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, 58 insertions, 0 deletions

diff --git a/lib/time_series_forecast.c b/lib/time_series_forecast.c
new file mode 100644
index 0000000..bf8e7af
--- /dev/null
+++ b/lib/time_series_forecast.c
@@ -0,0 +1,58 @@
+// Time Series Forecast
+//
+// time_series_forecast
+//
+// Time Series Forecast
+//
+// 
+//
+// Inputs:    1
+// Outputs:   1
+// Constants: 0
+
+
+#include <math.h>
+#include "ts.h"
+
+
+ts_parameter_t const ts_time_series_forecast_p = { .n_inputs = 1, .n_outputs = 1, .n_constants = 0, .params_size = 0 };
+
+uint_t ts_time_series_forecast_offset( ts_constant_t const *c )
+{
+	( void )c;
+	return ( 4 );
+}
+
+int ts_time_series_forecast(
+	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_time_series_forecast_p );
+	(void)c;
+	for ( uint_t j = 0; j < n && j < 4; ++j ) y[0][j] = 0;
+	for ( uint_t i = 4; i < n; ++i )
+	{
+		fp_t sum_x = 0, sum_y = 0, sum_xy = 0, sum_x2 = 0;
+		for ( uint_t j = 0; j < 5; ++j )
+		{
+			fp_t xv = (fp_t)j;
+			fp_t yv = x[0][i - 4 + j];
+			sum_x += xv;
+			sum_y += yv;
+			sum_xy += xv * yv;
+			sum_x2 += xv * xv;
+		}
+		fp_t denom = 5.0 * sum_x2 - sum_x * sum_x;
+		if (denom == 0) {
+			y[0][i] = sum_y / 5.0;
+		} else {
+			fp_t slope = (5.0 * sum_xy - sum_x * sum_y) / denom;
+			fp_t intercept = (sum_y - slope * sum_x) / 5.0;
+			y[0][i] = intercept + slope * 5.0;
+		}
+	}
+	return 0;
+}
+