Add mean_afid_set function

This commit adds a metric function that computes the mean spatial
position given a list of AfidSets. Adds in associated tests and
docstrings.

Additionally, makes use of lambda function rather than iterating across
list for tests.

afids_utils/metrics.py

@@ -1,39 +1,55 @@
 """Methods for computing various metrics pertaining to AFIDs"""
 from __future__ import annotations
 
-from afids_utils.afids import AfidDistance, AfidPosition
+from afids_utils.afids import AfidPosition, AfidSet
 
 
-def compute_distance(
-    afid_position: AfidPosition, template_position: AfidPosition
-) -> AfidDistance:
-    """Compute distance between two AfidPositions, returning Euclidean
-    distance, as well as distances along each spatial dimension
+def compute_mean_afid_sets(afid_sets: list[AfidSet]) -> AfidSet:
+    """Compute the mean spatial coordinates of corresponding AFIDs across a
+    list of ``AfidSet`` objects.
 
     Parameters
     ----------
-    afid_position
-        Input AfidPosition containing floating-point spatial coordinates
-        (x, y, z)
-
-    template_position
-        Template AfidPosition to compute distance against
+    afid_sets
+        List of AfidSets to compute mean from
 
     Returns
     -------
-    AfidDistance
-        Object containing distances along each spatial dimension
-        (x, y, z) and Euclidean distance respectively
+    AfidSet
+        Object containing mean spatial components for each AFID
+
+    Raises
+    ------
+    ValueError
+        If there are different coordinate systems in provided list of
+        ``AfidSet`` objects
     """
-    # Compute distances
-    x_dist, y_dist, z_dist = afid_position - template_position
-    euc = (x_dist**2 + y_dist**2 + z_dist**2) ** 0.5
-
-    return AfidDistance(
-        label=afid_position.label,
-        desc=afid_position.desc,
-        x=x_dist,
-        y=y_dist,
-        z=z_dist,
-        euc=euc,
+    # Check if coordinate systems are all the same
+    if not all(
+        afid_set.coord_system == afid_sets[0].coord_system
+        for afid_set in afid_sets
+    ):
+        raise ValueError(
+            "Mismatched coordinate system in provided list of AfidSet"
+        )
+
+    num_sets = len(afid_sets)
+    mean_afid_set = AfidSet(
+        slicer_version="Unknown",
+        coord_system=afid_sets[0].coord_system,
+        afids=[
+            AfidPosition(
+                label=afid_sets[0].afids[idx].label,
+                x=sum(afid_set.afids[idx].x for afid_set in afid_sets)
+                / num_sets,
+                y=sum(afid_set.afids[idx].y for afid_set in afid_sets)
+                / num_sets,
+                z=sum(afid_set.afids[idx].z for afid_set in afid_sets)
+                / num_sets,
+                desc=afid_sets[0].afids[idx].desc,
+            )
+            for idx in range(len(afid_sets[0].afids))
+        ],
     )
+
+    return mean_afid_set

afids_utils/tests/test_afids.py

@@ -375,9 +375,14 @@ def test_valid_afid_set(self, afid_set1: AfidSet, afid_set2: AfidSet):
         )
 
         # Check afids property is correct (list[AfidDistances])
-        assert isinstance(afid_distance_set.afids, list)
-        for idx in range(len(afid_set1.afids)):
-            assert isinstance(afid_distance_set.afids[idx], AfidDistance)
+        assert isinstance(afid_distance_set.afids, list) and all(
+            list(
+                map(
+                    lambda x: isinstance(x, AfidDistance),
+                    afid_distance_set.afids,
+                )
+            )
+        )
 
     @given(
         afid_set1=af_st.afid_sets(randomize_header=False),

afids_utils/tests/test_metrics.py

@@ -1,19 +1,37 @@
 from __future__ import annotations
 
+import pytest
 from hypothesis import given
 
 import afids_utils.metrics as af_metrics
 import afids_utils.tests.strategies as af_st
-from afids_utils.afids import AfidDistance, AfidPosition
+from afids_utils.afids import AfidPosition, AfidSet
 
 
-class TestMetrics:
-    @given(pos1=af_st.afid_positions(), pos2=af_st.afid_positions())
-    def test_compute_distance(self, pos1: AfidPosition, pos2: AfidPosition):
-        res = af_metrics.compute_distance(pos1, pos2)
-        assert isinstance(res, AfidDistance)
+class TestMeanAfidSet:
+    @given(
+        afid_set1=af_st.afid_sets(randomize_header=False),
+        afid_set2=af_st.afid_sets(randomize_header=False),
+    )
+    def test_mismatched_coords(self, afid_set1: AfidSet, afid_set2: AfidSet):
+        # Manually set the coord system to mistmatch
+        afid_set2.coord_system = "LPS"
+
+        with pytest.raises(ValueError, match=r"Mismatched coordinate.*"):
+            af_metrics.compute_mean_afid_sets([afid_set1, afid_set2])
+
+    @given(
+        afid_set1=af_st.afid_sets(randomize_header=False),
+        afid_set2=af_st.afid_sets(randomize_header=False),
+    )
+    def test_valid_afid_sets(self, afid_set1: AfidSet, afid_set2: AfidSet):
+        mean_afid_set = af_metrics.compute_mean_afid_sets(
+            [afid_set1, afid_set2]
+        )
+
         # Check internals
-        assert isinstance(res.x, float)
-        assert isinstance(res.y, float)
-        assert isinstance(res.z, float)
-        assert isinstance(res.euc, float) and res.euc >= 0
+        assert isinstance(mean_afid_set.afids, list) and all(
+            list(
+                map(lambda x: isinstance(x, AfidPosition), mean_afid_set.afids)
+            )
+        )