Move cbook._check_shape() to _api.check_shape()

timhoffm · timhoffm · commit 9f9ea545301a · 2020-09-18T01:38:19.000+02:00
diff --git a/lib/matplotlib/_api.py b/lib/matplotlib/_api.py
@@ -1,3 +1,4 @@
+import itertools
 
 
 def check_in_list(_values, *, _print_supported_values=True, **kwargs):
@@ -31,3 +32,42 @@ def check_in_list(_values, *, _print_supported_values=True, **kwargs):
                     f"supported values are {', '.join(map(repr, values))}")
             else:
                 raise ValueError(f"{val!r} is not a valid value for {key}")
+
+
+def check_shape(_shape, **kwargs):
+    """
+    For each *key, value* pair in *kwargs*, check that *value* has the shape
+    *_shape*, if not, raise an appropriate ValueError.
+
+    *None* in the shape is treated as a "free" size that can have any length.
+    e.g. (None, 2) -> (N, 2)
+
+    The values checked must be numpy arrays.
+
+    Examples
+    --------
+    To check for (N, 2) shaped arrays
+
+    >>> _api.check_shape((None, 2), arg=arg, other_arg=other_arg)
+    """
+    target_shape = _shape
+    for k, v in kwargs.items():
+        data_shape = v.shape
+
+        if len(target_shape) != len(data_shape) or any(
+                t not in [s, None]
+                for t, s in zip(target_shape, data_shape)
+        ):
+            dim_labels = iter(itertools.chain(
+                'MNLIJKLH',
+                (f"D{i}" for i in itertools.count())))
+            text_shape = ", ".join((str(n)
+                                    if n is not None
+                                    else next(dim_labels)
+                                    for n in target_shape))
+
+            raise ValueError(
+                f"{k!r} must be {len(target_shape)}D "
+                f"with shape ({text_shape}). "
+                f"Your input has shape {v.shape}."
+            )
diff --git a/lib/matplotlib/cbook/__init__.py b/lib/matplotlib/cbook/__init__.py
@@ -2281,45 +2281,6 @@ def type_name(tp):
                     type_name(type(v))))
 
 
-def _check_shape(_shape, **kwargs):
-    """
-    For each *key, value* pair in *kwargs*, check that *value* has the shape
-    *_shape*, if not, raise an appropriate ValueError.
-
-    *None* in the shape is treated as a "free" size that can have any length.
-    e.g. (None, 2) -> (N, 2)
-
-    The values checked must be numpy arrays.
-
-    Examples
-    --------
-    To check for (N, 2) shaped arrays
-
-    >>> _api.check_in_list((None, 2), arg=arg, other_arg=other_arg)
-    """
-    target_shape = _shape
-    for k, v in kwargs.items():
-        data_shape = v.shape
-
-        if len(target_shape) != len(data_shape) or any(
-                t not in [s, None]
-                for t, s in zip(target_shape, data_shape)
-        ):
-            dim_labels = iter(itertools.chain(
-                'MNLIJKLH',
-                (f"D{i}" for i in itertools.count())))
-            text_shape = ", ".join((str(n)
-                                    if n is not None
-                                    else next(dim_labels)
-                                    for n in target_shape))
-
-            raise ValueError(
-                f"{k!r} must be {len(target_shape)}D "
-                f"with shape ({text_shape}). "
-                f"Your input has shape {v.shape}."
-            )
-
-
 def _check_getitem(_mapping, **kwargs):
     """
     *kwargs* must consist of a single *key, value* pair.  If *key* is in
diff --git a/lib/matplotlib/path.py b/lib/matplotlib/path.py
@@ -15,7 +15,7 @@
 import numpy as np
 
 import matplotlib as mpl
-from . import _path, cbook
+from . import _api, _path, cbook
 from .cbook import _to_unmasked_float_array, simple_linear_interpolation
 from .bezier import BezierSegment
 
@@ -129,7 +129,7 @@ def __init__(self, vertices, codes=None, _interpolation_steps=1,
             and codes as read-only arrays.
         """
         vertices = _to_unmasked_float_array(vertices)
-        cbook._check_shape((None, 2), vertices=vertices)
+        _api.check_shape((None, 2), vertices=vertices)
 
         if codes is not None:
             codes = np.asarray(codes, self.code_type)
diff --git a/lib/matplotlib/tests/test_api.py b/lib/matplotlib/tests/test_api.py
@@ -0,0 +1,21 @@
+import re
+
+import numpy as np
+import pytest
+
+from matplotlib import _api
+
+
+@pytest.mark.parametrize('target,test_shape',
+                         [((None, ), (1, 3)),
+                          ((None, 3), (1,)),
+                          ((None, 3), (1, 2)),
+                          ((1, 5), (1, 9)),
+                          ((None, 2, None), (1, 3, 1))
+                          ])
+def test_check_shape(target, test_shape):
+    error_pattern = (f"^'aardvark' must be {len(target)}D.*" +
+                     re.escape(f'has shape {test_shape}'))
+    data = np.zeros(test_shape)
+    with pytest.raises(ValueError, match=error_pattern):
+        _api.check_shape(target, aardvark=data)
diff --git a/lib/matplotlib/tests/test_cbook.py b/lib/matplotlib/tests/test_cbook.py
@@ -1,6 +1,5 @@
 import itertools
 import pickle
-import re
 
 from weakref import ref
 from unittest.mock import patch, Mock
@@ -675,22 +674,6 @@ def divisors(n):
             check(x, rstride=rstride, cstride=cstride)
 
 
-@pytest.mark.parametrize('target,test_shape',
-                         [((None, ), (1, 3)),
-                          ((None, 3), (1,)),
-                          ((None, 3), (1, 2)),
-                          ((1, 5), (1, 9)),
-                          ((None, 2, None), (1, 3, 1))
-                          ])
-def test_check_shape(target, test_shape):
-    error_pattern = (f"^'aardvark' must be {len(target)}D.*" +
-                     re.escape(f'has shape {test_shape}'))
-    data = np.zeros(test_shape)
-    with pytest.raises(ValueError,
-                       match=error_pattern):
-        cbook._check_shape(target, aardvark=data)
-
-
 def test_setattr_cm():
     class A:
 
