def surface3D_flower() -> Surface3D:
def surface3d_data():
for t0 in range(-30, 30, 1):
y = t0 / 10
for t1 in range(-30, 30, 1):
x = t1 / 10
z = math.sin(x * x + y * y) * x / 3.14
yield [x, y, z]
c = (
Surface3D()
.add(
"",
list(surface3d_data()),
xaxis3d_opts=opts.Axis3DOpts(type_="value"),
yaxis3d_opts=opts.Axis3DOpts(type_="value"),
grid3d_opts=opts.Grid3DOpts(width=100, height=100, depth=100),
)
.set_global_opts(
title_opts=opts.TitleOpts(title="Surface3D-曲面波图"),
visualmap_opts=opts.VisualMapOpts(
max_=1, min_=-1, range_color=Faker.visual_color
),
)
)
return c
def creat_pivot_chart(pivot, index, column, agg, value):
index_list = pivot.index.tolist()
column_list = pivot.columns.tolist()
if pivot.max().tolist():
visualmap_max = max(pivot.max().tolist())
range_text = ['最大值', '最小值']
else:
visualmap_max = 1
range_text = ['无', '数据']
# print(pivot.max())
data = [(i, j, int(pivot.iloc[i, j])) for i in range(len(index_list))
for j in range(len(column_list))]
c = (Bar3D().add(
series_name=agg + '(' + value + ')',
data=data,
shading="lambert",
xaxis3d_opts=opts.Axis3DOpts(index_list, type_="category", name=index),
yaxis3d_opts=opts.Axis3DOpts(column_list,
type_="category",
name=column),
zaxis3d_opts=opts.Axis3DOpts(type_="value",
name=agg + '(' + value + ')'),
).set_global_opts(visualmap_opts=opts.VisualMapOpts(max_=visualmap_max,
range_text=range_text),
title_opts=opts.TitleOpts(title="数据透视三维图"),
toolbox_opts=opts.ToolboxOpts(),
datazoom_opts=opts.DataZoomOpts(type_="inside")))
return c
def line3d_base():
data = []
for t in range(0, 25000):
_t = t / 1000
x = (1 + 0.25 * math.cos(75 * _t)) * math.cos(_t)
y = (1 + 0.25 * math.cos(75 * _t)) * math.sin(_t)
z = _t + 2.0 * math.sin(75 * _t)
data.append([x, y, z])
c = (Line3D().add(
"",
data,
xaxis3d_opts=opts.Axis3DOpts(Faker.clock, type_="value"),
yaxis3d_opts=opts.Axis3DOpts(Faker.week_en, type_="value"),
grid3d_opts=opts.Grid3DOpts(width=100,
height=100,
depth=100,
rotate_speed=150,
is_rotate=True),
).set_global_opts(
visualmap_opts=opts.VisualMapOpts(max_=30,
min_=0,
range_color=Faker.visual_color),
title_opts=opts.TitleOpts(title="Line3D-旋转的弹簧"),
))
return c
def draw_bar3D(cls, title: str, data: pd.DataFrame) -> Bar3D:
"""
根据df内容绘制3D柱状图
:param title: 标题
:param data: 包含三轴数据的dataframe index为x轴 column为Y轴 value为z轴
:return:
"""
data_list = []
index_list = data.index.tolist()
column_list = data.columns.tolist()
# 获取dataframe最大最小值
min_data = data.min().min()
max_data = data.max().max()
# 遍历dataframe，准备待操作数组
for i in range(len(index_list)):
for j in range(len(column_list)):
# 记录 XYZ
temp_list = [index_list[i], column_list[j], data.iloc[i, j]]
# print(i,j,index_list[i],column_list[j])
data_list.append(temp_list)
c = (
Bar3D(init_opts=opts.InitOpts(
width=DEFAULT_WIDTH,
animation_opts=opts.AnimationOpts(
animation_delay=200,
animation_easing="bounceOut"), # 增加启动动效
)).add(
series_name=title,
data=data_list,
xaxis3d_opts=opts.Axis3DOpts(type_="category",
data=index_list),
yaxis3d_opts=opts.Axis3DOpts(type_="category",
data=column_list),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
).set_series_opts(label_opts=opts.LabelOpts(is_show=True)).
