Matplotlib Crosshair Cursor

Introduction

Matplotlib is a popular data visualization library that provides a wide range of tools for creating visualizations in Python. One of the interesting features of Matplotlib is the ability to add a crosshair cursor to a plot. In this lab, you will learn how to add a crosshair cursor to a Matplotlib plot.

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Simple Cursor

The first step is to add a simple cursor to a Matplotlib plot. This cursor will display the x and y values of the current mouse location.

import matplotlib.pyplot as plt
import numpy as np

from matplotlib.backend_bases import MouseEvent

class Cursor:
    """
    A cross hair cursor.
    """
    def __init__(self, ax):
        self.ax = ax
        self.horizontal_line = ax.axhline(color='k', lw=0.8, ls='--')
        self.vertical_line = ax.axvline(color='k', lw=0.8, ls='--')
        ## text location in axes coordinates
        self.text = ax.text(0.72, 0.9, '', transform=ax.transAxes)

    def set_cross_hair_visible(self, visible):
        need_redraw = self.horizontal_line.get_visible() != visible
        self.horizontal_line.set_visible(visible)
        self.vertical_line.set_visible(visible)
        self.text.set_visible(visible)
        return need_redraw

    def on_mouse_move(self, event):
        if not event.inaxes:
            need_redraw = self.set_cross_hair_visible(False)
            if need_redraw:
                self.ax.figure.canvas.draw()
        else:
            self.set_cross_hair_visible(True)
            x, y = event.xdata, event.ydata
            ## update the line positions
            self.horizontal_line.set_ydata([y])
            self.vertical_line.set_xdata([x])
            self.text.set_text(f'x={x:1.2f}, y={y:1.2f}')
            self.ax.figure.canvas.draw()

x = np.arange(0, 1, 0.01)
y = np.sin(2 * 2 * np.pi * x)

fig, ax = plt.subplots()
ax.set_title('Simple cursor')
ax.plot(x, y, 'o')
cursor = Cursor(ax)
fig.canvas.mpl_connect('motion_notify_event', cursor.on_mouse_move)

plt.show()

Faster Cursoring using Blitting

The cursor created in the previous step is a bit slow because it redraws the figure on every mouse move. In this step, we will create a cursor that uses blitting for faster rendering.

class BlittedCursor:
    """
    A cross-hair cursor using blitting for faster redraw.
    """
    def __init__(self, ax):
        self.ax = ax
        self.background = None
        self.horizontal_line = ax.axhline(color='k', lw=0.8, ls='--')
        self.vertical_line = ax.axvline(color='k', lw=0.8, ls='--')
        ## text location in axes coordinates
        self.text = ax.text(0.72, 0.9, '', transform=ax.transAxes)
        self._creating_background = False
        ax.figure.canvas.mpl_connect('draw_event', self.on_draw)

    def on_draw(self, event):
        self.create_new_background()

    def set_cross_hair_visible(self, visible):
        need_redraw = self.horizontal_line.get_visible() != visible
        self.horizontal_line.set_visible(visible)
        self.vertical_line.set_visible(visible)
        self.text.set_visible(visible)
        return need_redraw

    def create_new_background(self):
        if self._creating_background:
            ## discard calls triggered from within this function
            return
        self._creating_background = True
        self.set_cross_hair_visible(False)
        self.ax.figure.canvas.draw()
        self.background = self.ax.figure.canvas.copy_from_bbox(self.ax.bbox)
        self.set_cross_hair_visible(True)
        self._creating_background = False

    def on_mouse_move(self, event):
        if self.background is None:
            self.create_new_background()
        if not event.inaxes:
            need_redraw = self.set_cross_hair_visible(False)
            if need_redraw:
                self.ax.figure.canvas.restore_region(self.background)
                self.ax.figure.canvas.blit(self.ax.bbox)
        else:
            self.set_cross_hair_visible(True)
            ## update the line positions
            x, y = event.xdata, event.ydata
            self.horizontal_line.set_ydata([y])
            self.vertical_line.set_xdata([x])
            self.text.set_text(f'x={x:1.2f}, y={y:1.2f}')

            self.ax.figure.canvas.restore_region(self.background)
            self.ax.draw_artist(self.horizontal_line)
            self.ax.draw_artist(self.vertical_line)
            self.ax.draw_artist(self.text)
            self.ax.figure.canvas.blit(self.ax.bbox)

x = np.arange(0, 1, 0.01)
y = np.sin(2 * 2 * np.pi * x)

fig, ax = plt.subplots()
ax.set_title('Blitted cursor')
ax.plot(x, y, 'o')
blitted_cursor = BlittedCursor(ax)
fig.canvas.mpl_connect('motion_notify_event', blitted_cursor.on_mouse_move)

plt.show()

Snapping to Data Points

The cursor created in the previous step is still a bit slow because it updates the cursor position on every mouse move. In this step, we will create a cursor that snaps to the data points of a Line2D object.

class SnappingCursor:
    """
    A cross-hair cursor that snaps to the data point of a line, which is
    closest to the *x* position of the cursor.

    For simplicity, this assumes that *x* values of the data are sorted.
    """
    def __init__(self, ax, line):
        self.ax = ax
        self.horizontal_line = ax.axhline(color='k', lw=0.8, ls='--')
        self.vertical_line = ax.axvline(color='k', lw=0.8, ls='--')
        self.x, self.y = line.get_data()
        self._last_index = None
        ## text location in axes coords
        self.text = ax.text(0.72, 0.9, '', transform=ax.transAxes)

    def set_cross_hair_visible(self, visible):
        need_redraw = self.horizontal_line.get_visible() != visible
        self.horizontal_line.set_visible(visible)
        self.vertical_line.set_visible(visible)
        self.text.set_visible(visible)
        return need_redraw

    def on_mouse_move(self, event):
        if not event.inaxes:
            self._last_index = None
            need_redraw = self.set_cross_hair_visible(False)
            if need_redraw:
                self.ax.figure.canvas.draw()
        else:
            self.set_cross_hair_visible(True)
            x, y = event.xdata, event.ydata
            index = min(np.searchsorted(self.x, x), len(self.x) - 1)
            if index == self._last_index:
                return  ## still on the same data point. Nothing to do.
            self._last_index = index
            x = self.x[index]
            y = self.y[index]
            ## update the line positions
            self.horizontal_line.set_ydata([y])
            self.vertical_line.set_xdata([x])
            self.text.set_text(f'x={x:1.2f}, y={y:1.2f}')
            self.ax.figure.canvas.draw()

x = np.arange(0, 1, 0.01)
y = np.sin(2 * 2 * np.pi * x)

fig, ax = plt.subplots()
ax.set_title('Snapping cursor')
line, = ax.plot(x, y, 'o')
snap_cursor = SnappingCursor(ax, line)
fig.canvas.mpl_connect('motion_notify_event', snap_cursor.on_mouse_move)

plt.show()

Summary

In this lab, you learned how to add a crosshair cursor to a Matplotlib plot. You created a simple cursor, a cursor that uses blitting for faster rendering, and a cursor that snaps to data points of a Line2D object. These cursors can be useful for exploring data and gaining insights from visualizations.