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13
.github/workflows/ci.yml vendored
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@ -34,14 +34,11 @@ jobs:
cargo run -p apsis-rs --features network --example integrate_network
cargo run -p apsis-rs --features ops --example integrate_ops
cargo run -p apsis-rs --features sim --example integrate_sim
- name: Build the benchmarks
# The benchmarks are not run in CI, because their timings are only
# meaningful on a quiet machine, but they must still compile so that
# they do not rot.
run: |
cargo build -p apsis-rs --features full --example bench
cargo build -p apsis-rs --features full --example bench_scale
cargo build -p apsis-rs --features full --example bench_parallel
- name: Build the benchmark
# The benchmark is not run in CI, because its timings are only
# meaningful on a quiet machine, but it must still compile so that it
# does not rot.
run: cargo build -p apsis-rs --features full --example bench
- name: Documentation
# Catches a doc link that no longer resolves, which is how a doc
# comment drifts away from the code it describes.

2
Cargo.lock generated
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@ -9,8 +9,6 @@ dependencies = [
"apsis-coverage",
"apsis-geodesy",
"apsis-math",
"apsis-sgp4",
"apsis-tle",
]
[[package]]

11
README.md
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@ -65,11 +65,6 @@ apsis-rs = { path = "...", features = ["orbit"] }
- toolchain：`stable`，`edition 2024`，`rust-version 1.85`
- 默认禁止任何第三方 crate，包括开发依赖与 `build.rs`
- 库代码不使用 `unwrap()` / `expect()` / `panic!` / `unsafe`
- 外部输入的失败一律走 `Result` / `Option`，不用 `unwrap` / `expect` 转换
- 允许对**已守卫的内部不变量**用 `expect("…")` 断言不可能的分支（如刚 `push`
后的 `last()`、前置 `is_none()` 已检查后的取值）。这些断言不处理不可信
输入，而是把"若此处为空则是编码错误"写成可读的失败信息；全库共 12 处，
逐处均有前置守卫。
- 公共 API 必须有文档注释，注释自包含
## 目录
@ -97,12 +92,6 @@ cargo run -p apsis-rs --features sim --example integrate_sim
# 热点路径基准（release 下运行）
cargo run --release -p apsis-rs --features full --example bench
# 规模扫描：输入规模递增，观察每单位工作量的增长趋势
cargo run --release -p apsis-rs --features full --example bench_scale
# 并行扫描：同一批工作量在 1/2/4/8/16 线程下的加速比与效率
cargo run --release -p apsis-rs --features full --example bench_parallel
```
## 许可

16
crates/apsis-rs/Cargo.toml
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@ -209,19 +209,3 @@ required-features = ["full"]
[[example]]
name = "dump_coverage"
required-features = ["network"]
[[example]]
name = "dump_kepler"
required-features = ["orbit"]
[[example]]
name = "dump_tle"
required-features = ["orbit"]
[[example]]
name = "bench_scale"
required-features = ["full"]
[[example]]
name = "bench_parallel"
required-features = ["full"]

421
crates/apsis-rs/examples/bench_parallel.rs
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@ -1,421 +0,0 @@
//! Parallel scale benchmark: how well the hot paths use the cores.
//!
//! The serial `bench_scale` example measures the cost of a path. This one
//! asks the next question: when the work is spread over the cores, how much
//! of the wall clock does that save, and where does the parallel version
//! stop being worth it.
//!
//! The paths chosen are the ones a real run parallelises, because each is
//! either trivially parallel or has a clear serial tail:
//!
//! - **constellation propagation** propagates every satellite independently,
//! so it is embarrassingly parallel and should scale nearly linearly.
//! - **access search** searches each track independently, likewise.
//! - **topology construction** decides each pair of satellites independently,
//! but folding the results into one graph is serial, so it is the case
//! that shows the cost of a serial tail.
//!
//! The timing compares the same total work done serially and across a range
//! of thread counts, and reports the speedup against both the serial time
//! and the ideal linear time. The two differ, and the difference is the
//! parallel overhead: thread spawn, work imbalance, and the serial tail.
//!
//! There is no warm-up, for the reason given in `bench_scale`: the first
//! call pays for whatever the path allocates on first use, and a caller
//! waits for that too. The serial time and the parallel time are both
//! measured cold, so the comparison is between two numbers the caller could
//! actually observe.
//!
//! Usage:
//!
//! ```text
//! cargo run --release -p apsis-rs --features full --example bench_parallel
//! ```
use apsis_access::{AccessFinder, OrbitSample};
use apsis_coord::Eci;
use apsis_coverage::GroundPoint;
use apsis_frames::EarthRotationAngle;
use apsis_geodesy::Geodetic;
use apsis_isl::mutual_visibility;
use apsis_math::Vec3;
use apsis_sgp4::{GravityModel, Satellite};
use apsis_tle::TwoLineElement;
use apsis_topology::Topology;
use std::hint::black_box;
use std::time::{Duration, Instant};
/// The element set used as the source of every propagated track.
const ISS: &str = concat!(
"1 25544U 98067A 08264.51782528 -.00002182 00000-0 -11606-4 0 2927\r\n",
"2 25544 51.6416 247.4627 0006703 130.5360 325.0288 15.72125391563537\r\n",
);
/// The body radius, in kilometers, taken from the shared constants.
const BODY_RADIUS_KM: f64 = apsis_core::constant::EARTH_EQUATORIAL_RADIUS;
/// The sample step, in seconds.
const TRACK_STEP_SECONDS: f64 = 60.0;
/// Runs a path once and returns how long it took.
fn measure<F, T>(path: F) -> Duration
where
F: FnOnce() -> T,
{
let start = Instant::now();
black_box(path());
start.elapsed()
}
/// Runs a path `repeats` times and returns the fastest duration.
///
/// The fastest of several runs is the least contaminated by whatever else
/// the machine is doing, and it is the figure that scales cleanly, because a
/// scheduling hiccup on one run cannot inflate the reference every later
/// number is divided by. The cold cost of the very first call is still
/// reported on its own, so nothing is hidden.
fn measure_best<F, T>(repeats: u32, path: F) -> Duration
where
F: Fn() -> T,
{
let mut best = Duration::MAX;
for _ in 0..repeats {
let elapsed = measure(&path);
if elapsed < best {
best = elapsed;
}
}
best
}
/// Prints one row.
///
/// The efficiency is the speedup divided by the thread count, so one means
/// the path used every core fully. A value well below one means the threads
/// were idle, which is what a serial tail looks like.
fn row(threads: usize, wall: Duration, work: Duration, cores: usize) {
let wall_ms = wall.as_secs_f64() * 1e3;
let work_ms = work.as_secs_f64() * 1e3;
let speedup = work_ms / wall_ms;
let efficiency = speedup / threads as f64;
println!(
"{threads:>6} {wall_ms:>11.3} {work_ms:>11.3} {speedup:>9.2} {efficiency:>9.2} {cores:>8}"
);
}
/// Returns a prepared satellite.
fn satellite() -> Satellite {
let element = TwoLineElement::parse(ISS).expect("the sample parses");
Satellite::from_element(&element, GravityModel::WGS72).expect("the orbit propagates")
}
/// The epoch of the sample element set, as a Modified Julian Date.
fn epoch_mjd() -> f64 {
let element = TwoLineElement::parse(ISS).expect("the sample parses");
element
.epoch
.mjd(apsis_time::TimeScale::Utc)
.expect("the epoch is inside the leap second table")
}
/// Returns a track of Earth-fixed samples for one satellite.
fn track(satellite: &Satellite, samples: usize, epoch_mjd: f64) -> Vec<OrbitSample> {
(0..samples)
.map(|index| {
let seconds = index as f64 * TRACK_STEP_SECONDS;
let state = satellite
.propagate_minutes(seconds / 60.0)
.expect("the track propagates");
let angle =
EarthRotationAngle::from_ut1_days(epoch_mjd - 51_544.5 + seconds / 86_400.0);
let fixed = Eci::new(state.position).to_ecef(angle).vector();
OrbitSample::new(seconds, fixed)
})
.collect()
}
/// Propagates a whole constellation over a day, serially.
///
/// The serial time is the reference every parallel number is divided by.
fn propagate_serial(satellite: &Satellite, satellites: usize, samples: usize) -> usize {
let mut count = 0_usize;
for _ in 0..satellites {
for index in 0..samples {
let seconds = index as f64 * TRACK_STEP_SECONDS;
let state = satellite
.propagate_minutes(seconds / 60.0)
.expect("the track propagates");
black_box(state.position);
count += 1;
}
}
count
}
/// Propagates a whole constellation over a day across `threads` threads.
///
/// Each thread takes a disjoint slice of the satellites, so the work splits
/// evenly and no two threads write the same state. The `scope` form of
/// spawning borrows the satellite rather than requiring it to outlive the
/// threads, which is what lets the reference be shared without cloning.
fn propagate_parallel(
satellite: &Satellite,
satellites: usize,
samples: usize,
threads: usize,
) -> usize {
let chunk = satellites.div_ceil(threads);
let total = std::sync::atomic::AtomicUsize::new(0);
std::thread::scope(|scope| {
for worker in 0..threads {
let first = worker * chunk;
if first >= satellites {
break;
}
let last = (first + chunk).min(satellites);
let total = &total;
scope.spawn(move || {
let mut count = 0_usize;
for _ in first..last {
for index in 0..samples {
let seconds = index as f64 * TRACK_STEP_SECONDS;
let state = satellite
.propagate_minutes(seconds / 60.0)
.expect("the track propagates");
black_box(state.position);
count += 1;
}
}
total.fetch_add(count, std::sync::atomic::Ordering::Relaxed);
});
}
});
total.load(std::sync::atomic::Ordering::Relaxed)
}
/// Searches access for every track, serially.
fn access_serial(tracks: &[Vec<OrbitSample>], finder: &AccessFinder) -> usize {
let mut passes = 0_usize;
for track in tracks {
passes += finder.find(track).expect("the track is valid").count();
}
passes
}
/// Searches access for every track across `threads` threads.
///
/// The tracks are read only and the finder is a copy, so each thread can
/// take a disjoint slice without synchronisation.
fn access_parallel(tracks: &[Vec<OrbitSample>], finder: &AccessFinder, threads: usize) -> usize {
let chunk = tracks.len().div_ceil(threads);
let total = std::sync::atomic::AtomicUsize::new(0);
std::thread::scope(|scope| {
for worker in 0..threads {
let first = worker * chunk;
if first >= tracks.len() {
break;
}
let last = (first + chunk).min(tracks.len());
let total = &total;
let finder = *finder;
scope.spawn(move || {
let mut passes = 0_usize;
for track in &tracks[first..last] {
passes += finder.find(track).expect("the track is valid").count();
}
total.fetch_add(passes, std::sync::atomic::Ordering::Relaxed);
});
}
});
total.load(std::sync::atomic::Ordering::Relaxed)
}
/// Builds a topology serially, deciding each pair and folding it in.
fn topology_serial(positions: &[Vec3], satellites: usize, range: f64) -> usize {
let mut topology = Topology::new(satellites);
for first in 0..satellites {
for second in 0..satellites {
if first != second
&& mutual_visibility(positions[first], positions[second], range)
.is_some_and(|visible| visible)
{
let _ = topology.add_edge(first, second, 1.0);
}
}
}
topology.edge_count()
}
/// Builds a topology across `threads` threads.
///
/// The geometry of each pair is independent, so each thread computes the
/// visible pairs in its own slice and returns them. Folding them into the
/// single graph is serial, which is the point of measuring this path: it
/// shows how much of the time the parallel part actually saves.
fn topology_parallel(positions: &[Vec3], satellites: usize, range: f64, threads: usize) -> usize {
let chunk = satellites.div_ceil(threads);
let results: Vec<Vec<(usize, usize)>> = std::thread::scope(|scope| {
let handles: Vec<_> = (0..threads)
.map(|worker| {
let first = worker * chunk;
let last = (first + chunk).min(satellites);
scope.spawn(move || {
let mut pairs = Vec::new();
for first in first..last {
for second in 0..satellites {
if first != second
&& mutual_visibility(positions[first], positions[second], range)
.is_some_and(|visible| visible)
{
pairs.push((first, second));
}
}
}
pairs
})
})
.collect();
handles
.into_iter()
.map(|handle| handle.join().expect("the worker did not panic"))
.collect()
});
// The serial tail: fold every visible pair into one graph.
let mut topology = Topology::new(satellites);
for pairs in &results {
for &(first, second) in pairs {
let _ = topology.add_edge(first, second, 1.0);
}
}
topology.edge_count()
}
/// Splits topology construction into its geometric and its folding phase.
///
/// Returns the time of the visibility test and the time of folding the
/// visible pairs into a graph, both in milliseconds. The first is
/// embarrassingly parallel, the second is a serial pass whose cost grows
/// with the square of the edge count because each insertion checks for a
/// duplicate by scanning the edges already stored.
fn topology_phase_split(positions: &[Vec3], satellites: usize, range: f64) -> (f64, f64) {
let start = Instant::now();
let mut pairs = Vec::new();
for first in 0..satellites {
for second in 0..satellites {
if first != second
&& mutual_visibility(positions[first], positions[second], range)
.is_some_and(|visible| visible)
{
pairs.push((first, second));
}
}
}
let visible_ms = start.elapsed().as_secs_f64() * 1e3;
let start = Instant::now();
let mut topology = Topology::new(satellites);
for &(first, second) in &pairs {
let _ = topology.add_edge(first, second, 1.0);
}
let fold_ms = start.elapsed().as_secs_f64() * 1e3;
(visible_ms, fold_ms)
}
fn main() {
let cores = std::thread::available_parallelism()
.map(|count| count.get())
.unwrap_or(1);
println!("ApsisRS parallel scale benchmark: release build, no external dependency");
println!("available parallelism: {cores} core(s)");
println!("no warm-up: the cold cost of the first call is reported, not discarded");
let satellite = satellite();
let epoch = epoch_mjd();
// The thread counts swept: one is the serial reference, then the powers
// of two up to the machine, then the machine's own count.
let mut thread_counts = vec![1_usize, 2, 4, 8];
if cores > 8 {
thread_counts.push(cores);
}
thread_counts.retain(|count| *count <= cores.max(2));
thread_counts.dedup();
// ---- One: constellation propagation over a day. ----------------------
{
let samples = 1_441_usize; // one day at a one minute step
for &satellites in &[550_usize, 1_000, 2_000] {
println!(
"\none: propagate {satellites} satellite(s) over 1 day at 60 s ({samples} samples each)"
);
let serial = measure_best(3, || propagate_serial(&satellite, satellites, samples));
let work = serial;
for &threads in &thread_counts {
let wall = measure_best(3, || {
propagate_parallel(&satellite, satellites, samples, threads)
});
row(threads, wall, work, cores);
}
}
}
// ---- Two: access search. ---------------------------------------------
{
for &satellites in &[64_usize, 256] {
let tracks: Vec<Vec<OrbitSample>> = (0..satellites)
.map(|_| track(&satellite, 120, epoch))
.collect();
let finder = AccessFinder {
station: GroundPoint::new(Geodetic::new(0.0, 0.0, 0.0), 10.0_f64.to_radians()),
sample_step_seconds: TRACK_STEP_SECONDS,
crossing_tolerance_seconds: 0.01,
};
println!("\ntwo: access search over {satellites} track(s), 2 h each");
let serial = measure_best(5, || access_serial(&tracks, &finder));
let work = serial;
for &threads in &thread_counts {
let wall = measure_best(5, || access_parallel(&tracks, &finder, threads));
row(threads, wall, work, cores);
}
}
}
// ---- Three: topology construction. ------------------------------------
{
for &satellites in &[120_usize, 300] {
let positions: Vec<Vec3> = (0..satellites)
.map(|index| {
let angle = index as f64 * 0.4;
Vec3::new(
(BODY_RADIUS_KM + 550.0) * angle.cos(),
(BODY_RADIUS_KM + 550.0) * angle.sin(),
index as f64 * 20.0,
)
})
.collect();
println!("\nthree: build topology over {satellites} satellite(s), 4500 km range");
let serial = measure_best(2, || topology_serial(&positions, satellites, 4_500.0));
// The split shows where the time actually goes: the geometric
// visibility test is parallel, but folding the visible pairs into
// the graph is a serial pass whose cost is superlinear in the
// edge count. Reporting the two separately is the difference
// between "parallelism did not help" and knowing why.
let (vis_ms, fold_ms) = topology_phase_split(&positions, satellites, 4_500.0);
println!(
" split: visibility {vis_ms:.3} ms (parallel), edge fold {fold_ms:.3} ms (serial tail)"
);
for &threads in &thread_counts {
let wall = measure_best(2, || {
topology_parallel(&positions, satellites, 4_500.0, threads)
});
row(threads, wall, serial, cores);
}
}
}
println!();
println!("speedup is serial time over wall time; efficiency is speedup over thread count");
println!("an efficiency near one means the cores were kept busy; a low value is a serial tail");
}

323
crates/apsis-rs/examples/bench_scale.rs
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@ -1,323 +0,0 @@
//! Scale benchmark for the paths a real workload hammers.
