如何在 Plotly for Python 中悬停时突出显示整个跟踪?

How do I highlight an entire trace upon hover in Plotly for Python?(如何在 Plotly for Python 中悬停时突出显示整个跟踪?)

问题描述

我希望在鼠标悬停选择时突出显示轨迹(颜色或不透明度变化).我研究了 restyle 功能，但它可能不适合我的用例.

看起来

您可以使用 Plotly 的 FigureWidget 功能.

导入 plotly.graph_objs随机导入f = go.FigureWidget()f.layout.hovermode = '最近的'f.layout.hoverdistance = -1 #确保没有间隙"用于选择稀疏数据default_linewidth = 2highlight_linewidth_delta = 2# 只是一些带有随机数据点的轨迹num_of_traces = 5随机种子 = 42对于我在范围内(num_of_traces):y = [random.random() + i/2 for _ in range(100)]trace = go.Scatter(y=y, mode='lines', line={ 'width': default_linewidth })f.add_trace(跟踪)# 我们的自定义事件处理程序def update_trace(跟踪，点，选择器):# 这个列表存储了被点击的点# 除了一个痕迹之外，它们都是空的如果 len(points.point_inds) == 0:返回对于 i,_ in enumerate(f.data):f.data[i]['line']['width'] = default_linewidth + highlight_linewidth_delta * (i == points.trace_index)# 我们需要将 on_click 事件分别添加到每个跟踪对于我在范围内(len(f.data)):f.data[i].on_click(update_trace)# 让我们显示图F

I want a trace to be highlighted (color or opacity change) when selected with mouse hover. I have looked into restyle functionality, but it may not be appropriate for my use case.

It looks like this has been discussed on Github, but I'm not sure if it has been resolved/implemented.

Here is an example in Bokeh of what I want to accomplish in Plotly Python:

from bokeh.plotting import figure, show, output_notebook
from bokeh.models import HoverTool
from bokeh.models import ColumnDataSource
output_notebook()

p = figure(plot_width=400, plot_height=400,y_range=(0.2,0.5))


y_vals = [0.22,0.22,0.25,0.25,0.26,0.26,0.27,0.27]
y_vals2 = [y*1.4 for y in y_vals]
x_vals = [0,1,1,2,2,2,2,3]
data_dict = {'x':[x_vals,x_vals],
             'y':[y_vals,y_vals2],
             'color':["firebrick", "navy"],
             'alpha':[0.1, 0.1]}

source = ColumnDataSource(data_dict)

p.multi_line('x','y',source=source,
             color='color', alpha='alpha', line_width=4,
             hover_line_alpha=1.0,hover_line_color='color')

p.add_tools(HoverTool(show_arrow=True,
                      line_policy='nearest',
                      ))
show(p)

You can use Plotly's FigureWidget functionality.

import plotly.graph_objs as go
import random

f = go.FigureWidget()
f.layout.hovermode = 'closest'
f.layout.hoverdistance = -1 #ensures no "gaps" for selecting sparse data
default_linewidth = 2
highlighted_linewidth_delta = 2

# just some traces with random data points  
num_of_traces = 5
random.seed = 42
for i in range(num_of_traces):
    y = [random.random() + i / 2 for _ in range(100)]
    trace = go.Scatter(y=y, mode='lines', line={ 'width': default_linewidth })
    f.add_trace(trace)

# our custom event handler
def update_trace(trace, points, selector):
    # this list stores the points which were clicked on
    # in all but one trace they are empty
    if len(points.point_inds) == 0:
        return
        
    for i,_ in enumerate(f.data):
        f.data[i]['line']['width'] = default_linewidth + highlighted_linewidth_delta * (i == points.trace_index)


# we need to add the on_click event to each trace separately       
for i in range( len(f.data) ):
    f.data[i].on_click(update_trace)

# let's show the figure 
f

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