def draw_map_world(data, to_file, svg_name, label_name, number_max):
"""
画地图
:param data:
:param to_file:
:param svg_name:
:param label_name: 图例名称
:param number_max: 最大值
:return:
"""
geo = Map(init_opts=opts.InitOpts(width="800px", height="600px", bg_color='rgb(255, 255, 255)')) \
.add(label_name, data, maptype="world") \
.set_series_opts(label_opts=opts.LabelOpts(is_show=False),
showLegendSymbol=False) \
.set_global_opts(legend_opts=opts.LegendOpts(item_width=50,
item_height=30,
textstyle_opts=opts.TextStyleOpts(font_size=30)),
visualmap_opts=opts.VisualMapOpts(min_=0,
max_=int(number_max),
background_color='rgb(255, 255, 255)',
is_piecewise=True,
item_width=50,
item_height=30,
textstyle_opts=opts.TextStyleOpts(font_size=30)),
toolbox_opts=opts.ToolboxOpts(
feature=opts.ToolBoxFeatureOpts(
data_zoom=opts.ToolBoxFeatureDataZoomOpts(is_show=False),
# brush=opts.ToolBoxFeatureBrushOpts(is_show=False),
)
),
)
# geo.render(to_file)
make_snapshot(snapshot, geo.render(to_file), svg_name) # 生成svg图片
def draw_river_picture_right_legend(series_name,
data,
to_file,
svg_name,
pos_right,
width='800px'):
"""
主题河流图
:param width:
:param pos_right:
:param series_name: [str]
:param data: [[date, value, series_name]]
:param svg_name: svg文件
:param to_file: 结果文件
:return:
"""
bar = ThemeRiver(init_opts=opts.InitOpts(width="800px", height="600px", bg_color='white')) \
.add(
series_name=series_name,
data=data,
singleaxis_opts=opts.SingleAxisOpts(
pos_top="50",
pos_bottom="50",
type_="time",
name_textstyle_opts=opts.TextStyleOpts(font_size=20),
axislabel_opts=opts.LabelOpts(font_size=20)
),
label_opts=opts.LabelOpts(is_show=False),
) \
.set_global_opts(
tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="line"),
toolbox_opts=opts.ToolboxOpts(
feature=opts.ToolBoxFeatureOpts(
data_zoom=opts.ToolBoxFeatureDataZoomOpts(is_show=False),
# brush=opts.ToolBoxFeatureBrushOpts(is_show=False),
)
),
legend_opts=opts.LegendOpts(pos_right=pos_right,
pos_top="2%",
orient="vertical",
item_width=30,
item_height=14,
textstyle_opts=opts.TextStyleOpts(font_size=18)
),
)
grid = (Grid(init_opts=opts.InitOpts(
width=width, height="600px", bg_color='rgb(255, 255, 255)')).add(
bar,
grid_opts=opts.GridOpts(pos_right='10%'),
is_control_axis_index=True))
make_snapshot(snapshot, grid.render(to_file), svg_name) # 生成svg图片
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 to_linechart(data, proj):
versions = [version['version_name'] for version in data]
linechart = Line().add_xaxis(xaxis_data=versions)
for indicator in [
'complexity', 'maintainability', 'testability', 'readability',
'reusability', 'inheritance'
]:
linechart = linechart.add_yaxis(
series_name=indicator,
y_axis=[round(version[indicator], 2) for version in data],
is_smooth=True,
label_opts=opts.LabelOpts(is_show=False),
linestyle_opts=opts.LineStyleOpts(width=2),
)
linechart = (linechart.set_global_opts(
tooltip_opts=opts.TooltipOpts(trigger="axis",
axis_pointer_type="cross"),
xaxis_opts=opts.AxisOpts(boundary_gap=False),
yaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(formatter="{value}"),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
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,
pos_top='middle',
pos_left='1%',
orient='vertical',
padding=0),
datazoom_opts=opts.DataZoomOpts(type_='slider',
range_start=0,
range_end=100),
title_opts=opts.TitleOpts(title=f'Code Quality Linechart of {proj}',
pos_left='center')))
grid = Grid()
grid.add(linechart, grid_opts=opts.GridOpts(pos_left='150'))
return grid
def dayloss_line_base(self, x, y, t, st):
c = (Line(
init_opts=opts.InitOpts(width="1000px", height="500px")
).add_xaxis(x).add_yaxis("线损率(%)", y, is_smooth=True).set_global_opts(
tooltip_opts=opts.TooltipOpts(is_show=True,
trigger="axis",
axis_pointer_type="cross"),
title_opts=opts.TitleOpts(title=t, subtitle=st),
xaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(rotate=-90),
max_interval=366,
type_="category",
axispointer_opts=opts.AxisPointerOpts(is_show=True,
type_="shadow"),
),
yaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(formatter="{value} %"),
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
toolbox_opts=opts.ToolboxOpts(feature=opts.ToolBoxFeatureOpts(
save_as_image=opts.ToolBoxFeatureSaveAsImageOpts(
pixel_ratio=2, background_color='white'),
restore=opts.ToolBoxFeatureRestoreOpts(is_show=False),
data_view=opts.ToolBoxFeatureDataViewOpts(is_show=False),