//!
//! The companion `bench` example measures the cost of a single call, which
//! answers whether an operation is fast. This one measures how that cost
//! grows with the size of the problem, which is the question that decides
//! whether a constellation sized run is feasible. It sweeps the input size
//! over powers of two and reports the time per unit of work, so a change in
//! the growth rate shows up even when the absolute numbers move with the
//! machine.
//!
//! The paths are the ones a planning cycle actually runs: propagating a
//! Walker constellation, searching access windows for one station over every
//! satellite, building the inter-satellite topology and routing through it,
//! and planning a task set with precedence.
//!
//! Everything is measured in release mode. There is deliberately no warm-up:
//! the first call pays for whatever the path allocates or caches on first
//! use, and a caller waits for that too, so the cold cost is reported on its
//! own column beside the steady state rather than being hidden behind a
//! discarded run.
//!
//! Usage:
//!
//! ```text
//! cargo run --release -p apsis-rs --features full --example bench_scale
//! ```
use apsis_access::{AccessFinder, OrbitSample};
use apsis_constellation::{Constellation, WalkerPattern};
use apsis_coord::Eci;
use apsis_coverage::GroundPoint;
use apsis_frames::EarthRotationAngle;
use apsis_geodesy::Geodetic;
use apsis_isl::mutual_visibility;
use apsis_math::Vec3;
use apsis_resource::{Resource, ResourceId, ResourceSet, Window};
use apsis_scheduler::Planner;
use apsis_sgp4::{GravityModel, Satellite};
use apsis_task::{PrecedenceGraph, Task, TaskId};
use apsis_tle::TwoLineElement;
use apsis_topology::Topology;
use std::hint::black_box;
use std::time::{Duration, Instant};
/// The element set used as the source of every propagated track.
const ISS: &str = concat!(
"1 25544U 98067A 08264.51782528 -.00002182 00000-0 -11606-4 0 2927\r\n",
"2 25544 51.6416 247.4627 0006703 130.5360 325.0288 15.72125391563537\r\n",
);
/// The body radius, in kilometers, taken from the shared constants.
const BODY_RADIUS_KM: f64 = apsis_core::constant::EARTH_EQUATORIAL_RADIUS;
/// The sample step of a propagated track, in seconds.
const TRACK_STEP_SECONDS: f64 = 60.0;
/// Runs a path a number of times and returns the duration of each call.
///
/// There is deliberately no warm-up. The first call pays for whatever the
/// path allocates or caches on first use, and hiding that behind a discarded
/// run would report a number the caller never actually waits for. The first
/// duration is therefore kept and reported separately as the cold cost, and
/// the rest are the steady state.
fn measure<F, T>(iterations: u32, mut path: F) -> Vec<Duration>
where
F: FnMut() -> T,
{
(0..iterations)
.map(|_| {
let start = Instant::now();
black_box(path());
start.elapsed()
})
.collect()
}
/// The mean of a set of durations, ignoring the first.
///
/// The first call is excluded because it carries the cold cost, which is
/// reported on its own column.
fn steady_mean(durations: &[Duration]) -> Duration {
if durations.len() <= 1 {
return durations.first().copied().unwrap_or_default();
}
let total: Duration = durations[1..].iter().sum();
total / (durations.len() - 1) as u32
}
/// Prints one row of the sweep table.
///
/// The columns are the cold cost of the first call, the mean of the rest, and
/// the steady cost per unit of work. A cold cost far above the steady mean
/// means the path allocates or caches something on first use.
fn row(label: &str, size: usize, per_unit_work: f64, durations: &[Duration]) {
let cold = durations.first().copied().unwrap_or_default();
let steady = steady_mean(durations);
let per_unit_ns = if per_unit_work > 0.0 {
steady.as_nanos() as f64 / per_unit_work
} else {
0.0
};
println!(
"{label:<26} {size:>6} {:>10.3} {:>10.3} {per_unit_ns:>12.1}",
cold.as_secs_f64() * 1e3,
steady.as_secs_f64() * 1e3,
);
}
/// The header of the sweep table.
fn header(title: &str) {
println!("\n{title}");
println!(
"{:<26} {:>6} {:>10} {:>10} {:>12}",
"path", "size", "cold ms", "steady ms", "steady ns/u"
);
}
/// Returns a prepared satellite.
fn satellite() -> Satellite {
let element = TwoLineElement::parse(ISS).expect("the sample parses");
Satellite::from_element(&element, GravityModel::WGS72).expect("the orbit propagates")
}
/// The epoch of the sample element set, as a Modified Julian Date.
fn epoch_mjd() -> f64 {
let element = TwoLineElement::parse(ISS).expect("the sample parses");
element
.epoch
.mjd(apsis_time::TimeScale::Utc)
.expect("the epoch is inside the leap second table")
}
/// Returns a track of Earth-fixed samples for one satellite.
fn track(satellite: &Satellite, samples: usize, epoch_mjd: f64) -> Vec<OrbitSample> {
(0..samples)
.map(|index| {
let seconds = index as f64 * TRACK_STEP_SECONDS;
let state = satellite
.propagate_minutes(seconds / 60.0)
.expect("the track propagates");
let angle =
EarthRotationAngle::from_ut1_days(epoch_mjd - 51_544.5 + seconds / 86_400.0);
let fixed = Eci::new(state.position).to_ecef(angle).vector();
OrbitSample::new(seconds, fixed)
})
.collect()
}
fn main() {
println!("ApsisRS scale benchmark: release build, no external dependency");
println!("growth is what matters; absolute times depend on the machine");
let satellite = satellite();
let epoch = epoch_mjd();
// ---- One: sample a constellation over one day. -----------------------
// The path a coverage run actually performs: build the constellation,
// then propagate every satellite in it once per sample across a day.
// The sample step is sixty seconds, so a day is 1441 samples.
{
header("one: build a constellation and sample every satellite over 1 day (60 s step)");
// Each entry is (planes, satellites per plane), chosen so the total
// divides evenly, which the pattern requires.
for &(planes, per_plane) in &[
(3_usize, 8_usize),
(6, 11),
(6, 40),
(11, 50),
(16, 63),
(24, 84),
] {
let satellites = planes * per_plane;
let pattern = WalkerPattern {
total_satellites: satellites,
planes,
phase_factor: 1,
inclination: 53.0_f64.to_radians(),
semi_major_axis: BODY_RADIUS_KM + 550.0,
};
// A day at a one minute step is 1441 samples per satellite.
let samples = 1_441_usize;
let iterations = if satellites <= 240 { 3 } else { 1 };
let tracker = &satellite;
let durations = measure(iterations, || {
let constellation =
Constellation::walker(pattern, epoch).expect("the pattern is consistent");
// Every satellite is propagated at its own orbital elements,
// so the deep space branch is exercised where the period is
// long, exactly as a real constellation would.
let mut propagated = 0_usize;
for orbit in constellation.satellites() {
for index in 0..samples {
let seconds = index as f64 * TRACK_STEP_SECONDS;
// The reference satellite stands in for the
// constellation members, whose elements differ only
// in their orbital plane; the propagation cost is the
// same, and using one keeps the loop free of a second
// initialisation that would be charged to the cold
// column.
let state = tracker
.propagate_minutes(seconds / 60.0)
.expect("the track propagates");
black_box(state.position);
let _ = orbit;
propagated += 1;
}
}
propagated
});
let work = (satellites * samples) as f64;
row("constellation day", satellites, work, &durations);
}
}
// ---- Two: access search over N tracks. ------------------------------
{
header("two: access search for one station over N tracks (2 h each)");
for &satellites in &[8_usize, 32, 64, 128] {
let tracks: Vec<Vec<OrbitSample>> = (0..satellites)
.map(|_| track(&satellite, 120, epoch))
.collect();
let finder = AccessFinder {
station: GroundPoint::new(Geodetic::new(0.0, 0.0, 0.0), 10.0_f64.to_radians()),
sample_step_seconds: TRACK_STEP_SECONDS,
crossing_tolerance_seconds: 0.01,
};
let iterations = if satellites <= 32 { 50 } else { 10 };
let durations = measure(iterations, || {
let mut passes = 0_usize;
for track in &tracks {
passes += finder.find(track).expect("the track is valid").count();
}
passes
});
row("access search", satellites, satellites as f64, &durations);
}
}
// ---- Three: topology and routing over N satellites. ------------------
{
header("three: build topology over N satellites and route once");
for &satellites in &[8_usize, 24, 64, 120, 300, 600] {
// Positions spread on a ring so a fixed link range keeps a
// bounded number of neighbours, as a real shell does.
let positions: Vec<Vec3> = (0..satellites)
.map(|index| {
let angle = index as f64 * 0.4;
Vec3::new(
(BODY_RADIUS_KM + 550.0) * angle.cos(),
(BODY_RADIUS_KM + 550.0) * angle.sin(),
index as f64 * 20.0,
)
})
.collect();
let iterations = if satellites <= 24 {
50
} else if satellites <= 120 {
10
} else {
2
};
let durations = measure(iterations, || {
let mut topology = Topology::new(satellites);
for first in 0..satellites {
for second in 0..satellites {
if first == second {
continue;
}
if mutual_visibility(positions[first], positions[second], 4_500.0)
.is_some_and(|visible| visible)
{
let _ = topology.add_edge(first, second, 1.0);
}
}
}
let _ = apsis_routing::shortest_path(&topology, 0, satellites - 1);
topology.edge_count()
});
row(
"topology + route",
satellites,
satellites as f64,
&durations,
);
}
}
// ---- Four: plan N tasks on one resource. -----------------------------
{
header("four: plan N tasks on one resource, with a 50 long chain");
for &tasks in &[60_usize, 200, 500, 1_000, 2_000] {
let mut resource = Resource::new(ResourceId::new(0), 1.0);
resource
.set_windows(&[Window::new(0.0, tasks as f64 * 200.0 + 10_000.0)])
.expect("the window is usable");
let resources = ResourceSet::from_resources(vec![resource]).expect("distinct");
let set: Vec<Task> = (0..tasks)
.map(|index| {
let start = (index % 50) as f64 * 200.0;
Task::new(TaskId::new(index), 60.0)
.with_window(start, start + 180.0)
.with_priority(1.0 + (index % 7) as f64)
.try_require(ResourceId::new(0), 1.0)
.expect("the resource is new")
})
.collect();
let mut graph = PrecedenceGraph::new();
for index in 1..tasks.min(50) {
let _ = graph.add(TaskId::new(index - 1), TaskId::new(index));
}
let iterations = if tasks <= 200 { 20 } else { 5 };
let planner = Planner::new();
let durations = measure(iterations, || {
let result = planner.schedule_with_precedence(&set, &resources, &graph);
result.schedule.len()
});
row("plan tasks", tasks, tasks as f64, &durations);
}
}
println!();
println!("ns per unit is the figure to watch: a rising trend means super-linear growth");
}

228
crates/apsis-rs/examples/dump_kepler.rs
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@ -1,228 +0,0 @@
//! Writes the two-body conversions this workspace computes.
//!
//! The output is CSV on standard output, with a header row. It is consumed
//! by `validation/python/orbit/check_kepler.py`, which recomputes the same
//! quantities from the closed-form expressions and compares. The Python
//! side is written from the geometry rather than from this code, so a
//! transcription error shows up as a disagreement.
//!
//! Two tables are written. The first converts Keplerian elements to a
//! Cartesian state over a spread of orbits, which is the path a planning
//! caller uses. The second converts the other way and records the recovered
//! elements, which exercises the vector algebra and the conic section
//! relations rather than a single formula.
//!
//! Usage:
//!
//! ```text
//! cargo run -p apsis-rs --features orbit --example dump_kepler \
//! > validation/data/expected/rust_kepler.csv
//! ```
use apsis_kepler::{GravityParameter, KeplerianElements};
/// The gravitational parameter used throughout, WGS 84.
const MU: GravityParameter = GravityParameter::WGS84;
/// One orbit to convert, chosen to span the shapes the model must handle.
struct Case {
/// A name for the case, so a failure in the report is readable.
name: &'static str,
/// Semi-major axis, in kilometers.
semi_major_axis: f64,
/// Eccentricity, dimensionless.
eccentricity: f64,
/// Inclination, in degrees.
inclination_deg: f64,
/// Right ascension of the ascending node, in degrees.
right_ascension_deg: f64,
/// Argument of perigee, in degrees.
argument_of_perigee_deg: f64,
/// True anomaly, in degrees.
true_anomaly_deg: f64,
}
impl Case {
/// Returns the case as elements in the units the crate uses.
fn elements(&self) -> KeplerianElements {
KeplerianElements {
semi_major_axis: self.semi_major_axis,
eccentricity: self.eccentricity,
inclination: self.inclination_deg.to_radians(),
right_ascension: self.right_ascension_deg.to_radians(),
argument_of_perigee: self.argument_of_perigee_deg.to_radians(),
true_anomaly: self.true_anomaly_deg.to_radians(),
}
}
}
/// The orbits converted.
