发生最多的社区'))
def create_node(source_node,
categories,
cate_name,
nodes,
node_name,
links,
link_name,
node_value='-'):
categories.append(opts.GraphCategory(cate_name))
print(cate_name)
length = len(categories) - 1
nodes.append(
opts.GraphNode(name=node_name,
value=node_value,
symbol_size=50,
category=length))
print(node_name)
links.append(
opts.GraphLink(source=source_node, target=node_name, value=link_name))
print(link_name)
return 0
def set_type_node(model_name, model, categories, nodes, links):
if model_name == 'SubType':
sub_model = model
model = model.main_type
thetype = model.type
type_number = model.type.number
name = '类型'
categories.append(opts.GraphCategory(name=name))
index = len(categories) - 1
value = str(thetype)
if (model_name == 'SubType'
and value == str(sub_model)) or value == str(model):
value = value + '（问题类型）'
nodes.append(
opts.GraphNode(name=value,
symbol_size=50,
category=index,
value=type_number))
links.append(opts.GraphLink(source=str(model), target=value, value='类型'))
return 0
def get_subtype_data(model_name, model):
categories = [opts.GraphCategory(name='小类')]
number = model.number
nodes = [
opts.GraphNode(name=str(model),
symbol_size=100,
category=0,
value=number)
]
links = []
id = SubType.objects.filter(name=str(model)).values("id")[0]['id']
sub_model = SubType.objects.filter(id=id)[0]
try:
# 小类所属大类
node_name = str(sub_model.main_type)
print(node_name)
cate_name = '大类'
link_name = '所属大类'
source_node = str(model)
maintype_number = sub_model.main_type.number
create_node(source_node,
categories,
cate_name,
nodes,
node_name,
links,
link_name,
node_value=maintype_number)
# 小类发生最多的社区名
coms = Event.objects.filter(
sub_type_id=id).values('community').annotate(
count=Count('community')).values('community',
'count').order_by('-count')
coms = list(coms)
com = coms[0]
com_name = Community.objects.get(id=com['community']).name
print(com_name)
node_name = com_name
cate_name = '社区'
link_name = '小类发生最多社区'
source_node = str(model)
create_node(source_node,
categories,
cate_name,
nodes,
node_name,
links,
link_name,
node_value=str(com['count']))
# 小类编号
sub_model = SubType.objects.filter(id=id)[0]
aid = sub_model.aID
node_name = str(aid)
cate_name = '编号'
link_name = '小类编号'
source_node = str(model)
create_node(source_node, categories, cate_name, nodes, node_name,
links, link_name)
# 小类事件总数
node_name = str(sub_model.number)
print(node_name)
cate_name = '数量'
link_name = '事件总数'
source_node = str(model)
create_node(source_node,
categories,
cate_name,
nodes,
node_name,
links,
link_name,
node_value=node_name)
except Exception as e:
print(e)
return categories, nodes, links
def echarts_Location(graph,
h,
x,
y,
symbol_size=5,
line_width=1,
width="1400px",
height="800px",
path='locationExample.html',
title='Location_Graph',
subtitle='',
showName=True,
font_size=15,
edge_symbol_size=10,
pageLayout=Page.SimplePageLayout,
show_node_value=True,
show_edge_value=True,
render=True):
"""
A method to render a network in location layout.
Parameter(s):
-------------
graph : TemporalDiGraph
An object which represents a temporal, directed graph consisting of nodes and temporal arcs.
h : int
The threshold of temporal reachability. Nodes will be assigned different color based on this value.
x : String
The name of the x coordinates of the nodes.
For example, in the network of London subway stations, the name of x coordinate can be 'lon' or 'lat'.
y : String
The name of the y coordinates of the nodes.
For example, in the network of London subway stations, the name of x coordinate can be 'lon' or 'lat'.
symbol_size : int
The size of the nodes.
line_width : int
The width of the edges.
width: String
The width of the image.
Default value: 1200px
height: String
The height of the image.
Decault value: 600px
path : String
The path of the rendered image.
