Circle

SUMMARY

A circle in 2D space.

from telekinesis import datatypes
circle = datatypes.Circle(center=[50.0, 60.0], radius=10.0)

API Reference

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

View Reference →

Parameters

Parameter	Type	Default	Description
center	list[float] | np.ndarray	Required	Circle center: [x, y].
radius	float	Required	Circle radius, must be >= 0.

Raises

Exception	Condition
TypeError	center can't be converted to a float32 array, or radius can't be converted to a float
ValueError	center's shape (after conversion) isn't (2,), center contains a non-finite value (NaN/Inf), radius is non-finite, or radius < 0

Attributes

Attribute	Type	Description
center	np.ndarray	Defensive copy of the circle center, shape (2,), float32.
radius	float	The circle radius.

Methods

Method	Type	Description
Circle.coerce(value)	Circle	Converts a dict with center and radius keys into a Circle. If value is already a Circle, it is returned unchanged.

Operators

Operation	Behavior
circle == other	True only if other is a Circle with an equal center (elementwise) and an equal radius. NotImplemented (so False) for any other type.
repr(circle)	Circle(center=[50. 60.], radius=10.0) — verified empirically.

Visualization

import rerun as rr

# Your code block
# ....

rr.init("circle_example", spawn=True)
datatypes.visualize(circle, entity_path="/circle", label="Circle")

Example

"""Demonstrates the Telekinesis Circle datatype."""

import time

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

from telekinesis import datatypes

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

    # ======================= Create ============================================
    circle = datatypes.Circle(center=[50.0, 60.0], radius=10.0)
    logger.info(f"Original Circle: {circle}")

    circle_from_dict = datatypes.Circle.coerce({"center": [20.0, 30.0], "radius": 5.0})
    logger.info(f"Circle coerced from dict: {circle_from_dict}")

    # ======================= Inspect ===========================================
    logger.info(f"center={circle.center}")
    logger.info(f"radius={circle.radius}")

    # ======================= Operations =========================================
    # Circle is immutable; translate and scale by constructing a new instance.
    translated_circle = datatypes.Circle(
        center=circle.center + np.array([5.0, 5.0], dtype=np.float32), radius=circle.radius
    )
    logger.info(f"Translated Circle: {translated_circle}")

    scaled_circle = datatypes.Circle(
        center=translated_circle.center, radius=translated_circle.radius * 1.5
    )
    logger.info(f"Scaled Circle: {scaled_circle}")

    # ======================= Visualize =========================================
    rr.init("circle_example", spawn=True)
    datatypes.visualize(circle, entity_path="/circle/original", label="Original Circle")
    datatypes.visualize(scaled_circle, entity_path="/circle/scaled", label="Scaled Circle")

    # ======================= Serialize / Deserialize ===========================
    start = time.perf_counter()
    serialized = datatypes.serialize(scaled_circle)
    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 Circle: {deserialized}")
    logger.info(f"Round-trip successful: {scaled_circle == deserialized}")
    logger.info(f"Serialization time: {serialization_ms:.3f} ms")
    logger.info(f"Deserialization time: {deserialization_ms:.3f} ms")


if __name__ == "__main__":
    circle_example()