Нужна помощь в отладке этой Java ⇐ JAVA

[Anonymous]

Я работаю над заданием для курса машинного обучения с использованием Eclipse.
У меня есть цикл while в main(), который должен выводить переменную с именем totError. totError должен быть разным при каждом цикле (рассчитывается на основе изменяющегося параметра). Однако я не могу найти, где я ошибся в коде, он продолжает отображать то же самое. Я неправильно использую статические переменные и методы??
Файлы .java и .txt вставлены ниже (к сожалению, .txt слишком велик, поэтому я включил лишь небольшую его часть но размерность моих массивов правильная). Может ли кто-нибудь указать мне правильное направление?
package nn;

import java.io.File;
import java.io.FileReader;
import java.io.BufferedReader;
//import java.io.PrintStream;
import java.io.IOException;
import java.lang.Math;

public class learningBP {

// Declare variables
static int NUM_INPUTS = 10; // Including 1 bias
static int NUM_HIDDENS = 10; // Including 1 bias
static int NUM_OUTPUTS = 1;
static double LEARNING_RATE = 0.1;
static double MOMENTUM = 0.1;
static double TOT_ERROR_THRESHOLD = 0.05;
static double SIGMOID_UB = 1;
static double SIGMOID_LB = -1;

static double [][] wgtIH = new double[NUM_INPUTS][NUM_HIDDENS];
static double [][] dltWgtIH = new double[NUM_INPUTS][NUM_HIDDENS];
static double [][] wgtHO = new double[NUM_HIDDENS][NUM_OUTPUTS];
static double [][] dltWgtHO = new double[NUM_HIDDENS][NUM_OUTPUTS];

static int NUM_STATES_ACTIONS;

static String [][] strLUT = new String[4*4*4*3*4*4][2];
static double [][] arrayLUT = new double[strLUT.length][2];
static double [][] arrayNormLUT = new double[strLUT.length][2];
static double [] arrayErrors = new double[strLUT.length];
static double [] arrayOutputs = new double[strLUT.length];
static double [] arrayNormOutputs = new double[strLUT.length];
static double [][] valueInput = new double[strLUT.length][NUM_INPUTS];
static double [][] valueHidden = new double[strLUT.length][NUM_HIDDENS];
static double [] dltOutputs = new double[strLUT.length];
static double [][] dltHiddens = new double[strLUT.length][NUM_HIDDENS];

static double totError = 1;
static int numEpochs = 0;

public static void main(String[] args) {

// Load LUT
String fileName = "/Users/XXXXX/Desktop/LUT.txt";
try {
load(fileName);
}
catch (IOException e) {
e.printStackTrace();
}

// Initialize NN Weights
initializeWeights();

while (totError > TOT_ERROR_THRESHOLD) {

// Feed Forward
fwdFeed();

// Back Propagation
bckPropagation();

// Calculate Total Error
totError = calcTotError(arrayErrors);
numEpochs += 1;

System.out.println("Number of Epochs: "+numEpochs);
System.out.println(totError);

}

}

public double outputFor(double[] X) {
// TODO Auto-generated method stub
return 0;
}

public double train(double[] X, double argValue) {
// TODO Auto-generated method stub
return 0;
}

public void save(File argFile) {
// TODO Auto-generated method stub

}

public static void load(String argFileName) throws IOException {

// Load LUT training set from Part2
BufferedReader r = new BufferedReader(new FileReader(new File(argFileName)));
String l = r.readLine();
try {
int a = 0;
while (l != null) {
String spt[] = l.split(" ");
strLUT[a][0] = spt[0];
strLUT[a][1] = spt[1];
arrayLUT[a][0] = Double.parseDouble(strLUT[a][0]);
arrayLUT[a][1] = Double.parseDouble(strLUT[a][1]);
a += 1;
l = r.readLine();
}
} catch (IOException e) {
e.printStackTrace();
} finally {
r.close();
}

