Module reference_examples 

Reference Gallery Examples

This page tracks Rust ruviz examples inspired by the upstream pybaselines gallery at https://pybaselines.readthedocs.io/en/latest/generated/examples/index.html. pybaselines is credited as a documentation and behavioral reference only; the example code and rendered outputs are native Rust implementations.

The examples write PNGs to docs/assets/ruviz/. The generated PNGs are tracked for Markdown preview and excluded from Cargo packages.

See GALLERY.md for the generated-output index and the working Rust source file that creates each output set.

cargo run --example ruviz_lam_effects
cargo run --example ruviz_gallery_basic
cargo run --release --example ruviz_gallery_whittaker_sweeps
cargo run --release --example ruviz_gallery_whittaker_solver_timings
cargo run --release --example ruviz_gallery_beads_preprocessing
cargo run --release --example ruviz_gallery_pspline_whittaker
cargo run --release --example ruviz_gallery_spline_lam_vs_num_knots
cargo run --release --example ruviz_gallery_whittaker_2d_dof

Coverage

Upstream example	Rust example	Parameter status
general/plot_algorithm_convergence.py	ruviz_gallery_basic	Uses lam=5e6, tol=1e-3, max_iter=20 and 100; Rust now exposes and renders full tol_history diagnostics for the AsLS and asPLS fits used in this example.
general/plot_masked_data.py	ruviz_gallery_basic	Uses the same synthetic data, mask region, lam=1e5, half_window=35, linear interpolation, mask-aware arPLS demonstration, and arPLS weighted-interpolation pass using the final arPLS weights.
general/plot_noisy_data.py	ruviz_gallery_basic	Uses the same signal, baseline, noise scale, 11-point smoothing, modpoly(poly_order=3), and imodpoly(poly_order=3, num_std=0.7) settings.
general/plot_padding.py	ruviz_gallery_basic	Uses half_window=80, num_points=1000, pad_len=161, and the same padding mode names.
general/plot_padding_extrapolate.py	ruviz_gallery_basic	Uses num_points=1000, pad_len=100, and extrapolate_window values 1, 100, and [100, 40].
general/plot_reuse_Baseline.py	ruviz_gallery_basic	Uses matching num_points=1000 data and the same six method parameter sets: penalized_poly(poly_order=4), mixture_model(lam=1e5), iarpls(lam=1e5), mor(half_window=30), ria(half_window=20), and std_distribution(half_window=25). The timing comparison is represented by Rust’s allocation/workspace reuse patterns rather than pybaselines’ reusable Baseline object.
general/plot_sorted_data.py	ruviz_gallery_basic	Uses matching data and iarpls(lam=1e6) on forward and reversed input.
whittaker/plot_lam_effects.py	ruviz_lam_effects	Uses matching signal, baseline, noise scale, arPLS, and lambda values 1, 1e3, 1e6, and 1e10.
whittaker/plot_lam_vs_data_size.py	ruviz_gallery_whittaker_sweeps	Uses the same _make_data baseline formulas, data sizes [499, 1045, 2186, 4573, 9563, 20000], algorithms, coarse/fine lambda search, tol=1e-2, and max_iter=50. Candidate lambda values that fail a solve are skipped, matching the upstream example behavior.
whittaker/plot_whittaker_solvers.py	ruviz_gallery_whittaker_solver_timings	Uses the same _make_data default signal, lambda equation, data sizes [499, 935, 1748, 3270, 6115, 11437, 21388, 40000], repeats=25, AsLS, max_iter=8, and tol=-1 to force fixed iterations. The Rust-native timing comparison is allocating asls vs reusable-workspace asls_into, since this crate has one native pentadiagonal solver instead of SciPy/pentapy backend selection.
morphological/plot_half_window_effects.py	ruviz_gallery_basic	Uses matching data and half_window values 30, 60, and 120 through Rust full-window sizes 61, 121, and 241.
spline/plot_lam_vs_num_knots.py	ruviz_gallery_spline_lam_vs_num_knots	Uses the same exponential _make_data baseline, mixture_model, diff_order=2, knot counts [20, 53, 141, 376, 1000], data sizes [500, 1045, 2186, 4573, 9563, 20000], coarse/fine lambda search, tol=1e-2, and max_iter=50.
spline/plot_pspline_whittaker.py	ruviz_gallery_pspline_whittaker	Uses the same exponential _make_data baseline, arpls, pspline_arpls, data sizes [499, 1045, 2186, 4573, 9563, 20000], coarse/fine lambda search, tol=1e-2, and max_iter=50.
classification/plot_classifier_masks.py	ruviz_gallery_basic	Uses matching data, std_distribution, half_window values 15 and 45, smooth_half_window=10, and renders the returned baseline masks as signal-context ribbons instead of standalone 0/1 traces.
classification/plot_fastchrom_threshold.py	ruviz_gallery_basic	Uses matching data, half_window=15, fixed threshold 1.5, default 15th-percentile threshold, and the same median fallback used by the upstream example when scikit-image is unavailable; renders the returned masks as signal-context ribbons plus rolling standard-deviation thresholds.
misc/plot_beads_preprocessing.py	ruviz_gallery_beads_preprocessing	Uses the same 1000-point grid, signal, three baseline formulas, noise scale, endpoint parabola preprocessing formula, and BEADS parameter sets. The preprocessing figure shows the endpoint parabola against the raw data and known baseline to avoid overlaying parabola-subtracted data on the raw intensity scale. The Rust implementation now uses a banded BEADS solve for this workload.
optimizers/plot_custom_bc_1_whittaker.py	ruviz_gallery_basic	Uses matching data, lam_flexible=1e2, lam_stiff=5e5, crossover_index near x=160, sampling=15, and smoothing lam=1e1.
two_d/plot_along_axes_1d_baseline.py	ruviz_gallery_basic	Uses matching data and the same axis-1 row-wise pspline_arpls correction with lam=1e4; this is implemented directly in the gallery example because the Rust individual_axes helper is intentionally narrower than pybaselines’ dynamic method dispatch.
two_d/plot_whittaker_2d_dof.py	ruviz_gallery_whittaker_2d_dof	Uses the same 100x100 grid, gaussian2d peak parameters, polynomial and sinusoidal baselines, lam_poly=(1e2, 1e4), lam_sine=(1e2, 1e0), analytical solves, eigen-count cases (40, 40), (10, 4), (8, 35), (3, 3), and (5, 12), return_dof=true, tol=1e-3, and max_iter=50. Rust exposes this through a reduced eigenspace arpls_eigen API and returns a diagonal DOF estimate for the plotted eigenvector-selection surface.

Generated examples should cite pybaselines as a behavioral and documentation reference only. The Rust implementation does not copy pybaselines implementation code.