在 Altair 中组合悬停和点击选择

如何解决在 Altair 中组合悬停和点击选择

我想在 altair 图中组合悬停和单击选择。下面的代码产生了我想要的结果：默认情况下，点大部分是透明的，将鼠标悬停在该点上会增加不透明度，然后单击该点会进一步增加不透明度。我发现这很有用，这样用户可以将鼠标悬停在一个点上以快速了解结果，然后单击该点以“锁定”选择。虽然我对结果感到满意，但该方法似乎有点麻烦，因为我需要为悬停和单击选择定义不同的图表图层。如果我可以构造一个多路条件表达式，那么我似乎可以大大简化代码。我尝试将不透明度条件写为 alt.condition(click_selection,CLICK_OPACITY,alt.condition(hover_selection,HOVER_OPACITY,DEFAULT_OPACITY))，但出现错误。有没有办法简化我下面的代码以结合悬停和点击选择？

import altair as alt
import numpy as np
import pandas as pd

a_values = np.arange(1,4)
x_values = np.linspace(0,2,1000)
DEFAULT_OPACITY = 0.3
HOVER_OPACITY = 0.5
CLICK_OPACITY = 1.0

a_df = pd.DataFrame({'a': a_values})

df = pd.DataFrame({
    'a': np.tile(A=a_values,reps=len(x_values)),'x': np.repeat(a=x_values,repeats=len(a_values)),})
df['y'] = df['a'] * np.sin(2 * np.pi * df['x'])

hover_selection = alt.selection_single(
    clear='mouSEOut',empty='none',fields=['a'],name='hover_selection',on='mouSEOver',)
click_selection = alt.selection_single(
    empty='none',name='click_selection',on='click',)

a_base = alt.Chart(a_df).mark_point(
    filled=True,size=100,).encode(
    x=alt.X(shorthand='a:Q',scale=alt.Scale(domain=(min(a_values) - 1,max(a_values) + 1))),y=alt.Y(shorthand='a:Q',)
a_hover = a_base.encode(
    opacity=alt.condition(hover_selection,alt.value(HOVER_OPACITY),alt.value(DEFAULT_OPACITY))
).add_selection(hover_selection)
a_click = a_base.encode(
    opacity=alt.condition(click_selection,alt.value(CLICK_OPACITY),alt.value(0.0)),).add_selection(click_selection)

y_base = alt.Chart(df).mark_line().encode(
    x=alt.X(shorthand='x:Q',scale=alt.Scale(domain=(0,2))),y=alt.Y(shorthand='y:Q',scale=alt.Scale(domain=(-3,3))),)
y_hover = y_base.encode(
    opacity=alt.value(HOVER_OPACITY),).transform_filter(hover_selection)
y_click = y_base.encode(
    opacity=alt.value(CLICK_OPACITY),).transform_filter(click_selection)

alt.hconcat(
    alt.layer(a_hover,a_click),alt.layer(y_hover,y_click),)

解决方法

VegaLite 支持在相同条件下进行多项选择，但我认为在 alt.Condition 内写是不可能的。但是，您可以看到 alt.Condition 返回一个字典，因此您可以直接传递选择列表来编写它。

这样你就可以澄清这一部分

a_base = alt.Chart(a_df).mark_point(
    filled=True,size=100,).encode(
    x=alt.X(shorthand='a:Q',scale=alt.Scale(domain=(min(a_values) - 1,max(a_values) + 1))),y=alt.Y(shorthand='a:Q',)
a_hover = a_base.encode(
    opacity=alt.condition(hover_selection,alt.value(HOVER_OPACITY),alt.value(DEFAULT_OPACITY))
).add_selection(hover_selection)
a_click = a_base.encode(
    opacity=alt.condition(click_selection,alt.value(CLICK_OPACITY),alt.value(0.0)),).add_selection(click_selection)

像这样：

hover_and_click_condition = {
    'condition': [
        {'selection': 'hover_selection','value': HOVER_OPACITY},{'selection': 'click_selection','value': CLICK_OPACITY}],'value': DEFAULT_OPACITY}

a = alt.Chart(a_df).mark_point(
    filled=True,opacity=hover_and_click_condition
).add_selection(hover_selection,click_selection)

---

对于转换过滤器，您可以重写此部分

y_base = alt.Chart(df).mark_line().encode(
    x=alt.X(shorthand='x:Q',scale=alt.Scale(domain=(0,2))),y=alt.Y(shorthand='y:Q',scale=alt.Scale(domain=(-3,3))),)
y_hover = y_base.encode(
    opacity=alt.value(HOVER_OPACITY),).transform_filter(hover_selection)
y_click = y_base.encode(
    opacity=alt.value(CLICK_OPACITY),).transform_filter(click_selection)

alt.hconcat(
    alt.layer(a_hover,a_click),alt.layer(y_hover,y_click),)

像这样：

y = alt.Chart(df).mark_line().encode(
    x=alt.X(shorthand='x:Q',opacity=hover_and_click_condition
)

a | (y.transform_filter(click_selection) + y.transform_filter(hover_selection))