diff --git a/skais/ais/ais_points.py b/skais/ais/ais_points.py
index 3367cfd7e489cd913b5e0de2101eb35063ef7676..2a9df82a1241843d9df6647dba68eb9c43087d9e 100644
--- a/skais/ais/ais_points.py
+++ b/skais/ais/ais_points.py
@@ -36,9 +36,12 @@ from scipy.stats import stats
class AISPoints:
+
+ # Todo: Should be more elegant
def __init__(self, df=None):
if 'ts' in df:
df['ts'] = pd.to_datetime(df.ts)
+ if 'mmsi' in df:
df = df.sort_values(['mmsi', 'ts'])
self.df = df
diff --git a/skais/tests/ais/test_ais_points.py b/skais/tests/ais/test_ais_points.py
index eea6ea7fa877f46d30d6fafd9426313285a4ade8..40fe6b0f1e04ba0493a80dbfead063f377bb98d3 100644
--- a/skais/tests/ais/test_ais_points.py
+++ b/skais/tests/ais/test_ais_points.py
@@ -9,12 +9,29 @@ from skais.ais.ais_trajectory import AISTrajectory
class TestAISPositions(unittest.TestCase):
+ # Lazy test
+ def test_init(self):
+ ais_points = AISPoints(
+ pd.DataFrame(
+ {
+ "sog": [2, 3, 7, 15, 14, 12, 18, 25, 21, 12, 11, 16, 19, 2, 5, 15, 12, 7, 8, 9, 1],
+ "diff": [35, 45, 59, 12, 1, 2, 54, 5, 47, 86, 119, 68, 75, 54, 55, 12, 32, 62, 159, 157, 132],
+ "label": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
+ "ts": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
+ "mmsi": [0 for i in range(21)]
+ }
+ )
+ )
+
+ self.assertIsNotNone(ais_points)
+
def test_describe(self):
ais_points = AISPoints(pd.DataFrame(
{
"sog": [2, 3, 7, 15, 14, 12, 18, 25, 21, 12, 11, 16, 19, 2, 5, 15, 12, 7, 8, 9, 1],
"diff": [35, 45, 59, 12, 1, 2, 54, 5, 47, 86, 119, 68, 75, 54, 55, 12, 32, 62, 159, 157, 132],
"label": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
+ "ts": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
"mmsi": [0 for i in range(21)]
}
))
@@ -29,7 +46,6 @@ class TestAISPositions(unittest.TestCase):
'average diff': 1271 / 21
})
-
def test_remove_outliers_simple(self):
ais_points = AISPoints(pd.DataFrame(
{
@@ -46,7 +62,6 @@ class TestAISPositions(unittest.TestCase):
ais_points.remove_outliers(["cog", "heading"])
pd.testing.assert_frame_equal(expected.reset_index(drop=True), ais_points.df.reset_index(drop=True))
-
def test_remove_outliers_rank(self):
ais_points = AISPoints(pd.DataFrame(
{
@@ -91,7 +106,6 @@ class TestAISPositions(unittest.TestCase):
with self.assertRaises(ValueError):
ais_points.remove_outliers(["cog"], rank=0)
-
def test_clean_angles(self):
ais_points = AISPoints(pd.DataFrame(
{
@@ -161,6 +175,22 @@ class TestAISPositions(unittest.TestCase):
pd.testing.assert_frame_equal(expected.reset_index(drop=True), result.reset_index(drop=True),
check_exact=False, rtol=0.05)
+ def test_normalize_raise(self):
+ ais_points = AISPoints(pd.DataFrame(
+ {
+ "cog": [i for i in range(0, 359, 10)],
+ "heading": [180 for i in range(0, 359, 10)]
+ }
+ )
+ )
+
+ self.assertRaises(
+ ValueError,
+ ais_points.normalize,
+ ['cog', 'heading'],
+ normalization_type="non-existing-normalization"
+ )
+
def test_compute_drift(self):
ais_points = AISPoints(pd.DataFrame(
@@ -226,11 +256,20 @@ class TestAISPositions(unittest.TestCase):
#
# np.testing.assert_array_equal(ground_truth, self.ais_points.histogram_y_knowing_x(x_nb_bins=3))
- # def test_load_from_csv(self):
- # ais_points = AISPoints.load_from_csv("test_load_from_csv.csv")
- #
- # pd.testing.assert_frame_equal(ais_points.df, self.ais_points.df)
+ def test_load_from_csv(self):
+ result = AISPoints.load_from_csv("skais/tests/ais/test_load_from_csv.csv")
+
+ ais_points = AISPoints(pd.DataFrame(
+ {
+ "sog": [2, 3, 7, 15, 14, 12, 18, 25, 21, 12, 11, 16, 19, 2, 5, 15, 12, 7, 8, 9, 1],
