Merge pull request #251 from cerfacs-globc/adapt-to-xclim0-40

Adapt to xclim 0.40

doc/source/references/release_notes.rst

@@ -1,6 +1,13 @@
 Release history
 ===============
 
+6.2.0 (unreleased)
+------------------
+* [maint] Upgrade and adapt to xclim 0.40.
+  Moved PercentileDataArray from xclim to icclim.
+  Adapted the unit cenversion to use the hydro context.
+
+
 6.1.5
 -----
 * [fix] Bug fix: not assuming longitude and latitude are lon and lat with respect to output metadata. Fix needed to work on E-OBS and other datasets.

environment.yml

@@ -6,7 +6,7 @@ channels:
 dependencies:
 # Core dependencies
  - python>=3.8
- - xclim>=0.39
+ - xclim>=0.40
  - numpy
  - xarray>=2022.6
  - cf_xarray>=0.7.4

icclim/generic_indices/generic_indicators.py

@@ -125,7 +125,7 @@ def postprocess(
         out_unit: str | None,
     ):
         if out_unit is not None:
-            result = convert_units_to(result, out_unit)
+            result = convert_units_to(result, out_unit, context="hydro")
         if self.missing != "skip" and indexer is not None:
             # reference variable is a subset of the studied variable,
             # so no need to check it.
@@ -231,9 +231,10 @@ def preprocess(  # noqa signature != from super
             for climate_var in climate_vars:
                 current_unit = climate_var.studied_data.attrs.get(UNITS_KEY, None)
                 if current_unit is not None and not _is_amount_unit(current_unit):
-                    climate_var.studied_data = rate2amount(
-                        climate_var.studied_data, out_units=output_unit
-                    )
+                    with xc_units.context("hydro"):
+                        climate_var.studied_data = rate2amount(
+                            climate_var.studied_data, out_units=output_unit
+                        )
         if coef is not None:
             for climate_var in climate_vars:
                 climate_var.studied_data = coef * climate_var.studied_data
@@ -903,7 +904,7 @@ def get_couple_of_var(
         )
     study = climate_vars[0].studied_data
     ref = climate_vars[1].studied_data
-    study = convert_units_to(study, ref)
+    study = convert_units_to(study, ref, context="hydro")
     return study, ref
 
 

icclim/generic_indices/threshold.py

@@ -14,7 +14,7 @@
 from xclim.core.calendar import build_climatology_bounds, percentile_doy, resample_doy
 from xclim.core.units import convert_units_to, str2pint
 from xclim.core.units import units as xc_units
-from xclim.core.utils import PercentileDataArray, calc_perc
+from xclim.core.utils import calc_perc
 
 from icclim.generic_indices.threshold_templates import (
     EN_THRESHOLD_TEMPLATE,
@@ -37,6 +37,7 @@
     QuantileInterpolationRegistry,
 )
 from icclim.pre_processing.input_parsing import (
+    PercentileDataArray,
     build_reference_da,
     find_standard_vars,
     get_name_of_first_var,
@@ -439,7 +440,9 @@ def unit(self) -> str | None:
     def unit(self, unit: str | xr.DataArray | pint.Quantity | pint.Unit):
         if self.is_ready:
             if self.value.attrs.get(UNITS_KEY, None) is not None and unit is not None:
-                self._prepared_value = convert_units_to(self._prepared_value, unit)
+                self._prepared_value = convert_units_to(
+                    self._prepared_value, unit, context="hydro"
+                )
             self.value.attrs[UNITS_KEY] = unit
 