///
/// The set spans a circular orbit, two mildly eccentric ones, a highly
/// eccentric one that exercises the near-parabolic branch of the anomaly
/// iteration, a retrograde one, and one inclined close to the polar limit.
const CASES: &[Case] = &[
Case {
name: "circular_equatorial",
semi_major_axis: 7_000.0,
eccentricity: 0.0,
inclination_deg: 0.0,
right_ascension_deg: 0.0,
argument_of_perigee_deg: 0.0,
true_anomaly_deg: 0.0,
},
Case {
name: "low_eccentricity",
semi_major_axis: 7_000.0,
eccentricity: 0.01,
inclination_deg: 51.6,
right_ascension_deg: 68.8,
argument_of_perigee_deg: 22.9,
true_anomaly_deg: 40.1,
},
Case {
name: "moderate_eccentricity",
semi_major_axis: 26_600.0,
eccentricity: 0.74,
inclination_deg: 5.7,
right_ascension_deg: 114.6,
argument_of_perigee_deg: 286.5,
true_anomaly_deg: 63.0,
},
Case {
name: "highly_eccentric",
semi_major_axis: 26_000.0,
eccentricity: 0.97,
inclination_deg: 28.5,
right_ascension_deg: 300.0,
argument_of_perigee_deg: 10.0,
true_anomaly_deg: 170.0,
},
Case {
name: "retrograde",
semi_major_axis: 8_000.0,
eccentricity: 0.2,
inclination_deg: 120.0,
right_ascension_deg: 45.0,
argument_of_perigee_deg: 200.0,
true_anomaly_deg: 300.0,
},
Case {
name: "near_polar",
semi_major_axis: 7_300.0,
eccentricity: 0.005,
inclination_deg: 88.0,
right_ascension_deg: 15.0,
argument_of_perigee_deg: 95.0,
true_anomaly_deg: 200.0,
},
];
/// The geostationary radius, used for a circular orbit at that altitude.
const GEO_RADIUS: f64 = 42_164.0;
fn main() {
// The first table: elements to a Cartesian state.
println!(
"case,semi_major_axis_km,eccentricity,inclination_rad,right_ascension_rad,\
argument_of_perigee_rad,true_anomaly_rad,x_km,y_km,z_km,vx_kms,vy_kms,vz_kms,\
period_seconds,energy_kms2"
);
for case in CASES {
let elements = case.elements();
let state = elements
.to_state(MU)
.expect("the case describes an elliptical orbit");
// The specific energy is reported as well, because it is the
// quantity the Python side uses to check the speed independently of
// the direction.
let radius = state.position.norm();
let energy = state.velocity.norm_squared() / 2.0 - MU.value() / radius;
println!(
"{},{},{},{},{},{},{},{},{},{},{},{},{},{},{}",
case.name,
case.semi_major_axis,
case.eccentricity,
case.inclination_deg.to_radians(),
case.right_ascension_deg.to_radians(),
case.argument_of_perigee_deg.to_radians(),
case.true_anomaly_deg.to_radians(),
state.position.x,
state.position.y,
state.position.z,
state.velocity.x,
state.velocity.y,
state.velocity.z,
elements.period(MU),
energy
);
}
// A circular orbit at the geostationary radius, whose speed has a closed
// form, is included in the same table under its own name.
let geo = KeplerianElements {
semi_major_axis: GEO_RADIUS,
eccentricity: 0.0,
inclination: 0.0,
right_ascension: 0.0,
argument_of_perigee: 0.0,
true_anomaly: 1.0,
};
let state = geo.to_state(MU).expect("geostationary circle is valid");
let radius = state.position.norm();
let energy = state.velocity.norm_squared() / 2.0 - MU.value() / radius;
println!(
"geostationary_circular,{},{},{},{},{},{},{},{},{},{},{},{},{},{}",
GEO_RADIUS,
0.0,
0.0,
0.0,
0.0,
1.0,
state.position.x,
state.position.y,
state.position.z,
state.velocity.x,
state.velocity.y,
state.velocity.z,
geo.period(MU),
energy
);
// The second table: a state back to elements, over a grid of true
// anomalies on one orbit. This exercises the vector algebra rather than
// the perifocal formulae the first table uses.
println!();
println!(
"true_anomaly_deg,recovered_semi_major_axis_km,recovered_eccentricity,\
recovered_inclination_rad,recovered_right_ascension_rad,\
recovered_argument_of_perigee_rad,recovered_true_anomaly_rad,state_radius_km"
);
let base = KeplerianElements {
semi_major_axis: 7_000.0,
eccentricity: 0.3,
inclination: 0.7,
right_ascension: 1.2,
argument_of_perigee: 0.4,
true_anomaly: 0.0,
};
for step in 0..36 {
let true_anomaly = f64::from(step) * 10.0_f64.to_radians();
let elements = base.with_true_anomaly(true_anomaly);
let state = elements
.to_state(MU)
.expect("the orbit is valid at every angle");
let recovered = KeplerianElements::from_state(&state, MU).expect("the state is elliptical");
println!(
"{},{},{},{},{},{},{},{}",
true_anomaly,
recovered.semi_major_axis,
recovered.eccentricity,
recovered.inclination,
recovered.right_ascension,
recovered.argument_of_perigee,
recovered.true_anomaly,
state.position.norm()
);
}
}

160
crates/apsis-rs/examples/dump_tle.rs
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@ -1,160 +0,0 @@
//! Writes the element fields this workspace parses from a two-line set.
//!
//! The output is CSV on standard output, with a header row. It is consumed
//! by `validation/python/orbit/check_tle.py`, which reparses the same sets
//! with an independent, column-indexed reader and compares every field, and
//! recomputes the modulo ten checksum of each line.
//!
//! The sets include the historical test cases distributed with the SGP4
//! reference implementation plus synthetic ones that exercise the corners of
//! the format: a circular orbit with an implied leading zero in the
//! eccentricity, a retrograde inclination, a negative drag term, and a century
//! rollover in the two digit epoch year.
//!
//! Usage:
//!
//! ```text
//! cargo run -p apsis-rs --features orbit --example dump_tle \
//! > validation/data/expected/rust_tle.csv
//! ```
use apsis_time::TimeScale;
use apsis_tle::{Classification, TwoLineElement, line_checksum};
/// One element set to parse, with a name for the report.
struct Sample {
/// A name for the sample, so a failure in the report is readable.
name: &'static str,
/// The two lines of the set, without a trailing carriage return.
lines: [&'static str; 2],
}
const fn sample(name: &'static str, first: &'static str, second: &'static str) -> Sample {
Sample {
name,
lines: [first, second],
}
}
/// The element sets parsed.
///
/// The first four are the historical test cases distributed with the SGP4
/// reference implementation. The rest are synthetic and cover the edges of
/// the format: an implied leading zero in the eccentricity, a retrograde
/// inclination, a negative first derivative of the mean motion, a century
/// rollover in the two digit epoch year, and a name line.
const SAMPLES: &[Sample] = &[
sample(
"vanguard_1",
"1 00005U 58002B 00179.78495062 .00000023 00000-0 28098-4 0 4753",
"2 00005 34.2682 348.7242 1859667 331.7664 19.3264 10.82419157413667",
),
sample(
"iss_2008",
"1 25544U 98067A 08264.51782528 -.00002182 00000-0 -11606-4 0 2927",
"2 25544 51.6416 247.4627 0006703 130.5360 325.0288 15.72125391563537",
),
sample(
"teme_94_deep",
"1 27651U 03004A 06185.99374200 .00000109 00000-0 19909-4 0 445",
"2 27651 7.1743 182.9443 7867251 269.0386 18.6601 1.03461646 9884",
),
sample(
"lrs_4_deep",
"1 09880U 77021A 06174.85710247 .00000090 00000-0 10000-3 0 7322",
"2 09880 64.1526 313.1296 6546925 103.4683 305.3980 2.00754276 13047",
),
sample(
"circular_implied_zero",
"1 20500U 90001A 90001.00000000 .00000000 00000-0 00000-0 0 00",
"2 20500 82.0000 100.0000 0000000 90.0000 90.0000 14.90000000 13",
),
sample(
"retrograde",
"1 20600U 90002B 12345.50000000 -.00001234 00000-0 12345-6 0 9991",
"2 20600 120.0000 200.0000 0010000 30.0000 330.0000 15.00000000 12341",
),
sample(
// A two digit year of 99 must expand to 1999, the last year of the
// twentieth century branch of the convention.
"two_digit_year_1999",
"1 10000U 99001A 99365.00000000 .00000000 00000-0 00000-0 0 05",
"2 10000 45.0000 10.0000 0001000 0.0000 0.0000 14.00000000 09",
),
sample(
"with_name_line",
"1 12345U 80001C 20001.00000000 .00010000 00000-0 00000-0 0 9998",
"2 12345 60.0000 30.0000 0002000 100.0000 200.0000 12.00000000 12344",
),
];
/// Returns the day of the year for a calendar date, as a fraction.
///
/// The epoch field of an element set stores the day of the year and its
/// fraction, so the year and month are combined back into a day of year
/// before the fraction of the day is added.
fn day_of_year_fraction(year: i32, month: u32, day: u32) -> f64 {
use apsis_time::days_in_month;
let mut total = 0_u32;
for current in 1..month {
total += days_in_month(year, current);
}
f64::from(total + day - 1)
}
fn main() {
println!(
"name,satellite_number,classification,international_designator,\
epoch_year,epoch_month,epoch_day,epoch_fraction_day,e_mean_motion_dot,\
e_mean_motion_double_dot,bstar,element_set_number,inclination_deg,\
right_ascension_deg,eccentricity,argument_of_perigee_deg,mean_anomaly_deg,\
mean_motion,revolution_number,line1_checksum,line2_checksum"
);
for entry in SAMPLES {
let text = format!("{}\r\n{}\r\n", entry.lines[0], entry.lines[1]);
let element = TwoLineElement::parse(&text)
.unwrap_or_else(|error| panic!("{} does not parse: {error}", entry.name));
let classification = match element.classification {
Classification::Unclassified => "U".to_string(),
Classification::Secret => "S".to_string(),
Classification::Other(letter) => letter.to_string(),
};
// The epoch is stored as a Modified Julian Date; the calendar form
// is written so the reader can compare the year and the day of year
// against the two digit year and fraction the line encodes.
let calendar = element
.epoch
.calendar(TimeScale::Utc)
.expect("the TLE epoch is inside the leap second table");
let fraction_day = day_of_year_fraction(calendar.year, calendar.month, calendar.day)
+ (f64::from(calendar.hour) * 3600.0
+ f64::from(calendar.minute) * 60.0
+ calendar.second)
/ 86_400.0;
let fields = [
entry.name.to_string(),
element.satellite_number.to_string(),
classification,
element.international_designator.clone(),
calendar.year.to_string(),
calendar.month.to_string(),
calendar.day.to_string(),
format!("{fraction_day:.12}"),
format!("{:.12e}", element.mean_motion_dot),
format!("{:.12e}", element.mean_motion_double_dot),
format!("{:.12e}", element.bstar),
element.element_set_number.to_string(),
format!("{:.12}", element.inclination),
format!("{:.12}", element.right_ascension),
format!("{:.12}", element.eccentricity),
format!("{:.12}", element.argument_of_perigee),
format!("{:.12}", element.mean_anomaly),
format!("{:.12}", element.mean_motion),
element.revolution_number.to_string(),
line_checksum(entry.lines[0]).to_string(),
line_checksum(entry.lines[1]).to_string(),
];
println!("{}", fields.join(","));
}
}

1
crates/foundation/apsis-math/src/lib.rs
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@ -29,7 +29,6 @@
#![deny(missing_docs)]
mod mat3;
pub mod parallel;
mod quat;
mod vec3;

150
crates/foundation/apsis-math/src/parallel.rs
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@ -1,150 +0,0 @@
//! Scoped parallelism built on the standard library alone.
//!
//! The workspace forbids third party crates, so a threading pool would have to
//! be written here. It is not: the operations in this workspace that benefit
//! from several cores are all embarrassingly parallel loops over independent
//! items, and the standard library's scoped threads express those directly.
//! `std::thread::scope` borrows its data, so a caller can share a slice or a
//! reader without an atomic reference count, and joins every thread before returning, so no
//! result escapes the scope still being written.
//!
//! The entry point is [`for_each_index`], which splits a range into one chunk
//! per thread and runs a closure over each element. The closure must be
//! callable from another thread, so anything it captures has to be `Sync`;
//! in practice that means reading shared input and writing to a disjoint
//! slot of the output, which is the shape every parallel loop here has.
//!
//! Because there is no pool, the cost of a parallel call includes starting
//! the threads. That is worth paying only when each thread has real work, so
//! [`thread_count`] reports what the machine offers and the callers in this
//! workspace use it to skip the parallel path for small inputs.
//!
//! ```
//! use apsis_math::parallel::map_index;
//!
//! // Square every element, one value per index.
//! let input: Vec<f64> = (0..1000).map(f64::from).collect();
//! let output = map_index(input.len(), |index| input[index] * input[index]);
//! assert_eq!(output[10], 100.0);
//! ```
use core::hint;
/// The number of threads to use for a piece of work.
///
/// This is the machine's parallelism as reported by the standard library, at
/// least one. It is the number the callers use to decide whether a parallel
/// run is worth starting.
pub fn thread_count() -> usize {
std::thread::available_parallelism()
.map(|count| count.get())
.unwrap_or(1)
}
/// The number of threads that should run a loop over `len` items.
///
/// A loop shorter than the thread count would leave most threads with nothing
/// to do while still paying to start them, so this returns one thread until
/// there is enough work for a second. The threshold is a per item cost of
/// roughly a microsecond, below which starting a thread cannot pay for
/// itself.
pub fn threads_for(len: usize) -> usize {
const ITEMS_PER_THREAD: usize = 1_024;
thread_count().min(len.div_ceil(ITEMS_PER_THREAD)).max(1)
}
/// Runs a closure once for each index of a range, spread over several threads.
///
/// The range is split into one contiguous chunk per thread and each thread
/// runs the closure for the indices in its chunk. The closure may be called
/// from any thread, so it must be `Send` and `Sync`; anything it captures is
/// shared rather than copied. The call returns only after every thread has
/// finished, so the data the closure wrote is safe to read afterwards.
///
/// The closure is handed the index rather than the element, which keeps the
/// signature independent of the collection: the caller reads the input and
/// writes the output itself, and the two never overlap.
///
/// # Panics
///
/// If the closure panics, the panic is resumed on the calling thread after
/// the other threads have been joined, so a failure surfaces at the call
/// rather than in a detached thread.
pub fn for_each_index<F>(len: usize, operation: F)
where
F: Fn(usize) + Sync,
{
let threads = threads_for(len);
if threads <= 1 {
// A single thread would spawn and join one thread to do exactly what
// this loop does, so it runs directly.
for index in 0..len {
operation(index);
}
return;
}
let chunk = len.div_ceil(threads);
std::thread::scope(|scope| {
for worker in 0..threads {
let first = worker * chunk;
if first >= len {
break;
}
let last = hint::black_box((first + chunk).min(len));
let operation = &operation;
scope.spawn(move || {
for index in first..last {
operation(index);
}
});
}
});
}
/// Collects one value for each index of a range, spread over several threads.
///
/// This is [`for_each_index`] for the common case where the result of the
/// work is a value rather than a write into a shared array. The output is
/// returned in index order regardless of which thread produced which element,
/// so it does not depend on the scheduling.
///
/// The closure is handed the index and returns the value for that index. As
/// with [`for_each_index`], it may run on any thread, so captured data must be
/// `Sync`.
pub fn map_index<T, F>(len: usize, operation: F) -> Vec<T>
where
T: Send,
F: Fn(usize) -> T + Sync,
{
let threads = threads_for(len);
if threads <= 1 {
return (0..len).map(operation).collect();
}
let chunk = len.div_ceil(threads);
// Each thread writes a contiguous run of the output, so the buffer is
// split into disjoint mutable slices up front and no slot is written
// twice. `Vec<Option<T>>` is filled in parallel and unwrapped after the
// scope, which is where the values are moved into their final order.
let mut slots: Vec<Option<T>> = (0..len).map(|_| None).collect();
let operation = &operation;
std::thread::scope(|scope| {
let mut rest = &mut slots[..];
let mut offset = 0;
while offset < len {
let take = chunk.min(len - offset);
let (this, tail) = core::mem::take(&mut rest).split_at_mut(take);
let base = offset;
scope.spawn(move || {
for (index, slot) in this.iter_mut().enumerate() {
*slot = Some(operation(base + index));
}
});
rest = tail;
offset += take;
}
});
slots
.into_iter()
.map(|slot| slot.expect("every index was assigned"))
.collect()
}

136
crates/foundation/apsis-math/tests/parallel.rs
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@ -1,136 +0,0 @@
//! Tests for the scoped parallelism helpers.
//!
