Struct TimeSeries 

pub struct TimeSeries { /* private fields */ }

An iterator of a sequence of evenly spaced Epochs.

(Python documentation hints) :type start: Epoch :type end: Epoch :type step: Duration :type inclusive: bool

Implementations

impl TimeSeries

pub fn exclusive(start: Epoch, end: Epoch, step: Duration) -> TimeSeries

Return an iterator of evenly spaced Epochs, inclusive on start and exclusive on end.

use hifitime::{Epoch, Unit, TimeSeries};
let start = Epoch::from_gregorian_utc_at_midnight(2017, 1, 14);
let end = Epoch::from_gregorian_utc_at_noon(2017, 1, 14);
let step = Unit::Hour * 2;
let time_series = TimeSeries::exclusive(start, end, step);
let mut cnt = 0;
for epoch in time_series {
    println!("{}", epoch);
    cnt += 1
}
assert_eq!(cnt, 6)

pub fn inclusive(start: Epoch, end: Epoch, step: Duration) -> TimeSeries

Return an iterator of evenly spaced Epochs, inclusive on start and on end.

use hifitime::{Epoch, Unit, TimeSeries};
let start = Epoch::from_gregorian_utc_at_midnight(2017, 1, 14);
let end = Epoch::from_gregorian_utc_at_noon(2017, 1, 14);
let step = Unit::Hour * 2;
let time_series = TimeSeries::inclusive(start, end, step);
let mut cnt = 0;
for epoch in time_series {
    println!("{}", epoch);
    cnt += 1
}
assert_eq!(cnt, 7)

Examples found in repository

examples/04_lro_od/main.rs (line 325)

fn main() -> Result<(), Box<dyn Error>> {
    pel::init();

    // ====================== //
    // === ALMANAC SET UP === //
    // ====================== //

    // Dynamics models require planetary constants and ephemerides to be defined.
    // Let's start by grabbing those by using ANISE's MetaAlmanac.

    let data_folder: PathBuf = [env!("CARGO_MANIFEST_DIR"), "examples", "04_lro_od"]
        .iter()
        .collect();

    let meta = data_folder.join("lro-dynamics.dhall");

    // Load this ephem in the general Almanac we're using for this analysis.
    let mut almanac = MetaAlmanac::new(meta.to_string_lossy().as_ref())
        .map_err(Box::new)?
        .process(true)
        .map_err(Box::new)?;

    let mut moon_pc = almanac.get_planetary_data_from_id(MOON).unwrap();
    moon_pc.mu_km3_s2 = 4902.74987;
    almanac.set_planetary_data_from_id(MOON, moon_pc).unwrap();

    let mut earth = almanac.get_planetary_data_from_id(EARTH).unwrap();
    earth.mu_km3_s2 = 398600.436;
    almanac.set_planetary_data_from_id(EARTH, earth).unwrap();

    // Save this new kernel for reuse.
    // In an operational context, this would be part of the "Lock" process, and should not change throughout the mission.
    almanac
        .planetary_data
        .values()
        .next()
        .unwrap()
        .save_as(&data_folder.join("lro-specific.pca"), true)?;

    // Lock the almanac (an Arc is a read only structure).
    let almanac = Arc::new(almanac);

    // Orbit determination requires a Trajectory structure, which can be saved as parquet file.
    // In our case, the trajectory comes from the BSP file, so we need to build a Trajectory from the almanac directly.
    // To query the Almanac, we need to build the LRO frame in the J2000 orientation in our case.
    // Inspecting the LRO BSP in the ANISE GUI shows us that NASA has assigned ID -85 to LRO.
    let lro_frame = Frame::from_ephem_j2000(-85);

