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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"

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<head>

<title>Event handling and picking — Matplotlib 3.3.1 documentation</title>

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<h3><a href="../contents.html">Table of Contents</a></h3>

<ul>

<li><a class="reference internal" href="#">Event handling and picking</a><ul>

<li><a class="reference internal" href="#event-connections">Event connections</a></li>

<li><a class="reference internal" href="#event-attributes">Event attributes</a><ul>

<li><a class="reference internal" href="#draggable-rectangle-exercise">Draggable rectangle exercise</a></li>

</ul>

</li>

<li><a class="reference internal" href="#mouse-enter-and-leave">Mouse enter and leave</a></li>

<li><a class="reference internal" href="#object-picking">Object picking</a><ul>

<li><a class="reference internal" href="#simple-picking-example">Simple picking example</a></li>

<li><a class="reference internal" href="#picking-exercise">Picking exercise</a></li>

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<h1>Event handling and picking<a class="headerlink" href="#event-handling-and-picking" title="Permalink to this headline">¶</a></h1>

Matplotlib works with a number of user interface toolkits (wxpython,

tkinter, qt4, gtk, and macosx) and in order to support features like

interactive panning and zooming of figures, it is helpful to the

developers to have an API for interacting with the figure via key

presses and mouse movements that is "GUI neutral" so we don't have to

repeat a lot of code across the different user interfaces. Although

the event handling API is GUI neutral, it is based on the GTK model,

which was the first user interface matplotlib supported. The events

that are triggered are also a bit richer vis-a-vis matplotlib than

standard GUI events, including information like which

<a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><code class="xref py py-class docutils literal notranslate">matplotlib.axes.Axes</code></a> the event occurred in. The events also

understand the matplotlib coordinate system, and report event

locations in both pixel and data coordinates.

<h2>Event connections<a class="headerlink" href="#event-connections" title="Permalink to this headline">¶</a></h2>

To receive events, you need to write a callback function and then

connect your function to the event manager, which is part of the

<a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.FigureCanvasBase" title="matplotlib.backend_bases.FigureCanvasBase"><code class="xref py py-class docutils literal notranslate">FigureCanvasBase</code></a>. Here is a simple

example that prints the location of the mouse click and which button

was pressed:

<div class="highlight-default notranslate"><div class="highlight"><pre>fig, ax = plt.subplots()

ax.plot(np.random.rand(10))

def onclick(event):

print('%s click: button=%d, x=%d, y=%d, xdata=%f, ydata=%f' %

('double' if event.dblclick else 'single', event.button,

event.x, event.y, event.xdata, event.ydata))

cid = fig.canvas.mpl_connect('button_press_event', onclick)

</pre></div>

</div>

The <code class="docutils literal notranslate">FigureCanvas</code> method

<a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.FigureCanvasBase.mpl_connect" title="matplotlib.backend_bases.FigureCanvasBase.mpl_connect"><code class="xref py py-meth docutils literal notranslate">mpl_connect()</code></a> returns

a connection id which is simply an integer. When you want to

disconnect the callback, just call:

<div class="highlight-default notranslate"><div class="highlight"><pre>fig.canvas.mpl_disconnect(cid)

</pre></div>

</div>

Note

The canvas retains only weak references to instance methods used as

callbacks. Therefore, you need to retain a reference to instances owning

such methods. Otherwise the instance will be garbage-collected and the

callback will vanish.

This does not affect free functions used as callbacks.

</div>

Here are the events that you can connect to, the class instances that

are sent back to you when the event occurs, and the event descriptions:

</colgroup>

<tr class="row-odd"><th class="head">Event name</th>

<th class="head">Class</th>

<th class="head">Description</th>

</tr>

</thead>

<tr class="row-even"><td>'button_press_event'</td>

<td><a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.MouseEvent" title="matplotlib.backend_bases.MouseEvent"><code class="xref py py-obj docutils literal notranslate">MouseEvent</code></a></td>

<td>mouse button is pressed</td>

</tr>

<tr class="row-odd"><td>'button_release_event'</td>

<td>mouse button is released</td>

</tr>

<tr class="row-even"><td>'close_event'</td>

<td><a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.CloseEvent" title="matplotlib.backend_bases.CloseEvent"><code class="xref py py-obj docutils literal notranslate">CloseEvent</code></a></td>