//! The central property is that a parallel run and a serial run produce the
//! same values, because the whole point of the helpers is to be a drop-in for
//! the sequential loop they replace. Each test therefore compares against the
//! sequential answer rather than against a constant, and forces both the
//! single and multi thread paths by choosing lengths that fall on each side
//! of the threshold.
use std::sync::atomic::Ordering;
use apsis_math::parallel::{for_each_index, map_index, thread_count, threads_for};
#[test]
fn the_thread_count_is_at_least_one() {
assert!(thread_count() >= 1);
}
#[test]
fn small_work_uses_a_single_thread() {
// Below the per thread threshold there is nothing to gain from starting
// a thread, so the helper says so.
assert_eq!(threads_for(0), 1);
assert_eq!(threads_for(1), 1);
assert_eq!(threads_for(64), 1);
}
#[test]
fn large_work_uses_more_than_one_thread() {
let count = thread_count();
if count > 1 {
assert!(threads_for(1_000_000) > 1);
// Never more threads than there are items.
assert!(threads_for(10) <= 10);
}
}
#[test]
fn every_index_is_visited_exactly_once() {
use std::sync::atomic::AtomicUsize;
for &len in &[0_usize, 1, 7, 1_000, 5_000, 100_000] {
let visits = (0..len).map(|_| AtomicUsize::new(0)).collect::<Vec<_>>();
for_each_index(len, |index| {
visits[index].fetch_add(1, Ordering::Relaxed);
});
assert!(
visits
.iter()
.all(|count| count.load(Ordering::Relaxed) == 1),
"length {len} visited an index more than once"
);
}
}
#[test]
fn the_parallel_result_matches_the_sequential_one() {
for &len in &[0_usize, 1, 1_000, 50_000, 300_000] {
let sequential: Vec<f64> = (0..len)
.map(|index| (index as f64).sin() * 1_000.0)
.collect();
let parallel = map_index(len, |index| (index as f64).sin() * 1_000.0);
assert_eq!(parallel, sequential, "length {len} differs");
}
}
#[test]
fn the_output_is_in_index_order() {
// Threads finish out of order, so this checks that the helper restores
// index order rather than completion order.
let len = 200_000;
let values = map_index(len, |index| index);
for (position, value) in values.iter().enumerate() {
assert_eq!(*value, position);
}
}
#[test]
fn a_closure_may_capture_shared_input() {
// The shape every caller in the workspace uses: read a shared slice and
// produce one value per element. `map_index` owns the output buffer, so
// no shared mutable state is needed.
let input: Vec<f64> = (0..100_000).map(f64::from).collect();
let output = map_index(input.len(), |index| input[index] * input[index]);
for index in [0, 1, 999, 50_000, 99_999] {
assert_eq!(output[index], input[index] * input[index]);
}
}
#[test]
fn a_closure_may_accumulate_atomically() {
// Writing to a shared counter needs atomics; this checks the helper
// tolerates that, since summing a large range is a common pattern.
use std::sync::atomic::AtomicU64;
let total = AtomicU64::new(0);
let len = 200_000_u64;
for_each_index(len as usize, |index| {
total.fetch_add(index as u64, Ordering::Relaxed);
});
let expected: u64 = (0..len).sum();
assert_eq!(total.load(Ordering::Relaxed), expected);
}
#[test]
fn an_empty_range_does_nothing() {
let empty: Vec<f64> = map_index(0, |_| 1.0);
assert!(empty.is_empty());
// The index form accepts an empty range without spawning anything.
for_each_index(0, |_| unreachable!("an empty range runs no closure"));
}
#[test]
fn a_range_that_does_not_divide_evenly_covers_everything() {
// A length that is not a multiple of the thread count is where an
// off by one in the chunking would drop the tail.
use std::sync::atomic::AtomicUsize;
for &len in &[1_001_usize, 4_097, 65_537, 100_003] {
let marks = (0..len).map(|_| AtomicUsize::new(0)).collect::<Vec<_>>();
for_each_index(len, |index| {
marks[index].store(1, Ordering::Relaxed);
});
assert!(
marks.iter().all(|mark| mark.load(Ordering::Relaxed) == 1),
"length {len} missed an index"
);
}
}
#[test]
fn values_of_a_non_copy_type_survive_the_collect() {
// A string is not `Copy`, so this exercises the unwrap-and-move path that
// the parallel branch uses.
let values = map_index(10_000, |index| format!("item-{index}"));
assert_eq!(values[0], "item-0");
assert_eq!(values[9_999], "item-9999");
assert_eq!(values.len(), 10_000);
}

7
crates/network/apsis-access/Cargo.toml
View File

@ -13,11 +13,4 @@ workspace = true
[dependencies]
apsis-math.workspace = true
apsis-geodesy.workspace = true
apsis-tle.workspace = true
apsis-coverage.workspace = true
[dev-dependencies]
apsis-sgp4.workspace = true
apsis-coverage.workspace = true
apsis-geodesy.workspace = true
apsis-tle.workspace = true

38
crates/network/apsis-access/src/batch.rs
View File

@ -1,38 +0,0 @@
//! Searching access windows for many tracks, optionally across several
//! threads.
//!
//! A ground station sees a whole constellation, so the access schedule is
//! the search of one track per satellite. Each track is independent of the
//! others, which makes the search the natural place to use several cores: the
//! work is proportional to the number of satellites, and a shell of a few
//! hundred gives enough of it to be worth the threads.
//!
//! The parallel entry point returns exactly what the sequential one does, in
//! the same order, so a caller can switch between them without changing what
//! it computes.
use crate::{AccessError, AccessFinder, OrbitSample, PassSummary};
use apsis_math::parallel::map_index;
/// Searches access for many tracks, in order.
///
/// The sequential form, provided for comparison and for small sets where
/// starting a thread would cost more than the search.
pub fn find_all(
finder: &AccessFinder,
tracks: &[Vec<OrbitSample>],
) -> Vec<Result<PassSummary, AccessError>> {
tracks.iter().map(|track| finder.find(track)).collect()
}
/// Searches access for many tracks, across several threads.
///
/// The result matches [`find_all`] element for element and in the same order.
/// A track that cannot be searched yields its error in the same position the
/// sequential form would put it, so one bad track does not hide the rest.
pub fn find_all_parallel(
finder: &AccessFinder,
tracks: &[Vec<OrbitSample>],
) -> Vec<Result<PassSummary, AccessError>> {
map_index(tracks.len(), |index| finder.find(&tracks[index]))
}

2
crates/network/apsis-access/src/lib.rs
View File

@ -34,12 +34,10 @@
#![forbid(unsafe_code)]
#![deny(missing_docs)]
mod batch;
mod error;
mod finder;
mod pass;
pub use batch::{find_all, find_all_parallel};
pub use error::{AccessError, AccessErrorKind};
pub use finder::{AccessFinder, OrbitSample};
pub use pass::{Pass, PassSummary};

119
crates/network/apsis-access/tests/batch.rs
View File

@ -1,119 +0,0 @@
//! Tests for the batch access search.
//!
//! The parallel form must produce the same pass summaries, in the same
//! order, as the sequential one. Every test compares the two rather than
//! against a constant, so an ordering or content difference is caught.
use apsis_access::{AccessFinder, OrbitSample, find_all, find_all_parallel};
use apsis_coverage::GroundPoint;
use apsis_geodesy::Geodetic;
use apsis_math::Vec3;
use apsis_sgp4::{GravityModel, Satellite};
use apsis_tle::TwoLineElement;
const SAMPLE: &str = concat!(
"1 25544U 98067A 08264.51782528 -.00002182 00000-0 -11606-4 0 2927\r\n",
"2 25544 51.6416 247.4627 0006703 130.5360 325.0288 15.72125391563537\r\n",
);
/// Returns a finder for a station on the equator.
fn finder() -> AccessFinder {
AccessFinder {
station: GroundPoint::new(Geodetic::new(0.0, 0.0, 0.0), 10.0_f64.to_radians()),
sample_step_seconds: 60.0,
crossing_tolerance_seconds: 0.01,
}
}
/// Returns a track of Earth-fixed samples for one satellite.
///
/// The rotation is folded into a simple sweep so the track is a plausible
/// ground track; the exact geometry is not what this test is about, only
/// that the batch search reproduces the sequential one.
fn track(satellite: &Satellite, samples: usize) -> Vec<OrbitSample> {
(0..samples)
.map(|index| {
let seconds = index as f64 * 60.0;
// The propagated radius sets the shell the synthetic longitude
// sweep runs on, so the track is at a realistic altitude.
let radius = satellite
.propagate_minutes(seconds / 60.0)
.expect("the track propagates")
.position
.norm();
// A slow sweep in longitude stands in for the rotation into the
// Earth-fixed frame; the exact geometry is not what this test is
// about, only that the batch search reproduces the sequential one.
let angle = seconds / 4_000.0;
let position = Vec3::new(radius * angle.cos(), radius * angle.sin(), radius * 0.3);
OrbitSample::new(seconds, position)
})
.collect()
}
fn satellite() -> Satellite {
let element = TwoLineElement::parse(SAMPLE).expect("the sample parses");
Satellite::from_element(&element, GravityModel::WGS72).expect("the orbit propagates")
}
#[test]
fn a_single_track_matches_the_sequential_form() {
let finder = finder();
let tracks = vec![track(&satellite(), 120)];
assert_eq!(
find_all_parallel(&finder, &tracks),
find_all(&finder, &tracks)
);
}
#[test]
fn a_shell_of_tracks_matches_the_sequential_form() {
// Long enough that the parallel path takes the multi thread branch.
let finder = finder();
let satellite = satellite();
let tracks: Vec<Vec<OrbitSample>> = (0..200).map(|_| track(&satellite, 120)).collect();
assert_eq!(
find_all_parallel(&finder, &tracks),
find_all(&finder, &tracks)
);
}
#[test]
fn an_empty_set_of_tracks_is_empty() {
let finder = finder();
assert!(find_all_parallel(&finder, &[]).is_empty());
}
#[test]
fn a_bad_track_does_not_hide_the_others() {
// A track that is too short or out of order yields an error in both
// forms, at the same position, and the good tracks are still searched.
let finder = finder();
let satellite = satellite();
let mut tracks = vec![track(&satellite, 120), vec![], track(&satellite, 120)];
// The empty track is a degenerate case; search it as given.
let sequential = find_all(&finder, &tracks);
let parallel = find_all_parallel(&finder, &tracks);
assert_eq!(parallel, sequential);
tracks.clear();
assert!(tracks.is_empty());
}
#[test]
fn the_result_is_in_input_order() {
// Three tracks with different lengths, so each summary differs and the
// ordering is observable.
let finder = finder();
let satellite = satellite();
let tracks = vec![
track(&satellite, 40),
track(&satellite, 120),
track(&satellite, 80),
];
let parallel = find_all_parallel(&finder, &tracks);
assert_eq!(parallel.len(), 3);
for (index, summary) in parallel.iter().enumerate() {
let expected = finder.find(&tracks[index]).expect("the track is valid");
assert_eq!(summary.as_ref().expect("the track is valid"), &expected);
}
}

60
crates/network/apsis-isl/src/batch.rs
View File

@ -1,60 +0,0 @@
//! Deciding many links at once, optionally across several threads.
//!
//! Building a constellation's topology asks the same question for every pair
//! of satellites, which is a quadratic number of independent geometry tests.
//! Each one is small, but there are so many that the loop is the dominant
//! cost of building the graph, and the tests do not depend on each other, so
//! they are the natural place to use several cores.
//!
//! The parallel entry point returns exactly what the sequential one does, in
//! the same order, so a caller can switch between them without changing the
//! graph it builds.
use crate::geometry::mutual_visibility;
use apsis_math::{Vec3, parallel::map_index};
/// Returns the visibility of every ordered pair of positions, in order.
///
/// The result is row major: the entry at `row * positions.len() + column` is
/// the visibility from `positions[row]` to `positions[column]`. A satellite is
/// always visible to itself, which is the caller's cue to skip the diagonal.
///
/// A pair whose test is undefined, because a position is not finite or the
/// body radius is not positive, yields `false`.
pub fn visibility_matrix(positions: &[Vec3], body_radius: f64) -> Vec<bool> {
let len = positions.len();
let mut matrix = vec![false; len * len];
for (row, first) in positions.iter().enumerate() {
for (column, second) in positions.iter().enumerate() {
matrix[row * len + column] =
mutual_visibility(*first, *second, body_radius).unwrap_or(false);
}
}
matrix
}
/// Returns the visibility of every ordered pair of positions, across several
/// threads.
///
/// The result matches [`visibility_matrix`] element for element and in the
/// same order. The pairs are independent, so splitting the flat index space
/// across threads needs no coordination and produces the same matrix however
/// the work is divided.
///
/// The gain from threading is modest here and shrinks as the matrix shrinks.
/// A single visibility test is a few nanoseconds, so the cost of starting the
/// threads is only repaid by a large matrix: on a sixteen core machine a few
/// hundred satellites already gain, while a few dozen lose. The sequential
/// form is the better choice for a small shell, and this one exists for the
/// large ones where the quadratic sweep dominates.
pub fn visibility_matrix_parallel(positions: &[Vec3], body_radius: f64) -> Vec<bool> {
let len = positions.len();
// The pairs are independent, so splitting the flat index space across
// threads needs no coordination. `map_index` owns the output buffer,
// which is what lets the threads write disjoint slots of one allocation.
map_index(len * len, |index| {
let row = index / len;
let column = index - row * len;
mutual_visibility(positions[row], positions[column], body_radius).unwrap_or(false)
})
}

2
crates/network/apsis-isl/src/lib.rs
View File

@ -36,11 +36,9 @@
#![forbid(unsafe_code)]
#![deny(missing_docs)]
mod batch;
mod geometry;
mod link;
pub use batch::{visibility_matrix, visibility_matrix_parallel};
pub use geometry::{closest_approach_to_centre, link_geometry, mutual_visibility, sun_blocks_link};
pub use link::{LinkGeometry, LinkState};

123
crates/network/apsis-isl/tests/batch.rs
View File

@ -1,123 +0,0 @@
//! Tests for the batch visibility matrix.
//!
//! The parallel form must produce exactly the matrix the sequential form
//! does, in the same row major order. Every test compares the two rather than
//! against a constant, so a content or ordering difference is caught.
use apsis_isl::{visibility_matrix, visibility_matrix_parallel};
use apsis_math::Vec3;
/// The body radius used throughout, in kilometers.
const RADIUS: f64 = 6_378.137;
/// Returns a set of positions spread around a shell.
fn shell(count: usize) -> Vec<Vec3> {
(0..count)
.map(|index| {
let angle = index as f64 * 0.3;
let radius = 6_900.0;
Vec3::new(
radius * angle.cos(),
radius * angle.sin(),
radius * 0.2 * (index as f64 * 0.1).sin(),
)
})
.collect()
}
#[test]
fn a_single_position_gives_a_one_by_one_matrix() {
let positions = shell(1);
assert_eq!(
visibility_matrix_parallel(&positions, RADIUS),
visibility_matrix(&positions, RADIUS)
);
// A satellite is visible to itself over a body radius below its own.
assert!(visibility_matrix(&positions, RADIUS)[0]);
}
#[test]
fn a_shell_matches_the_sequential_matrix() {
// Long enough that the parallel path takes the multi thread branch.
for count in [2_usize, 16, 64, 200] {
let positions = shell(count);
assert_eq!(
visibility_matrix_parallel(&positions, RADIUS),
visibility_matrix(&positions, RADIUS),
"count {count} differs"
);
}
}
#[test]
fn an_empty_set_gives_an_empty_matrix() {
assert!(visibility_matrix_parallel(&[], RADIUS).is_empty());
}
#[test]
fn the_matrix_is_row_major_and_symmetric() {
// Row major: the entry at row * len + column is the visibility from the
// row satellite to the column one. For a spherical body the geometry is
// symmetric, so the matrix is symmetric, which is what a wrong ordering
// of a row major layout would break.
let positions = shell(12);
let matrix = visibility_matrix_parallel(&positions, RADIUS);
let len = positions.len();
assert_eq!(matrix.len(), len * len);
for row in 0..len {
for column in 0..len {
assert_eq!(
matrix[row * len + column],
matrix[column * len + row],
"not symmetric at ({row}, {column})"
);
}
}
}
#[test]
fn the_matrix_matches_the_scalar_test() {
// Each entry must agree with calling the geometry directly, so a wrong
// pairing of row and column is caught even when the matrix is symmetric.
let positions = shell(10);
let matrix = visibility_matrix_parallel(&positions, RADIUS);
let len = positions.len();
for row in 0..len {
for column in 0..len {
let expected = apsis_isl::mutual_visibility(positions[row], positions[column], RADIUS)
.unwrap_or(false);
assert_eq!(matrix[row * len + column], expected, "at ({row}, {column})");
}
}
}
#[test]
fn an_unusable_body_radius_yields_all_false() {
// A non positive radius makes every test undefined, which the sequential
// form reports as false; the parallel form must do the same.
let positions = shell(8);
for radius in [0.0, -1.0] {
let matrix = visibility_matrix_parallel(&positions, radius);
assert!(matrix.iter().all(|&visible| !visible));
}
}
#[test]
fn a_position_that_is_not_finite_yields_false_in_its_row() {
// A satellite with a non finite position cannot see anything. The rest
// of the matrix is unaffected.
let mut positions = shell(6);
positions[2] = Vec3::new(f64::NAN, 0.0, 0.0);
let matrix = visibility_matrix_parallel(&positions, RADIUS);
let len = positions.len();
for column in 0..len {
assert!(
!matrix[2 * len + column],
"row 2 column {column} should be false"
);
assert!(
!matrix[column * len + 2],
"row {column} column 2 should be false"
);
}
}

74
crates/network/apsis-topology/src/graph.rs
View File

@ -48,30 +48,14 @@ impl Edge {
pub struct Topology {
node_count: usize,
edges: Vec<Edge>,
/// The positions in `edges` of the edges leaving each node.
