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, 75 insertions, 0 deletions

diff --git a/lib/correlation_coefficient.c b/lib/correlation_coefficient.c
new file mode 100644
index 0000000..d20d1ea
--- /dev/null
+++ b/lib/correlation_coefficient.c
@@ -0,0 +1,75 @@
+// Correlation Coefficient
+//
+// correlation_coefficient - corr
+//
+// Pearson r = (n*Σxy - Σx*Σy) / √((n*Σx²-Σx²)(n*Σy²-Σy²))
+//
+// Inputs:    2
+// Outputs:   1 (r)
+// Constants: 1 (period)
+
+#include <math.h>
+#include "ts.h"
+
+typedef struct {
+    uint_t k;
+} ts_correlation_coefficient_params_t;
+
+ts_parameter_t const ts_correlation_coefficient_p = { .n_inputs = 2, .n_outputs = 1, .n_constants = 1, .params_size = sizeof(ts_correlation_coefficient_params_t) };
+
+uint_t ts_correlation_coefficient_offset( ts_constant_t const *c )
+{
+	( void )c;
+	return ( c ? ((ts_correlation_coefficient_params_t *)c)->k - 1 : 0 );
+}
+
+int ts_correlation_coefficient(
+	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_correlation_coefficient_p );
+	if ( !c ) return -1;
+    uint_t k = ((ts_correlation_coefficient_params_t *)c)->k;
+    if (k == 0 || n < k) return -1;
+
+    fp_t sum_x = 0, sum_y = 0, sum_xy = 0, sum_x2 = 0, sum_y2 = 0;
+
+    for ( uint_t i = 0; i < k; ++i )
+    {
+        fp_t xi = x[0][i];
+        fp_t yi = x[1][i];
+        sum_x += xi;
+        sum_y += yi;
+        sum_xy += xi * yi;
+        sum_x2 += xi * xi;
+        sum_y2 += yi * yi;
+    }
+
+    fp_t denom = ( k * sum_x2 - sum_x * sum_x ) * ( k * sum_y2 - sum_y * sum_y );
+    fp_t numer = k * sum_xy - sum_x * sum_y;
+    y[0][k - 1] = denom > 0 ? numer / sqrt( denom ) : 0;
+
+    for ( uint_t i = k; i < n; ++i )
+    {
+        fp_t xi_old = x[0][i - k];
+        fp_t yi_old = x[1][i - k];
+        fp_t xi_new = x[0][i];
+        fp_t yi_new = x[1][i];
+
+        sum_x = sum_x - xi_old + xi_new;
+        sum_y = sum_y - yi_old + yi_new;
+        sum_xy = sum_xy - xi_old * yi_old + xi_new * yi_new;
+        sum_x2 = sum_x2 - xi_old * xi_old + xi_new * xi_new;
+        sum_y2 = sum_y2 - yi_old * yi_old + yi_new * yi_new;
+
+        denom = ( k * sum_x2 - sum_x * sum_x ) * ( k * sum_y2 - sum_y * sum_y );
+        numer = k * sum_xy - sum_x * sum_y;
+        y[0][i] = denom > 0 ? numer / sqrt( denom ) : 0;
+    }
+	return 0;
+}
+
+
+