+ "diff": [35, 45, 59, 12, 1, 2, 54, 5, 47, 86, 119, 68, 75, 54, 55, 12, 32, 62, 159, 157, 132],
+ "label": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
+ "ts": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
+ "mmsi": [0 for i in range(21)]
+ }
+ ))
+ pd.testing.assert_frame_equal(result.df.reset_index(drop=True), ais_points.df.reset_index(drop=True))
# def test_histogram_x(self):
# ground_truth = np.array([[5, 1, 3],
@@ -241,13 +280,13 @@ class TestAISPositions(unittest.TestCase):
# self.ais_points.histogram(features=["sog", "diff"], bins=3,
# ranges=[[0, 30], [0, 180]]))
-
def test_fuse_single(self):
ais_points = AISPoints(pd.DataFrame(
{
"sog": [2, 3, 7, 15, 14, 12, 18, 25, 21, 12, 11, 16, 19, 2, 5, 15, 12, 7, 8, 9, 1],
"diff": [35, 45, 59, 12, 1, 2, 54, 5, 47, 86, 119, 68, 75, 54, 55, 12, 32, 62, 159, 157, 132],
"label": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
+ "ts": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
"mmsi": [0 for i in range(21)]
}
))
@@ -260,6 +299,7 @@ class TestAISPositions(unittest.TestCase):
"sog": [2, 3, 7, 15, 14, 12, 18, 25, 21, 12, 11, 16, 19, 2, 5, 15, 12, 7, 8, 9, 1],
"diff": [35, 45, 59, 12, 1, 2, 54, 5, 47, 86, 119, 68, 75, 54, 55, 12, 32, 62, 159, 157, 132],
"label": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
+ "ts": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
"mmsi": [0 for i in range(21)]
}
))
@@ -272,6 +312,7 @@ class TestAISPositions(unittest.TestCase):
"sog": [2, 3, 7, 15, 14, 12, 18, 25, 21, 12, 11, 16, 19, 2, 5, 15, 12, 7, 8, 9, 1],
"diff": [35, 45, 59, 12, 1, 2, 54, 5, 47, 86, 119, 68, 75, 54, 55, 12, 32, 62, 159, 157, 132],
"label": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
+ "ts": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
"mmsi": [0 for i in range(21)]
}
))
@@ -284,9 +325,13 @@ class TestAISPositions(unittest.TestCase):
59, 12, 1, 2, 54, 5, 47, 86, 119, 68, 75, 54, 55, 12, 32, 62, 159, 157, 132],
"label": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
+ "ts": [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, 0, 0, 0, 0, 0, 0, 0],
"mmsi": [0 for i in range(42)]
}
)
+
+ value['ts'] = pd.to_datetime(value.ts)
pd.testing.assert_frame_equal(AISPoints.fuse(ais_points, ais_points).df.reset_index(drop=True),
value.reset_index(drop=True))
#
@@ -354,7 +399,6 @@ class TestAISPositions(unittest.TestCase):
# for r, e in zip(result, expected):
# pd.testing.assert_frame_equal(e.reset_index(drop=True), r.df.reset_index(drop=True))
-
# def test_disjointed_histogram_label_none(self):
# ais_points = AISPoints(pd.DataFrame(
# {
@@ -425,5 +469,3 @@ class TestAISPositions(unittest.TestCase):
#
# for r, e in zip(result, expected):
# np.testing.assert_array_equal(e, r[0])
-
-
diff --git a/skais/tests/ais/test_load_from_csv.csv b/skais/tests/ais/test_load_from_csv.csv
index c0de7772d0f91aeabdf5f6b43ffe92ffa24092f4..0b13d5a623b95755e49b1a787b54f67a568d0703 100644
--- a/skais/tests/ais/test_load_from_csv.csv
+++ b/skais/tests/ais/test_load_from_csv.csv
@@ -1,22 +1,22 @@
-sog,diff,label,mmsi
-2,35,0,0
-3,45,0,0
-7,59,0,0
-15,12,0,0
-14,1,0,0
-12,2,0,0
-18,54,0,0
-25,5,0,0
-21,47,0,0
-12,86,0,0
-11,119,0,0
-16,68,0,0
-19,75,0,0
-2,54,1,0
-5,55,1,0
-15,12,1,0
-12,32,1,0
-7,62,1,0
-8,159,1,0
-9,157,1,0
-1,132,1,0
\ No newline at end of file
+sog,diff,label,ts,mmsi
+2,35,0,0,0
+3,45,0,0,0
+7,59,0,0,0
+15,12,0,0,0
+14,1,0,0,0
+12,2,0,0,0
+18,54,0,0,0
+25,5,0,0,0
+21,47,0,0,0
+12,86,0,0,0
+11,119,0,0,0
+16,68,0,0,0
+19,75,0,0,0
+2,54,1,1,0
+5,55,1,1,0
+15,12,1,1,0
+12,32,1,1,0
+7,62,1,1,0
+8,159,1,1,0
+9,157,1,1,0
+1,132,1,1,0
\ No newline at end of file