Remove mlab.rec2txt

dstansby · dstansby · commit f1c3ee338daa · 2018-09-29T11:05:07.000+01:00
diff --git a/doc/api/next_api_changes/2018-09-18-DS.rst b/doc/api/next_api_changes/2018-09-18-DS.rst
@@ -40,4 +40,5 @@ in Matplotlib 2.2 has been removed. See below for a list:
 - `mlab.poly_below`
 - `mlab.inside_poly`
 - `mlab.rec2csv` (use numpy.recarray.tofile instead)
+- `mlab.rec2text` (use numpy.recarray.tofile instead)
 - `mlab.donothing_callback`
diff --git a/lib/matplotlib/mlab.py b/lib/matplotlib/mlab.py
@@ -2320,127 +2320,6 @@ def csvformat_factory(format):
     return format
 
 
-@cbook.deprecated("2.2", alternative='numpy.recarray.tofile')
-def rec2txt(r, header=None, padding=3, precision=3, fields=None):
-    """
-    Returns a textual representation of a record array.
-
-    Parameters
-    ----------
-    r: numpy recarray
-
-    header: list
-        column headers
-
-    padding:
-        space between each column
-
-    precision: number of decimal places to use for floats.
-        Set to an integer to apply to all floats.  Set to a
-        list of integers to apply precision individually.
-        Precision for non-floats is simply ignored.
-
-    fields : list
-        If not None, a list of field names to print.  fields
-        can be a list of strings like ['field1', 'field2'] or a single
-        comma separated string like 'field1,field2'
-
-    Examples
-    --------
-
-    For ``precision=[0,2,3]``, the output is ::
-
-      ID    Price   Return
-      ABC   12.54    0.234
-      XYZ    6.32   -0.076
-    """
-
-    if fields is not None:
-        r = rec_keep_fields(r, fields)
-
-    if cbook.is_numlike(precision):
-        precision = [precision]*len(r.dtype)
-
-    def get_type(item, atype=int):
-        tdict = {None: int, int: float, float: str}
-        try:
-            atype(str(item))
-        except Exception:
-            return get_type(item, tdict[atype])
-        return atype
-
-    def get_justify(colname, column, precision):
-        ntype = column.dtype
-
-        if np.issubdtype(ntype, np.character):
-            fixed_width = int(ntype.str[2:])
-            length = max(len(colname), fixed_width)
-            return 0, length+padding, "%s"  # left justify
-
-        if np.issubdtype(ntype, np.integer):
-            length = max(len(colname),
-                         np.max(list(map(len, list(map(str, column))))))
-            return 1, length+padding, "%d"  # right justify
-
-        if np.issubdtype(ntype, np.floating):
-            fmt = "%." + str(precision) + "f"
-            length = max(
-                len(colname),
-                np.max(list(map(len, list(map(lambda x: fmt % x, column)))))
-            )
-            return 1, length+padding, fmt   # right justify
-
-        return (0,
-                max(len(colname),
-                    np.max(list(map(len, list(map(str, column))))))+padding,
-                "%s")
-
-    if header is None:
-        header = r.dtype.names
-
-    justify_pad_prec = [get_justify(header[i], r.__getitem__(colname),
-                                    precision[i])
-                        for i, colname in enumerate(r.dtype.names)]
-
-    justify_pad_prec_spacer = []
-    for i in range(len(justify_pad_prec)):
-        just, pad, prec = justify_pad_prec[i]
-        if i == 0:
-            justify_pad_prec_spacer.append((just, pad, prec, 0))
-        else:
-            pjust, ppad, pprec = justify_pad_prec[i-1]
-            if pjust == 0 and just == 1:
-                justify_pad_prec_spacer.append((just, pad-padding, prec, 0))
-            elif pjust == 1 and just == 0:
-                justify_pad_prec_spacer.append((just, pad, prec, padding))
-            else:
-                justify_pad_prec_spacer.append((just, pad, prec, 0))
-
-    def format(item, just_pad_prec_spacer):
-        just, pad, prec, spacer = just_pad_prec_spacer
-        if just == 0:
-            return spacer*' ' + str(item).ljust(pad)
-        else:
-            if get_type(item) == float:
-                item = (prec % float(item))
-            elif get_type(item) == int:
-                item = (prec % int(item))
-
-            return item.rjust(pad)
-
-    textl = []
-    textl.append(''.join([format(colitem, justify_pad_prec_spacer[j])
-                          for j, colitem in enumerate(header)]))
-    for i, row in enumerate(r):
-        textl.append(''.join([format(colitem, justify_pad_prec_spacer[j])
-                              for j, colitem in enumerate(row)]))
-        if i == 0:
-            textl[0] = textl[0].rstrip()
-
-    text = os.linesep.join(textl)
-    return text
-
-
 class GaussianKDE(object):
     """
     Representation of a kernel-density estimate using Gaussian kernels.
diff --git a/lib/matplotlib/tests/test_mlab.py b/lib/matplotlib/tests/test_mlab.py
@@ -193,20 +193,6 @@ def test_csv2rec_dates(tempcsv, input, kwargs):
     assert_array_equal(array['a'].tolist(), expected)
 
 
-def test_rec2txt_basic():
-    a = np.array([(1.0, 2, 'foo', 'bing'),
-                  (2.0, 3, 'bar', 'blah')],
-                 dtype=np.dtype([('x', np.float32),
-                                 ('y', np.int8),
-                                 ('s', str, 3),
-                                 ('s2', str, 4)]))
-    truth = ('       x   y   s     s2\n'
-             '   1.000   2   foo   bing   \n'
-             '   2.000   3   bar   blah   ').splitlines()
-    with pytest.warns(MatplotlibDeprecationWarning):
-        assert mlab.rec2txt(a).splitlines() == truth
-
-
 class TestWindow(object):
     def setup(self):
         np.random.seed(0)
