How to open a file using interactive click events in plot using python

Question

I have the application with the following requirement.

1. If I click the plot, it will display more information in the below plot.
2. If I click the plot on few DATAPOINTS, it should open a text/CSV file say C:\\Users\\Dm\\Desktop\\sample.txt in notepad/excel.

The first requirement is working fine, but I am quite struggling in the 2nd requirement.

The code I have so far for 1st requirement:

import numpy as np


class PointBrowser(object):
    """
    Click on a point to select and highlight it -- the data that
    generated the point will be shown in the lower axes.  Use the 'n'
    and 'p' keys to browse through the next and previous points
    """

    def __init__(self):
        self.lastind = 0

        self.text = ax.text(0.05, 0.95, 'selected: none',
                            transform=ax.transAxes, va='top')
        self.selected, = ax.plot([xs[0]], [ys[0]], 'o', ms=12, alpha=0.4,
                                 color='yellow', visible=False)

    def onpress(self, event):
        if self.lastind is None:
            return
        if event.key not in ('n', 'p'):
            return
        if event.key == 'n':
            inc = 1
        else:
            inc = -1

        self.lastind += inc
        self.lastind = np.clip(self.lastind, 0, len(xs) - 1)
        self.update()

    def onpick(self, event):

        if event.artist != line:
            return True

        N = len(event.ind)
        if not N:
            return True

        # the click locations
        x = event.mouseevent.xdata
        y = event.mouseevent.ydata

        distances = np.hypot(x - xs[event.ind], y - ys[event.ind])
        indmin = distances.argmin()
        dataind = event.ind[indmin]

        self.lastind = dataind
        self.update()

    def update(self):
        if self.lastind is None:
            return

        dataind = self.lastind

        ax2.cla()
        ax2.plot(X[dataind])

        ax2.text(0.05, 0.9, 'mu=%1.3f\nsigma=%1.3f' % (xs[dataind], ys[dataind]),
                 transform=ax2.transAxes, va='top')
        ax2.set_ylim(-0.5, 1.5)
        self.selected.set_visible(True)
        self.selected.set_data(xs[dataind], ys[dataind])

        self.text.set_text('selected: %d' % dataind)
        fig.canvas.draw()


if __name__ == '__main__':
    import matplotlib.pyplot as plt

    X = np.random.rand(100, 200)
    xs = np.mean(X, axis=1)
    ys = np.std(X, axis=1)

    fig, (ax, ax2) = plt.subplots(2, 1)
    ax.set_title('click on point to plot time series')
    line, = ax.plot(xs, ys, 'o', picker=5)  # 5 points tolerance

    browser = PointBrowser()

    fig.canvas.mpl_connect('pick_event', browser.onpick)
    fig.canvas.mpl_connect('key_press_event', browser.onpress)

    plt.show()

Questions:

1. Is it possible to achieve this? but I didn't get a single clue after research.

However, before coming up with some sort of convoluted solution to my problem, I figured I would ask the experts and see if there is something I'm missing. Unfortunately, I cannot change this paradigm easily without significant re-factoring.

Thanks in advance. I really appreciate example code snippets.

Answer 1

This will write the data from each point to a csv file using a threading.Thread with the csv module and open the file with notepad after using a subprocess, we just need to add a new method to do the writing and change update slightly:

   import csv
   import threading
   from subprocess import call


    def write_csv(self, dataind, xs, ys):
        fle = 'mu=%1.3f_sigma=%1.3f.csv' % (xs[dataind], ys[dataind])
        print("Writing to {}".format(fle))
        with open(fle, "w") as f:
            wr = csv.writer(f)
            wr.writerow(X[dataind])
        call(["notepad", fle])


    def update(self):
        if self.lastind is None:
            return

        dataind = self.lastind
        ax2.cla()
        ax2.plot(X[dataind])
        ax2.text(0.05, 0.9, 'mu=%1.3f\nsigma=%1.3f' % (xs[dataind], ys[dataind]),
                 transform=ax2.transAxes, va='top')

        ax2.set_ylim(-0.5, 1.5)
        self.selected.set_visible(True)
        self.selected.set_data(xs[dataind], ys[dataind])
        self.text.set_text('selected: %d' % dataind)
        t = threading.Thread(target=self.write_csv, args=(dataind, xs, ys))
        t.start()
        fig.canvas.draw()