Default value: forceExample.html
title : String
The title of the rendered image.
Default value: Location_Graph
subtitle : String
The subtitle of the rendered image.
Default value: ''
showName : boolean
Whether to show the name of nodes.
Default value: True
font_size : int
The font size of the value on the nodes.
Default value: 10
edge_symbol_size : int
The size of the symbol on the edges.
Default value: 10
pageLayout : PageLayoutOpts
There are two kinds of page layout: Page.DraggablePageLayout and Page.SimplePageLayout.
In Page.SimplePageLayout, the width and height of the image border is stable.
While in Page.DraggablePageLayout, the image border can be changed.
Default value: Page.SimplePageLayout
show_node_value : boolean
Whether to show the reachability of nodes.
Default value: True
show_edge_value : boolean
Whether to show the start time and end time of edges.
Default value: False
render : boolean
Whether to generate the html file directly.
Default value: True
Returns:
--------
c : Graph
basic charts object in pyecharts package
"""
# initialize nodes list
nodes = []
if show_node_value:
for i in range(len(graph.nodes.aslist())):
# calculate reachability for each nodes
reachability = ot.calculate_reachability(graph,
graph.nodes.labels()[i])
if reachability > h:
nodes.append(
opts.GraphNode(name=graph.nodes.labels()[i],
category=0,
x=graph.nodes.aslist()[i].data[x],
y=graph.nodes.aslist()[i].data[y],
label_opts=opts.LabelOpts(
is_show=showName, font_size=font_size),
value=reachability))
else:
nodes.append(
opts.GraphNode(name=graph.nodes.labels()[i],
category=1,
x=graph.nodes.aslist()[i].data[x],
y=graph.nodes.aslist()[i].data[y],
label_opts=opts.LabelOpts(
is_show=showName, font_size=font_size),
value=reachability))
else:
for i in range(len(graph.nodes.aslist())):
# calculate reachability for each nodes
reachability = ot.calculate_reachability(graph,
graph.nodes.labels()[i])
if reachability > h:
nodes.append(
opts.GraphNode(name=graph.nodes.labels()[i],
category=0,
x=graph.nodes.aslist()[i].data[x],
y=graph.nodes.aslist()[i].data[y],
label_opts=opts.LabelOpts(
is_show=showName, font_size=font_size)))
else:
nodes.append(
opts.GraphNode(name=graph.nodes.labels()[i],
category=1,
x=graph.nodes.aslist()[i].data[x],
y=graph.nodes.aslist()[i].data[y],
label_opts=opts.LabelOpts(
is_show=showName, font_size=font_size)))
# initialize links list
links = []
if show_edge_value:
# initialize value list of edges
edge_value = []
# 1. compare all edge labels with unique edge labels to find which edges are duplicated
# 2. edge value of duplicate edges will be added to the same list and shown together
for i in range(len(graph.edges.labels())):
for j in range(len(graph.edges.ulabels())):
if graph.edges.labels()[i] == graph.edges.ulabels()[j]:
if j < len(edge_value):
edge_value[j].append(
'{start time: ' +
str(graph.edges.start_times()[i]) +
', end time: ' + str(graph.edges.end_times()[i]) +
'}')
else:
tmp_edge_value = []
tmp_edge_value.append(
'{start time: ' +
str(graph.edges.start_times()[i]) +
', end time: ' + str(graph.edges.end_times()[i]) +
'}')
edge_value.append(tmp_edge_value)
# print the rate of progress
print('rate of progress: {}%'.format(
(i + 1) / len(graph.edges.labels()) * 100))
for i in range(len(graph.edges.ulabels())):
tmp = graph.edges.ulabels()[i].split('-')