// Normalize LUT to bipolar
for (int b = 0; b < arrayLUT.length; b++) {
arrayNormLUT[0] = arrayLUT[0];
arrayNormLUT[1] = sigmoid(arrayLUT[1]);
}

}

public static double sigmoid(double x) {

// Bipolar sigmoid
return (SIGMOID_UB - SIGMOID_LB) / (1 + Math.pow(Math.E, -x)) + SIGMOID_LB;

}

public static void initializeWeights() {

// Initialize weights from input layer to hidden layer
for (int i = 0; i < NUM_INPUTS; i++) {
for (int j = 0; j < NUM_HIDDENS; j++) {
wgtIH[j] = Math.random() - 0.5;
dltWgtIH[j] = 0;
}
}

// Initialize weights from hidden layer to output layer
for (int j = 0; j < NUM_HIDDENS; j++) {
for (int k = 0; k < NUM_OUTPUTS; k++) {
wgtHO[j][k] = Math.random() - 0.5;
dltWgtHO[j][k] = 0;
}
}

}

public void zeroWeights() {

// TODO Auto-generated method stub

}

public static void fwdFeed() {

for(int z = 0; z < arrayLUT.length; z++) {

// Normalize between [-1, 1]
valueInput[z][0] = (Character.getNumericValue(strLUT[z][0].charAt(0)) - 2.5)/1.5; // myX
valueInput[z][1] = (Character.getNumericValue(strLUT[z][0].charAt(1)) - 2.5)/1.5; // myY
valueInput[z][2] = (Character.getNumericValue(strLUT[z][0].charAt(2)) - 2.5)/1.5; // myHead
valueInput[z][3] = Character.getNumericValue(strLUT[z][0].charAt(3)) - 2; // enProx
valueInput[z][4] = (Character.getNumericValue(strLUT[z][0].charAt(4)) - 2.5)/1.5; // enAngle

// Vectorization of the four possible actions into binaries
valueInput[z][5] = 0;
valueInput[z][6] = 0;
valueInput[z][7] = 0;
valueInput[z][8] = 0;

int action = Character.getNumericValue(strLUT[z][0].charAt(5)); // action
valueInput[z][action-1] = 1;

// Apply bias input
valueInput[z][9] = 1;

// Calculate value for hidden neuron j
for(int j = 0; j < NUM_HIDDENS-1; j++) {
valueHidden[z][j] = 0;
for(int i = 0; i < NUM_INPUTS; i++) {
valueHidden[z][j] += valueInput[z]*wgtIH[j];
}
valueHidden[z][j] = sigmoid(valueHidden[z][j]);
}

// Apply bias hidden neuron
valueHidden[z][9] = 1;

// Calculate value for output neuron
arrayOutputs[z] = 0;
for(int j = 0; j < NUM_HIDDENS; j++) {
arrayOutputs[z] += valueHidden[z][j]*wgtHO[j][0];
}

arrayNormOutputs[z] = sigmoid(arrayOutputs[z]);
arrayErrors[z] = arrayNormOutputs[z] - arrayNormLUT[z][1];
}

}

public static void bckPropagation() {

for(int z = 0; z < arrayLUT.length; z++) {

// Delta rule for bipolar sigmoids
dltOutputs[z] = arrayErrors[z] * (1/2) * (1 + arrayNormLUT[z][1]) * (1 - arrayNormLUT[z][1]);

// Calculate update weights between hidden & output layers
for(int j = 0; j < NUM_HIDDENS; j++) {

dltWgtHO[j][0] = (LEARNING_RATE * dltOutputs[z] * valueHidden[z][j]) + (MOMENTUM * dltWgtHO[j][0]);
wgtHO[j][0] += dltWgtHO[j][0];

}

// Delta rule for bipolar sigmoids
for(int j = 0; j < NUM_HIDDENS-1; j++) {

dltHiddens[z][j] = (dltOutputs[z] * wgtHO[j][0]) * (1/2) * (1 + valueHidden[z][j]) * (1 - valueHidden[z][j]);

