Stop using deprecated aliases of builtin types (#3997)

* Stopped using deprecated aliases of builtin types. This is required to avoid warnings starting with NumPy 1.20.0. * Update lib/iris/tests/test_cell.py Co-authored-by: Bill Little <[email protected]> * Update lib/iris/tests/test_cell.py Co-authored-by: Bill Little <[email protected]> * Updated whatsnew. Co-authored-by: Bill Little <[email protected]>
SciTools · Feb 16, 2021 · 343d329 · 343d329
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diff --git a/docs/src/whatsnew/latest.rst b/docs/src/whatsnew/latest.rst
@@ -112,11 +112,15 @@ This document explains the changes made to Iris for this release
 #. `@bjlittle`_ enabled `cirrus-ci`_ compute credits for non-draft pull-requests
    from collaborators targeting the Iris ``master`` branch. (:pull:`4007`)
 
+#. `@akuhnregnier`_ replaced `deprecated numpy 1.20 aliases for builtin types`_.
+   (:pull:`3997`)
+
 
 .. comment
     Whatsnew author names (@github name) in alphabetical order. Note that,
     core dev names are automatically included by the common_links.inc:
 
+.. _@akuhnregnier: https://github.com/akuhnregnier
 .. _@gcaria: https://github.com/gcaria
 .. _@MHBalsmeier: https://github.com/MHBalsmeier
 
@@ -125,6 +129,7 @@ This document explains the changes made to Iris for this release
     Whatsnew resources in alphabetical order:
 
 .. _abstract base class: https://docs.python.org/3/library/abc.html
+.. _deprecated numpy 1.20 aliases for builtin types: https://numpy.org/doc/1.20/release/1.20.0-notes.html#using-the-aliases-of-builtin-types-like-np-int-is-deprecated
 .. _GitHub: https://github.com/SciTools/iris/issues/new/choose
 .. _Met Office: https://www.metoffice.gov.uk/
 .. _numpy: https://numpy.org/doc/stable/release/1.20.0-notes.html

diff --git a/lib/iris/_constraints.py b/lib/iris/_constraints.py
@@ -294,7 +294,7 @@ def call_func(c):
             except TypeError:
                 try_quick = False
         if try_quick:
-            r = np.zeros(coord.shape, dtype=np.bool)
+            r = np.zeros(coord.shape, dtype=np.bool_)
             if coord.cell(i) == self._coord_thing:
                 r[i] = True
         else:

diff --git a/lib/iris/analysis/__init__.py b/lib/iris/analysis/__init__.py
@@ -1454,7 +1454,7 @@ def interp_order(length):
     slices[-1] = endslice
     slices = tuple(slices)  # Numpy>=1.16 : index with tuple, *not* list.
 
-    if isinstance(array.dtype, np.float):
+    if isinstance(array.dtype, np.float64):
         data = array[slices]
     else:
         # Cast non-float data type.

diff --git a/lib/iris/analysis/_regrid.py b/lib/iris/analysis/_regrid.py
@@ -696,7 +696,7 @@ def _regrid(
 
         if ma.isMaskedArray(src_data):
             data = ma.empty(shape, dtype=dtype)
-            data.mask = np.zeros(data.shape, dtype=np.bool)
+            data.mask = np.zeros(data.shape, dtype=np.bool_)
         else:
             data = np.empty(shape, dtype=dtype)
 

diff --git a/lib/iris/experimental/regrid.py b/lib/iris/experimental/regrid.py
@@ -498,9 +498,9 @@ def _regrid_area_weighted_array(src_data, x_dim, y_dim, weights_info, mdtol=0):
     # Flag to indicate whether the original data was a masked array.
     src_masked = src_data.mask.any() if ma.isMaskedArray(src_data) else False
     if src_masked:
-        src_area_masks = np.full(src_areas_shape, True, dtype=np.bool)
+        src_area_masks = np.full(src_areas_shape, True, dtype=np.bool_)
     else:
-        new_data_mask = np.full(new_shape, False, dtype=np.bool)
+        new_data_mask = np.full(new_shape, False, dtype=np.bool_)
 
