def test_treemap_options(fake_writer):
c = TreeMap().add("演示数据", example_data, width="90%", height="100%", roam=False)
c.render()
_, content = fake_writer.call_args[0]
assert_in("width", content)
assert_in("height", content)
assert_in("roam", content)
def test_treemap_base(fake_writer):
data = [
{"value": 40, "name": "我是A"},
{
"value": 180,
"name": "我是B",
"children": [
{
"value": 76,
"name": "我是B.children",
"children": [
{"value": 12, "name": "我是B.children.a"},
{"value": 28, "name": "我是B.children.b"},
{"value": 20, "name": "我是B.children.c"},
{"value": 16, "name": "我是B.children.d"},
],
}
],
},
]
c = TreeMap().add("演示数据", data)
c.render()
_, content = fake_writer.call_args[0]
eq_(c.theme, "white")
eq_(c.renderer, "canvas")
def create_type_likes(df):
# 分组求和
likes_type_message = df.groupby(['category'])
likes_type_com = likes_type_message['likes'].agg(['sum'])
likes_type_com.reset_index(inplace=True)
# 处理数据
dom = []
for name, num in zip(likes_type_com['category'], likes_type_com['sum']):
data = {}
data['name'] = name
data['value'] = num
dom.append(data)
print(dom)
# 初始化配置
treemap = TreeMap(init_opts=opts.InitOpts(width="800px", height="400px"))
# 添加数据
treemap.add('', dom)
# 设置全局配置项，标题、工具箱(下载图片)
treemap.set_global_opts(title_opts=opts.TitleOpts(title="各类型抖音大V点赞数汇总图",
pos_left="center",
pos_top="5"),
toolbox_opts=opts.ToolboxOpts(
is_show=True, feature={"saveAsImage": {}}),
legend_opts=opts.LegendOpts(is_show=False))
treemap.render("各类型抖音大V点赞数汇总图.html")
def draw_tree_picture(data, to_file, svg_name, colors=None):
c = TreeMap(init_opts=opts.InitOpts(width="800px", height="600px", bg_color='white')) \
.add("", data) \
.set_global_opts(legend_opts=opts.LegendOpts(is_show=False), ) \
.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}", position='top'))
c.render(to_file)
to_svg(to_file, svg_name)
def test_treemap_base():
data = [
{"value": 40, "name": "我是A"},
{
"value": 180,
"name": "我是B",
"children": [
{
"value": 76,
"name": "我是B.children",
"children": [
{"value": 12, "name": "我是B.children.a"},
{"value": 28, "name": "我是B.children.b"},
{"value": 20, "name": "我是B.children.c"},
{"value": 16, "name": "我是B.children.d"},
],
}
],
},
]
c = TreeMap().add("演示数据", data)
assert c.theme == "white"
assert c.renderer == "canvas"
c.render("render.html")
def treemap_base() -> TreeMap:
data = [
{"value": 40, "name": "我是A"},
{
"value": 180,
"name": "我是B",
"children": [
{
"value": 76,
"name": "我是B.children",
"children": [
{"value": 12, "name": "我是B.children.a"},
{"value": 28, "name": "我是B.children.b"},
{"value": 20, "name": "我是B.children.c"},
{"value": 16, "name": "我是B.children.d"},
],
}
],
},
]
c = (
TreeMap()
.add("演示数据", data)
.set_global_opts(title_opts=opts.TitleOpts(title="TreeMap-基本示例"))
)
return c
def treemap_official():
with open(os.path.join("fixtures", "treemap.json"), "r",
encoding="utf-8") as f:
data = json.load(f)
c = (TreeMap().add(
"演示数据",
data).set_global_opts(title_opts=opts.TitleOpts(title="TreeMap-官方示例")))
return c
def paint_treemap():
data = get.get_treemap_data(get.get_today())
