12

plt.show()是否可以在 plotly 的 Dash 框架中显示一个简单的 matplotlib 图(通常由 生成的那种)?或者只是带有情节的散点图和数据轨迹的类似情节的图表?

具体来说,我想我需要一个不同于Graph(见下文)的组件和一种在update_figure函数中返回简单图的方法。

例子:

import dash
import dash_core_components as dcc
import dash_html_components as html
import numpy as np
import matplotlib.pyplot as plt

app = dash.Dash()

app.layout = html.Div(children=[
    html.H1(children='Hello Dash'),

    dcc.Slider(
        id='n_points',
        min=10,
        max=100,
        step=1,
        value=50,
    ),

    dcc.Graph(id='example') # or something other than Graph?...
])

@app.callback(
    dash.dependencies.Output('example', 'figure'),
    [dash.dependencies.Input('n_points', 'value')]
)

def update_figure(n_points):
    #create some matplotlib graph
    x = np.random.rand(n_points)
    y = np.random.rand(n_points)
    plt.scatter(x, y)
    # plt.show()
    return None # return what, I don't know exactly, `plt`?

if __name__ == '__main__':
    app.run_server(debug=True)
4

3 回答 3

11

请参阅https://plot.ly/matplotlib/modifying-a-matplotlib-figure/。库中有一个mpl_to_plotly函数plotly.tools将从 matplotlib 图形返回一个绘图图形(然后可以返回到图形的图形属性)。

编辑:刚刚注意到你问过这个问题。也许以上是一个新功能,但它是最干净的方式。

于 2018-08-28T18:40:19.213 回答
7

如果您不想要交互式绘图,则可以返回静态绘图(从此帮助中找到)

import io
import base64

...

app.layout = html.Div(children=[
    ...,

    html.Img(id='example') # img element
])

@app.callback(
    dash.dependencies.Output('example', 'src'), # src attribute
    [dash.dependencies.Input('n_points', 'value')]
)
def update_figure(n_points):
    #create some matplotlib graph
    x = np.random.rand(n_points)
    y = np.random.rand(n_points)
    buf = io.BytesIO() # in-memory files
    plt.scatter(x, y)
    plt.savefig(buf, format = "png") # save to the above file object
    plt.close()
    data = base64.b64encode(buf.getbuffer()).decode("utf8") # encode to html elements
    return "data:image/png;base64,{}".format(data)
于 2019-07-08T09:47:25.503 回答
2
UserWarning: Starting a Matplotlib GUI outside of the main thread will likely fail

就我而言,它可以工作,尽管有警告信息

于 2021-04-21T11:11:39.170 回答