     @property
@@ -645,7 +648,7 @@ def unit(self) -> str | None:
     @unit.setter
     def unit(self, unit):
         if self.value.attrs.get(UNITS_KEY, None) is not None and unit is not None:
-            self.value = convert_units_to(self.value, unit)
+            self.value = convert_units_to(self.value, unit, context="hydro")
         self.value.attrs[UNITS_KEY] = unit
 
     def __init__(
@@ -690,7 +693,7 @@ def __init__(
         else:
             raise NotImplementedError(f"Cannot build threshold from a {type(value)}.")
         if unit is not None:
-            built_value = convert_units_to(built_value, unit)
+            built_value = convert_units_to(built_value, unit, context="hydro")
         self.operator = operator
         self.value = built_value
         self.unit = unit
@@ -1049,9 +1052,10 @@ def _must_build_bounded_threshold(input: ThresholdBuilderInput) -> bool:
 def _apply_min_value(thresh_da: DataArray, min_value: pint.Quantity | None):
     if min_value is not None:
         if min_value.dimensionless:
-            min_value = convert_units_to(min_value.m, thresh_da)
+            # We assume min_value use the same unit as thresh_da if it's dimensionless
+            min_value = min_value.m
         else:
-            min_value = convert_units_to(str(min_value), thresh_da)
+            min_value = convert_units_to(str(min_value), thresh_da, context="hydro")
         built_value = thresh_da.where(thresh_da > min_value, np.nan)
         return built_value
     else:
@@ -1095,6 +1099,6 @@ def _build_per_thresh_from_dataset(
     )
     if unit is not None:
         if built_value.attrs.get(UNITS_KEY, None) is not None:
-            built_value = convert_units_to(built_value, unit)
+            built_value = convert_units_to(built_value, unit, context="hydro")
         built_value.attrs[UNITS_KEY] = unit
     return built_value, DOY_COORDINATE in built_value.coords

icclim/models/constants.py

@@ -3,7 +3,7 @@
 # fmt: off
 # flake8: noqa
 
-ICCLIM_VERSION = "6.1.5"
+ICCLIM_VERSION = "6.2.0"
 
 # placeholders for user_index
 PERCENTILE_THRESHOLD_STAMP = "p"

icclim/pre_processing/input_parsing.py

@@ -10,7 +10,6 @@
 from xarray.core.dataarray import DataArray
 from xarray.core.dataset import Dataset
 from xclim.core.units import convert_units_to
-from xclim.core.utils import PercentileDataArray
 
 from icclim.generic_indices.standard_variable import (
     StandardVariable,
@@ -26,6 +25,69 @@
 DEFAULT_INPUT_FREQUENCY = "days"
 
 
+class PercentileDataArray(xr.DataArray):
+    """Wrap xarray DataArray for percentiles values."""
+
+    __slots__ = ()
+
+    @classmethod
+    def is_compatible(cls, source: xr.DataArray) -> bool:
+        """Evaluate whether PecentileDataArray is conformant with expected fields.
+
+        A PercentileDataArray must have climatology_bounds attributes and either a
+        quantile or percentiles coordinate, the window is not mandatory.
+        """
+        return (
+            isinstance(source, xr.DataArray)
+            and source.attrs.get("climatology_bounds", None) is not None
+            and ("quantile" in source.coords or "percentiles" in source.coords)
+        )
+
+    @classmethod
+    def from_da(
+        cls, source: xr.DataArray, climatology_bounds: list[str] = None
+    ) -> PercentileDataArray:
+        """Create a PercentileDataArray from a xarray.DataArray.
+
+        Parameters
+        ----------
+        source : xr.DataArray
+            A DataArray with its content containing percentiles values.
+            It must also have a coordinate variable percentiles or quantile.
+        climatology_bounds : list[str]
+            Optional. A List of size two which contains the period on which the
+            percentiles were computed. See
+            `xclim.core.calendar.build_climatology_bounds`
+            to build this list from a DataArray.
+
+        Returns
+        -------
+        PercentileDataArray
+            The initial `source` DataArray but wrap by PercentileDataArray class.
+            The data is unchanged and only climatology_bounds attributes is overridden
+            if q new value is given in inputs.
+        """
+        if (
+            climatology_bounds is None
+            and source.attrs.get("climatology_bounds", None) is None
+        ):
+            raise ValueError("PercentileDataArray needs a climatology_bounds.")
+        per = cls(source)
+        # handle case where da was created with `quantile()` method
+        if "quantile" in source.coords:
+            per = per.rename({"quantile": "percentiles"})
+            per.coords["percentiles"] = per.coords["percentiles"] * 100
+        clim_bounds = source.attrs.get("climatology_bounds", climatology_bounds)
+        per.attrs["climatology_bounds"] = clim_bounds
+        if "percentiles" in per.coords:
+            return per
+        raise ValueError(
+            f"DataArray {source.name} could not be turned into"
+            f" PercentileDataArray. The DataArray must have a"
+            f" 'percentiles' coordinate variable."
+        )
+
+
 def guess_var_names(
     ds: Dataset,
     var_names: str | Sequence[str] | None,
@@ -300,7 +362,9 @@ def read_threshold_DataArray(
     else:
         if threshold_min_value:
             if isinstance(threshold_min_value, str):
-                threshold_min_value = convert_units_to(threshold_min_value, thresh_da)
+                threshold_min_value = convert_units_to(
+                    threshold_min_value, thresh_da, context="hydro"
+                )
             # todo in prcptot the replacing value (np.nan) needs to be 0
             built_value = thresh_da.where(thresh_da > threshold_min_value, np.nan)
         else:
@@ -330,6 +394,8 @@ def build_reference_da(
     if only_leap_years:
         reference = reduce_only_leap_years(original_da)
     if percentile_min_value is not None:
-        percentile_min_value = convert_units_to(str(percentile_min_value), reference)
+        percentile_min_value = convert_units_to(
+            str(percentile_min_value), reference, context="hydro"
+        )
         reference = reference.where(reference >= percentile_min_value, np.nan)
     return reference