data_zoom=opts.ToolBoxFeatureDataZoomOpts(is_show=False),
magic_type=opts.ToolBoxFeatureMagicTypeOpts(is_show=False),
brush=opts.ToolBoxFeatureBrushOpts(type_='clear'),
))).set_series_opts(
label_opts=opts.LabelOpts(is_show=False),
markline_opts=opts.MarkLineOpts(
data=[
opts.MarkLineItem(y=6),
],
label_opts=opts.LabelOpts(is_show=False),
),
))
return c
def __init__(self, title: str, output: str):
self.title = title
self.output = output
self.datas = []
self.chart = (Line(init_opts=opts.InitOpts(
page_title=self.title,
theme=ThemeType.DARK,
width="1280px",
height="720px",
)).set_global_opts(
title_opts=opts.TitleOpts(title=self.title),
xaxis_opts=opts.AxisOpts(type_="value",
is_scale=True,
split_number=10,
name="bitrate/kbps"),
yaxis_opts=opts.AxisOpts(type_="value", is_scale=True,
name="vmaf"),
toolbox_opts=opts.ToolboxOpts(
is_show=True,
orient="vertical",
pos_left="right",
feature=opts.ToolBoxFeatureOpts(
save_as_image=opts.ToolBoxFeatureSaveAsImageOpts(
title="save as image", is_show=True),
restore=opts.ToolBoxFeatureRestoreOpts(is_show=False),
data_zoom=opts.ToolBoxFeatureDataZoomOpts(is_show=False),
data_view=opts.ToolBoxFeatureDataViewOpts(
is_show=False, is_read_only=True, title="data"),
magic_type=opts.ToolBoxFeatureMagicTypeOpts(is_show=False),
brush=opts.ToolBoxFeatureBrushOpts(type_=[]))),
legend_opts=opts.LegendOpts(pos_top="bottom"),
tooltip_opts=opts.TooltipOpts(
is_show=True,
formatter=pyecharts_utils.JsCode(
"function(x) {return x.seriesName + '<br/>bitrate '+ x.data[0] + ' kbps<br/>vmaf ' + x.data[1];}"
))))
def draw_bar_reverse_picture(xaxis_data,
data,
to_file,
unit,
svg_name,
stack,
y_name,
pos_left='25%'):
"""
多个y列，是否堆叠要确认下
:param pos_left: "25%"
:param is_reverse: xy轴是否反转
:param y_name: y轴名称
:param stack: boolean, 是否要堆叠
:param xaxis_data: x轴
:param data: {series_name, data}
:param svg_name: svg文件
:param to_file: 结果文件
:param unit: 横轴的数值的单位（加在每个横轴值后面，比如 月）
:return:
"""
xaxis_data = [str(i) + unit for i in xaxis_data]
bar = Bar(init_opts=opts.InitOpts(
width="800px", height="600px", bg_color='white')).add_xaxis( # 1250px
xaxis_data=xaxis_data,
# add_xaxis=opts.LabelOpts(formatter="{value}" + unit),
)
for series_name, y_axis in data.items():
if stack:
bar = bar.add_yaxis(
series_name=series_name,
stack='1',
# color="#d14a61",
y_axis=y_axis,
yaxis_index=0,
label_opts=opts.LabelOpts(is_show=False),
)
else:
bar = bar.add_yaxis(
series_name=series_name,
color="#61a0a8",
category_gap='50%',
y_axis=y_axis,
yaxis_index=0,
label_opts=opts.LabelOpts(is_show=True, position='right'),
)
bar = bar.set_global_opts(
yaxis_opts=opts.AxisOpts(
type_="category",
# min_=0,
# max_=250,
position="left",
offset=0,
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts()),
axislabel_opts=opts.LabelOpts(formatter="{value}", font_size=20),
),
xaxis_opts=opts.AxisOpts(
name=y_name,
name_textstyle_opts=opts.TextStyleOpts(font_size=20),
axislabel_opts=opts.LabelOpts(formatter="{value}", font_size=20),
),
tooltip_opts=opts.TooltipOpts(trigger="axis",
axis_pointer_type="cross"),
toolbox_opts=opts.ToolboxOpts(feature=opts.ToolBoxFeatureOpts(
data_zoom=opts.ToolBoxFeatureDataZoomOpts(is_show=False),
# brush=opts.ToolBoxFeatureBrushOpts(is_show=False),
)),
legend_opts=opts.LegendOpts(is_show=False),
)
bar = bar.reversal_axis()
grid = (
Grid(init_opts=opts.InitOpts(width="800px",
height="600px",
bg_color='rgb(255, 255, 255)')) # 800px
.add(bar,
grid_opts=opts.GridOpts(pos_left=pos_left),
is_control_axis_index=True))
make_snapshot(snapshot, grid.render(to_file), svg_name) # 生成svg图片
def draw_bar_picture(xaxis_data, data, to_file, unit, svg_name, stack, y_name):
"""
多个y列，是否堆叠要确认下
:param is_reverse: xy轴是否反转
:param y_name: y轴名称
:param stack: boolean, 是否要堆叠
:param xaxis_data: x轴
:param data: {series_name, data}
:param svg_name: svg文件
:param to_file: 结果文件
:param unit: 横轴的数值的单位（加在每个横轴值后面，比如 月）
:return:
"""
xaxis_data = [str(i) + unit for i in xaxis_data]
bar = Bar(init_opts=opts.InitOpts(
width="900px", height="600px", bg_color='white')).add_xaxis(
xaxis_data=xaxis_data,
# add_xaxis=opts.LabelOpts(formatter="{value}" + unit),
)
for series_name, y_axis in data.items():
if stack:
bar = bar.add_yaxis(
series_name=series_name,
stack='1',
# color="#d14a61",
y_axis=y_axis,
yaxis_index=0,
label_opts=opts.LabelOpts(is_show=False),
)
else:
bar = bar.add_yaxis(
series_name=series_name,
# color="#d14a61",
y_axis=y_axis,
yaxis_index=0,
