Merge branch '20-get-time-windows-for-labels' into 'develop'

Resolve "Get time windows for labels"

See merge request !8

requirements.txt

 pandas~=1.1.5
 setuptools~=57.0.0
 numpy~=1.19.5
-numba~=0.53.1
+numba>0.53.1
 scipy~=1.5.4
 hmmlearn~=0.2.6
 scikit-learn~=1.0.1

skais/ais/ais_trajectory.py

@@ -214,3 +214,12 @@ class AISTrajectory(AISPoints):
             return self
         else:
             return AISTrajectory(new_df, mmsi=self.mmsi)
+
+    def get_time_per_label_shift(self, label_column='label'):
+        current_label = -1
+        result = []
+        for index, row in self.df.iterrows():
+            if current_label != row[label_column]:
+                current_label = row[label_column]
+                result.append((row['ts_sec'], current_label))
+        return result
\ No newline at end of file

skais/tests/ais/test_ais_trajectory.py

@@ -334,3 +334,48 @@ class TestAISTrajectory(unittest.TestCase):
         expected = np.array([2, 2, 2, 2, 2])
 
         np.testing.assert_equal(result, expected)
+
+    def test_get_time_per_label_shift_single_label(self):
+        trajectory = AISTrajectory(
+            pd.DataFrame(
+                {
+                    "label": [1 for _ in range(0, 101, 10)],
+                    "ts_sec": [i for i in range(0, 6001, 600)]
+                }
+            )
+        )
+
+        result = trajectory.get_time_per_label_shift()
+        expected = [(0, 1)]
+
+        self.assertListEqual(result, expected)
+
+    def test_get_time_per_label_shift_label_switch_1(self):
+        trajectory = AISTrajectory(
+            pd.DataFrame(
+                {
+                    "label": [1 for _ in range(11)] + [2 for _ in range(10)],
+                    "ts_sec": [i for i in range(0, 12001, 600)]
+                }
+            )
+        )
+
+        result = trajectory.get_time_per_label_shift()
+        expected = [(0, 1), (6600, 2)]
+
+        self.assertListEqual(result, expected)
+
+    def test_get_time_per_label_shift_label_switch_2(self):
+        trajectory = AISTrajectory(
+            pd.DataFrame(
+                {
+                    "label": [1 for _ in range(11)] + [2 for _ in range(10)]+ [1 for _ in range(10)],
+                    "ts_sec": [i for i in range(0, 18001, 600)]
+                }
+            )
+        )
+
+        result = trajectory.get_time_per_label_shift()
+        expected = [(0, 1), (6600, 2), (12600, 1)]
+
+        self.assertListEqual(result, expected)
\ No newline at end of file

skais/utils/geography.py

-from sklearn.metrics.pairwise import haversine_distances
 import numpy as np
 from numba import jit