test_snapshot module
Tests for weighted least squres in snapshot
- test_snapshot.fixture_set_sv_states()[source]
Get position of 4 satellite in ECEF coordinates.
See reference [1] for details.
- Returns:
pos_sv_m – Satellite positions in ECEF frame as an array of shape [# svs x 3] where the columns contain in order x_sv_m, y_sv_m, and z_sv_m.
- Return type:
np.ndarray
References
- test_snapshot.fixture_set_user_states()[source]
Set the location and clock bias of the user receiver in Earth-Centered, Earth-Fixed coordinates.
- Returns:
rx_truth_m – Truth receiver position in ECEF frame in meters and the truth receiver clock bias also in meters in an array with shape (4 x 1) and the following order: x_rx_m, y_rx_m, z_rx_m, b_rx_m.
- Return type:
np.ndarray
- test_snapshot.test_rotation_of_earth_fix(derived_2022)[source]
Tests that accounting for Earth’s rotation reduces WLS errors.
- Parameters:
derived_2022 (AndroidDerived2022) – Instance of AndroidDerived2022 for testing
- test_snapshot.test_solve_wls(derived_2021)[source]
Test that solving for wls doesn’t fail
- Parameters:
derived_2021 (AndroidDerived2021) – Instance of AndroidDerived2021 for testing.
- test_snapshot.test_solve_wls_bias_only(derived_2022)[source]
Tests that bias only WLS estimation works as expected.
- Parameters:
derived_2022 (AndroidDerived2022) – Instance of AndroidDerived2022 for testing
- test_snapshot.test_solve_wls_empty()[source]
Test scenario where an empty measurement class is passed in.
- test_snapshot.test_solve_wls_fails(derived_2021)[source]
Test expected fails
- Parameters:
derived_2021 (AndroidDerived2021) – Instance of AndroidDerived2021 for testing
- test_snapshot.test_solve_wls_weights(derived_2021, tolerance)[source]
Tests that weights are working for weighted least squares.
- Parameters:
derived_2021 (AndroidDerived2021) – Instance of AndroidDerived2021 for testing
tolerance (fixture) – Error threshold for test pass/fail
- test_snapshot.test_wls(set_user_states, set_sv_states, tolerance)[source]
Test snapshot positioning against truth user states.
- Parameters:
set_user_states (fixture) – Truth values for user position and clock bias
set_sv_states (fixture) – Satellite position and clock biases
tolerance (fixture) – Error threshold for test pass/fail
- test_snapshot.test_wls_fails(capsys)[source]
Test expected fails
- Parameters:
capsys (error) – The capsys fixture allows access to stdout/stderr output created during test execution.
- test_snapshot.test_wls_max_count(set_user_states, set_sv_states, count_test, random_noise)[source]
Test snapshot positioning against truth user states.
- Parameters:
set_user_states (fixture) – Truth values for user position and clock bias
set_sv_states (fixture) – Satellite position and clock biases
count_test (int) – Max count for wls solver
random_noise (np.ndarray) – Noise added to ground truth pseudoranges of shape 4x1
- test_snapshot.test_wls_only_bias(set_user_states, set_sv_states, tolerance)[source]
Test WLS positioning against truth user states.
In these only_bias tests, it is only solving for clock bias.
- Parameters:
set_user_states (fixture) – Truth values for user position and clock bias
set_sv_states (fixture) – Satellite position and clock biases
tolerance (fixture) – Error threshold for test pass/fail
- test_snapshot.test_wls_tolerance(set_user_states, set_sv_states, tolerance_test, random_noise)[source]
Test snapshot positioning against truth user states.
- Parameters:
set_user_states (fixture) – Truth values for user position and clock bias
set_sv_states (fixture) – Satellite position and clock biases
tolerance_test (float) – Tolerance with which to end the wls solver
random_noise (np.ndarray) – Noise added to ground truth pseudoranges of shape 4x1
- test_snapshot.test_wls_weights(set_user_states, set_sv_states, tolerance, random_noise)[source]
Test snapshot positioning against truth user states.
- Parameters:
set_user_states (fixture) – Truth values for user position and clock bias
set_sv_states (fixture) – Satellite position and clock biases
tolerance (fixture) – Error threshold for test pass/fail
random_noise (np.ndarray) – Noise added to ground truth pseudoranges of shape 4x1