def covariance(self, other):
try:
return mean(
math2.vecmul(math2.vecsub(self, [], self.mean),
math2.vecsub(other, [], other.mean)))
except:
return 0 # consider decorrelated
def box_size(self):
""":return: (x,y) size"""
min, max = self.box()
try:
min[0], max[0] # at least one dimension ?
return tuple(math2.vecsub(max, min))
except:
return (0, 0)
def box_size(self):
""":return: (x,y) size"""
a, b = self.box()
try:
a[0], b[0] # at least one dimension ?
return tuple(math2.vecsub(b, a))
except:
return (0, 0)
def __sub__(self,other):
from .image import Image
if isinstance(other, Image):
mode=other.mode
return Image(size=other.size,color=self.convert(mode),mode=mode)-other
if not isinstance(other, Color):
other=Color(other)
return Color(math2.vecsub(self.rgb,other.rgb)) #TODO: change to other space one day
