fdars_core/depth/
mod.rs

1//! Depth measures for functional data.
2//!
3//! This module provides various depth measures for assessing the centrality
4//! of functional observations within a reference sample.
5
6use crate::matrix::FdMatrix;
7use crate::maybe_par_chunks_mut_enumerate;
8use rand::prelude::*;
9use rand_distr::StandardNormal;
10
11pub mod band;
12pub mod dispatch;
13pub mod erl;
14pub mod extremal;
15pub mod fraiman_muniz;
16pub mod half_region;
17pub mod hypo_epi;
18pub mod linf;
19pub mod modal;
20pub mod random_projection;
21pub mod random_tukey;
22pub mod rpd;
23pub mod spatial;
24pub mod tvd;
25
26#[cfg(test)]
27mod tests;
28
29// Re-export all public functions
30pub use band::{band_1d, modified_band_1d, modified_epigraph_index_1d};
31pub use dispatch::{functional_boxplot, functional_depth, DepthMethod, FunctionalBoxplotResult};
32pub use erl::extreme_rank_length_depth_1d;
33pub use extremal::extremal_depth_1d;
34// The `_2d` shims are deprecated back-compat re-exports (API-03); re-exporting a deprecated item
35// emits a deprecation warning, so allow it on these back-compat re-export lines.
36#[allow(deprecated)]
37pub use fraiman_muniz::{fraiman_muniz, fraiman_muniz_1d, fraiman_muniz_2d};
38pub use half_region::{half_region_depth_1d, modified_half_region_depth_1d};
39pub use hypo_epi::{epigraph_index_1d, hypograph_index_1d, modified_hypograph_index_1d};
40pub use linf::linfinity_depth_1d;
41#[allow(deprecated)]
42pub use modal::{modal, modal_1d, modal_2d};
43#[allow(deprecated)]
44pub use random_projection::{
45    random_projection, random_projection_1d, random_projection_1d_seeded, random_projection_2d,
46};
47#[allow(deprecated)]
48pub use random_tukey::{random_tukey, random_tukey_1d, random_tukey_1d_seeded, random_tukey_2d};
49pub use rpd::{rpd_depth_1d, rpd_depth_1d_seeded};
50pub use spatial::{
51    functional_spatial_1d, functional_spatial_2d, kernel_functional_spatial_1d,
52    kernel_functional_spatial_2d,
53};
54pub use tvd::{total_variation_depth_1d, TvdMssResult};
55
56// ---------------------------------------------------------------------------
57// Shared helpers
58// ---------------------------------------------------------------------------
59
60/// Generate `nproj` unit-norm random projection vectors of dimension `m`.
61///
62/// Returns a flat buffer of length `nproj * m` where projection `p` occupies
63/// `[p*m .. (p+1)*m]`.
64///
65/// If `seed` is Some, uses a deterministic RNG seeded from the given value.
66pub(super) fn generate_random_projections(nproj: usize, m: usize, seed: Option<u64>) -> Vec<f64> {
67    let mut rng: Box<dyn RngCore> = match seed {
68        Some(s) => Box::new(StdRng::seed_from_u64(s)),
69        None => Box::new(rand::thread_rng()),
70    };
71    let mut projections = vec![0.0; nproj * m];
72    for p_idx in 0..nproj {
73        let base = p_idx * m;
74        let mut norm_sq = 0.0;
75        for t in 0..m {
76            let v: f64 = rng.sample(StandardNormal);
77            projections[base + t] = v;
78            norm_sq += v * v;
79        }
80        let inv_norm = 1.0 / norm_sq.sqrt();
81        for t in 0..m {
82            projections[base + t] *= inv_norm;
83        }
84    }
85    projections
86}
87
88/// Project each reference curve onto each projection direction and sort.
89///
90/// Returns a flat buffer of length `nproj * nori` where the sorted projections
91/// for direction `p` occupy `[p*nori .. (p+1)*nori]`.
92pub(super) fn project_and_sort_reference(
93    data_ori: &FdMatrix,
94    projections: &[f64],
95    nproj: usize,
96    nori: usize,
97    m: usize,
98) -> Vec<f64> {
99    let mut sorted = vec![0.0; nproj * nori];
100    maybe_par_chunks_mut_enumerate!(sorted, nori, |(p_idx, spo): (usize, &mut [f64])| {
101        let proj = &projections[p_idx * m..(p_idx + 1) * m];
102        for j in 0..nori {
103            let mut dot = 0.0;
104            for t in 0..m {
105                dot += data_ori[(j, t)] * proj[t];
106            }
107            spo[j] = dot;
108        }
109        spo.sort_unstable_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal));
110    });
111    sorted
112}
113
114/// Shared implementation for random projection-based depth measures.
115///
116/// Generates `nproj` random projections, projects both object and reference
117/// curves to scalars, and computes univariate depth via binary-search ranking.
118/// The `aggregate` and `finalize` closures control how per-projection depths
119/// are combined (e.g. average for RP depth, minimum for Tukey depth).
120pub(super) fn random_depth_core(
121    data_obj: &FdMatrix,
122    data_ori: &FdMatrix,
123    nproj: usize,
124    seed: Option<u64>,
125    init: f64,
126    aggregate: impl Fn(f64, f64) -> f64 + Sync,
127    finalize: impl Fn(f64, usize) -> f64 + Sync,
128) -> Vec<f64> {
129    use crate::iter_maybe_parallel;
130    #[cfg(feature = "parallel")]
131    use rayon::iter::ParallelIterator;
132
133    let nobj = data_obj.nrows();
134    let nori = data_ori.nrows();
135    let m = data_obj.ncols();
136
137    if nobj == 0 || nori == 0 || m == 0 || nproj == 0 {
138        return Vec::new();
139    }
140
141    let projections = generate_random_projections(nproj, m, seed);
142    let sorted_proj_ori = project_and_sort_reference(data_ori, &projections, nproj, nori, m);
143    let denom = nori as f64 + 1.0;
144
145    iter_maybe_parallel!(0..nobj)
146        .map(|i| {
147            let mut acc = init;
148            for p_idx in 0..nproj {
149                let proj = &projections[p_idx * m..(p_idx + 1) * m];
150                let sorted_ori = &sorted_proj_ori[p_idx * nori..(p_idx + 1) * nori];
151
152                let mut proj_i = 0.0;
153                for t in 0..m {
154                    proj_i += data_obj[(i, t)] * proj[t];
155                }
156
157                let below = sorted_ori.partition_point(|&v| v < proj_i);
158                let above = nori - sorted_ori.partition_point(|&v| v <= proj_i);
159                let depth = (below.min(above) as f64 + 1.0) / denom;
160                acc = aggregate(acc, depth);
161            }
162            finalize(acc, nproj)
163        })
164        .collect()
165}
fdars_core/depth/mod.rs

fdars_core/depth/
mod.rs