// calculate update weights between input & hidden layers
for(int i = 0; i < NUM_INPUTS; i++){

dltWgtIH[j] = (LEARNING_RATE * dltHiddens[z][j] * valueInput[z]) + (MOMENTUM * dltWgtIH[j]);
wgtIH[j] += dltWgtIH[j];

}

}

}
}

public static double calcTotError(double [] Ar) {

// Get total error
double outputTotError = 0;
for(int z = 0; z < Ar.length; z++) {

outputTotError += Math.pow(Ar[z], 2 ) ; < b r / > < b r / > } < b r / > r e t u r n o u t p u t T o t E r r o r / = 2 ; < b r / > < b r / > } < b r / > < b r / > } < b r / > < / к о д > < b r / > < b r / > < p r e c l a s s = " l a n g - h t m l P r e t t y p r i n t - o v e r r i d e " > < c o d e > L U T . t x t < b r / > < b r / > 1 1 1 1 1 1 1 0 . 9 4 1 1 1 8 0 7 9 5 8 9 0 6 4 < b r / > 1 1 1 1 1 2 - 0 . 1 < b r / > 1 1 1 1 1 3 0 . 5 5 6 2 0 0 4 9 9 0 8 4 8 5 7 9 < b r / > 1 1 1 1 1 4 1 . 9 8 9 0 7 1 2 8 9 0 2 5 9 5 < b r / > 1 1 1 1 2 1 1 1 . 8 6 2 1 5 1 1 5 7 5 2 6 2 9 1 < b r / > 1 1 1 1 2 2 0 < b r / > 1 1 1 1 2 3 - 0 . 3 8 4 2 3 5 5 9 4 4 3 1 2 8 2 3 6 < b r / > 1 1 1 1 2 4 0 . 2 9 2 4 4 2 9 8 8 2 3 7 2 8 2 2 < b r / > 1 1 1 1 3 1 0 < b r / > 1 1 1 1 3 2 0 < b r / > 1 1 1 1 3 3 0 < b r / > 1 1 1 1 3 4 0 . 1 2 2 7 5 0 9 5 8 8 6 2 9 4 2 4 3 < b r / > 1 1 1 1 4 1 - 0 . 0 5 4 5 6 1 8 0 3 2 2 3 7 3 8 6 < b r / > 1 1 1 1 4 2 1 . 1 1 1 1 4 9 7 5 4 5 3 6 8 1 5 < b r / > 1 1 1 1 4 3 - 0 . 6 4 8 3 9 4 0 6 9 6 0 9 8 0 7 6 < b r / > 1 1 1 1 4 4 - 0 . 3 0 3 9 7 0 0 4 4 4 1 3 3 6 3 9 5 < b r / > 1 1 1 2 1 1 8 . 1 0 4 9 4 6 5 1 5 8 4 5 2 2 4 < b r / > 1 1 1 2 1 2 3 . 4 6 7 9 9 1 4 8 6 3 3 3 4 4 4 7 < b r / > 1 1 1 2 1 3 3 . 6 6 2 0 0 3 9 8 5 1 1 9 9 5 2 < b r / > 1 1 1 2 1 4 6 . 2 7 7 6 8 5 6 7 6 4 5 7 8 3 9 < b r / > 1 1 1 2 2 1 1 2 . 5 5 2 7 1 0 5 4 6 0 2 2 2 8 1 < b r / > 1 1 1 2 2 2 - 0 . 0 9 0 9 9 2 6 7 9 4 8 1 9 0 8 4 5 < b r / > 1 1 1 2 2 3 - 0 . 