<td>figure is closed</td>

</tr>

<tr class="row-odd"><td>'draw_event'</td>

<td><a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.DrawEvent" title="matplotlib.backend_bases.DrawEvent"><code class="xref py py-obj docutils literal notranslate">DrawEvent</code></a></td>

<td>canvas has been drawn (but screen

widget not updated yet)</td>

</tr>

<tr class="row-even"><td>'key_press_event'</td>

<td><a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.KeyEvent" title="matplotlib.backend_bases.KeyEvent"><code class="xref py py-obj docutils literal notranslate">KeyEvent</code></a></td>

<td>key is pressed</td>

</tr>

<tr class="row-odd"><td>'key_release_event'</td>

<td>key is released</td>

</tr>

<tr class="row-even"><td>'motion_notify_event'</td>

<td>mouse moves</td>

</tr>

<tr class="row-odd"><td>'pick_event'</td>

<td><a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.PickEvent" title="matplotlib.backend_bases.PickEvent"><code class="xref py py-obj docutils literal notranslate">PickEvent</code></a></td>

<td>artist in the canvas is selected</td>

</tr>

<tr class="row-even"><td>'resize_event'</td>

<td><a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.ResizeEvent" title="matplotlib.backend_bases.ResizeEvent"><code class="xref py py-obj docutils literal notranslate">ResizeEvent</code></a></td>

<td>figure canvas is resized</td>

</tr>

<tr class="row-odd"><td>'scroll_event'</td>

<td>mouse scroll wheel is rolled</td>

</tr>

<tr class="row-even"><td>'figure_enter_event'</td>

<td><a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.LocationEvent" title="matplotlib.backend_bases.LocationEvent"><code class="xref py py-obj docutils literal notranslate">LocationEvent</code></a></td>

<td>mouse enters a new figure</td>

</tr>

<tr class="row-odd"><td>'figure_leave_event'</td>

<td>mouse leaves a figure</td>

</tr>

<tr class="row-even"><td>'axes_enter_event'</td>

<td>mouse enters a new axes</td>

</tr>

<tr class="row-odd"><td>'axes_leave_event'</td>

<td>mouse leaves an axes</td>

</tr>

</tbody>

</table>

</div>

<h2>Event attributes<a class="headerlink" href="#event-attributes" title="Permalink to this headline">¶</a></h2>

All matplotlib events inherit from the base class

<a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.Event" title="matplotlib.backend_bases.Event"><code class="xref py py-class docutils literal notranslate">matplotlib.backend_bases.Event</code></a>, which store the attributes:

<dt><code class="docutils literal notranslate">name</code></dt><dd>the event name</dd>

<dt><code class="docutils literal notranslate">canvas</code></dt><dd>the FigureCanvas instance generating the event</dd>

<dt><code class="docutils literal notranslate">guiEvent</code></dt><dd>the GUI event that triggered the matplotlib event</dd>

</dl>

</div></blockquote>

The most common events that are the bread and butter of event handling

are key press/release events and mouse press/release and movement

events. The <a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.KeyEvent" title="matplotlib.backend_bases.KeyEvent"><code class="xref py py-class docutils literal notranslate">KeyEvent</code></a> and

<a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.MouseEvent" title="matplotlib.backend_bases.MouseEvent"><code class="xref py py-class docutils literal notranslate">MouseEvent</code></a> classes that handle

these events are both derived from the LocationEvent, which has the

following attributes

<dt><code class="docutils literal notranslate">x</code></dt><dd>x position - pixels from left of canvas</dd>

<dt><code class="docutils literal notranslate">y</code></dt><dd>y position - pixels from bottom of canvas</dd>

<dt><code class="docutils literal notranslate">inaxes</code></dt><dd>the <a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><code class="xref py py-class docutils literal notranslate">Axes</code></a> instance if mouse is over axes</dd>

<dt><code class="docutils literal notranslate">xdata</code></dt><dd>x coord of mouse in data coords</dd>

<dt><code class="docutils literal notranslate">ydata</code></dt><dd>y coord of mouse in data coords</dd>

</dl>

</div></blockquote>

Let's look a simple example of a canvas, where a simple line segment

is created every time a mouse is pressed:

