refactor covariance_matrix usage to make code more compact and clear

satellogic · Nov 29, 2017 · df4485f · df4485f
1 parent f765db2
commit df4485f
Show file tree

Hide file tree

Showing 2 changed files with 3 additions and 5 deletions.
diff --git a/quaternions/quaternion.py b/quaternions/quaternion.py
@@ -254,7 +254,7 @@ def average_and_std_lerner(*quaternions, weights=None):
         """
         q_average = Quaternion.average(*quaternions, weights=weights)
         diffs = [quat / q_average for quat in quaternions]
-        angles_list = np.array([[2 * diff.coordinates[i] for i in [1, 2, 3]] for diff in diffs])
+        angles_list = [2 * diff.coordinates[1:] for diff in diffs]
         covariance_matrix = covariance_matrix_from_angles(angles_list)
         return q_average, np.degrees(sigma_lerner(covariance_matrix))
 

diff --git a/quaternions/utils.py b/quaternions/utils.py
@@ -6,10 +6,8 @@ def covariance_matrix_from_angles(angles_list):
     Computes covariance matrix from 3d vectors list
     :param angles_list: list of NumPy arrays
     """
-    covariance_matrix = np.zeros((3, 3))
-    for angles in angles_list:
-        covariance_matrix += np.outer(angles.T, angles)
-    covariance_matrix /= (angles_list.shape[0] + 1)
+    covariance_matrix = sum(np.outer(angles, angles) for angles in angles_list)
+    covariance_matrix /= (len(angles_list) + 1)
     return covariance_matrix