diff --git a/skais/ais/ais_trajectory.py b/skais/ais/ais_trajectory.py
index a08674ec4e24e3110fb4a35af84731bbb632f83c..7e1307e18352bf3caf025b5d89c6d73f1f02faba 100644
--- a/skais/ais/ais_trajectory.py
+++ b/skais/ais/ais_trajectory.py
@@ -62,7 +62,7 @@ def apply_time_sequence(dat, time, func):
def __get_image_value__(features, bounds):
value = []
for f, b in zip(features, bounds):
- value.append(1 - (b[1] - f) / b[1])
+ value.append(1 - (b[1] - f - b[0]) / (b[1] - b[0]))
return value
@@ -236,12 +236,11 @@ class AISTrajectory(AISPoints):
node_size=0):
nb_channels = 1
+ positions = self.df[['longitude', 'latitude']].to_numpy()
if bounding_box == 'fit':
- positions = self.df[['longitude', 'latitude']].to_numpy()
lower_lon, upper_lon = (min(positions[:, 0]), max(positions[:, 0]))
lower_lat, upper_lat = (min(positions[:, 1]), max(positions[:, 1]))
elif bounding_box == 'centered':
- positions = self.df[['longitude', 'latitude']].to_numpy()
center_lon, center_lat = positions[-1]
min_lon, max_lon = (min(positions[:, 0]), max(positions[:, 0]))
min_lat, max_lat = (min(positions[:, 1]), max(positions[:, 1]))
@@ -253,7 +252,11 @@ class AISTrajectory(AISPoints):
lower_lat = center_lat - distance_to_center
upper_lon = center_lon + distance_to_center
lower_lon = center_lon - distance_to_center
-
+ elif type(bounding_box) is list:
+ upper_lon = bounding_box[1][0]
+ lower_lon = bounding_box[0][0]
+ upper_lat = bounding_box[1][1]
+ lower_lat = bounding_box[0][1]
else:
raise ValueError(f"Option not supported: {bounding_box}")
@@ -291,17 +294,23 @@ class AISTrajectory(AISPoints):
data[x, y] = [1]
else:
+ bounds = []
if type(features) is list:
nb_channels = len(features)
+ features_vectors = self.df[features].to_numpy()
+ for c in features_vectors.T:
+ bounds.append((0, max(c)))
elif type(features) is str:
- features = [features]
+ features_vectors = self.df[[features]].to_numpy()
+ for c in features_vectors.T:
+ bounds.append((0, max(c)))
+ elif type(features) is dict:
+ bounds = list(features.values())
+ features_vectors = self.df[features.keys()].to_numpy()
else:
raise TypeError("Type not supported")
data = np.zeros((height, width, nb_channels), dtype=np.float)
- features_vectors = self.df[features].to_numpy()
- bounds = []
- for c in features_vectors.T:
- bounds.append((min(c), max(c)))
+
for pos, f in zip(positions, features_vectors):
latitude = pos[1]
diff --git a/skais/tests/ais/test_ais_trajectory.py b/skais/tests/ais/test_ais_trajectory.py
index 68085c864532384f6046e8dfa98dcce3dfa12b07..56aa71cd0dfbc24deed6671584a38f7862a732e8 100644
--- a/skais/tests/ais/test_ais_trajectory.py
+++ b/skais/tests/ais/test_ais_trajectory.py
@@ -380,6 +380,7 @@ class TestAISTrajectory(unittest.TestCase):
self.assertListEqual(result, expected)
+
class TestAISTrajectoryImageGeneration(unittest.TestCase):
def setUp(self) -> None:
self.trajectory = AISTrajectory(
@@ -394,7 +395,7 @@ class TestAISTrajectoryImageGeneration(unittest.TestCase):
def test_generate_array_from_positions(self):
result = self.trajectory.generate_array_from_positions(height=9, width=9, link=False, bounding_box='fit',
- features=None, node_size=0).reshape((9, 9))
+ features=None, node_size=0).reshape((9, 9))
expected = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
@@ -408,9 +409,8 @@ class TestAISTrajectoryImageGeneration(unittest.TestCase):
np.testing.assert_array_equal(result, expected)
def test_generate_array_from_positions_node_size(self):
-
result = self.trajectory.generate_array_from_positions(height=9, width=9, link=False, bounding_box='fit',
- features=None, node_size=1).reshape((9, 9))
+ features=None, node_size=1).reshape((9, 9))
expected = np.array([[0, 0, 0, 0, 0, 0, 0, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
@@ -505,7 +505,7 @@ class TestAISTrajectoryImageGeneration(unittest.TestCase):
"latitude": [0, 10, 0, 20],
"longitude": [0, 10, 20, 20],
"ts_sec": [i for i in range(4)],
- "sog": [10,10,20,40]
+ "sog": [10, 10, 20, 40]
}
)
)
@@ -531,7 +531,7 @@ class TestAISTrajectoryImageGeneration(unittest.TestCase):
"latitude": [0, 10, 0, 20],
"longitude": [0, 10, 20, 20],
"ts_sec": [i for i in range(4)],
- "sog": [10,10,20,40],
+ "sog": [10, 10, 20, 40],
"cog": [40, 20, 10, 10]
}
)