<div class="highlight-default notranslate"><div class="highlight"><pre>from matplotlib import pyplot as plt

class LineBuilder:

def __init__(self, line):

self.line = line

self.xs = list(line.get_xdata())

self.ys = list(line.get_ydata())

self.cid = line.figure.canvas.mpl_connect('button_press_event', self)

def __call__(self, event):

print('click', event)

if event.inaxes!=self.line.axes: return

self.xs.append(event.xdata)

self.ys.append(event.ydata)

self.line.set_data(self.xs, self.ys)

self.line.figure.canvas.draw()

fig = plt.figure()

ax = fig.add_subplot(111)

ax.set_title('click to build line segments')

linebuilder = LineBuilder(line)

plt.show()

</pre></div>

</div>

The <a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.MouseEvent" title="matplotlib.backend_bases.MouseEvent"><code class="xref py py-class docutils literal notranslate">MouseEvent</code></a> that we just used is a

<a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.LocationEvent" title="matplotlib.backend_bases.LocationEvent"><code class="xref py py-class docutils literal notranslate">LocationEvent</code></a>, so we have access to

the data and pixel coordinates in event.x and event.xdata. In

addition to the <code class="docutils literal notranslate">LocationEvent</code> attributes, it has

<dt><code class="docutils literal notranslate">button</code></dt><dd>button pressed None, 1, 2, 3, 'up', 'down' (up and down are used for scroll events)</dd>

<dt><code class="docutils literal notranslate">key</code></dt><dd>the key pressed: None, any character, 'shift', 'win', or 'control'</dd>

</dl>

</div></blockquote>

<h3>Draggable rectangle exercise<a class="headerlink" href="#draggable-rectangle-exercise" title="Permalink to this headline">¶</a></h3>

Write draggable rectangle class that is initialized with a

<a class="reference internal" href="../api/_as_gen/matplotlib.patches.Rectangle.html#matplotlib.patches.Rectangle" title="matplotlib.patches.Rectangle"><code class="xref py py-class docutils literal notranslate">Rectangle</code></a> instance but will move its x,y

location when dragged. Hint: you will need to store the original

<code class="docutils literal notranslate">xy</code> location of the rectangle which is stored as rect.xy and

connect to the press, motion and release mouse events. When the mouse

is pressed, check to see if the click occurs over your rectangle (see

<code class="xref py py-meth docutils literal notranslate">matplotlib.patches.Rectangle.contains()</code>) and if it does, store

the rectangle xy and the location of the mouse click in data coords.

In the motion event callback, compute the deltax and deltay of the

mouse movement, and add those deltas to the origin of the rectangle

you stored. The redraw the figure. On the button release event, just

reset all the button press data you stored as None.

Here is the solution:

<div class="highlight-default notranslate"><div class="highlight"><pre>import numpy as np

import matplotlib.pyplot as plt

class DraggableRectangle:

def __init__(self, rect):

self.rect = rect

self.press = None

def connect(self):

'connect to all the events we need'

self.cidpress = self.rect.figure.canvas.mpl_connect(

'button_press_event', self.on_press)

self.cidrelease = self.rect.figure.canvas.mpl_connect(

'button_release_event', self.on_release)

self.cidmotion = self.rect.figure.canvas.mpl_connect(

'motion_notify_event', self.on_motion)

def on_press(self, event):

'on button press we will see if the mouse is over us and store some data'

if event.inaxes != self.rect.axes: return

contains, attrd = self.rect.contains(event)

if not contains: return

print('event contains', self.rect.xy)

x0, y0 = self.rect.xy

self.press = x0, y0, event.xdata, event.ydata

def on_motion(self, event):

'on motion we will move the rect if the mouse is over us'

if self.press is None: return

if event.inaxes != self.rect.axes: return

x0, y0, xpress, ypress = self.press

dx = event.xdata - xpress

dy = event.ydata - ypress

#print('x0=%f, xpress=%f, event.xdata=%f, dx=%f, x0+dx=%f' %

# (x0, xpress, event.xdata, dx, x0+dx))

self.rect.set_x(x0+dx)

self.rect.set_y(y0+dy)

def on_release(self, event):

'on release we reset the press data'

self.press = None

def disconnect(self):

'disconnect all the stored connection ids'

self.rect.figure.canvas.mpl_disconnect(self.cidpress)

fig = plt.figure()

rects = ax.bar(range(10), 20*np.random.rand(10))

drs = []

for rect in rects:

dr = DraggableRectangle(rect)

dr.connect()

drs.append(dr)

plt.show()

</pre></div>

</div>

Extra credit: Use blitting to make the animated drawing faster and

smoother.

