Add unit test for reinitialize_distributions

Added a unit test to the `Parameters` class unit tests for the
`reinitialize_distributions` method that demonstrates how this method
affects the seeding behavior across workers.

flepimop/gempyor_pkg/tests/parameters/test_parameters_class.py

@@ -1,14 +1,16 @@
 from datetime import date
 from functools import partial
+from itertools import repeat
 import pathlib
+from tempfile import NamedTemporaryFile
 from typing import Any, Callable
 from uuid import uuid4
 
 import confuse
 import numpy as np
 import pandas as pd
 import pytest
-from tempfile import NamedTemporaryFile
+import tqdm.contrib.concurrent
 
 from gempyor.parameters import Parameters
 from gempyor.testing import (
@@ -192,6 +194,22 @@ def insufficient_dates_parameter_factory(tmp_path: pathlib.Path) -> MockParamete
     )
 
 
+def sample_params(params: Parameters, reinit: bool) -> np.ndarray:
+    """
+    Helper method for unit testing.
+
+    Args:
+        params: The instance of the Parameters class to sample from.
+        reinit: Whether to reinitialize the parameters.
+
+    Returns:
+        The sampled parameters as a flattened numpy array.
+    """
+    if reinit:
+        params.reinitialize_distributions()
+    return params.parameters_quick_draw(1, 1).flatten()
+
+
 class TestParameters:
     @pytest.mark.parametrize("factory", [(nonunique_invalid_parameter_factory)])
     def test_nonunique_parameter_names_value_error(
@@ -697,3 +715,34 @@ def test_parameters_reduce(self) -> None:
         # TODO: Come back and unit test this method after getting a better handle on
         # these NPI objects.
         pass
+
+    def test_reinitialize_parameters(self, tmp_path: pathlib.Path) -> None:
+        mock_inputs = distribution_three_valid_parameter_factory(tmp_path)
+
+        np.random.seed(123)
+
+        params = mock_inputs.create_parameters_instance()
+
+        results = tqdm.contrib.concurrent.process_map(
+            sample_params,
+            repeat(params, times=6),
+            repeat(False, times=6),
+            max_workers=2,
+            disable=True,
+        )
+
+        for i in range(1, len(results)):
+            assert np.allclose(results[i - 1], results[i])
+
+        np.random.seed(123)
+
+        results_with_reinit = tqdm.contrib.concurrent.process_map(
+            sample_params,
+            repeat(params, times=6),
+            repeat(True, times=6),
+            max_workers=2,
+            disable=True,
+        )
+
+        for i in range(1, len(results_with_reinit)):
+            assert not np.allclose(results_with_reinit[i - 1], results_with_reinit[i])