仅实时更新 Dash/plotly 中的数据
Live updating only the data in Dash/plotly
我想监控一些实时数据并允许用户在与绘图交互时 select 自己的范围。我创建了这个小示例(从教程中获取),问题是,每次我更新绘图时,自 update_graph_live()
returns 一个新的 Plotly 图以来,所有内容都会重置。 (见下面的例子)
是否可以仅更新数据,而不重新加载图形并重置为默认值 view/settings?
我之前用的是d3.js,通过websockets发送数据,所以可以在浏览器中过滤数据。但我想直接用 Dash 做。
import dash
from dash.dependencies import Output, Event
import dash_core_components as dcc
import dash_html_components as html
from random import random
import plotly
app = dash.Dash(__name__)
app.layout = html.Div(
html.Div([
html.H4('Example'),
dcc.Graph(id='live-update-graph'),
dcc.Interval(
id='interval-component',
interval=1*1000
)
])
)
@app.callback(Output('live-update-graph', 'figure'),
events=[Event('interval-component', 'interval')])
def update_graph_live():
fig = plotly.tools.make_subplots(rows=2, cols=1, vertical_spacing=0.2)
fig['layout']['margin'] = {
'l': 30, 'r': 10, 'b': 30, 't': 10
}
fig['layout']['legend'] = {'x': 0, 'y': 1, 'xanchor': 'left'}
fig.append_trace({
'x': [1, 2, 3, 4, 5],
'y': [random() for i in range(5)],
'name': 'Foo',
'mode': 'lines+markers',
'type': 'scatter'
}, 1, 1)
fig.append_trace({
'x': [1, 2, 3, 4, 5],
'y': [random() for i in range(5)],
'name': 'Bar',
'type': 'bar'
}, 2, 1)
return fig
if __name__ == '__main__':
app.run_server(debug=True)
如果您将 animate=True
添加到您的 dcc.Graph
中,切换的轨迹和选择的 zoom/marker/whatever 将被保留,但这不适用于条形图(尽管它应该有效:https://github.com/plotly/plotly.js/pull/1143).此外,您不需要 return 完整的 figure
,而是只需要 return 痕迹。
我能想到的最佳解决方案是将其分成两个图表,但您至少可以获得大部分所需功能。
import dash
from dash.dependencies import Output, Event
import dash_core_components as dcc
import dash_html_components as html
from random import random
import plotly
app = dash.Dash(__name__)
app.layout = html.Div(
html.Div([
dcc.Graph(id='live-update-graph-scatter', animate=True),
dcc.Graph(id='live-update-graph-bar'),
dcc.Interval(
id='interval-component',
interval=1*1000
)
])
)
@app.callback(Output('live-update-graph-scatter', 'figure'),
events=[Event('interval-component', 'interval')])
def update_graph_scatter():
traces = list()
for t in range(2):
traces.append(plotly.graph_objs.Scatter(
x=[1, 2, 3, 4, 5],
y=[(t + 1) * random() for i in range(5)],
name='Scatter {}'.format(t),
mode= 'lines+markers'
))
return {'data': traces}
@app.callback(Output('live-update-graph-bar', 'figure'),
events=[Event('interval-component', 'interval')])
def update_graph_bar():
traces = list()
for t in range(2):
traces.append(plotly.graph_objs.Bar(
x=[1, 2, 3, 4, 5],
y=[(t + 1) * random() for i in range(5)],
name='Bar {}'.format(t)
))
layout = plotly.graph_objs.Layout(
barmode='group'
)
return {'data': traces, 'layout': layout}
if __name__ == '__main__':
app.run_server(debug=True)
对于条形图、方框图和直方图,您不应该使用 animate=True
,否则该图将会失效的绘图区。此外,Event 已被 Dash Plotly 弃用,请改用 Input。
import dash
from dash.dependencies import Output,Input
import dash_core_components as dcc
import dash_html_components as html
from random import random
import plotly
app = dash.Dash(__name__)
app.layout = html.Div(
html.Div([
dcc.Graph(id='live-update-graph-scatter', animate=True),
dcc.Graph(id='live-update-graph-bar'),
dcc.Interval(
id='interval-component',
interval=1*1000
)
])
)
@app.callback(Output('live-update-graph-scatter', 'figure'),
[Input('interval-component', 'interval')])
def update_graph_scatter():
traces = list()
for t in range(2):
traces.append(plotly.graph_objs.Scatter(
x=[1, 2, 3, 4, 5],
y=[(t + 1) * random() for i in range(5)],
name='Scatter {}'.format(t),
mode= 'lines+markers'
))
return {'data': traces}
@app.callback(Output('live-update-graph-bar', 'figure'),
[Input('interval-component', 'interval')])
def update_graph_bar():
traces = list()
for t in range(2):
traces.append(plotly.graph_objs.Bar(
x=[1, 2, 3, 4, 5],
y=[(t + 1) * random() for i in range(5)],
name='Bar {}'.format(t)
))
layout = plotly.graph_objs.Layout(
barmode='group'
)
return {'data': traces, 'layout': layout}
if __name__ == '__main__':