Extra credit solution:

<div class="highlight-default notranslate"><div class="highlight"><pre># Draggable rectangle with blitting.

import numpy as np

import matplotlib.pyplot as plt

class DraggableRectangle:

lock = None # only one can be animated at a time

def __init__(self, rect):

self.rect = rect

self.press = None

self.background = None

def connect(self):

'connect to all the events we need'

'button_press_event', self.on_press)

'button_release_event', self.on_release)

'motion_notify_event', self.on_motion)

def on_press(self, event):

'on button press we will see if the mouse is over us and store some data'

if event.inaxes != self.rect.axes: return

if DraggableRectangle.lock is not None: return

if not contains: return

DraggableRectangle.lock = self

# draw everything but the selected rectangle and store the pixel buffer

canvas = self.rect.figure.canvas

axes = self.rect.axes

self.rect.set_animated(True)

canvas.draw()

self.background = canvas.copy_from_bbox(self.rect.axes.bbox)

# now redraw just the rectangle

axes.draw_artist(self.rect)

# and blit just the redrawn area

canvas.blit(axes.bbox)

def on_motion(self, event):

'on motion we will move the rect if the mouse is over us'

return

if event.inaxes != self.rect.axes: return

dx = event.xdata - xpress

dy = event.ydata - ypress

axes = self.rect.axes

# restore the background region

canvas.restore_region(self.background)

# redraw just the current rectangle

# blit just the redrawn area

def on_release(self, event):

'on release we reset the press data'

return

self.press = None

DraggableRectangle.lock = None

# turn off the rect animation property and reset the background

self.background = None

# redraw the full figure

def disconnect(self):

'disconnect all the stored connection ids'

fig = plt.figure()

drs = []

for rect in rects:

dr = DraggableRectangle(rect)

dr.connect()

drs.append(dr)

plt.show()

</pre></div>

</div>

<h2>Mouse enter and leave<a class="headerlink" href="#mouse-enter-and-leave" title="Permalink to this headline">¶</a></h2>

If you want to be notified when the mouse enters or leaves a figure or

axes, you can connect to the figure/axes enter/leave events. Here is

a simple example that changes the colors of the axes and figure

background that the mouse is over:

<div class="highlight-default notranslate"><div class="highlight"><pre>"""

Illustrate the figure and axes enter and leave events by changing the

frame colors on enter and leave

"""

import matplotlib.pyplot as plt

def enter_axes(event):

print('enter_axes', event.inaxes)

event.inaxes.patch.set_facecolor('yellow')

event.canvas.draw()

def leave_axes(event):

print('leave_axes', event.inaxes)

event.canvas.draw()

def enter_figure(event):

print('enter_figure', event.canvas.figure)

event.canvas.figure.patch.set_facecolor('red')

event.canvas.draw()

def leave_figure(event):

print('leave_figure', event.canvas.figure)

event.canvas.draw()

fig1 = plt.figure()

fig1.suptitle('mouse hover over figure or axes to trigger events')

ax1 = fig1.add_subplot(211)

ax2 = fig1.add_subplot(212)

fig1.canvas.mpl_connect('figure_enter_event', enter_figure)

fig1.canvas.mpl_connect('figure_leave_event', leave_figure)

fig1.canvas.mpl_connect('axes_enter_event', enter_axes)

fig1.canvas.mpl_connect('axes_leave_event', leave_axes)

fig2 = plt.figure()

fig2.suptitle('mouse hover over figure or axes to trigger events')

ax1 = fig2.add_subplot(211)

ax2 = fig2.add_subplot(212)

fig2.canvas.mpl_connect('figure_enter_event', enter_figure)

fig2.canvas.mpl_connect('figure_leave_event', leave_figure)

fig2.canvas.mpl_connect('axes_enter_event', enter_axes)

fig2.canvas.mpl_connect('axes_leave_event', leave_axes)

plt.show()

