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Note: you may need to restart the kernel to use updated packages.
from ipywidgets import interact, IntSlider
from IPython.display import Markdown, display
from tqdm.notebook import trange, tqdm
from time import sleep
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from ipywidgets import interact, interactive
from IPython.display import clear_output, display, HTML
import numpy as np
from scipy import integrate
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.colors import cnames
from matplotlib import animation# borrowed from https://jupyterlite.readthedocs.io/en/latest/_static/lab/index.html
slider = IntSlider()
@interact(cookies=slider)
def cookies(cookies=slider.value, calories=(0, 150)):
total_calories = calories * cookies
if cookies:
display(
Markdown(
f"If each cookie contains _{calories} calories_, _{cookies} cookies_ contain **{total_calories} calories**!"
)
)
else:
display(Markdown(f"No cookies!"))
if total_calories > 2000:
display(Markdown(f"> Maybe that's too many cookies..."))Loading...
for i in trange(2, desc='1st loop'):
for j in tqdm(range(100), desc='2nd loop'):
sleep(0.01)Loading...
def solve_lorenz(
N=10, angle=0.0, max_time=4.0,
sigma=10.0, beta=8./3, rho=28.0):
fig = plt.figure()
ax = fig.add_axes([0, 0, 1, 1], projection='3d')
ax.axis('off')
# prepare the axes limits
ax.set_xlim((-25, 25))
ax.set_ylim((-35, 35))
ax.set_zlim((5, 55))
def lorenz_deriv(x_y_z, t0, sigma=sigma, beta=beta, rho=rho):
"""Compute the time-derivative of a Lorenz system."""
x, y, z = x_y_z
return [sigma * (y - x), x * (rho - z) - y, x * y - beta * z]
# Choose random starting points, uniformly distributed from -15 to 15
np.random.seed(1)
x0 = -15 + 30 * np.random.random((N, 3))
# Solve for the trajectories
t = np.linspace(0, max_time, int(250*max_time))
x_t = np.asarray([integrate.odeint(lorenz_deriv, x0i, t)
for x0i in x0])
# choose a different color for each trajectory
colors = plt.cm.viridis(np.linspace(0, 1, N))
for i in range(N):
x, y, z = x_t[i,:,:].T
lines = ax.plot(x, y, z, '-', c=colors[i])
plt.setp(lines, linewidth=2)
ax.view_init(30, angle)
plt.show()
return t, x_t
w = interactive(solve_lorenz, angle=(0.,360.), max_time=(0.1, 4.0),
N=(0,50), sigma=(0.0,50.0), rho=(0.0,50.0))
display(w)Loading...