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#encoding=utf-8
import numpy as np
N1 = 'n1'
N2 = 'n2'
N4 = 'n4'
N8 = 'n8'
def _in_image(c, w, h):
cx, cy = c
return cx >=0 and cx < w and cy >= 0 and cy < h
def n1(x, y, w, h):
"""down and right"""
neighbours = []
candidates = [(x, y + 1), (x + 1, y)];
for c in candidates:
if _in_image(c, w, h):
neighbours.append(c)
return neighbours
def n2(x, y, w, h):
neighbours = []
candidates = [(x, y + 1), (x + 1, y), (x + 1, y + 1), (x - 1, y + 1)];
for c in candidates:
if _in_image(c, w, h):
neighbours.append(c)
return neighbours;
def n4(x, y, w, h):
neighbours = []
candidates = [(x, y - 1),(x, y + 1), (x + 1, y), (x - 1, y)];
for c in candidates:
if _in_image(c, w, h):
neighbours.append(c)
return neighbours
def n8(x, y, w, h):
neighbours = []
candidates = [(x + 1, y - 1),(x, y - 1),(x - 1, y - 1), (x - 1, y),(x, y + 1), (x + 1, y), (x + 1, y + 1), (x - 1, y + 1)];
for c in candidates:
if _in_image(c, w, h):
neighbours.append(c)
return neighbours;
def n1_count(w, h):
return 2 * w * h - w - h
def n2_count(w, h):
return 4 * w * h - 3 * w - 3 * h + 2
_dict1 = {N1:n1, N2:n2, N4:n4, N8:n8};
_dict2 = {N1:n1_count, N2:n2_count};
def get_neighbours(x, y, w, h, neighbour_type):
if neighbour_type in _dict1:
fn = _dict1[neighbour_type]
return fn(x, y, w, h)
raise NotImplementedError("unknown neighbour type '%s'" % (neighbour_type))
def count_neighbours(w, h, neighbour_type):
if neighbour_type in _dict2:
fn = _dict2[neighbour_type]
return fn(w, h)
raise NotImplementedError("unknown neighbour type '%s'" % (neighbour_type))
if __name__ == "__main__":
w, h = 10, 10
np.testing.assert_equal(len(n4(0, 0, w, h)), 2)
np.testing.assert_equal(len(n8(0, 0, w, h)), 3)
np.testing.assert_equal(len(n4(0, 2, w, h)), 3)
np.testing.assert_equal(len(n8(0, 2, w, h)), 5)
np.testing.assert_equal(len(n4(3, 3, w, h)), 4)
np.testing.assert_equal(len(n8(3, 3, w, h)), 8)
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