feat: Add validation for NaN values in datablocks

Refs: #433

hydrolib/core/dflowfm/ini/models.py

@@ -1,6 +1,7 @@
 import logging
 from abc import ABC
 from enum import Enum
+from math import isnan
 from typing import Any, Callable, List, Literal, Optional, Set, Type, Union
 
 from pydantic import Extra, Field, root_validator
@@ -167,15 +168,17 @@ def _to_section(self, config: INISerializerConfig) -> Section:
         return Section(header=self._header, content=props)
 
 
+Datablock = List[List[Union[float, str]]]
+
+
 class DataBlockINIBasedModel(INIBasedModel):
     """DataBlockINIBasedModel defines the base model for ini models with datablocks.
 
     Attributes:
-        datablock (List[List[Union[float, str]]]): (class attribute) the actual data
-            columns.
+        datablock (Datablock): (class attribute) the actual data columns.
     """
 
-    datablock: List[List[Union[float, str]]] = []
+    datablock: Datablock = []
 
     _make_lists = make_list_validator("datablock")
 
@@ -204,6 +207,28 @@ def convert_value(
 
         return value
 
+    @validator("datablock")
+    def _validate_no_nans_are_present(cls, datablock: Datablock) -> Datablock:
+        """Validate that the datablock does not have any NaN values.
+
+        Args:
+            datablock (Datablock): The datablock to verify.
+
+        Raises:
+            ValueError: When a NaN is present in the datablock.
+
+        Returns:
+            Datablock: The validated datablock.
+        """
+        if any(cls._is_float_and_nan(value) for list in datablock for value in list):
+            raise ValueError("NaN is not supported in datablocks.")
+
+        return datablock
+
+    @staticmethod
+    def _is_float_and_nan(value: float) -> bool:
+        return isinstance(value, float) and isnan(value)
+
 
 class INIGeneral(INIBasedModel):
     _header: Literal["General"] = "General"

tests/dflowfm/ini/test_models.py

@@ -0,0 +1,41 @@
+from math import nan
+
+import pytest
+from pydantic.error_wrappers import ValidationError
+
+from hydrolib.core.dflowfm.ini.models import DataBlockINIBasedModel
+
+from ...utils import error_occurs_only_once
+
+
+class TestDataBlockINIBasedModel:
+    def test_datablock_with_nan_values_should_raise_error(self):
+        model = DataBlockINIBasedModel()
+
+        with pytest.raises(ValidationError) as error:
+            model.datablock = [[nan, 0], [-1, 2]]
+
+        expected_message = "NaN is not supported in datablocks."
+        assert expected_message in str(error.value)
+
+    def test_updating_datablock_with_nan_values_should_raise_error(self):
+        model = DataBlockINIBasedModel()
+
+        valid_datablock = [[0, 1], [2, 3]]
+        model.datablock = valid_datablock
+
+        invalid_datablock = [[nan, 1], [2, 3]]
+        with pytest.raises(ValidationError) as error:
+            model.datablock = invalid_datablock
+
+        expected_message = "NaN is not supported in datablocks."
+        assert expected_message in str(error.value)
+
+    def test_datablock_with_multiple_nans_should_only_give_error_once(self):
+        model = DataBlockINIBasedModel()
+
+        with pytest.raises(ValidationError) as error:
+            model.datablock = [[nan, nan], [nan, nan]]
+
+        expected_message = "NaN is not supported in datablocks."
+        assert error_occurs_only_once(expected_message, str(error.value))

tests/dflowfm/test_bc.py

@@ -2,6 +2,7 @@
 from pathlib import Path
 from typing import Dict, List, Literal
 
+import numpy as np
 import pytest
 from pydantic.error_wrappers import ValidationError
 
@@ -357,6 +358,26 @@ def test_forcing_model_correct_default_serializer_config(self):
         assert model.serializer_config.comment_delimiter == "#"
         assert model.serializer_config.skip_empty_properties == True
 
+    def test_forcing_model_with_datablock_that_has_nan_values_should_raise_error(self):
+        datablock = np.random.uniform(low=-40, high=130.3, size=(4, 2)) * np.nan
+        datablock_list = datablock.tolist()
+
+        with pytest.raises(ValidationError) as error:
+            TimeSeries(
+                name="east2_0001",
+                quantityunitpair=[
+                    QuantityUnitPair(
+                        quantity="time", unit="seconds since 2022-01-01 00:00:00 +00:00"
+                    ),
+                    QuantityUnitPair(quantity="waterlevel", unit="m"),
+                ],
+                timeInterpolation=TimeInterpolation.linear,
+                datablock=datablock_list,
+            )
+
+        expected_message = "NaN is not supported in datablocks."
+        assert expected_message in str(error.value)
+
 
 class TestVectorForcingBase:
     class VectorForcingTest(VectorForcingBase):

tests/utils.py

@@ -2,8 +2,6 @@
 from pathlib import Path
 from typing import Generic, Optional, TypeVar
 
-import pytest
-from numpy import array
 from pydantic.generics import GenericModel
 
 TWrapper = TypeVar("TWrapper")
@@ -89,3 +87,20 @@ def assert_file_is_same_binary(
         assert filecmp.cmp(input_path, reference_path)
     else:
         assert not input_path.exists()
+
+
+def error_occurs_only_once(error_message: str, full_error: str) -> bool:
+    """Check if the given error message occurs exactly once in the full error string.
+
+    Args:
+        error_message (str): The error to check for.
+        full_error (str): The full error as a string.
+
+    Returns:
+        bool: Return True if the error message occurs exactly once in the full error.
+            Returns False otherwise.
+    """
+    if error_message is None or full_error is None:
+        return False
+
+    return full_error.count(error_message) == 1