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I wrote this Python vector class a while ago for this blog post: http://slowchop.com/2006/07/15/a-fast-python-vector-class/
from random import randint, random
import math
class Pos(object):
__slots__ = ('x', 'y')
def __init__(self, x=0.0, y=0.0):
self.x = x
self.y = y
def __str__(self):
return '(%.1f,%.1f)' % (self.x, self.y)
def __repr__(self):
return str(self)
def __eq__(self, o):
return self.x == o.x and self.y == o.y
def __cmp__(self, o):
return self.__eq__(o)
def __ne__(self, o):
return not self.__eq__(o)
def __hash__(self):
return self.x + self.y * 10000
def __lt__(self, o):
if self.x < o.x:
return True
if self.y < o.y:
return True
def __add__(self, o):
return Pos(self.x + o.x, self.y + o.y)
def __sub__(self, o):
return Pos(self.x - o.x, self.y - o.y)
def __div__(self, o):
return Pos(self.x / o, self.y / o)
def __mul__(self, o):
return Pos(self.x * o, self.y * o)
def __neg__(self):
return Pos(-self.x, -self.y)
# def __getitem__(self, a):
# if not a: return self.x
# return self.y
# def __setitem__(self, a, v):
# if a == 0: self.x = v
# if a == 1: self.y = v
def length(self):
return math.hypot(self.x, self.y)
def normalise(self):
length = math.hypot(self.x, self.y)
self.x = self.x / length
self.y = self.y / length
@staticmethod
def random(xrange,yrange):
return Pos(randint(xrange[0], xrange[1]), randint(yrange[0], yrange[1]))
@staticmethod
def random_range(center, max_radius):
a = random() * math.pi * 2
r = random() * max_radius
return Pos(center.x + math.cos(a) * r, center.y + math.sin(a) * r)
@staticmethod
def list(l):
return Pos(l[0], l[1])
def to_list(self):
return [self.x, self.y]
if __name__ == '__main__':
import timeit
t = timeit.Timer('b = a.y', 'from pos import Pos\na = Pos(5.3, 6.2)')
print min(t.repeat(5, 1000000))
# getitem is 10 times slower then attribute access!
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