TrackingDataArc

Struct TrackingDataArc 

Source
pub struct TrackingDataArc {
    pub measurements: BTreeMap<Epoch, Measurement>,
    pub source: Option<String>,
    pub moduli: Option<IndexMap<MeasurementType, f64>>,
    pub force_reject: bool,
}
Expand description

Tracking data storing all of measurements as a B-Tree. It inherently does NOT support multiple concurrent measurements from several trackers.

§Measurement Moduli, e.g. range modulus

In the case of ranging, and possibly other data types, a code is used to measure the range to the spacecraft. The length of this code determines the ambiguity resolution, as per equation 9 in section 2.2.2.2 of the JPL DESCANSO, document 214, Pseudo-Noise and Regenerative Ranging. For example, using the JPL Range Code and a frequency range clock of 1 MHz, the range ambiguity is 75,660 km. In other words, as soon as the spacecraft is at a range of 75,660 + 1 km the JPL Range Code will report the vehicle to be at a range of 1 km. This is simply because the range code overlaps with itself, effectively loosing track of its own reference: it’s due to the phase shift of the signal “lapping” the original signal length.

            (Spacecraft)
            ^
            |    Actual Distance = 75,661 km
            |
0 km                                         75,660 km (Wrap-Around)
|-----------------------------------------------|
  When the "code length" is exceeded,
  measurements wrap back to 0.

So effectively:
    Observed code range = Actual range (mod 75,660 km)
    75,661 km → 1 km

Nyx can only resolve the range ambiguity if the tracking data specifies a modulus for this specific measurement type. For example, in the case of the JPL Range Code and a 1 MHz range clock, the ambiguity interval is 75,660 km.

The measurement used in the Orbit Determination Process then becomes the following, where // represents the Euclidian division.

k = computed_obs // ambiguity_interval
real_obs = measured_obs + k * modulus

Reference: JPL DESCANSO, document 214, Pseudo-Noise and Regenerative Ranging.

Fields§

§measurements: BTreeMap<Epoch, Measurement>

All measurements in this data arc

§source: Option<String>

Source file if loaded from a file or saved to a file.

§moduli: Option<IndexMap<MeasurementType, f64>>

Optionally provide a map of modulos (e.g. the RANGE_MODULO of CCSDS TDM).

§force_reject: bool

Reject all of the measurements, useful for debugging passes.

Implementations§

Source§

impl TrackingDataArc

Source

pub fn from_tdm<P: AsRef<Path>>( path: P, aliases: Option<HashMap<String, String>>, ) -> Result<Self, InputOutputError>

Loads a tracking arc from its serialization in CCSDS TDM.

§Support level
  • Only the KVN format is supported.
  • Support is limited to orbit determination in “xGEO”, i.e. cislunar and deep space missions.
  • Only one metadata and data section per file is tested.
§Data types

Fully supported: - RANGE - DOPPLER_INSTANTANEOUS, DOPPLER_INTEGRATED - ANGLE_1 / ANGLE_2, as azimuth/elevation only

Partially supported: - TRANSMIT_FREQ / RECEIVE_FREQ : these will be converted to Doppler measurements using the TURNAROUND_NUMERATOR and TURNAROUND_DENOMINATOR in the TDM. The freq rate is not supported.

§Metadata support
§Mode

Only the MODE = SEQUENTIAL is supported.

§Time systems / time scales

All timescales supported by hifitime are supported here. This includes: UTC, TAI, GPS, TT, TDB, TAI, GST, QZSST.

§Path

Only one way or two way data is supported, i.e. path must be either PATH n,m,n or PATH n,m.

Note that the actual indexes of the path are ignored.

§Participants

PARTICIPANT_1 must be the ground station / tracker. The second participant is ignored: the user must ensure that the Orbit Determination Process is properly configured and the proper arc is given.

§Turnaround ratio

The turnaround ratio is only accounted for when the data contains RECEIVE_FREQ and TRANSMIT_FREQ data.

§Range and modulus

Only kilometers are supported in range units. Range modulus is accounted for to compute range ambiguity.

Source

pub fn to_tdm_file<P: AsRef<Path>>( self, spacecraft_name: String, aliases: Option<HashMap<String, String>>, path: P, cfg: ExportCfg, ) -> Result<PathBuf, InputOutputError>

Store this tracking arc to a CCSDS TDM file, with optional metadata and a timestamp appended to the filename.

Source§

impl TrackingDataArc

Source

pub fn from_parquet<P: AsRef<Path>>(path: P) -> Result<Self, InputOutputError>

Loads a tracking arc from its serialization in parquet.

Warning: no metadata is read from the parquet file, even that written to it by Nyx.

Source

pub fn to_parquet_simple<P: AsRef<Path>>( &self, path: P, ) -> Result<PathBuf, Box<dyn Error>>

Store this tracking arc to a parquet file.