    // To build the trajectory we need to provide a spacecraft template.
    let sc_template = Spacecraft::builder()
        .mass(Mass::from_dry_and_prop_masses(1018.0, 900.0)) // Launch masses
        .srp(SRPData {
            // SRP configuration is arbitrary, but we will be estimating it anyway.
            area_m2: 3.9 * 2.7,
            coeff_reflectivity: 0.96,
        })
        .orbit(Orbit::zero(MOON_J2000)) // Setting a zero orbit here because it's just a template
        .build();
    // Now we can build the trajectory from the BSP file.
    // We'll arbitrarily set the tracking arc to 24 hours with a five second time step.
    let traj_as_flown = Traj::from_bsp(
        lro_frame,
        MOON_J2000,
        almanac.clone(),
        sc_template,
        5.seconds(),
        Some(Epoch::from_str("2024-01-01 00:00:00 UTC")?),
        Some(Epoch::from_str("2024-01-02 00:00:00 UTC")?),
        Aberration::LT,
        Some("LRO".to_string()),
    )?;

    println!("{traj_as_flown}");

    // ====================== //
    // === MODEL MATCHING === //
    // ====================== //

    // Set up the spacecraft dynamics.

    // Specify that the orbital dynamics must account for the graviational pull of the Earth and the Sun.
    // The gravity of the Moon will also be accounted for since the spaceraft in a lunar orbit.
    let mut orbital_dyn = OrbitalDynamics::point_masses(vec![EARTH, SUN, JUPITER_BARYCENTER]);

    // We want to include the spherical harmonics, so let's download the gravitational data from the Nyx Cloud.
    // We're using the GRAIL JGGRX model.
    let mut jggrx_meta = MetaFile {
        uri: "http://public-data.nyxspace.com/nyx/models/Luna_jggrx_1500e_sha.tab.gz".to_string(),
        crc32: Some(0x6bcacda8), // Specifying the CRC32 avoids redownloading it if it's cached.
    };
    // And let's download it if we don't have it yet.
    jggrx_meta.process(true)?;

    // Build the spherical harmonics.
    // The harmonics must be computed in the body fixed frame.
    // We're using the long term prediction of the Moon principal axes frame.
    let moon_pa_frame = MOON_PA_FRAME.with_orient(31008);
    let sph_harmonics = Harmonics::from_stor(
        almanac.frame_info(moon_pa_frame)?,
        HarmonicsMem::from_shadr(&jggrx_meta.uri, 80, 80, true)?,
    );

    // Include the spherical harmonics into the orbital dynamics.
    orbital_dyn.accel_models.push(sph_harmonics);

    // We define the solar radiation pressure, using the default solar flux and accounting only
    // for the eclipsing caused by the Earth and Moon.
    // Note that by default, enabling the SolarPressure model will also enable the estimation of the coefficient of reflectivity.
    let srp_dyn = SolarPressure::new(vec![EARTH_J2000, MOON_J2000], almanac.clone())?;

    // Finalize setting up the dynamics, specifying the force models (orbital_dyn) separately from the
    // acceleration models (SRP in this case). Use `from_models` to specify multiple accel models.
    let dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn);

    println!("{dynamics}");

    // Now we can build the propagator.
    let setup = Propagator::default_dp78(dynamics.clone());

    // For reference, let's build the trajectory with Nyx's models from that LRO state.
    let (sim_final, traj_as_sim) = setup
        .with(*traj_as_flown.first(), almanac.clone())
        .until_epoch_with_traj(traj_as_flown.last().epoch())?;

    println!("SIM INIT:  {:x}", traj_as_flown.first());
    println!("SIM FINAL: {sim_final:x}");
    // Compute RIC difference between SIM and LRO ephem
    let sim_lro_delta = sim_final
        .orbit
        .ric_difference(&traj_as_flown.last().orbit)?;
    println!("{traj_as_sim}");
    println!(
        "SIM v LRO - RIC Position (m): {:.3}",
        sim_lro_delta.radius_km * 1e3
    );
    println!(
        "SIM v LRO - RIC Velocity (m/s): {:.3}",
        sim_lro_delta.velocity_km_s * 1e3
    );

    traj_as_sim.ric_diff_to_parquet(
        &traj_as_flown,
        "./data/04_output/04_lro_sim_truth_error.parquet",
        ExportCfg::default(),
    )?;

    // ==================== //
    // === OD SIMULATOR === //
    // ==================== //

    // 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
    // and the truth LRO state.

