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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/kaufman_adaptive_ma.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/kaufman_adaptive_ma.c')
| -rw-r--r-- | lib/kaufman_adaptive_ma.c | 61 |
1 files changed, 61 insertions, 0 deletions
diff --git a/lib/kaufman_adaptive_ma.c b/lib/kaufman_adaptive_ma.c new file mode 100644 index 0000000..f56c6a1 --- /dev/null +++ b/lib/kaufman_adaptive_ma.c @@ -0,0 +1,61 @@ +// Kaufman Adaptive Ma +// +// kaufman_adaptive_ma +// +// Kaufman Adaptive Moving Average +// +// AMA based on efficiency ratio +// +// Inputs: 1 +// Outputs: 1 +// Constants: 1 + + +#include <math.h> +#include "ts.h" + +typedef struct { + uint_t k; +} ts_kaufman_adaptive_ma_params_t; + +ts_parameter_t const ts_kaufman_adaptive_ma_p = { .n_inputs = 1, .n_outputs = 1, .n_constants = 1, .params_size = sizeof(ts_kaufman_adaptive_ma_params_t) }; + +uint_t ts_kaufman_adaptive_ma_offset( ts_constant_t const *c ) +{ + ( void )c; + return ( c ? ((ts_kaufman_adaptive_ma_params_t *)c)->k : 0 ); +} + +int ts_kaufman_adaptive_ma( + 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_kaufman_adaptive_ma_p ); + if ( !c ) return -1; + uint_t k = ((ts_kaufman_adaptive_ma_params_t *)c)->k; + if (k == 0 || n < k) return -1; + + fp_t ama = x[0][0]; + fp_t sm = 2.0 / ((fp_t)k + 1.0); + fp_t sn = 2.0 / (sqrt((fp_t)k) + 1.0); + + for (uint_t i = k; i < n; ++i) + { + fp_t price_change = fabs(x[0][i] - x[0][i - k]); + fp_t noise = 0; + for (uint_t j = i - k + 1; j <= i; ++j) + noise += fabs(x[0][j] - x[0][j - 1]); + + fp_t er = noise != 0 ? price_change / noise : 0; + fp_t er_sq = er * er; + fp_t sc = er_sq * (sn - sm) + sm; + sc = sc * sc; + + ama = ama + sc * (x[0][i] - ama); + y[0][i] = ama; + } + return 0; +} + |