egutierrez
fc734029c1
12 funciones puras con implementación real: Standardize, MinMaxScale, Clip, RollingWindow, ZipSlices, GroupBy, Histogram, Pearson, Autocorrelation, FFT (Cooley-Tukey), DetectOutliers, Impute 3 funciones impuras (stubs): LoadCSV, LoadParquet, FetchDataFrame Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
62 lines
1.1 KiB
Go
62 lines
1.1 KiB
Go
package datascience
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import (
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"math"
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"math/cmplx"
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)
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// FFT calcula la Fast Fourier Transform usando el algoritmo Cooley-Tukey radix-2.
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// Si la longitud de data no es potencia de 2, se rellena con ceros (zero-padding).
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func FFT(data []float64) []complex128 {
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n := len(data)
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if n == 0 {
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return []complex128{}
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}
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// Calcular la siguiente potencia de 2.
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size := nextPow2(n)
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// Convertir a complex128 con zero-padding.
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x := make([]complex128, size)
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for i := 0; i < n; i++ {
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x[i] = complex(data[i], 0)
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}
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fftRecursive(x)
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return x
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}
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// nextPow2 retorna la menor potencia de 2 >= n.
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func nextPow2(n int) int {
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p := 1
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for p < n {
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p <<= 1
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}
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return p
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}
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// fftRecursive aplica Cooley-Tukey radix-2 DIT in-place.
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func fftRecursive(x []complex128) {
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n := len(x)
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if n <= 1 {
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return
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}
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// Separar pares e impares.
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even := make([]complex128, n/2)
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odd := make([]complex128, n/2)
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for i := 0; i < n/2; i++ {
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even[i] = x[2*i]
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odd[i] = x[2*i+1]
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}
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fftRecursive(even)
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fftRecursive(odd)
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for k := 0; k < n/2; k++ {
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t := cmplx.Rect(1, -2*math.Pi*float64(k)/float64(n)) * odd[k]
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x[k] = even[k] + t
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x[k+n/2] = even[k] - t
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}
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}
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