    // Therefore, we will actually run an estimation from a dispersed LRO state.
    // The sc_seed is the true LRO state from the BSP.
    let sc_seed = *traj_as_flown.first();

    // Load the Deep Space Network ground stations.
    // Nyx allows you to build these at runtime but it's pretty static so we can just load them from YAML.
    let ground_station_file: PathBuf = [
        env!("CARGO_MANIFEST_DIR"),
        "examples",
        "04_lro_od",
        "dsn-network.yaml",
    ]
    .iter()
    .collect();

    let devices = GroundStation::load_named(ground_station_file)?;

    let mut proc_devices = devices.clone();

    // Increase the noise in the devices to accept more measurements.
    for gs in proc_devices.values_mut() {
        if let Some(noise) = &mut gs
            .stochastic_noises
            .as_mut()
            .unwrap()
            .get_mut(&MeasurementType::Range)
        {
            *noise.white_noise.as_mut().unwrap() *= 3.0;
        }
    }

    // Typical OD software requires that you specify your own tracking schedule or you'll have overlapping measurements.
    // Nyx can build a tracking schedule for you based on the first station with access.
    let trkconfg_yaml: PathBuf = [
        env!("CARGO_MANIFEST_DIR"),
        "examples",
        "04_lro_od",
        "tracking-cfg.yaml",
    ]
    .iter()
    .collect();

    let configs: BTreeMap<String, TrkConfig> = TrkConfig::load_named(trkconfg_yaml)?;

    // Build the tracking arc simulation to generate a "standard measurement".
    let mut trk = TrackingArcSim::<Spacecraft, GroundStation>::with_seed(
        devices.clone(),
        traj_as_flown.clone(),
        configs,
        123, // Set a seed for reproducibility
    )?;

    trk.build_schedule(almanac.clone())?;
    let arc = trk.generate_measurements(almanac.clone())?;
    // Save the simulated tracking data
    arc.to_parquet_simple("./data/04_output/04_lro_simulated_tracking.parquet")?;

    // We'll note that in our case, we have continuous coverage of LRO when the vehicle is not behind the Moon.
    println!("{arc}");

    // Now that we have simulated measurements, we'll run the orbit determination.

    // ===================== //
    // === OD ESTIMATION === //
    // ===================== //

    let sc = SpacecraftUncertainty::builder()
        .nominal(sc_seed)
        .frame(LocalFrame::RIC)
        .x_km(0.5)
        .y_km(0.5)
        .z_km(0.5)
        .vx_km_s(5e-3)
        .vy_km_s(5e-3)
        .vz_km_s(5e-3)
        .build();

    // Build the filter initial estimate, which we will reuse in the filter.
    let mut initial_estimate = sc.to_estimate()?;
    initial_estimate.covar *= 3.0;

    println!("== FILTER STATE ==\n{sc_seed:x}\n{initial_estimate}");

    // Build the SNC in the Moon J2000 frame, specified as a velocity noise over time.
    let process_noise = ProcessNoise3D::from_velocity_km_s(
        &[1e-10, 1e-10, 1e-10],
        1 * Unit::Hour,
        10 * Unit::Minute,
        None,
    );

    println!("{process_noise}");

    // We'll set up the OD process to reject measurements whose residuals are move than 3 sigmas away from what we expect.
    let odp = SpacecraftKalmanOD::new(
        setup,
        KalmanVariant::ReferenceUpdate,
        Some(ResidRejectCrit::default()),
        proc_devices,
        almanac.clone(),
    )
    .with_process_noise(process_noise);

    let od_sol = odp.process_arc(initial_estimate, &arc)?;

    let final_est = od_sol.estimates.last().unwrap();

    println!("{final_est}");

    let ric_err = traj_as_flown
        .at(final_est.epoch())?
        .orbit
        .ric_difference(&final_est.orbital_state())?;
    println!("== RIC at end ==");
    println!("RIC Position (m): {:.3}", ric_err.radius_km * 1e3);
    println!("RIC Velocity (m/s): {:.3}", ric_err.velocity_km_s * 1e3);

    println!(
        "Num residuals rejected: #{}",
        od_sol.rejected_residuals().len()
    );
    println!(
        "Percentage within +/-3: {}",
        od_sol.residual_ratio_within_threshold(3.0).unwrap()
    );
    println!("Ratios normal? {}", od_sol.is_normal(None).unwrap());

    od_sol.to_parquet(
        "./data/04_output/04_lro_od_results.parquet",
        ExportCfg::default(),
    )?;