charts = (TreeMap(init_opts=opts.InitOpts(width="80%", height="400%")).add(
"world",
data=data["children"],
label_opts=opts.LabelOpts(position="inside"),
).set_global_opts(
legend_opts=opts.LegendOpts(is_show=True),
title_opts=opts.TitleOpts(title="世界累计确诊分布", pos_left="leafDepth"),
))
return charts
def test_treemap_levels_options(fake_writer):
c = TreeMap().add(
"演示数据",
example_data,
width="90%",
height="100%",
roam=False,
levels=opts.TreeMapLevelsOpts(),
)
c.render()
_, content = fake_writer.call_args[0]
assert_in("levels", content)
def pyechart_Tree_plot(self, filedata, para):
from pyecharts.charts import Tree, TreeMap
file_name = '树图.html'
path_plotly = self.path_dir_plotly_html + os.sep + file_name # 文件路径，前面是文件夹后面是文件名
costumeTheme = self.themedict[para['theme']]
costomSymbol = self.symboldict[para['Tsymbol']]
# -----------------------------------------------------------------------
#df = pd.read_excel(r"E:\5-程序设计\A-编程语言\01Python\自定义\Pyecharts\组合\template\树.xlsx", sheet_name='Sheet1')
df = pd.read_excel(filedata, sheet_name='Sheet1')
dic = self.Tree_dict(df)
print(dic)
if para['Tstate'][0]:
Tr = (
# 数据特点：可以没有value值
Tree(
init_opts=opts.InitOpts(theme=costumeTheme,
renderer="canvs",
width=para['width'],
height=para['height'])
).add(
"",
dic,
layout=para['Tlayout'],
collapse_interval=2,
orient="LR",
symbol=costomSymbol,
symbol_size=para['Tsymbol_size'],
# label_opts=opts.LabelOpts(is_show=True, color=para["color"], position="top",
# font_size=para["font_size"],
# font_family=para["font_family"])
))
chart = Tr
elif para['Tstate'][1]:
c = (
TreeMap(init_opts=opts.InitOpts(
theme=costumeTheme,
renderer="canvs",
width=para['width'],
height=para['height'])).add(
series_name="演示数据",
data=dic,
leaf_depth=para['leaf_depth'], #节点深度,开启下钻，不完全显示
))
chart = c
# add() missing 2 required positional arguments: 'series_name' and 'data'
self.Common_code(chart, path_plotly, para)
return path_plotly # 返回该HTML文件路径
def treemap(d, series_name):
c = (
TreeMap()
.add(series_name, d)
.set_series_opts(
label_opts=opts.LabelOpts(position="inside",
font_size=11,
font_weight='lighter',
formatter='{b}\n{c}'
),
)
.set_global_opts(toolbox_opts=opts.ToolboxOpts(is_show=True),
legend_opts=opts.LegendOpts(is_show=False),
)
)
return c
def test_treemap_options(fake_writer):
data = [
{
"value": 40,
"name": "我是A"
},
{
"value":
180,
"name":
"我是B",
"children": [{
"value":
76,
"name":
"我是B.children",
"children": [
{
"value": 12,
"name": "我是B.children.a"
},
{
"value": 28,
"name": "我是B.children.b"
},
{
"value": 20,
"name": "我是B.children.c"
},
{
"value": 16,
"name": "我是B.children.d"
},
],
}],
},
]
c = TreeMap().add("演示数据", data, width="90%", height="100%", roam=False)
c.render()
_, content = fake_writer.call_args[0]
assert_in("width", content)
assert_in("height", content)
assert_in("roam", content)
def to_treemap(data, proj, version):
complexity = {'name': f'{proj}-{version}', 'children': []}
extract(complexity, 'complexity', data)
maintainability = {'name': f'{proj}-{version}', 'children': []}
extract(maintainability, 'maintainability', data)
testability = {'name': f'{proj}-{version}', 'children': []}
