python - 使用 Fig.update_layout Plotly 更新 Traces 的可见性

Question

继此问题之后:Set sqrt as yaxis scale from dropdown or button-Python/Plotly

我想要:

1. 定义包含所有迹线的绘图:visible = False

fig.add_scatter(mode="markers", x=df["gdpPercap"], y=df["lifeExp"], visible = False) #set both vis to False 
fig.add_scatter(mode="markers", x=df["gdpPercap"], y=np.sqrt(df["lifeExp"]), visible = False)

创建一个更新按钮，可以使trace1或trace2变得可见

# buttons for updatemenu
buttons = [dict(method='restyle',
                label='linear',
                visible=True,
                args=[{'label': 'linear',
                       'visible':[True, False],
                      }
                     ]),.....
         
 um = [{'buttons':buttons,
      'direction': 'down'}
      ]

fig.update_layout(updatemenus=um)

将初始条件设置为trace1 = 可见，trace2 = 不可见

fig.update_layout(dict(args = {"visible": [True, False]}))

前两点已经解决。 我找不到预设初始显示条件的方法。在此示例中，我可以在创建跟踪时轻松​​更改可见性，但在我的实际问题中，这会更困难。

这是完整的示例:

import numpy as np
import plotly.graph_objects as go
import plotly.express as px
df = px.data.gapminder().query("year == 2007")

# figure setup
fig = go.Figure()
fig.add_scatter(mode="markers", x=df["gdpPercap"], y=df["lifeExp"], visible = False) #set both vis to False 
fig.add_scatter(mode="markers", x=df["gdpPercap"], y=np.sqrt(df["lifeExp"]), visible = False)

# buttons for updatemenu
buttons = [dict(method='restyle',
                label='linear',
                visible=True,
                args=[{'label': 'linear',
                       'visible':[True, False],
                      }
                     ]),
           dict(method='restyle',
                label='sqrt',
                visible=True,
                args=[{'label': 'linear',
                       'visible':[False, True],
                      }
                     ])]
           
# specify updatemenu        
um = [{'buttons':buttons,
      'direction': 'down'}
      ]

fig.update_layout(updatemenus=um)


 #Update plot before showing to make 1st trace visible COMMENTED OUT CODE NOT WORKING 
# fig.update_layout(dict(args = {"visible": [True, False]}))

fig.show()

Answer 1

在这种情况下，您可以有条件地更新跟踪，如下所示 here .

首先，当您添加每条迹线时，为其指定一个名称(在本例中使用“线性”和“sqrt”):

fig.add_scatter(mode="markers", x=df["gdpPercap"], y=df["lifeExp"], 
                visible = False, name='linear')
fig.add_scatter(mode="markers", x=df["gdpPercap"], y=np.sqrt(df["lifeExp"]), 
                visible = False, name='sqrt')

然后稍后使用条件更新，如果名称是“线性”，则设置 visible=True:

fig.for_each_trace(
    lambda trace: trace.update(visible=True) if trace.name == "linear" else (),
)

完整示例:

import numpy as np
import plotly.express as px
import plotly.graph_objects as go
df = px.data.gapminder().query("year == 2007")

fig = go.Figure()
# adding names for reference
fig.add_scatter(mode="markers", x=df["gdpPercap"], y=df["lifeExp"], 
                visible = False, name='linear')
fig.add_scatter(mode="markers", x=df["gdpPercap"], y=np.sqrt(df["lifeExp"]), 
                visible = False, name='sqrt')

# buttons for updatemenu
buttons = [dict(method='restyle',
                label='linear',
                visible=True,
                args=[{'label': 'linear',
                       'visible':[True, False],}]),
           dict(method='restyle',
                label='sqrt',
                visible=True,
                args=[{'label': 'linear',
                       'visible':[False, True],}])]
           
# specify updatemenu        
um = [{'buttons':buttons, 'direction': 'down'}]
fig.update_layout(updatemenus=um)

# Conditionally Updating Traces 
fig.for_each_trace(
    lambda trace: trace.update(visible=True) if trace.name == "linear" else (),
)
fig.show()