Crate Hierarchy

changepoint-doctor is organized as a Cargo workspace with 10 crates, each with a focused responsibility.

Dependency graph

        graph TD
    core[cpd-core]
    costs[cpd-costs]
    preprocess[cpd-preprocess]
    offline[cpd-offline]
    online[cpd-online]
    doctor[cpd-doctor]
    python[cpd-python]
    cli[cpd-cli]
    bench[cpd-bench]
    eval[cpd-eval]

    costs --> core
    preprocess --> core
    offline --> core
    offline --> costs
    online --> core
    online --> costs
    doctor --> core
    doctor --> costs
    doctor --> offline
    doctor --> online
    doctor --> preprocess
    python --> core
    python --> costs
    python --> offline
    python --> online
    python --> doctor
    python --> preprocess
    cli --> doctor
    bench --> core
    bench --> costs
    bench --> offline
    bench --> online
    eval --> core
    eval --> offline
    eval --> online
    

Per-crate responsibilities

cpd-core

Foundation types shared across the workspace:

• TimeSeriesView<'a>: zero-copy borrowed view over signal data with layout, missing policy, and time index

• CpdError: unified error type with variants for invalid input, resource limits, cancellation, and algorithm failures

• ExecutionContext: constraints, cancellation token, budget mode, repro mode, progress/telemetry sinks

• Constraints: min_segment_len, jump, max_change_points, budget controls

• OfflineChangePointResult, OnlineStepResult: result types

• Diagnostics, PruningStats: metadata

• ReproMode: strict/balanced/fast reproducibility contracts

• Numeric utilities: log_sum_exp, stable_mean, Kahan summation, prefix sums

cpd-costs

All cost model implementations:

• CostModel trait and CachedCost<C> wrapper

• Implementations: CostL2Mean, CostL1Median, CostNormalMeanVar, CostNormalFullCov, CostNIGMarginal, CostAR, CostBernoulli, CostPoissonRate, CostRank, CostCosine

cpd-preprocess

Signal preprocessing pipeline:

• Detrend (linear, polynomial)

• Deseasonalize (differencing, STL-like)

• Winsorize

• Robust scale (MAD-based)

cpd-offline

Offline (batch) detector implementations:

• Pelt, BinSeg, Fpop, Dynp (SegNeigh), Wbs, BottomUp, SlidingWindow

• Each implements the OfflineDetector trait from cpd-core

• Experimental: KernelCpd, GpCpd, ArgpCpd (feature-gated)

cpd-online

Online (streaming) detector implementations:

• Bocpd with conjugate observation models (GaussianNigPrior, BernoulliBetaPrior, PoissonGammaPrior)

• Cusum, PageHinkley

• Each implements the OnlineDetector trait from cpd-core

• Checkpoint/restore via save_state() / load_state()

cpd-doctor

Recommendation engine:

• Signal diagnostics (distribution shape, autocorrelation, seasonality, missing patterns)

• Calibration families and per-family scoring

• Pipeline ranking with confidence intervals

• Preprocessing recommendations

• Pipeline execution helpers

cpd-python

PyO3 extension module:

• Python class wrappers for all detectors

• NumPy array interop for TimeSeriesView

• GIL-release strategy for batched operations

• Result serialization/deserialization

• Module: cpd._cpd_rs

cpd-cli

Command-line interface:

• cpd doctor for recommendation workflows

• CSV input, JSON output

cpd-bench

Criterion benchmark harness:

• Offline detector benchmarks (various n, k, cost combinations)

• Cost model benchmarks (univariate + multivariate)

• SegNeigh scaling benchmarks

cpd-eval

Evaluation framework:

• Parity testing against reference implementations (ruptures, bayesian_changepoint_detection)

• Corpus management and metric computation

Build configuration

Setting	Value
Rust edition	2024
MSRV	1.93
Resolver	2
License	MIT OR Apache-2.0
PyO3	0.24.1 with abi3-py39

Feature flags

Feature	Crates affected	Description
rayon	cpd-offline	Parallel execution for supported algorithms
serde	cpd-core, cpd-costs, cpd-offline, cpd-online, cpd-doctor	JSON serialization
tracing	cpd-core, cpd-offline, cpd-online	Structured logging
simd	cpd-costs	SIMD-accelerated numeric kernels
kernel	cpd-offline, cpd-costs	Kernel-based detection (experimental)
kernel-approx	cpd-offline, cpd-costs	Approximate kernel methods
blas	cpd-costs	BLAS-accelerated linear algebra
gp	cpd-offline, cpd-costs	Gaussian process detection (experimental)
preprocess	cpd-preprocess, cpd-doctor, cpd-python	Signal preprocessing
repro-strict	cpd-costs	Deterministic numeric paths for strict mode