Examples found in repository?
examples/05_cislunar_spacecraft_link_od/main.rs (line 180)
34fn main() -> Result<(), Box<dyn Error>> {
35    pel::init();
36
37    // ====================== //
38    // === ALMANAC SET UP === //
39    // ====================== //
40
41    let manifest_dir =
42        PathBuf::from(std::env::var("CARGO_MANIFEST_DIR").unwrap_or(".".to_string()));
43
44    let out = manifest_dir.join("data/04_output/");
45
46    let almanac = Arc::new(
47        Almanac::new(
48            &manifest_dir
49                .join("data/01_planetary/pck08.pca")
50                .to_string_lossy(),
51        )
52        .unwrap()
53        .load(
54            &manifest_dir
55                .join("data/01_planetary/de440s.bsp")
56                .to_string_lossy(),
57        )
58        .unwrap(),
59    );
60
61    let eme2k = almanac.frame_from_uid(EARTH_J2000).unwrap();
62    let moon_iau = almanac.frame_from_uid(IAU_MOON_FRAME).unwrap();
63
64    let epoch = Epoch::from_gregorian_tai(2021, 5, 29, 19, 51, 16, 852_000);
65    let nrho = Orbit::cartesian(
66        166_473.631_302_239_7,
67        -274_715.487_253_382_7,
68        -211_233.210_176_686_7,
69        0.933_451_604_520_018_4,
70        0.436_775_046_841_900_9,
71        -0.082_211_021_250_348_95,
72        epoch,
73        eme2k,
74    );
75
76    let tx_nrho_sc = Spacecraft::from(nrho);
77
78    let state_luna = almanac.transform_to(nrho, MOON_J2000, None).unwrap();
79    println!("Start state (dynamics: Earth, Moon, Sun gravity):\n{state_luna}");
80
81    let bodies = vec![EARTH, SUN];
82    let dynamics = SpacecraftDynamics::new(OrbitalDynamics::point_masses(bodies));
83
84    let setup = Propagator::rk89(
85        dynamics,
86        IntegratorOptions::builder().max_step(0.5.minutes()).build(),
87    );
88
89    /* == Propagate the NRHO vehicle == */
90    let prop_time = 1.1 * state_luna.period().unwrap();
91
92    let (nrho_final, mut tx_traj) = setup
93        .with(tx_nrho_sc, almanac.clone())
94        .for_duration_with_traj(prop_time)
95        .unwrap();
96
97    tx_traj.name = Some("NRHO Tx SC".to_string());
98
99    println!("{tx_traj}");
100
101    /* == Propagate an LLO vehicle == */
102    let llo_orbit =
103        Orbit::try_keplerian_altitude(110.0, 1e-4, 90.0, 0.0, 0.0, 0.0, epoch, moon_iau).unwrap();
104
105    let llo_sc = Spacecraft::builder().orbit(llo_orbit).build();
106
107    let (_, llo_traj) = setup
108        .with(llo_sc, almanac.clone())
109        .until_epoch_with_traj(nrho_final.epoch())
110        .unwrap();
111
112    // Export the subset of the first two hours.
113    llo_traj
114        .clone()
115        .filter_by_offset(..2.hours())
116        .to_parquet_simple(out.join("05_caps_llo_truth.pq"), almanac.clone())?;
117
118    /* == Setup the interlink == */
119
120    let mut measurement_types = IndexSet::new();
121    measurement_types.insert(MeasurementType::Range);
122    measurement_types.insert(MeasurementType::Doppler);
123
124    let mut stochastics = IndexMap::new();
125
126    let sa45_csac_allan_dev = 1e-11;
127
128    stochastics.insert(
129        MeasurementType::Range,
130        StochasticNoise::from_hardware_range_km(
131            sa45_csac_allan_dev,
132            10.0.seconds(),
133            link_specific::ChipRate::StandardT4B,
134            link_specific::SN0::Average,
135        ),
136    );
137
138    stochastics.insert(
139        MeasurementType::Doppler,
140        StochasticNoise::from_hardware_doppler_km_s(
141            sa45_csac_allan_dev,
142            10.0.seconds(),
143            link_specific::CarrierFreq::SBand,
144            link_specific::CN0::Average,
145        ),
146    );
147
148    let interlink = InterlinkTxSpacecraft {
149        traj: tx_traj,
150        measurement_types,
151        integration_time: None,
152        timestamp_noise_s: None,
153        ab_corr: Aberration::LT,
154        stochastic_noises: Some(stochastics),
155    };
156
157    // Devices are the transmitter, which is our NRHO vehicle.
158    let mut devices = BTreeMap::new();
159    devices.insert("NRHO Tx SC".to_string(), interlink);
160
161    let mut configs = BTreeMap::new();
162    configs.insert(
163        "NRHO Tx SC".to_string(),
164        TrkConfig::builder()
165            .strands(vec![Strand {
166                start: epoch,
167                end: nrho_final.epoch(),
168            }])
169            .build(),
170    );
171
172    let mut trk_sim =
173        TrackingArcSim::with_seed(devices.clone(), llo_traj.clone(), configs, 0).unwrap();
174    println!("{trk_sim}");
175
176    let trk_data = trk_sim.generate_measurements(almanac.clone()).unwrap();
177    println!("{trk_data}");
178
179    trk_data
180        .to_parquet_simple(out.clone().join("nrho_interlink_msr.pq"))
181        .unwrap();
182
183    // Run a truth OD where we estimate the LLO position
184    let llo_uncertainty = SpacecraftUncertainty::builder()
185        .nominal(llo_sc)
186        .x_km(1.0)
187        .y_km(1.0)
188        .z_km(1.0)
189        .vx_km_s(1e-3)
190        .vy_km_s(1e-3)
191        .vz_km_s(1e-3)
192        .build();
193
194    let mut proc_devices = devices.clone();
195
196    // Define the initial estimate, randomized, seed for reproducibility
197    let mut initial_estimate = llo_uncertainty.to_estimate_randomized(Some(0)).unwrap();
198    // Inflate the covariance -- https://github.com/nyx-space/nyx/issues/339
199    initial_estimate.covar *= 2.5;
200
201    // Increase the noise in the devices to accept more measurements.
202
203    for link in proc_devices.values_mut() {
204        for noise in &mut link.stochastic_noises.as_mut().unwrap().values_mut() {
205            *noise.white_noise.as_mut().unwrap() *= 3.0;
206        }
207    }
208
209    let init_err = initial_estimate
210        .orbital_state()
211        .ric_difference(&llo_orbit)
212        .unwrap();
213
214    println!("initial estimate:\n{initial_estimate}");
215    println!("RIC errors = {init_err}",);
216
217    let odp = InterlinkKalmanOD::new(
218        setup.clone(),
219        KalmanVariant::ReferenceUpdate,
220        Some(ResidRejectCrit::default()),
221        proc_devices,
222        almanac.clone(),
223    );
224
225    // Shrink the data to process.
226    let arc = trk_data.filter_by_offset(..2.hours());
227
228    let od_sol = odp.process_arc(initial_estimate, &arc).unwrap();
229
230    println!("{od_sol}");
231
232    od_sol
233        .to_parquet(
234            out.join(format!("05_caps_interlink_od_sol.pq")),
235            ExportCfg::default(),
236        )
237        .unwrap();
238
