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ENH: seed sensor measurement noise per instance (#1052)
* ENH: seed sensor measurement noise per instance Sensor noise (Accelerometer, Gyroscope, Barometer, GnssReceiver) was drawn from the process-global NumPy RNG, so it could not be seeded or reproduced, and it was unsafe under parallel or forked execution where workers share or reset the global RNG (issue #1042). Thread an optional seed argument through the Sensor base classes. Each sensor now owns a numpy.random.Generator from np.random.default_rng(seed) and draws its white noise and random walk from it instead of np.random. seed=None keeps the noise random but per-instance, so existing behaviour is unchanged unless a seed is given. Also adds tests/unit/sensors/test_sensor_seeding.py covering reproducibility, decorrelation across seeds, independence from the global RNG, and the GnssReceiver path. Signed-off-by: thc1006 <84045975+thc1006@users.noreply.github.com> * DOC: add CHANGELOG entry for sensor noise seeding (#1052) Signed-off-by: thc1006 <84045975+thc1006@users.noreply.github.com> * TST: seed the noisy sensor fixtures instead of the global RNG Sensor noise now comes from each sensor's own Generator, so the autouse `_seed_rng` fixture that seeded the global `np.random` no longer made the noisy assertions deterministic; they would flake on CI. Pass `seed=42` to the noisy accelerometer, gyroscope, barometer, and gnss fixtures so their noise is reproducible through the new per-instance seeding, and drop the now-defunct `_seed_rng` fixture. Signed-off-by: thc1006 <84045975+thc1006@users.noreply.github.com> * ENH: serialize the sensor seed and document it Address review feedback: document the seed argument in every sensor __init__ (this also fills in the name entry that was missing from Gyroscope's docstring), and carry seed through to_dict/from_dict so it survives serialization, including GnssReceiver's custom to_dict. from_dict reads it with data.get("seed") so dicts saved before this change still load, defaulting to None. Add serialization tests: the seed round-trips through the JSON encoder for every sensor type, and from_dict defaults the seed to None when the key is absent. Signed-off-by: thc1006 <84045975+thc1006@users.noreply.github.com> * TST: cover sensor base-class validation and dunders Add tests for the argument-validation error paths (measurement range, orientation, vectorized inputs, export file_format) and the __repr__ / __call__ helpers on Sensor and InertialSensor. These paths were untested; with them rocketpy/sensors reaches full statement coverage. Signed-off-by: thc1006 <84045975+thc1006@users.noreply.github.com> --------- Signed-off-by: thc1006 <84045975+thc1006@users.noreply.github.com>
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‎CHANGELOG.md‎

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@@ -44,6 +44,7 @@ Attention: The newest changes should be on top -->
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- ENH: ENH: Refactor flight.py latitude/longitude to use inverted_haversine [#1055](https://github.com/RocketPy-Team/RocketPy/pull/1055)
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- ENH: TST: Add unit tests for evaluate_reduced_mass and remove TODO [#1051](https://github.com/RocketPy-Team/RocketPy/pull/1051)
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- ENH: seed sensor measurement noise per instance [#1052](https://github.com/RocketPy-Team/RocketPy/pull/1052)
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- ENH: FIX: pre release hardening [#1047](https://github.com/RocketPy-Team/RocketPy/pull/1047)
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- ENH: DEV: Claude Code ruff hooks (auto-format on edit + pre-push lint guard) [#1046](https://github.com/RocketPy-Team/RocketPy/pull/1046)
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- ENH: CI: create a CI for testing docs updates + solve different docs issues [#1045](https://github.com/RocketPy-Team/RocketPy/pull/1045)

‎rocketpy/sensors/accelerometer.py‎

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@@ -78,6 +78,7 @@ def __init__(
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cross_axis_sensitivity=0,
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consider_gravity=False,
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name="Accelerometer",
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seed=None,
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):
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"""
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Initialize the accelerometer sensor
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acceleration. Default is False.
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name : str, optional
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The name of the sensor. Default is "Accelerometer".
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seed : int, optional
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Seed for the random number generator that draws the measurement
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noise. If given, the noise becomes reproducible and independent of
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the process-global NumPy RNG. Default is None, meaning the noise is
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seeded from fresh entropy per instance.
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Returns
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-------
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temperature_scale_factor=temperature_scale_factor,
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cross_axis_sensitivity=cross_axis_sensitivity,
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name=name,
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seed=seed,
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)
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self.consider_gravity = consider_gravity
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self.prints = _InertialSensorPrints(self)
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cross_axis_sensitivity=data["cross_axis_sensitivity"],
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consider_gravity=data["consider_gravity"],
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name=data["name"],
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seed=data.get("seed"),
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)