</pre></div>

</div>

<h2>Object picking<a class="headerlink" href="#object-picking" title="Permalink to this headline">¶</a></h2>

You can enable picking by setting the <code class="docutils literal notranslate">picker</code> property of an

<a class="reference internal" href="../api/artist_api.html#matplotlib.artist.Artist" title="matplotlib.artist.Artist"><code class="xref py py-class docutils literal notranslate">Artist</code></a> (e.g., a matplotlib

<a class="reference internal" href="../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D" title="matplotlib.lines.Line2D"><code class="xref py py-class docutils literal notranslate">Line2D</code></a>, <a class="reference internal" href="../api/text_api.html#matplotlib.text.Text" title="matplotlib.text.Text"><code class="xref py py-class docutils literal notranslate">Text</code></a>,

<a class="reference internal" href="../api/_as_gen/matplotlib.patches.Patch.html#matplotlib.patches.Patch" title="matplotlib.patches.Patch"><code class="xref py py-class docutils literal notranslate">Patch</code></a>, <a class="reference internal" href="../api/_as_gen/matplotlib.patches.Polygon.html#matplotlib.patches.Polygon" title="matplotlib.patches.Polygon"><code class="xref py py-class docutils literal notranslate">Polygon</code></a>,

<a class="reference internal" href="../api/image_api.html#matplotlib.image.AxesImage" title="matplotlib.image.AxesImage"><code class="xref py py-class docutils literal notranslate">AxesImage</code></a>, etc...)

There are a variety of meanings of the <code class="docutils literal notranslate">picker</code> property:

<dt><code class="docutils literal notranslate">None</code></dt><dd>picking is disabled for this artist (default)</dd>

<dt><code class="docutils literal notranslate">boolean</code></dt><dd>if True then picking will be enabled and the artist will fire a

pick event if the mouse event is over the artist</dd>

<dt><code class="docutils literal notranslate">float</code></dt><dd>if picker is a number it is interpreted as an epsilon tolerance in

points and the artist will fire off an event if its data is

within epsilon of the mouse event. For some artists like lines

and patch collections, the artist may provide additional data to

the pick event that is generated, e.g., the indices of the data

within epsilon of the pick event.</dd>

<dt><code class="docutils literal notranslate">function</code></dt><dd>if picker is callable, it is a user supplied function which

determines whether the artist is hit by the mouse event. The

signature is <code class="docutils literal notranslate">hit, props = picker(artist, mouseevent)</code> to

determine the hit test. If the mouse event is over the artist,

return <code class="docutils literal notranslate">hit=True</code> and props is a dictionary of properties you

want added to the <a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.PickEvent" title="matplotlib.backend_bases.PickEvent"><code class="xref py py-class docutils literal notranslate">PickEvent</code></a>

attributes</dd>

</dl>

</div></blockquote>

After you have enabled an artist for picking by setting the <code class="docutils literal notranslate">picker</code>

property, you need to connect to the figure canvas pick_event to get

pick callbacks on mouse press events. e.g.:

<div class="highlight-default notranslate"><div class="highlight"><pre>def pick_handler(event):

mouseevent = event.mouseevent

artist = event.artist

# now do something with this...

</pre></div>

</div>

The <a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.PickEvent" title="matplotlib.backend_bases.PickEvent"><code class="xref py py-class docutils literal notranslate">PickEvent</code></a> which is passed to

your callback is always fired with two attributes:

<dt><code class="docutils literal notranslate">mouseevent</code> the mouse event that generate the pick event. The</dt><dd>mouse event in turn has attributes like <code class="docutils literal notranslate">x</code> and <code class="docutils literal notranslate">y</code> (the

coords in display space, e.g., pixels from left, bottom) and xdata,

ydata (the coords in data space). Additionally, you can get

information about which buttons were pressed, which keys were

pressed, which <a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><code class="xref py py-class docutils literal notranslate">Axes</code></a> the mouse is over,

etc. See <a class="reference internal" href="../api/backend_bases_api.html#matplotlib.backend_bases.MouseEvent" title="matplotlib.backend_bases.MouseEvent"><code class="xref py py-class docutils literal notranslate">matplotlib.backend_bases.MouseEvent</code></a> for