239    let od_traj = od_sol.to_traj().unwrap();
240
241    od_traj
242        .ric_diff_to_parquet(
243            &llo_traj,
244            out.join(format!("05_caps_interlink_llo_est_error.pq")),
245            ExportCfg::default(),
246        )
247        .unwrap();
248
249    let final_est = od_sol.estimates.last().unwrap();
250    assert!(final_est.within_3sigma(), "should be within 3 sigma");
251
252    println!("ESTIMATE\n{final_est:x}\n");
253    let truth = llo_traj.at(final_est.epoch()).unwrap();
254    println!("TRUTH\n{truth:x}");
255
256    let final_err = truth
257        .orbit
258        .ric_difference(&final_est.orbital_state())
259        .unwrap();
260    println!("ERROR {final_err}");
261
262    // Build the residuals versus reference plot.
263    let rvr_sol = odp
264        .process_arc(initial_estimate, &arc.resid_vs_ref_check())
265        .unwrap();
266
267    rvr_sol
268        .to_parquet(
269            out.join(format!("05_caps_interlink_resid_v_ref.pq")),
270            ExportCfg::default(),
271        )
272        .unwrap();
273
274    let final_rvr = rvr_sol.estimates.last().unwrap();
275
276    println!("RMAG error {:.3} m", final_err.rmag_km() * 1e3);
277    println!(
278        "Pure prop error {:.3} m",
279        final_rvr
280            .orbital_state()
281            .ric_difference(&final_est.orbital_state())
282            .unwrap()
283            .rmag_km()
284            * 1e3
285    );
286
287    Ok(())
288}
More examples
Hide additional examples
examples/04_lro_od/main.rs (line 239)
34fn main() -> Result<(), Box<dyn Error>> {
35    pel::init();
36
37    // ====================== //
38    // === ALMANAC SET UP === //
39    // ====================== //
40
41    // Dynamics models require planetary constants and ephemerides to be defined.
42    // Let's start by grabbing those by using ANISE's MetaAlmanac.
43
44    let data_folder: PathBuf = [env!("CARGO_MANIFEST_DIR"), "examples", "04_lro_od"]
45        .iter()
46        .collect();
47
48    let meta = data_folder.join("lro-dynamics.dhall");
49
50    // Load this ephem in the general Almanac we're using for this analysis.
51    let mut almanac = MetaAlmanac::new(meta.to_string_lossy().to_string())
52        .map_err(Box::new)?
53        .process(true)
54        .map_err(Box::new)?;
55
56    let mut moon_pc = almanac.planetary_data.get_by_id(MOON)?;
57    moon_pc.mu_km3_s2 = 4902.74987;
58    almanac.planetary_data.set_by_id(MOON, moon_pc)?;
59
60    let mut earth_pc = almanac.planetary_data.get_by_id(EARTH)?;
61    earth_pc.mu_km3_s2 = 398600.436;
62    almanac.planetary_data.set_by_id(EARTH, earth_pc)?;
63
64    // Save this new kernel for reuse.
65    // In an operational context, this would be part of the "Lock" process, and should not change throughout the mission.
66    almanac
67        .planetary_data
68        .save_as(&data_folder.join("lro-specific.pca"), true)?;
69
70    // Lock the almanac (an Arc is a read only structure).
71    let almanac = Arc::new(almanac);
72
73    // Orbit determination requires a Trajectory structure, which can be saved as parquet file.
74    // In our case, the trajectory comes from the BSP file, so we need to build a Trajectory from the almanac directly.
75    // To query the Almanac, we need to build the LRO frame in the J2000 orientation in our case.
76    // Inspecting the LRO BSP in the ANISE GUI shows us that NASA has assigned ID -85 to LRO.
77    let lro_frame = Frame::from_ephem_j2000(-85);
78
79    // To build the trajectory we need to provide a spacecraft template.
80    let sc_template = Spacecraft::builder()
81        .mass(Mass::from_dry_and_prop_masses(1018.0, 900.0)) // Launch masses
82        .srp(SRPData {
83            // SRP configuration is arbitrary, but we will be estimating it anyway.
84            area_m2: 3.9 * 2.7,
85            coeff_reflectivity: 0.96,
86        })
87        .orbit(Orbit::zero(MOON_J2000)) // Setting a zero orbit here because it's just a template
88        .build();
89    // Now we can build the trajectory from the BSP file.
90    // We'll arbitrarily set the tracking arc to 24 hours with a five second time step.
91    let traj_as_flown = Traj::from_bsp(
92        lro_frame,
93        MOON_J2000,
94        almanac.clone(),
95        sc_template,
96        5.seconds(),
97        Some(Epoch::from_str("2024-01-01 00:00:00 UTC")?),
98        Some(Epoch::from_str("2024-01-02 00:00:00 UTC")?),
99        Aberration::LT,
100        Some("LRO".to_string()),
101    )?;
102
103    println!("{traj_as_flown}");
104
105    // ====================== //
106    // === MODEL MATCHING === //
107    // ====================== //
108
109    // Set up the spacecraft dynamics.
110
111    // Specify that the orbital dynamics must account for the graviational pull of the Earth and the Sun.
112    // The gravity of the Moon will also be accounted for since the spaceraft in a lunar orbit.
113    let mut orbital_dyn = OrbitalDynamics::point_masses(vec![EARTH, SUN, JUPITER_BARYCENTER]);
114
115    // We want to include the spherical harmonics, so let's download the gravitational data from the Nyx Cloud.
116    // We're using the GRAIL JGGRX model.
117    let mut jggrx_meta = MetaFile {
118        uri: "http://public-data.nyxspace.com/nyx/models/Luna_jggrx_1500e_sha.tab.gz".to_string(),
119        crc32: Some(0x6bcacda8), // Specifying the CRC32 avoids redownloading it if it's cached.
120    };
121    // And let's download it if we don't have it yet.
122    jggrx_meta.process(true)?;
123
124    // Build the spherical harmonics.
125    // The harmonics must be computed in the body fixed frame.
126    // We're using the long term prediction of the Moon principal axes frame.
127    let moon_pa_frame = MOON_PA_FRAME.with_orient(31008);
128    let sph_harmonics = Harmonics::from_stor(
129        almanac.frame_from_uid(moon_pa_frame)?,
130        HarmonicsMem::from_shadr(&jggrx_meta.uri, 80, 80, true)?,
131    );
132
133    // Include the spherical harmonics into the orbital dynamics.
134    orbital_dyn.accel_models.push(sph_harmonics);
135
136    // We define the solar radiation pressure, using the default solar flux and accounting only
137    // for the eclipsing caused by the Earth and Moon.
138    // Note that by default, enabling the SolarPressure model will also enable the estimation of the coefficient of reflectivity.
139    let srp_dyn = SolarPressure::new(vec![EARTH_J2000, MOON_J2000], almanac.clone())?;
140
141    // Finalize setting up the dynamics, specifying the force models (orbital_dyn) separately from the
142    // acceleration models (SRP in this case). Use `from_models` to specify multiple accel models.
