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Author: Nilesh Patra <npatra974@gmil.com>
Description: Two of the files use "gonum.org/v1/gonum/stat" packaging this would mean packaging entire "https://github.com/gonum" which is a relatively complex package with many functionalities embedded inside it
This effort is not justified for just two minor changes. Hence, patched the files in a way that it uses the source code of the functions from missing package directly.
Last-Changed: September 16, 2020
Forwarded: Not-Needed
--- a/cluster_gff/consensus.go
+++ b/cluster_gff/consensus.go
@@ -3,10 +3,67 @@
import (
"fmt"
"github.com/biogo/biogo/feat/gene"
- "gonum.org/v1/gonum/stat"
"sort"
+ "math"
)
+func Sumfloats(s []float64) float64 {
+ var sum float64
+ for _, val := range s {
+ sum += val
+ }
+ return sum
+}
+
+func floatsHasNaN(s []float64) bool {
+ for _, v := range s {
+ if math.IsNaN(v) {
+ return true
+ }
+ }
+ return false
+}
+
+func empiricalQuantile(p float64, x, weights []float64, sumWeights float64) float64 {
+ var cumsum float64
+ fidx := p * sumWeights
+ for i := range x {
+ if weights == nil {
+ cumsum++
+ } else {
+ cumsum += weights[i]
+ }
+ if cumsum >= fidx {
+ return x[i]
+ }
+ }
+ panic("impossible")
+}
+
+func Quantile(p float64, x, weights []float64) float64 {
+ if !(p >= 0 && p <= 1) {
+ panic("stat: percentile out of bounds")
+ }
+
+ if weights != nil && len(x) != len(weights) {
+ panic("stat: slice length mismatch")
+ }
+ if floatsHasNaN(x) {
+ return math.NaN() // This is needed because the algorithm breaks otherwise.
+ }
+ if !sort.Float64sAreSorted(x) {
+ panic("x data are not sorted")
+ }
+
+ var sumWeights float64
+ if weights == nil {
+ sumWeights = float64(len(x))
+ } else {
+ sumWeights = Sumfloats(weights)
+ }
+ return empiricalQuantile(p, x, weights, sumWeights)
+}
+
// Generate consensus of transcript cluster by taking medians of exon boundaries.
func MedianClusterConsensus(cluster *TranscriptCluster) *gene.CodingTranscript {
@@ -37,8 +94,8 @@
sort.Float64s(exonEnds)
// Calculate median boundaries:
- medianStart := stat.Quantile(0.5, stat.Empirical, exonStarts, nil)
- medianEnd := stat.Quantile(0.5, stat.Empirical, exonEnds, nil)
+ medianStart := Quantile(0.5, exonStarts, nil)
+ medianEnd := Quantile(0.5, exonEnds, nil)
consExonStarts[i] = int(medianStart)
consExonEnds[i] = int(medianEnd)
--- a/polish_clusters/polish.go
+++ b/polish_clusters/polish.go
@@ -2,7 +2,6 @@
import (
"fmt"
- "gonum.org/v1/gonum/stat"
"io/ioutil"
"math"
"os"
@@ -10,6 +9,64 @@
"sort"
)
+func Sumfloats(s []float64) float64 {
+ var sum float64
+ for _, val := range s {
+ sum += val
+ }
+ return sum
+}
+
+func floatsHasNaN(s []float64) bool {
+ for _, v := range s {
+ if math.IsNaN(v) {
+ return true
+ }
+ }
+ return false
+}
+
+func empiricalQuantile(p float64, x, weights []float64, sumWeights float64) float64 {
+ var cumsum float64
+ fidx := p * sumWeights
+ for i := range x {
+ if weights == nil {
+ cumsum++
+ } else {
+ cumsum += weights[i]
+ }
+ if cumsum >= fidx {
+ return x[i]
+ }
+ }
+ panic("impossible")
+}
+
+func Quantile(p float64, x, weights []float64) float64 {
+ if !(p >= 0 && p <= 1) {
+ panic("stat: percentile out of bounds")
+ }
+
+ if weights != nil && len(x) != len(weights) {
+ panic("stat: slice length mismatch")
+ }
+ if floatsHasNaN(x) {
+ return math.NaN() // This is needed because the algorithm breaks otherwise.
+ }
+ if !sort.Float64sAreSorted(x) {
+ panic("x data are not sorted")
+ }
+
+ var sumWeights float64
+ if weights == nil {
+ sumWeights = float64(len(x))
+ } else {
+ sumWeights = Sumfloats(weights)
+ }
+ return empiricalQuantile(p, x, weights, sumWeights)
+}
+
+
// Polish cluster using minimap2 and racon.
func PolishCluster(clusterId string, reads []*Seq, outChan chan *Seq, tempRoot string, threads int, minimapParams, raconParams string) {
// Set up working space:
@@ -119,7 +176,7 @@
lengths[i] = float64(len(seq.Seq))
}
sort.Float64s(lengths)
- medianLength := stat.Quantile(0.5, stat.Empirical, lengths, nil)
+ medianLength := Quantile(0.5, lengths, nil)
i := sort.SearchFloat64s(lengths, medianLength)
//fmt.Println(lengths[i], len(segments))
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