     # Axes of data over which the weighted mean is calculated.
     axis = (y_dim, x_dim)

diff --git a/lib/iris/fileformats/_ff.py b/lib/iris/fileformats/_ff.py
@@ -816,7 +816,7 @@ def __iter__(self):
         return pp._interpret_fields(self._extract_field())
 
 
-def _parse_binary_stream(file_like, dtype=np.float, count=-1):
+def _parse_binary_stream(file_like, dtype=np.float64, count=-1):
     """
     Replacement :func:`numpy.fromfile` due to python3 performance issues.
 

diff --git a/lib/iris/fileformats/pp.py b/lib/iris/fileformats/pp.py
@@ -752,7 +752,7 @@ def _data_bytes_to_shaped_array(
             # However, we still mask any MDI values in the array (below).
             pass
         else:
-            land_mask = mask.data.astype(np.bool)
+            land_mask = mask.data.astype(np.bool_)
             sea_mask = ~land_mask
             new_data = np.ma.masked_all(land_mask.shape)
             new_data.fill_value = mdi

diff --git a/lib/iris/fileformats/pp_load_rules.py b/lib/iris/fileformats/pp_load_rules.py
@@ -580,7 +580,7 @@ def _epoch_date_hours(epoch_hours_unit, datetime):
     # numpy.float64.  The behaviour of round is to recast this to an
     # int, which is not the desired behaviour for PP files.
     # So, cast the answer to numpy.float_ to be safe.
-    epoch_hours = np.float_(epoch_hours_unit.date2num(datetime))
+    epoch_hours = np.float64(epoch_hours_unit.date2num(datetime))
 
     if days_offset is not None:
         # Correct for any modifications to achieve a valid date.

diff --git a/lib/iris/tests/__init__.py b/lib/iris/tests/__init__.py
@@ -483,26 +483,26 @@ def assertDataAlmostEqual(self, data, reference_filename, **kwargs):
                         stats.get("max", 0.0),
                         stats.get("min", 0.0),
                     ),
-                    dtype=np.float_,
+                    dtype=np.float64,
                 )
                 if math.isnan(stats.get("mean", 0.0)):
                     self.assertTrue(math.isnan(data.mean()))
                 else:
                     data_stats = np.array(
                         (data.mean(), data.std(), data.max(), data.min()),
-                        dtype=np.float_,
+                        dtype=np.float64,
                     )
                     self.assertArrayAllClose(nstats, data_stats, **kwargs)
         else:
             self._ensure_folder(reference_path)
             stats = collections.OrderedDict(
                 [
-                    ("std", np.float_(data.std())),
-                    ("min", np.float_(data.min())),
-                    ("max", np.float_(data.max())),
+                    ("std", np.float64(data.std())),
+                    ("min", np.float64(data.min())),
+                    ("max", np.float64(data.max())),
                     ("shape", data.shape),
                     ("masked", ma.is_masked(data)),
-                    ("mean", np.float_(data.mean())),
+                    ("mean", np.float64(data.mean())),
                 ]
             )
             with open(reference_path, "w") as reference_file:

diff --git a/lib/iris/tests/experimental/regrid/test_regrid_conservative_via_esmpy.py b/lib/iris/tests/experimental/regrid/test_regrid_conservative_via_esmpy.py
@@ -675,7 +675,7 @@ def test_rotated(self):
                 [100, 100, 100, 100, 100, 100, 100, 100, 100],
                 [100, 100, 100, 100, 100, 100, 100, 100, 100],
             ],
-            dtype=np.float,
+            dtype=np.float64,
         )
 
         c1_areasum = _cube_area_sum(c1)
@@ -715,7 +715,7 @@ def test_rotated(self):
                 [100, 100, 199, 199, 100],
                 [100, 100, 199, 199, 199],
             ],
-            dtype=np.float,
+            dtype=np.float64,
         )
         c2_areasum = _cube_area_sum(c2)
 