icclim/tests/test_input_parsing.py

@@ -7,12 +7,12 @@
 import pandas as pd
 import pytest
 import xarray as xr
-from xclim.core.utils import PercentileDataArray
 
 from icclim.ecad.ecad_indices import EcadIndexRegistry
 from icclim.icclim_exceptions import InvalidIcclimArgumentError
 from icclim.models.constants import UNITS_KEY
 from icclim.pre_processing.input_parsing import (
+    PercentileDataArray,
     guess_var_names,
     read_dataset,
     update_to_standard_coords,

icclim/tests/test_threshold.py

@@ -21,6 +21,7 @@
 from icclim.models.constants import UNITS_KEY
 from icclim.models.logical_link import LogicalLinkRegistry
 from icclim.models.operator import OperatorRegistry
+from icclim.pre_processing.input_parsing import PercentileDataArray
 
 
 def test_value_error():
@@ -295,6 +296,7 @@ def test_threshold_min_value__number_from_file(self):
 
     def test_build_percentile_threshold__from_file(self):
         doys = percentile_doy(self.data)
+        doys = PercentileDataArray.from_da(doys)
         doys.to_netcdf(path=self.IN_FILE_PATH)
         res = build_threshold(operator=">=", value=self.IN_FILE_PATH)
         assert isinstance(res, PercentileThreshold)

requirements.txt

@@ -18,5 +18,5 @@ sphinx_codeautolink
 sphinx_copybutton
 sphinx_lfs_content
 xarray>=2022.6
-xclim~=0.39.0
+xclim~=0.40
 zarr

requirements_dev.txt

@@ -25,5 +25,5 @@ sphinx_copybutton
 sphinx_lfs_content
 twine
 xarray>=2022.6
-xclim~=0.39.0
+xclim~=0.40
 zarr

setup.py

@@ -5,7 +5,7 @@
 MINIMAL_REQUIREMENTS = [
     "numpy>=1.16",
     "xarray>=2022.6",
-    "xclim>=0.39",
+    "xclim>=0.40",
     "cf_xarray>=0.7.4",
     "cftime>=1.4.1",
     "dask[array]",
@@ -21,7 +21,7 @@
 
 setup(
     name="icclim",
-    version="6.1.5",
+    version="6.2.0",
     packages=find_packages(),
     author="Christian P.",
     author_email="[email protected]",