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test rewritten

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Shin
2016-04-18 16:03:33 +02:00
parent e6a5882e58
commit 9f1f0fe763
11 changed files with 289 additions and 287 deletions
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56
tests/perceptron_learning.cpp
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@@ -1,41 +1,39 @@
#include <NeuralNetwork/Learning/PerceptronLearning.h>
#include <cassert>
#include <iostream>
#include <gtest/gtest.h>
int main() {
{ // XOR problem
NeuralNetwork::FeedForward::Perceptron n(2,1);
n.randomizeWeights();
TEST(PerceptronLearning,XOR) {
NeuralNetwork::FeedForward::Perceptron n(2,1);
NeuralNetwork::Learning::PerceptronLearning learn(n);
n.randomizeWeights();
for(int i=0;i<10;i++) {
learn.teach({1,0},{1});
learn.teach({1,1},{1});
learn.teach({0,0},{0});
learn.teach({0,1},{1});
}
NeuralNetwork::Learning::PerceptronLearning learn(n);
{
std::vector<float> ret =n.computeOutput({1,1});
assert(ret[0] > 0.9);
}
for(int i=0;i<10;i++) {
learn.teach({1,0},{1});
learn.teach({1,1},{1});
learn.teach({0,0},{0});
learn.teach({0,1},{1});
}
{
std::vector<float> ret =n.computeOutput({0,1});
assert(ret[0] > 0.9);
}
{
std::vector<float> ret =n.computeOutput({1,1});
ASSERT_GT(ret[0], 0.9);
}
{
std::vector<float> ret =n.computeOutput({1,0});
assert(ret[0] > 0.9);
}
{
std::vector<float> ret =n.computeOutput({0,1});
ASSERT_GT(ret[0], 0.9);
}
{
std::vector<float> ret =n.computeOutput({0,0});
assert(ret[0] < 0.1);
}
{
std::vector<float> ret =n.computeOutput({1,0});
ASSERT_GT(ret[0], 0.9);
}
{
std::vector<float> ret =n.computeOutput({0,0});
ASSERT_LT(ret[0], 0.1);
}
}