///
/// The index is what makes membership a constant time test. Without it,
/// asking whether an edge already exists scans the whole edge list, and
/// building a graph of `E` edges costs `O(E^2)`, which turns the
/// visibility sweep of a constellation, quadratic in the number of
/// satellites, into cubic work. The index holds positions rather than
/// destinations so that `remove_edge`, which invalidates positions, can
/// repair it in one pass.
outgoing: Vec<Vec<usize>>,
}
impl Topology {
/// Creates an empty topology with the given number of nodes.
///
/// This is not a `const fn` because it sizes the adjacency index, which
/// allocates.
pub fn new(node_count: usize) -> Self {
let mut outgoing = Vec::new();
outgoing.resize_with(node_count, Vec::new);
pub const fn new(node_count: usize) -> Self {
Self {
node_count,
edges: Vec::new(),
outgoing,
}
}
@ -114,7 +98,6 @@ impl Topology {
return Err(TopologyError::new(TopologyErrorKind::DuplicateEdge)
.with_detail(format!("edge {from} to {to}")));
}
self.outgoing[from].push(self.edges.len());
self.edges.push(Edge::new(from, to, cost));
Ok(())
}
@ -133,7 +116,8 @@ impl Topology {
self.add_edge(first, second, cost)?;
if let Err(error) = self.add_edge(second, first, cost) {
// Remove the first direction so the topology is unchanged.
self.remove_edge_unchecked(first, second);
self.edges
.retain(|edge| !(edge.from == first && edge.to == second));
return Err(error);
}
Ok(())
@ -141,72 +125,50 @@ impl Topology {
/// Returns `true` when an edge exists from one node to another.
pub fn has_edge(&self, from: usize, to: usize) -> bool {
self.outgoing.get(from).is_some_and(|positions| {
positions
self.edges
.iter()
.any(|&position| self.edges[position].to == to)
})
.any(|edge| edge.from == from && edge.to == to)
}
/// Returns the cost of the edge between two nodes.
///
/// Returns `None` when there is no such edge.
pub fn cost(&self, from: usize, to: usize) -> Option<f64> {
let positions = self.outgoing.get(from)?;
positions
self.edges
.iter()
.find(|&&position| self.edges[position].to == to)
.map(|&position| self.edges[position].cost)
.find(|edge| edge.from == from && edge.to == to)
.map(|edge| edge.cost)
}
/// Removes the edge between two nodes.
///
/// Returns an error when there is no such edge.
pub fn remove_edge(&mut self, from: usize, to: usize) -> Result<(), TopologyError> {
if !self.has_edge(from, to) {
let before = self.edges.len();
self.edges
.retain(|edge| !(edge.from == from && edge.to == to));
if self.edges.len() == before {
return Err(TopologyError::new(TopologyErrorKind::NoSuchEdge)
.with_detail(format!("edge {from} to {to}")));
}
self.remove_edge_unchecked(from, to);
Ok(())
}
/// Removes an edge the caller has already established exists.
///
/// Removing an edge renumbers every position after it, so the index is
/// rebuilt from the surviving edges in one pass. Removal is rarer than
/// insertion, so paying for a rebuild here is cheaper than keeping the
/// index correct incrementally.
fn remove_edge_unchecked(&mut self, from: usize, to: usize) {
self.edges
.retain(|edge| !(edge.from == from && edge.to == to));
self.rebuild_index();
}
/// Rebuilds the adjacency index from the current edge list.
fn rebuild_index(&mut self) {
for positions in &mut self.outgoing {
positions.clear();
}
for (position, edge) in self.edges.iter().enumerate() {
self.outgoing[edge.from].push(position);
}
}
/// Returns the indices of the nodes reachable from a node in one hop.
///
/// The result is in the order the edges were added, so it is
/// deterministic for a given construction sequence.
pub fn neighbours(&self, node: usize) -> Vec<usize> {
self.outgoing
.get(node)
.map(|positions| positions.iter().map(|&p| self.edges[p].to).collect())
.unwrap_or_default()
self.edges
.iter()
.filter(|edge| edge.from == node)
.map(|edge| edge.to)
.collect()
}
/// Returns the number of edges leaving a node.
pub fn out_degree(&self, node: usize) -> usize {
self.outgoing.get(node).map_or(0, Vec::len)
self.edges.iter().filter(|edge| edge.from == node).count()
}
/// Returns the number of edges arriving at a node.

92
crates/ops/apsis-scheduler/src/greedy.rs
View File

@ -83,6 +83,68 @@ pub fn resources_free_at(
.collect()
}
/// Returns the earliest time at which a task can be placed.
///
/// The earliest feasible start is always one of a small set of candidate
/// times: the start of the task's window, the start of an availability
/// window of one of its resources, or the end of a placement already on one
/// of those resources. Feasibility cannot change at any other instant,
/// because the demand on every resource is constant between those events and
/// the availability is constant between them too. Enumerating that set and
/// taking the smallest feasible member therefore finds the true earliest
/// start.
///
/// Returns `None` when the task cannot be placed anywhere in its window.
pub fn earliest_feasible_start(
task: &Task,
tasks: &[Task],
schedule: &Schedule,
resources: &ResourceSet,
) -> Option<f64> {
if !task.is_valid() || !resources_have_capacity(task, resources) {
return None;
}
if task.requirements.is_empty() {
// A task with no requirements can start as soon as its window opens.
return Some(task.earliest_start);
}
// The candidate times, collected from every event that can change
// feasibility.
let mut candidates: Vec<f64> = vec![task.earliest_start];
for requirement in &task.requirements {
let resource = resources.get(requirement.resource)?;
for window in resource.windows() {
candidates.push(window.start());
}
for placement in schedule.placements() {
let overlaps = tasks
.iter()
.find(|other| other.id == placement.task)
.is_some_and(|other| other.demand_for(resource.id).is_some());
if overlaps {
candidates.push(placement.end());
}
}
}
// Only times at or after the window opens, and no later than the last
// start that could still fit, are worth testing.
let latest_start = task.latest_end - task.duration;
candidates
.retain(|time| time.is_finite() && *time >= task.earliest_start && *time <= latest_start);
candidates.sort_by(|first, second| {
first
.partial_cmp(second)
.unwrap_or(core::cmp::Ordering::Equal)
});
candidates.dedup();
candidates
.into_iter()
.find(|start| feasible_at(task, tasks, schedule, resources, *start))
}
/// Returns `true` when a task placed at a time is feasible.
///
/// The check is that every required resource is available for the whole
@ -94,24 +156,6 @@ pub fn feasible_at(
schedule: &Schedule,
resources: &ResourceSet,
start: f64,
) -> bool {
let index = crate::sweep::demand_index(tasks);
feasible_at_indexed(task, schedule, resources, start, &index)
}
/// Returns `true` when a task placed at a time is feasible, using a demand
/// index the caller built once.
///
/// The index replaces two linear scans of the task list: the one that finds a
/// placed task while collecting the boundaries, and the one inside that sums
/// the demand over every placement covering a boundary. The boundary
/// arithmetic is unchanged, so the answer is the same as the scans give.
pub(crate) fn feasible_at_indexed(
task: &Task,
schedule: &Schedule,
resources: &ResourceSet,
start: f64,
index: &crate::sweep::DemandIndex,
) -> bool {
if !start.is_finite() {
return false;
@ -130,7 +174,10 @@ pub(crate) fn feasible_at_indexed(
// overlapping placements, where the total is greatest.
let mut boundaries: Vec<f64> = vec![start];
for placement in schedule.placements() {
if crate::sweep::demand_on(index, placement.task, resource.id).is_none() {
let Some(other) = tasks.iter().find(|other| other.id == placement.task) else {
continue;
};
if other.demand_for(resource.id).is_none() {
continue;
}
if placement.start < end && start < placement.end() {
@ -142,7 +189,12 @@ pub(crate) fn feasible_at_indexed(
.placements()
.iter()
.filter(|placement| placement.covers(boundary))
.filter_map(|placement| crate::sweep::demand_on(index, placement.task, resource.id))
.filter_map(|placement| {
tasks
.iter()
.find(|other| other.id == placement.task)
.and_then(|other| other.demand_for(resource.id))
})
.sum();
if placed + requirement.demand > resource.capacity() + 1e-9 {
return false;

2
crates/ops/apsis-scheduler/src/improve.rs
View File

@ -26,7 +26,7 @@
//! rather than removing it, and the caller continues to see what was left
//! out.
use crate::sweep::earliest_feasible_start;
use crate::greedy::earliest_feasible_start;
use apsis_resource::ResourceSet;
use apsis_schedule::Schedule;
use apsis_task::{Task, TaskId, TaskState};

5
crates/ops/apsis-scheduler/src/lib.rs
View File

@ -46,14 +46,13 @@
mod greedy;
mod improve;
mod planner;
mod sweep;
pub use greedy::{
demand_at, feasible_at, infeasible_tasks, resources_free_at, resources_have_capacity,
demand_at, earliest_feasible_start, feasible_at, infeasible_tasks, resources_free_at,
resources_have_capacity,
};
pub use improve::{ImprovementOutcome, ImprovementSettings, improve};
pub use planner::{PlanOutcome, Planner, SchedulingResult};
pub use sweep::earliest_feasible_start;
pub use apsis_resource::{ResourceId, ResourceSet};
pub use apsis_schedule::Schedule;

3
crates/ops/apsis-scheduler/src/planner.rs
View File

@ -1,8 +1,7 @@
//! The greedy planner.
use crate::greedy::infeasible_tasks;
use crate::greedy::{earliest_feasible_start, infeasible_tasks};
use crate::improve::{ImprovementSettings, improve};
use crate::sweep::earliest_feasible_start;
use apsis_resource::ResourceSet;
use apsis_schedule::Schedule;
use apsis_task::{PrecedenceGraph, Task, TaskId, TaskState, task_order};

340
crates/ops/apsis-scheduler/src/sweep.rs
View File

@ -1,340 +0,0 @@
//! The earliest start search, done in one pass over the schedule.
//!
//! The sequential form asks the same question in a loop: it lists every time
//! at which feasibility could change, sorts them, and tests each in turn until
//! one passes. That is correct but it recomputes the busy profile of every
//! resource once per candidate, so a plan with many placements on one resource
//! spends quadratic work deciding each task and cubic work across the plan.
//!
//! The profile does not depend on the candidate. A placement is busy between
//! its start and its end whatever time the new task is proposed for, so the
//! intervals during which the resource has no room are the same for every
//! candidate. This module computes them once, subtracts them from the
//! availability windows, and reads the earliest surviving start off the front.
//! That is one sweep per resource and a linear merge, rather than a sweep per
//! candidate.
//!
//! The result is confirmed with [`feasible_at`] before it is returned, and the
//! candidate enumeration is kept as the fallback for the rare case where the
//! sweep and the direct test disagree because of floating point rounding at a
//! capacity boundary. The fast path is therefore an accelerator, never a
//! second definition of what is feasible.
use crate::greedy::{feasible_at_indexed, resources_have_capacity};
use apsis_resource::ResourceId;
use apsis_resource::{Resource, ResourceSet};
use apsis_schedule::Schedule;
use apsis_task::Task;
use apsis_task::TaskId;
/// The slack allowed when comparing a load against a capacity.
///
/// It matches the tolerance in [`feasible_at`], so the sweep and the direct
/// test draw the same line at a boundary.
const CAPACITY_SLACK: f64 = 1e-9;
/// Returns the earliest time at which a task can be placed.
///
/// The earliest feasible start is always one of a small set of candidate
/// times: the start of the task's window, the start of an availability
/// window of one of its resources, or the end of a placement already on one
/// of those resources. Feasibility cannot change at any other instant,
/// because the demand on every resource is constant between those events and
/// the availability is constant between them too.
///
/// Returns `None` when the task cannot be placed anywhere in its window.
pub fn earliest_feasible_start(
task: &Task,
tasks: &[Task],
schedule: &Schedule,
resources: &ResourceSet,
) -> Option<f64> {
if !task.is_valid() || !resources_have_capacity(task, resources) {
return None;
}
if task.requirements.is_empty() {
// A task with no requirements can start as soon as its window opens.
return Some(task.earliest_start);
}
let latest_start = task.latest_end - task.duration;
// The demand of every task, looked up by identifier once. The sweep
// visits every placement of every required resource, and reading the
// demand by scanning the task list at each of those visits would make
// deciding one task quadratic in the plan. The map is built once per
// task, which is linear, and shared by every visit.
let demands = demand_index(tasks);
// The sweep, confirmed by the direct test.
if let Some(candidate) = swept_earliest_start(task, schedule, resources, latest_start, &demands)
{
if feasible_at_indexed(task, schedule, resources, candidate, &demands) {
return Some(candidate);
}
}
// The enumeration, which is exact. It runs when the sweep could not
// produce a confirmed answer, which is when the task does not fit at all
// or when rounding made the two disagree.
enumerate_earliest_start(task, schedule, resources, latest_start, &demands)
}
/// Returns the earliest start by testing every candidate in turn.
///
/// This is the original formulation, kept as the fallback for the sweep.
fn enumerate_earliest_start(
task: &Task,
schedule: &Schedule,
resources: &ResourceSet,
latest_start: f64,
index: &DemandIndex,
) -> Option<f64> {
let mut candidates: Vec<f64> = vec![task.earliest_start];
for requirement in &task.requirements {
let resource = resources.get(requirement.resource)?;
for window in resource.windows() {
candidates.push(window.start());
}
for placement in schedule.placements() {
let overlaps = demand_on(index, placement.task, resource.id).is_some();
if overlaps {
candidates.push(placement.end());
}
}
}
candidates
.retain(|time| time.is_finite() && *time >= task.earliest_start && *time <= latest_start);
candidates.sort_by(|first, second| {
first
.partial_cmp(second)
.unwrap_or(core::cmp::Ordering::Equal)
});
candidates.dedup();
candidates
.into_iter()
.find(|start| feasible_at_indexed(task, schedule, resources, *start, index))
}
/// Returns the earliest start derived from the swept profile.
///
/// The intervals returned by [`starts_fitting_on`] for each resource are
/// intersected, and the first interval that lies inside the task's window
/// gives the answer.
fn swept_earliest_start(
task: &Task,
schedule: &Schedule,
resources: &ResourceSet,
latest_start: f64,
demands: &DemandIndex,
) -> Option<f64> {
let mut allowed = vec![(f64::NEG_INFINITY, f64::INFINITY)];
for requirement in &task.requirements {
let resource = resources.get(requirement.resource)?;
let fitting = starts_fitting_on(
task.duration,
requirement.demand,
requirement.resource,
schedule,
resource,
demands,
);
allowed = intersect(&allowed, &fitting);
if allowed.is_empty() {
return None;
}
}
let &(low, high) = allowed.first()?;
let start = low.max(task.earliest_start);
let end = high.min(latest_start);
(start <= end).then_some(start)
}
/// Returns the intervals of start times at which a placement of the given
/// duration and demand fits on one resource.
///
/// A start is in the result when the whole placement lies inside one
/// availability window and the demand already placed on the resource never
/// exceeds the capacity less the new demand. The result is sorted and the
/// intervals are disjoint.
fn starts_fitting_on(
duration: f64,
demand: f64,
resource_id: ResourceId,
schedule: &Schedule,
resource: &Resource,
demands: &DemandIndex,
) -> Vec<(f64, f64)> {
let blocked = blocked_intervals(demand, resource_id, schedule, resource, demands);
let mut result = Vec::new();
for window in resource.windows() {
for (from, to) in subtract(&blocked, window.start(), window.end()) {
// The placement has to fit inside, so the last start is the end
// of the free interval less the duration.
let last_start = to - duration;
if last_start >= from {
result.push((from, last_start));
}
}
}
result
}
/// Returns the intervals during which a resource has no room for a demand.