set_global_opts(
title_opts=opts.TitleOpts(title=title, pos_left="0%"),
toolbox_opts=opts.ToolboxOpts(), # 显示工具箱
tooltip_opts=opts.TooltipOpts(is_show=True),
axispointer_opts=opts.AxisPointerOpts(
is_show=True, type_="none"), # 指针移动时显示所有数值
legend_opts=opts.LegendOpts(
is_show=True,
selected_mode="multiple",
# pos_bottom="0%",
# pos_right="0%",
# orient="vertical",
), # 显示图例说明
# datazoom_opts=[
# opts.DataZoomOpts(
# range_start=0, range_end=100, orient="vertical", pos_left="2%"
# ),
# opts.DataZoomOpts(range_start=0, range_end=100, orient="horizontal"),
# ], # 增加缩放配置横纵轴都支持缩放
visualmap_opts=opts.VisualMapOpts(max_=max_data, min_=min_data)
# visualmap_opts=opts.VisualMapOpts(type_="color", max_=1, min_=-1),
))
return c
def bar3d_base() -> Bar3D:
data = read_do()
data_tip = [
"使用总能耗 [kW]", "发电 [kW]", "洗碗机 [kW]", "炉子 1 [kW]", "房屋整体能耗 [kW]",
"冰箱 [kW]", "酒窖 [kW]", "车库门 [kW]"
]
data_year = [
2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017,
2018, 2019
]
c = (Bar3D().add("",
data,
xaxis3d_opts=opts.Axis3DOpts(data_tip,
type_="category",
max_=8),
yaxis3d_opts=opts.Axis3DOpts(data_year, max_=2020),
zaxis3d_opts=opts.Axis3DOpts(type_="value", max_=1),
grid3d_opts=opts.Grid3DOpts(
width="180", height="50")).set_global_opts(
visualmap_opts=opts.VisualMapOpts(max_=1),
title_opts=opts.TitleOpts(title="部分能耗图"),
))
return c
def bar_base() -> Scatter3D:
c = (
Scatter3D(init_opts=opts.InitOpts(
width="1440px", height="720px")) # bg_color="black"
.add(
series_name="",
data=data,
xaxis3d_opts=opts.Axis3DOpts(
name=config_xAxis3D,
type_="value",
# textstyle_opts=opts.TextStyleOpts(color="#fff"),
),
yaxis3d_opts=opts.Axis3DOpts(
name=config_yAxis3D,
type_="value",
# textstyle_opts=opts.TextStyleOpts(color="#fff"),
),
zaxis3d_opts=opts.Axis3DOpts(
name=config_zAxis3D,
type_="value",
# textstyle_opts=opts.TextStyleOpts(color="#fff"),
),
grid3d_opts=opts.Grid3DOpts(width=100, height=100, depth=100),
)
# .render("scatter3d.html")
)
return c
def surface3d_base() -> Surface3D:
def surface3d_data():
for t0 in range(-60, 60, 1):
y = t0 / 60
for t1 in range(-60, 60, 1):
x = t1 / 60
if math.fabs(x) < 0.1 and math.fabs(y) < 0.1:
z = "-"
else:
z = math.sin(x * math.pi) * math.sin(y * math.pi)
yield [x, y, z]
c = (Surface3D().add(
"",
list(surface3d_data()),
xaxis3d_opts=opts.Axis3DOpts(type_="value"),
yaxis3d_opts=opts.Axis3DOpts(type_="value"),
grid3d_opts=opts.Grid3DOpts(width=100, height=100, depth=100),
).set_global_opts(
title_opts=opts.TitleOpts(title="Surface3D-基本示例"),
visualmap_opts=opts.VisualMapOpts(max_=3,
min_=-3,
range_color=Faker.visual_color),
))
return c
def bar3d():
data = [(i, j, random.randint(0, 12)) for i in range(6) for j in range(12)]
c = (Bar3D().add(
'', [[d[1], d[0], d[2]] for d in data],
xaxis3d_opts=op.Axis3DOpts(Faker.color, type_='category'),
yaxis3d_opts=op.Axis3DOpts(Faker.week_en, type_='category'),
