mirror of
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303 lines
7.9 KiB
Go
303 lines
7.9 KiB
Go
package sliceops
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import "math"
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// InsufficientElements is an error type used by FindFirst
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type InsufficientElements struct{}
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func (i InsufficientElements) Error() string {
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return "Insufficient elements found"
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}
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// Add returns the element-wise sum of all the slices with the
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// results stored in the first slice.
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// Example: Add(a,b) // result will be a[i] = a[i] + b[i]
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// a := make([]float64, len(b)); Add(a,b,c,d,e).
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// For computational efficiency, it is assumed that all of
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// the variadic arguments have the same length. If this is
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// in doubt, EqLengths can be called.
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func Add(dst []float64, slices ...[]float64) {
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if len(slices) == 0 {
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return
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}
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for i := 0; i < len(slices); i++ {
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for j, val := range slices[i] {
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dst[j] += val
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}
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}
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}
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// AddConst adds a constant to all of the values in s
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func AddConst(s []float64, c float64) {
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for i := range s {
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s[i] += c
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}
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}
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// ApplyFunc applies a function (math.Exp, math.Sin, etc.) to every element
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// of the slice
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func Apply(s []float64, f func(float64) float64) {
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for i, val := range s {
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s[i] = f(val)
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}
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}
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// Cumprod finds the cumulative product of the first i elements in
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// s and puts them in place into the ith element of the
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// destination. Assumes destination is at least as long as s
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func CumProd(dst, s []float64) []float64 {
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if dst == nil {
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dst = make([]float64, len(s))
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}
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if len(s) == 0 {
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return dst[:0]
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}
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dst[0] = s[0]
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for i := 1; i < len(s); i++ {
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dst[i] = dst[i-1] * s[i]
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}
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return dst
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}
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// Cumsum finds the cumulative sum of the first i elements in
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// s and puts them in place into the ith element of the
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// destination. Assumes destination is at least as long as s
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func CumSum(dst, s []float64) {
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dst[0] = s[0]
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for i := 1; i < len(s); i++ {
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dst[i] = dst[i-1] + s[i]
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}
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}
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// Dot computes the dot product of s1 and s2, i.e.
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// sum_{i = 1}^N s1[n]*s2[n]
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// Assumes the slices are of equal length. If this is
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// in doubt it should be checked with Eqlen
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func Dot(s1, s2 []float64) float64 {
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var sum float64
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for i, val := range s1 {
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sum += val * s2[i]
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}
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return sum
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}
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// Eq returns false if |s1[i] - s2[i]| > tol for any i.
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// Assumes that the slices are of equal length. If this
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// is in doubt it should be checked with Eqlen
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func Eq(s1, s2 []float64, tol float64) bool {
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for i, val := range s1 {
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if math.Abs(s2[i]-val) > tol {
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return false
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}
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}
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return true
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}
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// Eqlen returns true if all of the slices have equal length,
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// and false otherwise.
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// Special case: Returns true if there are no input slices
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func EqLen(slices ...[]float64) bool {
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if len(slices) == 0 {
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return true
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}
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l := len(slices[0])
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for i := 1; i < len(slices); i++ {
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if len(slices[i]) != l {
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return false
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}
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}
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return true
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}
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// Find applies a function returning a boolean to the elements of the slice
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// and returns a list of indices for which the value is true
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func Find(s []float64, f func(float64) bool) (inds []int) {
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// Not sure what an appropriate capacity is here. Don't want to make
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// it the length of the slice because if the slice is large that is
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// a lot of potentially wasted memory
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inds = make([]int, 0)
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for i, val := range s {
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if f(val) {
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inds = append(inds, i)
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}
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}
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return inds
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}
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// FindFirst applies a function returning a boolean to the elements of the slice
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// and returns a list of the first k indices for which the value is true.
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// If there are fewer than k indices for which the value is true, it returns
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// the found indices and an error.
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func FindFirst(s []float64, f func(float64) bool, k int) (inds []int, err error) {
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count := 0
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inds = make([]int, 0, k)
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for i, val := range s {
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if f(val) {
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inds = append(inds, i)
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count++
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if count == k {
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return inds, nil
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}
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}
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}
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return inds, InsufficientElements{}
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}
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// LogSpan returns a set of N equally spaced points in log space between l and u, where N
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// is equal to the length of the destination. The first element of the destination
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// is l, the final element of the destination is u. Will panic if the destination has
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// length < 2. Note that this call will return NaNs if l or u are negative, and
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// zeros if l or u is zero.
