def test_save_animation():
# just test that no errors are thrown, don't actually check
# that the saved animation makes any sense. Doing that seems hard :(
x = np.linspace(0, np.pi, 100)
tau = widgets.FloatSlider(min=1, max=10, step=1.5)
def f1(x, amp, tau, beta):
return amp * np.sin(x * tau) * x * beta
def f2(x, amp, tau, beta):
return amp * np.sin(x * beta) * x * tau
x = np.linspace(0, 2 * np.pi, 200)
fig, ax = plt.subplots()
plt.subplots_adjust(bottom=0.25)
axfreq = plt.axes([0.25, 0.1, 0.65, 0.03])
amp_slider = Slider(axfreq, label="amp", valmin=0.05, valmax=10)
ctrls = Controls(use_ipywidgets=True,
tau=tau,
beta=(1, 10, 15),
amp=amp_slider)
iplt.plot(x, f1, ax=ax, controls=ctrls)
iplt.plot(x, f2, ax=ax, controls=ctrls)
ctrls.save_animation("animation-amp.gif", fig, "amp", N_frames=10)
ctrls.save_animation("animation-beta.gif", fig, "beta")
ctrls.save_animation("animation-tau.gif", fig, "tau")
def test_title():
fig, ax = plt.subplots()
ctrls = iplt.plot(1, 1, E=3e7)
expected = "E=3.00e+07"
iplt.title("E={E:.2e}", controls=ctrls)
assert not isinstance(ctrls.params["E"], np.ndarray)
assert ax.get_title() == expected
plt.close()
fig, ax = plt.subplots()
ctrls = iplt.plot(1, 1, E=np.array([3e7, 3e9]))
iplt.title("E={E:.2e}", controls=ctrls)
assert ax.get_title() == expected
plt.close()
"""
=====================================================
Matplotlib Sliders without a separate Controls Figure
=====================================================
Demonstration of how to provide a matplotlib slider to prevent
the creation of a separate controls figure.
"""
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.widgets import Slider
from mpl_interactions import ipyplot as iplt
fig, ax = plt.subplots()
plt.subplots_adjust(bottom=0.25)
x = np.linspace(0, 2 * np.pi, 200)
def f(x, freq):
return np.sin(x * freq)
axfreq = plt.axes([0.25, 0.1, 0.65, 0.03])
slider = Slider(axfreq, label="freq", valmin=0.05, valmax=10)
controls = iplt.plot(x, f, freq=slider, ax=ax)
plt.show()