@@ -539,15 +539,24 @@ class TestAISTrajectoryImageGeneration(unittest.TestCase):
result = trajectory.generate_array_from_positions(height=9, width=18, link=True, bounding_box='fit',
features=['sog', 'cog'], node_size=0)
- expected = np.array([[[0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0.5,0.25]],
- [[0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0.5,0.25]],
- [[0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0.5,0.25]],
- [[0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0.5,0.25]],
- [[0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0.25,1], [0.25,0.5], [0.25,0.5], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0.5,0.25]],
- [[0,0], [0,0], [0,0], [0,0], [0,0], [0.25,1], [0.25,1], [0,0], [0,0], [0,0], [0.25,0.5], [0.25,0.5], [0,0], [0,0], [0,0], [0,0], [0,0], [0.5,0.25]],
- [[0,0], [0,0], [0,0], [0.25,1], [0.25,1], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0.25,0.5], [0.25,0.5], [0,0], [0,0], [0,0], [0.5,0.25]],
- [[0,0], [0.25,1], [0.25,1], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0.25,0.5], [0.25,0.5], [0,0], [0.5,0.25]],
- [[0.25,1], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0,0], [0.25,0.5], [0.5,0.25]]])
+ expected = np.array([[[0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0],
+ [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0.5, 0.25]],
+ [[0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0],
+ [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0.5, 0.25]],
+ [[0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0],
+ [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0.5, 0.25]],
+ [[0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0],
+ [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0.5, 0.25]],
+ [[0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0.25, 1], [0.25, 0.5],
+ [0.25, 0.5], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0.5, 0.25]],
+ [[0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0.25, 1], [0.25, 1], [0, 0], [0, 0], [0, 0],
+ [0.25, 0.5], [0.25, 0.5], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0.5, 0.25]],
+ [[0, 0], [0, 0], [0, 0], [0.25, 1], [0.25, 1], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0],
+ [0, 0], [0, 0], [0.25, 0.5], [0.25, 0.5], [0, 0], [0, 0], [0, 0], [0.5, 0.25]],
+ [[0, 0], [0.25, 1], [0.25, 1], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0],
+ [0, 0], [0, 0], [0, 0], [0, 0], [0.25, 0.5], [0.25, 0.5], [0, 0], [0.5, 0.25]],
+ [[0.25, 1], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0],
+ [0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0.25, 0.5], [0.5, 0.25]]])
np.testing.assert_array_equal(result, expected)
@@ -567,7 +576,8 @@ class TestAISTrajectoryImageGeneration(unittest.TestCase):
np.testing.assert_array_equal(result, expected)
def test_generate_array_bounding_box(self):
- result = self.trajectory.generate_array_from_positions(height=9, width=9, link=False, bounding_box=[(0, 0), (10,10)],
+ result = self.trajectory.generate_array_from_positions(height=9, width=9, link=False,
+ bounding_box=[(0, 0), (10, 10)],
features=None, node_size=0).reshape((9, 9))
expected = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
@@ -577,24 +587,24 @@ class TestAISTrajectoryImageGeneration(unittest.TestCase):
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
- [1, 0, 0, 0, 0, 0, 0, 0, 0]])
+ [1, 0, 0, 0, 0, 0, 0, 0, 1]])
np.testing.assert_array_equal(result, expected)
- def test_generate_array_from_positions_with_line_grey_scale(self):
+ def test_generate_array_feature_bounds(self):
trajectory = AISTrajectory(
pd.DataFrame(
{
"latitude": [0, 10, 0, 20],
"longitude": [0, 10, 20, 20],
"ts_sec": [i for i in range(4)],
- "sog": [10,10,20,40]
+ "sog": [10, 10, 20, 40]
}
)
)
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))
+ features={"sog": (0, 80)}, node_size=0).reshape((9, 18))
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],
@@ -603,6 +613,6 @@ class TestAISTrajectoryImageGeneration(unittest.TestCase):
[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
+ [0.25, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.25, 0.5]]) / 2
- np.testing.assert_array_equal(result, expected)
\ No newline at end of file
+ np.testing.assert_array_equal(result, expected)