143    let dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn);
144
145    println!("{dynamics}");
146
147    // Now we can build the propagator.
148    let setup = Propagator::default_dp78(dynamics.clone());
149
150    // For reference, let's build the trajectory with Nyx's models from that LRO state.
151    let (sim_final, traj_as_sim) = setup
152        .with(*traj_as_flown.first(), almanac.clone())
153        .until_epoch_with_traj(traj_as_flown.last().epoch())?;
154
155    println!("SIM INIT:  {:x}", traj_as_flown.first());
156    println!("SIM FINAL: {sim_final:x}");
157    // Compute RIC difference between SIM and LRO ephem
158    let sim_lro_delta = sim_final
159        .orbit
160        .ric_difference(&traj_as_flown.last().orbit)?;
161    println!("{traj_as_sim}");
162    println!(
163        "SIM v LRO - RIC Position (m): {:.3}",
164        sim_lro_delta.radius_km * 1e3
165    );
166    println!(
167        "SIM v LRO - RIC Velocity (m/s): {:.3}",
168        sim_lro_delta.velocity_km_s * 1e3
169    );
170
171    traj_as_sim.ric_diff_to_parquet(
172        &traj_as_flown,
173        "./04_lro_sim_truth_error.parquet",
174        ExportCfg::default(),
175    )?;
176
177    // ==================== //
178    // === OD SIMULATOR === //
179    // ==================== //
180
181    // After quite some time trying to exactly match the model, we still end up with an oscillatory difference on the order of 150 meters between the propagated state
182    // and the truth LRO state.
183
184    // Therefore, we will actually run an estimation from a dispersed LRO state.
185    // The sc_seed is the true LRO state from the BSP.
186    let sc_seed = *traj_as_flown.first();
187
188    // Load the Deep Space Network ground stations.
189    // Nyx allows you to build these at runtime but it's pretty static so we can just load them from YAML.
190    let ground_station_file: PathBuf = [
191        env!("CARGO_MANIFEST_DIR"),
192        "examples",
193        "04_lro_od",
194        "dsn-network.yaml",
195    ]
196    .iter()
197    .collect();
198
199    let devices = GroundStation::load_named(ground_station_file)?;
200
201    let mut proc_devices = devices.clone();
202
203    // Increase the noise in the devices to accept more measurements.
204    for gs in proc_devices.values_mut() {
205        if let Some(noise) = &mut gs
206            .stochastic_noises
207            .as_mut()
208            .unwrap()
209            .get_mut(&MeasurementType::Range)
210        {
211            *noise.white_noise.as_mut().unwrap() *= 3.0;
212        }
213    }
214
215    // Typical OD software requires that you specify your own tracking schedule or you'll have overlapping measurements.
216    // Nyx can build a tracking schedule for you based on the first station with access.
217    let trkconfg_yaml: PathBuf = [
218        env!("CARGO_MANIFEST_DIR"),
219        "examples",
220        "04_lro_od",
221        "tracking-cfg.yaml",
222    ]
223    .iter()
224    .collect();
225
226    let configs: BTreeMap<String, TrkConfig> = TrkConfig::load_named(trkconfg_yaml)?;
227
228    // Build the tracking arc simulation to generate a "standard measurement".
229    let mut trk = TrackingArcSim::<Spacecraft, GroundStation>::with_seed(
230        devices.clone(),
231        traj_as_flown.clone(),
232        configs,
233        123, // Set a seed for reproducibility
234    )?;
235
236    trk.build_schedule(almanac.clone())?;
237    let arc = trk.generate_measurements(almanac.clone())?;
238    // Save the simulated tracking data
239    arc.to_parquet_simple("./04_lro_simulated_tracking.parquet")?;
240
241    // We'll note that in our case, we have continuous coverage of LRO when the vehicle is not behind the Moon.
242    println!("{arc}");
243
244    // Now that we have simulated measurements, we'll run the orbit determination.
245
246    // ===================== //
247    // === OD ESTIMATION === //
248    // ===================== //
249
250    let sc = SpacecraftUncertainty::builder()
251        .nominal(sc_seed)
252        .frame(LocalFrame::RIC)
253        .x_km(0.5)
254        .y_km(0.5)
255        .z_km(0.5)
256        .vx_km_s(5e-3)
257        .vy_km_s(5e-3)
258        .vz_km_s(5e-3)
259        .build();
260
261    // Build the filter initial estimate, which we will reuse in the filter.
262    let mut initial_estimate = sc.to_estimate()?;
263    initial_estimate.covar *= 3.0;
264
265    println!("== FILTER STATE ==\n{sc_seed:x}\n{initial_estimate}");
266
267    // Build the SNC in the Moon J2000 frame, specified as a velocity noise over time.
268    let process_noise = ProcessNoise3D::from_velocity_km_s(
269        &[1e-10, 1e-10, 1e-10],
270        1 * Unit::Hour,
271        10 * Unit::Minute,
272        None,
273    );
274
275    println!("{process_noise}");
276
277    // We'll set up the OD process to reject measurements whose residuals are move than 3 sigmas away from what we expect.
278    let odp = SpacecraftKalmanOD::new(
279        setup,
280        KalmanVariant::ReferenceUpdate,
281        Some(ResidRejectCrit::default()),
282        proc_devices,
283        almanac.clone(),
284    )
285    .with_process_noise(process_noise);
286
287    let od_sol = odp.process_arc(initial_estimate, &arc)?;
288
289    let final_est = od_sol.estimates.last().unwrap();
290
291    println!("{final_est}");
292
293    let ric_err = traj_as_flown
294        .at(final_est.epoch())?
295        .orbit
296        .ric_difference(&final_est.orbital_state())?;
297    println!("== RIC at end ==");
298    println!("RIC Position (m): {:.3}", ric_err.radius_km * 1e3);
299    println!("RIC Velocity (m/s): {:.3}", ric_err.velocity_km_s * 1e3);
300
301    println!(
302        "Num residuals rejected: #{}",
303        od_sol.rejected_residuals().len()
304    );
305    println!(
306        "Percentage within +/-3: {}",
307        od_sol.residual_ratio_within_threshold(3.0).unwrap()
308    );
309    println!("Ratios normal? {}", od_sol.is_normal(None).unwrap());
310
311    od_sol.to_parquet("./04_lro_od_results.parquet", ExportCfg::default())?;
312
313    // In our case, we have the truth trajectory from NASA.
314    // So we can compute the RIC state difference between the real LRO ephem and what we've just estimated.
315    // Export the OD trajectory first.
316    let od_trajectory = od_sol.to_traj()?;
317    // Build the RIC difference.
318    od_trajectory.ric_diff_to_parquet(
319        &traj_as_flown,
320        "./04_lro_od_truth_error.parquet",
321        ExportCfg::default(),
322    )?;
323
324    Ok(())
325}
Source

