悬停时仅显示单行，隐藏所有其他行
Display only single line on hover, hide all other lines
有没有办法在我悬停一个图形时隐藏图形上的所有其他线条？
示例：
import numpy as np
import plotly.express as px
np.random.seed(42)
data = np.random.randint(0, 10, (5, 10))
fig = px.line(data_frame=pd.DataFrame(data))
fig.show()
将产生：
我想要这个，当我将鼠标悬停在特定的行上时（但没有手动关闭所有其他行并保持 X、Y 轴变暗）：
UPD：在 jupyter notebook 里面
import plotly.graph_objects as go
import numpy as np
import pandas as pd
# callback function for on_hover
def hide_traces_on_hover(trace, points, selector):
if len(points.point_inds)==1: # identify hover
i = points.trace_index # get the index of the hovered trace
f.data[i].visible = True # keep the hovered trace visible
# create a list of traces you want to hide
hide_traces = [l_trace for idx, l_trace in enumerate(f.data) if idx != i]
for l_trace in hide_traces: # iterate over hide_traces
l_trace.visible = 'legendonly' # hide all remaining traces
# callback function to unhide traces on click
def unhide_traces_on_click(trace, points, selector):
for l_trace in f.data:
l_trace.visible = True
# your sample data frame
np.random.seed(42)
data = np.random.randint(0, 10, (5, 10))
df = pd.DataFrame(data)
f = go.FigureWidget() # create figure widget
f.update_yaxes(autorange=False) # set auto range to false
# define the range of the y-axis using min and max functions
f.update_layout(yaxis_range=[df.values.min()-1, df.values.max()+1])
# create your traces from the data frame
for col in df.columns:
trace = go.Scatter(x=df.index, y=df[col], mode='lines+markers')
f.add_trace(trace)
# assign your functions to each trace
for trace in f.data:
trace.on_hover(hide_traces_on_hover)
trace.on_click(unhide_traces_on_click)
f
如果您 运行 遇到问题，这里是 jupyter notebook support documentation for using FigureWidget and here is the jupyter lab support documentation. Make sure you have the ipywidgets package installed. Also, just as a FYI, here is the FigureWidget documentation。
当您将鼠标悬停在图表中的标记上时。
当您点击可见痕迹的任何标记时，所有隐藏的痕迹将再次可见。
以下建议来自帖子 and ，您可以通过将鼠标悬停在线条的任意点或部分来显示单个轨迹。其余的痕迹并没有完全隐藏，而是在背景中变成灰色和透明的，这样您就可以更轻松地进行其他选择。
要重置图形并使所有痕迹同时完全可见，只需单击 Clear Selection。我知道您更喜欢“普通”的 Jupyter 方法来获得此功能，但您会错过 plotly 的真正力量，它只能通过 Dash and JupyterDash 充分展现自己。有了这个建议，您将看不到 Dash 和“普通”Jupyter 之间的任何区别，因为图形或应用程序以 app.run_server(mode='inline')
内联显示
情节 1 - 发射时。或者点击 Clear selection
后
绘图 2 - 选择 = 跟踪 a
绘图 3 - 选择 = 跟踪 b
完整代码
import pandas as pd
import plotly.graph_objects as go
import numpy as np
import dash
import dash_core_components as dcc
import dash_html_components as html
import plotly.express as px
from dash.dependencies import Input, Output
from jupyter_dash import JupyterDash
# pandas and plotly settings
pd.options.plotting.backend = "plotly"
# app info
app = JupyterDash(__name__)
# sample data and figure setup
df = pd.DataFrame(np.random.randint(-1,2,size=(200, 12)), columns=list('abcdefghijkl'))
df = df.cumsum()#.reset_index()
fig = df.plot(title = 'Selected traces = all', template='plotly_dark')#.update_traces(line_color = 'rgba(50,50,50,0.5)')
set_fig = go.Figure(fig)
colors = {d.name:d.line.color for i, d in enumerate(set_fig.data)}
# jupyterdash app
app.layout = html.Div([html.Button('Clear selection', id='clearit', n_clicks=0),
dcc.Graph(id='hoverfig',figure=fig,#clear_on_unhover = True
),])
colors = {d.name:d.line.color for i, d in enumerate(set_fig.data)}
# callbacks
@app.callback(
Output('hoverfig', 'figure'),
[Input('hoverfig', 'hoverData'), Input('clearit', 'n_clicks')])
def display_hover_data(hoverData, resetHover):
changed_id = [p['prop_id'] for p in dash.callback_context.triggered][0]
if 'clearit' in changed_id:
return set_fig
else:
try:
fig2 = fig.update_layout(title = 'Selected trace = ' + fig.data[hoverData['points'][0]['curveNumber']].name)
fig2.for_each_trace(lambda t: t.update(line_color = 'rgba(50,50,50,0.5)',line_width = 1) if t.name != fig.data[hoverData['points'][0]['curveNumber']].name else t.update(line_color = colors[t.name], line_width = 2))
return fig2
except:
return fig
