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Jan 11, 2021
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Expand on slider_demo example #19264

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266066f
Expand on slider_demo example
ianhi Jan 9, 2021
bf0530a
More explicit variable names
ianhi Jan 10, 2021
786e41b
Make vertical slider more nicely shaped
ianhi Jan 10, 2021
411bdde
Simplify explanation and remove valstep from example
ianhi Jan 10, 2021
b0730ee
Link between all the slider examples.
ianhi Jan 10, 2021
fc20f19
Try to fix doc build
ianhi Jan 10, 2021
d07830c
cleanup python 2isms
ianhi Jan 11, 2021
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6 changes: 6 additions & 0 deletions examples/widgets/range_slider.py
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Expand Up @@ -8,6 +8,12 @@
The RangeSlider widget can be used similarly to the `.widgets.Slider`
widget. The major difference is that RangeSlider's ``val`` attribute
is a tuple of floats ``(lower val, upper val)`` rather than a single float.

See :doc:`/gallery/widgets/slider_demo` for an example of using
a ``Slider`` to control a single float.

See :doc:`/gallery/widgets/slider_snap_demo` for an example of having
the ``Slider`` snap to discrete values.
"""

import numpy as np
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93 changes: 55 additions & 38 deletions examples/widgets/slider_demo.py
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Expand Up @@ -3,65 +3,83 @@
Slider
======

Using the slider widget to control visual properties of your plot.
In this example, sliders are used to control the frequency and amplitude of
a sine wave.

In this example, a slider is used to choose the frequency of a sine
wave. You can control many continuously-varying properties of your plot in
this way.
See :doc:`/gallery/widgets/slider_snap_demo` for an example of having
the ``Slider`` snap to discrete values.

See :doc:`/gallery/widgets/range_slider` for an example of using
a ``RangeSlider`` to define a range of values.
"""
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider, Button, RadioButtons
from matplotlib.widgets import Slider, Button


# The parametrized function to be plotted
def f(t, amplitude, frequency):
return amplitude * np.sin(2 * np.pi * frequency * t)

t = np.linspace(0, 1, 1000)

# Define initial parameters
init_amplitude = 5
init_frequency = 3

# Create the figure and the line that we will manipulate
fig, ax = plt.subplots()
plt.subplots_adjust(left=0.25, bottom=0.25)
t = np.arange(0.0, 1.0, 0.001)
a0 = 5
f0 = 3
delta_f = 5.0
s = a0 * np.sin(2 * np.pi * f0 * t)
l, = plt.plot(t, s, lw=2)
ax.margins(x=0)
line, = plt.plot(t, f(t, init_amplitude, init_frequency), lw=2)
ax.set_xlabel('Time [s]')

axcolor = 'lightgoldenrodyellow'
axfreq = plt.axes([0.25, 0.1, 0.65, 0.03], facecolor=axcolor)
axamp = plt.axes([0.25, 0.15, 0.65, 0.03], facecolor=axcolor)

sfreq = Slider(axfreq, 'Freq', 0.1, 30.0, valinit=f0, valstep=delta_f)
samp = Slider(axamp, 'Amp', 0.1, 10.0, valinit=a0)
ax.margins(x=0)

# adjust the main plot to make room for the sliders
plt.subplots_adjust(left=0.25, bottom=0.25)

# Make a horizontal slider to control the frequency.
axfreq = plt.axes([0.25, 0.1, 0.65, 0.03], facecolor=axcolor)
freq_slider = Slider(
ax=axfreq,
label='Frequency [Hz]',
valmin=0.1,
valmax=30,
valinit=init_frequency,
)

# Make a vertically oriented slider to control the amplitude
axamp = plt.axes([0.1, 0.25, 0.0225, 0.63], facecolor=axcolor)
amp_slider = Slider(
ax=axamp,
label="Amplitude",
valmin=0,
valmax=10,
valinit=init_amplitude,
orientation="vertical"
)


# The function to be called anytime a slider's value changes
def update(val):
amp = samp.val
freq = sfreq.val
l.set_ydata(amp*np.sin(2*np.pi*freq*t))
line.set_ydata(f(t, amp_slider.val, freq_slider.val))
fig.canvas.draw_idle()


sfreq.on_changed(update)
samp.on_changed(update)
# register the update function with each slider
freq_slider.on_changed(update)
amp_slider.on_changed(update)

# Create a `matplotlib.widgets.Button` to reset the sliders to initial values.
resetax = plt.axes([0.8, 0.025, 0.1, 0.04])
button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')


def reset(event):
sfreq.reset()
samp.reset()
freq_slider.reset()
amp_slider.reset()
button.on_clicked(reset)

rax = plt.axes([0.025, 0.5, 0.15, 0.15], facecolor=axcolor)
radio = RadioButtons(rax, ('red', 'blue', 'green'), active=0)


def colorfunc(label):
l.set_color(label)
fig.canvas.draw_idle()
radio.on_clicked(colorfunc)

# Initialize plot with correct initial active value
colorfunc(radio.value_selected)

plt.show()

#############################################################################
Expand All @@ -76,5 +94,4 @@ def colorfunc(label):

import matplotlib
matplotlib.widgets.Button
matplotlib.widgets.RadioButtons
matplotlib.widgets.Slider
6 changes: 6 additions & 0 deletions examples/widgets/slider_snap_demo.py
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Expand Up @@ -8,6 +8,12 @@
In this example the Freq slider is constrained to be multiples of pi, and the
Amp slider uses an array as the ``valstep`` argument to more densely sample
the first part of its range.

See :doc:`/gallery/widgets/slider_demo` for an example of using
a ``Slider`` to control a single float.

See :doc:`/gallery/widgets/range_slider` for an example of using
a ``RangeSlider`` to define a range of values.
"""
import numpy as np
import matplotlib.pyplot as plt
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