zaxis3d_opts=op.Axis3DOpts(type_='value')).set_global_opts(
visualmap_opts=op.VisualMapOpts(max_=20),
title_opts={'text': '三维'}))
return c
def bar3d_html(data):
raw = pd.read_csv(data, header=0, index_col=0, sep=None, engine='python')
data = [(i, j, raw.loc[j, i]) for i in raw.columns for j in raw.index]
c = (Bar3D().add(
"",
[[d[1], d[0], d[2]] for d in data],
xaxis3d_opts=opts.Axis3DOpts(raw.index, type_="category"),
yaxis3d_opts=opts.Axis3DOpts(raw.columns, type_="category"),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
).set_global_opts(visualmap_opts=opts.VisualMapOpts(max_=20), ))
c.render('bar3d.html')
def test_bar3d_base():
data = [(i, j, random.randint(0, 12)) for i in range(6) for j in range(24)]
c = (Bar3D().add(
"",
[[d[1], d[0], d[2]] for d in data],
xaxis3d_opts=opts.Axis3DOpts(Faker.clock, type_="category"),
yaxis3d_opts=opts.Axis3DOpts(Faker.week_en, type_="category"),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
).set_global_opts(visualmap_opts=opts.VisualMapOpts(max_=20)))
eq_(c.theme, "white")
eq_(c.renderer, "canvas")
c.render()
def bar3d_base() -> Bar3D:
data = [(i, j, random.randint(0, 12)) for i in range(6) for j in range(24)]
c = (Bar3D().add(
"",
[[d[1], d[0], d[2]] for d in data],
xaxis3d_opts=opts.Axis3DOpts(Faker.clock, type_="category"),
yaxis3d_opts=opts.Axis3DOpts(Faker.week_en, type_="category"),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
).set_global_opts(
visualmap_opts=opts.VisualMapOpts(max_=20),
title_opts=opts.TitleOpts(title="Bar3D-基本示例"),
))
return c
def bar3d_base() -> Bar3D:
data = [(i, j, int(results[i][j])) for i in range(11) for j in range(11)]
c = (Bar3D().add(
"",
[[d[1], d[0], d[2]] for d in data],
xaxis3d_opts=opts.Axis3DOpts(xlist, type_="category"),
yaxis3d_opts=opts.Axis3DOpts(ylist, type_="category"),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
).set_global_opts(
visualmap_opts=opts.VisualMapOpts(max_=1100),
title_opts=opts.TitleOpts(title="Bar3D-Boston crash accident account"),
))
return c
def bar3d_base() -> Bar3D:
data = [(i, j, random.randint(0, 1)) for i in range(6)
for j in range(24)]
c = (Bar3D().add(
"",
[[d[1], d[0], d[2]] for d in data],
xaxis3d_opts=opts.Axis3DOpts(city_nms_top10, type_="category"),
yaxis3d_opts=opts.Axis3DOpts(city_nums_top10, type_="category"),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
).set_global_opts(
visualmap_opts=opts.VisualMapOpts(max_=20),
title_opts=opts.TitleOpts(title="Bar3D-Python工程师"),
))
return c
def bar3d_stack():
x_data = y_data = list(range(10))
bar3d = Bar3D()
for _ in range(10):
bar3d.add(
"",
generate_date(),
shading="lambert",
xaxis3d_opts=opts.Axis3DOpts(data=x_data, type_="value"),
yaxis3d_opts=opts.Axis3DOpts(data=y_data, type_="value"),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
)
