from collections import namedtuple
from math import cos, sin, tau
import math
import numpy as np
import rerun as rr
rr.init("cube")
By default, Rerun will use a copy of the viewer hosted at https://app.rerun.io. This is generally preferable as it will work more seamlessly even if you are connected to a notebook instance on a remote machine. However there are some cases where this won't work such as running from source, or using your notebook in an offline environment.
In these cases you can start a local viewer server by uncommenting the following line:
# rr.start_web_viewer_server()
This is the same as the color cube demo from rerun -m rerun_demo, but the code
is repeated here for context.
ColorGrid = namedtuple("ColorGrid", ["positions", "colors"])
def build_color_grid(x_count=10, y_count=10, z_count=10, twist=0):
"""
Create a cube of points with colors.
The total point cloud will have x_count * y_count * z_count points.
Parameters
----------
x_count, y_count, z_count:
Number of points in each dimension.
twist:
Angle to twist from bottom to top of the cube
"""
grid = np.mgrid[
slice(-10, 10, x_count * 1j),
slice(-10, 10, y_count * 1j),
slice(-10, 10, z_count * 1j),
]
angle = np.linspace(-float(twist) / 2, float(twist) / 2, z_count)
for z in range(z_count):
xv, yv, zv = grid[:, :, :, z]
rot_xv = xv * cos(angle[z]) - yv * sin(angle[z])
rot_yv = xv * sin(angle[z]) + yv * cos(angle[z])
grid[:, :, :, z] = [rot_xv, rot_yv, zv]
positions = np.vstack([xyz.ravel() for xyz in grid])
colors = np.vstack(
[
xyz.ravel()
for xyz in np.mgrid[
slice(0, 255, x_count * 1j),
slice(0, 255, y_count * 1j),
slice(0, 255, z_count * 1j),
]
]
)
return ColorGrid(positions.T, colors.T.astype(np.uint8))
To start a new recording all you need to do is call rr.memory_recording().
rec = rr.memory_recording()
At any point you can show this recording by returning it as the last item in the cell. In this case the recording simply does not have any data in it yet.
rec
Timed out waiting for https://app.rerun.io/commit/625d2bd to load.
Consider using rr.self_host_assets()
Now we can create some data and add it to the recording before we show it again.
STEPS = 100
twists = math.pi * np.sin(np.linspace(0, math.tau, STEPS)) / 4
for t in range(STEPS):
rr.set_time_sequence("step", t)
cube = build_color_grid(10, 10, 10, twist=twists[t])
rr.log_points("cube", positions=cube.positions, colors=cube.colors, radii=0.5)
rec
Timed out waiting for https://app.rerun.io/commit/625d2bd to load.
Consider using rr.self_host_assets()
The recording also as a show method that lets you adjust properties such as width and height.
In the future this will support additional blueprint and layout options.
rec.show(width=400, height=400)
Timed out waiting for https://app.rerun.io/commit/625d2bd to load.
Consider using rr.self_host_assets()
You can always start another recording by calling rr.memory_recording() again.
rec2 = rr.memory_recording()
STEPS = 1
twists = math.pi * np.sin(np.linspace(0, math.tau, STEPS)) / 4
for t in range(STEPS):
rr.set_time_sequence("step", t)
cube = build_color_grid(50, 50, 50, twist=twists[t])
rr.log_points("cube", positions=cube.positions, colors=cube.colors, radii=0.5)
rec2
Timed out waiting for https://app.rerun.io/commit/625d2bd to load.
Consider using rr.self_host_assets()