extract(testability, 'testability', data)
readability = {'name': f'{proj}-{version}', 'children': []}
extract(readability, 'readability', data)
reusability = {'name': f'{proj}-{version}', 'children': []}
extract(reusability, 'reusability', data)
inheritance = {'name': f'{proj}-{version}', 'children': []}
extract(inheritance, 'inheritance', data)
treemap = TreeMap()
for indicator in [
'complexity', 'maintainability', 'testability', 'readability',
'reusability', 'inheritance'
]:
treemap = treemap.add(series_name=indicator,
data=[locals()[indicator]],
leaf_depth=2,
roam=False,
label_opts=opts.LabelOpts(position='inside'))
treemap = (treemap.set_global_opts(
tooltip_opts=opts.TooltipOpts(formatter='{b}<br/>{a}: {c}'),
toolbox_opts=opts.ToolboxOpts(feature=opts.ToolBoxFeatureOpts(
magic_type=opts.ToolBoxFeatureMagicTypeOpts(is_show=False),
data_zoom=opts.ToolBoxFeatureDataZoomOpts(is_show=False),
brush=opts.ToolBoxFeatureBrushOpts(type_='clear'))),
legend_opts=opts.LegendOpts(is_show=True,
selected_mode='single',
pos_top='7%',
orient='horizontal',
padding=0),
title_opts=opts.TitleOpts(
title=f'Code Quality Treemap of {proj}-{version}',
pos_left='center')))
grid = Grid()
grid.add(treemap, grid_opts=opts.GridOpts(pos_top='100%'))
return grid
def test_treemap_base():
data = [
{
"value": 40,
"name": "我是A"
},
{
"value":
180,
"name":
"我是B",
"children": [{
"value":
76,
"name":
"我是B.children",
"children": [
{
"value": 12,
"name": "我是B.children.a"
},
{
"value": 28,
"name": "我是B.children.b"
},
{
"value": 20,
"name": "我是B.children.c"
},
{
"value": 16,
"name": "我是B.children.d"
},
],
}],
},
]
c = TreeMap().add("演示数据", data)
eq_(c.theme, "white")
eq_(c.renderer, "canvas")
c.render()
def make_star_treemap(self):
"""
根据演员参演电影数生成矩形树图
:return:
"""
# print(get_current_time() + '|-------> 正在生成 演员参演电影数 图表...')
# 导入数据并初始化
csv_path = os.path.abspath(os.path.join(os.path.dirname("__file__"), os.path.pardir, "moviespider", "movie_info_top500.csv"))
rows = pd.read_csv(csv_path, encoding='utf-8', dtype=str)
# rows = pd.read_csv('../comments/movie_info_top500.csv', encoding='utf-8', dtype=str)
to_drop = ['名称', '导演', '年份', '国别', '类型', '语言', '评分', '评分人数', '五星占比', '四星占比', '三星占比', '二星占比', '一星占比', '短评数',
'简介']
res = rows.drop(to_drop, axis=1)
# 数据分割
all_star_list = []
for i in res.itertuples():
# print(i[1] + '\n')
for j in i[1].split(','):
all_star_list.append(j)
# 数据统计
df = pd.DataFrame(all_star_list, columns=['演员'])
res = df.groupby('演员')['演员'].count().sort_values(ascending=False)
all_star_list = []
for i in res.items():
if i[1] > 4:
all_star_list.append({"value": i[1], "name": i[0]})
# 生成图标
c = TreeMap()
c.add("参演电影数", all_star_list)
c.set_global_opts(title_opts=opts.TitleOpts(title="电影TOP500榜单中 - 演员参演电影数", subtitle="至少参演5部影评以上"))
htmlPath = os.path.abspath(os.path.join(os.path.abspath(os.path.dirname(os.path.dirname(__file__))), "analyse_data", "演员参演电影数.html"))
pngPath = os.path.abspath(os.path.join(os.path.abspath(os.path.dirname(os.path.dirname(__file__))), "analyse_data", "演员参演电影数.png"))
# 生成html
c.render(htmlPath)
