python - 将交互式 WebAgg 绘图嵌入 Tornado 时出现问题

标签 python matplotlib tornado

我正在尝试将交互式 WebAgg 绘图嵌入到 Tornado Web 应用程序中。该图由三个点和两条线段连接而成,可以移动这些点并重新绘制线段。 Tornado 应用程序启动并显示 WebAgg 图的初始状态,但单击这些点不会执行任何操作。

我尝试以相同的方式嵌入情节 this example嵌入一​​个情节。

我只是更换了

def create_figure():
    """
    Creates a simple example figure.
    """
    fig = Figure()
    a = fig.add_subplot(111)
    t = np.arange(0.0, 3.0, 0.01)
    s = np.sin(2 * np.pi * t)
    a.plot(t, s)
    return fig

使用我的交互式 WebAgg 绘图代码

class InteractiveLine:
    def __init__(self, points_list):
        self.fig, self.ax = self.setup_axes()
        self.tolerance = 10
        self.xy = points_list

        x_data = [pt[0] for pt in points_list]
        y_data = [pt[1] for pt in points_list]
        self.points = self.ax.scatter(
            x_data, y_data, s=200, color='#39ff14',
            picker=self.tolerance, zorder=1)
        self.line = self.ax.plot(
            x_data, y_data, ls='--', c='#666666',
            zorder=0)

        self.fig.canvas.mpl_connect('button_press_event', self.on_click)

    def on_click(self, event):
        contains, info = self.points.contains(event)
        print(contains)
        print(info)
        if contains:
            ind = info['ind'][0]
            print("You clicked {}!".format(ind))
            self.start_drag(ind)

    def start_drag(self, ind):
        self.drag_ind = ind
        connect = self.fig.canvas.mpl_connect
        cid1 = connect('motion_notify_event', self.drag_update)
        cid2 = connect('button_release_event', self.end_drag)
        self.drag_cids = [cid1, cid2]
        self.on_press()

    def drag_update(self, event):
        self.xy[self.drag_ind] = [event.xdata, event.ydata]
        self.points.set_offsets(self.xy)
        self.ax.draw_artist(self.points)
        self.fig.canvas.draw()

    def end_drag(self, event):
        """End the binding of mouse motion to a particular point."""
        self.redraw()
        for cid in self.drag_cids:
            self.fig.canvas.mpl_disconnect(cid)


    def on_press(self):
        self.line[0].set_alpha(.4)

    def redraw(self):
        x_data,y_data = self.line[0].get_data()
        pt_x,pt_y = self.xy[self.drag_ind]
        x_data[self.drag_ind] = pt_x
        y_data[self.drag_ind] = pt_y
        self.line[0].set_data(x_data,y_data)
        self.line[0].set_alpha(1)
        self.fig.canvas.draw()


    def setup_axes(self):
        fig, ax = plt.subplots()
        return fig, ax

    def show(self):
        plt.show()

完整代码如下:

import io

try:
    import tornado
except ImportError:
    raise RuntimeError("This example requires tornado.")
import tornado.web
import tornado.httpserver
import tornado.ioloop
import tornado.websocket

from matplotlib.backends.backend_webagg_core import (
    FigureManagerWebAgg, new_figure_manager_given_figure)
from matplotlib.figure import Figure
import matplotlib.pyplot as plt
import matplotlib

import numpy as np

import json

class InteractiveLine:
    def __init__(self, points_list):
        self.fig, self.ax = self.setup_axes()
        self.tolerance = 10
        self.xy = points_list

        x_data = [pt[0] for pt in points_list]
        y_data = [pt[1] for pt in points_list]
        self.points = self.ax.scatter(
            x_data, y_data, s=200, color='#39ff14',
            picker=self.tolerance, zorder=1)
        self.line = self.ax.plot(
            x_data, y_data, ls='--', c='#666666',
            zorder=0)

        self.fig.canvas.mpl_connect('button_press_event', self.on_click)

    def on_click(self, event):
        contains, info = self.points.contains(event)
        print(contains)
        print(info)
        if contains:
            ind = info['ind'][0]
            print("You clicked {}!".format(ind))
            self.start_drag(ind)