    // Create the ephemeris
    let ephem = od_sol.to_ephemeris("LRO rebuilt".to_string());
    let ephem_start = ephem.start_epoch().unwrap();
    let ephem_end = ephem.end_epoch().unwrap();
    // Check that the covariance is PSD throughout the ephemeris by interpolating it.
    for epoch in TimeSeries::inclusive(ephem_start, ephem_end, Unit::Minute * 5) {
        ephem
            .covar_at(
                epoch,
                anise::ephemerides::ephemeris::LocalFrame::RIC,
                &almanac,
            )
            .unwrap_or_else(|e| panic!("covar not PSD at {epoch}: {e}"));
    }
    // Export as BSP!
    ephem
        .write_spice_bsp(-85, "./data/04_output/04_lro_rebuilt.bsp", None)
        .expect("could not built BSP");
    let new_almanac = Almanac::default()
        .load("./data/04_output/04_lro_rebuilt.bsp")
        .unwrap();
    new_almanac.describe(None, None, None, None, None, None, None, None);
    let (spk_start, spk_end) = new_almanac.spk_domain(-85).unwrap();

    assert!((ephem_start - spk_start).abs() < Unit::Microsecond * 1);
    assert!((ephem_end - spk_end).abs() < Unit::Microsecond * 1);

    // In our case, we have the truth trajectory from NASA.
    // So we can compute the RIC state difference between the real LRO ephem and what we've just estimated.
    // Export the OD trajectory first.
    let od_trajectory = od_sol.to_traj()?;
    // Build the RIC difference.
    od_trajectory.ric_diff_to_parquet(
        &traj_as_flown,
        "./data/04_output/04_lro_od_truth_error.parquet",
        ExportCfg::default(),
    )?;

    Ok(())
}

Trait Implementations

impl Clone for TimeSeries

fn clone(&self) -> TimeSeries

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for TimeSeries

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

Formats the value using the given formatter.

impl Display for TimeSeries

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

Formats the value using the given formatter.

impl DoubleEndedIterator for TimeSeries

fn next_back(&mut self) -> Option<Epoch>

Removes and returns an element from the end of the iterator.

fn advance_back_by(&mut self, n: usize) -> Result<(), NonZero<usize>>

🔬This is a nightly-only experimental API. (iter_advance_by)

Advances the iterator from the back by n elements.

fn nth_back(&mut self, n: usize) -> Option<Self::Item>

Returns the nth element from the end of the iterator.

fn try_rfold<B, F, R>(&mut self, init: B, f: F) -> R

where Self: Sized, F: FnMut(B, Self::Item) -> R, R: Try<Output = B>,

This is the reverse version of Iterator::try_fold(): it takes elements starting from the back of the iterator.

fn rfold<B, F>(self, init: B, f: F) -> B

where Self: Sized, F: FnMut(B, Self::Item) -> B,

An iterator method that reduces the iterator’s elements to a single, final value, starting from the back.

fn rfind<P>(&mut self, predicate: P) -> Option<Self::Item>

where Self: Sized, P: FnMut(&Self::Item) -> bool,

Searches for an element of an iterator from the back that satisfies a predicate.

impl ExactSizeIterator for TimeSeries

where TimeSeries: Iterator,

fn len(&self) -> usize

Returns the exact remaining length of the iterator.

fn is_empty(&self) -> bool

🔬This is a nightly-only experimental API. (exact_size_is_empty)

Returns true if the iterator is empty.

impl Iterator for TimeSeries

type Item = Epoch

The type of the elements being iterated over.

fn next(&mut self) -> Option<Epoch>

Advances the iterator and returns the next value.

fn size_hint(&self) -> (usize, Option<usize>)

Returns the bounds on the remaining length of the iterator.

fn next_chunk<const N: usize>( &mut self, ) -> Result<[Self::Item; N], IntoIter<Self::Item, N>>

where Self: Sized,

🔬This is a nightly-only experimental API. (iter_next_chunk)

Advances the iterator and returns an array containing the next N values.

