def test_structured_to_unstructured(self):
a = np.zeros(4, dtype=[('a', 'i4'), ('b', 'f4,u2'), ('c', 'f4', 2)])
out = structured_to_unstructured(a)
assert_equal(out, np.zeros((4, 5), dtype='f8'))
b = np.array([(1, 2, 5), (4, 5, 7), (7, 8, 11), (10, 11, 12)],
dtype=[('x', 'i4'), ('y', 'f4'), ('z', 'f8')])
out = np.mean(structured_to_unstructured(b[['x', 'z']]), axis=-1)
assert_equal(out, np.array([3., 5.5, 9., 11.]))
c = np.arange(20).reshape((4, 5))
out = unstructured_to_structured(c, a.dtype)
want = np.array([(0, (1., 2), [3., 4.]), (5, (6., 7), [8., 9.]),
(10, (11., 12), [13., 14.]),
(15, (16., 17), [18., 19.])],
dtype=[('a', '<i4'),
('b', [('f0', '<f4'), ('f1', '<u2')]),
('c', '<f4', (2, ))])
assert_equal(out, want)
d = np.array([(1, 2, 5), (4, 5, 7), (7, 8, 11), (10, 11, 12)],
dtype=[('x', 'i4'), ('y', 'f4'), ('z', 'f8')])
assert_equal(apply_along_fields(np.mean, d),
np.array([8.0 / 3, 16.0 / 3, 26.0 / 3, 11.]))
assert_equal(apply_along_fields(np.mean, d[['x', 'z']]),
np.array([3., 5.5, 9., 11.]))
# check that for uniform field dtypes we get a view, not a copy:
d = np.array([(1, 2, 5), (4, 5, 7), (7, 8, 11), (10, 11, 12)],
dtype=[('x', 'i4'), ('y', 'i4'), ('z', 'i4')])
dd = structured_to_unstructured(d)
ddd = unstructured_to_structured(dd, d.dtype)
assert_(dd.base is d)
assert_(ddd.base is d)
def test_structured_to_unstructured(self):
a = np.zeros(4, dtype=[('a', 'i4'), ('b', 'f4,u2'), ('c', 'f4', 2)])
out = structured_to_unstructured(a)
assert_equal(out, np.zeros((4, 5), dtype='f8'))
b = np.array([(1, 2, 5), (4, 5, 7), (7, 8, 11), (10, 11, 12)],
dtype=[('x', 'i4'), ('y', 'f4'), ('z', 'f8')])
out = np.mean(structured_to_unstructured(b[['x', 'z']]), axis=-1)
assert_equal(out, np.array([3., 5.5, 9., 11.]))
out = np.mean(structured_to_unstructured(b[['x']]), axis=-1)
assert_equal(out, np.array([1., 4., 7., 10.]))
c = np.arange(20).reshape((4, 5))
out = unstructured_to_structured(c, a.dtype)
want = np.array([(0, (1., 2), [3., 4.]), (5, (6., 7), [8., 9.]),
(10, (11., 12), [13., 14.]),
(15, (16., 17), [18., 19.])],
dtype=[('a', 'i4'), ('b', [('f0', 'f4'),
('f1', 'u2')]),
('c', 'f4', (2, ))])
assert_equal(out, want)
d = np.array([(1, 2, 5), (4, 5, 7), (7, 8, 11), (10, 11, 12)],
dtype=[('x', 'i4'), ('y', 'f4'), ('z', 'f8')])
assert_equal(apply_along_fields(np.mean, d),
np.array([8.0 / 3, 16.0 / 3, 26.0 / 3, 11.]))
assert_equal(apply_along_fields(np.mean, d[['x', 'z']]),
np.array([3., 5.5, 9., 11.]))
