Data.allclose

.pre-commit-config.yaml

@@ -10,7 +10,7 @@ repos:
   # Use specific format-enforcing pre-commit hooks from the core library
   # with the default configuration (see pre-commit.com for documentation)
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v3.4.0
+    rev: v4.3.0
     hooks:
       - id: check-ast
       - id: debug-statements
@@ -23,7 +23,7 @@ repos:
   # (see https://black.readthedocs.io/en/stable/ for documentation and see
   # the cf-python pyproject.toml file for our custom black configuration)
   - repo: https://github.com/ambv/black
-    rev: 21.5b0
+    rev: 22.3.0
     hooks:
       - id: black
         language_version: python3
@@ -48,7 +48,7 @@ repos:
   # (see https://flake8.pycqa.org/en/latest/ for documentation and see
   # the cf-python .flake8 file for our custom flake8 configuration)
   - repo: https://gitlab.com/pycqa/flake8
-    rev: 3.9.1
+    rev: 3.9.2
     hooks:
       - id: flake8
 
@@ -57,7 +57,7 @@ repos:
   # compatible with 'black' with the lines set to ensure so in the repo's
   # pyproject.toml. Other than that and the below, no extra config is required.
   - repo: https://github.com/pycqa/isort
-    rev: 5.8.0
+    rev: 5.10.1
     hooks:
       - id: isort
         name: isort (python)

cf/__init__.py

@@ -185,7 +185,7 @@
     )
 
 # Check the version of dask
-_minimum_vn = "2022.03.0"
+_minimum_vn = "2022.6.0"
 if LooseVersion(dask.__version__) < LooseVersion(_minimum_vn):
     raise RuntimeError(
         f"Bad dask version: cf requires dask>={_minimum_vn}. "

cf/data/collapse.py

@@ -1137,11 +1137,7 @@ def cf_mean_chunk(x, weights=None, dtype="f8", computing_meta=False, **kwargs):
 
 
 def cf_mean_combine(
-    pairs,
-    axis=None,
-    dtype="f8",
-    computing_meta=False,
-    **kwargs,
+    pairs, axis=None, dtype="f8", computing_meta=False, **kwargs
 ):
     """Combination calculations for the mean.
 
@@ -1255,12 +1251,7 @@ def cf_max_chunk(x, dtype=None, computing_meta=False, **kwargs):
     }
 
 
-def cf_max_combine(
-    pairs,
-    axis=None,
-    computing_meta=False,
-    **kwargs,
-):
+def cf_max_combine(pairs, axis=None, computing_meta=False, **kwargs):
     """Combination calculations for the maximum.
 
     This function is passed to `dask.array.reduction` as its *combine*
@@ -1284,10 +1275,7 @@ def cf_max_combine(
     if computing_meta:
         return mx
 
-    return {
-        "max": mx,
-        "N": sum_sample_sizes(pairs, axis, **kwargs),
-    }
+    return {"max": mx, "N": sum_sample_sizes(pairs, axis, **kwargs)}
 
 
 def cf_max_agg(
@@ -1414,12 +1402,7 @@ def cf_min_chunk(x, dtype=None, computing_meta=False, **kwargs):
     }
 
 
-def cf_min_combine(
-    pairs,
-    axis=None,
-    computing_meta=False,
-    **kwargs,
-):
+def cf_min_combine(pairs, axis=None, computing_meta=False, **kwargs):
     """Combination calculations for the minimum.
 
     This function is passed to `dask.array.reduction` as its *combine*
@@ -1443,10 +1426,7 @@ def cf_min_combine(
     if computing_meta:
         return mn
 
-    return {
-        "min": mn,
-        "N": sum_sample_sizes(pairs, axis, **kwargs),
-    }
+    return {"min": mn, "N": sum_sample_sizes(pairs, axis, **kwargs)}
 
 
 def cf_min_agg(
@@ -1528,11 +1508,7 @@ def cf_range_chunk(x, dtype=None, computing_meta=False, **kwargs):
 
 
 def cf_range_combine(
-    pairs,
-    axis=None,
-    dtype=None,
-    computing_meta=False,
-    **kwargs,
+    pairs, axis=None, dtype=None, computing_meta=False, **kwargs
 ):
     """Combination calculations for the range.
 
