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design2garmentcode-impl/pygarment/garmentcode/utils.py

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2025-07-03 17:03:00 +08:00
from typing import TypeVar, Generic, Sequence, Callable
import numpy as np
from numpy.linalg import norm
from scipy.spatial.transform import Rotation
import svgpathtools as svgpath
# proper inserstions by key with bicest module in python <3.10
# https://stackoverflow.com/questions/27672494/how-to-use-bisect-insort-left-with-a-key
T = TypeVar('T')
V = TypeVar('V')
class KeyWrapper(Generic[T, V]):
def __init__(self, iterable: Sequence[T], key: Callable[[T], V]):
self.it = iterable
self.key = key
def __getitem__(self, i: int) -> V:
return self.key(self.it[i])
def __len__(self) -> int:
return len(self.it)
def vector_angle(v1, v2):
"""Find an angle between two 2D vectors"""
v1, v2 = np.asarray(v1), np.asarray(v2)
cos = np.dot(v1, v2) / (norm(v1) * norm(v2))
angle = np.arccos(cos)
# Cross to indicate correct relative orienataion of v2 w.r.t. v1
cross = np.cross(v1, v2)
if abs(cross) > 1e-5:
angle *= np.sign(cross)
return angle
def R2D(angle):
"""2D rotation matrix by an angle"""
return np.array([[np.cos(angle), -np.sin(angle)], [np.sin(angle), np.cos(angle)]])
def vector_align_3D(v1, v2):
"""Find a rotation to align v1 with v2"""
v1, v2 = np.asarray(v1), np.asarray(v2)
cos = np.dot(v1, v2) / (norm(v1) * norm(v2))
cos = max(min(cos, 1), -1) # NOTE: getting rid of numbers like 1.000002 that appear due to numerical instability
angle = np.arccos(cos)
# Cross to get the axis of rotation
cross = np.cross(v1, v2)
cross = cross / norm(cross)
return Rotation.from_rotvec(cross * angle)
def close_enough(f1, f2=0, tol=1e-4):
"""Compare two floats correctly """
return abs(f1 - f2) < tol
def bbox_paths(paths):
"""Bounding box of a list of paths/Edge Sequences"""
bboxes = np.array([p.bbox() for p in paths])
return (min(bboxes[:, 0]), max(bboxes[:, 1]),
min(bboxes[:, 2]), max(bboxes[:, 3]))
def lin_interpolation(val1, val2, factor):
"""Linear interpolation between val1 and val2 with factor [0, 1]
with factor == 0, output is val1
with factor == 1, output is val2
"""
if factor < 0 or factor > 1:
raise ValueError(f'lin_interpolation::ERROR::Expected a factor \in [0, 1], got {factor}')
return (1 - factor) * val1 + factor * val2
# ---- Complex numbers converters -----
def c_to_list(num):
"""Convert complex number to a list of 2 elements
Allows processing of lists of complex numbers
"""
if isinstance(num, (list, tuple, set, np.ndarray)):
return [c_to_list(n) for n in num]
else:
return [num.real, num.imag]
def c_to_np(num):
"""Convert complex number to a numpy array of 2 elements
Allows processing of lists of complex numbers
"""
if isinstance(num, (list, tuple, set, np.ndarray)):
return np.asarray([c_to_list(n) for n in num])
else:
return np.asarray([num.real, num.imag])
def list_to_c(num):
"""Convert 2D list or list of 2D lists into complex number/list of complex
numbers"""
if isinstance(num[0], (list, tuple, set, np.ndarray)):
return [complex(n[0], n[1]) for n in num]
else:
return complex(num[0], num[1])
# ---- Nested Dictionaries shortcuts ----
# https://stackoverflow.com/a/37704379
def nested_get(dic, keys):
for key in keys:
dic = dic[key]
return dic
def nested_set(dic, keys, value):
for key in keys[:-1]:
dic = dic.setdefault(key, {})
dic[keys[-1]] = value
def nested_del(dic, keys):
for key in keys[:-1]:
dic = dic[key]
del dic[keys[-1]]
# ----- Curves -----
def curve_extreme_points(curve, on_x=False, on_y=True):
"""Return extreme points of the current edge
NOTE: this does NOT include the border vertices of an edge
"""
# Variation of https://github.com/mathandy/svgpathtools/blob/5c73056420386753890712170da602493aad1860/svgpathtools/bezier.py#L197
poly = svgpath.bezier2polynomial(curve, return_poly1d=True)
x_extremizers, y_extremizers = [], []
if on_y:
y = svgpath.imag(poly)
dy = y.deriv()
y_extremizers = svgpath.polyroots(dy, realroots=True,
condition=lambda r: 0 < r < 1)
if on_x:
x = svgpath.real(poly)
dx = x.deriv()
x_extremizers = svgpath.polyroots(dx, realroots=True,
condition=lambda r: 0 < r < 1)
all_extremizers = x_extremizers + y_extremizers
extreme_points = np.array([c_to_list(curve.point(t))
for t in all_extremizers])
return extreme_points