ENH: Allow genfromtxt to unpack structured arrays (#16650)

* ENH: Allow genfromtxt to unpack structured arrays

genfromtxt failed to transpose output when
unpack=True and `dtype` was structured (or None).
This patch resolves the issue by
returning a list of arrays, as in `loadtxt`.

Co-authored-by: Matti Picus <matti.picus@gmail.com>
Co-authored-by: Eric Wieser <wieser.eric@gmail.com>
Co-authored-by: Sebastian Berg <sebastian@sipsolutions.net>
Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>

3 files changed, 79 insertions, 6 deletions

diff --git a/doc/release/upcoming_changes/16650.compatibility.rst b/doc/release/upcoming_changes/16650.compatibility.rst
new file mode 100644
index 000000000..653232355
--- /dev/null
+++ b/doc/release/upcoming_changes/16650.compatibility.rst
@@ -0,0 +1,16 @@
+`numpy.genfromtxt` now correctly unpacks structured arrays
+----------------------------------------------------------
+Previously, `numpy.genfromtxt` failed to unpack if it was called with
+``unpack=True`` and a structured datatype was passed to the ``dtype`` argument
+(or ``dtype=None`` was passed and a structured datatype was inferred).
+For example::
+
+    >>> data = StringIO("21 58.0\n35 72.0")
+    >>> np.genfromtxt(data, dtype=None, unpack=True)
+    array([(21, 58.), (35, 72.)], dtype=[('f0', '<i8'), ('f1', '<f8')])
+
+Structured arrays will now correctly unpack into a list of arrays,
+one for each column::
+
+    >>> np.genfromtxt(data, dtype=None, unpack=True)
+    [array([21, 35]), array([58., 72.])]
diff --git a/numpy/lib/npyio.py b/numpy/lib/npyio.py
index c6a19fda9..90e16643c 100644
--- a/numpy/lib/npyio.py
+++ b/numpy/lib/npyio.py
@@ -815,8 +815,9 @@ 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.
@@ -1640,7 +1641,9 @@ 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.
@@ -2269,9 +2272,18 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None,
     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
+            return output[names[0]]
+        else:
+            # For structured arrays with multiple fields,
+            # return an array for each field.
+            return [output[field] for field in names]
+    return output
 
 
 _genfromtxt_with_like = array_function_dispatch(
diff --git a/numpy/lib/tests/test_io.py b/numpy/lib/tests/test_io.py
index 38d698df4..aa4499764 100644
--- a/numpy/lib/tests/test_io.py
+++ b/numpy/lib/tests/test_io.py
@@ -1026,7 +1026,7 @@ class TestLoadTxt(LoadTxtBase):
         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)
@@ -2358,6 +2358,51 @@ M   33  21.99
         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_equal(a.dtype, np.dtype('S1'))
+        assert_equal(b.dtype, np.dtype('i4'))
+        assert_equal(c.dtype, np.dtype('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="utf-8")
+        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',)}
+        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