def test_band_cTe(self, its=100):
"""Checks band_cTe against its definition and required properties."""
for it in range(its):
l = random.choice([0, 1, randint(0, 10)])
u = random.choice([0, 1, randint(0, 10)])
size = random.choice([0, 1, randint(0, 10), randint(0, 100)])
mat_rect = randn(l + u + 1, size)
mat_rect_new = fl.band_cTe(l, u, mat_rect)
mat_rect_new_good = fl.band_e(u, l, fl.band_c(l, u, mat_rect).T)
assert_allequal(mat_rect_new, mat_rect_new_good)
assert not np.may_share_memory(mat_rect_new, mat_rect)
# check a property to do with doing band_cTe twice
assert_allequal(
fl.band_cTe(u, l, mat_rect_new),
fl.band_ce(l, u, mat_rect)
)
# check version that uses pre-specified target
mat_rect_new2 = np.empty((l + u + 1, size))
array_mem = get_array_mem(mat_rect, mat_rect_new2)
ret = fl.band_cTe(l, u, mat_rect, target_rect=mat_rect_new2)
self.assertIsNone(ret)
assert_allequal(mat_rect_new2, mat_rect_new)
assert get_array_mem(mat_rect, mat_rect_new2) == array_mem
def test_band_cTe(self, its=100):
"""Checks band_cTe against its definition and required properties."""
for it in range(its):
l = random.choice([0, 1, randint(0, 10)])
u = random.choice([0, 1, randint(0, 10)])
size = random.choice([0, 1, randint(0, 10), randint(0, 100)])
mat_rect = randn(l + u + 1, size)
mat_rect_new = fl.band_cTe(l, u, mat_rect)
mat_rect_new_good = fl.band_e(u, l, fl.band_c(l, u, mat_rect).T)
assert_allequal(mat_rect_new, mat_rect_new_good)
assert not np.may_share_memory(mat_rect_new, mat_rect)
# check a property to do with doing band_cTe twice
assert_allequal(
fl.band_cTe(u, l, mat_rect_new),
fl.band_ce(l, u, mat_rect)
)
# check version that uses pre-specified target
mat_rect_new2 = np.empty((l + u + 1, size))
array_mem = get_array_mem(mat_rect, mat_rect_new2)
ret = fl.band_cTe(l, u, mat_rect, target_rect=mat_rect_new2)
self.assertIsNone(ret)
assert_allequal(mat_rect_new2, mat_rect_new)
assert get_array_mem(mat_rect, mat_rect_new2) == array_mem
def test_band_e_bm(self, its=50):
for it in range(its):
size = random.choice([0, 1, randint(0, 10), randint(0, 100)])
mat_bm = gen_BandMat(size)
l = random.choice([0, 1, randint(0, 10)])
u = random.choice([0, 1, randint(0, 10)])
mat_rect = bm.band_e_bm(l, u, mat_bm)
mat_rect_good = fl.band_e(l, u, mat_bm.full())
assert_allequal(mat_rect, mat_rect_good)
assert not np.may_share_memory(mat_rect, mat_bm.data)
def test_band_e_bm(self, its=50):
for it in range(its):
size = random.choice([0, 1, randint(0, 10), randint(0, 100)])
mat_bm = gen_BandMat(size)
l = random.choice([0, 1, randint(0, 10)])
u = random.choice([0, 1, randint(0, 10)])
mat_rect = bm.band_e_bm(l, u, mat_bm)
mat_rect_good = fl.band_e(l, u, mat_bm.full())
assert_allequal(mat_rect, mat_rect_good)
assert not np.may_share_memory(mat_rect, mat_bm.data)
def test_band_e_linear(self, its=100):
"""Checks band_e is linear."""
for it in range(its):
l = random.choice([0, 1, randint(0, 10)])
u = random.choice([0, 1, randint(0, 10)])
size = random.choice([0, 1, randint(0, 10), randint(0, 100)])
# check additive
mat_full1 = randn(size, size)
mat_full2 = randn(size, size)
assert_allclose(
fl.band_e(l, u, mat_full1 + mat_full2),
fl.band_e(l, u, mat_full1) + fl.band_e(l, u, mat_full2)
)
# check homogeneous
mat_full = randn(size, size)
mult = random.choice([0.0, randn(), randn(), randn()])
assert_allclose(
fl.band_e(l, u, mat_full * mult),
fl.band_e(l, u, mat_full) * mult
)
# check output is a newly-created array
mat_rect = fl.band_e(l, u, mat_full)
assert not np.may_share_memory(mat_rect, mat_full)
def test_band_e_linear(self, its=100):
"""Checks band_e is linear."""
