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| author | Ethan Werner <mail@ethanwerner.com> | 2026-07-01 09:42:39 +0400 |
|---|---|---|
| committer | Ethan Werner <mail@ethanwerner.com> | 2026-07-01 09:42:39 +0400 |
| commit | 07e18043145f3d91c8ea7ec3ad41b3c905585277 (patch) | |
| tree | 2bdeae46973f4bdfce263679a4008ac768011f28 /lib/random_walk_index.c | |
initial commit: ts time series analysis library v0.1.0
- 354 financial and mathematical time-series indicators
- Uniform C11 API with consistent function signatures
- 349 passing tests with -Werror
- Static and shared library builds
- pkg-config integration
- Python bindings
- Fuzzing and sanitizer support
- Security hardening flags
Diffstat (limited to 'lib/random_walk_index.c')
| -rw-r--r-- | lib/random_walk_index.c | 64 |
1 files changed, 64 insertions, 0 deletions
diff --git a/lib/random_walk_index.c b/lib/random_walk_index.c new file mode 100644 index 0000000..b4375e5 --- /dev/null +++ b/lib/random_walk_index.c @@ -0,0 +1,64 @@ +// Random Walk Index +// +// random_walk_index +// +// Random Walk Index +// +// +// +// Inputs: 1 +// Outputs: 1 +// Constants: 0 + + +#include <math.h> +#include "ts.h" + +typedef struct { + uint_t k; +} ts_random_walk_index_params_t; + +ts_parameter_t const ts_random_walk_index_p = { .n_inputs = 1, .n_outputs = 1, .n_constants = 1, .params_size = sizeof(ts_random_walk_index_params_t) }; + +uint_t ts_random_walk_index_offset( ts_constant_t const *c ) +{ + ( void )c; + return ( c ? ((ts_random_walk_index_params_t *)c)->k : 0 ); +} + +int ts_random_walk_index( + fp_t * const *y, uint_t y_n, + fp_t const * const *x, uint_t x_n, + uint_t n, ts_constant_t const *c +) +{ + TS_PROLOGUE( ts_random_walk_index_p ); + if ( !c ) return -1; + uint_t k = ((ts_random_walk_index_params_t *)c)->k; + if (k == 0 || n < k + 1) return -1; + + fp_t sum_abs = 0; + fp_t sum_net = 0; + + for ( uint_t i = 0; i < k; ++i ) + { + fp_t change = x[0][i + 1] - x[0][i]; + sum_abs += fabs( change ); + sum_net += change; + } + + y[0][k] = sum_net == 0 ? 0 : sum_abs / sum_net; + + for ( uint_t i = k + 1; i < n; ++i ) + { + fp_t change_new = x[0][i] - x[0][i - 1]; + fp_t change_old = x[0][i - k] - x[0][i - k - 1]; + + sum_abs = sum_abs - fabs( change_old ) + fabs( change_new ); + sum_net = sum_net - change_old + change_new; + + y[0][i] = sum_net == 0 ? 0 : sum_abs / sum_net; + } + return 0; +} + |