实时更新Dash / plotly中的数据

问题描述 投票:8回答:2

我想监视一些实时数据,并允许用户在与图表交互时选择自己的范围。我创建了这个小例子(从教程中得到)并且问题是,每次我更新绘图时,一切都会重置,因为update_graph_live()返回一个新的Plotly数字。 (见下面的例子)

是否可以仅更新数据,因此图形不会重新加载并重置为默认视图/设置?之前我使用的是d3.js并通过websockets发送数据,因此我可以在浏览器中过滤数据。但是我想直接用Dash来做。

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)
python plotly plotly-dash
2个回答
10
投票

如果你将animate=True添加到你的dcc.Graph切换的痕迹和选定的缩放/标记/保留的任何东西,但这不适用于条形图(虽然它应该工作:https://github.com/plotly/plotly.js/pull/1143)。此外,您需要返回痕迹,而不是返回完整的figure

我可以提出的最佳解决方案是将其拆分为两个图形,但您至少可以获得所需的大部分功能。

enter image description here

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)

0
投票

对于条形图,方框图和直方图图,您不应使用animate=True,否则图将超出绘图区域。此外,Dash Plotly已弃用Event,而是使用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)
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