如何在情节中添加对单个子情节的控制？

Question

在 plotly 中，我使用了一个包含多个子图的图形。 对于最后一个子图，我希望能够使用下拉菜单更改类型。

但是，下拉菜单的“restyle”动作似乎适用于整个图形？ 如果我使用下拉菜单，其他子图就会消失：

=> 如何为特定的子图添加绘图控件？

或

=> 如何判断控件只影响特定子图的属性？

读取数据

import pandas as pd
​
# read in volcano database data
df = pd.read_csv(
    "https://raw.githubusercontent.com/plotly/datasets/master/volcano_db.csv",
    encoding="iso-8859-1",
)
​
# frequency of Country
freq = df
freq = freq.Country.value_counts().reset_index().rename(columns={"index": "x"})
​
# read in 3d volcano surface data
df_v = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/volcano.csv")

用子图初始化图形

from plotly.subplots import make_subplots
import plotly.graph_objects as go

fig = make_subplots(
    rows=3,
    cols=2,
    column_widths=[0.6, 0.4],
    row_heights=[0.4, 0.2, 0.4],
    specs=[
        [{"type": "scattergeo", "rowspan": 2}, {"type": "bar"}],
        [None, None],
        [None,                                 {"type": "surface"}]
    ]
)

# Add scattergeo globe map of volcano locations
scatter_geo = go.Scattergeo(
    lat=df["Latitude"],
    lon=df["Longitude"],
    mode="markers",
    hoverinfo="text",
    showlegend=False,
    marker=dict(color="crimson", size=4, opacity=0.8)
)

fig.add_trace(
    scatter_geo,
    row=1,
    col=1
)

# Add locations bar chart
bar = go.Bar(
    x=freq["x"][0:10],
    y=freq["Country"][0:10],
    marker=dict(color="crimson"),
    showlegend=False
)

fig.add_trace(
    bar,
    row=1,
    col=2
)

# Add 3d surface of volcano
surface_3d = go.Surface(
    z=df_v.values.tolist(),
    showscale=False
)

fig.add_trace(
    surface_3d,
    row=3,
    col=2
)
fig

添加控件

# Add dropdown

updatemenu = dict(
    buttons=list([
        dict(
            args=["type", "surface"],
            label="3D Surface",
            method="restyle"
        ),
        dict(
            args=["type", "heatmap"],
            label="Heatmap",
            method="restyle"
        )
    ]),
    direction="down",
    pad={"r": 10, "t": 10},
    showactive=True,  
    x=1,
    y=0.4
)

fig['layout'].update(
    updatemenus=[{}, {}, {}, {}, {}, updatemenu]
)

#Add slider

steps = []
for i in range(10):
    step = dict(
        method="update",
        args=[{"title": "Slider switched to step: " + str(i)}],  # layout attribute
    )
    steps.append(step)
    
slider = dict(
    active=10,
    currentvalue={"prefix": "Frequency: "},
    pad={"t": 50},
    steps=steps
)

fig.update_layout(
    sliders=[slider]
)

其他样式

# Update geo subplot properties
fig.update_geos(
    projection_type="orthographic",
    landcolor="white",
    oceancolor="MidnightBlue",
    showocean=True,
    lakecolor="LightBlue"
)

# Rotate x-axis labels
fig.update_xaxes(tickangle=45)

# Set theme, margin, and annotation in layout
fig.update_layout(
    autosize=False,
    width=800,
    height=500,
    template="plotly_dark",
    margin=dict(r=10, t=25, b=40, l=60),
    scene_camera_eye=dict(x=2, y=2, z=0.3),
    annotations=[
        dict(
            text="Source: NOAA",
            showarrow=False,
            xref="paper",
            yref="paper",
            x=0,
            y=0)
    ]
)
fig.show()

Answer 1

很遗憾，这不是一个完整的答案。但希望我将要向您展示的内容将在您的道路上对您有所帮助。您会看到，您可以通过该子图中包含的轨迹指定要编辑的子图。您可以通过adding an integer 在args() 中执行此操作，如下所示：

buttons=list([
    dict(
        args=["type", "surface", [2]],
        label="3D Surface",
        method="restyle"
    )