links.append(
opts.GraphLink(source=tmp[0],
target=tmp[1],
value=edge_value[i]))
else:
for i in range(len(graph.edges.ulabels())):
tmp = graph.edges.ulabels()[i].split('-')
links.append(opts.GraphLink(source=tmp[0], target=tmp[1]))
# initialize categories list
categories = [
opts.GraphCategory(
name='nodes with reachability more than {}'.format(h)),
opts.GraphCategory(
name='nodes with reachability less than or equal to {}'.format(h))
]
# generate an html file of the graph
c = (Graph(init_opts=opts.InitOpts(width=width, height=height)).add(
"",
nodes=nodes,
links=links,
categories=categories,
layout="none",
symbol_size=symbol_size,
linestyle_opts=opts.LineStyleOpts(is_show=True,
curve=0.1,
width=line_width),
label_opts=opts.LabelOpts(position="right"),
edge_symbol=['circle', 'arrow'],
edge_symbol_size=symbol_size).set_global_opts(
title_opts=opts.TitleOpts(
title=title,
subtitle=subtitle,
title_textstyle_opts=opts.TextStyleOpts(font_size=40),
subtitle_textstyle_opts=opts.TextStyleOpts(font_size=20)),
legend_opts=opts.LegendOpts(
orient="vertical",
pos_left="2%",
pos_top="20%",
textstyle_opts=opts.TextStyleOpts(font_size=20)),
))
if render:
page = Page(layout=pageLayout)
page.add(c)
page.render(path)
return c
def echarts_Timeline(graph,
h,
x='',
y='',
symbol_size=20,
line_width=1,
repulsion=500,
is_draggable=True,
width="800px",
height="500px",
path='timelineExample.html',
title='Timeline_graph',
subtitle='',
pageLayout=Page.DraggablePageLayout,
layout="circular",
show_node_value=True,
render=True):
"""
A method to render a network with timeline.
Parameter(s):
-------------
graph : TemporalDiGraph
An object which represents a temporal, directed graph consisting of nodes and temporal arcs.
h : int
The threshold of temporal reachability. Nodes will be assigned different color based on this value.
x : String
The name of the x coordinates of the nodes.
For example, in the network of London subway stations, the name of x coordinate can be 'lon' or 'lat'.
y : String
The name of the y coordinates of the nodes.
For example, in the network of London subway stations, the name of x coordinate can be 'lon' or 'lat'.
symbol_size : int
The size of the nodes.
line_width : int
The width of the edges.
repulsion : int
The repulsion between nodes.
is_draggable : boolean
Whether the nodes are moveable.
width: String
The width of the image.
Default value: 800px
height: String
The height of the image.
Decault value: 500px
path : String
The path of the rendered image.
Default value: circleExample.html
title : String
The title of the rendered image.
Default value: Circle_Graph
subtitle : String
The subtitle of the rendered image.
Default value: ''
pageLayout : PageLayoutOpts
There are two kinds of page layout: Page.DraggablePageLayout and Page.SimplePageLayout.
In Page.SimplePageLayout, the width and height of the image border is stable.
While in Page.DraggablePageLayout, the image border can be changed.
Default value: Page.DraggablePageLayout
layout : String
There are three kinds of image layout: circular, force and none
If the layout is none, you have to provide the x-coordinate and y-coordinate of nodes.
show_node_value : boolean
Whether show the reachability of nodes.
Default value: True
render : boolean
Whether generate the html file directly.
