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, 51 insertions, 0 deletions

diff --git a/lib/student_t_pdf.c b/lib/student_t_pdf.c
new file mode 100644
index 0000000..67c9f1d
--- /dev/null
+++ b/lib/student_t_pdf.c
@@ -0,0 +1,51 @@
+// Student T Pdf
+//
+// student_t_pdf
+//
+// Student's t probability density
+//
+// 
+//
+// Inputs:    1
+// Outputs:   1
+// Constants: 1
+
+
+#include <math.h>
+#include "ts.h"
+
+typedef struct {
+    fp_t nu;
+} ts_student_t_pdf_params_t;
+
+ts_parameter_t const ts_student_t_pdf_p = { .n_inputs = 1, .n_outputs = 1, .n_constants = 1, .params_size = sizeof(ts_student_t_pdf_params_t) };
+
+uint_t ts_student_t_pdf_offset( ts_constant_t const *c )
+{
+	( void )c;
+	return ( 0 );
+}
+
+int ts_student_t_pdf(
+	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_student_t_pdf_p );
+	if ( !c ) return -1;
+	fp_t nu = ((ts_student_t_pdf_params_t *)c)->nu;
+	if ( nu <= 0 )
+	{
+		for( uint_t i = 0; i < n; ++i ) y[0][i] = 0;
+	return -1;
+	}
+	fp_t coeff = tgamma( ( nu + 1.0 ) / 2.0 ) / ( sqrt( nu * PI ) * tgamma( nu / 2.0 ) );
+	for( uint_t i = 0; i < n; ++i )
+	{
+		fp_t xi = x[0][i];
+		y[0][i] = coeff * pow( 1.0 + xi * xi / nu, -( nu + 1.0 ) / 2.0 );
+	}
+	return 0;
+}
+