18170d7daf
All ADR-017 integration points now implemented: --- wifi-densepose-signal --- 1. subcarrier_selection.rs — ruvector-mincut: mincut_subcarrier_partition uses DynamicMinCut to dynamically partition sensitive/insensitive subcarriers via O(n^1.5 log n) graph bisection. Tests: 8 passed. 2. spectrogram.rs — ruvector-attn-mincut: gate_spectrogram applies self-attention (Q=K=V, configurable lambda) over STFT time frames to suppress noise/multipath interference. Tests: 2 added. 3. bvp.rs — ruvector-attention: attention_weighted_bvp uses ScaledDotProductAttention for sensitivity-weighted BVP aggregation across subcarriers (vs uniform sum). Tests: 2 added. 4. fresnel.rs — ruvector-solver: solve_fresnel_geometry estimates unknown TX-body-RX geometry from multi-subcarrier Fresnel observations via NeumannSolver. Regularization scaled to inv_w_sq_sum * 0.5 for guaranteed convergence (spectral radius = 0.667). Tests: 10 passed. --- wifi-densepose-mat --- 5. localization/triangulation.rs — ruvector-solver: solve_tdoa_triangulation solves multi-AP TDoA positioning via 2×2 NeumannSolver normal equations (Cramer's rule fallback). O(1) in AP count. Tests: 2 added. 6. detection/breathing.rs — ruvector-temporal-tensor: CompressedBreathingBuffer uses TemporalTensorCompressor with tiered quantization for 50-75% CSI amplitude memory reduction (13.4→3.4-6.7 MB/zone). Tests: 2 added. 7. detection/heartbeat.rs — ruvector-temporal-tensor: CompressedHeartbeatSpectrogram stores per-bin TemporalTensorCompressor for micro-Doppler spectrograms with hot/warm/cold tiers. Tests: 1 added. Cargo.toml: ruvector deps optional in MAT crate (feature = "ruvector"), enabled by default. Prevents --no-default-features regressions. Pre-existing MAT --no-default-features failures are unrelated (api/dto.rs serde gating, pre-existed before this PR). Test summary: 144 MAT lib tests + 91 signal tests = all passed. cargo check wifi-densepose-mat (default features): 0 errors. cargo check wifi-densepose-signal: 0 errors. https://claude.ai/code/session_01BSBAQJ34SLkiJy4A8SoiL4
76 lines
1.9 KiB
TOML
76 lines
1.9 KiB
TOML
[package]
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name = "wifi-densepose-mat"
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version = "0.1.0"
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edition = "2021"
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authors = ["WiFi-DensePose Team"]
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description = "Mass Casualty Assessment Tool - WiFi-based disaster survivor detection"
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license = "MIT OR Apache-2.0"
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repository = "https://github.com/ruvnet/wifi-densepose"
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keywords = ["wifi", "disaster", "rescue", "detection", "vital-signs"]
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categories = ["science", "algorithms"]
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[features]
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default = ["std", "api", "ruvector"]
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ruvector = ["dep:ruvector-solver", "dep:ruvector-temporal-tensor"]
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std = []
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api = ["dep:serde", "chrono/serde", "geo/use-serde"]
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portable = ["low-power"]
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low-power = []
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distributed = ["tokio/sync"]
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drone = ["distributed"]
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serde = ["dep:serde", "chrono/serde", "geo/use-serde"]
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[dependencies]
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# Workspace dependencies
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wifi-densepose-core = { path = "../wifi-densepose-core" }
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wifi-densepose-signal = { path = "../wifi-densepose-signal" }
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wifi-densepose-nn = { path = "../wifi-densepose-nn" }
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ruvector-solver = { workspace = true, optional = true }
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ruvector-temporal-tensor = { workspace = true, optional = true }
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# Async runtime
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tokio = { version = "1.35", features = ["rt", "sync", "time"] }
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async-trait = "0.1"
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# Web framework (REST API)
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axum = { version = "0.7", features = ["ws"] }
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futures-util = "0.3"
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# Error handling
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thiserror = "1.0"
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anyhow = "1.0"
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# Serialization
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serde = { version = "1.0", features = ["derive"], optional = true }
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serde_json = "1.0"
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# Time handling
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chrono = { version = "0.4", features = ["serde"] }
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# Math and signal processing
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num-complex = "0.4"
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ndarray = "0.15"
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rustfft = "6.1"
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# Utilities
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uuid = { version = "1.6", features = ["v4", "serde"] }
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tracing = "0.1"
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parking_lot = "0.12"
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# Geo calculations
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geo = "0.27"
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[dev-dependencies]
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tokio-test = "0.4"
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criterion = { version = "0.5", features = ["html_reports"] }
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proptest = "1.4"
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approx = "0.5"
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[[bench]]
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name = "detection_bench"
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harness = false
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[package.metadata.docs.rs]
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all-features = true
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rustdoc-args = ["--cfg", "docsrs"]
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