///
/// The intervals are where the demand already placed on the resource exceeds
/// the capacity less `demand`. They are computed with a single sweep over the
/// placement boundaries, and are sorted and disjoint.
fn blocked_intervals(
demand: f64,
resource_id: ResourceId,
schedule: &Schedule,
resource: &Resource,
demands: &DemandIndex,
) -> Vec<(f64, f64)> {
let spare = resource.capacity() - demand;
// The load profile changes only where a placement starts or ends, so the
// sweep needs only those two instants per placement.
let mut events: Vec<(f64, f64)> = Vec::new();
for placement in schedule.placements() {
let Some(placed) = demand_on(demands, placement.task, resource_id) else {
continue;
};
events.push((placement.start, placed));
events.push((placement.end(), -placed));
}
if events.is_empty() {
return Vec::new();
}
events.sort_by(|first, second| {
first
.0
.partial_cmp(&second.0)
.unwrap_or(core::cmp::Ordering::Equal)
.then_with(|| {
first
.1
.partial_cmp(&second.1)
.unwrap_or(core::cmp::Ordering::Equal)
})
});
let limit = spare + CAPACITY_SLACK;
let mut blocked: Vec<(f64, f64)> = Vec::new();
let mut load = 0.0;
let mut opened: Option<f64> = None;
let mut index = 0;
while index < events.len() {
let time = events[index].0;
// The load is constant on the interval that ends at this instant.
if load > limit {
opened.get_or_insert(time);
}
// Apply every change at this instant at once, so the load compared
// above belongs to the interval before it and the one after belongs
// to the next comparison.
let mut next = index;
while next < events.len() && events[next].0 == time {
load += events[next].1;
next += 1;
}
if load <= limit {
if let Some(start) = opened.take() {
blocked.push((start, time));
}
}
index = next;
}
// A run that never closes extends past every placement, so it is
// recorded as open ended and swallows the rest of the horizon.
if let Some(start) = opened {
blocked.push((start, f64::INFINITY));
}
blocked
}
/// The demand each task puts on each resource, by task identifier.
///
/// A task identifier is a small dense integer, so the demands are held in a
/// vector indexed by it rather than in a map. Reading one is then an array
/// index rather than a hash, and a hash of a small integer costs more than
/// the scan it replaces.
pub(crate) type DemandIndex = Vec<Option<std::collections::HashMap<ResourceId, f64>>>;
/// Builds a [`DemandIndex`] in one pass over the task list.
pub(crate) fn demand_index(tasks: &[Task]) -> DemandIndex {
let highest = tasks.iter().map(|task| task.id.index()).max().unwrap_or(0);
let mut index: DemandIndex = (0..=highest).map(|_| None).collect();
for task in tasks {
if task.requirements.is_empty() {
continue;
}
let demands: std::collections::HashMap<ResourceId, f64> = task
.requirements
.iter()
.map(|requirement| (requirement.resource, requirement.demand))
.collect();
index[task.id.index()] = Some(demands);
}
index
}
/// Returns the demand a placed task puts on a resource, if any.
pub(crate) fn demand_on(index: &DemandIndex, task: TaskId, resource: ResourceId) -> Option<f64> {
index
.get(task.index())
.and_then(Option::as_ref)
.and_then(|required| required.get(&resource))
.copied()
}
/// Returns the pieces of an interval that no blocked interval covers.
///
/// Both inputs are sorted and disjoint. The result is sorted and disjoint.
fn subtract(blocked: &[(f64, f64)], from: f64, to: f64) -> Vec<(f64, f64)> {
let mut pieces = Vec::new();
let mut cursor = from;
for &(start, end) in blocked {
if end <= cursor {
continue;
}
if start >= to {
break;
}
if start > cursor {
pieces.push((cursor, start.min(to)));
}
cursor = cursor.max(end);
if cursor >= to {
break;
}
}
if cursor < to {
pieces.push((cursor, to));
}
pieces
}
/// Returns the intersection of two sorted, disjoint lists of intervals.
///
/// The result is sorted and disjoint.
fn intersect(left: &[(f64, f64)], right: &[(f64, f64)]) -> Vec<(f64, f64)> {
let mut result = Vec::new();
let mut i = 0;
let mut j = 0;
while i < left.len() && j < right.len() {
let start = left[i].0.max(right[j].0);
let end = left[i].1.min(right[j].1);
if start < end {
result.push((start, end));
}
if left[i].1 < right[j].1 {
i += 1;
} else {
j += 1;
}
}
result
}

174
crates/ops/apsis-scheduler/tests/sweep_equivalence.rs
View File

@ -1,174 +0,0 @@
//! Differential test of the swept search against the candidate enumeration.
//!
//! The sweep computes the earliest start from a busy profile; the
//! enumeration tests every time feasibility could change. They must agree
//! exactly, because the sweep is only an accelerator for the enumeration and
//! not a second definition of what is feasible. The randomised cases below
//! are the check: many shapes of window, capacity and overlap, including the
//! crowded ones where the two could plausibly diverge.
use apsis_resource::{Resource, ResourceId, ResourceSet, Window};
use apsis_schedule::Schedule;
use apsis_scheduler::{earliest_feasible_start, feasible_at};
use apsis_task::{Task, TaskId};
/// A tiny deterministic generator, so a failure is reproducible from the
/// seed printed in the assertion.
struct Rng(u64);
impl Rng {
fn next(&mut self) -> u64 {
// SplitMix64, chosen because it is a few lines and has a long period.
self.0 = self.0.wrapping_add(0x9E37_79B9_7F4A_7C15);
let mut z = self.0;
z = (z ^ (z >> 30)).wrapping_mul(0xBF58_476D_1CE4_E5B9);
z = (z ^ (z >> 27)).wrapping_mul(0x94D0_49BB_1331_11EB);
z ^ (z >> 31)
}
fn below(&mut self, bound: u64) -> u64 {
self.next() % bound
}
/// Returns a value in `[low, high)`.
fn range(&mut self, low: f64, high: f64) -> f64 {
low + (self.next() >> 11) as f64 / (1u64 << 53) as f64 * (high - low)
}
}
/// Builds a random scenario and returns the two answers, or `None` when the
/// task does not fit at all.
fn compare(seed: u64) -> (Option<f64>, Option<f64>, Schedule) {
let mut rng = Rng(seed);
// One resource with a random capacity and a couple of availability
// windows.
let resource_id = ResourceId::new(0);
let capacity = rng.range(1.0, 4.0);
let mut resource = Resource::new(resource_id, capacity);
let window_count = 1 + rng.below(3) as usize;
let mut windows = Vec::new();
for index in 0..window_count {
let from = index as f64 * 100.0 + rng.range(0.0, 20.0);
let to = from + rng.range(30.0, 150.0);
windows.push(Window::new(from, to));
}
resource
.set_windows(&windows)
.expect("the windows are usable");
let resources = ResourceSet::from_resources(vec![resource]).expect("distinct");
// A set of tasks with random demands, windows and durations.
let task_count = rng.below(12) as usize;
let mut tasks = Vec::new();
let mut schedule = Schedule::new();
for index in 0..task_count {
let duration = rng.range(5.0, 60.0);
let from = rng.range(0.0, 300.0);
let to = from + rng.range(duration, 250.0);
let demand = rng.range(0.2, capacity.max(0.3));
let task = Task::new(TaskId::new(index), duration)
.with_window(from, to)
.try_require(resource_id, demand)
.expect("the resource is new");
// Place some of them, so the sweep sees a busy profile.
if rng.below(3) == 0 {
let _ = earliest_feasible_start(&task, &tasks, &schedule, &resources);
if let Some(start) = earliest_feasible_start(&task, &tasks, &schedule, &resources) {
let _ = schedule.place(&task, start);
}
}
tasks.push(task);
}
// The task under test.
let duration = rng.range(5.0, 60.0);
let from = rng.range(0.0, 300.0);
let to = from + rng.range(duration, 300.0);
let demand = rng.range(0.2, capacity.max(0.3));
let probe = Task::new(TaskId::new(9_999), duration)
.with_window(from, to)
.try_require(resource_id, demand)
.expect("the resource is new");
let swept = earliest_feasible_start(&probe, &tasks, &schedule, &resources);
// The enumeration, reached by asking for a start and checking each
// candidate the original way. The public entry is the sweep, so the
// enumeration is exercised through `feasible_at` over the same candidate
// set the original built.
let enumerated = enumerate(&probe, &tasks, &schedule, &resources);
(swept, enumerated, schedule)
}
/// The original enumeration, written out so the two can be compared.
fn enumerate(
task: &Task,
tasks: &[Task],
schedule: &Schedule,
resources: &ResourceSet,
) -> Option<f64> {
if !task.is_valid() {
return None;
}
let latest_start = task.latest_end - task.duration;
let mut candidates: Vec<f64> = vec![task.earliest_start];
for requirement in &task.requirements {
let resource = resources.get(requirement.resource)?;
for window in resource.windows() {
candidates.push(window.start());
}
for placement in schedule.placements() {
let overlaps = tasks
.iter()
.find(|other| other.id == placement.task)
.is_some_and(|other| other.demand_for(resource.id).is_some());
if overlaps {
candidates.push(placement.end());
}
}
}
candidates
.retain(|time| time.is_finite() && *time >= task.earliest_start && *time <= latest_start);
candidates.sort_by(|a, b| a.partial_cmp(b).unwrap_or(core::cmp::Ordering::Equal));
candidates.dedup();
candidates
.into_iter()
.find(|start| feasible_at(task, tasks, schedule, resources, *start))
}
#[test]
fn the_sweep_agrees_with_the_enumeration() {
let mut placed = 0_usize;
let mut agreed = 0_usize;
for seed in 1..20_000_u64 {
let (swept, enumerated, _) = compare(seed);
assert_eq!(swept, enumerated, "seed {seed} disagrees");
if swept.is_some() {
placed += 1;
agreed += 1;
}
}
// The cases must actually exercise the interesting path, or agreement
// would be vacuous.
assert!(placed > 1_000, "only {placed} cases placed the task");
assert_eq!(placed, agreed);
}
#[test]
fn a_placed_answer_is_always_feasible() {
// The sweep must never report a start that the direct test rejects,
// which is the property the confirmation step in the code relies on.
let mut checked = 0_usize;
for seed in 1..5_000_u64 {
let (swept, _, _) = compare(seed);
if let Some(start) = swept {
// Rebuild the probe to test it. The comparison helper does not
// return the scenario, so this checks the weaker but still
// useful property that the answer is finite and inside the task
// window whenever the test is constructed.
assert!(start.is_finite(), "seed {seed} produced {start}");
checked += 1;
}
}
assert!(checked > 500);
}

74
crates/orbit/apsis-sgp4/src/batch.rs
View File

@ -1,74 +0,0 @@
//! Batch propagation over many instants, optionally across several threads.
//!
//! A single satellite's track is the common case for a coverage run or an
//! access search: the caller wants the state at every minute of a day, for
//! every satellite in a shell. Each state is independent of the others, so
//! the loop is a candidate for several cores, and the work is large enough
//! that starting a thread pays for itself.
//!
//! The parallel entry point produces the same values as the sequential one,
//! in the same order. It differs only in how the work is distributed.
use crate::{Satellite, State};
use apsis_math::parallel::map_index;
/// Propagates a satellite at a list of minutes from its epoch, in order.
///
/// The sequential form, provided for comparison and for small lists where
/// starting a thread would cost more than the work.
pub fn propagate_minutes_at(satellite: &Satellite, minutes: &[f64]) -> Vec<Option<State>> {
minutes
.iter()
.map(|&value| satellite.propagate_minutes(value).ok())
.collect()
}
/// Propagates a satellite at a list of minutes from its epoch, across several
/// threads.
///
/// The result matches [`propagate_minutes_at`] element for element and in the
/// same order. A minute at which the model reports a decay yields `None`, as
/// it does in the sequential form; the threads do not stop at the first such
/// minute, because a caller usually wants the whole track and will decide for
/// itself what a decay means.
///
/// Propagation is deterministic and depends only on the minutes, so the
/// result does not depend on how the work was split.
///
/// The gain depends on how much work the list holds, because starting the
/// threads costs a fixed amount that a short list cannot repay. A day at a
/// one minute step is fourteen hundred states and gains little; a month is
/// forty three thousand and gains several fold. A caller with many short
/// tracks is better served by the per satellite form below, which takes the
/// whole list in one call.
pub fn propagate_minutes_at_parallel(satellite: &Satellite, minutes: &[f64]) -> Vec<Option<State>> {
map_index(minutes.len(), |index| {
satellite.propagate_minutes(minutes[index]).ok()
})
}
/// Propagates several satellites at one instant, in order.
///
/// The per satellite work is independent, so a shell's state at a single
/// instant is a natural batch. The satellites are read only, so they are
/// shared across the threads by reference.
pub fn propagate_at(satellites: &[Satellite], tai_mjd: f64) -> Vec<Option<State>> {
satellites
.iter()
.map(|satellite| satellite.propagate_at(tai_mjd).ok())
.collect()
}
/// Propagates several satellites at one instant, across several threads.
///
/// The result matches [`propagate_at`] element for element and in the same
/// order.
///
/// This is the form a coverage run wants: it holds the whole shell in one
/// call, so the threads start once for every satellite rather than once per
/// satellite, and even a shell of a few hundred gains.
pub fn propagate_at_parallel(satellites: &[Satellite], tai_mjd: f64) -> Vec<Option<State>> {
map_index(satellites.len(), |index| {
satellites[index].propagate_at(tai_mjd).ok()
})
}

4
crates/orbit/apsis-sgp4/src/lib.rs
View File

@ -53,7 +53,6 @@
#![forbid(unsafe_code)]
#![deny(missing_docs)]
mod batch;
mod deep_space;
mod error;
mod init;
@ -62,9 +61,6 @@ mod propagate;
mod satellite;
mod state;
pub use batch::{
propagate_at, propagate_at_parallel, propagate_minutes_at, propagate_minutes_at_parallel,
};
pub use error::{PropagationError, PropagationErrorKind};
pub use init::Elements;
pub use model::GravityModel;

99
crates/orbit/apsis-sgp4/tests/batch.rs
View File

@ -1,99 +0,0 @@
//! Tests for the batch propagation entry points.
//!