If you want the option of selecting multiple point and writing all those to a single file, this will allow you to choose a new file for each or if you hit ctrl while picking the points each point you pick while it is held will have it's data written to a single file, you can change the naming convention and how it is written to the csv, this is just a runnable example, I have added a few prints that should hopefully help to see what is happening:

import csv
import threading
from subprocess import call


class PointBrowser(object):
    """
    Click on a point to select and highlight it -- the data that
    generated the point will be shown in the lower axes.  Use the 'n'
    and 'p' keys to browse through the next and previous points
    """

    def __init__(self):
        self.lastind = 0

        self.text = ax.text(0.05, 0.95, 'selected: none',
                            transform=ax.transAxes, va='top')
        self.selected, = ax.plot([xs[0]], [ys[0]], 'o', ms=12, alpha=0.4,
                                 color='yellow', visible=False)
        self.cntrl = False
        self.lock = threading.Lock()

    def onpress(self, event):
        if event.key == "control":
            self.cntrl = True
            with self.lock:
                self.mult = []
        if self.lastind is None:
            return
        if event.key not in ('n', 'p'):
            return
        if event.key == 'n':
            inc = 1
        else:
            inc = -1

        self.lastind += inc
        self.lastind = np.clip(self.lastind, 0, len(xs) - 1)
        self.update()

    def onpick(self, event):
        if event.artist != line:
            return True

        N = len(event.ind)
        if not N:
            return True

        # the click locations
        x = event.mouseevent.xdata
        y = event.mouseevent.ydata

        distances = np.hypot(x - xs[event.ind], y - ys[event.ind])
        indmin = distances.argmin()
        dataind = event.ind[indmin]

        self.lastind = dataind
        self.update()

    def write_csv(self, dataind, xs, ys, rows=False):
        fle = 'mu=%1.3f_sigma=%1.3f.csv' % (xs[dataind], ys[dataind])
        print("Writing to {}".format(fle))
        with open(fle, "w") as f:
            wr = csv.writer(f)
            wr.writerow(X[dataind]) if not rows else wr.writerows(X[dataind])
        call(["gedit", fle])

    def write_csv_mult(self):
        print("Writing multiple data")
        with self.lock:
            with open('multi.csv', "w") as f:
                wr = csv.writer(f)
                wr.writerows(self.mult)
        call(["gedit", 'multi.csv'])

    def update(self):
        if self.lastind is None:
            return

        dataind = self.lastind
        ax2.cla()
        ax2.plot(X[dataind])
        ax2.text(0.05, 0.9, 'mu=%1.3f\nsigma=%1.3f' % (xs[dataind], ys[dataind]),
                 transform=ax2.transAxes, va='top')

        if self.cntrl:
            with self.lock:
                self.mult.append(X[dataind])

        ax2.set_ylim(-0.5, 1.5)
        self.selected.set_visible(True)
        self.selected.set_data(xs[dataind], ys[dataind])
        self.text.set_text('selected: %d' % dataind)

        if not self.cntrl:
            t = threading.Thread(target=self.write_csv, args=(dataind, xs, ys))
            t.start()

        fig.canvas.draw()

    def release(self, event):
        if event.key == "control":
            print("Finished selecting")
            t = threading.Thread(target=self.write_csv_mult)
            t.start()
            self.cntrl = False


if __name__ == '__main__':
    import matplotlib.pyplot as plt
    import numpy as np

    X = np.random.rand(100, 200)
    xs = np.mean(X, axis=1)
    ys = np.std(X, axis=1)

    fig, (ax, ax2) = plt.subplots(2, 1)
    ax.set_title('click on point to plot time series')
    line, = ax.plot(xs, ys, 'o', picker=5)  # 5 points tolerance

    browser = PointBrowser()
    fig.canvas.mpl_connect('pick_event', browser.onpick)
    fig.canvas.mpl_connect('key_release_event', browser.release)
    fig.canvas.mpl_connect('key_press_event', browser.onpress)

    plt.show()