Gnss kf whitespace

old-commit-hash: 7015a4704e

selfdrive/locationd/kalman/models/gnss_kf.py

@@ -40,7 +40,6 @@ class GNSSKalman():
 
   maha_test_kinds = []  # ObservationKind.PSEUDORANGE_RATE, ObservationKind.PSEUDORANGE, ObservationKind.PSEUDORANGE_GLONASS]
 
-
   @staticmethod
   def generate_code():
     dim_state = GNSSKalman.x_initial.shape[0]
@@ -68,7 +67,6 @@ class GNSSKalman():
     # Can be pretty bad if dt is big
     f_sym = state + dt * state_dot
 
-
     #
     # Observation functions
     #
@@ -85,17 +83,21 @@ class GNSSKalman():
     los_x, los_y, los_z = sat_los_sym
     orb_x, orb_y, orb_z = orb_epos_sym
 
-    h_pseudorange_sym = sp.Matrix([sp.sqrt(
+    h_pseudorange_sym = sp.Matrix([
+      sp.sqrt(
         (x - sat_x)**2 +
         (y - sat_y)**2 +
-                                    (z - sat_z)**2) +
-                                    cb])
+        (z - sat_z)**2
+      ) + cb
+    ])
 
-    h_pseudorange_glonass_sym = sp.Matrix([sp.sqrt(
+    h_pseudorange_glonass_sym = sp.Matrix([
+      sp.sqrt(
         (x - sat_x)**2 +
         (y - sat_y)**2 +
-                                    (z - sat_z)**2) +
-                                    cb + glonass_bias + glonass_freq_slope*glonass_freq])
+        (z - sat_z)**2
+      ) + cb + glonass_bias + glonass_freq_slope * glonass_freq
+    ])
 
     los_vector = (sp.Matrix(sat_pos_vel_sym[0:3]) - sp.Matrix([x, y, z]))
     los_vector = los_vector / sp.sqrt(los_vector[0]**2 + los_vector[1]**2 + los_vector[2]**2)