# 生成png
# make_snapshot(snapshot, c.render(), pngPath)
# print(get_current_time() + '|-------> 已生成 演员参演电影数 图表...')
return c
def create_type_fans(df):
dom = []
fans_type_message = df.groupby(['category'])
fans_type_com = fans_type_message['fans'].agg(['sum'])
fans_type_com.reset_index(inplace=True)
for name, num in zip(fans_type_com['category'], fans_type_com['sum']):
data = {}
data['name'] = name
data['value'] = num
dom.append(data)
print(dom)
treemap = TreeMap(init_opts=opts.InitOpts(width="800px", height="400px"))
treemap.add('', dom)
treemap.set_global_opts(title_opts=opts.TitleOpts(title="各类型抖音大V粉丝数汇总图",
pos_left="center",
pos_top="5"),
toolbox_opts=opts.ToolboxOpts(
is_show=True, feature={"saveAsImage": {}}),
legend_opts=opts.LegendOpts(is_show=False))
treemap.set_series_opts(treemapbreadcrumb_opts=opts.TreeMapBreadcrumbOpts(
is_show=False))
treemap.render("各类型抖音大V粉丝数汇总图.html")
def show_genres():
data=select_data()
# 矩形树图初始化
treemap = TreeMap(init_opts=opts.InitOpts(page_title="豆瓣电影-电影类型分布"))
# 添加数据
treemap.add(
series_name='电影类型',
data=data,
# 标签居中
label_opts=opts.LabelOpts(font_size=15, position="inside"),
)
# 全局配置
treemap.set_global_opts(
# 标题
title_opts=opts.TitleOpts(
title="豆瓣电影-电影类型分布", pos_left='center'
),
# 标签隐藏
legend_opts=opts.LegendOpts(is_show=False)
)
# 生成HTML
html="pages/iframes/genres.html"
treemap.render("./templates/"+html)
return html
label_opts=opts.LabelOpts(formatter="{b}: {c}",
font_size=16), ).render('热搜词饼图.html'))
resou_word_love = resou_word_love.sort_values('count',
ascending=False).reset_index()
words = [(resou_word_love['word'][i], resou_word_love['num'][i])
for i in range(resou_word_love.shape[0])]
pie = (Pie(init_opts=opts.InitOpts(theme=ThemeType.CHALK)).add(
"", words).set_global_opts(
title_opts=opts.TitleOpts(title="微博婚恋类词语出现次数", pos_left='center'),
legend_opts=opts.LegendOpts(is_show=False)).set_series_opts(
label_opts=opts.LabelOpts(formatter="{b}: {c}",
font_size=16), ).render('婚恋类热搜词饼图.html'))
resou_word_person = resou_word_person.sort_values(
'num', ascending=False).reset_index()
words = [{
'"value": {}, "name": {}"'.format(str(resou_word_person['num'][i]),
resou_word_person['name'][i])
} for i in range(resou_word_person.shape[0])]
tree = (TreeMap(init_opts=opts.InitOpts(theme=ThemeType.ESSOS)).add(
"", words, pos_left=0, pos_right=0, pos_top=50,
pos_bottom=50).set_global_opts(
title_opts=opts.TitleOpts(title="热搜明星出现次数排名", pos_left='center'),
legend_opts=opts.LegendOpts(is_show=False)).set_series_opts(
label_opts=opts.LabelOpts(formatter="{b}\n\n {c}",
font_size=17,
color='black',
position='inside',
font_weight='bolder')).render('排序.html'))
import json
from pyecharts import options as opts
from pyecharts.charts import TreeMap
with open("treemap.json", "r", encoding="utf-8") as f:
data = json.load(f)
c = (TreeMap().add(
series_name="演示数据",
data=data,
levels=[
opts.TreeMapLevelsOpts(
treemap_itemstyle_opts=opts.TreeMapItemStyleOpts(
border_color="#555", border_width=4, gap_width=4)),
opts.TreeMapLevelsOpts(
color_saturation=[0.3, 0.6],
treemap_itemstyle_opts=opts.TreeMapItemStyleOpts(
border_color_saturation=0.7, gap_width=2, border_width=2),
),
opts.TreeMapLevelsOpts(
color_saturation=[0.3, 0.5],
treemap_itemstyle_opts=opts.TreeMapItemStyleOpts(
border_color_saturation=0.6, gap_width=1),
),
opts.TreeMapLevelsOpts(color_saturation=[0.3, 0.5]),
],
).set_global_opts(title_opts=opts.TitleOpts(
title="TreeMap-Levels-配置")).render("Treemap_levels.html"))
from pyecharts import options as opts
from pyecharts.charts import TreeMap
data = [
{"value": 40, "name": "我是A"},
{
"value": 180,
"name": "我是B",
"children": [
{
"value": 76,
"name": "我是B.children",
"children": [
{"value": 12, "name": "我是B.children.a"},
{"value": 28, "name": "我是B.children.b"},
{"value": 20, "name": "我是B.children.c"},