pub fn to_parquet<P: AsRef<Path>>( &self, path: P, cfg: ExportCfg, ) -> Result<PathBuf, Box<dyn Error>>

Store this tracking arc to a parquet file, with optional metadata and a timestamp appended to the filename.

Source§

impl TrackingDataArc

Source

pub fn set_moduli(&mut self, msr_type: MeasurementType, modulus: f64)

Set (or overwrites) the modulus of the provided measurement type.

Source

pub fn apply_moduli(&mut self)

Applies the moduli to each measurement, if defined.

Source

pub fn unique_aliases(&self) -> IndexSet<String>

Returns the unique list of aliases in this tracking data arc

Source

pub fn unique_types(&self) -> IndexSet<MeasurementType>

Returns the unique measurement types in this tracking data arc

Source

pub fn unique(&self) -> (IndexSet<String>, IndexSet<MeasurementType>)

Returns the unique trackers and unique measurement types in this data arc

Source

pub fn start_epoch(&self) -> Option<Epoch>

Returns the start epoch of this tracking arc

Source

pub fn end_epoch(&self) -> Option<Epoch>

Returns the end epoch of this tracking arc

Source

pub fn duration(&self) -> Option<Duration>

Returns the duration this tracking arc

Source

pub fn len(&self) -> usize

Returns the number of measurements in this data arc

Source

pub fn is_empty(&self) -> bool

Returns whether this arc has no measurements.

Source

pub fn min_duration_sep(&self) -> Option<Duration>

Returns the minimum duration between two subsequent measurements.

Source

pub fn filter_by_epoch<R: RangeBounds<Epoch>>(self, bound: R) -> Self

Returns a new tracking arc that only contains measurements that fall within the given epoch range.

Source

pub fn filter_by_offset<R: RangeBounds<Duration>>(self, bound: R) -> Self

Returns a new tracking arc that only contains measurements that fall within the given offset from the first epoch. For example, a bound of 30.minutes()..90.minutes() will only read measurements from the start of the arc + 30 minutes until start + 90 minutes.

Examples found in repository?
examples/05_cislunar_spacecraft_link_od/main.rs (line 226)
34fn main() -> Result<(), Box<dyn Error>> {
35    pel::init();
36
37    // ====================== //
38    // === ALMANAC SET UP === //
39    // ====================== //
40
41    let manifest_dir =
42        PathBuf::from(std::env::var("CARGO_MANIFEST_DIR").unwrap_or(".".to_string()));
43
44    let out = manifest_dir.join("data/04_output/");
45
46    let almanac = Arc::new(
47        Almanac::new(
48            &manifest_dir
49                .join("data/01_planetary/pck08.pca")
50                .to_string_lossy(),
51        )
52        .unwrap()
53        .load(
54            &manifest_dir
55                .join("data/01_planetary/de440s.bsp")
56                .to_string_lossy(),
57        )
58        .unwrap(),
59    );
60
61    let eme2k = almanac.frame_from_uid(EARTH_J2000).unwrap();
62    let moon_iau = almanac.frame_from_uid(IAU_MOON_FRAME).unwrap();
63
64    let epoch = Epoch::from_gregorian_tai(2021, 5, 29, 19, 51, 16, 852_000);
65    let nrho = Orbit::cartesian(
66        166_473.631_302_239_7,
67        -274_715.487_253_382_7,
68        -211_233.210_176_686_7,
69        0.933_451_604_520_018_4,
70        0.436_775_046_841_900_9,
71        -0.082_211_021_250_348_95,
72        epoch,
73        eme2k,
74    );
75
76    let tx_nrho_sc = Spacecraft::from(nrho);
77
78    let state_luna = almanac.transform_to(nrho, MOON_J2000, None).unwrap();
79    println!("Start state (dynamics: Earth, Moon, Sun gravity):\n{state_luna}");
80
81    let bodies = vec![EARTH, SUN];
82    let dynamics = SpacecraftDynamics::new(OrbitalDynamics::point_masses(bodies));
83
84    let setup = Propagator::rk89(
85        dynamics,
86        IntegratorOptions::builder().max_step(0.5.minutes()).build(),
87    );
88
89    /* == Propagate the NRHO vehicle == */
90    let prop_time = 1.1 * state_luna.period().unwrap();
91
92    let (nrho_final, mut tx_traj) = setup
93        .with(tx_nrho_sc, almanac.clone())
94        .for_duration_with_traj(prop_time)
95        .unwrap();
96
97    tx_traj.name = Some("NRHO Tx SC".to_string());
98
99    println!("{tx_traj}");
100
101    /* == Propagate an LLO vehicle == */
102    let llo_orbit =
103        Orbit::try_keplerian_altitude(110.0, 1e-4, 90.0, 0.0, 0.0, 0.0, epoch, moon_iau).unwrap();
104
105    let llo_sc = Spacecraft::builder().orbit(llo_orbit).build();
106
107    let (_, llo_traj) = setup
108        .with(llo_sc, almanac.clone())
109        .until_epoch_with_traj(nrho_final.epoch())
110        .unwrap();
111
112    // Export the subset of the first two hours.
113    llo_traj
114        .clone()
115        .filter_by_offset(..2.hours())
116        .to_parquet_simple(out.join("05_caps_llo_truth.pq"), almanac.clone())?;
117
118    /* == Setup the interlink == */
119
120    let mut measurement_types = IndexSet::new();
121    measurement_types.insert(MeasurementType::Range);
122    measurement_types.insert(MeasurementType::Doppler);
123
124    let mut stochastics = IndexMap::new();
125
126    let sa45_csac_allan_dev = 1e-11;
127
128    stochastics.insert(
129        MeasurementType::Range,
130        StochasticNoise::from_hardware_range_km(
131            sa45_csac_allan_dev,
132            10.0.seconds(),
133            link_specific::ChipRate::StandardT4B,
134            link_specific::SN0::Average,
135        ),
136    );
137
138    stochastics.insert(
139        MeasurementType::Doppler,
140        StochasticNoise::from_hardware_doppler_km_s(
141            sa45_csac_allan_dev,
142            10.0.seconds(),
143            link_specific::CarrierFreq::SBand,
144            link_specific::CN0::Average,
145        ),
146    );
147
148    let interlink = InterlinkTxSpacecraft {
149        traj: tx_traj,
150        measurement_types,
151        integration_time: None,
152        timestamp_noise_s: None,
153        ab_corr: Aberration::LT,
154        stochastic_noises: Some(stochastics),
155    };
156
157    // Devices are the transmitter, which is our NRHO vehicle.
158    let mut devices = BTreeMap::new();
159    devices.insert("NRHO Tx SC".to_string(), interlink);
160
161    let mut configs = BTreeMap::new();
162    configs.insert(
163        "NRHO Tx SC".to_string(),
164        TrkConfig::builder()
165            .strands(vec![Strand {
166                start: epoch,
167                end: nrho_final.epoch(),
168            }])
169            .build(),
170    );
171
172    let mut trk_sim =
173        TrackingArcSim::with_seed(devices.clone(), llo_traj.clone(), configs, 0).unwrap();
174    println!("{trk_sim}");
175
176    let trk_data = trk_sim.generate_measurements(almanac.clone()).unwrap();
177    println!("{trk_data}");
178
179    trk_data
180        .to_parquet_simple(out.clone().join("nrho_interlink_msr.pq"))
181        .unwrap();
182
183    // Run a truth OD where we estimate the LLO position
184    let llo_uncertainty = SpacecraftUncertainty::builder()
185        .nominal(llo_sc)
186        .x_km(1.0)
187        .y_km(1.0)
188        .z_km(1.0)
189        .vx_km_s(1e-3)
190        .vy_km_s(1e-3)
191        .vz_km_s(1e-3)
192        .build();
193
194    let mut proc_devices = devices.clone();
195
196    // Define the initial estimate, randomized, seed for reproducibility
197    let mut initial_estimate = llo_uncertainty.to_estimate_randomized(Some(0)).unwrap();
198    // Inflate the covariance -- https://github.com/nyx-space/nyx/issues/339
199    initial_estimate.covar *= 2.5;
200
201    // Increase the noise in the devices to accept more measurements.
202
203    for link in proc_devices.values_mut() {
204        for noise in &mut link.stochastic_noises.as_mut().unwrap().values_mut() {
205            *noise.white_noise.as_mut().unwrap() *= 3.0;
206        }
207    }
208
209    let init_err = initial_estimate
210        .orbital_state()
211        .ric_difference(&llo_orbit)
212        .unwrap();
213
214    println!("initial estimate:\n{initial_estimate}");
215    println!("RIC errors = {init_err}",);
216
217    let odp = InterlinkKalmanOD::new(
218        setup.clone(),
219        KalmanVariant::ReferenceUpdate,
220        Some(ResidRejectCrit::default()),
221        proc_devices,
222        almanac.clone(),
223    );
224
225    // Shrink the data to process.
226    let arc = trk_data.filter_by_offset(..2.hours());
227
228    let od_sol = odp.process_arc(initial_estimate, &arc).unwrap();
229
230    println!("{od_sol}");
231
232    od_sol
233        .to_parquet(
234            out.join(format!("05_caps_interlink_od_sol.pq")),
235            ExportCfg::default(),
236        )
237        .unwrap();
238
239    let od_traj = od_sol.to_traj().unwrap();
240
241    od_traj
242        .ric_diff_to_parquet(
243            &llo_traj,
244            out.join(format!("05_caps_interlink_llo_est_error.pq")),
245            ExportCfg::default(),
246        )
247        .unwrap();
248
249    let final_est = od_sol.estimates.last().unwrap();
250    assert!(final_est.within_3sigma(), "should be within 3 sigma");
251
252    println!("ESTIMATE\n{final_est:x}\n");
253    let truth = llo_traj.at(final_est.epoch()).unwrap();
254    println!("TRUTH\n{truth:x}");
255
256    let final_err = truth
257        .orbit
258        .ric_difference(&final_est.orbital_state())
259        .unwrap();
260    println!("ERROR {final_err}");
261
262    // Build the residuals versus reference plot.
263    let rvr_sol = odp
264        .process_arc(initial_estimate, &arc.resid_vs_ref_check())
265        .unwrap();
266
267    rvr_sol
268        .to_parquet(
269            out.join(format!("05_caps_interlink_resid_v_ref.pq")),
270            ExportCfg::default(),
271        )
272        .unwrap();
273
274    let final_rvr = rvr_sol.estimates.last().unwrap();
275
276    println!("RMAG error {:.3} m", final_err.rmag_km() * 1e3);
277    println!(
278        "Pure prop error {:.3} m",
279        final_rvr
280            .orbital_state()
281            .ric_difference(&final_est.orbital_state())
282            .unwrap()
283            .rmag_km()
284            * 1e3
285    );
286
287    Ok(())
288}
Source