@@ -1559,11 +1535,7 @@ def cf_range_combine(
 
     mn = min_arrays(pairs, "min", axis, None, **kwargs)
 
-    return {
-        "max": mx,
-        "min": mn,
-        "N": sum_sample_sizes(pairs, axis, **kwargs),
-    }
+    return {"max": mx, "min": mn, "N": sum_sample_sizes(pairs, axis, **kwargs)}
 
 
 def cf_range_agg(
@@ -1724,11 +1696,7 @@ def cf_sample_size_chunk(x, dtype="i8", computing_meta=False, **kwargs):
 
 
 def cf_sample_size_combine(
-    pairs,
-    axis=None,
-    dtype="i8",
-    computing_meta=False,
-    **kwargs,
+    pairs, axis=None, dtype="i8", computing_meta=False, **kwargs
 ):
     """Combination calculations for the sample size.
 
@@ -1836,11 +1804,7 @@ def cf_sum_chunk(x, weights=None, dtype="f8", computing_meta=False, **kwargs):
 
 
 def cf_sum_combine(
-    pairs,
-    axis=None,
-    dtype="f8",
-    computing_meta=False,
-    **kwargs,
+    pairs, axis=None, dtype="f8", computing_meta=False, **kwargs
 ):
     """Combination calculations for the sum.
 
@@ -1865,10 +1829,7 @@ def cf_sum_combine(
     if computing_meta:
         return x
 
-    return {
-        "sum": x,
-        "N": sum_sample_sizes(pairs, axis, **kwargs),
-    }
+    return {"sum": x, "N": sum_sample_sizes(pairs, axis, **kwargs)}
 
 
 def cf_sum_agg(
@@ -2099,11 +2060,7 @@ def cf_var_chunk(
 
 
 def cf_var_combine(
-    pairs,
-    axis=None,
-    dtype="f8",
-    computing_meta=False,
-    **kwargs,
+    pairs, axis=None, dtype="f8", computing_meta=False, **kwargs
 ):
     """Combination calculations for the variance.
 

cf/data/dask_utils.py

@@ -14,8 +14,7 @@
 from ..cfdatetime import dt2rt, rt2dt
 from ..functions import atol as cf_atol
 from ..functions import rtol as cf_rtol
-
-# from dask.utils import deepmap  # Apply function inside nested lists
+from ..units import Units
 
 
 def _da_ma_allclose(x, y, masked_equal=True, rtol=None, atol=None):
@@ -94,26 +93,14 @@ def allclose(a_blocks, b_blocks, rtol=rtol, atol=atol):
 
         for a, b in zip(flatten(a_blocks), flatten(b_blocks)):
             result &= np.ma.allclose(
-                a,
-                b,
-                masked_equal=masked_equal,
-                rtol=rtol,
-                atol=atol,
+                a, b, masked_equal=masked_equal, rtol=rtol, atol=atol
             )
 
         return result
 
     axes = tuple(range(x.ndim))
     return da.blockwise(
-        allclose,
-        "",
-        x,
-        axes,
-        y,
-        axes,
-        dtype=bool,
-        rtol=rtol,
-        atol=atol,
+        allclose, "", x, axes, y, axes, dtype=bool, rtol=rtol, atol=atol
     )
 
 
@@ -594,3 +581,45 @@ def cf_dt2rt(a, units):
 
     """
     return dt2rt(a, units_out=units, units_in=None)
+
+
+def cf_units(a, from_units, to_units):
+    """Convert array values to have different equivalent units.
+
+    .. versionadded:: TODODASK
+
+    .. seealso:: `cf.Data.Units`
+
+    :Parameters:
+
+        a: `numpy.ndarray`
+            The array.
+
+        from_units: `Units`
+            The existing units of the array.
+
+        to_units: `Units`
+            The units that the array should be converted to. Must be
+            equivalent to *from_units*.
+
+    :Returns:
+
+        `numpy.ndarray`
+            An array containing values in the new units. In order to
+            represent the new units, the returned data type may be
+            different from that of the input array. For instance, if
+            *a* has an integer data type, *from_units* are kilometres,
+            and *to_units* are ``'miles'`` then the returned array
+            will have a float data type.
+
+    **Examples**
+
+    >>> import numpy as np
+    >>> a = np.array([1, 2])
+    >>> print(cf.data.dask_utils.cf_units(a, cf.Units('km'), cf.Units('m')))
+    [1000. 2000.]
+
+    """
+    return Units.conform(
+        a, from_units=from_units, to_units=to_units, inplace=False
+    )