2 9 5 6 6 5 4 5 0 2 3 9 5 2 9 6 7 < b r / > 1 1 1 2 2 4 3 . 1 4 8 7 8 9 0 5 0 0 9 2 7 0 6 3 < b r / > 1 1 1 2 3 1 0 < b r / > 1 1 1 2 3 2 0 < b r / > 1 1 1 2 3 3 0 < b r / > 1 1 1 2 3 4 8 . 9 3 4 9 1 2 1 4 3 0 4 0 6 5 2 E - 4 < b r / > 1 1 1 2 4 1 3 . 8 9 5 1 2 6 7 2 5 0 3 2 6 7 2 < b r / > 1 1 1 2 4 2 - 0 . 2 0 1 0 0 1 6 2 1 2 9 7 1 9 8 4 < b r / > 1 1 1 2 4 3 0 . 8 3 7 4 2 9 5 4 3 5 3 6 9 1 2 < b r / > 1 1 1 2 4 4 - 0 . 2 7 6 6 3 0 5 3 4 9 1 6 9 4 6 5 6 < b r / > 1 1 1 3 1 1 1 1 . 6 5 3 9 5 1 5 1 3 9 9 0 3 7 1 < b r / > 1 1 1 3 1 2 - 0 . 2 9 4 6 9 7 3 1 4 5 0 8 9 2 0 8 < b r / > 1 1 1 3 1 3 - 0 . 2 9 7 8 1 8 4 4 4 8 8 8 8 4 7 2 < b r / > 1 1 1 3 1 4 0 . 8 2 7 9 3 9 3 7 7 8 7 9 1 1 6 4 < b r / > 1 1 1 3 2 1 0 < b r / > 1 1 1 3 2 2 0 < b r / > 1 1 1 3 2 3 0 < b r / > 1 1 1 3 2 4 2 . 2 6 4 1 6 3 3 7 6 1 2 0 1 1 1 4 < b r / > 1 1 1 3 3 1 0 < b r / > 1 1 1 3 3 2 0 < b r / > 1 1 1 3 3 3 0 < b r / > 1 1 1 3 3 4 0 < b r / > 1 1 1 3 4 1 0 < b r / > 1 1 1 3 4 2 0 < b r / > 1 1 1 3 4 3 1 . 1 7 3 2 7 2 5 0 5 9 5 8 3 2 4 9 < b r / > 1 1 1 3 4 4 - 0 . 1 < b r / > 1 1 2 1 1 1 5 . 5 3 5 9 0 3 8 8 5 9 1 7 9 5 3 5 < b r / > 1 1 2 1 1 2 0 < b r / > 1 1 2 1 1 3 0 < b r / > 1 1 2 1 1 4 0 . 0 < b r / > 1 1 2 1 2 1 0 . 0 8 6 5 9 9 9 5 2 2 6 0 7 0 3 2 7 < b r / > 1 1 2 1 2 2 0 . 2 7 9 8 0 7 2 1 3 9 5 5 3 1 1 4 < b r / > 1 1 2 1 2 3 5 . 4 9 0 7 8 1 1 0 1 3 4 2 3 2 < b r / > 1 1 2 1 2 4 - 0 . 3 1 0 8 7 4 5 9 5 2 0 2 4 5 6 8 < b r / > 1 1 2 1 3 1 - 0 . 0 5 9 6 5 2 3 7 0 7 4 9 2 3 0 3 3 < b r / > 1 1 2 1 3 2 0 . 0 9 2 5 3 9 2 4 7 0 7 3 6 9 8 5 4 < b r / > 1 1 2 1 3 3 - 0 . 4 < b r / > 1 1 2 1 3 4 3 . 1 6 1 9 7 2 0 9 9 0 0 2 6 1 8 < b r / > 1 1 2 1 4 1 - 0 . 5 2 6 0 7 6 6 5 7 0 0 3 4 8 1 2 < b r / > 1 1 2 1 4 2 - 0 . 4 8 0 9 0 1 1 8 8 3 7 1 5 6 2 5 4 < b r / > 1 1 2 1 4 3 - 0 . 7 3 1 0 8 2 2 7 5 5 5 3 2 7 8 8 < b r / > 1 1 2 1 4 4 3 . 