pub fn filter_by_tracker(self, tracker: String) -> Self

Returns a new tracking arc that only contains measurements from the desired tracker.

Source

pub fn filter_by_measurement_type(self, included_type: MeasurementType) -> Self

Returns a new tracking arc that only contains measurements of the provided type.

Source

pub fn exclude_tracker(self, excluded_tracker: String) -> Self

Returns a new tracking arc that contains measurements from all trackers except the one provided

Source

pub fn exclude_by_epoch<R: RangeBounds<Epoch>>(self, bound: R) -> Self

Returns a new tracking arc that excludes measurements within the given epoch range.

Source

pub fn exclude_measurement_type(self, excluded_type: MeasurementType) -> Self

Returns a new tracking arc that contains measurements from all trackers except the one provided

Source

pub fn downsample(self, target_step: Duration) -> Self

Downsamples the tracking data to a lower frequency using a simple moving average low-pass filter followed by decimation, returning new TrackingDataArc with downsampled measurements.

It provides a computationally efficient approach to reduce the sampling rate while mitigating aliasing effects.

§Algorithm
  1. A simple moving average filter is applied as a low-pass filter.
  2. Decimation is performed by selecting every Nth sample after filtering.
§Advantages
  • Computationally efficient, suitable for large datasets common in spaceflight applications.
  • Provides basic anti-aliasing, crucial for preserving signal integrity in orbit determination and tracking.
  • Maintains phase information, important for accurate timing in spacecraft state estimation.
§Limitations
  • The frequency response is not as sharp as more sophisticated filters (e.g., FIR, IIR).
  • May not provide optimal stopband attenuation for high-precision applications.
§Considerations for Spaceflight Applications
  • Suitable for initial data reduction in ground station tracking pipelines.
  • Adequate for many orbit determination and tracking tasks where computational speed is prioritized.
  • For high-precision applications (e.g., interplanetary navigation), consider using more advanced filtering techniques.
Source

