def my_func(x):
# Declare empty arrays to be filled with the values passed into the function
# and the inverse of A into B
A = numba.cuda.shared.array((N,N), dtype=numba.types.complex64)
B = numba.cuda.shared.array((N,N), dtype=numba.types.complex64)
#tmp = numba.cuda.shared.array((N,N), dtype=numba.types.complex64)
# Assign the values in the array
A[0, 0] = x[0]
A[0, 1] = complex(x[1], x[2])
A[1, 0] = complex(x[1], -x[2])
A[1, 1] = x[3]
for i in range(N):
for j in range(N):
if i == j:
B[i,j] = complex(1,0)
else:
B[i,j] = complex(0,0)
B = la.myInvSZ(A, B, N)
tr = 0 + 0j
tr = la.trace(B, N, tr)
return tr.real
def my_func(x):
# Declare empty arrays to be filled with the values passed into the function
# and the inverse of A into B
A = numba.cuda.shared.array((N,N), dtype=numba.types.complex64)
B = numba.cuda.shared.array((N,N), dtype=numba.types.complex64)
#tmp = numba.cuda.shared.array((N,N), dtype=numba.types.complex64)
# Assign the values in the array
A[0, 0] = 1 / complex(x[0], x[1])
A[0, 1] = complex(0, 0)
A[1, 0] = complex(0, 0)
A[1, 1] = 1 / complex(x[2], x[3])
for i in range(N):
for j in range(N):
if i == j:
B[i,j] = complex(1,0)
else:
B[i,j] = complex(0,0)
# B = la.myInvSZ(A, B, N)
for k in range(N-1):
if (A[k,k].real != 1) or (A[k,k].imag != 0):
scale = A[k,k]
for j in range(N):
B[k,j] = B[k,j] / scale
A[k,j] = A[k,j] / scale
for i in range(k+1, N):
if (A[i,k].real != 0) or (A[i,k].imag != 0):
ratio = A[i,k]
for j in range(N):
A[i,j] = A[i,j] - ratio * A[k,j]
B[i,j] = B[i,j] - ratio * B[k,j]
if (A[N-1,N-1].real != 1) or (A[N-1,N-1].imag != 0):
for j in range(N):
B[N-1,j] = B[N-1,j] / A[N-1,N-1]
A[N-1,N-1] = complex(1,0)
# # ELIMINATE UPPER TRIANGLE
for k in range(1, N):
for i in range(k):
ratio = A[i,k]
for j in range(N):
A[i,j] = A[i,j] - ratio * A[k,j]
B[i,j] = B[i,j] - ratio * B[k,j]
tr = 0 + 0j
tr = la.trace(B, N, tr)
return (tr * complex(tr.real, - tr.imag)).real
def my_func(x):
# Declare empty arrays to be filled with the values passed into the function
# and the inverse of A into B
A = numba.cuda.shared.array((N, N), dtype=numba.types.complex64)
B = numba.cuda.shared.array((N, N), dtype=numba.types.complex64)
C = numba.cuda.shared.array((N, N), dtype=numba.types.complex64)
# Assign the values in the array
A[0, 0] = complex(x[0], x[1])
A[0, 1] = complex(x[2], x[3])
A[1, 0] = complex(-x[2], x[3])
A[1, 1] = complex(x[0], -x[1])
B[0, 0] = complex(x[0], -x[1])
B[1, 0] = complex(x[2], -x[3])
B[0, 1] = complex(-x[2], -x[3])
B[1, 1] = complex(x[0], x[1])
C = la.squareMatMul(A, B, C, N)
#for i in range(N):
#
# for j in range(N):
# tmp = 0+0j
#
# for l in range(N):
# tmp = A[i,l] * B[l,j] + tmp
#
# C[i,j] = tmp
# tr = C[0,0] + C[1,1]
tr = 0 + 0j
tr = la.trace(C, N, tr)
return tr.real