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 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 test_surface3d_base():
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(visualmap_opts=opts.VisualMapOpts(
max_=3, min_=-3, range_color=Faker.visual_color)))
eq_(c.theme, "white")
eq_(c.renderer, "canvas")
c.render()
Surface3D(init_opts=opts.InitOpts(width="1600px", height="800px"))
.add(
series_name="",
shading="color",
data=list(surface3d_data()),
xaxis3d_opts=opts.Axis3DOpts(type_="value"),
yaxis3d_opts=opts.Axis3DOpts(type_="value"),
grid3d_opts=opts.Grid3DOpts(width=100, height=40, depth=100),
)
.set_global_opts(
visualmap_opts=opts.VisualMapOpts(
dimension=2,
max_=1,
min_=-1,
range_color=[
"#313695",
"#4575b4",
"#74add1",
"#abd9e9",
"#e0f3f8",
"#ffffbf",
"#fee090",
"#fdae61",
"#f46d43",
"#d73027",
"#a50026",
],
)
)
.render("surface_wave.html")
# print(l)
# '''
c = (
Surface3D().add(
series_name="",
shading="color",
# data=list(zip(*x,*y,*z)),
data=l,
xaxis3d_opts=opts.Axis3DOpts(type_="value"),
yaxis3d_opts=opts.Axis3DOpts(type_="value"),
grid3d_opts=opts.Grid3DOpts(width=100, height=40, depth=100),
).set_global_opts(visualmap_opts=opts.VisualMapOpts(
dimension=2,
max_=1,
min_=-1,
# range_color=[
# "#313695",
# "#4575b4",
# "#74add1",
# "#abd9e9",
# "#e0f3f8",
# "#ffffbf",
# "#fee090",
# "#fdae61",
# "#f46d43",
# "#d73027",
# "#a50026",
# ],
)))
c.width = "100%"
put_html(c.render_notebook())
def __init__(self):
self.data_set = []
self.gragh = Surface3D()
Surface3D(init_opts=opts.InitOpts())
.add(
series_name="",
shading="color",
data=list(surface3d_data()),
xaxis3d_opts=opts.Axis3DOpts(type_="value"),
yaxis3d_opts=opts.Axis3DOpts(type_="value"),
grid3d_opts=opts.Grid3DOpts(width=100, height=80, depth=100),
)
.set_global_opts(
visualmap_opts=opts.VisualMapOpts(
dimension=2,
max_=1,
min_=-1,
range_color=[
"#313695",
"#4575b4",
"#74add1",
"#abd9e9",
"#e0f3f8",
"#ffffbf",
"#fee090",
"#fdae61",
"#f46d43",
"#d73027",
"#a50026",
],
),
title_opts=opts.TitleOpts(title="养老业与经济发展模拟图", pos_left='38%', pos_top='10%')
)
.render_notebook()
def plot_performance_overview(dict_results, plot_tymod, p):
if plot_tymod == "pic":
figs = {}
for k, v in dict_results.items():
v = v.unstack()
series = v.index.get_level_values(0).unique() if isinstance(
v.index, pd.MultiIndex) else [k]
c = 3
r = np.ceil(len(series) / c)
fig = plt.figure(figsize=(8, 6))
plt.subplots_adjust(hspace=0.3)
for i, _s in enumerate(series):
_data = v.loc[_s] if isinstance(v.index, pd.MultiIndex) else v
X, Y = np.meshgrid(_data.index, _data.columns, indexing='ij')
Z = _data.values
pos = int(r * 100 + c * 10 + (i + 1))
ax = fig.add_subplot(pos, projection='3d')
ax.plot_surface(X, Y, Z, color='b')
ax.set_title("%s" % _s, fontdict={"size": 8})
figs[k] = fig
fig.savefig("%s_%s.png" % (p, k))
return figs
elif plot_tymod == 'dyn-3d':
results = {}
for k, perf in dict_results.items():
perf = perf.unstack()
c = (Surface3D(init_opts=opts.InitOpts(
width="1000px", height="500px")).set_global_opts(
title_opts=opts.TitleOpts(title="绩效-曲面波图（%s）" % k),
visualmap_opts=opts.VisualMapOpts(
max_=perf.values.max(),
min_=perf.values.min(),
range_color=Faker.visual_color),
toolbox_opts=opts.ToolboxOpts(is_show=True),
))
series = perf.index.get_level_values(0).unique() if isinstance(
perf.index, pd.MultiIndex) else [k]
for i, _s in enumerate(series):
_data = perf.loc[_s] if isinstance(perf.index,
pd.MultiIndex) else perf
X, Y = np.meshgrid(_data.index, _data.columns)
d = list(
zip(X.flatten().astype(str),
Y.flatten().astype(str),
_data.values.T.flatten().astype(np.float)))
c = c.add(
series_name=str(_s),
shading="color",
data=d,
xaxis3d_opts=opts.Axis3DOpts(type_="category"),
yaxis3d_opts=opts.Axis3DOpts(type_="category"),
grid3d_opts=opts.Grid3DOpts(width=100,
height=50,
depth=100),
)
results[k] = c
tab = Tab()
for k, v in results.items():
tab.add(v, k)
tab.render("%s.html" % p)
elif plot_tymod == "dyn-hm":
tab = Tab()
for k, v in dict_results.items():
v = v.unstack()
_tl = _timeline(v, name=k)
tab.add(_tl, k)
tab.render("%s.html" % p)
x = t1
z = range_data[y, x]
yield [x, y, z]
(Surface3D(init_opts=opts.InitOpts(width="1600px", height="800px")).add(
series_name="",
shading="color",
data=list(surface3d_data(range_data)),
xaxis3d_opts=opts.Axis3DOpts(type_="value"),
yaxis3d_opts=opts.Axis3DOpts(type_="value"),
grid3d_opts=opts.Grid3DOpts(width=100, height=40, depth=100),
).set_global_opts(visualmap_opts=opts.VisualMapOpts(
dimension=2,
max_=50,
min_=40,
range_color=[
'#313695',
'#4575b4',
'#74add1',
'#abd9e9',
'#e0f3f8',
'#ffffbf',
'#fee090',
'#fdae61',
'#f46d43',
'#d73027',
'#a50026',
],
)).render("surface_wave.html"))