‎rocketpy/sensors/barometer.py‎

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@@ -62,6 +62,7 @@ def __init__(
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temperature_bias=0,
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temperature_scale_factor=0,
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name="Barometer",
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seed=None,
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):
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"""
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Initialize the barometer sensor
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meaning no temperature scale factor is applied.
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name : str, optional
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The name of the sensor. Default is "Barometer".
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seed : int, optional
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Seed for the random number generator that draws the measurement
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noise. If given, the noise becomes reproducible and independent of
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the process-global NumPy RNG. Default is None, meaning the noise is
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seeded from fresh entropy per instance.
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Returns
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-------
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temperature_bias=temperature_bias,
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temperature_scale_factor=temperature_scale_factor,
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name=name,
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seed=seed,
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)
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self.prints = _SensorPrints(self)
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@@ -206,4 +213,5 @@ def from_dict(cls, data):
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temperature_bias=data["temperature_bias"],
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temperature_scale_factor=data["temperature_scale_factor"],
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name=data["name"],
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seed=data.get("seed"),
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)

‎rocketpy/sensors/gnss_receiver.py‎

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import math
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import numpy as np
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from rocketpy.tools import inverted_haversine
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from ..mathutils.vector_matrix import Matrix, Vector
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position_accuracy=0,
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altitude_accuracy=0,
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name="GnssReceiver",
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seed=None,
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):
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"""Initialize the Gnss Receiver sensor.
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@@ -55,8 +54,13 @@ def __init__(
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position in meters. Default is 0.
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name : str
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The name of the sensor. Default is "GnssReceiver".
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seed : int, optional
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Seed for the random number generator that draws the measurement
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noise. If given, the noise becomes reproducible and independent of
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the process-global NumPy RNG. Default is None, meaning the noise is
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seeded from fresh entropy per instance.
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"""
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super().__init__(sampling_rate=sampling_rate, name=name)
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super().__init__(sampling_rate=sampling_rate, name=name, seed=seed)
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self.position_accuracy = position_accuracy
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self.altitude_accuracy = altitude_accuracy
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# Get from state u and add relative position
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x, y, z = (Matrix.transformation(u[6:10]) @ relative_position) + Vector(u[0:3])
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# Apply accuracy to the position
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x = np.random.normal(x, self.position_accuracy)
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y = np.random.normal(y, self.position_accuracy)
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altitude = np.random.normal(z, self.altitude_accuracy)
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x = self._rng.normal(x, self.position_accuracy)
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y = self._rng.normal(y, self.position_accuracy)
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altitude = self._rng.normal(z, self.altitude_accuracy)
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# Convert x and y to latitude and longitude
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drift = (x**2 + y**2) ** 0.5
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"position_accuracy": self.position_accuracy,
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"altitude_accuracy": self.altitude_accuracy,
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"name": self.name,
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"seed": self._seed,
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}
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@classmethod
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position_accuracy=data["position_accuracy"],
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altitude_accuracy=data["altitude_accuracy"],
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name=data["name"],
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seed=data.get("seed"),
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)

‎rocketpy/sensors/gyroscope.py‎

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cross_axis_sensitivity=0,
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acceleration_sensitivity=0,
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name="Gyroscope",
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seed=None,
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):
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"""
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Initialize the gyroscope sensor
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float or int is given, the same sensitivity is applied to all axes.
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The values of each axis can be set individually by passing a list of
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length 3.
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name : str, optional
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The name of the sensor. Default is "Gyroscope".
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seed : int, optional
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Seed for the random number generator that draws the measurement
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noise. If given, the noise becomes reproducible and independent of
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the process-global NumPy RNG. Default is None, meaning the noise is
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seeded from fresh entropy per instance.
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-------
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temperature_scale_factor=temperature_scale_factor,
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cross_axis_sensitivity=cross_axis_sensitivity,
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name=name,
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seed=seed,
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)
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self.acceleration_sensitivity = self._vectorize_input(
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acceleration_sensitivity, "acceleration_sensitivity"
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cross_axis_sensitivity=data["cross_axis_sensitivity"],
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acceleration_sensitivity=data["acceleration_sensitivity"],
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name=data["name"],
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seed=data.get("seed"),
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)