Default value: True
Returns:
--------
c : Graph
basic charts object in pyecharts package
"""
# initialize nodes list
nodes = []
if layout == 'none':
for i in range(len(graph.nodes.aslist())):
# calculate reachability for each nodes
reachability = ot.calculate_reachability(graph,
graph.nodes.labels()[i])
if reachability > h:
# nodes with reachability more than h will be assigned category 0
nodes.append(
opts.GraphNode(name=graph.nodes.labels()[i],
x=graph.nodes.aslist()[i].data[x],
y=graph.nodes.aslist()[i].data[y],
category=0,
value=reachability))
else:
# nodes with reachability less than or equal to h will be assigned category 1
nodes.append(
opts.GraphNode(name=graph.nodes.labels()[i],
x=graph.nodes.aslist()[i].data[x],
y=graph.nodes.aslist()[i].data[y],
category=1,
value=reachability))
else:
for i in range(len(graph.nodes.aslist())):
# calculate reachability for each nodes
reachability = ot.calculate_reachability(graph,
graph.nodes.labels()[i])
if reachability > h:
# nodes with reachability more than h will be assigned category 0
nodes.append(
opts.GraphNode(name=graph.nodes.labels()[i],
category=0,
value=reachability))
else:
# nodes with reachability less than or equal to h will be assigned category 1
nodes.append(
opts.GraphNode(name=graph.nodes.labels()[i],
category=1,
value=reachability))
# initialize links list
links = []
for i in graph.edges.timespan():
tmpLinks = []
for j in range(len(graph.edges.labels())):
if graph.edges.start_times()[j] == i:
tmp = graph.edges.labels()[j].split('-')
edgeval = '{start time: ' + str(
graph.edges.start_times()[j]) + ', end time: ' + str(
graph.edges.end_times()[j]) + '}'
tmpLinks.append(
opts.GraphLink(source=tmp[0], target=tmp[1],
value=edgeval))
links.append(tmpLinks)
# initialize categories list
categories = [
opts.GraphCategory(
name='nodes with reachability more than {}'.format(h)),
opts.GraphCategory(
name='nodes with reachability less than or equal to {}'.format(h))
]
tl = Timeline()
for i in graph.edges.timespan():
c = (Graph(init_opts=opts.InitOpts(width=width, height=height)).add(
"",
nodes=nodes,
links=links[i - graph.edges.start_times()[0]],
categories=categories,
layout=layout,
is_draggable=is_draggable,
is_rotate_label=True,
symbol_size=symbol_size,
linestyle_opts=opts.LineStyleOpts(is_show=True,
curve=0.1,
color="source",
width=line_width),
label_opts=opts.LabelOpts(position="right"),
edge_symbol=['circle', 'arrow'],
edge_symbol_size=10).set_global_opts(
title_opts=opts.TitleOpts(
title=title,
subtitle=subtitle,
title_textstyle_opts=opts.TextStyleOpts(font_size=40),
subtitle_textstyle_opts=opts.TextStyleOpts(font_size=20)),
legend_opts=opts.LegendOpts(
orient="vertical",
pos_left="2%",
pos_top="20%",
textstyle_opts=opts.TextStyleOpts(font_size=20)),
))
tl.add(c, "{}".format(i))
# if render is True, generate an html file
if render:
page = Page(layout=pageLayout)
page.add(tl)
page.render(path)
return c
def graph_with_opts() -> Graph:
g = []
layer_sizes = [2, 2, 1]
pos = negmas_draw.negmas_layout(g, layer_sizes)
nodes = [
opts.GraphNode(name="n1",
x=pos[0][0],
y=pos[0][1],
symbol_size=10,
category='c1'),
opts.GraphNode(name="n2",
x=pos[1][0],
y=pos[1][1],
symbol_size=20,
category='c2'),
opts.GraphNode(name="n3",
x=pos[2][0],
y=pos[2][1],
symbol_size=30,
category='c3'),
opts.GraphNode(name="n4",
x=pos[3][0],
y=pos[3][1],
symbol_size=40,
category='c1'),
opts.GraphNode(name="n5",
x=pos[4][0],
y=pos[4][1],
symbol_size=50,
category='c1'),
]
linestyleopts = [
opts.LineStyleOpts(width=5),
]
links = [
opts.GraphLink(source="n1", target="n2"),
opts.GraphLink(source="n2", target="n3"),
opts.GraphLink(source="n3", target="n4"),
opts.GraphLink(source="n4", target="n5"),
opts.GraphLink(source="n5", target="n1"),
]
categories = [
opts.GraphCategory(name='c1'),
opts.GraphCategory(name='c2'),
opts.GraphCategory(name='c3'),
opts.GraphCategory(name='c4'),
opts.GraphCategory(name='c5'),
]
c = (Graph().add("",
nodes,
links,
categories,
edge_symbol=['', 'arrow'],
edge_symbol_size=10,
layout='none',
repulsion=4000,
emphasis_itemstyle_opts=linestyleopts[0]).set_global_opts(
title_opts=opts.TitleOpts(title="")))
return c
def echarts_Circular(graph,
h,
symbol_size=20,
line_width=1,
width="800px",
height="500px",
curve_list=[0.1, 0.3],
path='circleExample.html',
title='Circle_Graph',
subtitle='',
pageLayout=Page.DraggablePageLayout,
show_node_value=True,
show_edge_value=True,
render=True):
"""
A method to render a network in circular layout.
