File size: 1,472 Bytes
2e6f68f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | #!/usr/bin/env python3
"""Regression tests for distinguishing observed sensor rows from instructions."""
import unittest
from convert_videos import parse_timeseries_block, parse_timeseries_data_line
class SensorRowTests(unittest.TestCase):
def test_format_example_is_not_an_observation(self) -> None:
self.assertIsNone(parse_timeseries_data_line("t(s): speed=, acceleration=, steering="))
def test_instruction_with_commas_is_not_an_observation(self) -> None:
self.assertIsNone(parse_timeseries_data_line("Per-frame sensor data, missing = unavailable:"))
def test_actual_missing_observations_are_preserved(self) -> None:
row = parse_timeseries_data_line("1.5: speed=10, acceleration=null")
self.assertEqual(row["speed"], 10)
self.assertNotEqual(row["acceleration"], row["acceleration"])
def test_iso_timestamp_rows_are_still_supported(self) -> None:
self.assertEqual(parse_timeseries_data_line("2024-06-30T12:00:00Z, speed=10"), {"speed": 10})
def test_template_line_does_not_increase_sequence_length(self) -> None:
frame = parse_timeseries_block(
"<timeseries>\nOne-line format example:\nt(s): speed=, acceleration=\n"
"1.0: speed=10, acceleration=null\n1.5: speed=9, acceleration=-1\n</timeseries>"
)
self.assertEqual(frame.shape, (2, 2))
self.assertEqual(frame["speed"].tolist(), [10, 9])
if __name__ == "__main__":
unittest.main()
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