@@ -770,7 +770,7 @@ def test_missing_data_rotated(self):
                     [100, 100, 100, 100, 100, 100, 100, 100, 100],
                     [100, 100, 100, 100, 100, 100, 100, 100, 100],
                 ],
-                dtype=np.float,
+                dtype=np.float64,
             )
 
             if do_add_missing:

diff --git a/lib/iris/tests/test_cell.py b/lib/iris/tests/test_cell.py
@@ -130,15 +130,15 @@ class Terry:
         self.assertEqual(self.d.__ne__(Terry()), NotImplemented)
 
     def test_numpy_int_equality(self):
-        dtypes = (np.int, np.int16, np.int32, np.int64)
+        dtypes = (np.int_, np.int16, np.int32, np.int64)
         for dtype in dtypes:
             val = dtype(3)
             cell = iris.coords.Cell(val, None)
             self.assertEqual(cell, val)
 
     def test_numpy_float_equality(self):
         dtypes = (
-            np.float,
+            np.float_,
             np.float16,
             np.float32,
             np.float64,

diff --git a/lib/iris/tests/test_concatenate.py b/lib/iris/tests/test_concatenate.py
@@ -415,7 +415,7 @@ def test_concat_masked_2x2d(self):
         self.assertEqual(result[0].shape, (2, 4))
         mask = np.array(
             [[True, False, False, True], [False, True, True, False]],
-            dtype=np.bool,
+            dtype=np.bool_,
         )
         self.assertArrayEqual(result[0].data.mask, mask)
 
@@ -436,7 +436,7 @@ def test_concat_masked_2y2d(self):
         self.assertEqual(result[0].shape, (4, 2))
         mask = np.array(
             [[True, False], [False, True], [False, True], [True, False]],
-            dtype=np.bool,
+            dtype=np.bool_,
         )
         self.assertArrayEqual(result[0].data.mask, mask)
 
@@ -458,7 +458,7 @@ def test_concat_masked_2y2d_with_concrete_and_lazy(self):
         self.assertEqual(result[0].shape, (4, 2))
         mask = np.array(
             [[True, False], [False, True], [False, True], [True, False]],
-            dtype=np.bool,
+            dtype=np.bool_,
         )
         self.assertArrayEqual(result[0].data.mask, mask)
 
@@ -480,7 +480,7 @@ def test_concat_masked_2y2d_with_lazy_and_concrete(self):
         self.assertEqual(result[0].shape, (4, 2))
         mask = np.array(
             [[True, False], [False, True], [False, True], [True, False]],
-            dtype=np.bool,
+            dtype=np.bool_,
         )
         self.assertArrayEqual(result[0].data.mask, mask)
 

diff --git a/lib/iris/tests/test_merge.py b/lib/iris/tests/test_merge.py
@@ -468,7 +468,7 @@ def _make_cube(self, a, b, c, d, data=0):
         )
 
         for name, value in zip(["a", "b", "c", "d"], [a, b, c, d]):
-            dtype = np.str if isinstance(value, str) else np.float32
+            dtype = np.str_ if isinstance(value, str) else np.float32
             cube.add_aux_coord(
                 AuxCoord(
                     np.array([value], dtype=dtype), long_name=name, units="1"
@@ -613,7 +613,7 @@ def _make_cube(self, a, b, data=0, a_dim=False, b_dim=False):
         )
 
         for name, value, dim in zip(["a", "b"], [a, b], [a_dim, b_dim]):
-            dtype = np.str if isinstance(value, str) else np.float32
+            dtype = np.str_ if isinstance(value, str) else np.float32
             ctype = DimCoord if dim else AuxCoord
             coord = ctype(
                 np.array([value], dtype=dtype), long_name=name, units="1"

diff --git a/lib/iris/tests/unit/analysis/cartography/test_rotate_winds.py b/lib/iris/tests/unit/analysis/cartography/test_rotate_winds.py
@@ -431,7 +431,7 @@ def test_rotated_to_osgb(self):
                 [1, 1, 1, 1, 1, 0, 0, 1, 1, 1],
                 [1, 1, 1, 1, 1, 0, 0, 1, 1, 1],
             ],
-            np.bool,
+            np.bool_,
         )
         self.assertArrayEqual(expected_mask, ut.data.mask)
         self.assertArrayEqual(expected_mask, vt.data.mask)