fn count(self) -> usize

where Self: Sized,

Consumes the iterator, counting the number of iterations and returning it.

fn last(self) -> Option<Self::Item>

where Self: Sized,

Consumes the iterator, returning the last element.

fn advance_by(&mut self, n: usize) -> Result<(), NonZero<usize>>

🔬This is a nightly-only experimental API. (iter_advance_by)

Advances the iterator by n elements.

fn nth(&mut self, n: usize) -> Option<Self::Item>

Returns the nth element of the iterator.

fn step_by(self, step: usize) -> StepBy<Self>

where Self: Sized,

Creates an iterator starting at the same point, but stepping by the given amount at each iteration.

fn chain<U>(self, other: U) -> Chain<Self, <U as IntoIterator>::IntoIter>

where Self: Sized, U: IntoIterator<Item = Self::Item>,

Takes two iterators and creates a new iterator over both in sequence.

fn zip<U>(self, other: U) -> Zip<Self, <U as IntoIterator>::IntoIter>

where Self: Sized, U: IntoIterator,

‘Zips up’ two iterators into a single iterator of pairs.

fn intersperse(self, separator: Self::Item) -> Intersperse<Self>

where Self: Sized, Self::Item: Clone,

🔬This is a nightly-only experimental API. (iter_intersperse)

Creates a new iterator which places a copy of separator between adjacent items of the original iterator.

fn intersperse_with<G>(self, separator: G) -> IntersperseWith<Self, G>

where Self: Sized, G: FnMut() -> Self::Item,

🔬This is a nightly-only experimental API. (iter_intersperse)

Creates a new iterator which places an item generated by separator between adjacent items of the original iterator.

fn map<B, F>(self, f: F) -> Map<Self, F>

where Self: Sized, F: FnMut(Self::Item) -> B,

Takes a closure and creates an iterator which calls that closure on each element.

fn for_each<F>(self, f: F)

where Self: Sized, F: FnMut(Self::Item),

Calls a closure on each element of an iterator.

fn filter<P>(self, predicate: P) -> Filter<Self, P>

where Self: Sized, P: FnMut(&Self::Item) -> bool,

Creates an iterator which uses a closure to determine if an element should be yielded.

fn filter_map<B, F>(self, f: F) -> FilterMap<Self, F>

where Self: Sized, F: FnMut(Self::Item) -> Option<B>,

Creates an iterator that both filters and maps.

fn enumerate(self) -> Enumerate<Self>

where Self: Sized,

Creates an iterator which gives the current iteration count as well as the next value.

fn peekable(self) -> Peekable<Self>

where Self: Sized,

Creates an iterator which can use the peek and peek_mut methods to look at the next element of the iterator without consuming it. See their documentation for more information.

fn skip_while<P>(self, predicate: P) -> SkipWhile<Self, P>

where Self: Sized, P: FnMut(&Self::Item) -> bool,

Creates an iterator that skips elements based on a predicate.

fn take_while<P>(self, predicate: P) -> TakeWhile<Self, P>

where Self: Sized, P: FnMut(&Self::Item) -> bool,

Creates an iterator that yields elements based on a predicate.

fn map_while<B, P>(self, predicate: P) -> MapWhile<Self, P>

where Self: Sized, P: FnMut(Self::Item) -> Option<B>,

Creates an iterator that both yields elements based on a predicate and maps.

fn skip(self, n: usize) -> Skip<Self>

where Self: Sized,

Creates an iterator that skips the first n elements.

fn take(self, n: usize) -> Take<Self>

where Self: Sized,

Creates an iterator that yields the first n elements, or fewer if the underlying iterator ends sooner.

fn scan<St, B, F>(self, initial_state: St, f: F) -> Scan<Self, St, F>

where Self: Sized, F: FnMut(&mut St, Self::Item) -> Option<B>,

An iterator adapter which, like fold, holds internal state, but unlike fold, produces a new iterator.

fn flat_map<U, F>(self, f: F) -> FlatMap<Self, U, F>

where Self: Sized, U: IntoIterator, F: FnMut(Self::Item) -> U,

Creates an iterator that works like map, but flattens nested structure.

