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/deviation_average.c | 78 +++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 78 insertions(+)
 create mode 100644 lib/deviation_average.c

(limited to 'lib/deviation_average.c')

diff --git a/lib/deviation_average.c b/lib/deviation_average.c
new file mode 100644
index 0000000..5ac7109
--- /dev/null
+++ b/lib/deviation_average.c
@@ -0,0 +1,78 @@
+// Moving Mean Deviation
+//
+// mean_deviation - md
+//
+// Inputs:    1
+// Outputs:   1
+// Constants: 0
+
+
+#include <math.h>
+#include "ts.h"
+
+
+typedef struct {
+    uint_t k;
+} ts_deviation_average_params_t;
+
+ts_parameter_t const ts_deviation_average_p = { .n_inputs = 1, .n_outputs = 1, .n_constants = 1, .params_size = sizeof(ts_deviation_average_params_t) };
+
+
+uint_t ts_deviation_average_offset( ts_constant_t const *c )
+{
+	( void )c;
+	return ( c ? ((ts_deviation_average_params_t *)c)->k > 0 ? ((ts_deviation_average_params_t *)c)->k - 1 : 0 : 0 );
+}
+
+int ts_deviation_average(
+	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_deviation_average_p );
+	if ( !c ) return -1;
+	uint_t k = ((ts_deviation_average_params_t *)c)->k;
+	if (k == 0 || n < k) return -1;
+
+	uint_t xi = 0;
+	uint_t yi = k - 1;
+
+	fp_t mean = 0;
+
+	for( ; xi < k; ++xi )
+	{
+		mean += x[0][xi];
+	}
+
+    fp_t rk = _ts_reciprocal( k );
+	mean = rk * mean;
+
+	{
+        fp_t sum = 0;
+        for( uint_t i = 0; i < k; i++ )
+        {
+            fp_t tmp = x[0][i] - mean;
+            sum += fabs( tmp );
+        }
+        y[0][yi] = sum * rk;
+	}
+
+	for( xi = k, yi = k; xi < n; ++xi, ++yi )
+	{
+		mean = mean + ( x[0][xi] - x[0][xi - k] ) * rk;
+        fp_t sum = 0;
+
+        for( uint_t i = xi - k + 1; i <= xi; i++ )
+        {
+            fp_t tmp = x[0][i] - mean;
+            sum += fabs( tmp );
+        }
+
+        y[0][yi] = sum * rk;
+	}
+	return 0;
+}
+
+
+
-- 
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