Draft: Develop

Improvements:

• Normalization using AIS_Points now raise exception if given a bad dictionary

New features:

• Added choosing fields for generating images for adding channels
• Added centering of image on last point
• Added chosing bounding box of image
• Added selecting range of values for features

skais/ais/ais_trajectory.py

@@ -60,14 +60,16 @@ def apply_time_sequence(dat, time, func):
     return result
 
 
+@jit(nopython=True)
 def __get_image_value__(features, bounds):
-    if len(bounds) < 1:
-        return [1]
-    value = []
+    value = np.zeros((len(features)))
+    i = 0
     for f, b in zip(features, bounds):
-        value.append(1 - (b[1] - f - b[0]) / (b[1] - b[0]))
+        value[i] = (1 - (b[1] - f - b[0]) / (b[1] - b[0]))
+        i = i + 1
     return value
 
+
 def __get_bounding_box__(bounding_box, positions, ref_index):
     if bounding_box == 'fit':
         lower_lon, upper_lon = (min(positions[:, 0]), max(positions[:, 0]))
@@ -110,6 +112,73 @@ def __get_bounding_box__(bounding_box, positions, ref_index):
 
     return lower_lon, upper_lon, lower_lat, upper_lat
 
+
+@jit(nopython=True)
+def generate_points(data, positions, height, width, node_size, lower_lat, upper_lat, lower_lon, upper_lon):
+    for longitude, latitude in positions:
+        x_coord, y_coord = get_coord(latitude, longitude, height, width, lower_lat, upper_lat, lower_lon,
+                                     upper_lon)
+
+        x_lower_bound = max(0, x_coord - node_size)
+        x_upper_bound = min(height - 1, x_coord + node_size)
+
+        y_lower_bound = max(0, y_coord - node_size)
+        y_upper_bound = min(width - 1, y_coord + node_size)
+
+        for x in range(x_lower_bound, x_upper_bound + 1):
+            for y in range(y_lower_bound, y_upper_bound + 1):
+                data[x, y] = [1]
+
+
+@jit(nopython=True)
+def generate_links(data, positions, height, width, lower_lat, upper_lat, lower_lon, upper_lon):
+    lon, lat = positions[0, 0], positions[0, 1]
+    for longitude, latitude in positions[1:]:
+        x_prv, y_prev = get_coord(lat, lon, height, width, lower_lat, upper_lat, lower_lon, upper_lon)
+        x_nxt, y_nxt = get_coord(latitude, longitude, height, width, lower_lat, upper_lat, lower_lon,
+                                 upper_lon)
+
+        lon, lat = longitude, latitude
+        for x, y in bresenham(x_prv, y_prev, x_nxt, y_nxt):
+            data[x, y] = [1]
+
+
+@jit(nopython=True)
+def generate_points_with_features(data, positions, features_vectors, bounds, node_size, height, width,
+                                  lower_lat, upper_lat, lower_lon, upper_lon, link):
+    for pos, f in zip(positions, features_vectors):
+        latitude = pos[1]
+        longitude = pos[0]
+        x_coord, y_coord = get_coord(latitude, longitude, height, width, lower_lat, upper_lat, lower_lon,
+                                     upper_lon)
+        value = __get_image_value__(f, bounds)
+        x_lower_bound = max(0, x_coord - node_size)
+        x_upper_bound = min(height - 1, x_coord + node_size)
+
+        y_lower_bound = max(0, y_coord - node_size)
+        y_upper_bound = min(width - 1, y_coord + node_size)
+
+        for x in range(x_lower_bound, x_upper_bound + 1):
+            for y in range(y_lower_bound, y_upper_bound + 1):
+                for i, v in enumerate(value):
+                    data[x, y, i] = v
+    if link:
+        lon, lat = positions[0, 0], positions[0, 1]
+
+        value = __get_image_value__(features_vectors[0], bounds)
+        for pos, f in zip(positions[1:], features_vectors[1:]):
+            latitude = pos[1]
+            longitude = pos[0]
+            x_prv, y_prev = get_coord(lat, lon, height, width, lower_lat, upper_lat, lower_lon, upper_lon)
+            x_nxt, y_nxt = get_coord(latitude, longitude, height, width, lower_lat, upper_lat, lower_lon,
+                                     upper_lon)
+            lon, lat = longitude, latitude
+            for x, y in bresenham(x_prv, y_prev, x_nxt, y_nxt):
+                for i, v in enumerate(value):
+                    data[x, y, i] = v
+            value = __get_image_value__(f, bounds)
+
+
 class AISTrajectory(AISPoints):
     def __init__(self, df, mmsi=0, interpolation_time=None):
         df = df.drop_duplicates(subset=['ts_sec'])
@@ -276,8 +345,6 @@ class AISTrajectory(AISPoints):
                 result.append((row['ts_sec'], current_label))
         return result
 