app.run_server(mode='inline', port = 8070, dev_tools_ui=True,
dev_tools_hot_reload =True, threaded=True)
有没有办法在我悬停一个图形时隐藏图形上的所有其他线条？
示例：
import numpy as np
import plotly.express as px
np.random.seed(42)
data = np.random.randint(0, 10, (5, 10))
fig = px.line(data_frame=pd.DataFrame(data))
fig.show()
将产生：
我想要这个，当我将鼠标悬停在特定的行上时（但没有手动关闭所有其他行并保持 X、Y 轴变暗）：
UPD：在 jupyter notebook 里面
import plotly.graph_objects as go
import numpy as np
import pandas as pd
# callback function for on_hover
def hide_traces_on_hover(trace, points, selector):
if len(points.point_inds)==1: # identify hover
i = points.trace_index # get the index of the hovered trace
f.data[i].visible = True # keep the hovered trace visible
# create a list of traces you want to hide
hide_traces = [l_trace for idx, l_trace in enumerate(f.data) if idx != i]
for l_trace in hide_traces: # iterate over hide_traces
l_trace.visible = 'legendonly' # hide all remaining traces
# callback function to unhide traces on click
def unhide_traces_on_click(trace, points, selector):
for l_trace in f.data:
l_trace.visible = True
# your sample data frame
np.random.seed(42)
data = np.random.randint(0, 10, (5, 10))
df = pd.DataFrame(data)
f = go.FigureWidget() # create figure widget
f.update_yaxes(autorange=False) # set auto range to false
# define the range of the y-axis using min and max functions
f.update_layout(yaxis_range=[df.values.min()-1, df.values.max()+1])
# create your traces from the data frame
for col in df.columns:
trace = go.Scatter(x=df.index, y=df[col], mode='lines+markers')
f.add_trace(trace)
# assign your functions to each trace
for trace in f.data:
trace.on_hover(hide_traces_on_hover)
trace.on_click(unhide_traces_on_click)
f
如果您 运行 遇到问题，这里是 jupyter notebook support documentation for using FigureWidget and here is the jupyter lab support documentation. Make sure you have the ipywidgets package installed. Also, just as a FYI, here is the FigureWidget documentation。
当您将鼠标悬停在图表中的标记上时。
当您点击可见痕迹的任何标记时，所有隐藏的痕迹将再次可见。
以下建议来自帖子
要重置图形并使所有痕迹同时完全可见，只需单击 Clear Selection。我知道您更喜欢“普通”的 Jupyter 方法来获得此功能，但您会错过 plotly 的真正力量，它只能通过 Dash and JupyterDash 充分展现自己。有了这个建议，您将看不到 Dash 和“普通”Jupyter 之间的任何区别，因为图形或应用程序以 app.run_server(mode='inline')
情节 1 - 发射时。或者点击 Clear selection
后
绘图 2 - 选择 = 跟踪 a
绘图 3 - 选择 = 跟踪 b
完整代码
import pandas as pd
import plotly.graph_objects as go
import numpy as np
import dash
import dash_core_components as dcc
import dash_html_components as html
import plotly.express as px
from dash.dependencies import Input, Output
from jupyter_dash import JupyterDash
# pandas and plotly settings
pd.options.plotting.backend = "plotly"
# app info
app = JupyterDash(__name__)
# sample data and figure setup
df = pd.DataFrame(np.random.randint(-1,2,size=(200, 12)), columns=list('abcdefghijkl'))
df = df.cumsum()#.reset_index()
fig = df.plot(title = 'Selected traces = all', template='plotly_dark')#.update_traces(line_color = 'rgba(50,50,50,0.5)')
set_fig = go.Figure(fig)
colors = {d.name:d.line.color for i, d in enumerate(set_fig.data)}
# jupyterdash app
app.layout = html.Div([html.Button('Clear selection', id='clearit', n_clicks=0),
dcc.Graph(id='hoverfig',figure=fig,#clear_on_unhover = True
),])
colors = {d.name:d.line.color for i, d in enumerate(set_fig.data)}
# callbacks
@app.callback(
Output('hoverfig', 'figure'),
[Input('hoverfig', 'hoverData'), Input('clearit', 'n_clicks')])
def display_hover_data(hoverData, resetHover):
changed_id = [p['prop_id'] for p in dash.callback_context.triggered][0]
if 'clearit' in changed_id:
return set_fig
else:
try:
fig2 = fig.update_layout(title = 'Selected trace = ' + fig.data[hoverData['points'][0]['curveNumber']].name)
fig2.for_each_trace(lambda t: t.update(line_color = 'rgba(50,50,50,0.5)',line_width = 1) if t.name != fig.data[hoverData['points'][0]['curveNumber']].name else t.update(line_color = colors[t.name], line_width = 2))
return fig2
except:
return fig
app.run_server(mode='inline', port = 8070, dev_tools_ui=True,
dev_tools_hot_reload =True, threaded=True)