GRID Docs | General Robotics

from grid_types import PointCloud

A class to represent a point cloud.

Fields

np.ndarray

Array of points with shape (N, D) where N is the number of points and D is the dimensionality of each point (e.g., D=3 for x,y,z). Each row is a point, and each column is a dimension/feature.

List[str]

List of field names for the point cloud data. The order of field names must correspond to the columns in the points array. If not provided, defaults to [‘x’, ‘y’] for 2D points (N,2) or [‘x’, ‘y’, ‘z’] for 3D points (N,3). For other dimensions, fields must be explicitly provided.

Constructor

Signature

PointCloud(points: np.ndarray, fields: Optional[List[str]] = None)

Methods

`from_dict()`

Signature

from_dict(data: dict) -> PointCloud

Deserialize from dictionary

`to_dict()`

Signature

to_dict() -> dict

Serialize to dictionary for JSON transfer

Example

import numpy as np
# 3D points with x, y, z
points_data_3d = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.float32)
pc1 = PointCloud(points=points_data_3d)
print(pc1.points)
print(pc1.fields)
# 2D points with x, y
points_data_2d = np.array([[1, 2], [3, 4]], dtype=np.float32)
pc2 = PointCloud(points=points_data_2d)
print(pc2.fields)
# 3D points with custom fields (e.g., x, y, intensity)
points_data_custom = np.array([[10, 20, 100], [30, 40, 150]], dtype=np.float32)
pc3 = PointCloud(points=points_data_custom, fields=['x', 'y', 'intensity'])
print(pc3.fields)
# Points with x, y, z, r, g, b
points_rgb = np.array([[1,2,3, 255,0,0], [4,5,6, 0,255,0]], dtype=np.float32)
fields_rgb = ['x', 'y', 'z', 'r', 'g', 'b']
pc4 = PointCloud(points=points_rgb, fields=fields_rgb)
print(pc4.points.shape)
print(pc4.fields)

​Fields

​Constructor

​Methods

​from_dict()

​to_dict()

​Example

Fields

Constructor

Methods

`from_dict()`

`to_dict()`

Example