fn flatten(self) -> Flatten<Self>

where Self: Sized, Self::Item: IntoIterator,

Creates an iterator that flattens nested structure.

fn map_windows<F, R, const N: usize>(self, f: F) -> MapWindows<Self, F, N>

where Self: Sized, F: FnMut(&[Self::Item; N]) -> R,

🔬This is a nightly-only experimental API. (iter_map_windows)

Calls the given function f for each contiguous window of size N over self and returns an iterator over the outputs of f. Like slice::windows(), the windows during mapping overlap as well.

fn fuse(self) -> Fuse<Self>

where Self: Sized,

Creates an iterator which ends after the first None.

fn inspect<F>(self, f: F) -> Inspect<Self, F>

where Self: Sized, F: FnMut(&Self::Item),

Does something with each element of an iterator, passing the value on.

fn by_ref(&mut self) -> &mut Self

where Self: Sized,

Creates a “by reference” adapter for this instance of Iterator.

fn collect<B>(self) -> B

where B: FromIterator<Self::Item>, Self: Sized,

Transforms an iterator into a collection.

fn try_collect<B>( &mut self, ) -> <<Self::Item as Try>::Residual as Residual<B>>::TryType

where Self: Sized, Self::Item: Try, <Self::Item as Try>::Residual: Residual<B>, B: FromIterator<<Self::Item as Try>::Output>,

🔬This is a nightly-only experimental API. (iterator_try_collect)

Fallibly transforms an iterator into a collection, short circuiting if a failure is encountered.

fn collect_into<E>(self, collection: &mut E) -> &mut E

where E: Extend<Self::Item>, Self: Sized,

🔬This is a nightly-only experimental API. (iter_collect_into)

Collects all the items from an iterator into a collection.

fn partition<B, F>(self, f: F) -> (B, B)

where Self: Sized, B: Default + Extend<Self::Item>, F: FnMut(&Self::Item) -> bool,

Consumes an iterator, creating two collections from it.

fn partition_in_place<'a, T, P>(self, predicate: P) -> usize

where T: 'a, Self: Sized + DoubleEndedIterator<Item = &'a mut T>, P: FnMut(&T) -> bool,

🔬This is a nightly-only experimental API. (iter_partition_in_place)

Reorders the elements of this iterator in-place according to the given predicate, such that all those that return true precede all those that return false. Returns the number of true elements found.

fn is_partitioned<P>(self, predicate: P) -> bool

where Self: Sized, P: FnMut(Self::Item) -> bool,

🔬This is a nightly-only experimental API. (iter_is_partitioned)

Checks if the elements of this iterator are partitioned according to the given predicate, such that all those that return true precede all those that return false.

fn try_fold<B, F, R>(&mut self, init: B, f: F) -> R

where Self: Sized, F: FnMut(B, Self::Item) -> R, R: Try<Output = B>,

An iterator method that applies a function as long as it returns successfully, producing a single, final value.

fn try_for_each<F, R>(&mut self, f: F) -> R

where Self: Sized, F: FnMut(Self::Item) -> R, R: Try<Output = ()>,

An iterator method that applies a fallible function to each item in the iterator, stopping at the first error and returning that error.

fn fold<B, F>(self, init: B, f: F) -> B

where Self: Sized, F: FnMut(B, Self::Item) -> B,

Folds every element into an accumulator by applying an operation, returning the final result.

fn reduce<F>(self, f: F) -> Option<Self::Item>

where Self: Sized, F: FnMut(Self::Item, Self::Item) -> Self::Item,

Reduces the elements to a single one, by repeatedly applying a reducing operation.

fn try_reduce<R>( &mut self, f: impl FnMut(Self::Item, Self::Item) -> R, ) -> <<R as Try>::Residual as Residual<Option<<R as Try>::Output>>>::TryType

where Self: Sized, R: Try<Output = Self::Item>, <R as Try>::Residual: Residual<Option<Self::Item>>,

🔬This is a nightly-only experimental API. (iterator_try_reduce)

Reduces the elements to a single one by repeatedly applying a reducing operation. If the closure returns a failure, the failure is propagated back to the caller immediately.