    def start_drag(self, ind):
        self.drag_ind = ind
        connect = self.fig.canvas.mpl_connect
        cid1 = connect('motion_notify_event', self.drag_update)
        cid2 = connect('button_release_event', self.end_drag)
        self.drag_cids = [cid1, cid2]
        self.on_press()

    def drag_update(self, event):
        self.xy[self.drag_ind] = [event.xdata, event.ydata]
        self.points.set_offsets(self.xy)
        self.ax.draw_artist(self.points)
        self.fig.canvas.draw()

    def end_drag(self, event):
        """End the binding of mouse motion to a particular point."""
        self.redraw()
        for cid in self.drag_cids:
            self.fig.canvas.mpl_disconnect(cid)


    def on_press(self):
        self.line[0].set_alpha(.4)

    def redraw(self):
        x_data,y_data = self.line[0].get_data()
        pt_x,pt_y = self.xy[self.drag_ind]
        x_data[self.drag_ind] = pt_x
        y_data[self.drag_ind] = pt_y
        self.line[0].set_data(x_data,y_data)
        self.line[0].set_alpha(1)
        self.fig.canvas.draw()


    def setup_axes(self):
        fig, ax = plt.subplots()
        return fig, ax

    def show(self):
        plt.show()


# The following is the content of the web page.  You would normally
# generate this using some sort of template facility in your web
# framework, but here we just use Python string formatting.
html_content = """
<html>
  <head>
    <!-- TODO: There should be a way to include all of the required javascript
               and CSS so matplotlib can add to the set in the future if it
               needs to. -->
    <link rel="stylesheet" href="_static/css/page.css" type="text/css">
    <link rel="stylesheet" href="_static/css/boilerplate.css" type="text/css" />
    <link rel="stylesheet" href="_static/css/fbm.css" type="text/css" />
    <link rel="stylesheet" href="_static/jquery-ui-1.12.1/jquery-ui.min.css" >
    <script src="_static/jquery-ui-1.12.1/external/jquery/jquery.js"></script>
    <script src="_static/jquery-ui-1.12.1/jquery-ui.min.js"></script>
    <script src="mpl.js"></script>

    <script>
      /* This is a callback that is called when the user saves
         (downloads) a file.  Its purpose is really to map from a
         figure and file format to a url in the application. */
      function ondownload(figure, format) {
        window.open('download.' + format, '_blank');
      };

      $(document).ready(
        function() {
          /* It is up to the application to provide a websocket that the figure
             will use to communicate to the server.  This websocket object can
             also be a "fake" websocket that underneath multiplexes messages
             from multiple figures, if necessary. */
          var websocket_type = mpl.get_websocket_type();
          var websocket = new websocket_type("%(ws_uri)sws");

          // mpl.figure creates a new figure on the webpage.
          var fig = new mpl.figure(
              // A unique numeric identifier for the figure
              %(fig_id)s,
              // A websocket object (or something that behaves like one)
              websocket,
              // A function called when a file type is selected for download
              ondownload,
              // The HTML element in which to place the figure
              $('div#figure'));
        }
      );
    </script>

    <title>matplotlib</title>
  </head>

  <body>
    <div id="figure">
    </div>
  </body>
</html>
"""


class MyApplication(tornado.web.Application):
    class MainPage(tornado.web.RequestHandler):
        """
        Serves the main HTML page.
        """

        def get(self):
            manager = self.application.manager
            ws_uri = "ws://{req.host}/".format(req=self.request)
            content = html_content % {
                "ws_uri": ws_uri, "fig_id": manager.num}
            self.write(content)

    class MplJs(tornado.web.RequestHandler):
        """
        Serves the generated matplotlib javascript file.  The content
        is dynamically generated based on which toolbar functions the
        user has defined.  Call `FigureManagerWebAgg` to get its
        content.
        """

        def get(self):
            self.set_header('Content-Type', 'application/javascript')
            js_content = FigureManagerWebAgg.get_javascript()

            self.write(js_content)

