#
# ISC License
#
# Copyright (c) 2026, Autonomous Vehicle Systems Lab, University of Colorado Boulder
#
# Permission to use, copy, modify, and/or distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
# copyright notice and this permission notice appear in all copies.
#
# THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
# WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
# ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
# WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
# ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
# OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
#
import numpy as np
from Basilisk.architecture import messaging
from Basilisk.simulation import magnetometer
from Basilisk.utilities import SimulationBaseClass
from Basilisk.utilities import macros
NOISE_STD = 1.0e-9 # [T]
[docs]
def run_sensor(sampleCount, seed, propagationMatrix=None, walkBounds=None):
"""Run a zero-field magnetometer and return its noise samples."""
simulation = SimulationBaseClass.SimBaseClass()
process = simulation.CreateNewProcess("testProcess")
taskPeriod = 1.0 # [s]
process.addTask(simulation.CreateNewTask("testTask", macros.sec2nano(taskPeriod)))
sensor = magnetometer.Magnetometer()
sensor.RNGSeed = seed
sensor.senNoiseStd = [NOISE_STD, NOISE_STD, NOISE_STD]
if propagationMatrix is not None:
sensor.setAMatrix(propagationMatrix)
if walkBounds is not None:
sensor.walkBounds = walkBounds
stateMessage = messaging.SCStatesMsg().write(messaging.SCStatesMsgPayload())
fieldMessage = messaging.MagneticFieldMsg().write(messaging.MagneticFieldMsgPayload())
sensor.stateInMsg.subscribeTo(stateMessage)
sensor.magInMsg.subscribeTo(fieldMessage)
recorder = sensor.tamDataOutMsg.recorder()
simulation.AddModelToTask("testTask", sensor)
simulation.AddModelToTask("testTask", recorder)
simulation.InitializeSimulation()
simulation.ConfigureStopTime(macros.sec2nano(float(sampleCount - 1)))
simulation.ExecuteSimulation()
return sensor, np.asarray(recorder.tam_S)
[docs]
def test_default_noise_is_white():
"""The default propagation must produce the configured white-noise sigma."""
sampleCount = 1000
sensor, samples = run_sensor(sampleCount, seed=1234)
assert np.array_equal(sensor.getAMatrix(), np.zeros((3, 3)))
for axis in range(3):
axisSamples = samples[:, axis]
assert abs(np.mean(axisSamples)) < 5.0 * NOISE_STD / np.sqrt(sampleCount)
assert abs(np.std(axisSamples, ddof=1) / NOISE_STD - 1.0) < 0.1
assert abs(np.corrcoef(axisSamples[:-1], axisSamples[1:])[0, 1]) < 0.15
[docs]
def test_explicit_random_walk_is_bounded():
"""Identity propagation and positive bounds must create a bounded walk."""
bound = 5.0 * NOISE_STD # [T]
_, samples = run_sensor(
400,
seed=1234,
propagationMatrix=np.eye(3),
walkBounds=[bound, bound, bound],
)
assert np.max(np.abs(samples)) <= bound
assert np.any(np.isclose(np.abs(samples), bound, rtol=0.0, atol=1.0e-20))
assert np.corrcoef(samples[:-1, 0], samples[1:, 0])[0, 1] > 0.5
[docs]
def test_rng_seed_controls_noise_sequence():
"""Equal seeds must repeat and different seeds must change the sequence."""
_, first = run_sensor(8, seed=1234)
_, repeated = run_sensor(8, seed=1234)
_, different = run_sensor(8, seed=5678)
assert np.array_equal(first, repeated)
assert not np.array_equal(first, different)