Moved neuralnet classes into own library

neuralnetdemo/main.cpp

@@ -0,0 +1,92 @@
+#include <QCoreApplication>
+#include <QQueue>
+#include <QList>
+#include <QVector>
+#include <QDebug>
+
+#include "debug.h"
+#include "neuralnet.h"
+#include "interfaces/ineurallayer.h"
+#include "interfaces/ineuron.h"
+
+const qreal low = .01;
+const qreal mid = .5;
+const qreal high = .99;
+const int iterations = 5;
+
+int main(int argc, char *argv[])
+{
+    QCoreApplication a(argc, argv);
+
+    if(!initDebug())
+        return -1;
+
+    QQueue<qreal> random;
+    random.enqueue(0.248668584157093);
+    random.enqueue(0.110743977181029);
+    random.enqueue(0.467010679872246);
+    random.enqueue(0.771604122021982);
+    random.enqueue(0.657518893786482);
+    random.enqueue(0.432782601300991);
+    random.enqueue(0.354083763600366);
+    random.enqueue(0.943862276125635);
+    random.enqueue(0.101266453555444);
+
+    NeuralNet net(2, 2, 1, random);
+
+    QList<QVector<qreal> > input {
+        QVector<qreal> { high, high },
+        QVector<qreal> { low, high },
+        QVector<qreal> { high, low },
+        QVector<qreal> { low, low }
+    };
+
+    QList<QVector<qreal> > output {
+        QVector<qreal> { low },
+        QVector<qreal> { high },
+        QVector<qreal> { high },
+        QVector<qreal> { low }
+    };
+
+    int count = 0;
+    qreal hh, lh, hl, ll;
+    do
+    {
+        net.setLearningRate(3);
+        net.trainBackPropagation(input, output, iterations);
+
+        net.inputLayer()->neurons().at(0)->setOutput(high);
+        net.inputLayer()->neurons().at(1)->setOutput(high);
+        net.pulse();
+        hh = net.outputLayer()->neurons().at(0)->output();
+
+        net.inputLayer()->neurons().at(0)->setOutput(low);
+        net.inputLayer()->neurons().at(1)->setOutput(high);
+        net.pulse();
+        lh = net.outputLayer()->neurons().at(0)->output();
+
+        net.inputLayer()->neurons().at(0)->setOutput(high);
+        net.inputLayer()->neurons().at(1)->setOutput(low);
+        net.pulse();
+        hl = net.outputLayer()->neurons().at(0)->output();
+
+        net.inputLayer()->neurons().at(0)->setOutput(low);
+        net.inputLayer()->neurons().at(1)->setOutput(low);
+        net.pulse();
+        ll = net.outputLayer()->neurons().at(0)->output();
+
+        debug(QString("round %0: hh=%1 lh=%2 hl=%3 ll=%4").arg(count++).arg(hh, 0, 'f', 8).arg(lh, 0, 'f', 8).arg(hl, 0, 'f', 8).arg(ll, 0, 'f', 8));
+    }
+    while(hh > (mid + low) / 2.0 ||
+          lh < (mid + high) / 2.0 ||
+          hl < (mid + low) / 2.0 ||
+          ll > (mid + high) / 2);
+
+    qDebug() << count * iterations << "iterations";
+    qDebug() << "hh" << hh;
+    qDebug() << "lh" << lh;
+    qDebug() << "hl" << hl;
+    qDebug() << "ll" << ll;
+
+    return 0;
+}