diff options
Diffstat (limited to 'utils.py')
-rw-r--r-- | utils.py | 58 |
1 files changed, 57 insertions, 1 deletions
@@ -1,8 +1,64 @@ from collections import deque from collections.abc import Iterable, Iterator, Generator +from dataclasses import dataclass from itertools import islice +from math import sqrt from sys import argv -from typing import TypeVar +from typing import TypeVar, Generic, Union, Optional, cast + +Numeric = Union[int, float] + +T = TypeVar('T', bound=Numeric) +@dataclass(frozen=True) +class Point2D(Generic[T]): + x: T + y: T + + def __str__(self) -> str: + return f'({self.x}, {self.y})' + + def __add__(self, other: 'Point2D') -> Union['Point2D', bool]: + if isinstance(other, Point2D): + return Point2D(self.x + other.x, self.y + other.y) + return NotImplemented + + def __sub__(self, other: 'Point2D') -> Union['Point2D', bool]: + if isinstance(other, Point2D): + return Point2D(self.x - other.x, self.y - other.y) + return NotImplemented + + def __abs__(self) -> 'Point2D': + return Point2D(abs(self.x), abs(self.y)) + +T = TypeVar('T', bound=Numeric) +def norm_1(p: Point2D[T]) -> T: + return abs(p.x) + abs(p.y) + +def norm_2(p: Point2D) -> float: + return sqrt(p.x ** 2 + p.y ** 2) + +T = TypeVar('T', bound=Numeric) +def norm_inf(p: Point2D[T]) -> T: + return max(abs(p.x), abs(p.y)) + +T = TypeVar('T', bound=Numeric) +def inbounds(p: Point2D[T], a: Point2D[T], b: Optional[Point2D[T]] = None) -> bool: + if b is None and isinstance(a.x, int): + b = a + a = cast(Point2D[T], Point2D(0, 0)) + return p.x >= a.x and p.y >= a.y and p.x < b.x and p.y < b.y + +def adjacent(p: Point2D[int], diagonal: bool = True) \ + -> Generator[Point2D[int], None, None]: + for dx in range(-1, 2): + for dy in range(-1, 2): + if dx == 0 and dy == 0: continue + if dx != 0 and dy != 0 and not adjacent: continue + yield Point2D(p.x + dx, p.y + dy) + +def adjacent_bounded(p: Point2D[int], bound: Point2D[int], diagonal: bool = True) \ + -> filter[Point2D[int]]: # This has to return filter[...] not Generator[...] because ??? + return filter(lambda p: inbounds(p, bound), adjacent(p, diagonal)) T = TypeVar('T') def sliding_window(iterable: Iterable[T], n: int) -> Generator[tuple[T, ...], None, None]: |