Rename variables

python/tests/beagle_numba.py

@@ -74,7 +74,7 @@ def convert_to_genetic_map_positions(pos, genetic_map=None):
 
 
 @njit
-def get_weights(genotyped_pos, ungenotyped_pos, genotyped_cm, ungenotyped_cm):
+def get_weights(typed_pos, untyped_pos, typed_cm, untyped_cm):
     """
     Get weights for ungenotyped markers in the query haplotype, which are used in
     linear interpolation of HMM state probabilities at the ungenotyped markers.
@@ -93,8 +93,8 @@ def get_weights(genotyped_pos, ungenotyped_pos, genotyped_cm, ungenotyped_cm):
     :rtype: tuple(numpy.ndarray, numpy.ndarray)
     """
     MIN_CM_DIST = 1e-7  # Avoid division by zero.
-    m = len(genotyped_pos)
-    x = len(ungenotyped_pos)
+    m = len(typed_pos)
+    x = len(untyped_pos)
     # Calculate weights for ungenotyped markers.
     weights = np.zeros(x, dtype=np.float32)
     # Identify genotype markers m and m+1 bounding ungenotyped marker i.
@@ -103,19 +103,19 @@ def get_weights(genotyped_pos, ungenotyped_pos, genotyped_cm, ungenotyped_cm):
     # TODO: Refactor using np.searchsorted().
     idx_m = m - 1
     for idx_x in range(x - 1, -1, -1):
-        while idx_m > 0 and ungenotyped_pos[idx_x] < genotyped_pos[idx_m]:
+        while idx_m > 0 and untyped_pos[idx_x] < typed_pos[idx_m]:
             idx_m = max(idx_m - 1, 0)
         if idx_m == m - 1:
             # Right of the last genotyped marker.
             weights[idx_x] = 0.0
-        elif idx_m == 0 and ungenotyped_pos[idx_x] < genotyped_pos[idx_m]:
+        elif idx_m == 0 and untyped_pos[idx_x] < typed_pos[idx_m]:
             # Left of the first genotyped marker.
             weights[idx_x] = 1.0
         else:
             # Between two genotyped markers.
-            cm_mP1_x = genotyped_cm[idx_m + 1] - ungenotyped_cm[idx_x]
+            cm_mP1_x = typed_cm[idx_m + 1] - untyped_cm[idx_x]
             # TODO: Check if this a subtle source of numerical error.
-            cm_mP1_m = max(genotyped_cm[idx_m + 1] - genotyped_cm[idx_m], MIN_CM_DIST)
+            cm_mP1_m = max(typed_cm[idx_m + 1] - typed_cm[idx_m], MIN_CM_DIST)
             weights[idx_x] = cm_mP1_x / cm_mP1_m
         left_idx[idx_x] = idx_m
     return (weights, left_idx)