bar3d.set_global_opts(title_opts=opts.TitleOpts("Bar3D-堆叠柱状图示例"))
bar3d.set_series_opts(**{"stack": "stack"})
return bar3d
def init_bar3d_base(self):
from example.commons import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar3D
c = (Bar3D().add(
"",
[],
xaxis3d_opts=opts.Axis3DOpts(Faker.clock, type_="category"),
yaxis3d_opts=opts.Axis3DOpts(Faker.week_en, type_="category"),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
).set_global_opts(
visualmap_opts=opts.VisualMapOpts(max_=20),
title_opts=opts.TitleOpts(title=""),
))
return c
def draw():
areas = [
'0-50', '50-100', '100-150', '150-200', '200-250', '250-300',
'300-350', '350+'
]
dic = {}
with open("清洗后城市二手房数据.csv", 'r', encoding='utf8') as f:
reader = csv.reader(f)
data = list(reader)
Bar3D().add(
series_name="",
data=[[item[0], item[4], item[6]] for item in data],
xaxis3d_opts=opts.Axis3DOpts(name='城市', type_='category'),
yaxis3d_opts=opts.Axis3DOpts(name='总价'),
zaxis3d_opts=opts.Axis3DOpts(name='面积')).render("bar3D.html")
def article_day_3d():
today = datetime.datetime.strptime('2019-12-31', '%Y-%m-%d')
date_list = [[(today - datetime.timedelta(days=i)).strftime('%Y-%m-%d'),
(today - datetime.timedelta(days=i)).isocalendar()[1],
(today - datetime.timedelta(days=i)).isocalendar()[2]]
for i in range(365)]
date_list.reverse()
data = [[
date[1], date[2],
WechatArticle.query.filter(
and_(
extract('year', WechatArticle.publish_time) == str(
date[0]).split('-')[0],
extract('month', WechatArticle.publish_time) == str(
date[0]).split('-')[1],
extract('day', WechatArticle.publish_time) == str(
date[0]).split('-')[2],
)).count()
] for date in date_list]
c = (Bar3D().add(
"",
[[d[0], d[1] - 1, d[2]] for d in data],
xaxis3d_opts=opts.Axis3DOpts(data=[i for i in range(1, 53)],
type_="category",
name='一年周期',
name_gap=30),
yaxis3d_opts=opts.Axis3DOpts(data=Faker.week_en,
type_="category",
name='week'),
zaxis3d_opts=opts.Axis3DOpts(type_="value", name='每天数量'),
grid3d_opts=opts.Grid3DOpts(width=300,
height=120,
depth=120,
rotate_speed=10,
is_rotate=True),
).set_global_opts(
visualmap_opts=opts.VisualMapOpts(max_=210,
range_color=Faker.visual_color),
title_opts=opts.TitleOpts(title="2019公众号文章发布统计",
pos_top='10%',
pos_left='43%'),
legend_opts=opts.LegendOpts(item_gap=20, item_width=20),
))
c.render(path='./static/year/article_day_3d.html')
print('生成3D文章发布统计')
return c
def plot_asset_distribution():
months = [
"1月", "2月", "3月", "4月", "5月", "6月", "7月", "8月", "9月", "10月", "11月",
"12月"
]
years = [str(x.year) for x in YearDB.objects.all()]
years = years[::-1]
data = []
for idx1, month in enumerate(months):
for idx2, year in enumerate(years):
data.append([idx1, idx2, 0])
for each in IncomDB.objects.all():
each_year = each.Year.year
each_month = each.monthly
if each_year in years and each_month in months:
idx = years.index(
each_year) + months.index(each_month) * len(years)
