def readRecord():
line=122
df = pd.read_csv("/Users/sean/Documents/Projects/Packing-Algorithm/arrangements/record.csv")
polygons=json.loads(df["result"][line])
for poly in polygons:
PltFunc.addPolygon(poly)
PltFunc.showPlt()
def getHeight(self):
_max=0
for i in range(1,len(self.polygons)):
top_index=GeoFunc.checkTop(self.polygons[i])
top=self.polygons[i][top_index][1]
if top>_max:
_max=top
self.contain_height=_max
PltFunc.addLine([[0,self.contain_height],[self.width,self.contain_height]],color="blue")
def testData():
df = pd.read_csv("/Users/sean/Documents/Projects/Packing-Algorithm/record/convex.csv")
poly1=json.loads(df['polygon'][4674])
poly2=json.loads(df['polygon'][3652])
nfp=NFP(poly1,poly2) # NFP计算，error<0表示错误
PltFunc.addPolygon(poly1)
PltFunc.addPolygon(poly2)
# PltFunc.addPolygonColor(nfp.nfp)
# PltFunc.showPlt()
bfp=bestFitPosition(nfp,False)
def getConvexRandom():
polygon=[]
num=10
for i in range(0,num):
# radian=(2/num)*math.pi*i+math.pi*random.randrange(0,5,1)/12 # convex 4的角度
radian=(2/num)*math.pi*i+math.pi*random.randrange(0,3,1)/(num*2) # convex num>4的角度
radius=random.randrange(200,500,100)
pt=[radius*math.cos(radian),radius*math.sin(radian)]
polygon.append(pt)
GeoFunc.slidePoly(polygon,750,750)
storePolygon(polygon,num=num)
PltFunc.addPolygon(polygon)
PltFunc.showPlt()
def showResult(self, **kw):
if "current" in kw and kw["current"] == True:
for poly in self.cur_polys:
PltFunc.addPolygonColor(poly)
PltFunc.addLine(
[[0, self.new_height], [self.width, self.new_height]],
color="blue")
if "initial" in kw and kw["initial"] == True:
for poly in self.polys:
PltFunc.addPolygon(poly)
PltFunc.addLine([[0, self.height], [self.width, self.height]],
color="blue")
PltFunc.showPlt()
def pltArea(self):
A, B, C = 0, 0, 0
for i, coefficient in enumerate(self.break_points_list):
print(coefficient)
A = A + coefficient[1]
B = A + coefficient[2]
C = A + coefficient[3]
if i > 0:
x = [self.break_points_list[i - 1][0], coefficient[0]]
else:
x = [0, coefficient[0]]
y0 = self.getQuadratic(x[0], A, B, C)
y1 = self.getQuadratic(x[1], A, B, C)
PltFunc.addLine([[x[0], y0], [x[1], y1]])
PltFunc.showPlt()
def showAll(self):
for i in range(0,len(self.polygons)):
PltFunc.addPolygon(self.polygons[i])
length=max(self.width,self.contain_height)
PltFunc.addLine([[self.width,0],[self.width,self.contain_height]],color="blue")
PltFunc.showPlt(width=length,height=length)
def CuckooSearch(self, poly_id, ori=''):
'''
poly_id: 当前多边形index
ori: 允许旋转的角度
'''
cuckoos = []
poly = self.polygons[poly_id]
GL_Algo = BottomLeftFill(self.W, self.polygons)
R = GL_Algo.getInnerFitRectangleNew(poly) # 为当前多边形计算inner-fit矩形
i = 0
while i < self.n_c: # 产生初始种群
c = Cuckoo(R)
if self.censorCuckoo(c) == False:
continue
cuckoos.append(c)
print(c.getXY())
i = i + 1
bestCuckoo = cuckoos[0]
t = 0
while t < self.maxGen: # 开始搜索
c_i = random.choice(cuckoos)
# 通过Levy飞行产生解
newCuckooFlag = False
while newCuckooFlag == False:
newX, newY = self.getCuckoos_Levy(1, bestCuckoo)
c_i.setXY(newX[0], newY[0])
if self.censorCuckoo(c_i):
newCuckooFlag = True
self.evaluate(poly_id, c_i, ori)
c_j = random.choice(cuckoos)
self.evaluate(poly_id, c_j, ori)
if c_i.getF() < c_j.getF():
c_j = c_i
bestCuckoo = c_j
# 丢弃一部分最坏的巢并在新位置建立新巢
cuckoos.sort(key=lambda x: x.getF(), reverse=True)
newX, newY = self.getCuckoos_Levy(
int(self.percentage * len(cuckoos)) + 1, bestCuckoo)
newi = 0
for i in range(int(len(cuckoos) * self.percentage)):
print('----- 第', str(t + 1), '代 // 第', str(i + 1), '只 ----')
if newi >= len(newX):
break
c_new = Cuckoo(R)
newCuckooFlag = False
while newCuckooFlag == False:
c_new.setXY(newX[newi], newY[newi])
if self.censorCuckoo(c_new) == False:
newX, newY = self.getCuckoos_Levy(
int(self.percentage * len(cuckoos)) + 1,
bestCuckoo)
newi = 0
else:
newCuckooFlag = True
self.evaluate(poly_id, c_new, ori)
cuckoos[i] = c_new
if c_new.getF() == 0:
break
newi = newi + 1
cuckoos.sort(key=lambda x: x.getF(), reverse=False)
bestCuckoo = cuckoos[0]
bestCuckoo.slidePolytoMe(poly)
print(bestCuckoo.getF(), bestCuckoo.getXY())
self.bestF = bestCuckoo.getF()
for i in range(0, self.n_polys):
PltFunc.addPolygon(self.polygons[i])
t = t + 1
PltFunc.saveFig(str(t))
return bestCuckoo
def showAll(self):
for i in range(0, self.n_polys):
PltFunc.addPolygon(self.polygons[i])
PltFunc.showPlt()
def readPoly():
line=1000*10+random.randint(0,1000)
df = pd.read_csv("/Users/sean/Documents/Projects/Packing-Algorithm/record/convex.csv")
polygon=json.loads(df["polygon"][line])
PltFunc.addPolygon(polygon)
PltFunc.showPlt()