label_opts=opts.LabelOpts(is_show=False),
)
bar = bar.set_global_opts(
yaxis_opts=opts.AxisOpts(
type_="value",
name=y_name,
name_textstyle_opts=opts.TextStyleOpts(font_size=15),
# min_=0,
# max_=250,
position="left",
offset=0,
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts()),
axislabel_opts=opts.LabelOpts(formatter="{value}", font_size=15),
),
xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(
formatter="{value}", font_size=15, interval=0), ),
tooltip_opts=opts.TooltipOpts(trigger="axis",
axis_pointer_type="cross"),
toolbox_opts=opts.ToolboxOpts(feature=opts.ToolBoxFeatureOpts(
data_zoom=opts.ToolBoxFeatureDataZoomOpts(is_show=False),
# brush=opts.ToolBoxFeatureBrushOpts(is_show=False),
)),
legend_opts=opts.LegendOpts(
item_width=25,
item_height=15,
textstyle_opts=opts.TextStyleOpts(font_size=15)),
)
make_snapshot(snapshot, bar.render(to_file), svg_name) # 生成svg图片
def draw_line_picture(xaxis_data, data, to_file, unit, svg_name, stack,
y_name):
"""
多条线，是否堆叠要确认下
:param label_right:
:param y_name: y轴名称
:param stack: boolean, 是否要堆叠
:param xaxis_data: x轴
:param data: {series_name, data}
:param svg_name: svg文件
:param to_file: 结果文件
:param unit: 横轴的数值的单位（加在每个横轴值后面，比如 月）
:return:
"""
xaxis_data = [str(i) + unit for i in xaxis_data]
bar = Line(init_opts=opts.InitOpts(
width="800px", height="600px", bg_color='white')).add_xaxis(
xaxis_data=xaxis_data,
# add_xaxis=opts.LabelOpts(formatter="{value}" + unit),
)
for series_name, y_axis in data.items():
if stack:
bar = bar.add_yaxis(
series_name=series_name,
is_smooth=True,
symbol="circle",
# symbol_size=8,
stack='1',
is_symbol_show=False,
# color="#d14a61",
y_axis=y_axis,
yaxis_index=0,
label_opts=opts.LabelOpts(is_show=False),
# linestyle_opts=opts.LineStyleOpts(width=2),
areastyle_opts=opts.AreaStyleOpts(opacity=1))
else:
bar = bar.add_yaxis(
series_name=series_name,
is_smooth=True,
symbol="circle",
symbol_size=8,
is_symbol_show=True,
# color="#d14a61",
y_axis=y_axis,
yaxis_index=0,
label_opts=opts.LabelOpts(is_show=False),
linestyle_opts=opts.LineStyleOpts(width=2),
)
bar = bar.set_global_opts(
yaxis_opts=opts.AxisOpts(
type_="value",
name=y_name,
name_textstyle_opts=opts.TextStyleOpts(font_size=25),
# min_=0,
# max_=250,
position="left",
offset=0,
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts()),
axislabel_opts=opts.LabelOpts(formatter="{value}", font_size=25),
),
xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(
formatter="{value}", font_size=25, interval=0), ),
tooltip_opts=opts.TooltipOpts(trigger="axis",
axis_pointer_type="cross"),
toolbox_opts=opts.ToolboxOpts(feature=opts.ToolBoxFeatureOpts(
data_zoom=opts.ToolBoxFeatureDataZoomOpts(is_show=False),
# brush=opts.ToolBoxFeatureBrushOpts(is_show=False),
)),
legend_opts=opts.LegendOpts(
pos_left="12%",
pos_top="10%",
orient="vertical",
# backgroundColor='rgb(255, 255, 255)',
item_width=40,
item_height=20,
textstyle_opts=opts.TextStyleOpts(font_size=25)),
)
make_snapshot(snapshot, bar.render(to_file), svg_name) # 生成svg图片
def draw_line_with_two_y(xaxis_data, y1_series_name, y1_axis, y2_series_name,
y2_axis, y3_series_name, y3_axis, y1_name, y2_name,
to_file, unit, svg_name):
"""
左边是 两条线； 右边是 一条线。
:param svg_name: svg文件
:param xaxis_data: 横轴
:param y1_series_name: 左边第一条线的系列名
:param y1_axis: 左边第一条线的数值
:param y2_series_name: 左边第二条线的系列名
:param y2_axis: 左边第二条线的数值
:param y3_series_name: 右边第一条线的系列名
:param y3_axis: 右边第一条线的数值
:param y1_name: 左边的纵轴名称
:param y2_name: 右边的纵轴名称
:param to_file: 结果文件
:param unit: 横轴的数值的单位（加在每个横轴值后面，比如 月）
:return:
"""
xaxis_data = [str(i) + unit for i in xaxis_data]
bar = Line(init_opts=opts.InitOpts(
width="800px", height="600px", bg_color='white'
)).add_xaxis(
xaxis_data=xaxis_data,
# add_xaxis=opts.LabelOpts(formatter="{value}" + unit),
).add_yaxis(
series_name=y1_series_name,
is_smooth=True,
symbol="circle",
symbol_size=8,
is_symbol_show=True,
# color="#d14a61",
y_axis=y1_axis,
yaxis_index=0,
label_opts=opts.LabelOpts(is_show=False),
linestyle_opts=opts.LineStyleOpts(width=2),
).add_yaxis(
series_name=y2_series_name,
is_smooth=True,
symbol="circle",
symbol_size=8,
is_symbol_show=True,
# color="#d14a61",
y_axis=y2_axis,
yaxis_index=0,
label_opts=opts.LabelOpts(is_show=False),
linestyle_opts=opts.LineStyleOpts(width=2),
).add_yaxis(
series_name=y3_series_name,
is_smooth=True,
symbol="circle",
symbol_size=8,
is_symbol_show=True,
# color="#d14a61",
y_axis=y3_axis,
