Render full numpy numeric names (e.g. numpy.int32)

include/pybind11/numpy.h

@@ -1007,14 +1007,14 @@ struct npy_format_descriptor_name;
 template <typename T>
 struct npy_format_descriptor_name<T, enable_if_t<std::is_integral<T>::value>> {
     static constexpr auto name = _<std::is_same<T, bool>::value>(
-        _("bool"), _<std::is_signed<T>::value>("int", "uint") + _<sizeof(T)*8>()
+        _("bool"), _<std::is_signed<T>::value>("numpy.int", "numpy.uint") + _<sizeof(T)*8>()
     );
 };
 
 template <typename T>
 struct npy_format_descriptor_name<T, enable_if_t<std::is_floating_point<T>::value>> {
     static constexpr auto name = _<std::is_same<T, float>::value || std::is_same<T, double>::value>(
-        _("float") + _<sizeof(T)*8>(), _("longdouble")
+        _("numpy.float") + _<sizeof(T)*8>(), _("numpy.longdouble")
     );
 };
 
@@ -1022,7 +1022,7 @@ template <typename T>
 struct npy_format_descriptor_name<T, enable_if_t<is_complex<T>::value>> {
     static constexpr auto name = _<std::is_same<typename T::value_type, float>::value
                                    || std::is_same<typename T::value_type, double>::value>(
-        _("complex") + _<sizeof(typename T::value_type)*16>(), _("longcomplex")
+        _("numpy.complex") + _<sizeof(typename T::value_type)*16>(), _("numpy.longcomplex")
     );
 };
 

tests/test_eigen.py

@@ -79,15 +79,17 @@ def test_mutator_descriptors():
     m.fixed_mutator_a(zc)
     with pytest.raises(TypeError) as excinfo:
         m.fixed_mutator_r(zc)
-    assert ('(arg0: numpy.ndarray[float32[5, 6], flags.writeable, flags.c_contiguous]) -> None'
+    assert ('(arg0: numpy.ndarray[numpy.float32[5, 6],'
+            ' flags.writeable, flags.c_contiguous]) -> None'
             in str(excinfo.value))
     with pytest.raises(TypeError) as excinfo:
         m.fixed_mutator_c(zr)
-    assert ('(arg0: numpy.ndarray[float32[5, 6], flags.writeable, flags.f_contiguous]) -> None'
+    assert ('(arg0: numpy.ndarray[numpy.float32[5, 6],'
+            ' flags.writeable, flags.f_contiguous]) -> None'
             in str(excinfo.value))
     with pytest.raises(TypeError) as excinfo:
         m.fixed_mutator_a(np.array([[1, 2], [3, 4]], dtype='float32'))
-    assert ('(arg0: numpy.ndarray[float32[5, 6], flags.writeable]) -> None'
+    assert ('(arg0: numpy.ndarray[numpy.float32[5, 6], flags.writeable]) -> None'
             in str(excinfo.value))
     zr.flags.writeable = False
     with pytest.raises(TypeError):
@@ -179,7 +181,7 @@ def test_negative_stride_from_python(msg):
         m.double_threer(second_row)
     assert msg(excinfo.value) == """
         double_threer(): incompatible function arguments. The following argument types are supported:
-            1. (arg0: numpy.ndarray[float32[1, 3], flags.writeable]) -> None
+            1. (arg0: numpy.ndarray[numpy.float32[1, 3], flags.writeable]) -> None
 
         Invoked with: """ + repr(np.array([ 5.,  4.,  3.], dtype='float32'))  # noqa: E501 line too long
 
@@ -187,7 +189,7 @@ def test_negative_stride_from_python(msg):
         m.double_threec(second_col)
     assert msg(excinfo.value) == """
         double_threec(): incompatible function arguments. The following argument types are supported:
-            1. (arg0: numpy.ndarray[float32[3, 1], flags.writeable]) -> None
+            1. (arg0: numpy.ndarray[numpy.float32[3, 1], flags.writeable]) -> None
 
         Invoked with: """ + repr(np.array([ 7.,  4.,  1.], dtype='float32'))  # noqa: E501 line too long
 
@@ -607,17 +609,19 @@ def test_special_matrix_objects():
 
 def test_dense_signature(doc):
     assert doc(m.double_col) == """
-        double_col(arg0: numpy.ndarray[float32[m, 1]]) -> numpy.ndarray[float32[m, 1]]
+        double_col(arg0: numpy.ndarray[numpy.float32[m, 1]]) -> numpy.ndarray[numpy.float32[m, 1]]
     """
     assert doc(m.double_row) == """
-        double_row(arg0: numpy.ndarray[float32[1, n]]) -> numpy.ndarray[float32[1, n]]
-    """
-    assert doc(m.double_complex) == """
-        double_complex(arg0: numpy.ndarray[complex64[m, 1]]) -> numpy.ndarray[complex64[m, 1]]
-    """
-    assert doc(m.double_mat_rm) == """
-        double_mat_rm(arg0: numpy.ndarray[float32[m, n]]) -> numpy.ndarray[float32[m, n]]
+        double_row(arg0: numpy.ndarray[numpy.float32[1, n]]) -> numpy.ndarray[numpy.float32[1, n]]
     """
+    assert doc(m.double_complex) == ("""
+        double_complex(arg0: numpy.ndarray[numpy.complex64[m, 1]])"""
+                                     """ -> numpy.ndarray[numpy.complex64[m, 1]]
+    """)
+    assert doc(m.double_mat_rm) == ("""
+        double_mat_rm(arg0: numpy.ndarray[numpy.float32[m, n]])"""
+                                    """ -> numpy.ndarray[numpy.float32[m, n]]
+    """)
 