//! The property that matters is that the parallel forms produce exactly the
//! values the sequential forms do, in the same order. Every test compares
//! against the sequential answer rather than against a constant, so a
//! mismatch in either the propagation or the ordering is caught.
use apsis_sgp4::{
GravityModel, Satellite, TwoLineElement, propagate_at, propagate_at_parallel,
propagate_minutes_at, propagate_minutes_at_parallel,
};
const SAMPLE: &str = concat!(
"1 25544U 98067A 08264.51782528 -.00002182 00000-0 -11606-4 0 2927\r\n",
"2 25544 51.6416 247.4627 0006703 130.5360 325.0288 15.72125391563537\r\n",
);
fn satellite() -> Satellite {
let element = TwoLineElement::parse(SAMPLE).expect("the sample parses");
Satellite::from_element(&element, GravityModel::WGS72).expect("the orbit propagates")
}
#[test]
fn a_short_track_matches_the_sequential_form() {
let satellite = satellite();
let minutes: Vec<f64> = (0..100).map(|index| index as f64 * 1.0).collect();
let sequential = propagate_minutes_at(&satellite, &minutes);
let parallel = propagate_minutes_at_parallel(&satellite, &minutes);
assert_eq!(parallel, sequential);
}
#[test]
fn a_long_track_matches_the_sequential_form() {
// A day at a one minute step, which is long enough that the parallel path
// takes the multi thread branch.
let satellite = satellite();
let minutes: Vec<f64> = (0..1_441).map(|index| index as f64).collect();
let sequential = propagate_minutes_at(&satellite, &minutes);
let parallel = propagate_minutes_at_parallel(&satellite, &minutes);
assert_eq!(parallel, sequential);
assert_eq!(parallel.len(), 1_441);
}
#[test]
fn a_backwards_track_matches() {
// Negative minutes propagate backwards and must behave the same way in
// both forms.
let satellite = satellite();
let minutes: Vec<f64> = (0..2_000).map(|index| -(index as f64) * 0.5).collect();
assert_eq!(
propagate_minutes_at_parallel(&satellite, &minutes),
propagate_minutes_at(&satellite, &minutes)
);
}
#[test]
fn an_empty_track_is_empty() {
let satellite = satellite();
assert!(propagate_minutes_at_parallel(&satellite, &[]).is_empty());
}
#[test]
fn a_decayed_instant_is_reported_in_both_forms() {
// Far enough ahead that the drag term brings the satellite down, both
// forms must agree that the instant is unusable rather than one of them
// stopping early.
let satellite = satellite();
let minutes = vec![0.0, 1.0, 60.0 * 24.0 * 365.0 * 20.0];
let sequential = propagate_minutes_at(&satellite, &minutes);
let parallel = propagate_minutes_at_parallel(&satellite, &minutes);
assert_eq!(parallel, sequential);
}
#[test]
fn a_shell_at_one_instant_matches() {
let satellite = satellite();
let shell = vec![satellite; 500];
let instant = 54_723.5;
assert_eq!(
propagate_at_parallel(&shell, instant),
propagate_at(&shell, instant)
);
}
#[test]
fn a_shell_result_is_in_input_order() {
// The states of a repeated satellite are identical, so ordering is checked
// through the minutes form, where each value differs.
let satellite = satellite();
let minutes: Vec<f64> = (0..3_000).map(|index| index as f64 * 0.25).collect();
let parallel = propagate_minutes_at_parallel(&satellite, &minutes);
for (index, state) in parallel.iter().enumerate() {
let state = state.as_ref().expect("the orbit has not decayed here");
let direct = satellite
.propagate_minutes(minutes[index])
.expect("the orbit propagates");
assert_eq!(state.position, direct.position, "at index {index}");
}
}

1
docs/design/README.md
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@ -10,7 +10,6 @@
- [单位与坐标约定](units.md)
- [错误与容差策略](errors.md)
- [分层边界](layers.md)
- [并行化](parallel.md)
## 各层设计

27
docs/design/errors.md
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@ -115,33 +115,6 @@ impl core::error::Error for FooError {}
（`wrap_to_pi`）在边界上用半开区间，不引入 epsilon。浮点比较仅在量本身
是连续近似时使用。
## 库代码中的 expect 断言
工作区约定库代码不使用 `unwrap` / `expect` / `panic!`。这条规则的**意图**是
不允许用它们处理外部输入的失败——那种失败必须走 `Result` 或 `Option`，让
调用方能够处理。
但完全不出现 `expect` 会迫使代码用 `unwrap`（更差）或写出冗长的手工分支。
因此允许一种例外：**对已由前置检查守卫的内部不变量使用
`expect("说明")`**。这类断言不把不可信数据转成 panic，而是把"若此处为空，
则是本 crate 的编码错误"写成一条可读的失败信息。
判据：能否在紧邻的前一行找到使该分支不可达的守卫，或该值是否由本函数
刚刚构造。当前 12 处全部满足，逐处为：
| 位置 | 不变量 | 守卫 |
| --- | --- | --- |
| `apsis-schedule/schedule.rs` | 刚 `push` 的 placement 存在 | 同函数上一行 |
| `apsis-scheduler/improve.rs` | 刚检查 `is_none()` 的值非空 | 上一行 `is_none()` 分支 |
| `apsis-scheduler/planner.rs` | order 中的 id 在 task 列表里 | order 由 task 列表构造 |
| `apsis-topology/series.rs` | 时间有限 | 构造时已校验 |
| `apsis-handover/decision.rs` | 候选列表非空 | 上一行 `validate` |
| `apsis-constellation/walker.rs` | 平面数 / 每面星数为正 | 构造时已校验除数 |
| `apsis-kepler/elements.rs` | node / 半径非零 | 紧邻的 `norm() == 0.0` 分支 |
| `apsis-event/queue.rs` | 出堆项必有 payload | 队列构造时序保证 |
若将某条守卫移除，相应的 `expect` 就必须改为 `Result`。修改时二者应同时进行。
## 检查
- 各 crate 测试覆盖其错误的每个 `kind`，包括构造失败与恢复路径。

121
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@ -1,121 +0,0 @@
# 并行化
本文件记录并行化的判定标准、提供的接口，以及实测结果。跨层的单位与坐标约定见
[单位与坐标约定](units.md)，分层边界见 [分层边界](layers.md)。
## 为什么不引入线程池
工作区禁止任何第三方 crate，因此没有 `rayon` 这样的线程池可用。也不需要：
工作区中值得多核的运算，无一例外都是**逐元素独立**的循环，用标准库的
`std::thread::scope` 就能直接表达。
作用域线程按引用借用数据，调用方无需 `Arc` 即可共享一个切片或一个只读对象；
作用域结束前会 join 全部线程，因此不会有结果在线程仍在写时被读走。
## 接口
### apsis-math：并行原语
`apsis_math::parallel` 提供两个入口，是所有并行接口的基础：
| 函数 | 用途 |
| --- | --- |
| `thread_count()` | 机器的并行度 |
| `threads_for(len)` | 该长度下值得启用的线程数 |
| `for_each_index(len, f)` | 对每个下标调用 `f` |
| `map_index(len, f)` | 每个下标产出一个值，按下标序返回 |
两个入口都只要求闭包可**同步调用**（`Fn` + `Sync`），因为它们把输入当作共享
的、把输出写进各自负责的槽位；调用方不需要自己同步。
`threads_for` 在长度小于每线程一千项时返回 1：在这个量级上，启动线程的成本
高于它能省下的工作。
### 各层的批处理接口
| crate | 接口 | 适用规模 |
| --- | --- | --- |
| `apsis-sgp4` | `propagate_minutes_at_parallel` | 长轨道（≥ 数万样本） |
| `apsis-sgp4` | `propagate_at_parallel` | 整壳一次性传播 |
| `apsis-access` | `find_all_parallel` | 数百条轨道 |
| `apsis-isl` | `visibility_matrix_parallel` | 数百颗以上（见下） |
每个接口都有一个同名的顺序版本，两者结果逐元素相同、顺序相同，调用方可自由
切换。
## 判定标准
并非所有批处理都值得并行化。判定依据是**单次工作成本**与**总量**：
- **值得并行**：单次工作昂贵（≥ 微秒），且逐元素独立，规模可达数百次以上。
典型是 SGP4 传播（约 230 ns/样本，百万样本量级）与可见性搜索（约 7 μs/轨）。
- **不值得并行**：
- `Constellation::instantiate`：纯算术，几百颗星只需微秒，线程开销完全淹没。
- 调度器：贪心放置本质串行，每次放置改变后续任务的可行区间，不是独立
循环，因此没有并行接口；但其中的搜索已改为单次扫描（见下）。
- 事件引擎：单队列时序，无法分块。
- 大地与坐标变换：单点调用本身已是 O(1)，没有批量。
- `mutual_visibility` 单次：约 4 ns，**单次**不值得，但成矩阵（见下）。
## 实测（16 核，release）
### SGP4 单条轨道（`propagate_minutes_at_parallel`）
| 轨道长度 | 顺序 | 并行 | 加速 |
| --- | --- | --- | --- |
| 1 天（1,440 样本） | 0.3 ms | 0.3 ms | 1.28× |
| 7 天（10,080） | 2.3 ms | 0.9 ms | 2.46× |
| 30 天（43,200） | 10.1 ms | 1.9 ms | 5.45× |
| 365 天（525,600） | 144.1 ms | 26.0 ms | 5.54× |
**结论**：轨道越长加速越高，30 天以上稳定在 5.5×。一天以内收益很小——
1,440 个样本分给多线程后每线程不足一千项，低于 `threads_for` 的阈值。
**实践要点**：有大量短轨道时，应使用 `propagate_at_parallel`（整壳一次调用），
而不是对每颗星各调一次并行版——后者会让每颗星都付一次线程启动成本。
### 可见性矩阵（`visibility_matrix_parallel`）
| 星数 | 对数 | 顺序 | 并行 | 加速 |
| --- | --- | --- | --- | --- |
| 200 | 4 万 | 0.16 ms | 0.31 ms | 0.53× |
| 600 | 36 万 | 1.50 ms | 1.37 ms | 1.09× |
| 1,000 | 100 万 | 4.09 ms | 2.50 ms | 1.64× |
**结论**：单次可见性判定只有几纳秒，**小规模下并行反而更慢**（线程开销占比高），
数百颗星以上才开始获益，且远未饱和。这个接口是为大规模壳准备的；小壳应直接用
顺序版。接口文档也如实说明了这一点。
### 跨层组合
`bench_parallel` 的测量显示，整壳在多核上传播与构建拓扑的并行效果最好，因为
它把整个工作量一次性摊给所有线程。相关数据见该示例的输出。
## 确定性
并行不改变结果：所有批量接口都逐元素比对顺序版的结果（SGP4 的状态、可见性
的布尔矩阵、access 的过站摘要），顺序也一致。传播本身是确定性的，只依赖时刻，
与如何分块无关；可见性与过站搜索是逐元素独立的。因此同一输入在任意线程数下
产生相同输出，测试也按此断言。
## 调度器搜索的优化
调度器没有并行接口，但它的最坏情况曾达到每任务数百微秒。优化分两步，两者都
保持结果逐位不变。
**第一步：一次扫描代替逐候选测试。** 旧的做法列出所有"可行性可能变化"的时刻，
逐个测试，每次都重新计算每个资源的负载曲线。负载曲线与候选时刻无关，因此改为
扫一次：把"资源没有余量的区间"从可用窗口中减去，多资源求交，取第一个存活区间
的起点。结果仍由 `feasible_at` 确认，枚举法保留为浮点边界不一致时的回退。
**第二步：确认调用复用索引。** 去掉确认调用后耗时降到八分之一，这定位了真正
的开销：确认用的公开可行性测试在收集边界时扫描一次任务表，又在每个边界上对每
个覆盖该边界的放置再扫描一次任务表。把第一步建好的索引传进去，两处扫描都变成
按标识符直接读取。
任务标识符是小而稠密的整数，因此索引用向量而非哈希表：数组下标比哈希一个整数
更便宜，这在本仓库已测到两次（拓扑的邻接表用索引、这里的任务表用向量）。
**结果**：全部任务争用单一资源、容量为瓶颈时，3200 个任务从 6.7 秒降到 0.48
秒（14 倍），6400 个任务 2.2 秒。计划结果不变——测试在两种资源、窗口不相交的
场景下逐个比对了每个放置的起止时刻。

12
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@ -93,14 +93,6 @@ cargo run -p apsis-rs --features physics --example dump_teme \
# 覆盖几何（仰角、星下点角、地心角、斜距、覆盖面积）
cargo run -p apsis-rs --features network --example dump_coverage \
> validation/data/expected/rust_coverage.csv
# 二体模型（开普勒要素↔状态矢量，往返转换）
cargo run -p apsis-rs --features orbit --example dump_kepler \
> validation/data/expected/rust_kepler.csv
# 两线元素集解析（字段、历元展开、模十校验和）
cargo run -p apsis-rs --features orbit --example dump_tle \
> validation/data/expected/rust_tle.csv
```
Python 侧读取同一批输入，用参考实现重算并输出误差表：
@ -119,8 +111,6 @@ pixi run python validation/python/atmosphere/check_gas_exact.py
pixi run python validation/python/time/check_iau2000.py
pixi run python validation/python/coord/check_teme.py
pixi run python validation/python/constellation/check_coverage.py
pixi run python validation/python/orbit/check_kepler.py
pixi run python validation/python/orbit/check_tle.py
```
两个脚本都以退出码 0 表示通过、1 表示超差、2 表示缺少输入文件。
@ -162,8 +152,6 @@ Earth orientation 数据自动下载；本 crate 涉及的换算不需要该数
| `time/check_iau2000.py` | 岁差、章动、框架偏移、GAST、GCRS→ITRF，8 个历元 × 28 个量 | ERFA 2.0.1（IAU SOFA 派生） | 章动 6.6e-15 rad；BPN 矩阵 6.0e-15；GAST 1.1e-11 rad |
| `coord/check_teme.py` | TEME → 地固系，4 个历元 | ERFA 的 `gmst82` 与 `pom00`（同为 0 极移） | 4.9e-10 km |
| `constellation/check_coverage.py` | 覆盖几何，6 个场景（LEO/MEO/GEO × 低/常规/严格遮蔽角）；以及地心角与仰角的往返 | 球面三角关系（Python 从几何独立重写） | 角度 0，面积相对 2.2e-16 |
| `orbit/check_kepler.py` | 二体转换，7 个轨道（圆/低偏心/中偏心/高偏心 e=0.97/逆行/近极/地球同步）；以及 36 个真近点角的状态反解 | 近日点公式 + 旋转矩阵 + 活力公式（Python 独立重写） | 位置、速度、周期 0；能量 3.0e-14 km²/s²；反解要素 ~1e-11 km |
| `orbit/check_tle.py` | TLE 字段解析，8 个元素集 × 17 字段（含两数字年展开、隐含前导零偏心率、指数记法拖动项、模十校验和） | 按列索引的 NORAD 格式独立解析器 | 逐字段精确一致 |
### 关于射频层对拍的说明

268
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@ -1,268 +0,0 @@
"""Cross-check the ApsisRS two-body model against an independent computation.
Reads the quantities written by ``cargo run -p apsis-rs --features orbit
--example dump_kepler`` and recomputes them from the closed-form expressions
of orbital mechanics, using only the standard library and numpy. The point is
that the Python side is written from the geometry, not from the Rust code, so
an error in the Rust formulae shows up as a disagreement.
The relations used are the standard ones:
* the perifocal position and velocity at a true anomaly ``nu``,
p = a (1 - e^2), r = p / (1 + e cos nu)
x = r cos nu, y = r sin nu
vx = -sqrt(mu / p) sin nu
vy = sqrt(mu / p) (e + cos nu)
rotated into the inertial frame by ``R3(O) R1(i) R3(w)``;
* the vis-viva equation, ``v^2 = mu (2/r - 1/a)``, used to check the speed
independently of the direction;
* the specific orbital energy, ``E = v^2/2 - mu/r``;
* Kepler's third law for the period, ``T = 2 pi sqrt(a^3/mu)``;
* the conic radius, ``r = p / (1 + e cos nu)``.
The second table is checked in the other direction: a state is converted back
to elements, and the recovered elements must equal the ones that produced it.
The script needs no network access.
Usage:
pixi run python validation/python/orbit/check_kepler.py [path]
Exit status is zero when every quantity agrees within tolerance and one
otherwise.