yaxis_index=1,
label_opts=opts.LabelOpts(is_show=False),
linestyle_opts=opts.LineStyleOpts(width=2),
).extend_axis(yaxis=opts.AxisOpts(
type_="value",
name=y2_name,
# min_=0,
# max_=25,
position="right",
axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts()),
axislabel_opts=opts.LabelOpts(formatter="{value}", font_size=15),
splitline_opts=opts.SplitLineOpts(
is_show=True, linestyle_opts=opts.LineStyleOpts(opacity=1)),
name_textstyle_opts=opts.TextStyleOpts(font_size=15))).set_global_opts(
yaxis_opts=opts.AxisOpts(
type_="value",
name=y1_name,
# min_=0,
# max_=250,
position="left",
offset=0,
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts()),
axislabel_opts=opts.LabelOpts(formatter="{value}",
font_size=15),
name_textstyle_opts=opts.TextStyleOpts(font_size=15)),
xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(
formatter="{value}", font_size=15), ),
tooltip_opts=opts.TooltipOpts(trigger="axis",
axis_pointer_type="cross"),
toolbox_opts=opts.ToolboxOpts(feature=opts.ToolBoxFeatureOpts(
data_zoom=opts.ToolBoxFeatureDataZoomOpts(is_show=False),
# brush=opts.ToolBoxFeatureBrushOpts(is_show=False),
)),
legend_opts=opts.LegendOpts(
item_width=25,
item_height=10,
textstyle_opts=opts.TextStyleOpts(font_size=15)),
)
make_snapshot(snapshot, bar.render(to_file), svg_name) # 生成svg图片
def day_sxdl(self, x, mc, a, b, c, k):
c = (Line(
init_opts=opts.InitOpts(width="1000px", height="500px")
).add_xaxis(x).add_yaxis("电压A", a, is_smooth=True).add_yaxis(
"电压B", b, is_smooth=True).add_yaxis(
"电压C", c, is_smooth=True).set_global_opts(
tooltip_opts=opts.TooltipOpts(is_show=True,
trigger="axis",
axis_pointer_type="cross"),
title_opts={
'text': mc,
'subtext': None
},
xaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(rotate=-90),
max_interval=366,
type_="category",
axispointer_opts=opts.AxisPointerOpts(is_show=True,
type_="shadow"),
),
yaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(formatter="{value} v"),
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
toolbox_opts=opts.
ToolboxOpts(feature=opts.ToolBoxFeatureOpts(
save_as_image=opts.ToolBoxFeatureSaveAsImageOpts(
pixel_ratio=2, background_color='white'),
restore=opts.ToolBoxFeatureRestoreOpts(is_show=False),
data_view=opts.ToolBoxFeatureDataViewOpts(
is_show=False),
data_zoom=opts.ToolBoxFeatureDataZoomOpts(
is_show=False),
magic_type=opts.ToolBoxFeatureMagicTypeOpts(
is_show=False),
brush=opts.ToolBoxFeatureBrushOpts(type_='clear'),
))).set_series_opts(label_opts=opts.LabelOpts(
is_show=False), ).extend_axis(
yaxis=opts.AxisOpts(name='方差',
axislabel_opts=opts.LabelOpts(
formatter="{value} "))))
line1 = Line().add_xaxis(x).add_yaxis(
"方差",
k,
yaxis_index=1,
is_smooth=True,
linestyle_opts=opts.LineStyleOpts(
color="black", width=2, type_="solid")).set_series_opts(
label_opts=opts.LabelOpts(is_show=False), )
c.overlap(line1)
return c
# def day_loss_1(self,x,y,t,st,z,m):
# c = self.dayloss_line_base(x,y,t,st)
# c = c.extend_axis(
# yaxis=opts.AxisOpts(
# axislabel_opts=opts.LabelOpts(formatter="{value} kWh")
# )
# ).extend_axis(
# yaxis=opts.AxisOpts(
# name = '数据完整率',
# position = 'right',
# offset = 62,
# axislabel_opts=opts.LabelOpts(formatter="{value} "),
# axisline_opts=opts.AxisLineOpts(
# linestyle_opts=opts.LineStyleOpts(color="#675bba")
# ),
# )
# )
# line = Line().add_xaxis(x).add_yaxis("供入电量", z,yaxis_index=1,is_smooth=True).set_series_opts(
# label_opts=opts.LabelOpts(is_show=False), )
# line_1 = Line().add_xaxis(x).add_yaxis("数据完整率", m,yaxis_index=2).set_series_opts(
# label_opts=opts.LabelOpts(is_show=False), )
# c.overlap(line)
# c.overlap(line_1)
# return c
# def day_loss_2(self,x,y,t,st,a,b):
# c = self.dayloss_line_base(x,y,t,st)
# c = c.extend_axis(
# yaxis=opts.AxisOpts(
# axislabel_opts=opts.LabelOpts(formatter="{value} kWh")
# )
# )
# line = Line().add_xaxis(a).add_yaxis("用电量", b,yaxis_index=1,is_smooth=True).set_series_opts(
# label_opts=opts.LabelOpts(is_show=False), )
# c.overlap(line)
# return c
# class electricity():
# """docstring for electricity"""
# def __init__(self,df):
# self.df = df
# def day_data(self,a):
# tq = self.df[self.df.测量点号==a][['数据时间','正向']].set_index('数据时间').sort_values(by='数据时间')
# x = [i[-5:] for i in tq.index]
# y = [float(i[0]) for i in tq.values]
# t = a
# return x,y,t
# def measure_num(self):
# num = set(i for i in self.df.