 
 def test_named_arguments():
@@ -654,10 +658,10 @@ def test_sparse():
 @pytest.requires_eigen_and_scipy
 def test_sparse_signature(doc):
     assert doc(m.sparse_copy_r) == """
-        sparse_copy_r(arg0: scipy.sparse.csr_matrix[float32]) -> scipy.sparse.csr_matrix[float32]
+        sparse_copy_r(arg0: scipy.sparse.csr_matrix[numpy.float32]) -> scipy.sparse.csr_matrix[numpy.float32]
     """  # noqa: E501 line too long
     assert doc(m.sparse_copy_c) == """
-        sparse_copy_c(arg0: scipy.sparse.csc_matrix[float32]) -> scipy.sparse.csc_matrix[float32]
+        sparse_copy_c(arg0: scipy.sparse.csc_matrix[numpy.float32]) -> scipy.sparse.csc_matrix[numpy.float32]
     """  # noqa: E501 line too long
 
 

tests/test_numpy_array.py

@@ -286,13 +286,13 @@ def test_overload_resolution(msg):
         m.overloaded("not an array")
     assert msg(excinfo.value) == """
         overloaded(): incompatible function arguments. The following argument types are supported:
-            1. (arg0: numpy.ndarray[float64]) -> str
-            2. (arg0: numpy.ndarray[float32]) -> str
-            3. (arg0: numpy.ndarray[int32]) -> str
-            4. (arg0: numpy.ndarray[uint16]) -> str
-            5. (arg0: numpy.ndarray[int64]) -> str
-            6. (arg0: numpy.ndarray[complex128]) -> str
-            7. (arg0: numpy.ndarray[complex64]) -> str
+            1. (arg0: numpy.ndarray[numpy.float64]) -> str
+            2. (arg0: numpy.ndarray[numpy.float32]) -> str
+            3. (arg0: numpy.ndarray[numpy.int32]) -> str
+            4. (arg0: numpy.ndarray[numpy.uint16]) -> str
+            5. (arg0: numpy.ndarray[numpy.int64]) -> str
+            6. (arg0: numpy.ndarray[numpy.complex128]) -> str
+            7. (arg0: numpy.ndarray[numpy.complex64]) -> str
 
         Invoked with: 'not an array'
     """
@@ -307,8 +307,8 @@ def test_overload_resolution(msg):
     assert m.overloaded3(np.array([1], dtype='intc')) == 'int'
     expected_exc = """
         overloaded3(): incompatible function arguments. The following argument types are supported:
-            1. (arg0: numpy.ndarray[int32]) -> str
-            2. (arg0: numpy.ndarray[float64]) -> str
+            1. (arg0: numpy.ndarray[numpy.int32]) -> str
+            2. (arg0: numpy.ndarray[numpy.float64]) -> str
 
         Invoked with: """
 

tests/test_numpy_vectorize.py

@@ -109,7 +109,7 @@ def test_type_selection():
 
 def test_docs(doc):
     assert doc(m.vectorized_func) == """
-        vectorized_func(arg0: numpy.ndarray[int32], arg1: numpy.ndarray[float32], arg2: numpy.ndarray[float64]) -> object
+        vectorized_func(arg0: numpy.ndarray[numpy.int32], arg1: numpy.ndarray[numpy.float32], arg2: numpy.ndarray[numpy.float64]) -> object
     """  # noqa: E501 line too long
 
 
@@ -160,12 +160,12 @@ def test_passthrough_arguments(doc):
     assert doc(m.vec_passthrough) == (
         "vec_passthrough(" + ", ".join([
             "arg0: float",
-            "arg1: numpy.ndarray[float64]",
-            "arg2: numpy.ndarray[float64]",
-            "arg3: numpy.ndarray[int32]",
+            "arg1: numpy.ndarray[numpy.float64]",
+            "arg2: numpy.ndarray[numpy.float64]",
+            "arg3: numpy.ndarray[numpy.int32]",
             "arg4: int",
             "arg5: m.numpy_vectorize.NonPODClass",
-            "arg6: numpy.ndarray[float64]"]) + ") -> object")
+            "arg6: numpy.ndarray[numpy.float64]"]) + ") -> object")
 
     b = np.array([[10, 20, 30]], dtype='float64')
     c = np.array([100, 200])  # NOT a vectorized argument