-
-
     def generate_array_from_positions(self, height=256, width=256, link=True, bounding_box='fit', ref_index=-1,
                                       features=None, node_size=0):
 
@@ -310,59 +377,12 @@ class AISTrajectory(AISPoints):
 
         if features_vectors is None:
 
-            for longitude, latitude in positions:
-                x_coord, y_coord = get_coord(latitude, longitude, height, width, lower_lat, upper_lat, lower_lon,
-                                             upper_lon)
-
-                x_lower_bound = max(0, x_coord - node_size)
-                x_upper_bound = min(height - 1, x_coord + node_size)
+            generate_points(data, positions, height, width, node_size, lower_lat, upper_lat, lower_lon, upper_lon)
 
-                y_lower_bound = max(0, y_coord - node_size)
-                y_upper_bound = min(width - 1, y_coord + node_size)
-
-                for x in range(x_lower_bound, x_upper_bound + 1):
-                    for y in range(y_lower_bound, y_upper_bound + 1):
-                        data[x, y] = [1]
             if link:
-                lon, lat = positions[0, 0], positions[0, 1]
-                for longitude, latitude in positions[1:]:
-                    x_prv, y_prev = get_coord(lat, lon, height, width, lower_lat, upper_lat, lower_lon, upper_lon)
-                    x_nxt, y_nxt = get_coord(latitude, longitude, height, width, lower_lat, upper_lat, lower_lon,
-                                             upper_lon)
-
-                    lon, lat = longitude, latitude
-                    for x, y in bresenham(x_prv, y_prev, x_nxt, y_nxt):
-                        data[x, y] = [1]
+                generate_links(data, positions, height, width, lower_lat, upper_lat, lower_lon, upper_lon)
+
         else:
-            for pos, f in zip(positions, features_vectors):
-                latitude = pos[1]
-                longitude = pos[0]
-                x_coord, y_coord = get_coord(latitude, longitude, height, width, lower_lat, upper_lat, lower_lon,
-                                             upper_lon)
-                value = __get_image_value__(f, bounds)
-                x_lower_bound = max(0, x_coord - node_size)
-                x_upper_bound = min(height - 1, x_coord + node_size)
-
-                y_lower_bound = max(0, y_coord - node_size)
-                y_upper_bound = min(width - 1, y_coord + node_size)
-
-                for x in range(x_lower_bound, x_upper_bound + 1):
-                    for y in range(y_lower_bound, y_upper_bound + 1):
-                        for i, v in enumerate(value):
-                            data[x, y, i] = v
-                if link:
-                    lon, lat = positions[0, 0], positions[0, 1]
-
-                    value = __get_image_value__(features_vectors[0], bounds)
-                    for pos, f in zip(positions[1:], features_vectors[1:]):
-                        latitude = pos[1]
-                        longitude = pos[0]
-                        x_prv, y_prev = get_coord(lat, lon, height, width, lower_lat, upper_lat, lower_lon, upper_lon)
-                        x_nxt, y_nxt = get_coord(latitude, longitude, height, width, lower_lat, upper_lat, lower_lon,
-                                                 upper_lon)
-                        lon, lat = longitude, latitude
-                        for x, y in bresenham(x_prv, y_prev, x_nxt, y_nxt):
-                            for i, v in enumerate(value):
-                                data[x, y, i] = v
-                        value = __get_image_value__(f, bounds)
+            generate_points_with_features(data, positions, features_vectors, bounds, node_size, height, width,
+                                          lower_lat, upper_lat, lower_lon, upper_lon, link)
         return data