4 8 6 6 1 7 4 3 9 6 3 1 5 8 1 < b r / > 1 1 2 2 1 1 0 < b r / > 1 1 2 2 1 2 0 < b r / > 1 1 2 2 1 3 0 < b r / > 1 1 2 2 1 4 0 . 6 5 2 2 5 8 8 1 1 9 3 2 6 0 3 2 < b r / > 1 1 2 2 2 1 0 < b r / > 1 1 2 2 2 2 0 < b r / > 1 1 2 2 2 3 0 < b r / > 1 1 2 2 2 4 0 . 7 4 6 0 3 0 3 9 8 4 8 4 7 7 4 9 < b r / > 1 1 2 2 3 1 0 . 2 3 7 3 6 4 8 4 5 2 9 8 2 1 2 9 5 < b r / > 1 1 2 2 3 2 0 . 4 0 5 2 7 8 8 5 4 4 8 5 7 5 4 6 < b r / > 1 1 2 2 3 3 0 < b r / > 1 1 2 2 3 4 2 . 9 5 1 6 3 1 1 0 0 3 4 4 3 7 2 < b r / > 1 1 2 2 4 1 0 . 5 6 5 3 6 5 5 6 7 9 3 7 5 4 0 6 < b r / > 1 1 2 2 4 2 0 . 4 9 7 1 8 1 0 4 6 5 3 3 4 6 1 6 < b r / > 1 1 2 2 4 3 7 . 4 0 2 0 0 4 6 9 3 8 6 6 5 4 3 < b r / > 1 1 2 2 4 4 - 0 . 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 < b r / > 1 1 2 3 1 1 0 < b r / > 1 1 2 3 1 2 0 < b r / > 1 1 2 3 1 3 0 < b r / > 1 1 2 3 1 4 0 < b r / > 1 1 2 3 2 1 0 < b r / > 1 1 2 3 2 2 0 < b r / > 1 1 2 3 2 3 0 < b r / > 1 1 2 3 2 4 0 < b r / > 1 1 2 3 3 1 0 < b r / > 1 1 2 3 3 2 0 < b r / > 1 1 2 3 3 3 0 . 4 1 5 1 8 7 8 2 5 9 7 6 8 6 0 4 < b r / > 1 1 2 3 3 4 1 . 7 7 2 4 1 0 4 7 3 6 0 4 2 4 0 5 < b r / > 1 1 2 3 4 1 0 < b r / > 1 1 2 3 4 2 0 < b r / > 1 1 2 3 4 3 4 . 0 6 9 8 9 6 8 8 5 4 6 4 7 4 9 < b r / > 1 1 2 3 4 4 - 0 . 4 < b r / > 1 1 3 1 1 1 0 < b r / > 1 1 3 1 1 2 0 . 0 2 2 5 6 6 9 8 6 5 9 8 2 8 2 8 2 3 < b r / > 1 1 3 1 1 3 0 . 0 8 7 2 4 3 2 0 7 5 8 2 0 8 1 4 4 < b r / > 1 1 3 1 1 4 1 0 . 0 5 4 3 2 2 1 4 8 2 4 6 6 2 < b r / > 1 1 3 1 2 1 1 . 0 5 6 4 4 1 4 0 3 5 1 6 1 5 9 1 < b r / > 1 1 3 1 2 2 - 0 . 2 9 0 2 9 6 0 2 9 2 4 1 5 3 3 6 4 < b r / > 1 1 3 1 2 3 - 0 . 5 5 4 1 0 3 8 2 2 5 1 3 1 5 9 1 < b r / > 1 1 3 1 2 4 8 . 6 7 2 3 2 4 8 7 2 3 7 8 9 8 8 < b r / > 1 1 3 1 3 1 - 0 . 3 6 5 4 2 3 4 5 6 6 0 0 3 7 3 9 < b r / > 1 1 3 1 3 2 - 0 . 4 < b r / > 1 1 3 1 3 3 0 . 5 0 0 4 1 9 2 6 6 9 3 4 9 1 9 9 < b r / > 1 1 3 1 3 4 2 . 