测量点号)
# num = list(num)[1:]
# return num
# class relation(object):
# """docstring for relation"""
# def curr_relation(self,x,y,a,b):
# lineloss = pd.Series(y,index=x)
# day_electricity = pd.Series(b,index= a)
# c = lineloss.corr(day_electricity)
# # c1 = lineloss.cov(day_electricity)
# return c
# IO = '石鼓12月.xls'
# k = []
# day_loss = data(IO)
# tq_index = day_loss.day_lineloss_index()
# for i in tq_index:
# x,y,a,z,m = data(IO).day_lineloss(i)
# nc = relation().curr_relation(x,y,x,z)
# c = drawing().day_loss_1(x,y, a+ str(nc),z,m)
# k.append(c)
# drawing().all_day_lineloss(k,'石鼓12')
# IO = '石鼓12月.xls'
# name = '宝丰12.xlsx'
# num = electricity(name).measure_num()
# day_loss = data(IO)
# a,b,j,z,m = data(IO).day_lineloss('宝丰公用台变')
# k1 = []
# for i in num:
# x,y,t = electricity(name).day_data(i)
# c = relation().curr_relation(a,b,x,y)
# c1 = drawing().day_loss_2(a,b,str(t)+' & '+str(c),x,y)
# k1.append(c1)
# ny = np.array(electricity(name).day_data(92)[1]) + np.array(electricity(name).day_data(37)[1])
# c = relation().curr_relation(a,b,x,ny)
# c1 = drawing().day_loss_2(a,b,'9237'+str(c),x,ny)
# k1.append(c1)
# drawing().all_day_lineloss(k1,'宝丰12')
# k2 = []
# for i in num:
# x,y,t = electricity(name).day_data(i)
# c = relation().curr_relation(a,b,x,y)
# k2.append(c)
# print(str(c) + 10*'-'+str(i))
# print(10*'--')
# k3 = []
# nyy= []
# for i in num:
# x,y,t = electricity(name).day_data(i)
# c = relation().curr_relation(a,b,x,y)
# print(c[0])
# if c[0] > 0.5:
# nyy.append(np.array(y))
# c1 = drawing().day_loss_2(a,b,t,x,y)
# k3.append(c1)
# c2 = drawing().day_loss_2(a,b,'all',x,sum(nyy))
# k3.append(c2)
# drawing().all_day_lineloss(k3,'test_class_5')
# c = relation().curr_relation(a,b,x,sum(nyy))
# print(c)
def html_plot(file):
sp = file.split(".")
with open(file) as f:
l = f.readlines()
i = 0
ks = {}
for line in l:
if i == 0:
head = line.strip().split("\t")
i = 1
else:
t = line.strip().split("\t")
name = t[0]
del t[0]
ks[name] = t
bar = Bar(init_opts=opts.InitOpts(
page_title=sp[0] + "-ks.htmlpolt", width="1500px", height="700px"))
bar.add_xaxis(head)
for key, value in ks.items():
bar.add_yaxis(key,
value,
category_gap=0,
stack="stack1",
is_large=True)
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
bar.set_global_opts(
title_opts=opts.TitleOpts(title=sp[0] + ".ks.polt",
subtitle="Plot by Tree2gd v1.0"),
toolbox_opts=opts.ToolboxOpts(
is_show=True,
pos_top='10%',
orient='vertical',
pos_left='right',
feature=opts.ToolBoxFeatureOpts(
save_as_image=opts.ToolBoxFeatureSaveAsImageOpts(
title="Save as png"),
restore=opts.ToolBoxFeatureRestoreOpts(title="Recovery"),
data_view=opts.ToolBoxFeatureDataViewOpts(
title="Data", lang=['Data View', 'Close', 'Refresh']),
data_zoom=opts.ToolBoxFeatureDataZoomOpts(is_show=False),
magic_type=opts.ToolBoxFeatureMagicTypeOpts(
line_title="Switch to line plot",
bar_title="Switch to histogram plot",
stack_title="Switch to stack plot",
tiled_title="Switch to tiled plot"),
brush=opts.ToolBoxFeatureBrushOpts(
rect_title="Rectangle selection",
polygon_title="Circle selection",
line_x_title="X line selection",
line_y_title="Y line selection",
keep_title="Keep selection",
clear_title="Clear selection"),
)),
legend_opts=opts.LegendOpts(pos_left='right', ),
datazoom_opts=[
opts.DataZoomOpts(range_start=0, range_end=60),
opts.DataZoomOpts(type_="inside")
],
xaxis_opts=opts.AxisOpts(name="Ks"),
)
bar.render(os.sep.join(["..", "ks_html_plot",
sp[0] + ".ks.plot.html"]))
def day_sxdl(self, x, mc, a, b, c, m, n, rca, rcb, rcc, j, rcj):
c = (Line(
init_opts=opts.InitOpts(width="1000px", height="500px")
).add_xaxis(x).add_yaxis(
"电流A",
a,
is_smooth=True,
itemstyle_opts=opts.ItemStyleOpts(color='black')).add_yaxis(
"电流B",
b,
is_smooth=True,
itemstyle_opts=opts.ItemStyleOpts(color='blue')).add_yaxis(
"电流C",
c,
is_smooth=True,
itemstyle_opts=opts.ItemStyleOpts(
color='green')).set_global_opts(
tooltip_opts=opts.TooltipOpts(
is_show=True,
trigger="axis",
axis_pointer_type="cross"),
title_opts=opts.TitleOpts(
title=mc,
subtitle='A: ' + str(rca)[:12] + ' ' + 'B: ' +
str(rcb)[:12] + ' ' + 'C: ' + str(rcc)[:12] +
' '),
xaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(rotate=-90),
max_interval=366,
type_="category",
axispointer_opts=opts.AxisPointerOpts(
is_show=True, type_="shadow"),
),
yaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(
formatter="{value} A"),
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(
is_show=True),
),
toolbox_opts=opts.