"""
from __future__ import annotations
import csv
import math
import sys
from pathlib import Path
# The agreement is at the floating point level because both sides evaluate
# the same closed forms. The tolerances are set to catch a transposed sign, a
# radians/degrees slip, or a dropped rotation, not to allow a loose match.
LENGTH_TOLERANCE_KM = 1e-9
VELOCITY_TOLERANCE_KMS = 1e-11
ANGLE_TOLERANCE_RAD = 1e-12
RELATIVE_TOLERANCE = 1e-12
DEFAULT_INPUT = Path("validation/data/expected/rust_kepler.csv")
# The WGS 84 gravitational parameter, matching the constant the example uses.
MU = 398_600.5
def rotation_matrix(inclination: float, right_ascension: float, argument_of_perigee: float):
"""Returns R3(O) R1(i) R3(w), the perifocal to inertial rotation."""
sw, cw = math.sin(argument_of_perigee), math.cos(argument_of_perigee)
si, ci = math.sin(inclination), math.cos(inclination)
so, co = math.sin(right_ascension), math.cos(right_ascension)
return [
[co * cw - so * sw * ci, -co * sw - so * cw * ci, so * si],
[so * cw + co * sw * ci, -so * sw + co * cw * ci, -co * si],
[sw * si, cw * si, ci],
]
def apply(matrix, vector):
"""Applies a 3x3 matrix to a vector."""
return [sum(matrix[row][col] * vector[col] for col in range(3)) for row in range(3)]
def reference_state(a, e, i, om, w, nu, mu=MU):
"""Returns the position, velocity and radius from the closed forms."""
p = a * (1.0 - e * e)
radius = p / (1.0 + e * math.cos(nu))
x = radius * math.cos(nu)
y = radius * math.sin(nu)
scale = math.sqrt(mu / p)
vx = -scale * math.sin(nu)
vy = scale * (e + math.cos(nu))
matrix = rotation_matrix(i, om, w)
return (
apply(matrix, [x, y, 0.0]),
apply(matrix, [vx, vy, 0.0]),
radius,
)
def reference_period(a, mu=MU):
"""Returns the orbital period from Kepler's third law."""
return 2.0 * math.pi * math.sqrt(a**3 / mu)
def check_states(rows):
"""Checks the elements to state table and returns pass flag and report."""
worst = {
"position": 0.0,
"velocity": 0.0,
"radius": 0.0,
"period": 0.0,
"energy": 0.0,
}
for row in rows:
a = float(row["semi_major_axis_km"])
e = float(row["eccentricity"])
i = float(row["inclination_rad"])
om = float(row["right_ascension_rad"])
w = float(row["argument_of_perigee_rad"])
nu = float(row["true_anomaly_rad"])
position, velocity, radius = reference_state(a, e, i, om, w, nu)
rust_position = [float(row["x_km"]), float(row["y_km"]), float(row["z_km"])]
rust_velocity = [float(row["vx_kms"]), float(row["vy_kms"]), float(row["vz_kms"])]
position_error = max(abs(p - q) for p, q in zip(position, rust_position))
velocity_error = max(abs(p - q) for p, q in zip(velocity, rust_velocity))
radius_error = abs(radius - float(row["state_radius_km"]) if "state_radius_km" in row else 0.0)
# The speed is checked through the vis-viva equation, which is
# independent of the direction, and the energy through its own
# closed form.
speed = math.sqrt(sum(component * component for component in rust_velocity))
vis_viva = math.sqrt(mu := MU * (2.0 / math.hypot(*rust_position) - 1.0 / a))
energy_reference = vis_viva * vis_viva / 2.0 - MU / math.hypot(*rust_position)
energy_error = abs(energy_reference - float(row["energy_kms2"]))
period_error = abs(reference_period(a) - float(row["period_seconds"]))
worst["position"] = max(worst["position"], position_error)
worst["velocity"] = max(worst["velocity"], velocity_error)
worst["radius"] = max(worst["radius"], radius_error)
worst["period"] = max(worst["period"], period_error)
worst["energy"] = max(worst["energy"], energy_error)
_ = speed # the magnitude check is folded into the vis-viva step
return worst
def check_recovery(rows):
"""Checks the state to elements table and returns the worst deviations."""
worst = {
"semi_major_axis": 0.0,
"eccentricity": 0.0,
"inclination": 0.0,
"right_ascension": 0.0,
"argument_of_perigee": 0.0,
"true_anomaly": 0.0,
}
for row in rows:
# The input orbit for the second table is fixed by the example.
expected_a = 7_000.0
expected_e = 0.3
expected_i = 0.7
expected_om = 1.2
expected_w = 0.4
nu = float(row["true_anomaly_deg"])
# The recovered semi-major axis and eccentricity must be unchanged.
worst["semi_major_axis"] = max(
worst["semi_major_axis"], abs(float(row["recovered_semi_major_axis_km"]) - expected_a)
)
worst["eccentricity"] = max(
worst["eccentricity"], abs(float(row["recovered_eccentricity"]) - expected_e)
)
# The angles must be reproduced, modulo a full revolution. The
# argument of perigee and the node are compared through the total
# longitude, which is the quantity that is actually determined.
recovered_lon = float(row["recovered_argument_of_perigee_rad"]) + float(
row["recovered_right_ascension_rad"]
)
expected_lon = expected_w + expected_om
delta = (recovered_lon - expected_lon + math.pi) % (2.0 * math.pi) - math.pi
worst["argument_of_perigee"] = max(worst["argument_of_perigee"], abs(delta))
worst["inclination"] = max(
worst["inclination"], abs(float(row["recovered_inclination_rad"]) - expected_i)
)
recovered_nu = float(row["recovered_true_anomaly_rad"])
delta_nu = (recovered_nu - nu + math.pi) % (2.0 * math.pi) - math.pi
worst["true_anomaly"] = max(worst["true_anomaly"], abs(delta_nu))
return worst
def read_blocks(path: Path):
"""Returns the two CSV blocks separated by a blank line."""
text = path.read_text().splitlines()
blocks: list[list[str]] = [[]]
for line in text:
if line.strip():
blocks[-1].append(line)
else:
blocks.append([])
return [block for block in blocks if block]
def main(argv: list[str]) -> int:
path = Path(argv[1]) if len(argv) > 1 else DEFAULT_INPUT
if not path.exists():
print(f"missing input file: {path}", file=sys.stderr)
print(
"generate it with: cargo run -p apsis-rs --features orbit "
"--example dump_kepler > " + str(path),
file=sys.stderr,
)
return 2
blocks = read_blocks(path)
if len(blocks) < 2:
print("input file does not have the two expected blocks", file=sys.stderr)
return 2
states = list(csv.DictReader(blocks[0]))
recovery = list(csv.DictReader(blocks[1]))
if not states or not recovery:
print("input file has an empty block", file=sys.stderr)
return 2
worst = check_states(states)
print(f"states compared: {len(states)}")
print(f"worst position: {worst['position']:.6e} km")
print(f"worst velocity: {worst['velocity']:.6e} km/s")
print(f"worst radius: {worst['radius']:.6e} km")
print(f"worst period: {worst['period']:.6e} s")
print(f"worst energy: {worst['energy']:.6e} km^2/s^2")
recovered = check_recovery(recovery)
print(f"recovered compared: {len(recovery)}")
print(f"worst semi-major: {recovered['semi_major_axis']:.6e} km")
print(f"worst eccentricity: {recovered['eccentricity']:.6e}")
print(f"worst inclination: {recovered['inclination']:.6e} rad")
print(f"worst longitude: {recovered['argument_of_perigee']:.6e} rad")
print(f"worst true anomaly: {recovered['true_anomaly']:.6e} rad")
failures = []
if worst["position"] > LENGTH_TOLERANCE_KM:
failures.append("position")
if worst["velocity"] > VELOCITY_TOLERANCE_KMS:
failures.append("velocity")
if worst["period"] > LENGTH_TOLERANCE_KM:
failures.append("period")
if worst["energy"] > RELATIVE_TOLERANCE * abs(MU):
failures.append("energy")
if recovered["semi_major_axis"] > LENGTH_TOLERANCE_KM:
failures.append("recovered semi-major axis")
if recovered["eccentricity"] > RELATIVE_TOLERANCE:
failures.append("recovered eccentricity")
if recovered["inclination"] > ANGLE_TOLERANCE_RAD:
failures.append("recovered inclination")
if recovered["argument_of_perigee"] > ANGLE_TOLERANCE_RAD:
failures.append("recovered longitude")
if recovered["true_anomaly"] > ANGLE_TOLERANCE_RAD:
failures.append("recovered true anomaly")
for failure in failures:
print(f" {failure} exceeds tolerance")
if failures:
print("result: FAIL")
return 1
print("result: pass")
return 0
if __name__ == "__main__":
raise SystemExit(main(sys.argv))

275
validation/python/orbit/check_tle.py
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@ -1,275 +0,0 @@
"""Cross-check the ApsisRS two-line element parser against an independent reader.
Reads the element fields written by ``cargo run -p apsis-rs --features orbit
--example dump_tle`` and reparses the same element sets with a column indexed
reader written from the NORAD format, then compares every field. The
checksum of each line is recomputed from its definition, so a field placed in
the wrong column or a sign convention that was dropped shows up as a
disagreement.
The format is positional, with the first character of a line at column zero:
* line 1: satellite number in columns 2 to 6, classification in column 7,
international designator in columns 9 to 16, epoch year and fraction of a
day in columns 18 to 32, the first derivative of the mean motion divided
by two in columns 33 to 43, the second derivative divided by six in columns
44 to 52, the drag term in columns 53 to 61, the element set number in
columns 62 to 67, and the checksum in column 68;
* line 2: inclination in columns 8 to 16, right ascension in columns 17 to
25, eccentricity in columns 26 to 33 as an implied leading decimal,
argument of perigee in columns 34 to 42, mean anomaly in columns 43 to 51,
mean motion in columns 52 to 63, the revolution number in columns 63 to 68,
and the checksum in column 68.
A dash counts as one and every digit counts as its own value, summed over the
first sixty eight columns and reduced modulo ten.
The script needs no network access.
Usage:
pixi run python validation/python/orbit/check_tle.py [path]
Exit status is zero when every field agrees and one otherwise.
"""
from __future__ import annotations
import csv
import sys
from pathlib import Path
# The reader works on the same characters the parser saw, so the two must
# agree to the last digit. The tolerance is therefore exact, not
# approximate, and only guards the exponent fields against a difference in
# how the two languages round a very small value.
ABSOLUTE_TOLERANCE = 1e-12
EXPONENT_TOLERANCE = 1e-18
DEFAULT_INPUT = Path("validation/data/expected/rust_tle.csv")
# The element sets, in the order the example writes them. The lines are the
# same ones the example parses.
ELEMENT_SETS = {
"vanguard_1": (
"1 00005U 58002B 00179.78495062 .00000023 00000-0 28098-4 0 4753",
"2 00005 34.2682 348.7242 1859667 331.7664 19.3264 10.82419157413667",
),
"iss_2008": (
"1 25544U 98067A 08264.51782528 -.00002182 00000-0 -11606-4 0 2927",
"2 25544 51.6416 247.4627 0006703 130.5360 325.0288 15.72125391563537",
),
"teme_94_deep": (
"1 27651U 03004A 06185.99374200 .00000109 00000-0 19909-4 0 445",
"2 27651 7.1743 182.9443 7867251 269.0386 18.6601 1.03461646 9884",
),
"lrs_4_deep": (
"1 09880U 77021A 06174.85710247 .00000090 00000-0 10000-3 0 7322",
"2 09880 64.1526 313.1296 6546925 103.4683 305.3980 2.00754276 13047",
),
"circular_implied_zero": (
"1 20500U 90001A 90001.00000000 .00000000 00000-0 00000-0 0 00",
"2 20500 82.0000 100.0000 0000000 90.0000 90.0000 14.90000000 13",
),
"retrograde": (
"1 20600U 90002B 12345.50000000 -.00001234 00000-0 12345-6 0 9991",
"2 20600 120.0000 200.0000 0010000 30.0000 330.0000 15.00000000 12341",
),
"two_digit_year_1999": (
"1 10000U 99001A 99365.00000000 .00000000 00000-0 00000-0 0 05",
"2 10000 45.0000 10.0000 0001000 0.0000 0.0000 14.00000000 09",
),
"with_name_line": (
"1 12345U 80001C 20001.00000000 .00010000 00000-0 00000-0 0 9998",
"2 12345 60.0000 30.0000 0002000 100.0000 200.0000 12.00000000 12344",
),
}
def checksum(line: str) -> int:
"""Returns the modulo ten checksum of a line from its definition."""
total = 0
for character in line[:68]:
if character == "-":
total += 1
elif character.isdigit():
total += int(character)
return total % 10
def field(line: str, start: int, end: int) -> str:
"""Returns a slice of a line."""
return line[start:end]
def parse_exponential(text: str) -> float:
"""Reads a NORAD assumed decimal point exponential.
The second derivative of the mean motion and the drag term are stored
with the decimal point assumed before the first digit and the exponent
written without an ``E``: ``-11606-4`` is ``-0.11606e-4``. A leading
``+`` or ``-`` before the mantissa is the sign of the value, and the sign
before the exponent is the sign of the exponent.
"""
text = text.strip()
if not text:
return 0.0
# The exponent is introduced by the last sign, once a mantissa digit is
# in hand, so scan from the end.
index = len(text) - 1
while index > 0 and text[index] not in "+-":
index -= 1
mantissa = text[:index].strip()
exponent = text[index:]
if mantissa.startswith("-"):
sign = -1.0
mantissa = mantissa[1:]
elif mantissa.startswith("+"):
sign = 1.0
mantissa = mantissa[1:]
else:
sign = 1.0
if not mantissa:
mantissa = "0"
if not exponent:
return 0.0
return sign * float("0." + mantissa) * 10.0 ** int(exponent)
def parse_line_one(line: str) -> dict:
"""Parses the first line by column index."""
epoch = field(line, 18, 32).strip()
year = int(epoch[:2])
fraction = float(epoch[2:])
# The two digit year expands with the catalogue convention: 57 to 99 is
# the twentieth century and 00 to 56 the twenty first.
century = 1900 if year >= 57 else 2000
return {
"satellite_number": int(field(line, 2, 7)),
"classification": field(line, 7, 8).strip(),
"international_designator": field(line, 9, 17).strip(),
"epoch_year": century + year,
"epoch_fraction": fraction,
"mean_motion_dot": float(field(line, 33, 43)),
"mean_motion_double_dot": parse_exponential(field(line, 44, 52)),
"bstar": parse_exponential(field(line, 53, 61)),
"element_set_number": int(field(line, 65, 68)),
"checksum": checksum(line),
}
def parse_line_two(line: str) -> dict:
"""Parses the second line by column index."""
# The eccentricity is stored as a leading decimal: the column holds the
# fractional digits and the decimal point is implied before the first.
eccentricity = float("0." + field(line, 26, 33).strip())
return {
"inclination_deg": float(field(line, 8, 16)),
"right_ascension_deg": float(field(line, 17, 25)),
"eccentricity": eccentricity,
"argument_of_perigee_deg": float(field(line, 34, 42)),
"mean_anomaly_deg": float(field(line, 43, 51)),
"mean_motion": float(field(line, 52, 63)),
"revolution_number": int(field(line, 63, 68)),
"checksum": checksum(line),
}
def main(argv: list[str]) -> int:
path = Path(argv[1]) if len(argv) > 1 else DEFAULT_INPUT
if not path.exists():
print(f"missing input file: {path}", file=sys.stderr)
print(
"generate it with: cargo run -p apsis-rs --features orbit "
"--example dump_tle > " + str(path),
file=sys.stderr,
)
return 2
with path.open(newline="") as handle:
rows = list(csv.DictReader(handle))
if not rows:
print("input file has no data rows", file=sys.stderr)
return 2
failures: list[str] = []
compared = 0
for row in rows:
name = row["name"]
if name not in ELEMENT_SETS:
failures.append(f"{name}: not in the reference set")
continue
first, second = ELEMENT_SETS[name]
one = parse_line_one(first)
two = parse_line_two(second)
def check(field_name: str, expected, actual, tolerance=ABSOLUTE_TOLERANCE) -> None:
if isinstance(expected, float):
if abs(expected - actual) > tolerance:
failures.append(f"{name}.{field_name}: {actual} against {expected}")
elif expected != actual:
failures.append(f"{name}.{field_name}: {actual!r} against {expected!r}")
check("satellite_number", one["satellite_number"], int(row["satellite_number"]))
check("classification", one["classification"], row["classification"])
check(
"international_designator",
one["international_designator"],
row["international_designator"],
)
check("epoch_year", one["epoch_year"], int(row["epoch_year"]))
check(
"mean_motion_dot",
one["mean_motion_dot"],
float(row["e_mean_motion_dot"]),
EXPONENT_TOLERANCE,
)
check(
"mean_motion_double_dot",
one["mean_motion_double_dot"],
float(row["e_mean_motion_double_dot"]),
EXPONENT_TOLERANCE,
)
check("bstar", one["bstar"], float(row["bstar"]), EXPONENT_TOLERANCE)
check(
"element_set_number",
one["element_set_number"],
int(row["element_set_number"]),
)
check("inclination_deg", two["inclination_deg"], float(row["inclination_deg"]))
check(
"right_ascension_deg",
two["right_ascension_deg"],
float(row["right_ascension_deg"]),
)
check("eccentricity", two["eccentricity"], float(row["eccentricity"]))
check(
"argument_of_perigee_deg",
two["argument_of_perigee_deg"],
float(row["argument_of_perigee_deg"]),
)
check("mean_anomaly_deg", two["mean_anomaly_deg"], float(row["mean_anomaly_deg"]))
check("mean_motion", two["mean_motion"], float(row["mean_motion"]))
check(
"revolution_number",
two["revolution_number"],
int(row["revolution_number"]),
)
check("line1_checksum", one["checksum"], int(row["line1_checksum"]))
check("line2_checksum", two["checksum"], int(row["line2_checksum"]))
compared += 1
print(f"element sets compared: {compared}")
print(f"fields per set: 17")
for failure in failures:
print(f" {failure}")
if failures:
print("result: FAIL")
return 1
print("result: pass")
return 0
if __name__ == "__main__":
raise SystemExit(main(sys.argv))