fn all<F>(&mut self, f: F) -> bool

where Self: Sized, F: FnMut(Self::Item) -> bool,

Tests if every element of the iterator matches a predicate.

fn any<F>(&mut self, f: F) -> bool

where Self: Sized, F: FnMut(Self::Item) -> bool,

Tests if any element of the iterator matches a predicate.

fn find<P>(&mut self, predicate: P) -> Option<Self::Item>

where Self: Sized, P: FnMut(&Self::Item) -> bool,

Searches for an element of an iterator that satisfies a predicate.

fn find_map<B, F>(&mut self, f: F) -> Option<B>

where Self: Sized, F: FnMut(Self::Item) -> Option<B>,

Applies function to the elements of iterator and returns the first non-none result.

fn try_find<R>( &mut self, f: impl FnMut(&Self::Item) -> R, ) -> <<R as Try>::Residual as Residual<Option<Self::Item>>>::TryType

where Self: Sized, R: Try<Output = bool>, <R as Try>::Residual: Residual<Option<Self::Item>>,

🔬This is a nightly-only experimental API. (try_find)

Applies function to the elements of iterator and returns the first true result or the first error.

fn position<P>(&mut self, predicate: P) -> Option<usize>

where Self: Sized, P: FnMut(Self::Item) -> bool,

Searches for an element in an iterator, returning its index.

fn rposition<P>(&mut self, predicate: P) -> Option<usize>

where P: FnMut(Self::Item) -> bool, Self: Sized + ExactSizeIterator + DoubleEndedIterator,

Searches for an element in an iterator from the right, returning its index.

fn max(self) -> Option<Self::Item>

where Self: Sized, Self::Item: Ord,

Returns the maximum element of an iterator.

fn min(self) -> Option<Self::Item>

where Self: Sized, Self::Item: Ord,

Returns the minimum element of an iterator.

fn max_by_key<B, F>(self, f: F) -> Option<Self::Item>

where B: Ord, Self: Sized, F: FnMut(&Self::Item) -> B,

Returns the element that gives the maximum value from the specified function.

fn max_by<F>(self, compare: F) -> Option<Self::Item>

where Self: Sized, F: FnMut(&Self::Item, &Self::Item) -> Ordering,

Returns the element that gives the maximum value with respect to the specified comparison function.

fn min_by_key<B, F>(self, f: F) -> Option<Self::Item>

where B: Ord, Self: Sized, F: FnMut(&Self::Item) -> B,

Returns the element that gives the minimum value from the specified function.

fn min_by<F>(self, compare: F) -> Option<Self::Item>

where Self: Sized, F: FnMut(&Self::Item, &Self::Item) -> Ordering,

Returns the element that gives the minimum value with respect to the specified comparison function.

fn rev(self) -> Rev<Self>

where Self: Sized + DoubleEndedIterator,

Reverses an iterator’s direction.

fn unzip<A, B, FromA, FromB>(self) -> (FromA, FromB)

where FromA: Default + Extend<A>, FromB: Default + Extend<B>, Self: Sized + Iterator<Item = (A, B)>,

Converts an iterator of pairs into a pair of containers.

fn copied<'a, T>(self) -> Copied<Self>

where T: Copy + 'a, Self: Sized + Iterator<Item = &'a T>,

Creates an iterator which copies all of its elements.

fn cloned<'a, T>(self) -> Cloned<Self>

where T: Clone + 'a, Self: Sized + Iterator<Item = &'a T>,

Creates an iterator which clones all of its elements.

fn cycle(self) -> Cycle<Self>

where Self: Sized + Clone,

Repeats an iterator endlessly.

fn array_chunks<const N: usize>(self) -> ArrayChunks<Self, N>

where Self: Sized,

🔬This is a nightly-only experimental API. (iter_array_chunks)

Returns an iterator over N elements of the iterator at a time.

fn sum<S>(self) -> S

where Self: Sized, S: Sum<Self::Item>,

Sums the elements of an iterator.

fn product<P>(self) -> P

where Self: Sized, P: Product<Self::Item>,

Iterates over the entire iterator, multiplying all the elements

fn cmp<I>(self, other: I) -> Ordering

where I: IntoIterator<Item = Self::Item>, Self::Item: Ord, Self: Sized,

Lexicographically compares the elements of this Iterator with those of another.

