sixth commit: test added

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Tia Lechner committed 2026-10-27 12:13:33 +01:00
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from .compute import matmul, transpose, rot_2D, rot_3D from .compute import matmul, transpose, rot_2D, rot_3D, project_ortho, project_perspective
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@@ -142,6 +142,26 @@ def rot_3D(angle: float, axis: str) -> list[list[float]]:
[0, 0, 1], [0, 0, 1],
] ]
def project_ortho(point: tuple[float, float, float], scale: float = 1) -> tuple[float, float]:
"""Project a 3D point onto a 2D plane using orthogonal projection."""
x, y, _z = point
return (x * scale, y * scale)
def project_perspective(point: tuple[float, float, float],
focal_length: float = 1.0,
scale: float = 1.0,
camera_distance: float = 4.0) -> tuple[float, float]:
"""Project a 3D point onto a 2D plane using perspective projection."""
x, y ,z = point
factor = focal_length / (z+camera_distance)
x_2d = x * factor * scale
y_2d = y * factor * scale
return (x_2d, y_2d)
if __name__ == "__main__": if __name__ == "__main__":
@@ -0,0 +1,48 @@
import math
import pytest
from matrixmania import project_perspective
def approx_equal(a: float, b: float, rel_tol: float = 1e-9) -> bool:
"""Utility to compare two floats with a relative tolerance."""
return math.isclose(a, b, rel_tol=rel_tol)
@pytest.mark.parametrize(
"point,focal_length,scale,expected",
[
# Case 1 – no scaling, unit focal length
(
(1.0, 2.0, 3.0),
1.0, # focal_length
1.0, # scale
(
1.0 / (4.0 + 3.0), # x projected
2.0 / (4.0 + 3.0), # y projected
),
),
# Case 2 – scale 100, focal length 2
(
(1.0, 2.0, 3.0),
2.0, # focal_length
100.0, # scale
(
2.0 * 100.0 / (4.0 + 3.0), # x projected
2.0 * 100.0 * 2.0 / (4.0 + 3.0), # y projected
),
),
],
)
def test_project_perspective(point, focal_length, scale, expected):
"""Test that project_perspective returns the correct 2‑D projection."""
# Call the function under test
result = project_perspective(point, focal_length=focal_length, scale=scale)
# Basic sanity checks
assert isinstance(result, tuple), "Result should be a tuple"
assert len(result) == 2, "Result should contain two coordinates"
# Confirm values are close to expected (within tiny tolerance)
assert approx_equal(result[0], expected[0]), f"X coordinate mismatch: {result[0]} != {expected[0]}"
assert approx_equal(result[1], expected[1]), f"Y coordinate mismatch: {result[1]} != {expected[1]}"
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from matrixmania import project_ortho
def test_projection_point():
#Arrange
point = (1.0, 2.0, 3.0)
expected_value = (1.0, 2.0)
#Act
result = project_ortho(point)
#Assert
assert result == expected_value
def test_projection_scale():
point = (1.0, 2.0, 3.0)
scale = 100
expected_value = (100.0, 200.0)
result = project_ortho(point, scale)
assert result == expected_value