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, 56 insertions, 0 deletions

diff --git a/lib/psychological_line.c b/lib/psychological_line.c
new file mode 100644
index 0000000..35fd912
--- /dev/null
+++ b/lib/psychological_line.c
@@ -0,0 +1,56 @@
+// Psychological Line
+//
+// psychological_line
+//
+// Psychological Line
+//
+// 
+//
+// Inputs:    4
+// Outputs:   1
+// Constants: 1
+
+
+#include "ts.h"
+
+typedef struct {
+    uint_t k;
+} ts_psychological_line_params_t;
+
+ts_parameter_t const ts_psychological_line_p = { .n_inputs = 4, .n_outputs = 1, .n_constants = 1, .params_size = sizeof(ts_psychological_line_params_t) };
+
+uint_t ts_psychological_line_offset( ts_constant_t const *c )
+{
+	( void )c;
+	return ( c ? ((ts_psychological_line_params_t *)c)->k - 1 : 0 );
+}
+
+int ts_psychological_line(
+	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_psychological_line_p );
+	if ( !c ) return -1;
+    uint_t k = ((ts_psychological_line_params_t *)c)->k;
+    if (k == 0 || n < k) return -1;
+
+    fp_t sum = 0;
+
+    for( uint_t i = 0; i < k; ++i )
+    {
+        sum += ( ts_c( x, i ) > ts_o( x, i ) ) ? 100.0 : 0.0;
+    }
+
+    y[0][k - 1] = sum / (fp_t)k;
+
+    for( uint_t i = k; i < n; ++i )
+    {
+        fp_t s = ( ts_c( x, i ) > ts_o( x, i ) ) ? 100.0 : 0.0;
+        fp_t s_old = ( ts_c( x, i - k ) > ts_o( x, i - k ) ) ? 100.0 : 0.0;
+        y[0][i] = y[0][i - 1] + ( s - s_old ) / (fp_t)k;
+    }
+	return 0;
+}
+