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99 lines
3.0 KiB
Python
99 lines
3.0 KiB
Python
"""
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Various helper functions
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"""
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from typing import Any, Union, Tuple
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import numpy
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# Type definitions
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vector2 = Union[numpy.ndarray, Tuple[float, float]]
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def is_scalar(var: Any) -> bool:
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"""
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Alias for 'not hasattr(var, "__len__")'
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:param var: Checks if var has a length.
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"""
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return not hasattr(var, "__len__")
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def get_bit(bit_string: Any, bit_id: int) -> bool:
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"""
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Returns true iff bit number 'bit_id' from the right of 'bit_string' is 1
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:param bit_string: Bit string to test
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:param bit_id: Bit number, 0-indexed from the right (lsb)
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:return: value of the requested bit (bool)
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"""
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return bit_string & (1 << bit_id) != 0
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def set_bit(bit_string: Any, bit_id: int, value: bool) -> Any:
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"""
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Returns 'bit_string' with bit number 'bit_id' set to 'value'.
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:param bit_string: Bit string to alter
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:param bit_id: Bit number, 0-indexed from right (lsb)
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:param value: Boolean value to set bit to
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:return: Altered 'bit_string'
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"""
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mask = (1 << bit_id)
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bit_string &= ~mask
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if value:
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bit_string |= mask
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return bit_string
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def rotation_matrix_2d(theta: float) -> numpy.ndarray:
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"""
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2D rotation matrix for rotating counterclockwise around the origin.
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:param theta: Angle to rotate, in radians
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:return: rotation matrix
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"""
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return numpy.array([[numpy.cos(theta), -numpy.sin(theta)],
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[numpy.sin(theta), +numpy.cos(theta)]])
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def normalize_mirror(mirrored: Tuple[bool, bool]) -> Tuple[bool, float]:
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mirrored_x, mirrored_y = mirrored
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mirror_x = (mirrored_x != mirrored_y) #XOR
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angle = numpy.pi if mirrored_y else 0
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return mirror_x, angle
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def remove_duplicate_vertices(vertices: numpy.ndarray, closed_path: bool = True) -> numpy.ndarray:
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duplicates = (vertices == numpy.roll(vertices, 1, axis=0)).all(axis=1)
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if not closed_path:
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duplicates[0] = False
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return vertices[~duplicates]
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def remove_colinear_vertices(vertices: numpy.ndarray, closed_path: bool = True) -> numpy.ndarray:
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'''
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Given a list of vertices, remove any superflous vertices (i.e.
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those which lie along the line formed by their neighbors)
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:param vertices: Nx2 ndarray of vertices
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:param closed_path: If True, the vertices are assumed to represent an implicitly
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closed path. If False, the path is assumed to be open. Default True.
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:return:
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'''
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vertices = numpy.array(vertices)
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# Check for dx0/dy0 == dx1/dy1
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dv = numpy.roll(vertices, -1, axis=0) - vertices # [y1-y0, y2-y1, ...]
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dxdy = dv * numpy.roll(dv, 1, axis=0)[:, ::-1] #[[dx0*(dy_-1), (dx_-1)*dy0], dx1*dy0, dy1*dy0]]
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dxdy_diff = numpy.abs(numpy.diff(dxdy, axis=1))[:, 0]
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err_mult = 2 * numpy.abs(dxdy).sum(axis=1) + 1e-40
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slopes_equal = (dxdy_diff / err_mult) < 1e-15
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if not closed_path:
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slopes_equal[[0, -1]] = False
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return vertices[~slopes_equal]
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