pub fn resid_vs_ref_check(self) -> Self

Examples found in repository?
examples/05_cislunar_spacecraft_link_od/main.rs (line 264)
34fn main() -> Result<(), Box<dyn Error>> {
35    pel::init();
36
37    // ====================== //
38    // === ALMANAC SET UP === //
39    // ====================== //
40
41    let manifest_dir =
42        PathBuf::from(std::env::var("CARGO_MANIFEST_DIR").unwrap_or(".".to_string()));
43
44    let out = manifest_dir.join("data/04_output/");
45
46    let almanac = Arc::new(
47        Almanac::new(
48            &manifest_dir
49                .join("data/01_planetary/pck08.pca")
50                .to_string_lossy(),
51        )
52        .unwrap()
53        .load(
54            &manifest_dir
55                .join("data/01_planetary/de440s.bsp")
56                .to_string_lossy(),
57        )
58        .unwrap(),
59    );
60
61    let eme2k = almanac.frame_from_uid(EARTH_J2000).unwrap();
62    let moon_iau = almanac.frame_from_uid(IAU_MOON_FRAME).unwrap();
63
64    let epoch = Epoch::from_gregorian_tai(2021, 5, 29, 19, 51, 16, 852_000);
65    let nrho = Orbit::cartesian(
66        166_473.631_302_239_7,
67        -274_715.487_253_382_7,
68        -211_233.210_176_686_7,
69        0.933_451_604_520_018_4,
70        0.436_775_046_841_900_9,
71        -0.082_211_021_250_348_95,
72        epoch,
73        eme2k,
74    );
75
76    let tx_nrho_sc = Spacecraft::from(nrho);
77
78    let state_luna = almanac.transform_to(nrho, MOON_J2000, None).unwrap();
79    println!("Start state (dynamics: Earth, Moon, Sun gravity):\n{state_luna}");
80
81    let bodies = vec![EARTH, SUN];
82    let dynamics = SpacecraftDynamics::new(OrbitalDynamics::point_masses(bodies));
83
84    let setup = Propagator::rk89(
85        dynamics,
86        IntegratorOptions::builder().max_step(0.5.minutes()).build(),
87    );
88
89    /* == Propagate the NRHO vehicle == */
90    let prop_time = 1.1 * state_luna.period().unwrap();
91
92    let (nrho_final, mut tx_traj) = setup
93        .with(tx_nrho_sc, almanac.clone())
94        .for_duration_with_traj(prop_time)
95        .unwrap();
96
97    tx_traj.name = Some("NRHO Tx SC".to_string());
98
99    println!("{tx_traj}");
100
101    /* == Propagate an LLO vehicle == */
102    let llo_orbit =
103        Orbit::try_keplerian_altitude(110.0, 1e-4, 90.0, 0.0, 0.0, 0.0, epoch, moon_iau).unwrap();
104
105    let llo_sc = Spacecraft::builder().orbit(llo_orbit).build();
106
107    let (_, llo_traj) = setup
108        .with(llo_sc, almanac.clone())
109        .until_epoch_with_traj(nrho_final.epoch())
110        .unwrap();
111
112    // Export the subset of the first two hours.
113    llo_traj
114        .clone()
115        .filter_by_offset(..2.hours())
116        .to_parquet_simple(out.join("05_caps_llo_truth.pq"), almanac.clone())?;
117
118    /* == Setup the interlink == */
119
120    let mut measurement_types = IndexSet::new();
121    measurement_types.insert(MeasurementType::Range);
122    measurement_types.insert(MeasurementType::Doppler);
123
124    let mut stochastics = IndexMap::new();
125
126    let sa45_csac_allan_dev = 1e-11;
127
128    stochastics.insert(
129        MeasurementType::Range,
130        StochasticNoise::from_hardware_range_km(
131            sa45_csac_allan_dev,
132            10.0.seconds(),
133            link_specific::ChipRate::StandardT4B,
134            link_specific::SN0::Average,
135        ),
136    );
137
138    stochastics.insert(
139        MeasurementType::Doppler,
140        StochasticNoise::from_hardware_doppler_km_s(
141            sa45_csac_allan_dev,
142            10.0.seconds(),
143            link_specific::CarrierFreq::SBand,
144            link_specific::CN0::Average,
145        ),
146    );
147
148    let interlink = InterlinkTxSpacecraft {
149        traj: tx_traj,
150        measurement_types,
151        integration_time: None,
152        timestamp_noise_s: None,
153        ab_corr: Aberration::LT,
154        stochastic_noises: Some(stochastics),
155    };
156
157    // Devices are the transmitter, which is our NRHO vehicle.
158    let mut devices = BTreeMap::new();
159    devices.insert("NRHO Tx SC".to_string(), interlink);
160
161    let mut configs = BTreeMap::new();
162    configs.insert(
163        "NRHO Tx SC".to_string(),
164        TrkConfig::builder()
165            .strands(vec![Strand {
166                start: epoch,
167                end: nrho_final.epoch(),
168            }])
169            .build(),
170    );
171
172    let mut trk_sim =
173        TrackingArcSim::with_seed(devices.clone(), llo_traj.clone(), configs, 0).unwrap();
174    println!("{trk_sim}");
175
176    let trk_data = trk_sim.generate_measurements(almanac.clone()).unwrap();
177    println!("{trk_data}");
178
179    trk_data
180        .to_parquet_simple(out.clone().join("nrho_interlink_msr.pq"))
181        .unwrap();
182
183    // Run a truth OD where we estimate the LLO position
184    let llo_uncertainty = SpacecraftUncertainty::builder()
185        .nominal(llo_sc)
186        .x_km(1.0)
187        .y_km(1.0)
188        .z_km(1.0)
189        .vx_km_s(1e-3)
190        .vy_km_s(1e-3)
191        .vz_km_s(1e-3)
192        .build();
193
194    let mut proc_devices = devices.clone();
195
196    // Define the initial estimate, randomized, seed for reproducibility
197    let mut initial_estimate = llo_uncertainty.to_estimate_randomized(Some(0)).unwrap();
198    // Inflate the covariance -- https://github.com/nyx-space/nyx/issues/339
199    initial_estimate.covar *= 2.5;
200
201    // Increase the noise in the devices to accept more measurements.
202
203    for link in proc_devices.values_mut() {
204        for noise in &mut link.stochastic_noises.as_mut().unwrap().values_mut() {
205            *noise.white_noise.as_mut().unwrap() *= 3.0;
206        }
207    }
208
209    let init_err = initial_estimate
210        .orbital_state()
211        .ric_difference(&llo_orbit)
212        .unwrap();
213
214    println!("initial estimate:\n{initial_estimate}");
215    println!("RIC errors = {init_err}",);
216
217    let odp = InterlinkKalmanOD::new(
218        setup.clone(),
219        KalmanVariant::ReferenceUpdate,
220        Some(ResidRejectCrit::default()),
221        proc_devices,
222        almanac.clone(),
223    );
224
225    // Shrink the data to process.
226    let arc = trk_data.filter_by_offset(..2.hours());
227
228    let od_sol = odp.process_arc(initial_estimate, &arc).unwrap();
229
230    println!("{od_sol}");
231
232    od_sol
233        .to_parquet(
234            out.join(format!("05_caps_interlink_od_sol.pq")),
235            ExportCfg::default(),
236        )
237        .unwrap();
238
239    let od_traj = od_sol.to_traj().unwrap();
240
241    od_traj
242        .ric_diff_to_parquet(
243            &llo_traj,
244            out.join(format!("05_caps_interlink_llo_est_error.pq")),
245            ExportCfg::default(),
246        )
247        .unwrap();
248
249    let final_est = od_sol.estimates.last().unwrap();
250    assert!(final_est.within_3sigma(), "should be within 3 sigma");
251
252    println!("ESTIMATE\n{final_est:x}\n");
253    let truth = llo_traj.at(final_est.epoch()).unwrap();
254    println!("TRUTH\n{truth:x}");
255
256    let final_err = truth
257        .orbit
258        .ric_difference(&final_est.orbital_state())
259        .unwrap();
260    println!("ERROR {final_err}");
261
262    // Build the residuals versus reference plot.
263    let rvr_sol = odp
264        .process_arc(initial_estimate, &arc.resid_vs_ref_check())
265        .unwrap();
266
267    rvr_sol
268        .to_parquet(
269            out.join(format!("05_caps_interlink_resid_v_ref.pq")),
270            ExportCfg::default(),
271        )
272        .unwrap();
273
274    let final_rvr = rvr_sol.estimates.last().unwrap();
275
276    println!("RMAG error {:.3} m", final_err.rmag_km() * 1e3);
277    println!(
278        "Pure prop error {:.3} m",
279        final_rvr
280            .orbital_state()
281            .ric_difference(&final_est.orbital_state())
282            .unwrap()
283            .rmag_km()
284            * 1e3
285    );
286
287    Ok(())
288}