details.</dd>

<dt><code class="docutils literal notranslate">artist</code></dt><dd>the <a class="reference internal" href="../api/artist_api.html#matplotlib.artist.Artist" title="matplotlib.artist.Artist"><code class="xref py py-class docutils literal notranslate">Artist</code></a> that generated the pick

event.</dd>

</dl>

</div></blockquote>

Additionally, certain artists like <a class="reference internal" href="../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D" title="matplotlib.lines.Line2D"><code class="xref py py-class docutils literal notranslate">Line2D</code></a>

and <a class="reference internal" href="../api/collections_api.html#matplotlib.collections.PatchCollection" title="matplotlib.collections.PatchCollection"><code class="xref py py-class docutils literal notranslate">PatchCollection</code></a> may attach

additional meta data like the indices into the data that meet the

picker criteria (e.g., all the points in the line that are within the

specified epsilon tolerance)

<h3>Simple picking example<a class="headerlink" href="#simple-picking-example" title="Permalink to this headline">¶</a></h3>

In the example below, we set the line picker property to a scalar, so

it represents a tolerance in points (72 points per inch). The onpick

callback function will be called when the pick event it within the

tolerance distance from the line, and has the indices of the data

vertices that are within the pick distance tolerance. Our onpick

callback function simply prints the data that are under the pick

location. Different matplotlib Artists can attach different data to

the PickEvent. For example, <code class="docutils literal notranslate">Line2D</code> attaches the ind property,

which are the indices into the line data under the pick point. See

<code class="xref py py-meth docutils literal notranslate">pick()</code> for details on the <code class="docutils literal notranslate">PickEvent</code>

properties of the line. Here is the code:

<div class="highlight-default notranslate"><div class="highlight"><pre>import numpy as np

import matplotlib.pyplot as plt

fig = plt.figure()

ax.set_title('click on points')

line, = ax.plot(np.random.rand(100), 'o', picker=5) # 5 points tolerance

def onpick(event):

thisline = event.artist

xdata = thisline.get_xdata()

ydata = thisline.get_ydata()

ind = event.ind

points = tuple(zip(xdata[ind], ydata[ind]))

print('onpick points:', points)

fig.canvas.mpl_connect('pick_event', onpick)

plt.show()

</pre></div>

</div>

<h3>Picking exercise<a class="headerlink" href="#picking-exercise" title="Permalink to this headline">¶</a></h3>

Create a data set of 100 arrays of 1000 Gaussian random numbers and

compute the sample mean and standard deviation of each of them (hint:

NumPy arrays have a mean and std method) and make a xy marker plot of

the 100 means vs. the 100 standard deviations. Connect the line

created by the plot command to the pick event, and plot the original

time series of the data that generated the clicked on points. If more

than one point is within the tolerance of the clicked on point, you

can use multiple subplots to plot the multiple time series.

Exercise solution:

<div class="highlight-default notranslate"><div class="highlight"><pre>"""

compute the mean and stddev of 100 data sets and plot mean vs. stddev.

When you click on one of the mu, sigma points, plot the raw data from

the dataset that generated the mean and stddev

"""

import numpy as np

import matplotlib.pyplot as plt

X = np.random.rand(100, 1000)

xs = np.mean(X, axis=1)

ys = np.std(X, axis=1)

fig = plt.figure()

ax.set_title('click on point to plot time series')

line, = ax.plot(xs, ys, 'o', picker=5) # 5 points tolerance

def onpick(event):

if event.artist!=line: return True

N = len(event.ind)

if not N: return True

figi = plt.figure()

for subplotnum, dataind in enumerate(event.ind):

ax = figi.add_subplot(N,1,subplotnum+1)

ax.plot(X[dataind])

ax.text(0.05, 0.9, 'mu=%1.3f\nsigma=%1.3f'%(xs[dataind], ys[dataind]),

transform=ax.transAxes, va='top')

ax.set_ylim(-0.5, 1.5)

figi.show()

return True

plt.show()

</pre></div>

</div>

</div>

Last updated on Aug 14, 2020.

Created using

<a href="http://sphinx-doc.org/">Sphinx</a> 3.1.1.

Doc version v3.3.1-2-ge49322daa.

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