0 7 8 0 8 2 5 3 2 1 1 9 6 7 4 < b r / > 1 1 3 1 4 1 0 < b r / > 1 1 3 1 4 2 0 < b r / > 1 1 3 1 4 3 0 < b r / > 1 1 3 1 4 4 1 . 2 5 2 5 1 0 7 2 2 1 5 3 3 3 5 4 < b r / > 1 1 3 2 1 1 0 < b r / > 1 1 3 2 1 2 0 . 2 9 4 9 5 6 9 5 5 0 2 8 8 8 5 6 4 < b r / > 1 1 3 2 1 3 - 0 . 0 7 5 2 9 4 8 1 4 0 1 5 9 5 7 5 6 < b r / > 1 1 3 2 1 4 - 0 . 2 4 0 4 5 1 4 4 2 1 5 1 4 2 7 2 < b r / > 1 1 3 2 2 1 - 0 . 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 < b r / > 1 1 3 2 2 2 0 . 7 4 4 5 6 1 5 1 9 5 5 1 4 3 9 5 < b r / > 1 1 3 2 2 3 - 0 . 3 6 5 8 3 1 7 7 5 5 6 6 6 0 4 7 < b r / > 1 1 3 2 2 4 8 . 5 5 3 6 5 6 9 4 0 7 5 6 9 0 2 < b r / > 1 1 3 2 3 1 - 0 . 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 < b r / > 1 1 3 2 3 2 4 . 6 0 1 0 5 5 7 4 9 6 6 5 0 9 1 5 < b r / > 1 1 3 2 3 3 - 0 . 3 8 7 9 3 8 5 8 4 0 4 6 5 7 4 2 < b r / > 1 1 3 2 3 4 - 0 . 2 < b r / > 1 1 3 2 4 1 0 . 4 3 2 6 8 1 9 9 3 8 5 4 8 7 7 4 < b r / > 1 1 3 2 4 2 0 < b r / > 1 1 3 2 4 3 0 < b r / > 1 1 3 2 4 4 1 . 1 9 4 2 5 9 5 4 2 7 1 2 1 4 0 7 < b r / > 1 1 3 3 1 1 0 < b r / > 1 1 3 3 1 2 0 < b r / > 1 1 3 3 1 3 0 . 0 < b r / > 1 1 3 3 1 4 - 0 . 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 < b r / > 1 1 3 3 2 1 - 0 . 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 < b r / > 1 1 3 3 2 2 0 < b r / > 1 1 3 3 2 3 0 < b r / > 1 1 3 3 2 4 0 . 1 2 6 2 8 4 3 6 0 3 9 4 7 4 9 3 3 < b r / > 1 1 3 3 3 1 0 < b r / > 1 1 3 3 3 2 0 < b r / > 1 1 3 3 3 3 0 < b r / > 1 1 3 3 3 4 1 . 1 9 9 0 7 5 7 3 5 8 6 8 5 4 0 9 < b r / > 1 1 3 3 4 1 0 < b r / > 1 1 3 3 4 2 0 < b r / > 1 1 3 3 4 3 0 < b r / > 1 1 3 3 4 4 0 < b r / > 1 1 4 1 1 1 - 0 . 2 6 2 0 8 5 4 0 5 7 6 1 9 0 8 4 < b r / > 1 1 4 1 1 2 4 . 1 2 5 8 5 4 6 3 8 3 2 2 6 1 8 < b r / > 1 1 4 1 1 3 - 0 . 6 3 5 7 4 0 8 6 0 2 2 1 4 7 6 2 < b r / > 1 1 4 1 1 4 - 0 . 3 8 3 3 4 4 0 4 7 8 1 8 8 0 9 8 < b r / > 1 1 4 1 2 1 4 . 1 5 1 5 9 2 1 9 8 1 0 0 2 6 8 < b r / > 1 1 4 1 2 2 0 . 