{"value": 16, "name": "我是B.children.d"},
],
}
],
},
]
c = (
TreeMap()
.add("演示数据", data)
.set_global_opts(title_opts=opts.TitleOpts(title="TreeMap-基本示例"))
.render("Treemap_base.html")
)
data = [
{"value": 40, "name": "我是A"},
{
"value": 180,
"name": "我是B",
"children": [
{
"value": 76,
"name": "我是B.children",
"children": [
{"value": 12, "name": "我是B.children.a"},
{"value": 28, "name": "我是B.children.b"},
{"value": 20, "name": "我是B.children.c"},
{"value": 16, "name": "我是B.children.d"},
],
}
],
},
]
c = (
TreeMap()
.add("演示数据", data)
.set_global_opts(title_opts=opts.TitleOpts(title="TreeMap-基本示例"))
)
c.width = "100%"
put_html(c.render_notebook())
def treeMapChart(df):
type_of_plot = st.selectbox("Select Type of Plot",["TreeMap1 Multi-level","TreeMap2"])
# allc = list(df.columns[:20])
# allc
# tmap = px.treemap(df,path=[allc, "Enfants de 0 à 14 ans", "CJE"], values= "Population 2016")
# return tmap
all_columns = df.columns
treemap = TreeMap()
if type_of_plot == "TreeMap1 Multi-level":
columns_to_plot = st.selectbox("Select 1 column",all_columns,key='a' )
columns_to_plot1 = st.selectbox("Select 2 column",[col for col in df.columns if col not in [columns_to_plot]], key='b' )
# columns_to_plot2 = st.selectbox("Select 3 column",[col for col in df.columns if col not in [columns_to_plot, columns_to_plot1]], key='c' )
names = list(df[columns_to_plot])
def get_all_values(d):
if isinstance(d, dict):
for v in d.values():
yield from get_all_values(v)
elif isinstance(d, list):
for v in d:
yield from get_all_values(v)
else:
yield d
dictionaryObject = df.to_dict();
# print(list(get_all_values(dictionaryObject)))
df2 = df.copy()
df3 = df.drop('CJE', axis=1)
df3.values.tolist()
values_market = df3.values.tolist()
df2 = df.copy()
# print(values_market)
childs = []
for j,indu_one in enumerate(names):
data_now = df2[df2[columns_to_plot]==indu_one]
data_1 = list(data_now[columns_to_plot])
# print(data_now.values.tolist())
child = []
child.extend({'name':data_1[i],'value':list(data_now[columns_to_plot])[i]} for i in range(0,len(data_now[columns_to_plot])))
childs.append(child)
data_n = [{ 'name':i,'value':j, 'children': m} for i,j,m in zip(names,values_market,childs)]
treemap.add(series_name="option",data=data_n,visual_min=300,leaf_depth=1,
label_opts=opts.LabelOpts(position="inside"),)
return treemap
if type_of_plot == "TreeMap2":
columns_to_plot = st.selectbox("Select 1 column",all_columns,key='a' )
columns_to_plot1 = st.selectbox("Select 1 column",[col for col in df.columns if col not in [columns_to_plot]], key='b' )
names = list(df[columns_to_plot])
values_market = list(df[columns_to_plot1])
df2 = df.copy()
childs = []
data_n = [{'name':i, 'value':j,'value1':j} for i,j in zip(names,values_market)]
# treemap = TreeMap(init_opts=opts.InitOpts(height='1080px',width='1920px'))
treemap.add(
series_name=columns_to_plot1,
data=data_n,
leaf_depth=2,
node_click="zoomToNode",
zoom_to_node_ratio=0.5*0.5,
levels=[
opts.TreeMapLevelsOpts(
#color_mapping_by='value',
upper_label_opts= opts.LabelOpts(position="inside") ,
treemap_itemstyle_opts=opts.TreeMapItemStyleOpts(
border_color="#555", border_width=4, gap_width=4
)
),
opts.TreeMapLevelsOpts(
upper_label_opts= opts.LabelOpts(position="inside"),
color_saturation=[0.3, 0.6],
treemap_itemstyle_opts=opts.TreeMapItemStyleOpts(
border_color_saturation=0.7, gap_width=2, border_width=2
),
),
# opts.TreeMapLevelsOpts(
# color_saturation=[0.3, 0.5],
# treemap_itemstyle_opts=opts.TreeMapItemStyleOpts(
# border_color_saturation=0.6, gap_width=1
# ),
# ),
# opts.TreeMapLevelsOpts(color_saturation=[0.3, 0.5]),
],
)
treemap.set_series_opts(label_opts=opts.LabelOpts(
is_show = True,
position = 'inside',# position 'top'，'left'，'right'，'bottom'，'inside'，'insideLeft'，'insideRight'.....
