All (or most of) the changes in scatter and quiver plots are (linearly) interpolated. On top top that, scatter plots and quiver plots can take a sequence of arrays (the first dimension), where only one array is visualized. Together this can make smooth animations with coarse timesteps. Lets see an example.
import ipyvolume as ipv import numpy as np
# only x is a sequence of arrays x = np.array([[-1, -0.8], [1, -0.1], [0., 0.5]]) y = np.array([0.0, 0.0]) z = np.array([0.0, 0.0]) ipv.figure() s = ipv.scatter(x, y, z, marker='sphere', size=10) ipv.xyzlim(-1, 1) ipv.animation_control(s) # shows controls for animation controls ipv.show()
You can control which array to visualize, using the
scatter.sequence_index property. Actually, the
pylab.animate_glyphs is connecting the
Play button to that property, but you can also set it from Python.
s.sequence_index = 1
Animating color and size¶
We now demonstrate that you can also animate color and size
# create 2d grids: x, y, and r u = np.linspace(-10, 10, 25) x, y = np.meshgrid(u, u) r = np.sqrt(x**2+y**2) print("x,y and z are of shape", x.shape) # and turn them into 1d x = x.flatten() y = y.flatten() r = r.flatten() print("and flattened of shape", x.shape)
x,y and z are of shape (25, 25) and flattened of shape (625,)
Now we only animate the z component
# create a sequence of 15 time elements time = np.linspace(0, np.pi*2, 15) z = np.array([(np.cos(r + t) * np.exp(-r/5)) for t in time]) print("z is of shape", z.shape)
z is of shape (15, 625)
# draw the scatter plot, and add controls with animate_glyphs ipv.figure() s = ipv.scatter(x, z, y, marker="sphere") ipv.animation_control(s, interval=200) ipv.ylim(-3,3) ipv.show()
# Now also include, color, which containts rgb values color = np.array([[np.cos(r + t), 1-np.abs(z[i]), 0.1+z[i]*0] for i, t in enumerate(time)]) size = (z+1) print("color is of shape", color.shape)
color is of shape (15, 3, 625)
color is of the wrong shape, the last dimension should contain the rgb value, i.e. the shape of should be (15, 2500, 3)
color = np.transpose(color, (0, 2, 1)) # flip the last axes
ipv.figure() s = ipv.scatter(x, z, y, color=color, size=size, marker="sphere") ipv.animation_control(s, interval=200) ipv.ylim(-3,3) ipv.show()
Creating movie files¶
We now make a movie, with a 2 second duration, where we rotate the camera, and change the size of the scatter points.
# This is commented out, otherwise it would run on readthedocs # def set_view(figure, framenr, fraction): # ipv.view(fraction*360, (fraction - 0.5) * 180, distance=2 + fraction*2) # s.size = size * (2+0.5*np.sin(fraction * 6 * np.pi)) # ipv.movie('wave.gif', set_view, fps=20, frames=40)
Resulting gif file¶
Not only scatter plots can be animated, quiver as well, so the direction vector (vx, vy, vz) can also be animated, as shown in the example below, which is a (subsample of) a simulation of a small galaxy orbiting a host galaxy (not visible).
import ipyvolume.datasets stream = ipyvolume.datasets.animated_stream.fetch() print("shape of steam data", stream.data.shape) # first dimension contains x, y, z, vx, vy, vz, then time, then particle
Downloading https://github.com/maartenbreddels/ipyvolume/raw/master/datasets/stream-animation.npy.bz2 to /home/docs/.ipyvolume/datasets/stream-animation.npy.bz2 shape of steam data (6, 200, 1250)
fig = ipv.figure() # instead of doing x=stream.data, y=stream.data, ... vz=stream.data, use *stream.data # limit to 50 timesteps to avoid having a huge notebook q = ipv.quiver(*stream.data[:,0:50,:200], color="red", size=7) ipv.style.use("dark") # looks better ipv.animation_control(q, interval=200) ipv.show()
# fig.animation = 0 # set to 0 for no interpolation