Struct nyx_space::od::noise::StochasticNoise

pub struct StochasticNoise {
    pub white_noise: Option<WhiteNoise>,
    pub bias: Option<GaussMarkov>,
}

Stochastic noise modeling used primarily for synthetic orbit determination measurements.

This implementation distinguishes between the white noise model and the bias model. It also includes a constant offset.

Fields

white_noise: Option<WhiteNoise>

bias: Option<GaussMarkov>

Implementations

impl StochasticNoise

pub const ZERO: Self = _

Zero noise stochastic process.

pub const MIN: Self = _

The minimum stochastic noise process with a zero mean white noise of 1e-6.

pub fn default_range_km() -> Self

Default stochastic process of the Deep Space Network, as per DESCANSO Chapter 3, Table 3-3. Using the instrument bias as the white noise value, zero constant bias.

pub fn default_doppler_km_s() -> Self

Default stochastic process of the Deep Space Network, using as per DESCANSO Chapter 3, Table 3-3 for the GM process.

pub fn sample<R: Rng>(&mut self, epoch: Epoch, rng: &mut R) -> f64

Sample these stochastics

pub fn covariance(&self, epoch: Epoch) -> f64

Return the covariance of these stochastics at a given time.

pub fn simulate<P: AsRef<Path>>( self, path: P, runs: Option<u32>, unit: Option<String>, ) -> Result<Vec<StochasticState>, Box<dyn Error>>

Simulate the configured stochastic model and store the bias in a parquet file. Python: call as simulate(path, runs=25, unit=None) where the path is the output Parquet file, runs is the number of runs, and unit is the unit of the bias, reflected only in the headers of the parquet file.

The unit is only used in the headers of the parquet file.

This will simulate the model with “runs” different seeds, sampling the process 500 times for a duration of 5 times the time constant.

Trait Implementations

impl Clone for StochasticNoise

fn clone(&self) -> StochasticNoise

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for StochasticNoise

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for StochasticNoise

fn default() -> StochasticNoise

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for StochasticNoise

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for StochasticNoise

fn eq(&self, other: &StochasticNoise) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for StochasticNoise

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl Copy for StochasticNoise

impl StructuralPartialEq for StochasticNoise