Position3D

SUMMARY

A position in 3D space.

from telekinesis import datatypes
position = datatypes.Position3D([1.0, 2.0, 3.0])

API Reference

Complete API documentation for Position3D, including parameters, attributes, and methods.

View Reference →

Parameters

Parameter	Type	Default	Description
data	np.ndarray | list | tuple	Required	Position coordinates [x, y, z] with shape (3,).

Raises

Exception	Condition
TypeError	data can't be converted to float32 (e.g. non-numeric elements)
ValueError	data is not rank-1, or its shape isn't (3,)
ValueError	data contains a non-finite value (NaN/Inf)

Attributes

Attribute	Type	Description
data	np.ndarray	Defensive copy of the underlying (3,) float32 array. Assigning a new value re-validates it the same way as construction.
shape	tuple[int, ...]	Always (3,).
ndim	int	Always 1.
dtype	np.dtype	Always float32.
size	int	Always 3.

Methods

Method	Type	Description
Position3D.coerce(value)	Position3D	Converts array-like data into a Position3D. If value is already a Position3D, it is returned unchanged; otherwise it goes through the same checks as constructing one directly.
to_numpy(copy=True)	np.ndarray	Returns the position as a plain array. With the default copy=True you get an independent copy; pass copy=False to get a direct reference to the internal array instead, so mutating it also mutates the Position3D.
copy()	Position3D	Returns a new, independent Position3D with the same data.

Operators

Operation	Behavior
pos == other	True only if other is also a Position3D with element-equal data. False for anything else, including a Vector3D with the same values — comparison requires the exact same type.
len(pos)	Always 3.
np.asarray(pos)	Returns a copy of data as an np.ndarray; NumPy functions accept a Position3D directly.
pos + array, pos - array	Not implemented on Position3D — Python falls back to NumPy's array coercion (__array__), so e.g. pos - np.array([1.0, 1.0, 1.0]) returns a plain np.ndarray, not a Position3D.

Visualization

import rerun as rr

# Your code block
# ....

rr.init("position3d_example", spawn=True)
datatypes.visualize(position, entity_path="/position", label="Position3D")

Example

"""Demonstrates the Telekinesis Position3D datatype."""

import time

import numpy as np
import rerun as rr
from loguru import logger

from telekinesis import datatypes


def position3d_example():
    """Demonstrate creation, inspection, operations, visualization, and serialization."""

    # ======================= Create ============================================
    position3d = datatypes.Position3D([1.0, 2.0, 3.0])
    logger.info(f"Created Position3D: {position3d}")

    # ======================= Inspect ===========================================
    logger.info(f"data={position3d.data}")
    logger.info(f"shape={position3d.shape}")
    logger.info(f"ndim={position3d.ndim}")
    logger.info(f"dtype={position3d.dtype}")
    logger.info(f"size={position3d.size}")

    # ======================= Operations =========================================
    position3d.data = [4.0, 5.0, 6.0]
    logger.info(f"Updated Position3D: {position3d}")

    position3d_copy = position3d.copy()
    logger.info(f"Copied Position3D: {position3d_copy}")

    position3d_numpy = position3d.to_numpy(copy=True)
    logger.info(f"NumPy Position3D: {position3d_numpy}")

    numpy_array = np.asarray(position3d)
    logger.info(f"NumPy array: {numpy_array}")

    difference_with_numpy = position3d - np.array([1.0, 1.0, 1.0])
    logger.info(f"Difference of Position3D with NumPy array: {difference_with_numpy}")

    distance_from_origin = np.linalg.norm(position3d)
    logger.info(f"Distance from origin (np.linalg.norm): {distance_from_origin}")

    # ======================= Visualize =========================================
    rr.init("position3d_example", spawn=True)
    datatypes.visualize(position3d, entity_path="/position3d", label="Updated Position3D")

    # ======================= Serialize / Deserialize ===========================
    start = time.perf_counter()
    serialized = datatypes.serialize(position3d)
    serialization_ms = (time.perf_counter() - start) * 1000

    start = time.perf_counter()
    deserialized = datatypes.deserialize(serialized)["param_0"]
    deserialization_ms = (time.perf_counter() - start) * 1000

    logger.info(f"Deserialized Position3D: {deserialized}")
    logger.info(f"Round-trip successful: {position3d == deserialized}")
    logger.info(f"Serialization time: {serialization_ms:.3f} ms")
    logger.info(f"Deserialization time: {deserialization_ms:.3f} ms")


if __name__ == "__main__":
    position3d_example()