ToolboxOpts(feature=opts.ToolBoxFeatureOpts(
save_as_image=opts.
ToolBoxFeatureSaveAsImageOpts(
pixel_ratio=2, background_color='white'),
restore=opts.ToolBoxFeatureRestoreOpts(
is_show=False),
data_view=opts.ToolBoxFeatureDataViewOpts(
is_show=False),
data_zoom=opts.ToolBoxFeatureDataZoomOpts(
is_show=False),
magic_type=opts.ToolBoxFeatureMagicTypeOpts(
is_show=False),
brush=opts.ToolBoxFeatureBrushOpts(
type_='clear'),
))).set_series_opts(
label_opts=opts.LabelOpts(is_show=False), ).
extend_axis(yaxis=opts.AxisOpts(name='线损率',
axislabel_opts=opts.LabelOpts(
formatter="{value} %"))))
line = (Line(init_opts=opts.InitOpts(
width="1000px", height="500px")).add_xaxis(m).add_yaxis(
"线损率",
n,
is_smooth=True,
linestyle_opts=opts.LineStyleOpts(color="red",
width=2,
type_="solid")
).set_series_opts(
label_opts=opts.LabelOpts(is_show=False), ).set_global_opts(
tooltip_opts=opts.TooltipOpts(is_show=True,
trigger="axis",
axis_pointer_type="cross"),
title_opts=opts.TitleOpts(title=mc,
subtitle='相关性系数: ' +
str(rcj)[:12]),
xaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(rotate=-90),
max_interval=366,
type_="category",
axispointer_opts=opts.AxisPointerOpts(is_show=True,
type_="shadow"),
),
yaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(formatter="{value} %"),
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
toolbox_opts=opts.
ToolboxOpts(feature=opts.ToolBoxFeatureOpts(
save_as_image=opts.ToolBoxFeatureSaveAsImageOpts(
pixel_ratio=2, background_color='white'),
restore=opts.ToolBoxFeatureRestoreOpts(is_show=False),
data_view=opts.ToolBoxFeatureDataViewOpts(
is_show=False),
data_zoom=opts.ToolBoxFeatureDataZoomOpts(
is_show=False),
magic_type=opts.ToolBoxFeatureMagicTypeOpts(
is_show=False),
brush=opts.ToolBoxFeatureBrushOpts(type_='clear'),
))).set_series_opts(label_opts=opts.LabelOpts(
is_show=False), ).extend_axis(
yaxis=opts.AxisOpts(name='方差',
axislabel_opts=opts.LabelOpts(
formatter="{value} "))))
line3 = (Line().add_xaxis(m).add_yaxis(
"线损率",
n,
yaxis_index=1,
is_smooth=True,
is_selected=False,
linestyle_opts=opts.LineStyleOpts(
color="red", width=2, type_="dotted")).set_series_opts(
label_opts=opts.LabelOpts(is_show=False), ))
line1 = Line().add_xaxis(x).add_yaxis(
"方差",
j,
yaxis_index=1,
is_smooth=True,
linestyle_opts=opts.LineStyleOpts(
color="black", width=2, type_="solid")).set_series_opts(
label_opts=opts.LabelOpts(is_show=False), )
d = line.overlap(line1)
c.overlap(line3)
return c, d
def Plot(self, jine: list, hushu: list, coef: list, date :str = None, title : str = None, size_def = lambda x: 50 if 10 + x > 50 else 10 + x):
##配置全局变量
j_list = [0 for _ in jine]
h_list = [0 for _ in hushu]
plot = Scatter(init_opts = opts.InitOpts(width = self.width, height = self.height, theme = self.theme))
plot.set_global_opts(
title_opts=opts.TitleOpts(title=title),
xaxis_opts = opts.AxisOpts(type_="value",
splitline_opts=opts.SplitLineOpts(is_show=False),
min_ = self.x_min, max_ = self.x_max,
name = self.data_name[self.x_index]),
yaxis_opts = opts.AxisOpts(type_="value",
splitline_opts=opts.SplitLineOpts(is_show=False),
min_ = self.y_min, max_ = self.y_max,
name = self.data_name[self.y_index]),
toolbox_opts = opts.ToolboxOpts(orient = 'horizontal', pos_top = 0,
feature = opts.ToolBoxFeatureOpts(
save_as_image = opts.ToolBoxFeatureSaveAsImageOpts(type_ = "jpeg", pixel_ratio = 4, background_color = 'white'),
restore = opts.ToolBoxFeatureRestoreOpts(),
data_zoom = opts.ToolBoxFeatureDataZoomOpts(),
data_view = opts.ToolBoxFeatureDataViewOpts(is_show = False),
magic_type = opts.ToolBoxFeatureMagicTypeOpts(is_show = False),
brush = opts.ToolBoxFeatureBrushOpts(type_=[]))),
tooltip_opts=opts.TooltipOpts(is_show=True, trigger="item", axis_pointer_type="cross")
)
##逐个添加点
for item in self.data_value:
#数据处理
local = str(item[self.local_index])
num = float(item[self.x_index])
gold = float(item[self.y_index])
name = str(item[self.name_index])
size = 0.
