generating linearly interpolated links

skais/ais/ais_trajectory.py

@@ -9,7 +9,7 @@ from scipy.interpolate import interp1d
 
 from skais.utils.geography import great_circle, position_from_distance, get_coord
 from skais.ais.ais_points import AISPoints
-from skais.utils.geometry import bresenham
+from skais.utils.geometry import bresenham, dist_on_grid
 
 
 @jit(nopython=True)
@@ -153,7 +153,7 @@ def generate_points_with_features(data, positions, features_vectors, bounds, nod
 
 
 @jit(nopython=True)
-def generate_links(data, positions, height, width, lower_lat, upper_lat, lower_lon, upper_lon, values):
+def generate_links(data, positions, height, width, lower_lat, upper_lat, lower_lon, upper_lon, values, interpolate=None):
     lon, lat = positions[0, 0], positions[0, 1]
 
     current_value = values[0]
@@ -164,6 +164,16 @@ def generate_links(data, positions, height, width, lower_lat, upper_lat, lower_l
         x_nxt, y_nxt = get_coord(latitude, longitude, height, width, lower_lat, upper_lat, lower_lon,
                                  upper_lon)
         lon, lat = longitude, latitude
+        if interpolate is not None and nxt_value != current_value:
+            dist = dist_on_grid(x_prv, y_prev, x_nxt, y_nxt)
+            for x, y in bresenham(x_prv, y_prev, x_nxt, y_nxt):
+                dist_prev = dist_on_grid(x_prv, y_prev, x, y)
+                dist_next = dist_on_grid(x, y, x_nxt, y_nxt)
+
+                pixel_color = current_value * (1-dist_prev/dist) + nxt_value * (1-dist_next/dist)
+                for i in range(len(pixel_color)):
+                    data[x, y, i] = pixel_color[i]
+        else:
             for x, y in bresenham(x_prv, y_prev, x_nxt, y_nxt):
                 for i in range(len(current_value)):
                     data[x, y, i] = current_value[i]
@@ -349,7 +359,7 @@ class AISTrajectory(AISPoints):
         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):
+                                      features=None, node_size=0, interpolation=None):
 
         positions = self.df[['longitude', 'latitude']].to_numpy()
 
@@ -377,7 +387,7 @@ class AISTrajectory(AISPoints):
             bounds = np.array(bounds)
         else:
             nb_channels = 1
-        data = np.zeros((height, width, nb_channels), dtype=np.float)
+        data = np.zeros((height, width, nb_channels), dtype=float)
 
         if features_vectors is None:
 
@@ -392,5 +402,5 @@ class AISTrajectory(AISPoints):
                                           lower_lat, upper_lat, lower_lon, upper_lon, )
             if link:
                 generate_links(data, positions, height, width, lower_lat, upper_lat, lower_lon, upper_lon,
-                               generate_values(features_vectors, bounds))
+                               generate_values(features_vectors, bounds), interpolation)
         return data

skais/tests/ais/test_ais_trajectory.py

@@ -653,7 +653,6 @@ class TestAISTrajectoryImageGeneration(unittest.TestCase):
 
         np.testing.assert_array_equal(result, expected)
 
-
     def test_generate_array_interpolate_links(self):
         trajectory = AISTrajectory(
             pd.DataFrame(
@@ -667,15 +666,17 @@ class TestAISTrajectoryImageGeneration(unittest.TestCase):
         )
 
         result = trajectory.generate_array_from_positions(height=9, width=18, link=True, bounding_box='fit',
-                                                          features={"sog": (0, 80)}, node_size=0).reshape((9, 18), interpolation='linear')
+                                                          features={"sog": (0, 80)},  node_size=0,
+                                                          interpolation='linear').reshape((9, 18))
+        print(result)
         expected = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5],
-                             [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5],
-                             [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5],
-                             [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5],
-                             [0, 0, 0, 0, 0, 0, 0, 0.25, 0.25, 0.25, 0, 0, 0, 0, 0, 0, 0, 0.5],
-                             [0, 0, 0, 0, 0, 0.25, 0.25, 0, 0, 0, 0.25, 0.25, 0, 0, 0, 0, 0, 0.5],
-                             [0, 0, 0, 0.25, 0.25, 0, 0, 0, 0, 0, 0, 0, 0.25, 0.25, 0, 0, 0, 0.5],
-                             [0, 0.25, 0.25, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.25, 0.25, 0, 0.5],
-                             [0.25, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.25, 0.5]]) / 2
+                             [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.46875],
+                             [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.4375],
+                             [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.40625],
+                             [0, 0, 0, 0, 0, 0, 0, 0.125, 0.125, 0.13526987, 0, 0, 0, 0, 0, 0, 0, 0.375],
+                             [0, 0, 0, 0, 0, 0.125, 0.125, 0, 0, 0, 0.15330406, 0.16458619, 0, 0, 0, 0, 0, 0.34375],
+                             [0, 0, 0, 0.125, 0.125, 0, 0, 0, 0, 0, 0, 0, 0.18154526, 0.19313327, 0, 0, 0, 0.3125],
+                             [0, 0.125, 0.125, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.20959047, 0.22158235, 0, 0.28125],
+                             [0.125, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.23609719, 0.25]])
 
         np.testing.assert_array_almost_equal(result, expected)

skais/utils/geometry.py

+import numpy as np
 from numba import jit
 
+@jit(nopython=True)
+def dist_on_grid(x1, y1, x2, y2):
+    dx = int(x2 - x1)
+    dy = int(y2 - y1)
+    return np.sqrt(dx ** 2 + dy ** 2)
+
 
 @jit(nopython=True)
 def bresenham(x1, y1, x2, y2):
@@ -12,7 +19,6 @@ def bresenham(x1, y1, x2, y2):
     if dy < 0:
         sy = -1
 
-
     pixels = []
     if abs(dx) > abs(dy):  # slope < 1
         if x1 > x2:
@@ -59,4 +65,3 @@ def bresenham(x1, y1, x2, y2):
             pixels.append((x, y))
 
     return pixels
-