font_size = 20,
# color
color= '#ffffff',
# font_style 'normal'，'italic'，'oblique'
font_style = 'nomal' ,
# font_weight 'normal'，'bold'，'bolder'，'lighter'
font_weight = None,
# font_family 'Arial', 'Courier New', 'Microsoft YaHei' ....
font_family = 'Microsoft YaHei',
# rotate -90 90
rotate = '0',
# margin
margin = 20,
interval = None,
# horizontal_align 'left'，'center'，'right'
horizontal_align = 'center',
# vertical_align ：'top'，'middle'，'bottom'
vertical_align = None,
) )
treemap.set_global_opts(toolbox_opts=opts.ToolboxOpts(pos_left='8%'),
title_opts=opts.TitleOpts(title="TreeMap"))
return treemap
import json
from pyecharts.charts import TreeMap
import pyecharts.options as opts
with open('GDP_data_1.json', 'r', encoding='utf-8') as f:
j = json.load(f)
data = [j]
map = TreeMap(init_opts=opts.InitOpts(width='1200px', height='800px'))
map.add(
'',
data,
label_opts=opts.LabelOpts(position='inside'),
)
map.render('map.html')
'value': '1',
'name': '人力资源管理'
}]
},
]
treemap = (
TreeMap().add(
'各专业体育检测抽样人数',
data,
pos_left='center', # 主图的位置
tooltip_opts=opts.TooltipOpts(is_show=True),
# 子标签展示，大小，字体
label_opts=opts.LabelOpts(is_show=True,
font_size=14,
font_family='serif',
vertical_align='top')).
set_global_opts(
title_opts=opts.TitleOpts(title='矩形树图\n'), # 图左上角:标题
legend_opts=opts.LegendOpts(is_show=True), # 图上面中间:图例
toolbox_opts=opts.ToolboxOpts(is_show=True), # 图右上角:工具箱
# tooltip_opts=opts.TooltipOpts(is_show=True), # 图上:提示框
# visualmap_opts=opts.VisualMapOpts(is_show=True), # 图右下角:视觉映射
))
# 图的宽高
treemap.width = '1000px'
treemap.height = '600px'
# 保存为html文件
treemap.render('./data/treemap.html')
if base_path != "":
path = base_path + "." + key
else:
path = key
if re.match(r"/^\$/", key):
pass
else:
child = {"name": path, "children": []}
target["children"].append(child)
if isinstance(source[key], dict):
convert(source[key], child, path)
else:
target["value"] = source["$count"]
convert(source=data, target=tree_map_data, base_path="")
(TreeMap(init_opts=opts.InitOpts(width="1200px", height="720px")).add(
series_name="option",
data=tree_map_data["children"],
visual_min=300,
leaf_depth=1,
# 标签居中为 position = "inside"
label_opts=opts.LabelOpts(position="inside"),
).set_global_opts(
legend_opts=opts.LegendOpts(is_show=False),
title_opts=opts.TitleOpts(title="Echarts 配置项查询分布",
subtitle="2016/04",
pos_left="leafDepth"),
).render("echarts_option_query.html"))
def plot_tree(self, depth=3):
data = self.describe_tree(self.tree)
tree_map = TreeMap()
tree_map.add(self.name, data, leaf_depth=depth, width=800, height=600)
tree_map.render()
return tree_map
"name":
"我是B",
"children": [{
"value":
76,
"name":
"我是B.children",
"children": [
{
"value": 12,
"name": "我是B.children.a"
},
{
"value": 28,
"name": "我是B.children.b"
},
{
"value": 20,
"name": "我是B.children.c"
},
{
"value": 16,
"name": "我是B.children.d"
},
],
}],
},
]
maptree = TreeMap()
maptree.add("", data).render_notebook()
def test_treemap_base(fake_writer):
c = TreeMap().add("演示数据", example_data)
