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ENH: Allow genfromtxt to unpack structured arrays #16650

Merged
merged 13 commits into from Sep 11, 2020
23 changes: 18 additions & 5 deletions numpy/lib/npyio.py
Expand Up @@ -837,8 +837,9 @@ def loadtxt(fname, dtype=float, comments='#', delimiter=None,
fourth column the same way as ``usecols = (3,)`` would.
unpack : bool, optional
If True, the returned array is transposed, so that arguments may be
unpacked using ``x, y, z = loadtxt(...)``. When used with a structured
data-type, arrays are returned for each field. Default is False.
unpacked using ``x, y, z = loadtxt(...)``. When used with a
structured data-type, arrays are returned for each field.
Default is False.
ndmin : int, optional
The returned array will have at least `ndmin` dimensions.
Otherwise mono-dimensional axes will be squeezed.
Expand Down Expand Up @@ -1631,7 +1632,9 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None,
If 'lower', field names are converted to lower case.
unpack : bool, optional
If True, the returned array is transposed, so that arguments may be
unpacked using ``x, y, z = loadtxt(...)``
unpacked using ``x, y, z = genfromtxt(...)``. When used with a
structured data-type, arrays are returned for each field.
Default is False.
usemask : bool, optional
If True, return a masked array.
If False, return a regular array.
Expand Down Expand Up @@ -2242,9 +2245,19 @@ def encode_unicode_cols(row_tup):
if usemask:
output = output.view(MaskedArray)
output._mask = outputmask
output = np.squeeze(output)
if unpack:
return output.squeeze().T
return output.squeeze()
if names is None:
return output.T
elif len(names) == 1:
# squeeze single-name dtypes too
# squeeze single-name dtypes too
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return output[names[0]]
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else:
# For structured arrays with multiple fields,
# return an array for each field.
return [output[field] for field in names]
return output


def ndfromtxt(fname, **kwargs):
Expand Down
47 changes: 46 additions & 1 deletion numpy/lib/tests/test_io.py
Expand Up @@ -1011,7 +1011,7 @@ def test_empty_field_after_tab(self):
a = np.array([b'start ', b' ', b''])
assert_array_equal(x['comment'], a)

def test_structure_unpack(self):
def test_unpack_structured(self):
txt = TextIO("M 21 72\nF 35 58")
dt = {'names': ('a', 'b', 'c'), 'formats': ('|S1', '<i4', '<f4')}
a, b, c = np.loadtxt(txt, dtype=dt, unpack=True)
Expand Down Expand Up @@ -2343,6 +2343,51 @@ def test_auto_dtype_largeint(self):
assert_equal(test['f1'], 17179869184)
assert_equal(test['f2'], 1024)

def test_unpack_structured(self):
# Regression test for gh-4341
# Unpacking should work on structured arrays
txt = TextIO("M 21 72\nF 35 58")
dt = {'names': ('a', 'b', 'c'), 'formats': ('|S1', '<i4', '<f4')}
a, b, c = np.genfromtxt(txt, dtype=dt, unpack=True)
assert_(a.dtype.str == '|S1')
assert_(b.dtype.str == '<i4')
assert_(c.dtype.str == '<f4')
assert_array_equal(a, np.array([b'M', b'F']))
assert_array_equal(b, np.array([21, 35]))
assert_array_equal(c, np.array([72., 58.]))

def test_unpack_auto_dtype(self):
# Regression test for gh-4341
# Unpacking should work when dtype=None
txt = TextIO("M 21 72.\nF 35 58.")
expected = (np.array(["M", "F"]), np.array([21, 35]), np.array([72., 58.]))
test = np.genfromtxt(txt, dtype=None, unpack=True, encoding=None)
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for arr, result in zip(expected, test):
assert_array_equal(arr, result)
assert_equal(arr.dtype, result.dtype)

def test_unpack_single_name(self):
# Regression test for gh-4341
# Unpacking should work when structured dtype has only one field
txt = TextIO("21\n35")
dt = {'names': ('a',), 'formats': ('<i4',)}
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expected = np.array([21, 35], dtype=np.int32)
test = np.genfromtxt(txt, dtype=dt, unpack=True)
assert_array_equal(expected, test)
assert_equal(expected.dtype, test.dtype)

def test_squeeze_scalar(self):
# Regression test for gh-4341
# Unpacking a scalar should give zero-dim output,
# even if dtype is structured
txt = TextIO("1")
dt = {'names': ('a',), 'formats': ('<i4',)}
expected = np.array((1,), dtype=np.int32)
test = np.genfromtxt(txt, dtype=dt, unpack=True)
assert_array_equal(expected, test)
assert_equal((), test.shape)
assert_equal(expected.dtype, test.dtype)


class TestPathUsage:
# Test that pathlib.Path can be used
Expand Down