for s in range(len(self.size_index)):
size += item[self.size_index[s]]*self.size_coef[s]
tips = '日期:{}'.format(date)
for s in range(len(self.data_name)):
tips += '<br>'
tips += '{}:{}'.format(self.data_name[s], item[s])
#添加点及其tips
plot.add_xaxis([num])
plot.add_yaxis(local, [gold], symbol_size = size_def(size),
tooltip_opts=opts.TooltipOpts(formatter = tips),
label_opts=opts.LabelOpts(formatter = name))
#计算达标人数
for i in range(len(j_list)):
if gold >= jine[i]:
j_list[i] += 1
for i in range(len(h_list)):
if num >= hushu[i]:
h_list[i] += 1
##添加达标线及其注释点
for item in range(len(j_list)):
plot.add_xaxis([self.x_max])
plot.add_yaxis('达标线', [jine[item]], symbol_size = 25, symbol = 'pin',
label_opts = opts.LabelOpts(is_show = False),
tooltip_opts = opts.TooltipOpts(formatter = '达标人数:{}<br>未达标人数:{}'.format(j_list[item], self.num-j_list[item])),
markline_opts = opts.MarkLineOpts(data = [opts.MarkLineItem(y = jine[item], name = '金额达标线{}'.format(i+1))],
label_opts = opts.LabelOpts(is_show = False),
symbol_size = 0))
for item in range(len(h_list)):
plot.add_xaxis([hushu[item]])
plot.add_yaxis('达标线', [self.y_max], symbol_size = 25, symbol = 'pin',
label_opts = opts.LabelOpts(is_show = False),
tooltip_opts = opts.TooltipOpts(formatter = '奖励系数:x{}<br>达标人数:{}<br>未达标人数:{}'.format(coef[item], h_list[item], self.num-h_list[item])),
markline_opts = opts.MarkLineOpts(data = [opts.MarkLineItem(x = hushu[item], name = '户数达标线{}'.format(i+1))],
label_opts = opts.LabelOpts(is_show = False),
symbol_size = 0))
return plot
def plot_ground_truth_analysis(
all_score_columns: typing.List[str],
title: str,
output_path: str,
df: pd.DataFrame,
add_wrong_candidates: bool = False,
wrong_candidates_score_column: str = None,
) -> None:
"""
use pyechart to plot html interactive figure
"""
df_processed = copy.deepcopy(df)
for each_col in df_processed.columns:
df_processed[each_col] = pd.to_numeric(df_processed[each_col],
errors='ignore')
xaxis_labels = []
memo = defaultdict(list)
groupby_res = df_processed[df_processed["evaluation_label"] ==
1].groupby(["column", "row"])
for key, each_group in reversed(tuple(groupby_res)):
if add_wrong_candidates:
df_wrong_examples = df_processed[(df_processed["column"] == key[0]) &
(df_processed["row"] == key[1]) &
(df_processed["evaluation_label"] == -1)] \
.sort_values(by=[wrong_candidates_score_column], ascending=False).iloc[:3, :]
# add wrong candidate information
for _, each_row in df_wrong_examples.iterrows():
longest_string = max(each_row["kg_labels"].split("|"),
key=len)
xaxis_labels.append(each_row["label_clean"] +
" \n({})".format(longest_string))
for each_score_column in all_score_columns:
memo[each_score_column].append("{:.2f}".format(
each_row[each_score_column]))
# add ground truth information
xaxis_labels.append(each_group["label_clean"].iloc[0])
for each_score_column in all_score_columns:
memo[each_score_column].append("{:.2f}".format(
each_group[each_score_column].iloc[0]))
# build figure
bar = Bar()
bar.add_xaxis(xaxis_labels)
for k, v in memo.items():
bar.add_yaxis(k, v)
# set the global options
bar.set_global_opts(
title_opts=opts.TitleOpts(title=title, pos_left='40%'),
legend_opts=opts.LegendOpts(pos_left="center",
pos_top="bottom",
orient='horizontal'),
brush_opts=opts.BrushOpts(),
toolbox_opts=opts.ToolboxOpts(feature=opts.ToolBoxFeatureOpts(
save_as_image=opts.ToolBoxFeatureSaveAsImageOpts(
title="save as image"),
magic_type=opts.ToolBoxFeatureMagicTypeOpts(
line_title="switch to line chart",
bar_title="switch to bar chart",
stack_title="switch to stacked values",
tiled_title="switch to tiled values"),
data_zoom=opts.ToolBoxFeatureDataZoomOpts(
zoom_title="zoom in", back_title="zoom reset"),
restore=opts.ToolBoxFeatureRestoreOpts(title="reset"),
data_view=opts.ToolBoxFeatureDataViewOpts(
title="Data table view",
lang=["Table view", "Close", "Refresh"],
),
brush=opts.ToolBoxFeatureBrushOpts(
rect_title="rectangle choice",
polygon_title="polygon choice",
clear_title="clear choices",
keep_title="keep choices"))),