‎rocketpy/sensors/sensor.py‎

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temperature_bias=0,
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temperature_scale_factor=0,
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name="Sensor",
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seed=None,
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):
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"""
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Initialize the accelerometer sensor
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meaning no temperature scale factor is applied.
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name : str, optional
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The name of the sensor. Default is "Sensor".
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seed : int, optional
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Seed for the random number generator that draws the measurement
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noise. If given, the noise becomes reproducible and independent of
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the process-global NumPy RNG. Default is None, meaning the noise is
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seeded from fresh entropy per instance.
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-------
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self._random_walk_drift = 0
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self.normal_vector = Vector([0, 0, 0])
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# Per-instance RNG, seeded deterministically when a seed is given, so
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# the measurement noise is reproducible and independent of the
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# process-global NumPy RNG (and therefore safe under parallel or
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# forked evaluation). seed=None keeps the noise random but still
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# drawn from this instance's generator.
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self._seed = seed
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self._rng = np.random.default_rng(seed)
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# handle measurement range
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if isinstance(measurement_range, (tuple, list)):
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if len(measurement_range) != 2:
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"temperature_bias": self.temperature_bias,
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"temperature_scale_factor": self.temperature_scale_factor,
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"name": self.name,
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"seed": self._seed,
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}
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temperature_scale_factor=0,
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cross_axis_sensitivity=0,
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name="Sensor",
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seed=None,
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):
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"""
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Initialize the accelerometer sensor
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no cross-axis sensitivity is applied.
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name : str, optional
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The name of the sensor. Default is "Sensor".
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seed : int, optional
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Seed for the random number generator that draws the measurement
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noise. If given, the noise becomes reproducible and independent of
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the process-global NumPy RNG. Default is None, meaning the noise is
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seeded from fresh entropy per instance.
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temperature_scale_factor, "temperature_scale_factor"
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),
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name=name,
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seed=seed,
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)
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self.orientation = orientation
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"""
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# white noise
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white_noise = Vector(
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[np.random.normal(0, self.noise_variance[i] ** 0.5) for i in range(3)]
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[self._rng.normal(0, self.noise_variance[i] ** 0.5) for i in range(3)]
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) & (self.noise_density * self.sampling_rate**0.5)
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# random walk
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self._random_walk_drift = self._random_walk_drift + Vector(
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[np.random.normal(0, self.random_walk_variance[i] ** 0.5) for i in range(3)]
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[self._rng.normal(0, self.random_walk_variance[i] ** 0.5) for i in range(3)]
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) & (self.random_walk_density / self.sampling_rate**0.5)
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# add noise
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temperature_bias=0,
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temperature_scale_factor=0,
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name="Sensor",
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seed=None,
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):
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"""
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Initialize the accelerometer sensor
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meaning no temperature scale factor is applied.
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name : str, optional
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The name of the sensor. Default is "Sensor".
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seed : int, optional
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Seed for the random number generator that draws the measurement
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noise. If given, the noise becomes reproducible and independent of
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the process-global NumPy RNG. Default is None, meaning the noise is
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seeded from fresh entropy per instance.
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temperature_bias=temperature_bias,
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temperature_scale_factor=temperature_scale_factor,
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name=name,
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seed=seed,
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)
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def quantize(self, value):
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"""
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# white noise
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white_noise = (
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np.random.normal(0, self.noise_variance**0.5)
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self._rng.normal(0, self.noise_variance**0.5)
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* self.noise_density
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* self.sampling_rate**0.5
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)
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# random walk
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self._random_walk_drift = (
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self._random_walk_drift
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+ np.random.normal(0, self.random_walk_variance**0.5)
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+ self._rng.normal(0, self.random_walk_variance**0.5)
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* self.random_walk_density
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/ self.sampling_rate**0.5
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‎tests/fixtures/sensors/sensors_fixtures.py‎

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cross_axis_sensitivity=0.5,
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consider_gravity=True,
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name="Accelerometer",
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seed=42,
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)
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cross_axis_sensitivity=0.5,
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acceleration_sensitivity=[0, 0.0008, 0.0017],
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name="Gyroscope",
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seed=42,
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)
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operating_temperature=25 + 273.15,
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temperature_bias=0.02,
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temperature_scale_factor=0.02,
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seed=42,
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)
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sampling_rate=1,
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position_accuracy=1,
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altitude_accuracy=1,
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seed=42,
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)
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‎tests/unit/sensors/test_sensor.py‎

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from rocketpy.tools import euler313_to_quaternions
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@pytest.fixture(autouse=True)
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def _seed_rng():
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"""Seed NumPy's global RNG before each test so that the noise-based
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sensor measurements are deterministic. Without this, tests such as
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``test_noisy_barometer`` are flaky because the random white noise can
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occasionally exceed the assertion tolerance."""
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np.random.seed(42)
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# calisto standard simulation no wind solution index 200
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TIME = 3.338513236767685
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U = [

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