Implement DataValidator.apply()

nomenclature/processor/data_validator.py

@@ -1,14 +1,20 @@
+import logging
 from pathlib import Path
+import textwrap
 from typing import List, Union
 
 import yaml
+from pyam import IamDataFrame
+from pyam.logging import adjust_log_level
 
 from nomenclature.definition import DataStructureDefinition
 from nomenclature.error import ErrorCollector
 from nomenclature.processor.iamc import IamcDataFilter
 from nomenclature.processor import Processor
 from nomenclature.processor.utils import get_relative_path
 
+logger = logging.getLogger(__name__)
+
 
 class DataValidationCriteria(IamcDataFilter):
     """Data validation criteria"""
@@ -29,14 +35,39 @@ def from_file(cls, file: Union[Path, str]) -> "DataValidator":
             content = yaml.safe_load(f)
         return cls(file=file, criteria_items=content)
 
-    def apply(self):
-        pass
+    def apply(self, df: IamDataFrame) -> IamDataFrame:
+        error_list = []
+
+        with adjust_log_level():
+            for item in self.criteria_items:
+                failed_validation = df.validate(**item.criteria)
+                if failed_validation is not None:
+                    error_list.append(
+                        "  Criteria: "
+                        + ", ".join(
+                            [f"{key}: {value}" for key, value in item.criteria.items()]
+                        )
+                    )
+                    error_list.append(
+                        textwrap.indent(str(failed_validation), prefix="    ") + "\n"
+                    )
+
+            if error_list:
+                logger.error(
+                    "Failed data validation (file %s):\n%s",
+                    get_relative_path(self.file),
+                    "\n".join(error_list),
+                )
+                raise ValueError(
+                    "Data validation failed. Please check the log for details."
+                )
+        return df
 
     def validate_with_definition(self, dsd: DataStructureDefinition) -> None:
         errors = ErrorCollector(description=f"in file '{self.file}'")
-        for data in self.criteria_items:
+        for criterion in self.criteria_items:
             try:
-                data.validate_with_definition(dsd)
+                criterion.validate_with_definition(dsd)
             except ValueError as value_error:
                 errors.append(value_error)
         if errors:

nomenclature/processor/iamc.py

@@ -1,4 +1,4 @@
-from typing import List, Tuple, Any
+from typing import List
 from pydantic import BaseModel, field_validator
 
 from pyam import IAMC_IDX
@@ -19,15 +19,20 @@ class IamcDataFilter(BaseModel):
     def single_input_to_list(cls, v):
         return v if isinstance(v, list) else [v]
 
+    @property
+    def criteria(self):
+        return dict(item for item in self.model_dump().items() if item[1] is not None)
+
     def validate_with_definition(self, dsd: DataStructureDefinition) -> None:
         error_msg = ""
 
         # check for filter-items that are not defined in the codelists
         for dimension in IAMC_IDX:
             codelist = getattr(dsd, dimension, None)
-            if codelist is None:
+            # no validation if codelist is not defined or filter-item is None
+            if codelist is None or getattr(self, dimension) is None:
                 continue
-            if invalid := codelist.validate_items(getattr(self, dimension, [])):
+            if invalid := codelist.validate_items(getattr(self, dimension)):
                 error_msg += (
                     f"The following {dimension}s are not defined in the "
                     f"DataStructureDefinition:\n   {', '.join(invalid)}\n"

tests/data/validation/definitions/variable/variable.yaml

@@ -2,6 +2,8 @@
     unit: EJ/yr
 - Primary Energy:
     unit: EJ/yr
+- Primary Energy|Coal:
+    unit: EJ/yr
 - Emissions|CO2:
     unit: Mt CO2/yr
 - Emissions|CH4:

tests/data/validation/validate_data/simple_validation.yaml

@@ -1,6 +1,4 @@
- - region: World
-   variable: Final Energy
+ - variable: Final Energy
    year: 2010
    upper_bound: 2.5
    lower_bound: 1
-

tests/data/validation/validate_data/validate_data_fails.yaml

@@ -0,0 +1,11 @@
+ # 2005 value passes the validation, but the 2010 value does not
+ - variable: Primary Energy
+   upper_bound: 5.
+# variable exists only for 'scen_a'
+ - variable: Primary Energy|Coal
+   lower_bound: 2
+# both upper and lower bound are triggered
+ - variable: Primary Energy
+   year: 2005
+   upper_bound: 1.9
+   lower_bound: 1.1

tests/test_validate_data.py

@@ -1,3 +1,5 @@
+from pathlib import Path
+
 import pytest
 from conftest import TEST_DATA_DIR
 
@@ -12,7 +14,6 @@ def test_DataValidator_from_file():
         **{
             "criteria_items": [
                 {
-                    "region": ["World"],
                     "variable": "Final Energy",
                     "year": [2010],
                     "upper_bound": 2.5,
@@ -57,3 +58,37 @@ def test_DataValidator_validate_with_definition_raises(dimension, match):
         dimensions=[dim for dim in ["region", "variable"] if dim != dimension],
     )
     assert data_validator.validate_with_definition(dsd) is None
+
+
+def test_DataValidator_apply_no_matching_data(simple_df):
+    data_validator = DataValidator.from_file(
+        DATA_VALIDATION_TEST_DIR / "simple_validation.yaml"
+    )
+    # no data matches validation criteria, `apply()` passes and returns unchanged object
+    assert data_validator.apply(simple_df) == simple_df
+
+
+def test_DataValidator_apply_fails(simple_df, caplog):
+    data_file = DATA_VALIDATION_TEST_DIR / "validate_data_fails.yaml"
+    data_validator = DataValidator.from_file(data_file)
+
+    failed_validation_message = f"""Failed data validation (file {data_file.relative_to(Path.cwd())}):
+  Criteria: variable: ['Primary Energy'], upper_bound: 5.0
+         model scenario region        variable   unit  year  value
+    0  model_a   scen_a  World  Primary Energy  EJ/yr  2010    6.0
+    1  model_a   scen_b  World  Primary Energy  EJ/yr  2010    7.0
+
+  Criteria: variable: ['Primary Energy|Coal'], lower_bound: 2.0
+         model scenario region             variable   unit  year  value
+    0  model_a   scen_a  World  Primary Energy|Coal  EJ/yr  2005    0.5
+
+  Criteria: variable: ['Primary Energy'], year: [2005], upper_bound: 1.9, lower_bound: 1.1
+         model scenario region        variable   unit  year  value
+    0  model_a   scen_a  World  Primary Energy  EJ/yr  2005    1.0
+    1  model_a   scen_b  World  Primary Energy  EJ/yr  2005    2.0"""
+
+    with pytest.raises(ValueError, match="Data validation failed"):
+        data_validator.apply(simple_df)
+
+    # check if the log message contains the correct information
+    assert failed_validation_message in caplog.text