Parameter(s):
-------------
graph : TemporalDiGraph
An object which represents a temporal, directed graph consisting of nodes and temporal arcs.
h : int
The threshold of temporal reachability. Nodes will be assigned different color based on this value.
symbol_size : int
The size of the nodes.
line_width : int
The width of the edges.
width: String
The width of the image.
Default value: 800px
height: String
The height of the image.
Decault value: 500px
curve_list : list
A list contains one or two values which represent the curvature of edges.
If you give two values in this list, then duplicate edges (a->b, b->a) will be rendered using different curvature.
Otherwise, duplicate edges will be rendered using the same curvature.
Decault value: [0.1, 0.3]
path : String
The path of the rendered image.
Default value: circleExample.html
title : String
The title of the rendered image.
Default value: Circle_Graph
subtitle : String
The subtitle of the rendered image.
Default value: ''
pageLayout : PageLayoutOpts
There are two kinds of page layout: Page.DraggablePageLayout and Page.SimplePageLayout.
In Page.SimplePageLayout, the width and height of the image border is stable.
While in Page.DraggablePageLayout, the image border can be changed.
Default value: Page.DraggablePageLayout
show_node_value : boolean
Whether show the reachability of nodes.
Default value: True
show_edge_value : boolean
Whether show the start time and end time of edges.
Default value: True
render : boolean
Whether generate the html file directly.
Default value: True
Returns:
--------
c : Graph
basic charts object in pyecharts package
"""
# initialize nodes list
nodes = []
if show_node_value:
for i in range(len(graph.nodes.aslist())):
# calculate reachability for each nodes
reachability = ot.calculate_reachability(graph,
graph.nodes.labels()[i])
if reachability > h:
# nodes with reachability more than h will be assigned category 0
nodes.append(
opts.GraphNode(name=graph.nodes.labels()[i],
category=0,
value=reachability))
else:
# nodes with reachability less than or equal to h will be assigned category 1
nodes.append(
opts.GraphNode(name=graph.nodes.labels()[i],
category=1,
value=reachability))
else:
for i in range(len(graph.nodes.aslist())):
# calculate reachability for each nodes
reachability = ot.calculate_reachability(graph,
graph.nodes.labels()[i])
if reachability > h:
# nodes with reachability more than h will be assigned category 0
nodes.append(
opts.GraphNode(name=graph.nodes.labels()[i], category=0))
else:
# nodes with reachability less than or equal to h will be assigned category 1
nodes.append(
opts.GraphNode(name=graph.nodes.labels()[i], category=1))
# initialize links list
links = []
# used to check duplicate edges
edge_list = []
# accumulate the appearance times of each edge
accumulator = np.zeros(len(graph.edges.labels()))
if show_edge_value:
# initialize value list of edges
edge_value = []
# 1. compare all edge labels with unique edge labels to find which edges are duplicated
# 2. edge value of duplicate edges will be added to the same list and shown together
for i in range(len(graph.edges.labels())):
for j in range(len(graph.edges.ulabels())):
if graph.edges.labels()[i] == graph.edges.ulabels()[j]:
if j < len(edge_value):
edge_value[j].append(
'{start time: ' +
str(graph.edges.start_times()[i]) +
', end time: ' + str(graph.edges.end_times()[i]) +
'}')
else:
tmp_edge_value = []