data[idx] = [
months.index(each_month),
years.index(each_year),
float(each.actual_balance)
]
bar_3d = (Bar3D(
init_opts=opts.InitOpts(width="1400px", height="700px")).add(
series_name="存款",
data=data,
xaxis3d_opts=opts.Axis3DOpts(type_="category", data=months),
yaxis3d_opts=opts.Axis3DOpts(type_="category", data=years),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
).set_global_opts(visualmap_opts=opts.VisualMapOpts(max_=100000,
range_color=[
"#313695",
"#4575b4",
"#74add1",
"#abd9e9",
"#e0f3f8",
"#ffffbf",
"#fee090",
"#fdae61",
"#f46d43",
"#d73027",
"#a50026",
])))
abs = os.path.dirname(__file__)
bar_3d.render(abs + "/static/analysis.html")
def bar3d_base() -> Bar3D:
import random
from example.commons import Faker
from pyecharts import options as opts
from pyecharts.charts import Bar3D
data = [(i, j, random.randint(0, 12)) for i in range(6) for j in range(24)]
c = (Bar3D().add(
"",
[[d[1], d[0], d[2]] for d in data],
xaxis3d_opts=opts.Axis3DOpts(Faker.clock, type_="category"),
yaxis3d_opts=opts.Axis3DOpts(Faker.week_en, type_="category"),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
).set_global_opts(
visualmap_opts=opts.VisualMapOpts(max_=20),
title_opts=opts.TitleOpts(title=""),
))
return c
def bar3d_base() -> Bar3D:
# data = [(i, j, random.randint(0, 12)) for i in range(6) for j in range(24)]
# print([[d[1], d[0], d[2]] for d in data])
c = (
Bar3D(init_opts=opts.InitOpts(width='1200px', height='1000px'))
.add(
"",
data,
xaxis3d_opts=opts.Axis3DOpts(date1, type_="category"),
yaxis3d_opts=opts.Axis3DOpts(start_uids, type_="category"),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
)
.set_global_opts(
visualmap_opts=opts.VisualMapOpts(max_=500),
title_opts=opts.TitleOpts(title="情感分析3D"),
)
)
return c
def gzu_major_satisfied():
data1 = analysis_data.gzu_satisfied()
data1 = data1.iloc[:, :5]
data = [(i, j, data1.iloc[i, j + 1]) for i in range(data1.shape[0])
for j in range(data1.shape[1] - 1)]
c = (Bar3D().add(
"",
[[d[0], d[1], d[2]] for d in data],
xaxis3d_opts=opts.Axis3DOpts([x[0] for x in data1.values],
type_="category"),
yaxis3d_opts=opts.Axis3DOpts(['综合满意度', '办学条件满意度', '教学质量满意度', '就业满意度'],
type_="category"),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
).set_global_opts(
visualmap_opts=opts.VisualMapOpts(min_=0, max_=2),
title_opts=opts.TitleOpts(title="贵州大学专业满意度"),
))
return c
def echart_plot_3d(data):
from pyecharts.charts import Bar3D
from pyecharts import options as opts
print(data.tail())
df = data[['s_Time', '未来=月终收益', '预测值']].values.tolist()
(Bar3D(init_opts=opts.InitOpts(width="1600px", height="800px")).add(
"",
df,
xaxis3d_opts=opts.Axis3DOpts(type_="category"),
yaxis3d_opts=opts.Axis3DOpts(type_="value"),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
).set_global_opts(
visualmap_opts=opts.VisualMapOpts(max_=100000),
