In [1]:
%matplotlib inline
from matplotlib.collections import LineCollection
import matplotlib.pyplot as plt
from scipy import interpolate
import numpy as np
from numpy.random import rand
from ipywidgets import FloatSlider, interactive, IntSlider
In [2]:
def simple_example(amplitude=2.0, phase=0.0):
plt.rcParams['figure.figsize'] = 8,6
plt.figure()
x = np.linspace(-2*np.pi, 2*np.pi, 1000)
y = amplitude * np.sin(x + phase)
plt.plot(x, y)
plt.xlim(-3, 3)
plt.ylim(-2*np.pi, 2*np.pi)
return
In [3]:
amplitude_slider = FloatSlider(value=2.0, min=0, max=3.0, step=.05)
phase_slider = FloatSlider(value=0.0, min=-np.pi, max=np.pi, step=.05)
interactive(simple_example,
amplitude=amplitude_slider,
phase=phase_slider
)
In [4]:
def spline_demo(num=14, smooth=0, seed=10, brush_strokes=30, alpha=0.5):
a = np.random.RandomState(seed=seed)
x = a.rand(num)
y = a.rand(num)
t = np.arange(0, 1.1, .1)
plt.rcParams['figure.figsize'] = 8,8
plt.figure()
for _ in range(brush_strokes):
tck, u = interpolate.splprep([x+a.rand(num)/10.0,y+a.rand(num)/10.0], s=smooth)
unew = np.arange(0, 1.01, 0.001)
out = interpolate.splev(unew, tck)
plt.plot(out[0], out[1], alpha=alpha, c='black', linewidth=3.0)
plt.xlim(-1.5, 2.5)
plt.ylim(-1.5, 2.5)
plt.axis('off')
smooth_slider = FloatSlider(value=0, min=0, max=20.0, step=.1)
num_points_slider = IntSlider(value=8, min=4, max=20)
seed_slider = IntSlider(value=4, min=4, max=20)
brush_slider = IntSlider(value=1, min=1, max=20)
alpha_slider = FloatSlider(value=.5, min=0, max=1.0, step=.05)
w=interactive(spline_demo,
smooth=smooth_slider,
num=num_points_slider,
seed=seed_slider,
brush_strokes=brush_slider,
alpha=alpha_slider)
w
In [ ]:
In [ ]: