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def test_list_order():
""" https://github.com/telegraphic/hickle/issues/26 """
d = [np.arange(n + 1) for n in range(20)]
hickle.dump(d, 'test.h5')
d_hkl = hickle.load('test.h5')
try:
for ii, xx in enumerate(d):
assert d[ii].shape == d_hkl[ii].shape
for ii, xx in enumerate(d):
assert np.allclose(d[ii], d_hkl[ii])
except AssertionError:
print(d[ii], d_hkl[ii])
raise
def test_astropy_angle():
for uu in ['radian', 'degree']:
a = Angle(1.02, unit=uu)
hkl.dump(a, "test_ap.h5")
b = hkl.load("test_ap.h5")
assert a == b
assert a.unit == b.unit
def test_astropy_time_array():
times = ['1999-01-01T00:00:00.123456789', '2010-01-01T00:00:00']
t1 = Time(times, format='isot', scale='utc')
hkl.dump(t1, "test_ap2.h5")
t2 = hkl.load("test_ap2.h5")
print(t1)
print(t2)
assert t1.value.shape == t2.value.shape
for ii in range(len(t1)):
assert t1.value[ii] == t2.value[ii]
assert t1.format == t2.format
assert t1.scale == t2.scale
times = [58264, 58265, 58266]
t1 = Time(times, format='mjd', scale='utc')
hkl.dump(t1, "test_ap2.h5")
t2 = hkl.load("test_ap2.h5")
print(t1)
print(t2)
def test_list_order():
""" https://github.com/telegraphic/hickle/issues/26 """
d = [np.arange(n + 1) for n in range(20)]
hickle.dump(d, 'test.h5')
d_hkl = hickle.load('test.h5')
try:
for ii, xx in enumerate(d):
assert d[ii].shape == d_hkl[ii].shape
for ii, xx in enumerate(d):
assert np.allclose(d[ii], d_hkl[ii])
except AssertionError:
print(d[ii], d_hkl[ii])
raise
def test_ndarray():
a = np.array([1,2,3])
b = np.array([2,3,4])
z = (a, b)
print "Original:"
pprint(z)
dump(z, 'test.hkl', mode='w')
print "\nReconstructed:"
z = load('test.hkl')
pprint(z)
def test_embedded_array():
""" See https://github.com/telegraphic/hickle/issues/24 """
d_orig = [[np.array([10., 20.]), np.array([10, 20, 30])], [np.array([10, 2]), np.array([1.])]]
hickle.dump(d_orig, 'test.h5')
d_hkl = hickle.load('test.h5')
for ii, xx in enumerate(d_orig):
for jj, yy in enumerate(xx):
assert np.allclose(d_orig[ii][jj], d_hkl[ii][jj])
print(d_hkl)
print(d_orig)
sm0 = csr_matrix((3, 4), dtype=np.int8).toarray()
row = np.array([0, 0, 1, 2, 2, 2])
col = np.array([0, 2, 2, 0, 1, 2])
data = np.array([1, 2, 3, 4, 5, 6])
sm1 = csr_matrix((data, (row, col)), shape=(3, 3))
sm2 = csc_matrix((data, (row, col)), shape=(3, 3))
indptr = np.array([0, 2, 3, 6])
indices = np.array([0, 2, 2, 0, 1, 2])
data = np.array([1, 2, 3, 4, 5, 6]).repeat(4).reshape(6, 2, 2)
sm3 = bsr_matrix((data,indices, indptr), shape=(6, 6))
hickle.dump(sm1, 'test_sp.h5')
sm1_h = hickle.load('test_sp.h5')
hickle.dump(sm2, 'test_sp2.h5')
sm2_h = hickle.load('test_sp2.h5')
hickle.dump(sm3, 'test_sp3.h5')
sm3_h = hickle.load('test_sp3.h5')
assert isinstance(sm1_h, csr_matrix)
assert isinstance(sm2_h, csc_matrix)
assert isinstance(sm3_h, bsr_matrix)
assert np.allclose(sm1_h.data, sm1.data)
assert np.allclose(sm2_h.data, sm2.data)
assert np.allclose(sm3_h.data, sm3.data)
assert sm1_h. shape == sm1.shape
assert sm2_h. shape == sm2.shape
assert sm3_h. shape == sm3.shape
def test_check_is_scipy_sparse_array():
t_csr = scipy.sparse.csr_matrix([0])
t_csc = scipy.sparse.csc_matrix([0])
t_bsr = scipy.sparse.bsr_matrix([0])
assert check_is_scipy_sparse_array(t_csr) is True
assert check_is_scipy_sparse_array(t_csc) is True
assert check_is_scipy_sparse_array(t_bsr) is True
assert check_is_scipy_sparse_array(np.array([1])) is False
def test_is_sparse():
sm0 = csr_matrix((3, 4), dtype=np.int8)
sm1 = csc_matrix((1, 2))
assert check_is_scipy_sparse_array(sm0)
assert check_is_scipy_sparse_array(sm1)
def test_check_is_scipy_sparse_array():
t_csr = scipy.sparse.csr_matrix([0])
t_csc = scipy.sparse.csc_matrix([0])
t_bsr = scipy.sparse.bsr_matrix([0])
assert check_is_scipy_sparse_array(t_csr) is True
assert check_is_scipy_sparse_array(t_csc) is True
assert check_is_scipy_sparse_array(t_bsr) is True
assert check_is_scipy_sparse_array(np.array([1])) is False