title_opts=opts.TitleOpts(title="predict"),
).render("predict.html"))
def draw_bar3D(self):
from pyecharts.faker import Faker
from pyecharts import options as opts
data = [(i, j, random.randint(0, 12)) for i in range(6)
for j in range(24)]
c = (Bar3D(init_opts=opt.InitOpts(js_host="js2/")).add(
"",
[[d[1], d[0], d[2]] for d in data],
xaxis3d_opts=opts.Axis3DOpts(Faker.clock, type_="category"),
yaxis3d_opts=opts.Axis3DOpts(Faker.week_en, type_="category"),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
).set_global_opts(
visualmap_opts=opts.VisualMapOpts(max_=20),
title_opts=opts.TitleOpts(title="Bar3D-基本示例"),
).render('bar3d1.html'))
print(c)
return c
def test_line3d_base():
data = []
for t in range(0, 25000):
_t = t / 1000
x = (1 + 0.25 * math.cos(75 * _t)) * math.cos(_t)
y = (1 + 0.25 * math.cos(75 * _t)) * math.sin(_t)
z = _t + 2.0 * math.sin(75 * _t)
data.append([x, y, z])
c = (Line3D().add(
"",
data,
xaxis3d_opts=opts.Axis3DOpts(Faker.clock, type_="value"),
yaxis3d_opts=opts.Axis3DOpts(Faker.week_en, type_="value"),
grid3d_opts=opts.Grid3DOpts(width=100, height=100, depth=100),
).set_global_opts(visualmap_opts=opts.VisualMapOpts(
max_=30, min_=0, range_color=Faker.visual_color)))
eq_(c.theme, "white")
eq_(c.renderer, "canvas")
c.render()
def line3d():
week_en = "Saturday Friday Thursday Wednesday Tuesday Monday Sunday".split(
)
clock = ("12a 1a 2a 3a 4a 5a 6a 7a 8a 9a 10a 11a 12p "
"1p 2p 3p 4p 5p 6p 7p 8p 9p 10p 11p".split())
_data = []
for t in range(0, 25000):
_t = t / 1000
x = (1 + 0.25 * math.cos(75 * _t)) * math.cos(_t)
y = (1 + 0.25 * math.cos(75 * _t)) * math.sin(_t)
z = _t + 2.0 * math.sin(75 * _t)
_data.append([x, y, z])
range_color = [
'#313695', '#4575b4', '#74add1', '#abd9e9', '#e0f3f8', '#ffffbf',
'#fee090', '#fdae61', '#f46d43', '#d73027', '#a50026'
]
line3d = Line3D()
line3d.set_global_opts(visualmap_opts=opts.VisualMapOpts(
dimension=2,
max_=30,
min_=0,
range_color=[
"#313695",
"#4575b4",
"#74add1",
"#abd9e9",
"#e0f3f8",
"#ffffbf",
"#fee090",
"#fdae61",
"#f46d43",
"#d73027",
"#a50026",
],
))
line3d.add(
"",
_data,
xaxis3d_opts=opts.Axis3DOpts(data=clock, type_="value"),
yaxis3d_opts=opts.Axis3DOpts(data=week_en, type_="value"),
grid3d_opts=opts.Grid3DOpts(width=100, height=100, depth=100),
)
return line3d
def scatter3d_base():
data = [
[random.randint(0, 100),
random.randint(0, 100),
random.randint(0, 100)]
for _ in range(80)
]
scatter3d = Scatter3D(init_opts=opts.InitOpts(width="1440px", height="720px"))
scatter3d.add(
"",
data,
xaxis3d_opts=opts.Axis3DOpts(type_="value"),
yaxis3d_opts=opts.Axis3DOpts(type_="value")
)
scatter3d.set_global_opts(
visualmap_opts=opts.VisualMapOpts(),
title_opts=opts.TitleOpts(title="Scatter3D-基本示例")
)
scatter3d.render("./scatter3d_base.html")
def plot(self):
self.data_process()
self.gragh.add(
# series name
"",
# 通过k*k循环展开测出来的数据集
data=self.data_set,