app.run_server(debug=True)
我想监控一些实时数据并允许用户在与绘图交互时 select 自己的范围。我创建了这个小示例(从教程中获取),问题是,每次我更新绘图时,自 update_graph_live()
returns 一个新的 Plotly 图以来,所有内容都会重置。 (见下面的例子)
是否可以仅更新数据,而不重新加载图形并重置为默认值 view/settings? 我之前用的是d3.js,通过websockets发送数据,所以可以在浏览器中过滤数据。但我想直接用 Dash 做。
import dash
from dash.dependencies import Output, Event
import dash_core_components as dcc
import dash_html_components as html
from random import random
import plotly
app = dash.Dash(__name__)
app.layout = html.Div(
html.Div([
html.H4('Example'),
dcc.Graph(id='live-update-graph'),
dcc.Interval(
id='interval-component',
interval=1*1000
)
])
)
@app.callback(Output('live-update-graph', 'figure'),
events=[Event('interval-component', 'interval')])
def update_graph_live():
fig = plotly.tools.make_subplots(rows=2, cols=1, vertical_spacing=0.2)
fig['layout']['margin'] = {
'l': 30, 'r': 10, 'b': 30, 't': 10
}
fig['layout']['legend'] = {'x': 0, 'y': 1, 'xanchor': 'left'}
fig.append_trace({
'x': [1, 2, 3, 4, 5],
'y': [random() for i in range(5)],
'name': 'Foo',
'mode': 'lines+markers',
'type': 'scatter'
}, 1, 1)
fig.append_trace({
'x': [1, 2, 3, 4, 5],
'y': [random() for i in range(5)],
'name': 'Bar',
'type': 'bar'
}, 2, 1)
return fig
if __name__ == '__main__':
app.run_server(debug=True)
如果您将 animate=True
添加到您的 dcc.Graph
中,切换的轨迹和选择的 zoom/marker/whatever 将被保留,但这不适用于条形图(尽管它应该有效:https://github.com/plotly/plotly.js/pull/1143).此外,您不需要 return 完整的 figure
,而是只需要 return 痕迹。
我能想到的最佳解决方案是将其分成两个图表,但您至少可以获得大部分所需功能。
import dash
from dash.dependencies import Output, Event
import dash_core_components as dcc
import dash_html_components as html
from random import random
import plotly
app = dash.Dash(__name__)
app.layout = html.Div(
html.Div([
dcc.Graph(id='live-update-graph-scatter', animate=True),
dcc.Graph(id='live-update-graph-bar'),
dcc.Interval(
id='interval-component',
interval=1*1000
)
])
)
@app.callback(Output('live-update-graph-scatter', 'figure'),
events=[Event('interval-component', 'interval')])
def update_graph_scatter():
traces = list()
for t in range(2):
traces.append(plotly.graph_objs.Scatter(
x=[1, 2, 3, 4, 5],
y=[(t + 1) * random() for i in range(5)],
name='Scatter {}'.format(t),
mode= 'lines+markers'
))
return {'data': traces}
@app.callback(Output('live-update-graph-bar', 'figure'),
events=[Event('interval-component', 'interval')])
def update_graph_bar():
traces = list()
for t in range(2):
traces.append(plotly.graph_objs.Bar(
x=[1, 2, 3, 4, 5],
y=[(t + 1) * random() for i in range(5)],
name='Bar {}'.format(t)
))
layout = plotly.graph_objs.Layout(
barmode='group'
)
return {'data': traces, 'layout': layout}
if __name__ == '__main__':
app.run_server(debug=True)
对于条形图、方框图和直方图,您不应该使用 animate=True
,否则该图将会失效的绘图区。此外,Event 已被 Dash Plotly 弃用,请改用 Input。
import dash
from dash.dependencies import Output,Input
import dash_core_components as dcc
import dash_html_components as html
from random import random
import plotly
app = dash.Dash(__name__)
app.layout = html.Div(
html.Div([
dcc.Graph(id='live-update-graph-scatter', animate=True),
dcc.Graph(id='live-update-graph-bar'),
dcc.Interval(
id='interval-component',
interval=1*1000
)
])
)
@app.callback(Output('live-update-graph-scatter', 'figure'),
[Input('interval-component', 'interval')])
def update_graph_scatter():
traces = list()
for t in range(2):
traces.append(plotly.graph_objs.Scatter(
x=[1, 2, 3, 4, 5],
y=[(t + 1) * random() for i in range(5)],
name='Scatter {}'.format(t),
mode= 'lines+markers'
))
return {'data': traces}
@app.callback(Output('live-update-graph-bar', 'figure'),
[Input('interval-component', 'interval')])
def update_graph_bar():
traces = list()
for t in range(2):
traces.append(plotly.graph_objs.Bar(
x=[1, 2, 3, 4, 5],
y=[(t + 1) * random() for i in range(5)],
name='Bar {}'.format(t)
))
layout = plotly.graph_objs.Layout(
barmode='group'
)
return {'data': traces, 'layout': layout}
if __name__ == '__main__':
app.run_server(debug=True)