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

1 files changed, 84 insertions, 0 deletions

diff --git a/lib/adx.c b/lib/adx.c
new file mode 100644
index 0000000..505732b
--- /dev/null
+++ b/lib/adx.c
@@ -0,0 +1,84 @@
+// Adx
+//
+// adx
+//
+// Time series function
+//
+// See implementation
+//
+// Inputs:    4
+// Outputs:   4
+// Constants: 1
+
+
+#include <math.h>
+#include <stdint.h>
+#include "ts.h"
+
+typedef struct {
+    uint_t k;
+} ts_adx_params_t;
+
+ts_parameter_t const ts_adx_p = { .n_inputs = 4, .n_outputs = 4, .n_constants = 1, .params_size = sizeof(ts_adx_params_t) };
+
+uint_t ts_adx_offset( ts_constant_t const *c )
+{
+	( void )c;
+	return ( c ? ((ts_adx_params_t *)c)->k + 1 : 0 );
+}
+
+int ts_adx(
+	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_adx_p );
+	if ( !c ) return -1;
+	TS_CHECK_INPUT(x, x_n, n);
+	uint_t k = ((ts_adx_params_t *)c)->k;
+	if (k == 0) return -1;
+
+	fp_t ema_plus = 0, ema_minus = 0, ema_tr = 0;
+	fp_t prev_dx = 0;
+
+	for( uint_t i = 1; i < n; ++i )
+	{
+		fp_t hdmd = ts_h( x, i ) - ts_h( x, i - 1 );
+		fp_t ldml = ts_l( x, i - 1 ) - ts_l( x, i );
+
+		fp_t plus_dm = hdmd > ldml && hdmd > 0 ? hdmd : 0;
+		fp_t minus_dm = ldml > hdmd && ldml > 0 ? ldml : 0;
+
+		fp_t tr = fmax( ts_h( x, i ) - ts_l( x, i ),
+		                fmax( fabs( ts_h( x, i ) - ts_c( x, i - 1 ) ),
+		                      fabs( ts_l( x, i ) - ts_c( x, i - 1 ) ) ) );
+
+		ema_plus = i == 1 ? plus_dm
+		                  : ema_plus + ( 1.0 / k ) * ( plus_dm - ema_plus );
+		ema_minus = i == 1 ? minus_dm
+		                   : ema_minus + ( 1.0 / k ) * ( minus_dm - ema_minus );
+		ema_tr = i == 1 ? tr
+		                 : ema_tr + ( 1.0 / k ) * ( tr - ema_tr );
+
+		if( i > k )
+		{
+			fp_t di_plus = ema_tr != 0 ? 100.0 * ema_plus / ema_tr : 0;
+			fp_t di_minus = ema_tr != 0 ? 100.0 * ema_minus / ema_tr : 0;
+
+			y[0][i] = di_plus;
+			y[1][i] = di_minus;
+
+			fp_t sum = di_plus + di_minus;
+			fp_t dx = sum != 0 ? 100.0 * fabs( di_plus - di_minus ) / sum : 0;
+
+			y[2][i] = dx;
+			y[3][i] = i == k + 1 ? dx
+			                         : prev_dx + ( 1.0 / k ) * ( dx - prev_dx );
+			prev_dx = y[3][i];
+		}
+	}
+
+	return 0;
+}
+