def compareSupportFunctions(repeats, eps):
P = rP.getRandomPolygon(3)
Q = rP.getRandomPolygon(4)
cD_P = cV.getConeVol(P)
for i in range(len(P)):
u = [cD_P[i - 1][0], cD_P[i - 1][1]]
alpha = rP.supportFunctionCartesianCentered(Q, u)
beta = rP.supportFunctionCartesianCentered2(Q, u)
alternative = trySupport(Q, u)
print(alternative)
print(alpha)
print(beta)
def supportTest(repeats):
tooSmall = 0
tooSmall2 = 0
tooSmall3 = 3
tooBig = 0
easyFail = 0
n = 0
while (n < repeats):
containsPoint_eps = 0
P = rP.getRandomPolygon(3)
Q = rP.getRandomPolygon(4)
cD_P = cV.getConeVol(P)
for i in range(len(P)):
print(len(P))
u = [cD_P[i - 1][0], cD_P[i - 1][1]]
alpha = rP.supportFunctionCartesianCentered(Q, u)
beta = rP.supportFunctionCartesianCentered2(Q, u)
gamma = 1 #trySupport( Q , u , 0.0000001)
if math.fabs(
M.scal(u, P[i - 1]) -
rP.supportFunctionCartesianCentered2(P, u)) > 1:
easyFail += 1
if not (containsPoint(Q, M.scaleVek(alpha - math.exp(-15), u))):
tooBig += 1
if (containsPoint(Q, M.scaleVek(alpha + 0.01, u))):
#plotPoly( P , 'r' )
#plotPoly( Q , 'y')
tooSmall += 1
if (containsPoint(Q, M.scaleVek(beta + 0.01, u))):
#plotPoly( P , 'r' )
#plotPoly( Q , 'y')
tooSmall2 += 1
if (containsPoint(Q, M.scaleVek(gamma + 0.01, u))):
#plotPoly( P , 'r' )
#plotPoly( Q , 'y')
tooSmall3 += 1
n += 1
print([easyFail, tooBig, tooSmall, tooSmall2, tooSmall3])
def getWorsteNormalsDirection(polygon):
n = len(polygon)
result = 0
cD = cV.getConeVol(polygon)
for i in range(n):
u = [cD[i % n][0], cD[i % n][1]]
v = polygon[i - 1]
w = polygon[i % n]
diff = math.fabs(M.scal(v, u) - M.scal(w, u))
if diff > result:
result = diff
return result
def makeNormalsTest(polygon, eps_norm, eps_direction):
n = len(polygon)
cD = cV.getConeVol(polygon)
for i in range(n):
u = [cD[i % n][0], cD[i % n][1]]
if math.fabs(M.norm(u) - 1) > eps_norm:
return False
v = polygon[i - 1]
w = polygon[i % n]
diff = math.fabs(M.scal(v, u) - M.scal(w, u))
if diff > eps_direction:
return False
return True
result = [ [ 0 , 0 ] , math.inf ]
n = 2
while( result[1] > eps_orthGrad):
temp = min( getGrid( n ) , cD , scalAbsGrad )
if temp[1] < result[1]:
result = temp
n = n + 1
return result
cD_random = cV.getConeVol(rP.getRandomPolygon( 5 ))
eps_orthGrad = 0.01
orthGrad_test = getOrthGrad( cD_test )
# print(cV.coneVolumeNewton( cD_test , [ orthGrad_test[0][0] , orthGrad_test[0][1] ] ) )
# newton läuft gegen [ 0 , inf ] mit orthGrad_test-startpunkt bei [5.25, 7.0]. Der presolver ist nicht geeignet. Baue lieber Quadrat im 1. Quadranten, der eine Aufsteigsrichtung enthält. Verfeinere dann dieses Quadrat, ohne es zu vergrößern
def startPoint():
n=4
result=[[0,0],float("inf")]
while(result[1]>min_grid):
grid=getGrid(n)
result=min_psi(grid)
if(result[1]==0):