dask: Deal with some (but not all) TODODASK placeolders

cf/data/dask_utils.py

@@ -31,9 +31,7 @@ def _da_ma_allclose(x, y, masked_equal=True, rtol=None, atol=None):
     the corresponding NumPy method (see the `numpy.ma.allclose` API
     reference).
 
-    TODODASK: put in a PR to Dask to request to add as genuine method.
-
-    .. versionadded:: 4.0.0
+    .. versionadded:: 3.14.0
 
         :Parameters:
 
@@ -58,6 +56,8 @@ def _da_ma_allclose(x, y, masked_equal=True, rtol=None, atol=None):
                 the given *rtol* and *atol* tolerance.
 
     """
+    # TODODASK: put in a PR to Dask to request to add as genuine method.
+
     if rtol is None:
         rtol = cf_rtol()
     if atol is None:

cf/data/data.py

@@ -57,11 +57,11 @@
 from .mixin import DataClassDeprecationsMixin
 from .utils import (
     YMDhms,
-    _is_numeric_dtype,
     conform_units,
     convert_to_datetime,
     convert_to_reftime,
     first_non_missing_value,
+    is_numeric_dtype,
     new_axis_identifier,
     scalar_masked_array,
 )
@@ -7128,8 +7128,8 @@ def equals(
         # We assume that all inputs are masked arrays. Note we compare the
         # data first as this may return False due to different dtype without
         # having to wait until the compute call.
-        self_is_numeric = _is_numeric_dtype(self_dx)
-        other_is_numeric = _is_numeric_dtype(other_dx)
+        self_is_numeric = is_numeric_dtype(self_dx)
+        other_is_numeric = is_numeric_dtype(other_dx)
         if self_is_numeric and other_is_numeric:
             data_comparison = _da_ma_allclose(
                 self_dx,
@@ -10201,8 +10201,6 @@ def squeeze(self, axes=None, inplace=False, i=False):
         """
         d = _inplace_enabled_define_and_cleanup(self)
 
-        # TODODASK - check if axis parsing is done in dask
-
         if not d.ndim:
             if axes or axes == 0:
                 raise ValueError(
@@ -10757,10 +10755,6 @@ def func(
 
         dx = d.to_dask_array()
 
-        # TODODASK: Steps to preserve invalid values shown, taking same
-        # approach as pre-daskification, but maybe we can now change approach
-        # to avoid finding mask and data, which requires early compute...
-        # Step 1. extract the non-masked data and the mask separately
         if preserve_invalid:
             # Assume all inputs are masked, as checking for a mask to confirm
             # is expensive. If unmasked, effective mask will be all False.

cf/data/fragment/abstract/fragmentarray.py

@@ -184,7 +184,7 @@ def _parse_indices(self, indices):
                 continue
 
             if isinstance(i, Integral) or not getattr(i, "ndim", True):
-                # TODODASK: what about [] or np.array([])?
+                # TODOCFA: what about [] or np.array([])?
 
                 # 'i' is an integer or a scalar numpy/dask array
                 raise ValueError(

cf/data/utils.py

@@ -19,10 +19,10 @@
 _units_None = Units(None)
 
 
-def _is_numeric_dtype(array):
+def is_numeric_dtype(array):
     """True if the given array is of a numeric or boolean data type.
 
-    .. versionadded:: 4.0.0
+    .. versionadded:: 3.14.0
 
         :Parameters:
 
@@ -36,29 +36,27 @@ def _is_numeric_dtype(array):
     **Examples**
 
     >>> a = np.array([0, 1, 2])
-    >>> cf.data.utils._is_numeric_dtype(a)
+    >>> cf.data.utils.is_numeric_dtype(a)
     True
     >>> a = np.array([False, True, True])
-    >>> cf.data.utils._is_numeric_dtype(a)
+    >>> cf.data.utils.is_numeric_dtype(a)
     True
     >>> a = np.array(["a", "b", "c"], dtype="S1")
-    >>> cf.data.utils._is_numeric_dtype(a)
+    >>> cf.data.utils.is_numeric_dtype(a)
     False
     >>> a = np.ma.array([10.0, 2.0, 3.0], mask=[1, 0, 0])
-    >>> cf.data.utils._is_numeric_dtype(a)
+    >>> cf.data.utils.is_numeric_dtype(a)
     True
     >>> a = np.array(10)
-    >>> cf.data.utils._is_numeric_dtype(a)
+    >>> cf.data.utils.is_numeric_dtype(a)
     True
     >>> a = np.empty(1, dtype=object)
-    >>> cf.data.utils._is_numeric_dtype(a)
+    >>> cf.data.utils.is_numeric_dtype(a)
     False
 
     """
-    # TODODASK: do we need to make any specific checks relating to ways of
-    # encoding datetimes, which could be encoded as strings, e.g. as in
-    # "2000-12-3 12:00", yet could be considered, or encoded as, numeric?
     dtype = array.dtype
+
     # This checks if the dtype is either a standard "numeric" type (i.e.
     # int types, floating point types or complex floating point types)
     # or Boolean, which are effectively a restricted int type (0 or 1).

cf/domain.py

@@ -781,7 +781,8 @@ def roll(self, axis, shift, inplace=False):
         >>> f.roll('X', -3)
 
         """
-        # TODODASK - allow multiple roll axes
+        # TODODASK: Consider allowing multiple roll axes, now that
+        #           Data supports them.
 