0 7 8 8 1 0 2 0 2 8 5 5 8 9 5 6 8 < b r / > 1 1 4 1 2 3 0 . 2 4 7 0 9 6 2 2 6 6 5 8 6 3 1 7 < b r / > 1 1 4 1 2 4 - 0 . 6 1 4 3 5 1 1 3 0 3 1 4 1 2 3 < b r / > 1 1 4 1 3 1 0 < b r / > 1 1 4 1 3 2 0 < b r / > 1 1 4 1 3 3 0 . 1 3 7 1 6 6 4 0 8 2 3 5 6 8 7 < b r / > 1 1 4 1 3 4 - 0 . 0 7 3 6 6 0 2 2 8 3 3 8 3 4 0 6 < b r / > 1 1 4 1 4 1 0 < b r / > 1 1 4 1 4 2 1 . 7 9 4 5 5 7 0 6 2 3 5 2 7 6 < b r / > 1 1 4 1 4 3 - 0 . 1 0 7 7 8 1 8 0 5 0 4 3 8 9 9 6 7 < b r / > 1 1 4 1 4 4 - 0 . 1 0 9 5 < b r / > 1 1 4 2 1 1 4 . 0 9 3 0 9 9 2 3 5 3 6 1 0 0 4 < b r / > 1 1 4 2 1 2 0 . 4 3 7 7 3 3 6 8 5 1 5 3 4 5 2 8 5 < b r / > 1 1 4 2 1 3 - 0 . 2 2 7 2 2 1 4 3 1 7 0 6 8 8 8 1 3 < b r / > 1 1 4 2 1 4 - 0 . 4 7 2 5 4 4 0 8 3 7 5 0 8 4 9 5 5 < b r / > 1 1 4 2 2 1 0 . 9 6 6 6 0 7 0 6 5 6 0 2 1 0 3 1 < b r / > 1 1 4 2 2 2 5 . 3 2 5 7 6 4 8 1 9 7 2 1 2 1 7 5 < b r / > 1 1 4 2 2 3 0 . 8 5 5 0 2 5 7 5 7 1 9 8 3 3 9 1 < b r / > 1 1 4 2 2 4 1 . 7 2 9 4 1 3 3 6 1 8 5 8 1 1 9 6 < b r / > 1 1 4 2 3 1 0 < b r / > 1 1 4 2 3 2 0 < b r / > 1 1 4 2 3 3 0 . 2 1 6 9 3 0 9 8 9 6 5 9 2 9 4 3 3 < b r / > 1 1 4 2 3 4 - 0 . 2 0 0 5 6 6 4 9 2 5 8 7 2 7 2 7 2 < b r / > 1 1 4 2 4 1 0 < b r / > 1 1 4 2 4 2 0 < b r / > 1 1 4 2 4 3 - 0 . 0 0 4 2 0 7 8 9 0 7 6 4 5 4 6 6 4 < b r / > 1 1 4 2 4 4 - 0 . 0 3 9 8 0 3 9 6 6 1 7 1 4 8 6 9 9 < b r / > 1 1 4 3 1 1 - 0 . 1 4 8 9 4 6 6 1 3 1 9 0 7 1 2 4 2 < b r / > 1 1 4 3 1 2 2 . 8 3 1 8 0 0 4 9 8 4 9 9 6 0 8 6 < b r / > 1 1 4 3 1 3 0 . 0 9 9 7 2 0 0 3 8 3 5 4 2 1 4 2 8 < b r / > 1 1 4 3 1 4 - 0 . 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 < b r / > 1 1 4 3 2 1 - 0 . 2 2 0 1 4 7 7 1 2 0 7 8 5 2 6 1 8 < b r / > 1 1 4 3 2 2 3 . 6 6 1 3 2 6 3 8 4 8 4 9 0 2 3 6 < b r / > 1 1 4 3 2 3 - 0 . 9 6 1 6 4 2 1 3 2 9 1 1 2 8 9 < b r / > 1 1 4 3 2 4 - 0 . 