for it in range(its):
l = random.choice([0, 1, randint(0, 10)])
u = random.choice([0, 1, randint(0, 10)])
size = random.choice([0, 1, randint(0, 10), randint(0, 100)])
# check additive
mat_full1 = randn(size, size)
mat_full2 = randn(size, size)
assert_allclose(
fl.band_e(l, u, mat_full1 + mat_full2),
fl.band_e(l, u, mat_full1) + fl.band_e(l, u, mat_full2)
)
# check homogeneous
mat_full = randn(size, size)
mult = random.choice([0.0, randn(), randn(), randn()])
assert_allclose(
fl.band_e(l, u, mat_full * mult),
fl.band_e(l, u, mat_full) * mult
)
# check output is a newly-created array
mat_rect = fl.band_e(l, u, mat_full)
assert not np.may_share_memory(mat_rect, mat_full)
def test_BandMat_equiv(self, its=50):
for it in range(its):
size = random.choice([0, 1, randint(0, 10), randint(0, 100)])
mat_bm = gen_BandMat(size)
l_new = random.choice([None, 0, 1, randint(0, 10)])
u_new = random.choice([None, 0, 1, randint(0, 10)])
transposed_new = random.choice([None, True, False])
zero_extra = rand_bool()
l_new_value = mat_bm.l if l_new is None else l_new
u_new_value = mat_bm.u if u_new is None else u_new
transposed_new_value = (mat_bm.transposed if transposed_new is None
else transposed_new)
if l_new_value < mat_bm.l or u_new_value < mat_bm.u:
self.assertRaises(AssertionError,
mat_bm.equiv,
l_new=l_new,
u_new=u_new,
transposed_new=transposed_new,
zero_extra=zero_extra)
else:
mat_bm_new = mat_bm.equiv(l_new=l_new,
u_new=u_new,
transposed_new=transposed_new,
zero_extra=zero_extra)
assert mat_bm_new.l == l_new_value
assert mat_bm_new.u == u_new_value
assert mat_bm_new.transposed == transposed_new_value
assert_allequal(mat_bm_new.full(), mat_bm.full())
assert not np.may_share_memory(mat_bm_new.data, mat_bm.data)
if zero_extra:
mat_new_data_good = (fl.band_e(
u_new_value, l_new_value,
mat_bm.full().T)) if mat_bm_new.transposed else (
fl.band_e(l_new_value, u_new_value, mat_bm.full()))
assert_allequal(mat_bm_new.data, mat_new_data_good)
def test_zero_extra_entries(self, its=100):
"""Checks zero_extra_entries against its equivalent definition."""
for it in range(its):
l = random.choice([0, 1, randint(0, 10)])
u = random.choice([0, 1, randint(0, 10)])
size = random.choice([0, 1, randint(0, 10), randint(0, 100)])
mat_rect = randn(l + u + 1, size)
mat_rect_good = mat_rect.copy()
array_mem = get_array_mem(mat_rect)
fl.zero_extra_entries(l, u, mat_rect)
mat_rect_good[:] = fl.band_e(l, u, fl.band_c(l, u, mat_rect_good))
assert_allequal(mat_rect, mat_rect_good)
assert get_array_mem(mat_rect) == array_mem
def test_zero_extra_entries(self, its=100):
"""Checks zero_extra_entries against its equivalent definition."""
