test: update test

Author: frodehk

tests/libecalc/domain/infrastructure/energy_components/legacy_consumer/test_tabular_consumer_function.py

@@ -1,31 +1,50 @@
+from datetime import datetime
+
 from libecalc.domain.infrastructure.energy_components.legacy_consumer.tabulated import TabularConsumerFunction
 from libecalc.domain.infrastructure.energy_components.legacy_consumer.tabulated.common import (
     Variable,
     VariableExpression,
 )
+from libecalc.domain.regularity import Regularity
 from libecalc.expression import Expression
+from libecalc.presentation.yaml.domain.expression_time_series_variable import ExpressionTimeSeriesVariable
+from libecalc.presentation.yaml.domain.time_series_expression import TimeSeriesExpression
+from tests.conftest import expression_evaluator_factory
 
 
-def test_tabular_consumer_single_period_returns_list():
+def test_tabular_consumer_single_period_returns_list(expression_evaluator_factory):
+    test_time_vector = [datetime(2020, 1, 1), datetime(2030, 1, 1)]
     # Minimal setup: one variable, one function value
     headers = ["RATE", "FUEL"]
     data = [[1.0], [10.0]]  # Variable value and function value
-    variables_expressions = [VariableExpression(name="RATE", expression=Expression.setup_from_expression("RATE"))]
+
+    expression_evaluator = expression_evaluator_factory.from_time_vector(test_time_vector)
+    regularity = Regularity(
+        expression_evaluator=expression_evaluator, target_period=expression_evaluator.get_period(), expression_input=1
+    )
+
+    variables = ExpressionTimeSeriesVariable(
+        name="RATE",
+        time_series_expression=TimeSeriesExpression(expressions="RATE", expression_evaluator=expression_evaluator),
+        regularity=regularity,
+    )
     consumer_function = TabularConsumerFunction(
         headers=headers,
         data=data,
         energy_usage_adjustment_constant=0.0,
         energy_usage_adjustment_factor=1.0,
-        variables_expressions=variables_expressions,
-        condition_expression=None,
-        power_loss_factor_expression=None,
+        variables=[variables],
     )
 
     # Test with a single variable and a single value (e.g. only one period).
     # Ensures that the function returns a flat list (not a scalar)
     # even when only one period and one value are present.
-    rate_input = [Variable(name="RATE", values=[1.0])]
+    rate_input = ExpressionTimeSeriesVariable(
+        name="RATE",
+        time_series_expression=TimeSeriesExpression(expressions="1.0", expression_evaluator=expression_evaluator),
+        regularity=regularity,
+    )
 
-    result = consumer_function.evaluate_variables(rate_input)
+    result = consumer_function.evaluate_variables([rate_input])
     assert isinstance(result.energy_usage, list)
     assert result.energy_usage == [10.0]