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func LogSpan(dst []float64, l, u float64) {
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Span(dst, math.Log(l), math.Log(u))
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Apply(dst, math.Exp)
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}
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// Logsumexp returns the log of the sum of the exponentials of the values in s
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func LogSumExp(s []float64) (lse float64) {
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// Want to do this in a numerically stable way which avoids
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// overflow and underflow
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// First, find the maximum value in the slice.
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maxval, _ := Max(s)
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if math.IsInf(maxval, 0) {
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// If it's infinity either way, the logsumexp will be infinity as well
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// returning now avoids NaNs
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return maxval
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}
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// Subtract off the largest value, so the largest value in
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// the new slice is 0
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AddConst(s, -maxval)
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defer AddConst(s, maxval) // make sure we add it back on at the end
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// compute the sumexp part
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for _, val := range s {
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lse += math.Exp(val)
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}
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// Take the log and add back on the constant taken out
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lse = math.Log(lse) + maxval
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return logsumexp
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}
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// Max returns the maximum value in the slice and the location of
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// the maximum value. If the input slice is empty, zero is returned
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// as the minimum value and -1 is returned as the index.
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// Use: val,ind := sliceops.Max(slice)
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func Max(s []float64) (max float64, ind int) {
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if len(s) == 0 {
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return max, -1 // Ind is -1 to make clear it's not the zeroth index.
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}
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max = s[0]
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ind = 0
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for i, val := range s {
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if val > max {
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max = val
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ind = i
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}
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}
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return max, ind
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}
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// Min returns the minimum value in the slice and the index of
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// the minimum value. If the input slice is empty, zero is returned
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// as the minimum value and -1 is returned as the index.
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// Use: val,ind := sliceops.Min(slice)
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func Min(s []float64) (min float64, ind int) {
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if len(s) == 0 {
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return min, -1 // Ind is -1 to make clear it's not the zeroth index.
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}
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min = s[0]
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ind = 0
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for i, val := range s {
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if val < min {
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min = val
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ind = i
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}
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}
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return min, ind
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}
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// Norm returns the L norm of the slice S.
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// Special cases:
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// L = math.Inf(1) gives the maximum value
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// Does not correctly compute the zero norm, as the zero norm is a count.
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func Norm(s []float64, L float64) (norm float64) {
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// Should this complain if L is not positive?
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// Should this be done in log space for better numerical stability?
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// would be more cost
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// maybe only if L is high?
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if L == 2 {
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for _, val := range s {
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norm += val * val
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}
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return math.Pow(norm, 0.5)
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}
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if L == 1 {
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for _, val := range s {
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norm += math.Abs(val)
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}
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return norm
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}
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if math.IsInf(L, 1) {
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norm, _ = Max(s)
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return norm
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}
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for _, val := range s {
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norm += math.Pow(math.Abs(val), L)
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}
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return math.Pow(norm, 1/L)
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}
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// Prod returns the product of the elements of the slice
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// Returns 1 if the input has length zero
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func Prod(s []float64) (prod float64) {
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prod = 1
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for _, val := range s {
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prod *= val
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}
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return prod
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}
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// Scale multiplies every element in s by a constant in place
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func Scale(s []float64, c float64) {
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for i := range s {
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s[i] *= c
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}
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}
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// Span returns a set of N equally spaced points between l and u, where N
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// is equal to the length of the destination. The first element of the destination
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// is l, the final element of the destination is u. Will panic if the destination has
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// length < 2
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func Span(dst []float64, l, u float64) {
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n := len(dst)
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step := (u - l) / float64(n-1)
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for i := range dst {
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dst[i] = l + step*float64(i)
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}
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}
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// Sub subtracts, element-wise, the first argument from the second. Assumes
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// the lengths of s and t match (can be tested with EqLen)
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func Sub(s, t []float64) {
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for i, val := range t {
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s[i] -= val
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}
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}
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// SubDst subtracts, element-wise, the first argument from the second and
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// store the result in destination. Assumes the lengths of s and t match
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// (can be tested with EqLen)
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func SubDst(dst, s, t []float64) {
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for i, val := range t {
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dst[i] = s[i] - val
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}
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}
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// Sum returns the sum of the elements of the slice
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func Sum(s []float64) (sum float64) {
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for _, val := range s {
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sum += val
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}
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return
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}
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