Trait Implementations§

Source§

impl Add for TrackingDataArc

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type Output = TrackingDataArc

The resulting type after applying the + operator.
Source§

fn add(self, rhs: Self) -> Self::Output

Performs the + operation. Read more
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impl AddAssign for TrackingDataArc

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fn add_assign(&mut self, rhs: Self)

Performs the += operation. Read more
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impl Clone for TrackingDataArc

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fn clone(&self) -> TrackingDataArc

Returns a duplicate of the value. Read more
1.0.0 · Source§

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

Performs copy-assignment from source. Read more
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impl Debug for TrackingDataArc

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

Formats the value using the given formatter. Read more
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impl Default for TrackingDataArc

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fn default() -> TrackingDataArc

Returns the “default value” for a type. Read more
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impl Display for TrackingDataArc

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

Formats the value using the given formatter. Read more
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impl PartialEq for TrackingDataArc

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

Tests for self and other values to be equal, and is used by ==.
1.0.0 · Source§

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

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

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impl<T> Any for T
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fn type_id(&self) -> TypeId

Gets the TypeId of self. Read more
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impl<T> Borrow<T> for T
where T: ?Sized,

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fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more
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impl<T> BorrowMut<T> for T
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fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more
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impl<T> CloneToUninit for T
where T: Clone,

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unsafe fn clone_to_uninit(&self, dest: *mut u8)

🔬This is a nightly-only experimental API. (clone_to_uninit)
Performs copy-assignment from self to dest. Read more
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impl<T> From<T> for T

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fn from(t: T) -> T

Returns the argument unchanged.

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impl<T> Instrument for T

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fn instrument(self, span: Span) -> Instrumented<Self>

Instruments this type with the provided [Span], returning an Instrumented wrapper. Read more
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fn in_current_span(self) -> Instrumented<Self>

Instruments this type with the current Span, returning an Instrumented wrapper. Read more
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where U: From<T>,

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fn into(self) -> U

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

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impl<T> IntoEither for T

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fn into_either(self, into_left: bool) -> Either<Self, Self>

Converts self into a Left variant of Either<Self, Self> if into_left is true. Converts self into a Right variant of Either<Self, Self> otherwise. Read more
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fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
where F: FnOnce(&Self) -> bool,

Converts self into a Left variant of Either<Self, Self> if into_left(&self) returns true. Converts self into a Right variant of Either<Self, Self> otherwise. Read more
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impl<T> Pointable for T

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const ALIGN: usize

The alignment of pointer.
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type Init = T

The type for initializers.
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unsafe fn init(init: <T as Pointable>::Init) -> usize

Initializes a with the given initializer. Read more
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unsafe fn deref<'a>(ptr: usize) -> &'a T

Dereferences the given pointer. Read more
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unsafe fn deref_mut<'a>(ptr: usize) -> &'a mut T

Mutably dereferences the given pointer. Read more
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unsafe fn drop(ptr: usize)

Drops the object pointed to by the given pointer. Read more
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impl<T> Same for T

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type Output = T

Should always be Self
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impl<SS, SP> SupersetOf<SS> for SP
where SS: SubsetOf<SP>,

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fn to_subset(&self) -> Option<SS>

The inverse inclusion map: attempts to construct self from the equivalent element of its superset. Read more
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fn is_in_subset(&self) -> bool

Checks if self is actually part of its subset T (and can be converted to it).
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fn to_subset_unchecked(&self) -> SS

Use with care! Same as self.to_subset but without any property checks. Always succeeds.
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fn from_subset(element: &SS) -> SP

The inclusion map: converts self to the equivalent element of its superset.
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impl<T> ToOwned for T
where T: Clone,

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type Owned = T

The resulting type after obtaining ownership.
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fn to_owned(&self) -> T

Creates owned data from borrowed data, usually by cloning. Read more
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fn clone_into(&self, target: &mut T)

Uses borrowed data to replace owned data, usually by cloning. Read more
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impl<T> ToString for T
where T: Display + ?Sized,

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fn to_string(&self) -> String

Converts the given value to a String. Read more
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impl<T, U> TryFrom<U> for T
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type Error = Infallible

The type returned in the event of a conversion error.
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fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>

Performs the conversion.
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impl<T, U> TryInto<U> for T
where U: TryFrom<T>,

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type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.
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fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>

Performs the conversion.
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impl<V, T> VZip<V> for T
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fn vzip(self) -> V

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impl<T> WithSubscriber for T

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fn with_subscriber<S>(self, subscriber: S) -> WithDispatch<Self>
where S: Into<Dispatch>,

Attaches the provided Subscriber to this type, returning a [WithDispatch] wrapper. Read more
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fn with_current_subscriber(self) -> WithDispatch<Self>

Attaches the current default Subscriber to this type, returning a [WithDispatch] wrapper. Read more
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impl<T> Allocation for T
where T: RefUnwindSafe + Send + Sync,

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impl<T, Right> ClosedAdd<Right> for T
where T: Add<Right, Output = T> + AddAssign<Right>,

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impl<T, Right> ClosedAddAssign<Right> for T
where T: ClosedAdd<Right> + AddAssign<Right>,

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impl<T> ErasedDestructor for T
where T: 'static,

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impl<T> Scalar for T
where T: 'static + Clone + PartialEq + Debug,