for it in range(its):
l = random.choice([0, 1, randint(0, 10)])
u = random.choice([0, 1, randint(0, 10)])
size = random.choice([0, 1, randint(0, 10), randint(0, 100)])
mat_rect = randn(l + u + 1, size)
mat_rect_good = mat_rect.copy()
array_mem = get_array_mem(mat_rect)
fl.zero_extra_entries(l, u, mat_rect)
mat_rect_good[:] = fl.band_e(l, u, fl.band_c(l, u, mat_rect_good))
assert_allequal(mat_rect, mat_rect_good)
assert get_array_mem(mat_rect) == array_mem
def test_BandMat_equiv(self, its=50):
for it in range(its):
size = random.choice([0, 1, randint(0, 10), randint(0, 100)])
mat_bm = gen_BandMat(size)
l_new = random.choice([None, 0, 1, randint(0, 10)])
u_new = random.choice([None, 0, 1, randint(0, 10)])
transposed_new = random.choice([None, True, False])
zero_extra = rand_bool()
l_new_value = mat_bm.l if l_new is None else l_new
u_new_value = mat_bm.u if u_new is None else u_new
transposed_new_value = (mat_bm.transposed if transposed_new is None
else transposed_new)
if l_new_value < mat_bm.l or u_new_value < mat_bm.u:
self.assertRaises(AssertionError,
mat_bm.equiv,
l_new=l_new, u_new=u_new,
transposed_new=transposed_new,
zero_extra=zero_extra)
else:
mat_bm_new = mat_bm.equiv(l_new=l_new, u_new=u_new,
transposed_new=transposed_new,
zero_extra=zero_extra)
assert mat_bm_new.l == l_new_value
assert mat_bm_new.u == u_new_value
assert mat_bm_new.transposed == transposed_new_value
assert_allequal(mat_bm_new.full(), mat_bm.full())
assert not np.may_share_memory(mat_bm_new.data, mat_bm.data)
if zero_extra:
mat_new_data_good = (
fl.band_e(u_new_value, l_new_value, mat_bm.full().T)
) if mat_bm_new.transposed else (
fl.band_e(l_new_value, u_new_value, mat_bm.full())
)
assert_allequal(mat_bm_new.data, mat_new_data_good)
def test_band_ec(self, its=100):
"""Checks band_ec against its definition and required properties."""
for it in range(its):
l = random.choice([0, 1, randint(0, 10)])
u = random.choice([0, 1, randint(0, 10)])
size = random.choice([0, 1, randint(0, 10), randint(0, 100)])
mat_full = randn(size, size)
mat_full_new = fl.band_ec(l, u, mat_full)
mat_full_new_good = fl.band_c(l, u, fl.band_e(l, u, mat_full))
assert_allequal(mat_full_new, mat_full_new_good)
assert not np.may_share_memory(mat_full_new, mat_full)
# check idempotent
assert_allequal(fl.band_ec(l, u, mat_full_new), mat_full_new)
def test_band_ec(self, its=100):
"""Checks band_ec against its definition and required properties."""
for it in range(its):
l = random.choice([0, 1, randint(0, 10)])
u = random.choice([0, 1, randint(0, 10)])
size = random.choice([0, 1, randint(0, 10), randint(0, 100)])
mat_full = randn(size, size)
mat_full_new = fl.band_ec(l, u, mat_full)
mat_full_new_good = fl.band_c(l, u, fl.band_e(l, u, mat_full))
assert_allequal(mat_full_new, mat_full_new_good)
assert not np.may_share_memory(mat_full_new, mat_full)
# check idempotent
assert_allequal(
fl.band_ec(l, u, mat_full_new),
mat_full_new
)
def test_band_e_basis(self, its=100):
"""Checks band_e behaves correctly on canonical basis matrices."""
for it in range(its):
l = random.choice([0, 1, randint(0, 10)])
u = random.choice([0, 1, randint(0, 10)])
# size >= 1 (there are no canonical basis matrices if size == 0)
size = random.choice([1, 2, randint(1, 10), randint(1, 100)])
# pick a random canonical basis matrix
k = randint(size)
j = randint(size)
mat_full = np.zeros((size, size))
mat_full[k, j] = 1.0
mat_rect = fl.band_e(l, u, mat_full)
i = k - j
mat_rect_good = np.zeros((l + u + 1, size))
if -u <= i <= l:
mat_rect_good[u + i, j] = 1.0
assert_allequal(mat_rect, mat_rect_good)
def test_band_e_basis(self, its=100):
"""Checks band_e behaves correctly on canonical basis matrices."""
for it in range(its):
l = random.choice([0, 1, randint(0, 10)])
u = random.choice([0, 1, randint(0, 10)])
# size >= 1 (there are no canonical basis matrices if size == 0)
size = random.choice([1, 2, randint(1, 10), randint(1, 100)])
# pick a random canonical basis matrix
k = randint(size)
j = randint(size)
mat_full = np.zeros((size, size))
mat_full[k, j] = 1.0
mat_rect = fl.band_e(l, u, mat_full)
i = k - j
mat_rect_good = np.zeros((l + u + 1, size))
if -u <= i <= l:
mat_rect_good[u + i, j] = 1.0
assert_allequal(mat_rect, mat_rect_good)