    class Download(tornado.web.RequestHandler):
        """
        Handles downloading of the figure in various file formats.
        """

        def get(self, fmt):
            manager = self.application.manager

            mimetypes = {
                'ps': 'application/postscript',
                'eps': 'application/postscript',
                'pdf': 'application/pdf',
                'svg': 'image/svg+xml',
                'png': 'image/png',
                'jpeg': 'image/jpeg',
                'tif': 'image/tiff',
                'emf': 'application/emf'
            }

            self.set_header('Content-Type', mimetypes.get(fmt, 'binary'))

            buff = io.BytesIO()
            manager.canvas.figure.savefig(buff, format=fmt)
            self.write(buff.getvalue())

    class WebSocket(tornado.websocket.WebSocketHandler):
        """
        A websocket for interactive communication between the plot in
        the browser and the server.

        In addition to the methods required by tornado, it is required to
        have two callback methods:

            - ``send_json(json_content)`` is called by matplotlib when
              it needs to send json to the browser.  `json_content` is
              a JSON tree (Python dictionary), and it is the responsibility
              of this implementation to encode it as a string to send over
              the socket.

            - ``send_binary(blob)`` is called to send binary image data
              to the browser.
        """
        supports_binary = True

        def open(self):
            # Register the websocket with the FigureManager.
            manager = self.application.manager
            manager.add_web_socket(self)
            if hasattr(self, 'set_nodelay'):
                self.set_nodelay(True)

        def on_close(self):
            # When the socket is closed, deregister the websocket with
            # the FigureManager.
            manager = self.application.manager
            manager.remove_web_socket(self)

        def on_message(self, message):
            # The 'supports_binary' message is relevant to the
            # websocket itself.  The other messages get passed along
            # to matplotlib as-is.

            # Every message has a "type" and a "figure_id".
            message = json.loads(message)
            if message['type'] == 'supports_binary':
                self.supports_binary = message['value']
            else:
                manager = self.application.manager
                manager.handle_json(message)

        def send_json(self, content):
            self.write_message(json.dumps(content))

        def send_binary(self, blob):
            if self.supports_binary:
                self.write_message(blob, binary=True)
            else:
                data_uri = "data:image/png;base64,{0}".format(
                    blob.encode('base64').replace('\n', ''))
                self.write_message(data_uri)

    def __init__(self, figure):
        self.figure = figure
        self.manager = new_figure_manager_given_figure(id(figure), figure)

        super().__init__([
            # Static files for the CSS and JS
            (r'/_static/(.*)',
             tornado.web.StaticFileHandler,
             {'path': FigureManagerWebAgg.get_static_file_path()}),

            # The page that contains all of the pieces
            ('/', self.MainPage),

            ('/mpl.js', self.MplJs),

            # Sends images and events to the browser, and receives
            # events from the browser
            ('/ws', self.WebSocket),

            # Handles the downloading (i.e., saving) of static images
            (r'/download.([a-z0-9.]+)', self.Download),
        ])


if __name__ == "__main__":
    point_coords = [[.75, .75],
                    [1, 1],
                    [1.25, .125]]
    il = InteractiveLine(point_coords)
    application = MyApplication(il.fig)

    http_server = tornado.httpserver.HTTPServer(application)
    http_server.listen(8080)

    print("http://127.0.0.1:8080/")
    print("Press Ctrl+C to quit")

    tornado.ioloop.IOLoop.instance().start()

当我使用时,绘图按预期工作

InteractiveLine(point_coords).show()

我知道 .show() 方法也使用 Tornado,但我不确定如何获得与编写我自己的 Tornado 应用程序的 .show() 相同的结果。

最佳答案

我成功了!我更换了线路

self.manager = new_figure_manager_given_figure(id(figure), figure)

self.manager = self.figure.canvas.manager

我还明确告诉 matplotlib 使用 webagg:

matplotlib.use('webagg')

我认为创建一个新的图形管理器会覆盖事件连接,因此当图形收到鼠标事件时什么也没有发生。

关于python - 将交互式 WebAgg 绘图嵌入 Tornado 时出现问题,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/57564536/

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