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, 88 insertions, 0 deletions

diff --git a/lib/bollinger_bands.c b/lib/bollinger_bands.c
new file mode 100644
index 0000000..55da054
--- /dev/null
+++ b/lib/bollinger_bands.c
@@ -0,0 +1,88 @@
+// Bollinger Bands
+//
+// bollinger_bands - BB
+//
+// Upper: SMA + mult * stddev
+// Middle: SMA
+// Lower: SMA - mult * stddev
+//
+// Inputs:    1
+// Outputs:   3 (Upper, Middle, Lower)
+// Constants: 2 (period, std multiplier)
+
+#include <math.h>
+#include "ts.h"
+
+
+typedef struct {
+    uint_t k;
+    fp_t std_mult;
+} ts_bollinger_bands_params_t;
+
+ts_parameter_t const ts_bollinger_bands_p = { .n_inputs = 1, .n_outputs = 3, .n_constants = 2, .params_size = sizeof(ts_bollinger_bands_params_t) };
+
+
+uint_t ts_bollinger_bands_offset( ts_constant_t const *c )
+{
+	( void )c;
+	return ( c ? ((ts_bollinger_bands_params_t *)c)->k - 1 : 0 );
+}
+
+int ts_bollinger_bands(
+	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_bollinger_bands_p );
+	if ( !c ) return -1;
+	TS_CHECK_INPUT(x, x_n, n);
+	uint_t k = ((ts_bollinger_bands_params_t *)c)->k;
+	if (k == 0 || n < k) return -1;
+	fp_t std_mult = ((ts_bollinger_bands_params_t *)c)->std_mult;
+	if (std_mult < 0 || isnan(std_mult)) return -1;
+
+	// Two-pass initial window for numerical stability
+	{
+		fp_t mean = 0;
+		for( uint_t j = 0; j < k; ++j )
+			mean += x[0][j];
+		mean /= (fp_t)k;
+		fp_t variance = 0;
+		for( uint_t j = 0; j < k; ++j )
+		{
+			fp_t d = x[0][j] - mean;
+			variance += d * d;
+		}
+		variance /= (fp_t)k;
+		fp_t stddev = sqrt( variance );
+		y[1][k - 1] = mean + std_mult * stddev;
+		y[0][k - 1] = mean;
+		y[2][k - 1] = mean - std_mult * stddev;
+	}
+
+	// Sliding window: maintain running mean, two-pass variance
+	fp_t sum = 0;
+	for( uint_t j = 0; j < k; ++j )
+		sum += x[0][j];
+	fp_t rk = 1.0 / (fp_t)k;
+	for( uint_t i = k; i < n; ++i )
+	{
+		sum = sum + x[0][i] - x[0][i - k];
+		fp_t mean = sum * rk;
+		// Two-pass variance for stability
+		fp_t variance = 0;
+		for( uint_t j = i - k + 1; j <= i; ++j )
+		{
+			fp_t d = x[0][j] - mean;
+			variance += d * d;
+		}
+		variance *= rk;
+		fp_t stddev = sqrt( variance );
+		y[1][i] = mean + std_mult * stddev;
+		y[0][i] = mean;
+		y[2][i] = mean - std_mult * stddev;
+	}
+	return 0;
+}
+