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package bin;
import java.util.ArrayList;
import java.util.Random;
import dna.Data;
import fileIO.ByteFile;
import fileIO.FileFormat;
import shared.LineParser1;
import shared.Shared;
import shared.Tools;
import stream.Read;
import stream.ReadInputStream;
import structures.FloatList;
import tracker.EntropyTracker;
public class AdjustEntropy {
public static void main(String[] args) {
int k=Integer.parseInt(args[0]);
int window=Integer.parseInt(args[1]);
float step=Float.parseFloat(args[2]);
int length=(args.length<4 ? 100000 : Integer.parseInt(args[3]));
int trials=(args.length<5 ? 9 : Integer.parseInt(args[4]));
assert(step>0 && step<1);
assert(length>window);
assert(window>k);
assert(k>0 && k<=10);
AdjustEntropy ea=new AdjustEntropy();
EntropyTracker et=new EntropyTracker(k, window, false);
FloatList fl=new FloatList();
System.out.println("#K\t"+k);
System.out.println("#Window\t"+window);
System.out.println("#Length\t"+length);
System.out.println("#Step\t"+step);
System.out.println("#Trials\t"+trials);
System.out.println("#GC\tAvgEnt\tMaxEnt");
for(double gc=0; gc<1 || Tools.absdif(gc, 1)<0.5*step; gc+=step) {
float entropy=ea.randomSequenceEntropy(length, (float)gc, et, trials);
fl.add(entropy);
System.out.println(String.format("%.4f\t%.6f\t%.6f", gc, entropy, ea.max));
}
String fname=args.length<6 ? null : args[5];
entropyArray=fl.toArray();
if(fname!=null) {
processFile(fname, et);
}
}
static void processFile(String fname, EntropyTracker et) {
ArrayList<Read> reads=ReadInputStream.toReads(fname, FileFormat.FASTA, 2000);
System.out.println("#GC\tgcCompEntropy\tstrandedness");
int[] counts=new int[1<<(2*et.k())];
for(Read r : reads) {
float gc=r.gc();
float entropy=et.averageEntropy(r.bases, false);
float comp=compensate(gc, entropy);
float strandedness=EntropyTracker.strandedness(r.bases, counts, et.k());
System.out.println(String.format("%.4f\t%.6f\t%6f", gc, comp, strandedness));
}
}
static float maxEntropy(float gc, float[] array) {
int steps=array.length-1;
float stepSize=1f/steps;
int lowBin=(int)Math.floor(gc*steps);
int highBin=(int)Math.ceil(gc*steps);
float lowE=array[lowBin], highE=array[highBin];
float lowGC=stepSize*lowBin, highGC=stepSize*highBin;
float lowFraction=highGC-gc, highFraction=gc-lowGC;
float max=(lowFraction*lowE+highFraction*highE)*steps;
// assert(false) : "GC "+gc+" -> "+max;
return max;
}
public static synchronized void load() {
load(4, 150);
}
public static synchronized void load(int k, int window) {
String fname="?entropy_k"+k+"_w"+window+".tsv";
fname=Data.findPath(fname);
setEntropyFile(fname);
}
private static synchronized void setEntropyFile(String fname) {
assert(fname!=null);
if(fnameLoaded==null || !fnameLoaded.equals(fname)) {
entropyArray=loadEntropyFile(fname);
}
}
private static float[] loadEntropyFile(String fname) {
ArrayList<byte[]> lines=ByteFile.toLines(fname);
FloatList floats=new FloatList(lines.size());
LineParser1 lp=new LineParser1('\t');
for(byte[] line : lines) {
lp.set(line);
if(lp.startsWith('#')){
if(lp.startsWith("#K\t")) {
kLoaded=lp.parseInt(1);
}else if(lp.startsWith("#Window\t")) {
wLoaded=lp.parseInt(1);
}
}else {
floats.add(lp.parseFloat(1));
}
}
return floats.toArray();
}
/** Returns entropy as a fraction of random entropy for this GC level */
static float compensate(float gc, float entropy) {
float max=maxEntropy(gc, entropyArray);
return Tools.min(1, 1-(max-entropy));//entropy/max;
}
float randomSequenceEntropy(int len, float gc, EntropyTracker et, int trials) {
FloatList fl=new FloatList(trials);
for(int i=0; i<trials; i++) {fl.add(randomSequenceEntropy(len, gc, et));}
fl.sort();
min=fl.get(0);
max=fl.lastElement();
assert(min<=max) : fl;
double sum=0;
int count=0;
int samples=Tools.max((int)Math.sqrt(trials), trials/4);
for(int i=0; i<samples; i++) {
sum+=fl.get(fl.size()-i-1);
count++;
}
assert(count==samples);
mid=(float)(sum/samples);
// else if((trials&1)==1) {//odd
// double sum=0;
// int count=0;
// int center=trials/2;
// for(int i=0; i<=trials/4; i++) {
// sum+=fl.get(center+i);
// sum+=fl.get(center-i);
// count+=2;
// }
// mid=(float)(sum/count);
// }else {
// double sum=0;
// int count=0;
// int center=trials/2-1;
// for(int i=0; i<=trials/4; i++) {
// sum+=fl.get(center+i+1);
// sum+=fl.get(center-i);
// count+=2;
// }
// mid=(float)(sum/count);
// }
assert(min<=max) : fl;
assert(min<=mid) : fl;
assert(mid<=max) : fl;
return mid;
}
static float randomSequenceEntropy(int len, float gc, EntropyTracker et) {
byte[] bases=randomSequence(len, gc);
return et.averageEntropy(bases, false);
}
static byte[] randomSequence(int len, float gc) {
byte[] bases=new byte[len];
Random randy=Shared.threadLocalRandom();
byte[] atcg={'A','T','C','G'};
for(int i=0; i<len; i++) {
int high=(randy.nextFloat()>=gc ? 0 : 2);
int low=(randy.nextInt()&1);
byte b=atcg[high+low];
bases[i]=b;
}
return bases;
}
float min, mid, max;
private static String fnameLoaded=null;
public static int kLoaded=0;
public static int wLoaded=0;
private static float[] entropyArray=null;
}
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