def create_mul_testvectors():
"""Yield pairs of matrices for testing matrix multiplication
These matrices are instances of class ``QStateMatrix``.
"""
for i in range(2, 6):
for j in range(2, 6):
for r in range(2, 12, 2):
for n in range(2):
m1 = qs_rand_matrix(i, j, r)
rand_mul_scalar(m1)
m2 = qs_rand_matrix(i, j, r)
rand_mul_scalar(m2)
yield m1, m2
def large_matmul_testvectors():
"""Yield test data for large matrix multiplication
yield pairs ``m1``, ``m2`` of 2**12 times 2**12
and also pairs random slices of about 40 elements
in range(2**12)
"""
nn = 12
for r in range(10, 27):
m1 = qs_rand_matrix(nn, nn, r)
rand_mul_scalar(m1)
m2 = qs_rand_matrix(nn, nn, r)
rand_mul_scalar(m2)
r1 = slice(randint(0, 100), 1 << nn, 2 * randint(150, 160) + 1)
r2 = slice(randint(0, 100), 1 << nn, 2 * randint(150, 160) + 1)
yield m1, m2, r1, r2
def gate_not_testdata():
for cols, data, v in gate_not_data:
yield QStateMatrix(0, cols, data), v
for cols in list(range(6)):
for r in range(cols + 3):
for i in range(3):
v = randint(0, (1 << cols) - 1)
yield qs_rand_matrix(0, cols, r), v
def gate_phi_testdata():
for cols in list(range(6)):
for r in range(cols + 3):
for i in range(3):
v = randint(0, (1 << cols) - 1)
phi = randint(0, 4)
m = qs_rand_matrix(0, cols, r)
yield m, v, phi
def create_display_testvectors():
"""yield instances of class ``QStateMatrix`` for tests """
for rows, cols, factor, data in qs_matrix_data:
m = QStateMatrix(rows, cols, data)
m.mul_scalar(*factor)
yield m
yield qs_unit_matrix(4)
for i in range(20):
yield qs_rand_matrix(2, 0, 3)
for i in range(20):
yield qs_rand_matrix(1, 0, 2)
for rows in range(6):
for cols in range(5):
for nr in [1, 2] + list(range(rows + cols, rows + cols + 3)):
m = qs_rand_matrix(rows, cols, nr)
m.mul_scalar(randint(-8, 8), randint(0, 7))
yield m
def create_testmatrices():
"""yield instances of class ``QStateMatrix`` for tests """
for m_data in qs_matrix_data:
m = create_m(*m_data)
yield m
yield qs_unit_matrix(4)
for i in range(20):
yield qs_rand_matrix(2, 2, 4)
for cols in range(0,7):
for rows in range(0, 7):
if rows + cols > 9:
break
yield QStateMatrix(rows, cols)
for data_rows in range(1, rows + cols + 3):
for n in range(2):
m = qs_rand_matrix(rows, cols, data_rows)
rand_mul_scalar(m)
yield m
def gate_ctrl_phi_testdata():
for cols, data, v1, v2 in gate_ctrl_phi_data:
yield QStateMatrix(0, cols, data), v1, v2
for cols in list(range(6)):
for r in range(cols + 3):
for i in range(3):
v1 = randint(0, (1 << cols) - 1)
v2 = randint(0, (1 << cols) - 1)
m = qs_rand_matrix(0, cols, r)
yield m, v1, v1
def restrict_testdata():
for cols, data, j, nqb in restrict_data:
yield QStateMatrix(0, cols, data), j, nqb
for cols in list(range(6)):
for r in range(cols + 3):
for i in range(3):
m = qs_rand_matrix(0, cols, r)
m.mul_scalar(randint(-8, 8), randint(0, 7))
j = randint(0, cols)
nqb = randint(0, cols - j)
yield m, j, nqb
def gate_ctrl_not_testdata():
for cols, data, v1, v2 in gate_ctrl_not_data:
yield QStateMatrix(0, cols, data), v1, v2
for cols in list(range(6)):
for r in range(cols + 3):
for i in range(3):
vc = randint(0, (1 << cols) - 1)
v = randint(0, (1 << cols) - 1)
while bitparity(vc & v):
v = randint(0, (1 << cols) - 1)
m = qs_rand_matrix(0, cols, r)
yield m, vc, v
def create_product_testvectors():
"""yield instances of class ``QStateMatrix`` for tests """
for m1_data, m2_data, nqb in qs_matrix_data:
m1 = create_m(*m1_data)
m2 = create_m(*m2_data)
yield m1, m2, nqb
yield qs_unit_matrix(4), qs_unit_matrix(4), 3
for i in range(20):
nqb = randint(0, 2)
yield qs_rand_matrix(2, 0, 3), qs_rand_matrix(2, 0, 3), nqb
for cols1 in range(2, 6):
for cols2 in range(2, 6):
for nqb in range(min(cols1, cols2)):
for n in range(2):
m1 = qs_rand_matrix(0, cols1, cols1 + 3)
rand_mul_scalar(m1)
m2 = qs_rand_matrix(0, cols2, cols2 + 3)
rand_mul_scalar(m2)
yield m1, m2, nqb
# Sparse states
for cols1 in range(2, 6):
for cols2 in range(2, 6):
for nqb in range(min(cols1, cols2)):
for r in range(3):
for n in range(2):
m1 = qs_rand_matrix(0, cols1, r)
m1.mul_scalar(randint(-8, 8), randint(0, 7))
m2 = qs_rand_matrix(0, cols2, r)
m1.mul_scalar(randint(-8, 8), randint(0, 7))
yield m1, m2, nqb
def rot_testdata():
for cols, data, rot, nrot, n0 in rot_data:
yield QStateMatrix(0, cols, data), rot, nrot, n0
for cols in list(range(6)):
for r in range(cols + 3):
for i in range(3):
nrot = n0 = cols
while n0 + nrot > cols:
n0, nrot = randint(0, cols), randint(0, cols)
rot = randint(-nrot, nrot)
m = qs_rand_matrix(0, cols, r)
m.mul_scalar(randint(-8, 8), randint(0, 7))
yield m, rot, nrot, n0
def xch_bits_testdata():
for cols, data, sh, mask in xch_bits_data:
yield QStateMatrix(0, cols, data), sh, mask
for cols in list(range(6)):
for r in range(cols + 3):
for i in range(3):
m = qs_rand_matrix(0, cols, r)
m.mul_scalar(randint(-8, 8), randint(0, 7))
if cols == 0:
yield m, 0, 0
else:
sh = randint(0, cols - 1)
mask = randint(0, (1 << (cols - sh)) - 1)
mask &= ~(mask << sh)
yield m, sh, mask