3 7 5 8 7 6 2 9 8 2 2 5 2 6 0 1 4 < b r / > 1 1 4 3 3 1 0 < b r / > 1 1 4 3 3 2 0 < b r / > 1 1 4 3 3 3 0 < b r / > 1 1 4 3 3 4 0 < b r / > 1 1 4 3 4 1 0 < b r / > 1 1 4 3 4 2 0 < b r / > 1 1 4 3 4 3 0 < b r / > 1 1 4 3 4 4 0 . 0 1 0 2 9 1 7 4 9 1 2 9 2 0 4 0 1 < b r / > 1 2 1 1 1 1 8 . 7 4 9 2 8 3 1 5 0 5 4 4 0 2 5 < b r / > 1 2 1 1 1 2 5 . 1 6 0 3 0 3 4 3 6 3 0 1 4 4 5 < b r / > 1 2 1 1 1 3 5 . 4 9 2 9 6 8 8 8 2 6 5 9 6 8 6 < b r / > 1 2 1 1 1 4 5 . 1 3 0 0 0 0 5 4 5 6 1 8 7 5 4 5 < b r / > 1 2 1 1 2 1 9 . 0 8 0 2 9 6 3 7 1 0 0 3 4 8 5 < b r / > 1 2 1 1 2 2 5 . 4 8 4 5 2 0 9 4 1 7 8 3 9 4 < b r / > 1 2 1 1 2 3 8 . 3 6 4 7 8 5 5 6 3 9 6 4 7 0 7 < b r / > 1 2 1 1 2 4 8 . 9 8 8 9 0 5 3 3 4 3 8 5 4 5 3 < b r / > 1 2 1 1 3 1 0 < b r / > 1 2 1 1 3 2 0 < b r / > 1 2 1 1 3 3 3 . 9 6 5 7 6 5 3 2 0 2 2 1 7 7 6 4 < b r / > 1 2 1 1 3 4 - 0 . 1 < b r / > 1 2 1 1 4 1 4 . 2 9 9 7 1 4 7 9 5 4 8 5 2 4 2 < b r / > 1 2 1 1 4 2 - 0 . 2 0 1 0 0 9 4 0 6 6 1 8 9 6 5 8 2 < b r / > 1 2 1 1 4 3 - 0 . 1 4 4 7 5 8 9 9 9 9 4 0 1 0 9 0 5 < b r / > 1 2 1 1 4 4 0 . 7 7 3 5 7 2 6 0 9 2 1 0 9 7 1 6 < b r / > 1 2 1 2 1 1 8 . 9 2 5 2 8 5 9 2 7 6 5 1 6 6 8 < b r / > 1 2 1 2 1 2 7 . 2 4 2 3 7 8 8 0 9 7 1 4 6 2 8 < b r / > 1 2 1 2 1 3 5 . 8 2 5 2 4 1 5 5 1 7 5 6 8 1 6 < b r / > 1 2 1 2 1 4 7 . 1 1 3 4 5 5 2 6 4 7 4 9 1 4 7 < b r / > 1 2 1 2 2 1 1 0 . 9 5 7 1 7 2 4 1 0 5 0 7 5 8 5 < b r / > 1 2 1 2 2 2 7 . 9 1 4 4 9 9 9 5 4 0 4 5 6 1 5 < b r / > 1 2 1 2 2 3 8 . 4 3 6 7 0 5 0 7 9 1 3 8 2 8 < b r / > 1 2 1 2 2 4 9 . 4 8 3 2 7 1 7 2 5 9 0 3 0 4 5 < b r / > 1 2 1 2 3 1 0 < b r / > 1 2 1 2 3 2 0 < b r / > 1 2 1 2 3 3 0 < b r / > 1 2 1 2 3 4 1 . 0 6 1 8 6 7 9 3 2 3 1 5 4 6 0 5 < b r / > 1 2 1 2 4 1 3 . 9 1 6 7 4 3 5 1 0 5 8 9 5 8 5 < b r / > 1 2 1 2 4 2 - 0 . 3 0 8 1 6 9 8 3 2 1 5 5 0 4 3 2 3 < b r / > 1 2 1 2 4 3 0 . 1 8 6 4 4 5 4 8 9 6 2 1 0 0 6 8 8 < b r / > 1 2 1 2 4 4 - 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