feat: initial release

Assisted-by: GLM 5.3 Flash

examples/fft/main.go

@@ -0,0 +1,62 @@
+// Copyright (c) 2026 Petr Balvín <opensource@petrbalvin.org> (https://petrbalvin.org)
+// SPDX-License-Identifier: MIT
+
+// Command fft demonstrates the Fourier transform: it synthesises a
+// signal from two sinusoids, transforms it, and prints the dominant
+// frequency components.
+//
+// Usage: go run ./examples/fft
+package main
+
+import (
+	"fmt"
+	"log"
+	"math"
+
+	"sourcedock.dev/petrbalvin/tensor"
+	sig "sourcedock.dev/petrbalvin/tensor/signal"
+)
+
+func main() {
+	// Two sinusoids: 5 Hz and 13 Hz, sampled at 100 Hz for 2 seconds.
+	const (
+		fs      = 100.0
+		seconds = 2.0
+	)
+	n := int(fs * seconds)
+	vals := make([]float64, n)
+	for i := range n {
+		t := float64(i) / fs
+		vals[i] = math.Sin(2*math.Pi*5*t) + 0.5*math.Sin(2*math.Pi*13*t)
+	}
+	signal, err := tensor.FromFloats(vals, n)
+	if err != nil {
+		log.Fatal(err)
+	}
+
+	spec, err := sig.FFT(signal)
+	if err != nil {
+		log.Fatal(err)
+	}
+	freqs := sig.FFTFreq(n, 1/fs)
+
+	// Find the two strongest bins (excluding DC).
+	var peaks [2]struct {
+		freq float64
+		mag  float64
+	}
+	for i := 1; i < n/2; i++ {
+		m, _ := tensor.ComplexAt(spec, i)
+		mag := math.Hypot(real(m), imag(m))
+		for p := range peaks {
+			if mag > peaks[p].mag {
+				peaks[p].freq, _ = tensor.FloatAt(freqs, i)
+				peaks[p].mag = mag
+				break
+			}
+		}
+	}
+	for _, p := range peaks {
+		fmt.Printf("peak at %.1f Hz (magnitude %.1f)\n", p.freq, p.mag)
+	}
+}