c.render()
_, content = fake_writer.call_args[0]
assert_equal(c.theme, "white")
assert_equal(c.renderer, "canvas")
def generate_treemap_html(cur,
title,
key_field_name,
area_field_name,
click_link,
area_data_name='数量',
area_data_unit='个'):
data, item_opts = [], []
min_rise = 100
max_rise = -100
for row in cur.fetchall():
item = get_dict_row(cur, row)
rise_value = item['涨跌']
if rise_value > max_rise:
max_rise = rise_value
if rise_value < min_rise:
min_rise = rise_value
if rise_value > 0:
rise = '\n+{}%'.format(rise_value)
rich = {
'name': {
'fontSize': 14,
'color': '#000'
},
'涨跌': {
'fontSize': 14,
'fontWeight': 'bolder',
"align": "center",
'color': '#FF0000'
}
}
tree_item = opts.TreeMapItemStyleOpts(color_alpha=1,
color='rgb(255,0,0)',
border_color='#fff')
else:
rise = '\n{}%'.format(rise_value)
rich = {
'name': {
'fontSize': 14,
'color': '#000'
},
'涨跌': {
'fontSize': 14,
'fontWeight': 'bolder',
"align": "center",
'color': '#2E8B57'
}
}
tree_item = opts.TreeMapItemStyleOpts(color_alpha=1,
color='rgb(60,179,113)',
border_color='#fff')
data.append(
opts.TreeItem(
name=item[key_field_name],
# value 包含持仓占比和涨跌幅两项数据
value=[item[area_field_name], rise_value],
label_opts=opts.LabelOpts(position='insideBottomLeft',
formatter='{name|{b}}{rise|%s}' %
rise,
rich=rich)))
item_opts.append(tree_item)
color_range, rise_range = calc_range(max_rise, min_rise)
tooltip_js = """function (param)
{ const color = param.value[1] > 0 ? '#FF0000' : '#2E8B57';
const detail_style = `color:${color};`;
const msgContent = `<div style='width:fit-content;height:fit-content;'>
${param.name}<br/>
""" + area_data_name + """： <span style='color:'#fff';'> ${param.value[0]} """ + area_data_unit + """  </span><br/>
涨跌： <span style='${detail_style};'> ${param.value[1]} %  </span><br/>
<div>`;
return msgContent}
"""
tp = TreeMap(init_opts=opts.InitOpts(
theme='white', width='1424px', height='700px', chart_id='cb_tree_map'))
tp.add_js_funcs(
"""
chart_cb_tree_map.on('click', function(params){
// alert(params)
window.location.replace('""" + click_link +
"""?key=' + encodeURIComponent(params['data']['name']) + '&rise=' + params['data']['value'][1] + '#cb_detail_list')
})
""")
tp.add(
'ALL',
data,
roam=False,
node_click='link',
width='90%',
breadcrumb_opts=opts.TreeMapBreadcrumbOpts(is_show=False),
levels=[
opts.TreeMapLevelsOpts(
treemap_itemstyle_opts=opts.TreeMapItemStyleOpts(
gap_width=1, stroke_width=1, stroke_color='#fff'),
color_mapping_by='value',
)
],
tooltip_opts=opts.TooltipOpts(
is_show=True,
formatter=JsCode(tooltip_js),
textstyle_opts=opts.TextStyleOpts(font_size=14)),
color_mapping_by='value',
)
tp.set_global_opts(
title_opts=opts.TitleOpts(title=title,
pos_left='center',
pos_top='30px'),
legend_opts=opts.LegendOpts(is_show=False),
visualmap_opts=opts.VisualMapOpts(
is_show=False,
type_='color',
min_=min_rise,
max_=max_rise,
range_color=color_range,
# 指定使用的数据维度
dimension=1,
is_piecewise=True,
pieces=rise_range),
)
return tp.render_embed('template.html', env)