tmp_edge_value.append(
'{start time: ' +
str(graph.edges.start_times()[i]) +
', end time: ' + str(graph.edges.end_times()[i]) +
'}')
edge_value.append(tmp_edge_value)
# print the rate of progress
print('rate of progress: {}%'.format(
(i + 1) / len(graph.edges.labels()) * 100))
# check duplicate edges
# 1. get nodes' name by spliting the edge labels
# 2. transform them to set and compare them with elements in 'edge_list'
# 3. if they are not duplicated, add them to 'edge_list'
for i in range(len(graph.edges.ulabels())):
tmp = graph.edges.ulabels()[i].split('-')
flag = True
for j in np.arange(0, len(edge_list)):
if set(tmp) == set(edge_list[j]):
accumulator[i] = 1
flag = False
break
if flag:
edge_list.append(tmp)
# add links
# duplicate edges with different direction will be rendered based on their corresponding curvature
# duplicate edges with the same direction will be rendered only once
links.append(
opts.GraphLink(source=tmp[0],
target=tmp[1],
value=edge_value[i],
linestyle_opts=opts.LineStyleOpts(
curve=curve_list[int(accumulator[i]) %
len(curve_list)])))
else:
# check duplicate edges
for i in range(len(graph.edges.ulabels())):
tmp = graph.edges.labels()[i].split('-')
flag = True
for j in np.arange(0, len(edge_list)):
if set(tmp) == set(edge_list[j]):
accumulator[i] = 1
flag = False
break
if flag:
edge_list.append(tmp)
links.append(
opts.GraphLink(source=tmp[0],
target=tmp[1],
linestyle_opts=opts.LineStyleOpts(
curve=curve_list[int(accumulator[i]) %
len(curve_list)])))
# initialize categories list
categories = [
opts.GraphCategory(
name='nodes with reachability more than {}'.format(h)),
opts.GraphCategory(
name='nodes with reachability less than or equal to {}'.format(h))
]
# generate an html file of the graph
c = (Graph(init_opts=opts.InitOpts(width=width, height=height)).add(
"",
nodes=nodes,
links=links,
categories=categories,
layout="circular",
is_rotate_label=True,
symbol_size=symbol_size,
linestyle_opts=opts.LineStyleOpts(color="source", width=line_width),
label_opts=opts.LabelOpts(position="right"),
edge_symbol=['circle', 'arrow'],
edge_symbol_size=10).set_global_opts(
title_opts=opts.TitleOpts(
title=title,
subtitle=subtitle,
title_textstyle_opts=opts.TextStyleOpts(font_size=40),
subtitle_textstyle_opts=opts.TextStyleOpts(font_size=20)),
legend_opts=opts.LegendOpts(
orient="vertical",
pos_left="2%",
pos_top="20%",
textstyle_opts=opts.TextStyleOpts(font_size=20)),
))
# if render is True, generate an html file
if render:
page = Page(layout=pageLayout)
page.add(c)
page.render(path)
return c
def get_community_data(model_name, model):
com_number = model.number
categories = [opts.GraphCategory(name='社区')]
nodes = [
opts.GraphNode(name=str(model),
symbol_size=100,
category=0,
value=com_number)
]
links = []
id = Community.objects.filter(name=str(model)).values("id")[0]['id']
com_model = Community.objects.filter(id=id)[0]
try:
# 社区所属街道
str_number = com_model.street.number
node_name = str(com_model.street)
print(node_name)
cate_name = '街道'
link_name = '所属街道'
source_node = str(com_model)
create_node(source_node,
categories,
cate_name,
nodes,
node_name,
links,
link_name,
node_value=str_number)
# 编号
aid = com_model.aID
node_name = str(aid)
cate_name = '编号'
link_name = '社区编号'
create_node(source_node, categories, cate_name, nodes, node_name,
links, link_name)
# 事件最多类型
type_count = Event.objects.filter(
