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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]>
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‎docs/src/whatsnew/latest.rst‎

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@@ -112,11 +112,15 @@ This document explains the changes made to Iris for this release
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#. `@bjlittle`_ enabled `cirrus-ci`_ compute credits for non-draft pull-requests
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from collaborators targeting the Iris ``master`` branch. (:pull:`4007`)
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#. `@akuhnregnier`_ replaced `deprecated numpy 1.20 aliases for builtin types`_.
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(:pull:`3997`)
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.. comment
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Whatsnew author names (@github name) in alphabetical order. Note that,
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core dev names are automatically included by the common_links.inc:
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.. _@akuhnregnier: https://github.com/akuhnregnier
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.. _@gcaria: https://github.com/gcaria
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.. _@MHBalsmeier: https://github.com/MHBalsmeier
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@@ -125,6 +129,7 @@ This document explains the changes made to Iris for this release
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Whatsnew resources in alphabetical order:
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.. _abstract base class: https://docs.python.org/3/library/abc.html
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.. _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
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.. _GitHub: https://github.com/SciTools/iris/issues/new/choose
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.. _Met Office: https://www.metoffice.gov.uk/
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.. _numpy: https://numpy.org/doc/stable/release/1.20.0-notes.html

‎lib/iris/_constraints.py‎

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@@ -294,7 +294,7 @@ def call_func(c):
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except TypeError:
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try_quick = False
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if try_quick:
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r = np.zeros(coord.shape, dtype=np.bool)
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r = np.zeros(coord.shape, dtype=np.bool_)
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if coord.cell(i) == self._coord_thing:
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r[i] = True
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else:

‎lib/iris/analysis/__init__.py‎

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

‎lib/iris/analysis/_regrid.py‎

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

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

‎lib/iris/fileformats/_ff.py‎

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

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# However, we still mask any MDI values in the array (below).
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pass
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else:
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land_mask = mask.data.astype(np.bool)
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land_mask = mask.data.astype(np.bool_)
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sea_mask = ~land_mask
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new_data = np.ma.masked_all(land_mask.shape)
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new_data.fill_value = mdi

‎lib/iris/fileformats/pp_load_rules.py‎

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

‎lib/iris/tests/__init__.py‎

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stats.get("max", 0.0),
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stats.get("min", 0.0),
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),
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dtype=np.float_,
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dtype=np.float64,
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)
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if math.isnan(stats.get("mean", 0.0)):
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self.assertTrue(math.isnan(data.mean()))
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else:
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data_stats = np.array(
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(data.mean(), data.std(), data.max(), data.min()),
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dtype=np.float_,
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dtype=np.float64,
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)
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self.assertArrayAllClose(nstats, data_stats, **kwargs)
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else:
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self._ensure_folder(reference_path)
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stats = collections.OrderedDict(
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[
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("std", np.float_(data.std())),
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("min", np.float_(data.min())),
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("max", np.float_(data.max())),
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("std", np.float64(data.std())),
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("min", np.float64(data.min())),
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("max", np.float64(data.max())),
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("shape", data.shape),
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("masked", ma.is_masked(data)),
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("mean", np.float_(data.mean())),
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("mean", np.float64(data.mean())),
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]
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)
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with open(reference_path, "w") as reference_file:

‎lib/iris/tests/experimental/regrid/test_regrid_conservative_via_esmpy.py‎

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[100, 100, 100, 100, 100, 100, 100, 100, 100],
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[100, 100, 100, 100, 100, 100, 100, 100, 100],
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],
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dtype=np.float,
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dtype=np.float64,
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)
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c1_areasum = _cube_area_sum(c1)
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[100, 100, 199, 199, 100],
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[100, 100, 199, 199, 199],
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],
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dtype=np.float,
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dtype=np.float64,
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)
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c2_areasum = _cube_area_sum(c2)
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[100, 100, 100, 100, 100, 100, 100, 100, 100],
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[100, 100, 100, 100, 100, 100, 100, 100, 100],
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],
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dtype=np.float,
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dtype=np.float64,
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)
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if do_add_missing:

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