fn cmp_by<I, F>(self, other: I, cmp: F) -> Ordering

where Self: Sized, I: IntoIterator, F: FnMut(Self::Item, <I as IntoIterator>::Item) -> Ordering,

🔬This is a nightly-only experimental API. (iter_order_by)

Lexicographically compares the elements of this Iterator with those of another with respect to the specified comparison function.

fn partial_cmp<I>(self, other: I) -> Option<Ordering>

where I: IntoIterator, Self::Item: PartialOrd<<I as IntoIterator>::Item>, Self: Sized,

Lexicographically compares the PartialOrd elements of this Iterator with those of another. The comparison works like short-circuit evaluation, returning a result without comparing the remaining elements. As soon as an order can be determined, the evaluation stops and a result is returned.

fn partial_cmp_by<I, F>(self, other: I, partial_cmp: F) -> Option<Ordering>

where Self: Sized, I: IntoIterator, F: FnMut(Self::Item, <I as IntoIterator>::Item) -> Option<Ordering>,

🔬This is a nightly-only experimental API. (iter_order_by)

Lexicographically compares the elements of this Iterator with those of another with respect to the specified comparison function.

fn eq<I>(self, other: I) -> bool

where I: IntoIterator, Self::Item: PartialEq<<I as IntoIterator>::Item>, Self: Sized,

Determines if the elements of this Iterator are equal to those of another.

fn eq_by<I, F>(self, other: I, eq: F) -> bool

where Self: Sized, I: IntoIterator, F: FnMut(Self::Item, <I as IntoIterator>::Item) -> bool,

🔬This is a nightly-only experimental API. (iter_order_by)

Determines if the elements of this Iterator are equal to those of another with respect to the specified equality function.

fn ne<I>(self, other: I) -> bool

where I: IntoIterator, Self::Item: PartialEq<<I as IntoIterator>::Item>, Self: Sized,

Determines if the elements of this Iterator are not equal to those of another.

fn lt<I>(self, other: I) -> bool

where I: IntoIterator, Self::Item: PartialOrd<<I as IntoIterator>::Item>, Self: Sized,

Determines if the elements of this Iterator are lexicographically less than those of another.

fn le<I>(self, other: I) -> bool

where I: IntoIterator, Self::Item: PartialOrd<<I as IntoIterator>::Item>, Self: Sized,

Determines if the elements of this Iterator are lexicographically less or equal to those of another.

fn gt<I>(self, other: I) -> bool

where I: IntoIterator, Self::Item: PartialOrd<<I as IntoIterator>::Item>, Self: Sized,

Determines if the elements of this Iterator are lexicographically greater than those of another.

fn ge<I>(self, other: I) -> bool

where I: IntoIterator, Self::Item: PartialOrd<<I as IntoIterator>::Item>, Self: Sized,

Determines if the elements of this Iterator are lexicographically greater than or equal to those of another.

fn is_sorted(self) -> bool

where Self: Sized, Self::Item: PartialOrd,

Checks if the elements of this iterator are sorted.

fn is_sorted_by<F>(self, compare: F) -> bool

where Self: Sized, F: FnMut(&Self::Item, &Self::Item) -> bool,

Checks if the elements of this iterator are sorted using the given comparator function.

fn is_sorted_by_key<F, K>(self, f: F) -> bool

where Self: Sized, F: FnMut(Self::Item) -> K, K: PartialOrd,

Checks if the elements of this iterator are sorted using the given key extraction function.

impl LowerExp for TimeSeries

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

Prints the Epoch in TDB

impl LowerHex for TimeSeries

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

Prints the Epoch in TAI

impl Octal for TimeSeries

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

Prints the Epoch in GPS

impl PartialEq for TimeSeries

fn eq(&self, other: &TimeSeries) -> 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 Pointer for TimeSeries

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

Prints the Epoch in UNIX

impl UpperExp for TimeSeries

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

Prints the Epoch in ET

impl UpperHex for TimeSeries

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

Prints the Epoch in TT

impl Eq for TimeSeries

impl StructuralPartialEq for TimeSeries