community=id).values('type').annotate(count=Count('type')).values(
'type', 'count').order_by('-count')
type_count = list(type_count)
tid = type_count[0]['type']
t = Type.objects.filter(id=tid)[0]
c = type_count[0]['count']
node_name = str(t)
cate_name = '类型'
link_name = '事件最多类型'
create_node(source_node,
categories,
cate_name,
nodes,
node_name,
links,
link_name,
node_value=str(c))
# 社区事件总数
node_name = str(com_model.number)
# print(node_name)
cate_name = '数量'
link_name = '事件总数'
create_node(source_node, categories, cate_name, nodes, node_name,
links, link_name)
# 事件占街道百分比
strt = com_model.street
x = com_model.number
y = strt.number
percentage = round(x * 100 / y, 2)
cate_name = '百分比'
node_name = str(percentage) + '%'
link_name = '事件占街道百分比'
create_node(source_node, categories, cate_name, nodes, node_name,
links, link_name)
except Exception as e:
print(e)
return categories, nodes, links
def get_property_data(model_name, model):
events = model.event.get_queryset()
intime_number = 0
intime_to_number = 0
overtime_number = 0
community_list = {}
for event in events:
achieve = event.achieve.name
community = event.community.name
if community in community_list.keys():
community_list[community] += 1
else:
community_list.update({community: 1})
if achieve == "执行中":
intime_to_number += 1
elif achieve == '按期办结':
overtime_number += 1
elif achieve == "逾期办结":
intime_number += 1
number_max = 0
for key in community_list:
if community_list[key] > number_max:
community = key
number_max = community_list[key]
community_model = Community.objects.get(name=community)
street = community_model.street
district = street.district
categories = [
opts.GraphCategory(name="事件性质"),
opts.GraphCategory(name="事件数量"),
opts.GraphCategory(name="百分比"),
opts.GraphCategory(name="百分比"),
# opts.GraphCategory(name="逾期办结"),
opts.GraphCategory(name="社区"),
opts.GraphCategory(name="街道"),
opts.GraphCategory(name="区域"),
]
nodes = [
opts.GraphNode(name=str(model), symbol_size=80, category=0),
opts.GraphNode(name=str(model.number), symbol_size=50, category=1),
opts.GraphNode(name=str(
(round(intime_to_number * 100 / model.number, 2))) + '%',
symbol_size=50,
category=2),
opts.GraphNode(name=str(
(round(intime_number * 100 / model.number, 2))) + '%',
symbol_size=50,
category=3),
# opts.GraphNode(name=str(overtime_number), symbol_size=50, category=4),
opts.GraphNode(name=community, symbol_size=50, category=5),
opts.GraphNode(name=street.name, symbol_size=40, category=6),
opts.GraphNode(name=district.name, symbol_size=30, category=7),
]
links = [
opts.GraphLink(source=str(model),
target=str(model.number),
value='事件总数'),
opts.GraphLink(source=str(model),
target=str(
(round(intime_to_number * 100 / model.number, 2))) +
'%',
value='执行中事件百分比'),
opts.GraphLink(
source=str(model),
target=str((round(intime_number * 100 / model.number, 2))) + '%',
value='按期办结百分比'),
# opts.GraphLink(source=str(model), target=str(overtime_number), value=50),
opts.GraphLink(source=str(model),
target=community,
value=str(model) + "下最多社区"),
opts.GraphLink(source=community, target=street.name, value="对应街道"),
opts.GraphLink(source=street.name, target=district.name, value="对应区域"),
]
return categories, nodes, links
def pre_graph_data(df):
#筛选数据&去除全为空值的行
volunteer_cols = [
'volunteer_1', 'volunteer_2', 'volunteer_3', 'volunteer_4',
'volunteer_5'
]
graph_data = df[['school'] + volunteer_cols]
notna_idx = graph_data[volunteer_cols].dropna(how='all').index
