Adds tests to convergence solver

tardis/simulation/tests/test_convergence.py

@@ -0,0 +1,55 @@
+from pathlib import Path
+
+import numpy as np
+import pytest
+
+from tardis.io.configuration.config_reader import Configuration
+from tardis.simulation.convergence import ConvergenceSolver
+
+
+@pytest.fixture(scope="function")
+def config(example_configuration_dir: Path):
+    return Configuration.from_yaml(
+        example_configuration_dir / "tardis_configv1_verysimple.yml"
+    )
+
+
+@pytest.fixture(scope="function")
+def strategy(config):
+    return config.montecarlo.convergence_strategy.t_rad
+
+def test_convergence_solver_init_damped(strategy):
+    solver = ConvergenceSolver(strategy)
+    assert solver.damping_factor == 0.5
+    assert solver.threshold == 0.05
+    assert solver.converge == solver.damped_converge
+
+def test_convergence_solver_init_custom(strategy):
+    strategy.type = 'custom'
+    with pytest.raises(NotImplementedError):
+        ConvergenceSolver(strategy)
+
+def test_convergence_solver_init_invalid(strategy):
+    strategy.type = 'invalid'
+    with pytest.raises(ValueError):
+        ConvergenceSolver(strategy)
+
+def test_damped_converge(strategy):
+    solver = ConvergenceSolver(strategy)
+    value = np.float64(10.0)
+    estimated_value = np.float64(20.0)
+    converged_value = solver.damped_converge(value, estimated_value)
+    assert converged_value == 15.0
+
+def test_get_convergence_status(strategy):
+    solver = ConvergenceSolver(strategy)
+    value = np.array([1.0, 2.0, 3.0], dtype=np.float64)
+    estimated_value = np.array([1.01, 2.02, 3.03], dtype=np.float64)
+    no_of_cells = np.int64(3)
+    status = solver.get_convergence_status(value, estimated_value, no_of_cells)
+    assert status
+
+    value = np.array([1.0, 2.0, 3.0], dtype=np.float64)
+    estimated_value = np.array([2.0, 3.0, 4.0], dtype=np.float64)
+    status = solver.get_convergence_status(value, estimated_value, no_of_cells)
+    assert not status