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matplotlib.use('module://kivy.garden.matplotlib.backend_kivy')
Once this is done, any figure instantiated after will be wrapped by a
:class:`FigureCanvasKivy` ready to use. From here there are two options to
continue with the development.
1. Use the :class:`FigureCanvasKivy` attribute defined as canvas from Figure,
to embed your matplotlib graph in your own Kivy application as can be seen in
the first example in the following section.
.. warning::
One can create a matplotlib widget by importing FigureCanvas::
from kivy.garden.matplotlib.backend_kivyagg import FigureCanvas
or
from kivy.garden.matplotlib.backend_kivy import FigureCanvas
and then instantiate an object::
fig, ax = plt.subplots()
my_mpl_kivy_widget = FigureCanvas(fig)
which will certainly work but a problem will arise if events were connected
before the FigureCanvas is instantiated. If this approach is taken please
connect matplotlib events after generating the matplotlib kivy widget
object ::
fig, ax = plt.subplots()
fig.canvas.mpl_connect('button_press_event', callback_handler)
my_mpl_kivy_widget = FigureCanvas(fig)
In this scenario button_press_event won't be connected with the object
being created in line 3, because will be connected to the default canvas
set by matplotlib. If this approach is taken be sure of connecting the
events after instantiation like the following: ::
fig, ax = plt.subplots()
my_mpl_kivy_widget = FigureCanvas(fig)
fig.canvas.mpl_connect('button_press_event', callback_handler)
2. Use pyplot to write the application following matplotlib sintax as can be
seen in the second example below. In this case a Kivy application will be
created automatically from the matplotlib instructions and a NavigationToolbar
will be added to the main canvas.
Examples
--------
1. Example of a simple Hello world matplotlib App::
fig, ax = plt.subplots()
ax.text(0.6, 0.5, "hello", size=50, rotation=30.,
ha="center", va="center",
bbox=dict(boxstyle="round",
ec=(1., 0.5, 0.5),
fc=(1., 0.8, 0.8),
)
)
ax.text(0.5, 0.4, "world", size=50, rotation=-30.,
ha="right", va="top",
bbox=dict(boxstyle="square",
ec=(1., 0.5, 0.5),
fc=(1., 0.8, 0.8),
)
)
canvas = fig.canvas
The object canvas can be added as a widget into the kivy tree widget.
If a change is done on the figure an update can be performed using
:meth:`~kivy.ext.mpl.backend_kivyagg.FigureCanvasKivyAgg.draw`.::
# update graph
canvas.draw()
The plot can be exported to png with
:meth:`~kivy.ext.mpl.backend_kivyagg.FigureCanvasKivyAgg.print_png`, as an
argument receives the `filename`.::
# export to png
canvas.print_png("my_plot.png")
2. Example of a pyplot application using matplotlib instructions::
import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = (20, 35, 30, 35, 27)
menStd = (2, 3, 4, 1, 2)
ind = np.arange(N) # the x locations for the groups
width = 0.35 # the width of the bars
figure, ax = plt.subplots()
rects1 = ax.bar(ind, menMeans, width, color='r', yerr=menStd)
womenMeans = (25, 32, 34, 20, 25)
womenStd = (3, 5, 2, 3, 3)
rects2 = ax.bar(ind + width, womenMeans, width, color='y', yerr=womenStd)