REF: Fix PET model exception test functions

Fix PET model exception test functions:
- Refactor functions so that the last midpoint value exception is
  properly captured: rename tests functions so that their purposes
  becomes apparent from the name and add a test to check the last
  midpoint value exception.
- Check both `midframe` and `xlim` missing exceptions.
- Define the exception messages so that tests can check exactly the
  captured message.

Author: jhlegarreta

src/nifreeze/model/pet.py

@@ -38,6 +38,13 @@
 DEFAULT_TIMEFRAME_MIDPOINT_TOL = 1e-2
 """Time frame tolerance in seconds."""
 
+TIMEPOINT_XLIM_DATA_MISSING_ERROR_MSG = "timepoints must be provided in initialization."
+"""PET model timepoint data missing error message."""
+FIRST_MIDPOINT_VALUE_ERROR_MSG = "First frame midpoint should not be zero or negative."
+"""PET model first midpoint value error message."""
+LAST_MIDPOINT_VALUE_ERROR_MSG = "Last frame midpoint should not be equal or greater than duration."
+"""PET model last midpoint value error message."""
+
 
 class PETModel(BaseModel):
     """A PET imaging realignment model based on B-Spline approximation."""
@@ -84,7 +91,7 @@ def __init__(
         super().__init__(dataset, **kwargs)
 
         if timepoints is None or xlim is None:
-            raise TypeError("timepoints must be provided in initialization")
+            raise TypeError(TIMEPOINT_XLIM_DATA_MISSING_ERROR_MSG)
 
         self._order = order
         self._x = np.array(timepoints, dtype="float32")
@@ -93,9 +100,9 @@ def __init__(
         self._thresh_pct = thresh_pct
 
         if self._x[0] < DEFAULT_TIMEFRAME_MIDPOINT_TOL:
-            raise ValueError("First frame midpoint should not be zero or negative")
+            raise ValueError(FIRST_MIDPOINT_VALUE_ERROR_MSG)
         if self._x[-1] > (self._xlim - DEFAULT_TIMEFRAME_MIDPOINT_TOL):
-            raise ValueError("Last frame midpoint should not be equal or greater than duration")
+            raise ValueError(LAST_MIDPOINT_VALUE_ERROR_MSG)
 
         # Calculate index coordinates in the B-Spline grid
         self._n_ctrl = n_ctrl or (len(timepoints) // 4) + 1

test/test_model_pet.py

@@ -25,7 +25,13 @@
 import pytest
 
 from nifreeze.data.pet import PET
-from nifreeze.model.pet import PETModel
+from nifreeze.model.pet import (
+    DEFAULT_TIMEFRAME_MIDPOINT_TOL,
+    FIRST_MIDPOINT_VALUE_ERROR_MSG,
+    LAST_MIDPOINT_VALUE_ERROR_MSG,
+    TIMEPOINT_XLIM_DATA_MISSING_ERROR_MSG,
+    PETModel,
+)
 
 
 @pytest.fixture
@@ -71,13 +77,38 @@ def test_petmodel_fit_predict(random_dataset):
 
 
 @pytest.mark.random_pet_data(5, (4, 4, 4), np.asarray([10.0, 20.0, 30.0, 40.0, 50.0]), 60.0)
-def test_petmodel_invalid_init(random_dataset):
-    with pytest.raises(TypeError):
+def test_petmodel_init_mandatory_attr_errors(random_dataset):
+    with pytest.raises(TypeError, match=TIMEPOINT_XLIM_DATA_MISSING_ERROR_MSG):
         PETModel(dataset=random_dataset)
 
+    xlim = 55.0
+    with pytest.raises(TypeError, match=TIMEPOINT_XLIM_DATA_MISSING_ERROR_MSG):
+        PETModel(dataset=random_dataset, xlim=xlim)
+
+    timepoints = np.array([20, 30, 40, 50, 60], dtype=np.float32)
+    with pytest.raises(TypeError, match=TIMEPOINT_XLIM_DATA_MISSING_ERROR_MSG):
+        PETModel(dataset=random_dataset, timepoints=timepoints)
+
 
 @pytest.mark.random_pet_data(5, (4, 4, 4), np.asarray([10.0, 20.0, 30.0, 40.0, 50.0]), 60.0)
-def test_petmodel_time_check(random_dataset):
-    bad_times = np.array([0, 10, 20, 30, 50], dtype=np.float32)
-    with pytest.raises(ValueError):
-        PETModel(dataset=random_dataset, timepoints=bad_times, xlim=60.0)
+def test_petmodel_first_midpoint_error(random_dataset):
+    timepoints = np.array([0, 10, 20, 30, 50], dtype=np.float32)
+    xlim = 60.0
+    with pytest.raises(ValueError, match=FIRST_MIDPOINT_VALUE_ERROR_MSG):
+        PETModel(dataset=random_dataset, timepoints=timepoints, xlim=xlim)
+
+    timepoints[0] = DEFAULT_TIMEFRAME_MIDPOINT_TOL
+    with pytest.raises(ValueError, match=FIRST_MIDPOINT_VALUE_ERROR_MSG):
+        PETModel(dataset=random_dataset, timepoints=timepoints, xlim=xlim)
+
+
+@pytest.mark.random_pet_data(5, (4, 4, 4), np.asarray([10.0, 20.0, 30.0, 40.0, 50.0]), 40.0)
+def test_petmodel_last_midpoint_error(random_dataset):
+    xlim = 45.0
+    timepoints = np.array([5, 10, 20, 30, 50], dtype=np.float32)
+    with pytest.raises(ValueError, match=LAST_MIDPOINT_VALUE_ERROR_MSG):
+        PETModel(dataset=random_dataset, timepoints=timepoints, xlim=xlim)
+
+    timepoints[-1] = xlim - DEFAULT_TIMEFRAME_MIDPOINT_TOL
+    with pytest.raises(ValueError, match=LAST_MIDPOINT_VALUE_ERROR_MSG):
+        PETModel(dataset=random_dataset, timepoints=timepoints, xlim=xlim)