graph_data = graph_data.loc[notna_idx]
#高中名称添加(高)
def add_high_school(x):
try:
return (x + '(高)')
except:
return x
graph_data[volunteer_cols] = graph_data[volunteer_cols].applymap(
add_high_school)
nodes = []
#初中学校
for school_name in graph_data['school'].unique():
count = (graph_data['school'] == school_name).sum()
nodes.append(
opts.GraphNode(name=school_name,
symbol_size=int(count),
value=int(count),
category='初中'))
#第一批次学校
first_batch = (graph_data['volunteer_1'].append(
graph_data['volunteer_2'])).dropna()
for school_name in first_batch.unique():
count = (first_batch == school_name).sum()
nodes.append(
opts.GraphNode(name=school_name,
symbol_size=int(count),
value=int(count),
category='第一批次'))
#第二批次学校
second_batch = (graph_data['volunteer_3'].append(
graph_data['volunteer_4']).append(graph_data['volunteer_5'])).dropna()
for school_name in second_batch.unique():
count = (second_batch == school_name).sum()
nodes.append(
opts.GraphNode(name=school_name,
symbol_size=int(count),
value=int(count),
category='第二批次'))
def data2links(pivot_data, color):
'''
将分志愿计数的dataframe处理成links
'''
links = []
for idx in pivot_data.index:
for col in pivot_data.columns:
if not np.isnan(pivot_data.loc[idx, col]):
links.append(
opts.GraphLink(source=idx,
target=col,
value=int(pivot_data.loc[idx, col]),
linestyle_opts=opts.LineStyleOpts(
width=int(pivot_data.loc[idx, col]),
color=color,
curve=0.2)))
return links
#各志愿对应的线条颜色
colors = ['#FF8947', '#41E89D', '#FF8947', '#41E89D', '#557EFF']
links = []
for volunteer, color in list(zip(volunteer_cols, colors)):
pivot_data = graph_data.pivot_table(index='school',
columns=volunteer,
aggfunc='size')
link = data2links(pivot_data, color)
links += link
#Categories
categories = [
opts.GraphCategory(name='初中'),
opts.GraphCategory(name='第一批次'),
opts.GraphCategory(name='第二批次')
]
return nodes, links, categories
def get_graph(request):
# data_num = request.GET.get('data_num')
data_all = [[
"2020/11/29", "福田区 香景大厦", "深圳市城市管理和综合执法局", "投诉", "晚上城市作业车在楼下作业"
], ["2020/11/23", " ", "市场监督局", "感谢", "投诉积极响应"],
["2020/11/24", "皇岗口岸附近", " ", "投诉", "施工扰民", "噪音超标"],
["2020/11/21", "三联山咀头小区", "深圳人居委", "投诉", "施工 没有降噪措施"],
["2020/11/21", " ", "深圳交委", "投诉", "宜停车 钓鱼执法"]]
data = data_all
cate = ["时间", "地点", "部门", "性质", "事件"]
link_value = ["发生时间", "发生地点", "责任部门", "事件性质", "事件本身"]
categories_all = []
nodes_all = []
links_all = []
nodes_name = []
node_index = 0
for record in data:
categories = []
nodes = []
links = []
for c in cate:
print("cate:" + c + "\n")
categories.append(opts.GraphCategory(name=c))
for anode, i in zip(record, range(0, len(cate))):
print("node:" + anode + "\n")
if anode == " ":
pass
else:
if is_node_exist(nodes_name, anode) == -1:
nodes.append(
opts.GraphNode(name=anode, symbol_size=80, category=i))
nodes_name.append(anode)
node_index += len(nodes_name) - 1
else:
node_index = is_node_exist(nodes_name, anode)
for anode, i in zip(record, range(0, len(link_value) - 1)):
print("link:" + record[4] + "->" + link_value[i] + "->" +
record[i] + "\n")
if anode == record[4]:
pass
else:
links.append(
opts.GraphLink(source=record[4],
target=anode,
value=link_value[i]))
categories_all = categories_all + categories
nodes_all = nodes_all + nodes
links_all = links_all + links
page = "graph"
kgraph = to_graph(categories_all, nodes_all, links_all)
context = {
'graph': kgraph,
"page": page,
'cur_page': "kgraph",
}
return render(request, 'tograph/tograph.html', context)