diff --git a/lib/iris/tests/unit/analysis/regrid/test_RectilinearRegridder.py b/lib/iris/tests/unit/analysis/regrid/test_RectilinearRegridder.py
@@ -266,7 +266,7 @@ def _regrid(self, data, method, extrapolation_mode=None):
     def test_default_ndarray(self):
         # NaN           -> NaN
         # Extrapolated  -> NaN
-        data = np.arange(12, dtype=np.float).reshape(3, 4)
+        data = np.arange(12, dtype=np.float64).reshape(3, 4)
         data[0, 0] = np.nan
         for method in self.methods:
             result = self._regrid(data, method)
@@ -278,7 +278,7 @@ def test_default_maskedarray(self):
         # NaN           -> NaN
         # Extrapolated  -> Masked
         # Masked        -> Masked
-        data = ma.arange(12, dtype=np.float).reshape(3, 4)
+        data = ma.arange(12, dtype=np.float64).reshape(3, 4)
         data[0, 0] = np.nan
         data[2, 3] = ma.masked
         for method in self.methods:
@@ -293,7 +293,7 @@ def test_default_maskedarray_none_masked(self):
         # NaN           -> NaN
         # Extrapolated  -> Masked
         # Masked        -> N/A
-        data = ma.arange(12, dtype=np.float).reshape(3, 4)
+        data = ma.arange(12, dtype=np.float64).reshape(3, 4)
         data[0, 0] = np.nan
         for method in self.methods:
             result = self._regrid(data, method)
@@ -307,7 +307,7 @@ def test_default_maskedarray_none_masked_expanded(self):
         # NaN           -> NaN
         # Extrapolated  -> Masked
         # Masked        -> N/A
-        data = ma.arange(12, dtype=np.float).reshape(3, 4)
+        data = ma.arange(12, dtype=np.float64).reshape(3, 4)
         # Make sure the mask has been expanded
         data.mask = False
         data[0, 0] = np.nan
@@ -322,7 +322,7 @@ def test_default_maskedarray_none_masked_expanded(self):
     def test_method_ndarray(self):
         # NaN           -> NaN
         # Extrapolated  -> linear
-        data = np.arange(12, dtype=np.float).reshape(3, 4)
+        data = np.arange(12, dtype=np.float64).reshape(3, 4)
         data[0, 0] = np.nan
         for method in self.methods:
             result = self._regrid(data, method, "extrapolate")
@@ -334,7 +334,7 @@ def test_method_maskedarray(self):
         # NaN           -> NaN
         # Extrapolated  -> linear
         # Masked        -> Masked
-        data = ma.arange(12, dtype=np.float).reshape(3, 4)
+        data = ma.arange(12, dtype=np.float64).reshape(3, 4)
         data[0, 0] = np.nan
         data[2, 3] = ma.masked
         for method in self.methods:
@@ -348,7 +348,7 @@ def test_method_maskedarray(self):
     def test_nan_ndarray(self):
         # NaN           -> NaN
         # Extrapolated  -> NaN
-        data = np.arange(12, dtype=np.float).reshape(3, 4)
+        data = np.arange(12, dtype=np.float64).reshape(3, 4)
         data[0, 0] = np.nan
         for method in self.methods:
             result = self._regrid(data, method, "nan")
@@ -360,7 +360,7 @@ def test_nan_maskedarray(self):
         # NaN           -> NaN
         # Extrapolated  -> NaN
         # Masked        -> Masked
-        data = ma.arange(12, dtype=np.float).reshape(3, 4)
+        data = ma.arange(12, dtype=np.float64).reshape(3, 4)
         data[0, 0] = np.nan
         data[2, 3] = ma.masked
         for method in self.methods:
@@ -373,15 +373,15 @@ def test_nan_maskedarray(self):
 
     def test_error_ndarray(self):
         # Values irrelevant - the function raises an error.
-        data = np.arange(12, dtype=np.float).reshape(3, 4)
+        data = np.arange(12, dtype=np.float64).reshape(3, 4)
         data[0, 0] = np.nan
         for method in self.methods:
             with self.assertRaisesRegex(ValueError, "out of bounds"):
                 self._regrid(data, method, "error")
 
