Fixes in documentation. Some other smaller changes.

README.md

@@ -199,7 +199,7 @@ Using two star fixes a sight reduction can be done in the following way
     b = Sight (....Parameters....)
 
     collection = SightCollection ([a, b])
-    intersections = collection.get_intersections ()
+    intersections, fitness = collection.get_intersections ()
     print (get_representation(intersections,1))
 
 The result will be a tuple of **two** coordinates (intersections of two circles 
@@ -301,7 +301,7 @@ Using three (or more) sights a sight reduction can be done in the following way
     c = Sight (....Parameters....)
 
     collection = SightCollection ([a, b, c]) # Add more sights if needed
-    intersections = collection.getIntersections ()
+    intersections, fitness = collection.getIntersections ()
     print (getRepresentation(intersections,1))
 
 A *sight* is defined as a collection of data as described in the section 1 above,
@@ -423,7 +423,7 @@ See above for how to create a sight object
 
 Now you can calculate the coordinates for this trip.
 
-    intersections = st.get_intersections ()
+    intersections, fitness = st.get_intersections ()
     print ("Starting point = " + str(get_representation(intersections[0],1)))
     print ("End point = " + str(get_representation(intersections[1],1)))
 

starfix.py

@@ -269,7 +269,7 @@ def get_intersections (latlon1 : LatLon, latlon2 : LatLon,\
     int1 = normalize_vect(rotate_vector (q, rot_axis, rho))
     int2 = normalize_vect(rotate_vector (q, rot_axis, -rho))
 
-    # Calculate fitness of intersections. TODO
+    # Calculate fitness of intersections.
     fitness = 1
     if use_fitness:
         d1 = add_vecs (int1, mult_scalar_vect(-1,a_vec))
@@ -284,17 +284,17 @@ def get_intersections (latlon1 : LatLon, latlon2 : LatLon,\
     ret_tuple = (to_latlon(int1), to_latlon(int2))
     if estimated_position is None:
         return ret_tuple, fitness
-    else:
-        # Check which of the intersections is closest to our estimatedCoordinates
-        best_distance = EARTH_CIRCUMFERENCE
-        best_intersection = None
-        for ints in ret_tuple:
-            the_distance = distance_between_points (ints, estimated_position)
-            if the_distance < best_distance:
-                best_distance = the_distance
-                best_intersection = ints
-        assert best_intersection is not None
-        return best_intersection, fitness
+
+    # Check which of the intersections is closest to our estimatedCoordinates
+    best_distance = EARTH_CIRCUMFERENCE
+    best_intersection = None
+    for ints in ret_tuple:
+        the_distance = distance_between_points (ints, estimated_position)
+        if the_distance < best_distance:
+            best_distance = the_distance
+            best_intersection = ints
+    assert best_intersection is not None
+    return best_intersection, fitness
 
 # Atmospheric refraction