mirror of
https://github.com/ruvnet/RuView
synced 2026-08-10 20:31:42 +00:00
4b1005524e
- Add 154 missing vendor files (gitignore was filtering them) - vendor/midstream: 564 files (was 561) - vendor/sublinear-time-solver: 1190 files (was 1039) - Add ESP32 edge processing (ADR-039): presence, vitals, fall detection - Add WASM programmable sensing (ADR-040/041) with wasm3 runtime - Add firmware CI workflow (.github/workflows/firmware-ci.yml) - Add wifi-densepose-wasm-edge crate for edge WASM modules - Update sensing server, provision.py, UI components Co-Authored-By: claude-flow <ruv@ruv.net>
98 lines
2.7 KiB
TypeScript
98 lines
2.7 KiB
TypeScript
/**
|
|
* Temporal Attractor Studio Handlers
|
|
* WASM-based implementation for chaos analysis tools
|
|
*/
|
|
export declare const temporalAttractorHandlers: {
|
|
chaos_analyze: (args: any) => Promise<{
|
|
lambda: any;
|
|
is_chaotic: any;
|
|
chaos_level: any;
|
|
lyapunov_time: any;
|
|
doubling_time: any;
|
|
safe_prediction_steps: any;
|
|
pairs_found: any;
|
|
interpretation: string;
|
|
}>;
|
|
temporal_delay_embed: (args: any) => Promise<{
|
|
original_length: any;
|
|
embedded_vectors: number;
|
|
embedding_dim: any;
|
|
tau: any;
|
|
data: any;
|
|
}>;
|
|
temporal_predict: (args: any) => Promise<{
|
|
initialized: boolean;
|
|
reservoir_size: any;
|
|
training_complete?: undefined;
|
|
mse?: undefined;
|
|
n_samples?: undefined;
|
|
input?: undefined;
|
|
prediction?: undefined;
|
|
trajectory?: undefined;
|
|
n_steps?: undefined;
|
|
} | {
|
|
training_complete: boolean;
|
|
mse: any;
|
|
n_samples: any;
|
|
initialized?: undefined;
|
|
reservoir_size?: undefined;
|
|
input?: undefined;
|
|
prediction?: undefined;
|
|
trajectory?: undefined;
|
|
n_steps?: undefined;
|
|
} | {
|
|
input: any;
|
|
prediction: any;
|
|
initialized?: undefined;
|
|
reservoir_size?: undefined;
|
|
training_complete?: undefined;
|
|
mse?: undefined;
|
|
n_samples?: undefined;
|
|
trajectory?: undefined;
|
|
n_steps?: undefined;
|
|
} | {
|
|
input: any;
|
|
trajectory: any;
|
|
n_steps: any;
|
|
initialized?: undefined;
|
|
reservoir_size?: undefined;
|
|
training_complete?: undefined;
|
|
mse?: undefined;
|
|
n_samples?: undefined;
|
|
prediction?: undefined;
|
|
}>;
|
|
temporal_fractal_dimension: (args: any) => Promise<{
|
|
fractal_dimension: any;
|
|
interpretation: string;
|
|
}>;
|
|
temporal_regime_changes: (args: any) => Promise<{
|
|
n_windows: any;
|
|
lyapunov_values: any;
|
|
changes_detected: boolean;
|
|
max_lambda: number;
|
|
min_lambda: number;
|
|
variance: number;
|
|
}>;
|
|
temporal_generate_attractor: (args: any) => Promise<{
|
|
system: any;
|
|
n_points: any;
|
|
dimensions: any;
|
|
dt: any;
|
|
data: any;
|
|
}>;
|
|
temporal_interpret_chaos: (args: any) => Promise<any>;
|
|
temporal_recommend_parameters: (args: any) => Promise<any>;
|
|
temporal_attractor_pullback: (args: any) => Promise<{
|
|
ensemble_size: any;
|
|
evolution_time: any;
|
|
snapshots: any[];
|
|
drift: any[];
|
|
convergence_rate: number;
|
|
}>;
|
|
temporal_kaplan_yorke_dimension: (args: any) => Promise<{
|
|
kaplan_yorke_dimension: number;
|
|
lyapunov_spectrum: any;
|
|
interpretation: string;
|
|
}>;
|
|
};
|