def generate_nfp(nfp_paris):
"""
:param nfp_paris:
:return:
"""
nfp_list = list()
for pair in nfp_paris:
poly_a = pair['A']
poly_a['points'] = nfp_utls.rotate_polygon(
poly_a['points'], pair['key']['A_rotation'])['points']
poly_b = pair['B']
poly_b['points'] = nfp_utls.rotate_polygon(
poly_b['points'], pair['key']['B_rotation'])['points']
if pair['key']['inside']:
nfp = nfp_utls.nfp_rectangle(poly_a['points'], poly_b['points'])
if nfp_utls.polygon_area(nfp) > 0:
nfp.reverse()
else:
# pair['key']['inside'] == False , so compute no fit polygon between two segments
# nfp = nfp_utls.nfp_polygon(poly_a, poly_b) # 使用自己写的生成nfp的函数
nfp = minkowski_difference(
poly_a, poly_b) # 使用 Minkowski_difference和求两个零件的nfp, 考虑用lib
# print("nfp = ", nfp)
if nfp_utls.polygon_area(nfp) > 0:
nfp.reverse()
nfp_list.append({'key': pair['key'], 'value': nfp})
return nfp_list
def process_nfp(self, pair):
"""
计算所有图形两两组合的相切多边形（NFP）
:param pair: 两个组合图形的参数
:return:
"""
if pair is None or len(pair) == 0:
return None
# 考虑有没有洞和凹面
search_edges = self.config['exploreConcave']
use_holes = self.config['useHoles']
# 图形参数
A = copy.deepcopy(pair['A'])
A['points'] = nfp_utls.rotate_polygon(
A['points'], pair['key']['A_rotation'])['points']
B = copy.deepcopy(pair['B'])
B['points'] = nfp_utls.rotate_polygon(
B['points'], pair['key']['B_rotation'])['points']
if pair['key']['inside']:
# 内切或者外切
if nfp_utls.is_rectangle(A['points'], 0.0001):
nfp = nfp_utls.nfp_rectangle(A['points'], B['points'])
else:
nfp = nfp_utls.nfp_polygon(A, B, True, search_edges)
# ensure all interior NFPs have the same winding direction
if nfp and len(nfp) > 0:
for i in range(0, len(nfp)):
if nfp_utls.polygon_area(nfp[i]) > 0:
nfp[i].reverse()
else:
pass
# print('NFP Warning:', pair['key'])
else:
if search_edges:
nfp = nfp_utls.nfp_polygon(A, B, False, search_edges)
else:
nfp = minkowski_difference(A, B)
# 检查NFP多边形是否合理
if nfp is None or len(nfp) == 0:
pass
# print('error in NFP 260')
# print('NFP Error:', pair['key'])
# print('A;', A)
# print('B:', B)
return None
for i in range(0, len(nfp)):
# if search edges is active, only the first NFP is guaranteed to pass sanity check
if not search_edges or i == 0:
if abs(nfp_utls.polygon_area(nfp[i])) < abs(
nfp_utls.polygon_area(A['points'])):
pass
# print('error in NFP area 269')
# print('NFP Area Error: ', abs(nfp_utls.polygon_area(nfp[i])), pair['key'])
# print('NFP:', json.dumps(nfp[i]))
# print('A: ', A)
# print('B: ', B)
nfp.pop(i)
return None
if len(nfp) == 0:
return None
# for outer NFPs, the first is guaranteed to be the largest.
# Any subsequent NFPs that lie inside the first are hole
for i in range(0, len(nfp)):
if nfp_utls.polygon_area(nfp[i]) > 0:
nfp[i].reverse()
if i > 0:
if nfp_utls.point_in_polygon(nfp[i][0], nfp[0]):
if nfp_utls.polygon_area(nfp[i]) < 0:
nfp[i].reverse()
# generate nfps for children (holes of parts) if any exist
# 有洞的暂时不管
if use_holes and len(A) > 0:
pass
return {'key': pair['key'], 'value': nfp}
def process_nfp(self, pair):
"""
Tính đa giác tiếp tuyến của tất cả các cặp hình
:param pair: Tham số kết hợp của hai hình
:return:
"""
if pair is None or len(pair) == 0:
return None
# Tham số cài đặt, có lỗ hay mặt lõm hay không
search_edges = self.config['exploreConcave']
use_holes = self.config['useHoles']
# Thông số đồ họa, quay các hình theo góc quay
# A nếu là bin thì không chứa thông tin offset
A = copy.deepcopy(pair['A'])
A['points'] = nfp_utls.rotate_polygon(
A['points'], pair['key']['A_rotation'])['points']
# Là path, chứa thông tin offset
B = copy.deepcopy(pair['B'])
# Rotate B theo key pair đã tạo với A
B['points'] = nfp_utls.rotate_polygon(
B['points'], pair['key']['B_rotation'])['points']
if pair['key']['inside']:
# Inside or outside
# Thường thì đây là cặp bin và path, tính NPF của part với bin hoặc giữa các path với nhau
if nfp_utls.is_rectangle(A['points'], 0.0001):
# Tính npf của hình với bin
nfp = nfp_utls.nfp_rectangle(A['points'], B['points'])
else:
nfp = nfp_utls.nfp_polygon(A, B, True, search_edges)
# ensure all interior NFPs have the same winding direction
# Test_Di chuyển về sát lề
# for nf in nfp:
# for p in nf:
# p['x'] = p['x'] - 10
# p['y'] = p['y'] - 10
if nfp and len(nfp) > 0:
for i in range(0, len(nfp)):
if nfp_utls.polygon_area(nfp[i]) > 0:
nfp[i].reverse()
else:
pass
# print('NFP Warning:', pair['key'])
else:
if search_edges:
nfp = nfp_utls.nfp_polygon(A, B, False, search_edges)
else:
nfp = minkowski_difference(A, B)
# Kiểm tra xem đa giác NFP có hợp lý không
if nfp is None or len(nfp) == 0:
pass
# print('error in NFP 260')
# print('NFP Error:', pair['key'])
# print('A;', A)
# print('B:', B)
return None
for i in range(0, len(nfp)):
# if search edges is active, only the first NFP is guaranteed to pass sanity check
if not search_edges or i == 0:
if abs(nfp_utls.polygon_area(nfp[i])) < abs(
nfp_utls.polygon_area(A['points'])):
pass
# print('error in NFP area 269')
# print('NFP Area Error: ', abs(nfp_utls.polygon_area(nfp[i])), pair['key'])
# print('NFP:', json.dumps(nfp[i]))
# print('A: ', A)
# print('B: ', B)
nfp.pop(i)
return None
if len(nfp) == 0:
return None
# for outer NFPs, the first is guaranteed to be the largest.
# Any subsequent NFPs that lie inside the first are hole
for i in range(0, len(nfp)):
if nfp_utls.polygon_area(nfp[i]) > 0:
nfp[i].reverse()
if i > 0:
if nfp_utls.point_in_polygon(nfp[i][0], nfp[0]):
if nfp_utls.polygon_area(nfp[i]) < 0:
nfp[i].reverse()
# generate nfps for children (holes of parts) if any exist
# Leave the hole in
if use_holes and len(A) > 0:
pass
return {'key': pair['key'], 'value': nfp}