datazoom_opts=opts.DataZoomOpts(orient="vertical"),
# yaxis_opts=opts.AxisOpts(name='labels', name_gap=5000, name_rotate=15),
tooltip_opts=opts.TooltipOpts(is_show=True,
trigger="axis",
axis_pointer_type="shadow"),
xaxis_opts=opts.AxisOpts(axistick_opts=opts.AxisTickOpts(
is_inside=True,
length=850,
linestyle_opts=opts.LineStyleOpts(type_="dotted",
opacity=0.5))))
# do not shown bar label values
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
bar.reversal_axis()
grid = (Grid(init_opts=opts.InitOpts(
width="1500px",
height="1000px",
page_title="Table Linker visualization page")).add(
bar,
grid_opts=opts.GridOpts(pos_top='5%',
pos_bottom="10%",
pos_right='5%',
pos_left="20%")))
grid.render(output_path + ".html")
# 数据视图工具
opts.ToolBoxFeatureDataViewOpts(
# 是否显示该工具
is_show=True,
# 提示语
title="数据视图",
# 是否不可编辑
is_read_only=False,
),
# 缩放工具配置项，直角坐标系适用
opts.ToolBoxFeatureDataZoomOpts(
# 是否显示该工具。
is_show=False,
# 提示语
zoom_title="区域缩放",
# 提示语
back_title="区域缩放还原",
),
# 图表类型切换，适用于直角坐标系
opts.ToolBoxFeatureMagicTypeOpts(
# 是否显示该工具
is_show=False,
# 启用的动态类型
type_=['stack', 'line', 'bar', 'tiled'],
),
# 工具箱选框组件配置项
opts.ToolBoxFeatureBrushOpts(
# 选择显示哪些选框
def draw_heat_map_picture(grid_data,
x_list,
max_number,
to_file,
svg_name,
height='1200px'):
"""
grid堆叠热力图
:param height:
:param x_list: 横轴列表
:param max_number: 最大值
:param grid_data: [{}] key包括 series_name, y_name, sub_title, value
:param to_file:
:param svg_name:
:return:
"""
grid_number = len(grid_data)
grid = (Grid(init_opts=opts.InitOpts(
width="900px", height=height, bg_color='rgb(255, 255, 255)')))
i = 0
all_top = 5
for grid_data_one in grid_data:
# max_number_list = [i[2] for i in grid_data_one['value'][3:]]
# max_number = max(max_number_list)
length = int(len(grid_data_one['y_name'])) * 1.5
top_position = all_top
bottom_position = 100 - top_position - length
all_top = top_position + length + 2
# print(top_position)
# print(bottom_position)
# print(all_top)
c = HeatMap() \
.add_xaxis(x_list) \
.add_yaxis(grid_data_one['series_name'], grid_data_one['y_name'], grid_data_one['value'],
label_opts=opts.LabelOpts(is_show=True, position="inside"),
)
if i == grid_number - 1:
c = c.set_global_opts(
title_opts=opts.TitleOpts(
title="",
subtitle=grid_data_one['sub_title'],
pos_top=str(top_position) + "%",
),
visualmap_opts=opts.VisualMapOpts(
is_show=False,
min_=0,
max_=max_number,
range_color=['#fff799', '#ae4130']),
xaxis_opts=opts.AxisOpts(
is_show=True,
axislabel_opts=opts.LabelOpts(interval=0, rotate=30),
splitarea_opts=opts.SplitAreaOpts(
is_show=False,
areastyle_opts=opts.AreaStyleOpts(opacity=0))),
yaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(font_size=14, interval=0),
splitarea_opts=opts.SplitAreaOpts(
is_show=False,
areastyle_opts=opts.AreaStyleOpts(opacity=0))),
legend_opts=opts.LegendOpts(pos_top="120%"),
toolbox_opts=opts.ToolboxOpts(feature=opts.ToolBoxFeatureOpts(
data_zoom=opts.ToolBoxFeatureDataZoomOpts(is_show=False),
# brush=opts.ToolBoxFeatureBrushOpts(is_show=False),
)),
)
else:
c = c.set_global_opts(
title_opts=opts.TitleOpts(
title="",
subtitle=grid_data_one['sub_title'],
pos_top=str(top_position - 2) + "%",
),
visualmap_opts=opts.VisualMapOpts(
is_show=False,
min_=0,
max_=max_number,
range_color=['#fff799', '#ae4130']),
xaxis_opts=opts.AxisOpts(
is_show=False,
splitarea_opts=opts.SplitAreaOpts(
is_show=False,
areastyle_opts=opts.AreaStyleOpts(opacity=0))),
yaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(font_size=14, interval=0),
splitarea_opts=opts.SplitAreaOpts(
is_show=False,
areastyle_opts=opts.AreaStyleOpts(opacity=0))),
legend_opts=opts.LegendOpts(pos_top="120%"),
toolbox_opts=opts.ToolboxOpts(feature=opts.ToolBoxFeatureOpts(
data_zoom=opts.ToolBoxFeatureDataZoomOpts(is_show=False),
# brush=opts.ToolBoxFeatureBrushOpts(is_show=False),
)),
)
# 加到grid
grid = grid.add(c,
grid_opts=opts.GridOpts(
pos_bottom=str(bottom_position) + "%",
pos_top=str(top_position) + "%",
pos_left="25%",
pos_right="10%"))
i = i + 1
make_snapshot(snapshot, grid.render(to_file), svg_name) # 生成svg图片