diff --git a/skais/ais/ais_trajectory.py b/skais/ais/ais_trajectory.py
index b719d3de5350b6ba15da13c857dd69462ac711c0..359705c1cc71a2db79d7b5c952fe5bc02c64b727 100644
--- a/skais/ais/ais_trajectory.py
+++ b/skais/ais/ais_trajectory.py
@@ -154,7 +154,7 @@ def apply_time_sequence(dat, time, func):
class AISTrajectory(AISPoints):
def __init__(self, df, interpolation_time=None):
- df = df.drop_duplicates(subset=['ts_sec'])
+ # df = df.drop_duplicates(subset=['ts_sec'])
if interpolation_time and len(df.index) > 4:
@@ -184,9 +184,6 @@ class AISTrajectory(AISPoints):
# self.df = df.dropna()
AISPoints.__init__(self, df)
- def __eq__(self, other):
- return self.df.equals(other.df)
-
def sliding_window(self, size=10, offset=1, fields=None):
result = []
@@ -208,7 +205,8 @@ class AISTrajectory(AISPoints):
else:
self.df[new_column] = result
- def apply_time_sequence_func(self, func, column, new_column=None):
+ # TODO rename function/simplify
+ def apply_func_on_time_sequence(self, func, column, new_column=None):
dat = self.df[column].to_numpy()
time = self.df['ts_sec'].to_numpy()
diff --git a/skais/tests/ais/test_ais_trajectory.py b/skais/tests/ais/test_ais_trajectory.py
index 78fff0bb0b83fc724d6671a4d2ad9582d00b00c8..0e5ded1d6854814e1ab7cb8737b764c8c3b94435 100644
--- a/skais/tests/ais/test_ais_trajectory.py
+++ b/skais/tests/ais/test_ais_trajectory.py
@@ -1,5 +1,7 @@
import unittest
+import numpy as np
+
from skais.ais.ais_trajectory import *
@@ -28,7 +30,8 @@ class TestAISTrajectory(unittest.TestCase):
# def test_get_stopped_snippets_multi_snippets(self):
# ais_trajectory = AISTrajectory(pd.DataFrame(
# {
- # "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, 1, 1, 1, 0, 0, 0],
+ # "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, 1, 1, 1, 0, 0, 0],
# "ts_sec": [i * 60 for i in range(31)]
# }
# ))
@@ -167,7 +170,7 @@ class TestAISTrajectory(unittest.TestCase):
pd.DataFrame(
{
"ts_sec": [i for i in range(0, 6001, 600)],
- "label": [0 for i in range(0, 3001, 600)] + [1 for i in range(3001, 6001, 600)]
+ "label": [0 for _ in range(0, 3001, 600)] + [1 for _ in range(3001, 6001, 600)]
}
),
interpolation_time=5
@@ -176,7 +179,7 @@ class TestAISTrajectory(unittest.TestCase):
expected = pd.DataFrame(
{
"ts_sec": [i for i in range(0, 6001, 300)],
- "label": [0 for i in range(0, 3301, 300)] + [1 for i in range(3301, 6001, 300)]
+ "label": [0 for _ in range(0, 3301, 300)] + [1 for _ in range(3301, 6001, 300)]
}
)
@@ -205,7 +208,7 @@ class TestAISTrajectory(unittest.TestCase):
pd.DataFrame(
{
"ts_sec": [i for i in range(4001, 7001, 600)],
- "label": [1 for i in range(4001, 7001, 600)]
+ "label": [1 for _ in range(4001, 7001, 600)]
}
)
)
@@ -213,6 +216,161 @@ class TestAISTrajectory(unittest.TestCase):
for e, r in zip(expected, trajectory.split_trajectory(800)):
pd.testing.assert_frame_equal(e.df.reset_index(drop=True), r.df.reset_index(drop=True))
+
+ def test_split_trajectory_raise(self):
+ trajectory = AISTrajectory(
+ pd.DataFrame(
+ {
+ "label": [0 for _ in range(0, 3001, 600)] + [1 for _ in range(4001, 7001, 600)]
+ }
+ )
+ )
+ self.assertRaises(NoTimeInformation, trajectory.split_trajectory)
+
+ def test_apply_func_on_points_no_column(self):
+ trajectory = AISTrajectory(
+ pd.DataFrame(
+ {
+ "sog": [i for i in range(100)]
+ }
+ )
+ )
+ expected = pd.DataFrame(
+ {
+ "sog": [np.sqrt(i) for i in range(100)]