     def test_error_maskedarray(self):
         # Values irrelevant - the function raises an error.
-        data = ma.arange(12, dtype=np.float).reshape(3, 4)
+        data = ma.arange(12, dtype=np.float64).reshape(3, 4)
         data[0, 0] = np.nan
         data[2, 3] = ma.masked
         for method in self.methods:
@@ -392,7 +392,7 @@ def test_mask_ndarray(self):
         # NaN           -> NaN
         # Extrapolated  -> Masked (this is different from all the other
         #                          modes)
-        data = np.arange(12, dtype=np.float).reshape(3, 4)
+        data = np.arange(12, dtype=np.float64).reshape(3, 4)
         data[0, 0] = np.nan
         for method in self.methods:
             result = self._regrid(data, method, "mask")
@@ -406,7 +406,7 @@ def test_mask_maskedarray(self):
         # NaN           -> NaN
         # Extrapolated  -> Masked
         # Masked        -> Masked
-        data = ma.arange(12, dtype=np.float).reshape(3, 4)
+        data = ma.arange(12, dtype=np.float64).reshape(3, 4)
         data[0, 0] = np.nan
         data[2, 3] = ma.masked
         for method in self.methods:
@@ -420,7 +420,7 @@ def test_mask_maskedarray(self):
     def test_nanmask_ndarray(self):
         # NaN           -> NaN
         # Extrapolated  -> NaN
-        data = np.arange(12, dtype=np.float).reshape(3, 4)
+        data = np.arange(12, dtype=np.float64).reshape(3, 4)
         data[0, 0] = np.nan
         for method in self.methods:
             result = self._regrid(data, method, "nanmask")
@@ -432,7 +432,7 @@ def test_nanmask_maskedarray(self):
         # NaN           -> NaN
         # Extrapolated  -> Masked
         # Masked        -> Masked
-        data = ma.arange(12, dtype=np.float).reshape(3, 4)
+        data = ma.arange(12, dtype=np.float64).reshape(3, 4)
         data[0, 0] = np.nan
         data[2, 3] = ma.masked
         for method in self.methods:
@@ -444,7 +444,7 @@ def test_nanmask_maskedarray(self):
             self.assertMaskedArrayEqual(result, expected)
 
     def test_invalid(self):
-        data = np.arange(12, dtype=np.float).reshape(3, 4)
+        data = np.arange(12, dtype=np.float64).reshape(3, 4)
         emsg = "Invalid extrapolation mode"
         for method in self.methods:
             with self.assertRaisesRegex(ValueError, emsg):

diff --git a/lib/iris/tests/unit/aux_factory/test_OceanSFactory.py b/lib/iris/tests/unit/aux_factory/test_OceanSFactory.py
@@ -195,12 +195,12 @@ def setUp(self):
             np.arange(-0.975, 0, 0.05, dtype=float), units="1", long_name="s"
         )
         self.eta = AuxCoord(
-            np.arange(-1, 3, dtype=np.float).reshape(2, 2),
+            np.arange(-1, 3, dtype=np.float64).reshape(2, 2),
             long_name="eta",
             units="m",
         )
         self.depth = AuxCoord(
-            np.arange(4, dtype=np.float).reshape(2, 2) * 1e3,
+            np.arange(4, dtype=np.float64).reshape(2, 2) * 1e3,
             long_name="depth",
             units="m",
         )

diff --git a/lib/iris/tests/unit/aux_factory/test_OceanSg1Factory.py b/lib/iris/tests/unit/aux_factory/test_OceanSg1Factory.py
@@ -179,12 +179,12 @@ def setUp(self):
             np.linspace(-0.959, -0.001, 36), units="1", long_name="c"
         )
         self.eta = AuxCoord(
-            np.arange(-1, 3, dtype=np.float).reshape(2, 2),
+            np.arange(-1, 3, dtype=np.float64).reshape(2, 2),
             long_name="eta",
             units="m",
         )
         self.depth = AuxCoord(
-            np.array([[5, 200], [1000, 4000]], dtype=np.float),
+            np.array([[5, 200], [1000, 4000]], dtype=np.float64),
             long_name="depth",
             units="m",
         )