在 Plotly Dash 中使用多条轨迹实时回调图形

Call back in real time graph with multiple traces in Plotly Dash

如何制作包含多条轨迹的实时动态更新图? 对于每个时间间隔,我需要从“tmp.txt”读取行到数据['prof']和数据['pred']并更新折线图。

我在这里 (https://pythonprogramming.net/live-graphs-data-visualization-application-dash-python-tutorial/) 找到了实时更新的解决方案,但它没有显示如何对多个跟踪进行 @app.callback。我还发现它使用了过时的“事件”。

我的代码如下,如果有人能帮助我,我将不胜感激。谢谢

import dash
import dash_daq as daq
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
from collections import deque

def read():
    with open ("tmp.txt", "r") as f:
        for line in f:
            data=line.split(',')
    return data 

i=0

data =  { 'prof':deque(maxlen=120), 'pred': deque(maxlen=120) }

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)

app.layout = html.Div(

        children=[
            dcc.Interval(id='timer', interval=1000),
            html.Br(),
            html.Div([  
                dcc.Graph(id='graph')
                ])
            ])

@app.callback(Output('graph','figure'), [Input('timer','n_intervals')])
def update_graph():
    data=read()
    data=read()
    X.append(i)
    data['prof'].append(float(data[1]))
    data['pred'].append(float(data[2]))

    figure={
        'data':[
            {'x':X,'y':CPU['prof'],'type':'scatter','name':'Profiled'},
            {'x':X,'y':CPU['pred'],'type':'scatter','name':'Predicted'}
            ]}
    i+=1
    return figure

编辑: 'tmp.txt' 是一个不断被另一个程序覆盖的文件。 它只有一行,如下所示: '3.2233 4.33445', 32, 74.0, 0.13, 0.0, 0.0

经过反复试验,最后我想出了一个解决方案 plotly.graph_objs:

   ....
   dcc.Interval(id='timer', interval=1000),
   html.Div([
            dcc.Graph(id='graph', animate=True),
            ], 
    ....

关于回调:

@app.callback(Output('graph', 'figure'),
    [Input('timer', 'n_intervals')])
def update_graph_scatter(n):
    data=read()
    X.append(X[-1]+1)
    data['prof'].append(float(data[1]))
    data['pred'].append(float(data[2]))

    data = [go.Scatter(
            x=list(X),
            y=list(CPU['prof']),
            name='Prof',
            mode= 'lines+markers'
            ),
            go.Scatter(
            x=list(X),
            y=list(data['pred']),
            name='Pred',
            mode= 'lines+markers'
            ),
            ]

    return {'data': data,'layout' : go.Layout(xaxis=dict(range=[min(X),max(X)]),
                                                yaxis=dict(range=[0,380]))}