+ }
+ )
+
+ trajectory.apply_func_on_points(np.sqrt, 'sog')
+
+ result = trajectory.df
+
+ pd.testing.assert_frame_equal(expected.reset_index(drop=True), result.reset_index(drop=True))
+
+
+ def test_apply_func_on_points(self):
+ trajectory = AISTrajectory(
+ pd.DataFrame(
+ {
+ "sog": [i for i in range(100)]
+ }
+ )
+ )
+ expected = pd.DataFrame(
+ {
+ "sog": [i for i in range(100)],
+ "sqrt_sog": [np.sqrt(i) for i in range(100)]
+ }
+ )
+
+ trajectory.apply_func_on_points(np.sqrt, 'sog', 'sqrt_sog')
+
+ result = trajectory.df
+
+ pd.testing.assert_frame_equal(expected.reset_index(drop=True), result.reset_index(drop=True))
+
+
+ def test_apply_func_on_time_sequence_no_column(self):
+ def sog_div_ts(p1, _, t1, __):
+ return p1 / t1
+
+ trajectory = AISTrajectory(
+ pd.DataFrame(
+ {
+ "sog": [i + 1 for i in range(100)],
+ "ts_sec": [i + 1 for i in range(100)]
+ }
+ )
+ )
+ expected = pd.DataFrame(
+ {
+ "sog": [1.0 for _ in range(100)],
+ "ts_sec": [i + 1 for i in range(100)]
+ }
+ )
+
+ trajectory.apply_func_on_time_sequence(sog_div_ts, 'sog')
+
+ result = trajectory.df
+
+ pd.testing.assert_frame_equal(expected.reset_index(drop=True), result.reset_index(drop=True))
+
+ def test_apply_func_on_time_sequence(self):
+ def sog_div_ts(p1, _, t1, __):
+ return p1 / t1
+
+ trajectory = AISTrajectory(
+ pd.DataFrame(
+ {
+ "sog": [i + 1 for i in range(100)],
+ "ts_sec": [i + 1 for i in range(100)]
+ }
+ )
+ )
+ expected = pd.DataFrame(
+ {
+ "sog": [i + 1 for i in range(100)],
+ "ts_sec": [i + 1 for i in range(100)],
+ "div": [1.0 for _ in range(100)]
+ }
+ )
+
+ trajectory.apply_func_on_time_sequence(sog_div_ts, 'sog', 'div')
+
+ result = trajectory.df
+
+ pd.testing.assert_frame_equal(expected.reset_index(drop=True), result.reset_index(drop=True))
+
+ def test_apply_func_on_time_window_no_column(self):
+ trajectory = AISTrajectory(
+ pd.DataFrame(
+ {
+ "sog": [i for i in range(100)]
+ }
+ )
+ )
+ expected = pd.DataFrame(
+ {
+ "sog": [0.6, 1.2] +
+ [np.average(np.array([i - 2, i - 1, i, i + 1, i + 2])) for i in range(2, 98)] +
+ [97.8, 98.4]
+ }
+ )
+
+ trajectory.apply_func_on_time_window(np.average, 2, 'sog', )
+
+ result = trajectory.df
+
+ pd.testing.assert_frame_equal(expected.reset_index(drop=True), result.reset_index(drop=True))
+
+ def test_apply_func_on_time_window(self):
+ trajectory = AISTrajectory(
+ pd.DataFrame(
+ {
+ "sog": [i for i in range(100)]
+ }
+ )
+ )
+ expected = pd.DataFrame(
+ {
+ "sog": [i for i in range(100)],
+ "mean": [0.6, 1.2] +
+ [np.average(np.array([i - 2, i - 1, i, i + 1, i + 2])) for i in range(2, 98)] +
+ [97.8, 98.4]
+ }
+ )
+
+ trajectory.apply_func_on_time_window(np.average, 2, 'sog', 'mean')
+
+ result = trajectory.df
+
+ pd.testing.assert_frame_equal(expected.reset_index(drop=True), result.reset_index(drop=True))
+
+ def test_compute_trajectory(self):
+ times = np.array([i for i in range(0, 3001, 600)] + [i for i in range(4001, 7001, 600)])
+
+ self.assertEqual(6, compute_trajectory.py_func(times, 800))
+
# def test_compute_angle_l1(self):
# trajectory = AISTrajectory(
# pd.DataFrame(
@@ -280,4 +438,4 @@ class TestAISTrajectory(unittest.TestCase):
# dat = [(0, i * 10) for i in range(5)] + [(0, 50 - i * 10) for i in range(5)]
# result = compute_position_dist_std(dat, 2)
#
- # # hard to test
\ No newline at end of file
+ # # hard to test