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Description:

animatearrays 0.0.1

animate_arrays

This module wraps some setup scripts and functions to make Matplotlib’s
animations a little simpler to interface with. The starting point here
becomes creating data with
Install
pip install animate_arrays

How to use 2D arrays
Import libraries
The animate_arrays functions work in Jupyter notebooks. You’ll need to
import some of the libraries to build some arrays, plots, and animations
as such,
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation
from IPython.display import HTML

I prefer to use the
fivethirtyeight
style sheet, but you can use any style.
plt.style.use('fivethirtyeight')

Then, import the
animate_lines
function from the animate_arrays.animate module.
from animate_arrays.animate import animate_lines

Build arrays and watch them move
With the libraries imported, I build 2 arrays, X and Y where each
column is ×3 (x, y) coordinates that define two rotating arms.

Arm 1 rotates once around the origin
Arm 2 is connected to arm 1 and rotates twice

a = np.linspace(0, 2*np.pi, 100)

x1 = np.cos(a)
y1 = np.sin(a)

x2 = np.cos(2*a)
y2 = np.sin(2*a)
X = np.array([np.zeros(len(a)), x1, x1+x2])
Y = np.array([np.zeros(len(a)), y1, y1+y2])

a = animate_lines(X, Y)
HTML(a.to_html5_video())

Your browser does not support the video tag.

The animation does not have equal axes, so the arms appear to be
changing lengths as the rotations occur.
The setup_fig_function option allows you to define a custom plot
setup. Here, I name it fig_setup
def fig_setup():
fig, ax = plt.subplots()

ax.plot(X[2, :], Y[2, :], '--')
ax.axis('equal')
return fig, ax

The setup_fig_function should not take any arguments. I used it to set
up 2 new display additions, 1. plot the path of arm 2’s end so we can
see where its been and where its going on the dashed line 2. equal axes
with ax.axis('equal')
Below, I try running the function and looking at the resulting static
figure for the animation
fig, ax = fig_setup()

a = animate_lines(X, Y, setup_fig_function= fig_setup)

HTML(a.to_html5_video())

Your browser does not support the video tag.

How to use 3D arrays
In the first example, we used a 2D array where each column defined the
line for a point in time. The
animate_lines
function can also plot multiple lines in each frame. Here, we’ll add
another set of rotating arms.
a = np.linspace(0, 2*np.pi, 100)

x1 = np.cos(a)
y1 = np.sin(a)

x2 = np.cos(2*a)
y2 = np.sin(2*a)

x3 = np.cos(2*a)
y3 = np.sin(2*a)

x4 = np.cos(3*a)
y4 = np.sin(3*a)

X = np.zeros((3, 2, len(a)))
Y = np.zeros((3, 2, len(a)))

X[:, 0, :] = np.array([np.zeros(len(a)), x1, x1+x2])
X[:, 1, :] = np.array([np.zeros(len(a)), x3, x3+x4])

Y[:, 0, :] = np.array([np.zeros(len(a)), y1, y1+y2])
Y[:, 1, :] = np.array([np.zeros(len(a)), y3, y3+y4])

def fig_setup():
fig, ax = plt.subplots()

ax.plot(X[2, 0, :], Y[2, 0, :], '--')
ax.plot(X[2, 1, :], Y[2, 1, :], '--')
ax.axis('equal')
return fig, ax

fig_setup()

(<Figure size 640x480 with 1 Axes>, <AxesSubplot: >)

a2 = animate_lines(X, Y, setup_fig_function=fig_setup)
HTML(a2.to_html5_video())

Your browser does not support the video tag.