而[2] 引用了您在fig.data 中的跟踪位置：

(Scattergeo({
     'geo': 'geo',
     'hoverinfo': 'text',
     'lat': array([ 34.5  , -23.3  ,  14.501, ...,  15.05 ,  14.02 ,  34.8  ]),
     'lon': array([ 131.6  ,  -67.62 ,  -90.876, ...,   42.18 ,   42.75 , -108.   ]),
     'marker': {'color': 'crimson', 'opacity': 0.8, 'size': 4},
     'mode': 'markers',
     'showlegend': False
 }),
 Bar({
     'marker': {'color': 'crimson'},
     'showlegend': False,
     'x': array(['United States', 'Russia', 'Indonesia', 'Japan', 'Chile', 'Ethiopia',
                 'Papua New Guinea', 'Philippines', 'Mexico', 'Iceland'], dtype=object),
     'xaxis': 'x',
     'y': array([184, 169, 136, 111,  87,  57,  54,  49,  41,  38], dtype=int64),
     'yaxis': 'y'
 }),
 Surface({
     'scene': 'scene',
     'showscale': False,

问题是，在你的情况下这样做会触发一些 非常 特殊行为：当按钮设置为热图时，数据变成 Bart of Bar图：

更奇怪的是，当你再次选择 3D Surface 时，它看起来应该是这样的：

老实说，我不知道是什么原因造成的。在下面的完整代码 sn-p 中查看自己，看看你能做些什么。也许我们最终能够弄清楚......

完整代码：

from plotly.subplots import make_subplots
import plotly.graph_objects as go

import pandas as pd

# read in volcano database data
df = pd.read_csv(
    "https://raw.githubusercontent.com/plotly/datasets/master/volcano_db.csv",
    encoding="iso-8859-1",
)

# frequency of Country
freq = df
freq = freq.Country.value_counts().reset_index().rename(columns={"index": "x"})

# read in 3d volcano surface data
df_v = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/volcano.csv")
df_v

fig = make_subplots(
    rows=3,
    cols=2,
    column_widths=[0.6, 0.4],
    row_heights=[0.4, 0.2, 0.4],
    specs=[
        [{"type": "scattergeo", "rowspan": 2}, {"type": "bar"}],
        [None, None],
        [None,                                 {"type": "surface"}]
    ]
)

# Add scattergeo globe map of volcano locations
scatter_geo = go.Scattergeo(
    lat=df["Latitude"],
    lon=df["Longitude"],
    mode="markers",
    hoverinfo="text",
    showlegend=False,
    marker=dict(color="crimson", size=4, opacity=0.8)
)

fig.add_trace(
    scatter_geo,
    row=1,
    col=1
)

# Add locations bar chart
bar = go.Bar(
    x=freq["x"][0:10],
    y=freq["Country"][0:10],
    marker=dict(color="crimson"),
    showlegend=False
)

fig.add_trace(
    bar,
    row=1,
    col=2
)

# Add 3d surface of volcano
surface_3d = go.Surface(
    z=df_v.values.tolist(),
    showscale=False
)

fig.add_trace(
    surface_3d,
    row=3,
    col=2
)

# Add dropdown

updatemenu = dict(
    buttons=list([
        dict(
            args=["type", "surface", [2]],
            label="3D Surface",
            method="restyle"
        ),
        dict(
            args=["type", "heatmap", [2]],
            label="Heatmap",
            method="restyle"
        )
    ]),
    direction="down",
    pad={"r": 10, "t": 10},
    showactive=True,  
    x=1,
    y=0.4
)

fig['layout'].update(
    updatemenus=[{}, {}, {}, {}, {}, updatemenu]
)

#Add slider

steps = []
for i in range(10):
    step = dict(
        method="update",
        args=[{"title": "Slider switched to step: " + str(i)}],  # layout attribute
    )
    steps.append(step)
    
slider = dict(
    active=10,
    currentvalue={"prefix": "Frequency: "},
    pad={"t": 50},
    steps=steps
)

fig.update_layout(
    sliders=[slider]
)

# Update geo subplot properties
fig.update_geos(
    projection_type="orthographic",
    landcolor="white",
    oceancolor="MidnightBlue",
    showocean=True,
    lakecolor="LightBlue"
)

# Rotate x-axis labels
fig.update_xaxes(tickangle=45)

# Set theme, margin, and annotation in layout
fig.update_layout(
    autosize=False,
    width=800,
    height=500,
    template="plotly_dark",
    margin=dict(r=10, t=25, b=40, l=60),
    scene_camera_eye=dict(x=2, y=2, z=0.3),
    annotations=[
        dict(
            text="Source: NOAA",
            showarrow=False,
            xref="paper",
            yref="paper",
            x=0,
            y=0)
    ]
)
fig.show()