def test_dump_r(nrows=10):
A = IntegerMatrix(nrows, nrows)
A.randomize("ntrulike", bits=10, q=1023)
M = GSO.Mat(A)
if not have_numpy:
return
M.update_gso()
r = dump_r(M, 0, nrows)
for i in range(nrows):
assert abs(M.get_r(i, i) - r[i]) < 0.001
def test_dump_r(nrows=10):
A = IntegerMatrix(nrows, nrows)
A.randomize("ntrulike", bits=10, q=1023)
M = GSO.Mat(A)
if not have_numpy:
return
M.update_gso()
r = dump_r(M, 0, nrows)
for i in range(nrows):
assert abs(M.get_r(i, i) - r[i]) < 0.001
def test_dump_mu(nrows=10):
A = IntegerMatrix(nrows, nrows)
A.randomize("ntrulike", bits=10, q=1023)
M = GSO.Mat(A)
if not have_numpy:
return
M.update_gso()
mu = dump_mu(M, 0, nrows)
for i in range(nrows):
for j in range(i):
assert abs(M.get_mu(i, j) - mu[i, j]) < 0.001
def test_dump_mu(nrows=10):
A = IntegerMatrix(nrows, nrows)
A.randomize("ntrulike", bits=10, q=1023)
M = GSO.Mat(A)
if not have_numpy:
return
M.update_gso()
mu = dump_mu(M, 0, nrows)
for i in range(nrows):
for j in range(nrows):
assert abs(M.get_mu(i, j) - mu[i, j]) < 0.001
def test_dump_r(nrows=10):
A = IntegerMatrix(nrows, nrows)
A.randomize("ntrulike", bits=10, q=1023)
M = GSO.Mat(A)
if not have_numpy:
return
r = numpy.ndarray(dtype='double', shape=nrows)
M.update_gso()
dump_r(r, M, 0, nrows)
for i in range(nrows):
assert abs(M.get_r(i, i) - r[i]) < 0.001
def test_dump_mu(nrows=10):
A = IntegerMatrix(nrows, nrows)
A.randomize("ntrulike", bits=10, q=1023)
M = GSO.Mat(A)
if not have_numpy:
return
mu = numpy.ndarray(dtype='double', shape=(nrows, nrows))
M.update_gso()
dump_mu(mu, M, 0, nrows)
for i in range(nrows):
for j in range(nrows):
assert abs(M.get_mu(i, j) - mu[i, j]) < 0.001
def make_integer_matrix(m, n):
A = IntegerMatrix(m, n)
A.randomize("uniform", bits=m+n)
return A
def make_integer_matrix(m, n):
A = IntegerMatrix(m, n)
A.randomize("uniform", bits=m + n)
return A
def make_integer_matrix(d, int_type="mpz"):
A = IntegerMatrix(d, d, int_type=int_type)
A.randomize("qary", k=d // 2, bits=10)
return A
def make_integer_matrix(m, n, int_type="mpz"):
A = IntegerMatrix(m, n, int_type=int_type)
A.randomize("uniform", bits=20)
return A
def make_integer_matrix(m, n, int_type="mpz"):
A = IntegerMatrix(m, n, int_type=int_type)
A.randomize("qary", k=m // 2, bits=m)
return A
def make_integer_matrix(m, n):
A = IntegerMatrix(m, n)
A.randomize(algorithm="ntrulike", bits=30, q=2147483647)
return A
def make_integer_matrix(m, n, int_type="mpz"):
A = IntegerMatrix(m, n, int_type=int_type)
A.randomize("qary", bits=20, k=min(m, n) // 2)
return A
