Python 中的 Plotly-Dash 库存应用程序，带有客户端回调（x 轴缩放上的 y 轴自动缩放）

我正在使用 xaxis 滑块在 dash-plotly (python) 中创建一个简单的股票图表应用程序。滑动 x 轴时，我希望 y 轴动态重新缩放到视图。我想我已经设法在通过“relayoutData”挂钩滑动 xaxis 刻度时触发回调函数。但脚本没有更新 yaxis，而是抛出错误。我不确定从回调函数更新布局的正确语法。有任何想法吗？

到目前为止，这是我的代码。它运行，但 yaxis 在运行时设置，并且不更新。

非常感谢您的帮助=）

import dash
from dash.dependencies import Output, Input
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objs as go
import numpy as np
import datetime

#some random values
a = datetime.datetime.today()
numdays = 100
dateList = []
for x in range (0, numdays):
    dateList.append(a - datetime.timedelta(days = x))
xy = [dateList,np.random.rand(100)]

app = dash.Dash()

app.title = 'Random'
dataS = go.Scatter(
        x = xy[0],
        y = xy[1],
        name = 'Rand',
        mode = 'lines'
    )
layoutS = go.Layout(
    title="Rand",
    xaxis=dict(
        rangeslider_visible=True,
        rangeselector=dict(
            buttons=list([
                dict(count=1, label="1m", step="month", stepmode="backward"),
                dict(count=6, label="6m", step="month", stepmode="backward"),
                dict(count=1, label="YTD", step="year", stepmode="todate"),
                dict(count=1, label="1y", step="year", stepmode="backward"),
                dict(count=5, label="5y", step="year", stepmode="backward"),
                dict(step="all")
            ])
        )
    )
)

app.layout = html.Div(
    html.Div([
        html.H1(children='Random nums'),
        html.Div(children='''
            Rand rand rand.
        '''),

        dcc.Graph(id='RandGraph', animate=True, figure=go.FigureWidget(data=dataS,layout=layoutS))
    ])
)

@app.callback(Output('RandGraph','figure'),[Input('RandGraph','relayoutData')])
def update_graph(relOut):
    layout = go.Layout(
        yaxis=dict(range=[min(y),max(y)])
    )
    return {'layout':layout}

if __name__ == '__main__':
    app.run_server(debug=False)

这是结果。我首先尝试了服务器端实现，但最终速度非常慢（我保留它以供参考）。客户端实现的响应速度更快、响应速度更快。使用起来很愉快。我只需要学习一些 javascript 就可以工作 =) 当我尝试进行数组过滤时，我肯定缺少 pandas ！

这是工作代码。享受！

import dash
from dash.dependencies import Output, Input, State
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objs as go
import numpy as np
import pandas as pd
import datetime

#some random values
a = datetime.datetime.today()
numdays = 100
dateList = []
for x in range (0, numdays):
    dateList.append(a - datetime.timedelta(days = x))
xy = [dateList,np.random.rand(100)]
df = pd.DataFrame(data=xy[1],columns=["y"],index=xy[0])


#Graph data
dataS = [dict(
    x = df.index,
    y = df['y'],
    name = 'meter',
    mode = 'lines'
)]

#Graph layout
layoutS = go.Layout(
    title="Meter",
    xaxis=dict(
        rangeslider_visible=True,
        rangeselector=dict(
            buttons=list([
                dict(count=1, label="1m", step="month", stepmode="backward"),
                dict(count=6, label="6m", step="month", stepmode="backward"),
                dict(count=1, label="YTD", step="year", stepmode="todate"),
                dict(count=1, label="1y", step="year", stepmode="backward"),
                dict(count=5, label="5y", step="year", stepmode="backward"),
                dict(step="all")
            ])
        )
    ),
    yaxis=dict(range=[0,2])
)

#Dash app layout
app = dash.Dash()
app.title = 'Random'

app.layout = html.Div(
    html.Div([
        html.H1(children='Random nums'),
        html.Div(children='''
            Rand rand rand.
        '''),

        dcc.Input(
            id='input-y',
            placeholder='Insert y value',
            type='number',
            value='',
        ),
        html.Div(id='result'),

        dcc.Graph(id='RandGraph',figure=dict(data=dataS,layout=layoutS))
    ])
)

#client side implementation
app.clientside_callback(
    """
    function(relOut, Figure) {
        if (typeof relOut !== 'undefined') {
            if (typeof relOut["xaxis.range"] !== 'undefined') {
                //get active filter from graph
                fromS = new Date(relOut["xaxis.range"][0]).getTime()
                toS = new Date(relOut["xaxis.range"][1]).getTime()

                xD = Figure.data[0].x
                yD = Figure.data[0].y

                //filter y data with graph display
                yFilt = xD.reduce(function (pV,cV,cI){
                    sec = new Date(cV).getTime()
                    if (sec >= fromS && sec <= toS) {
                        pV.push(yD[cI])
                    }
                    return pV
                }, [])

                yMax = Math.max.apply(Math, yFilt)
                yMin = Math.min.apply(Math, yFilt)
            } else { 
                yMin = Math.min.apply(Math, Figure.data[0].y)
                yMax = Math.max.apply(Math, Figure.data[0].y) 
            }
        } else { 
            yMin = Math.min.apply(Math, Figure.data[0].y)
            yMax = Math.max.apply(Math, Figure.data[0].y) 
        }
        Figure.layout.yaxis = {
            'range': [yMin,yMax],
            'type': 'linear'
        }
        return {'data': Figure.data, 'layout': Figure.layout};
    }
    """,
    Output('RandGraph','figure'),
    [Input('RandGraph','relayoutData')],[State('RandGraph', 'figure')]
)

#Server side implementation (slow)
#@app.callback(
#    Output('RandGraph','figure'),
#    [Input('RandGraph','relayoutData')],[State('RandGraph', 'figure')]
#)
#def update_result(relOut,Fig):
#    ymin = df.loc[relOut['xaxis.range'][1]:relOut['xaxis.range'][0],'y'].min()
#    ymax = df.loc[relOut['xaxis.range'][1]:relOut['xaxis.range'][0],'y'].max()
#    newLayout = go.Layout(
#        title="OL Meter",
#        xaxis=dict(
#            rangeslider_visible=True,
#            rangeselector=dict(
#                buttons=list([
#                    dict(count=0, label="1m", step="month", stepmode="backward"),
#                    dict(count=6, label="6m", step="month", stepmode="backward"),
#                    dict(count=1, label="YTD", step="year", stepmode="todate"),
#                    dict(count=1, label="1y", step="year", stepmode="backward"),
#                    dict(count=5, label="5y", step="year", stepmode="backward"),
#                    dict(step="all")
#                ])
#            ),
#            range=relOut['xaxis.range']
#        ),
#        yaxis=dict(range=[ymin,ymax])
#    )
#    
#    
#    Fig['layout']=newLayout
#    return Fig

if __name__ == '__main__':
    app.run_server(debug=False)