| import numpy as np | |
| # Defined because pre-commit is inserting an unacceptable line-break | |
| # between the "1" (or "2") and the "/ 3" | |
| one_third = 1 / 3 | |
| two_thirds = 2 / 3 | |
| # Expected values for matrices in split_bezier | |
| SPLIT_MATRICES = { | |
| # For 0-degree Béziers | |
| 0: { | |
| 0: np.array([[1], [1]]), | |
| one_third: np.array([[1], [1]]), | |
| two_thirds: np.array([[1], [1]]), | |
| 1: np.array([[1], [1]]), | |
| }, | |
| # For linear Béziers | |
| 1: { | |
| 0: np.array( | |
| [ | |
| [1, 0], | |
| [1, 0], | |
| [1, 0], | |
| [0, 1], | |
| ] | |
| ), | |
| one_third: np.array( | |
| [ | |
| [3, 0], | |
| [2, 1], | |
| [2, 1], | |
| [0, 3], | |
| ] | |
| ) | |
| / 3, | |
| two_thirds: np.array( | |
| [ | |
| [3, 0], | |
| [1, 2], | |
| [1, 2], | |
| [0, 3], | |
| ] | |
| ) | |
| / 3, | |
| 1: np.array( | |
| [ | |
| [1, 0], | |
| [0, 1], | |
| [0, 1], | |
| [0, 1], | |
| ] | |
| ), | |
| }, | |
| # For quadratic Béziers | |
| 2: { | |
| 0: np.array( | |
| [ | |
| [1, 0, 0], | |
| [1, 0, 0], | |
| [1, 0, 0], | |
| [1, 0, 0], | |
| [0, 1, 0], | |
| [0, 0, 1], | |
| ] | |
| ), | |
| one_third: np.array( | |
| [ | |
| [9, 0, 0], | |
| [6, 3, 0], | |
| [4, 4, 1], | |
| [4, 4, 1], | |
| [0, 6, 3], | |
| [0, 0, 9], | |
| ] | |
| ) | |
| / 9, | |
| two_thirds: np.array( | |
| [ | |
| [9, 0, 0], | |
| [3, 6, 0], | |
| [1, 4, 4], | |
| [1, 4, 4], | |
| [0, 3, 6], | |
| [0, 0, 9], | |
| ] | |
| ) | |
| / 9, | |
| 1: np.array( | |
| [ | |
| [1, 0, 0], | |
| [0, 1, 0], | |
| [0, 0, 1], | |
| [0, 0, 1], | |
| [0, 0, 1], | |
| [0, 0, 1], | |
| ] | |
| ), | |
| }, | |
| # For cubic Béziers | |
| 3: { | |
| 0: np.array( | |
| [ | |
| [1, 0, 0, 0], | |
| [1, 0, 0, 0], | |
| [1, 0, 0, 0], | |
| [1, 0, 0, 0], | |
| [1, 0, 0, 0], | |
| [0, 1, 0, 0], | |
| [0, 0, 1, 0], | |
| [0, 0, 0, 1], | |
| ] | |
| ), | |
| one_third: np.array( | |
| [ | |
| [27, 0, 0, 0], | |
| [18, 9, 0, 0], | |
| [12, 12, 3, 0], | |
| [8, 12, 6, 1], | |
| [8, 12, 6, 1], | |
| [0, 12, 12, 3], | |
| [0, 0, 18, 9], | |
| [0, 0, 0, 27], | |
| ] | |
| ) | |
| / 27, | |
| two_thirds: np.array( | |
| [ | |
| [27, 0, 0, 0], | |
| [9, 18, 0, 0], | |
| [3, 12, 12, 0], | |
| [1, 6, 12, 8], | |
| [1, 6, 12, 8], | |
| [0, 3, 12, 12], | |
| [0, 0, 9, 18], | |
| [0, 0, 0, 27], | |
| ] | |
| ) | |
| / 27, | |
| 1: np.array( | |
| [ | |
| [1, 0, 0, 0], | |
| [0, 1, 0, 0], | |
| [0, 0, 1, 0], | |
| [0, 0, 0, 1], | |
| [0, 0, 0, 1], | |
| [0, 0, 0, 1], | |
| [0, 0, 0, 1], | |
| [0, 0, 0, 1], | |
| ] | |
| ), | |
| }, | |
| # Test case with a quartic Bézier | |
| # to check if the fallback algorithms work | |
| 4: { | |
| 0: np.array( | |
| [ | |
| [1, 0, 0, 0, 0], | |
| [1, 0, 0, 0, 0], | |
| [1, 0, 0, 0, 0], | |
| [1, 0, 0, 0, 0], | |
| [1, 0, 0, 0, 0], | |
| [1, 0, 0, 0, 0], | |
| [0, 1, 0, 0, 0], | |
| [0, 0, 1, 0, 0], | |
| [0, 0, 0, 1, 0], | |
| [0, 0, 0, 0, 1], | |
| ] | |
| ), | |
| one_third: np.array( | |
| [ | |
| [81, 0, 0, 0, 0], | |
| [54, 27, 0, 0, 0], | |
| [36, 36, 9, 0, 0], | |
| [24, 36, 18, 3, 0], | |
| [16, 32, 24, 8, 1], | |
| [16, 32, 24, 8, 1], | |
| [0, 24, 36, 18, 3], | |
| [0, 0, 36, 36, 9], | |
| [0, 0, 0, 54, 27], | |
| [0, 0, 0, 0, 81], | |
| ] | |
| ) | |
| / 81, | |
| two_thirds: np.array( | |
| [ | |
| [81, 0, 0, 0, 0], | |
| [27, 54, 0, 0, 0], | |
| [9, 36, 36, 0, 0], | |
| [3, 18, 36, 24, 0], | |
| [1, 8, 24, 32, 16], | |
| [1, 8, 24, 32, 16], | |
| [0, 3, 18, 36, 24], | |
| [0, 0, 9, 36, 36], | |
| [0, 0, 0, 27, 54], | |
| [0, 0, 0, 0, 81], | |
| ] | |
| ) | |
| / 81, | |
| 1: np.array( | |
| [ | |
| [1, 0, 0, 0, 0], | |
| [0, 1, 0, 0, 0], | |
| [0, 0, 1, 0, 0], | |
| [0, 0, 0, 1, 0], | |
| [0, 0, 0, 0, 1], | |
| [0, 0, 0, 0, 1], | |
| [0, 0, 0, 0, 1], | |
| [0, 0, 0, 0, 1], | |
| [0, 0, 0, 0, 1], | |
| [0, 0, 0, 0, 1], | |
| ] | |
| ), | |
| }, | |
| } | |