# check that for uniform field dtypes we get a view, not a copy:
d = np.array([(1, 2, 5), (4, 5, 7), (7, 8, 11), (10, 11, 12)],
dtype=[('x', 'i4'), ('y', 'i4'), ('z', 'i4')])
dd = structured_to_unstructured(d)
ddd = unstructured_to_structured(dd, d.dtype)
assert_(dd.base is d)
assert_(ddd.base is d)
# including uniform fields with subarrays unpacked
d = np.array([(1, [2, 3], [[4, 5], [6, 7]]),
(8, [9, 10], [[11, 12], [13, 14]])],
dtype=[('x0', 'i4'), ('x1', ('i4', 2)),
('x2', ('i4', (2, 2)))])
dd = structured_to_unstructured(d)
ddd = unstructured_to_structured(dd, d.dtype)
assert_(dd.base is d)
assert_(ddd.base is d)
# test that nested fields with identical names don't break anything
point = np.dtype([('x', int), ('y', int)])
triangle = np.dtype([('a', point), ('b', point), ('c', point)])
arr = np.zeros(10, triangle)
res = structured_to_unstructured(arr, dtype=int)
assert_equal(res, np.zeros((10, 6), dtype=int))
def test_structured_to_unstructured(self):
a = np.zeros(4, dtype=[('a', 'i4'), ('b', 'f4,u2'), ('c', 'f4', 2)])
out = structured_to_unstructured(a)
assert_equal(out, np.zeros((4,5), dtype='f8'))
b = np.array([(1, 2, 5), (4, 5, 7), (7, 8 ,11), (10, 11, 12)],
dtype=[('x', 'i4'), ('y', 'f4'), ('z', 'f8')])
out = np.mean(structured_to_unstructured(b[['x', 'z']]), axis=-1)
assert_equal(out, np.array([ 3. , 5.5, 9. , 11. ]))
out = np.mean(structured_to_unstructured(b[['x']]), axis=-1)
assert_equal(out, np.array([ 1. , 4. , 7. , 10. ]))
c = np.arange(20).reshape((4,5))
out = unstructured_to_structured(c, a.dtype)
want = np.array([( 0, ( 1., 2), [ 3., 4.]),
( 5, ( 6., 7), [ 8., 9.]),
(10, (11., 12), [13., 14.]),
(15, (16., 17), [18., 19.])],
dtype=[('a', 'i4'),
('b', [('f0', 'f4'), ('f1', 'u2')]),
('c', 'f4', (2,))])
assert_equal(out, want)
d = np.array([(1, 2, 5), (4, 5, 7), (7, 8 ,11), (10, 11, 12)],
dtype=[('x', 'i4'), ('y', 'f4'), ('z', 'f8')])
assert_equal(apply_along_fields(np.mean, d),
np.array([ 8.0/3, 16.0/3, 26.0/3, 11. ]))
assert_equal(apply_along_fields(np.mean, d[['x', 'z']]),
np.array([ 3. , 5.5, 9. , 11. ]))
# check that for uniform field dtypes we get a view, not a copy:
d = np.array([(1, 2, 5), (4, 5, 7), (7, 8 ,11), (10, 11, 12)],
dtype=[('x', 'i4'), ('y', 'i4'), ('z', 'i4')])
dd = structured_to_unstructured(d)
ddd = unstructured_to_structured(dd, d.dtype)
assert_(dd.base is d)
assert_(ddd.base is d)
# including uniform fields with subarrays unpacked
d = np.array([(1, [2, 3], [[ 4, 5], [ 6, 7]]),
(8, [9, 10], [[11, 12], [13, 14]])],
dtype=[('x0', 'i4'), ('x1', ('i4', 2)), ('x2', ('i4', (2, 2)))])
dd = structured_to_unstructured(d)
ddd = unstructured_to_structured(dd, d.dtype)
assert_(dd.base is d)
assert_(ddd.base is d)
# test that nested fields with identical names don't break anything
point = np.dtype([('x', int), ('y', int)])
triangle = np.dtype([('a', point), ('b', point), ('c', point)])
arr = np.zeros(10, triangle)
res = structured_to_unstructured(arr, dtype=int)
assert_equal(res, np.zeros((10, 6), dtype=int))
def test_structured_to_unstructured(self):
a = np.zeros(4, dtype=[('a', 'i4'), ('b', 'f4,u2'), ('c', 'f4', 2)])