         axis = self.domain_axis(
             axis,

cf/field.py

@@ -8865,11 +8865,6 @@ def collapse(
 
                     d = aux[0]
 
-                    # TODODASK: remove once dask. For some reason,
-                    # without this we now get LAMA related failures in
-                    # Partition.nbytes ...
-                    _ = aux.dtype
-
                     if aux.has_bounds() or (aux[:-1] != aux[1:]).any():
                         logger.info(
                             f"    Removing {aux.construct_type} {key!r}"
@@ -13759,8 +13754,7 @@ def percentile(
         # Initialise the output field with the percentile data
         # ------------------------------------------------------------
 
-        # TODODASK: Make sure that this is OK whaen `ranks` is a
-        #           scalar
+        # TODODASK: Make sure that this is OK when `ranks` is a scalar
 
         out = type(self)()
         out.set_properties(self.properties())
@@ -14219,7 +14213,8 @@ def roll(self, axis, shift, inplace=False, i=False, **kwargs):
         >>> f.roll('X', -3)
 
         """
-        # TODODASK - allow multiple roll axes
+        # TODODASK: Consider allowing multiple roll axes, since Data
+        #           now supports them.
 
         axis = self.domain_axis(
             axis,
@@ -14238,8 +14233,9 @@ def roll(self, axis, shift, inplace=False, i=False, **kwargs):
 
         iaxes = self._axis_positions(axis, parse=False)
         if iaxes:
-            # TODODASK - remove these two lines when multiaxis rolls
-            #            are allowed at 3.14.0
+            # TODODASK: Remove these two lines if multiaxis rolls are
+            #           allowed
+
             iaxis = iaxes[0]
             shift = shift[0]
 
@@ -14833,7 +14829,6 @@ def section(self, axes=None, stop=None, min_step=1, **kwargs):
          <CF Field: eastward_wind(model_level_number(1), latitude(145), longitude(192)) m s-1>]
 
         """
-
         # TODODASK: This still need some attention, keyword checking,
         #           testing, docs, etc., but has been partially
         #           already updated due to changes already happening
@@ -15414,7 +15409,6 @@ def regrids(
         # Retrieve the destination field's mask if appropriate
         dst_mask = None
         if dst_field and use_dst_mask and dst.data.ismasked:
-            # TODODASK: Just get the mask?
             dst_mask = regrid_get_destination_mask(
                 dst, dst_order, axes=dst_axis_keys
             )
@@ -16168,7 +16162,6 @@ def regridc(
         # Retrieve the destination field's mask if appropriate
         dst_mask = None
         if not dst_dict and use_dst_mask and dst.data.ismasked:
-            # TODODASK: Just get the mask?
             dst_mask = regrid_get_destination_mask(
                 dst,
                 dst_order,

cf/functions.py

@@ -2921,10 +2921,10 @@ def _section(x, axes=None, stop=None, chunks=False, min_step=1):
     ndim = x.ndim
     shape = x.shape
 
-    # TODODASK: For v4.0.0, redefine axes by removing the next
-    #           line. I.e. the specified axes would be those that you
-    #           want to be chopped, not those that you want to remain
-    #           whole.
+    # TODODASK: For v4.0.0, consider redefining the axes by removing
+    #           the next line. I.e. the specified axes would be those
+    #           that you want to be chopped, not those that you want
+    #           to remain whole.
     axes = [i for i in range(ndim) if i not in axes]
 
     indices = [

cf/mixin/fielddomain.py

@@ -369,7 +369,7 @@ def _indices(self, mode, data_axes, ancillary_mask, kwargs):
 
                     if envelope or full:
                         size = domain_axes[axis].get_size()
-                        # TODODASK - consider using dask.arange here
+                        # TODODASK: consider using dask.arange here
                         d = np.arange(size)  # self._Data(range(size))
                         ind = (d[value],)  # .array,)
                         index = slice(None)
@@ -735,8 +735,8 @@ def _roll_constructs(self, axis, shift):
                 # This construct does not span the roll axes
                 continue
 
-            # TODODASK - remove these two lines when multiaxis rolls
-            #            are allowed at v4.0.0
+            # TODODASK: Consider removing these two lines, now that
+            #           multiaxis rolls are allowed on Data objects.
             c_axes = c_axes[0]
             c_shifts = c_shifts[0]
 

cf/test/test_Data_utils.py

@@ -69,22 +69,22 @@ def test_Data_Utils__da_ma_allclose(self):
         b2 = a / 10000
         self.assertTrue(allclose(b1, b2, atol=1e-05).compute())
 
-    def test_Data_Utils__is_numeric_dtype(self):
+    def test_Data_Utils_is_numeric_dtype(self):
         """TODO."""
-        _is_numeric_dtype = cf.data.utils._is_numeric_dtype
+        is_numeric_dtype = cf.data.utils.is_numeric_dtype
         for a in [
             np.array([0, 1, 2]),
             np.array([False, True, True]),
             np.ma.array([10.0, 2.0, 3.0], mask=[1, 0, 0]),
             np.array(10),
         ]:
-            self.assertTrue(_is_numeric_dtype(a))
+            self.assertTrue(is_numeric_dtype(a))
 
         for b in [
             np.array(["a", "b", "c"], dtype="S1"),
             np.empty(1, dtype=object),
         ]:
-            self.assertFalse(_is_numeric_dtype(b))
+            self.assertFalse(is_numeric_dtype(b))
 
     def test_Data_Utils_convert_to_datetime(self):
         """TODO."""