raycast2D 0.1.0

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raycast2D

raycast2D is a fast, single-core 2D raycasting implementation written in C with a small Python API. It operates on NumPy occupancy grids / binary images (free cells are non-zero; occupied cells are 0) and computes ray intersections using Bresenham line algorithm.

The core package depends only on numpy. Optional extras are provided for the interactive demo and development.

Installation

$ pip install raycast2D

Performance

The benchmark script in test/benchmark.py runs a small set of examples and prints throughput in rays/s. Example results (tested on an i7-9700k):

Map size	Ray length	Rays per call	Mean time (ms)	Throughput (rays/s)
512×512	2000px	5000	0.2904	17,216,880
4096×4096	2000px	5000	1.7626	2,836,661
8192×8192	2000px	5000	7.3452	680,719

To reproduce on your machine:

$ python3 test/benchmark.py

Usage

Basic raycast on an image

import numpy as np
from raycast2D import cast
from PIL import Image
import matplotlib.pyplot as plt

img = Image.open("media/lab_intel.png")
img_array = np.array(img)
img_array = img_array[:, :, 0].astype(np.uint8)  # Use single channel
# img_array = img_array[img_array < 100] = 0  # threshold if needed

rays = cast(img_array, pose=(250, 250), num_rays=360, ray_length=500)
# rays is an array of shape (N, 2) where each row contains the (x, y) coordinates of the ray collisions

plt.imshow(img_array, cmap='gray')
plt.scatter([250], [250], c='green', s=10)
plt.scatter(rays[:, 0], rays[:, 1], c='blue', s=1)
for ray in rays:
    plt.plot([250, ray[0]], [250, ray[1]], c='red', linewidth=0.5, alpha=0.3)
plt.show()

Interactive demo

The repository includes an interactive pygame demo that raycasts from the current mouse position.

pip install "raycast2D[extra]"
python3 test/demo.py

Testing and development

Install the test/development dependencies:

pip install "raycast2D[test]"

Run the test suite with:

pytest

License

GPL-3.0-only. See LICENSE.