out = structured_to_unstructured(a)
assert_equal(out, np.zeros((4,5), dtype='f8'))
b = np.array([(1, 2, 5), (4, 5, 7), (7, 8 ,11), (10, 11, 12)],
dtype=[('x', 'i4'), ('y', 'f4'), ('z', 'f8')])
out = np.mean(structured_to_unstructured(b[['x', 'z']]), axis=-1)
assert_equal(out, np.array([ 3. , 5.5, 9. , 11. ]))
out = np.mean(structured_to_unstructured(b[['x']]), axis=-1)
assert_equal(out, np.array([ 1. , 4. , 7. , 10. ]))
c = np.arange(20).reshape((4,5))
out = unstructured_to_structured(c, a.dtype)
want = np.array([( 0, ( 1., 2), [ 3., 4.]),
( 5, ( 6., 7), [ 8., 9.]),
(10, (11., 12), [13., 14.]),
(15, (16., 17), [18., 19.])],
dtype=[('a', 'i4'),
('b', [('f0', 'f4'), ('f1', 'u2')]),
('c', 'f4', (2,))])
assert_equal(out, want)
d = np.array([(1, 2, 5), (4, 5, 7), (7, 8 ,11), (10, 11, 12)],
dtype=[('x', 'i4'), ('y', 'f4'), ('z', 'f8')])
assert_equal(apply_along_fields(np.mean, d),
np.array([ 8.0/3, 16.0/3, 26.0/3, 11. ]))
assert_equal(apply_along_fields(np.mean, d[['x', 'z']]),
np.array([ 3. , 5.5, 9. , 11. ]))
# check that for uniform field dtypes we get a view, not a copy:
d = np.array([(1, 2, 5), (4, 5, 7), (7, 8 ,11), (10, 11, 12)],
dtype=[('x', 'i4'), ('y', 'i4'), ('z', 'i4')])
dd = structured_to_unstructured(d)
ddd = unstructured_to_structured(dd, d.dtype)
assert_(dd.base is d)
assert_(ddd.base is d)
# including uniform fields with subarrays unpacked
d = np.array([(1, [2, 3], [[ 4, 5], [ 6, 7]]),
(8, [9, 10], [[11, 12], [13, 14]])],
dtype=[('x0', 'i4'), ('x1', ('i4', 2)),
('x2', ('i4', (2, 2)))])
dd = structured_to_unstructured(d)
ddd = unstructured_to_structured(dd, d.dtype)
assert_(dd.base is d)
assert_(ddd.base is d)
# test that nested fields with identical names don't break anything
point = np.dtype([('x', int), ('y', int)])
triangle = np.dtype([('a', point), ('b', point), ('c', point)])
arr = np.zeros(10, triangle)
res = structured_to_unstructured(arr, dtype=int)
assert_equal(res, np.zeros((10, 6), dtype=int))
# test nested combinations of subarrays and structured arrays, gh-13333
def subarray(dt, shape):
return np.dtype((dt, shape))
def structured(*dts):
return np.dtype([('x{}'.format(i), dt) for i, dt in enumerate(dts)])
def inspect(dt, dtype=None):
arr = np.zeros((), dt)
ret = structured_to_unstructured(arr, dtype=dtype)
backarr = unstructured_to_structured(ret, dt)
return ret.shape, ret.dtype, backarr.dtype
dt = structured(subarray(structured(np.int32, np.int32), 3))
assert_equal(inspect(dt), ((6,), np.int32, dt))
dt = structured(subarray(subarray(np.int32, 2), 2))
assert_equal(inspect(dt), ((4,), np.int32, dt))
dt = structured(np.int32)
assert_equal(inspect(dt), ((1,), np.int32, dt))
dt = structured(np.int32, subarray(subarray(np.int32, 2), 2))
assert_equal(inspect(dt), ((5,), np.int32, dt))
dt = structured()
assert_raises(ValueError, structured_to_unstructured, np.zeros(3, dt))
# these currently don't work, but we may make it work in the future
assert_raises(NotImplementedError, structured_to_unstructured,
np.zeros(3, dt), dtype=np.int32)
assert_raises(NotImplementedError, unstructured_to_structured,
np.zeros((3,0), dtype=np.int32))