# 三维图形的着色效果配置，realistic即为真实感渲染
shading="realistic",
# 图元配置项
itemstyle_opts=opts.ItemStyleOpts(),
# 3D X坐标轴配置项
xaxis3d_opts=opts.Axis3DOpts(name="步长", name_gap=40),
# 3D Y坐标轴配置项
yaxis3d_opts=opts.Axis3DOpts(name="大小/B", name_gap=40),
# 3D Z坐标轴配置项
zaxis3d_opts=opts.Axis3DOpts(name="存储器读取速度MB/s", name_gap=40),
# 三维笛卡尔坐标系配置项
grid3d_opts=opts.Grid3DOpts(width=100, height=100, depth=100),
).set_global_opts(title_opts=opts.TitleOpts(
title="Memory Mountain K*K Loop unrolling",
pos_left="center",
pos_top=90,
),
visualmap_opts=opts.VisualMapOpts(
dimension=3,
max_=1,
min_=-1,
range_color=[
"#313695",
"#4575b4",
"#74add1",
"#abd9e9",
"#e0f3f8",
"#ffffbf",
"#fee090",
"#fdae61",
"#f46d43",
"#d73027",
"#a50026",
],
)).render()
def plot(self):
self.chart = Bar3D(init_opts=opts.InitOpts(page_title=self.title))
self.chart.add(
self.zaxis_name,
[[d[1], d[0], d[2]] for d in self.heat_map],
xaxis3d_opts=opts.Axis3DOpts(self.data_y,
type_="category",
name=self.yaxis_name,
name_gap=25),
yaxis3d_opts=opts.Axis3DOpts(self.data_x,
type_="category",
name=self.xaxis_name,
name_gap=25),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
)
self.chart.set_global_opts(title_opts=opts.TitleOpts(title=self.title),
visualmap_opts=opts.VisualMapOpts(
max_=self.max_value,
min_=self.min_value))
return self
def line3d_base():
data = []
for t in range(0, 25000):
_t = t / 1000
x = (1 + 0.25 * math.cos(75 * _t)) * math.cos(_t)
y = (1 + 0.25 * math.cos(75 * _t)) * math.sin(_t)
z = _t + 2.0 * math.sin(75 * _t)
data.append([x, y, z])
line3d = Line3D()
line3d.add(
"",
data,
xaxis3d_opts=opts.Axis3DOpts(type_="value"),
yaxis3d_opts=opts.Axis3DOpts(type_="value"),
grid3d_opts=opts.Grid3DOpts(width=100, depth=100),
)
line3d.set_global_opts(
title_opts=opts.TitleOpts(title="Line3D-基本示例"),
visualmap_opts=opts.VisualMapOpts(max_=30)
)
line3d.render("./line3d_base.html")
def scatter3d_base() -> Scatter3D:
# data = [
# [random.randint(0, 100), random.randint(0, 200), random.randint(0, 100)]
# for _ in range(10000)
# ]
data, max_rel = read_as_info(
'..\\000LocalData\\as_compare\\as_core_map_data_integrate20191203.csv')
c = (Scatter3D(init_opts=opts.InitOpts(
width="1080px",
height="1080px",
page_title="全球互联网网络3D散点图",
theme=ThemeType.ROMANTIC)).add(
"随机散点",
data,
grid3d_opts=opts.Grid3DOpts(width=300,
height=160,
depth=300,
rotate_speed=5,
is_rotate=True,
rotate_sensitivity=2),
xaxis3d_opts=opts.Axis3DOpts(type_="value",
name="经度",
min_=180.0,
max_=-180.0),
yaxis3d_opts=opts.Axis3DOpts(type_="value",
name="维度",
min_=-180.0,
max_=180.0),
zaxis3d_opts=opts.Axis3DOpts(type_="value",
name="连通度",
min_=0,
max_=max_rel + 1),
itemstyle_opts=opts.ItemStyleOpts()).set_global_opts(
title_opts=opts.TitleOpts("全球互联网网络3D散点图"),
visualmap_opts=opts.VisualMapOpts(
range_color=Faker.visual_color),
))
print(data)
print(Faker.visual_color)
return c
