From 07e18043145f3d91c8ea7ec3ad41b3c905585277 Mon Sep 17 00:00:00 2001
From: Ethan Werner <mail@ethanwerner.com>
Date: Wed, 1 Jul 2026 09:42:39 +0400
Subject: 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
---
 lib/parabolic_sar.c | 99 +++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 99 insertions(+)
 create mode 100644 lib/parabolic_sar.c

(limited to 'lib/parabolic_sar.c')

diff --git a/lib/parabolic_sar.c b/lib/parabolic_sar.c
new file mode 100644
index 0000000..ff84834
--- /dev/null
+++ b/lib/parabolic_sar.c
@@ -0,0 +1,99 @@
+// Parabolic Sar
+//
+// parabolic_sar
+//
+// Parabolic SAR
+//
+//
+//
+// Inputs:    4
+// Outputs:   2
+// Constants: 2
+
+
+#include <math.h>
+#include "ts.h"
+
+typedef struct {
+    fp_t step;
+    fp_t max_af;
+} ts_parabolic_sar_params_t;
+
+ts_parameter_t const ts_parabolic_sar_p = { .n_inputs = 4, .n_outputs = 2, .n_constants = 2, .params_size = sizeof(ts_parabolic_sar_params_t) };
+
+uint_t ts_parabolic_sar_offset( ts_constant_t const *c )
+{
+	( void )c;
+	return ( 0 );
+}
+
+int ts_parabolic_sar(
+	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_parabolic_sar_p );
+	if ( !c ) return -1;
+    fp_t step = ((ts_parabolic_sar_params_t *)c)->step;
+    fp_t max_af = ((ts_parabolic_sar_params_t *)c)->max_af;
+    if (step <= 0 || max_af <= 0) return -1;
+    if (isnan(step) || isnan(max_af)) return -1;
+    if (step > max_af) return -1;
+    if (n == 0) return -1;
+
+    int_t trend = 1;
+    fp_t sar = ts_l( x, 0 );
+    fp_t ep = ts_h( x, 0 );
+    fp_t af = step;
+
+    for ( uint_t i = 0; i < n; ++i )
+    {
+        y[0][i] = sar;
+        y[1][i] = (fp_t)(trend > 0);
+
+        if (i == 0) continue;
+
+        if (trend > 0)
+        {
+            sar = sar + af * (ep - sar);
+            if (ts_l( x, i ) < sar)
+            {
+                trend = -1;
+                sar = ep;
+                ep = ts_l( x, i );
+                af = step;
+            }
+            else
+            {
+                if (ts_h( x, i ) > ep)
+                {
+                    ep = ts_h( x, i );
+                    af = af + step;
+                    if (af > max_af) af = max_af;
+                }
+            }
+        }
+        else
+        {
+            sar = sar + af * (ep - sar);
+            if (ts_h( x, i ) > sar)
+            {
+                trend = 1;
+                sar = ep;
+                ep = ts_h( x, i );
+                af = step;
+            }
+            else
+            {
+                if (ts_l( x, i ) < ep)
+                {
+                    ep = ts_l( x, i );
+                    af = af + step;
+                    if (af > max_af) af = max_af;
+                }
+            }
+        }
+    }
+	return 0;
+}
-- 
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