// This macro reads in the data file "test_results.dat" that is made by the
// test_results program and makes a plot of the output produced by the
// ANN vs. the actual output.
//
// As a reminder, this test trained the ANN to multiply two numbers, each
// from 0 to 3. The training sample only used integer values for each
// input so the values in between are a result of the ANN exrapolating into
// an area where no training samples were provided.


void output_vs_actual(void)
{	
	TTree *t = new TTree("t","A tree");
	t->ReadFile("test_results.dat","input1:input2:output");
	
	TCanvas *c1 = new TCanvas("c1");
	c1->SetGrid();
	c1->SetTicks();
	
	TH2D *axes = new TH2D("axes","ANN multiplication test2", 100, -0.5, 10.0, 100, -0.5, 10.0);
	axes->SetStats(0);
	axes->SetXTitle("ANN output");
	axes->SetYTitle("input1*input2");
	axes->Draw();
	
	TLegend *leg = new TLegend(0.15, 0.6, 0.5, 0.85);
	leg->SetFillColor(kWhite);
	
	TLine *l = new TLine(-0.5, -0.5, 10.0, 10.0);
	l->SetLineColor(kMagenta);
	l->Draw();
	leg->AddEntry(l, "perfect correlation");
	
	// Draw line of ideal result
	t->SetMarkerStyle(1);
	t->SetMarkerSize(0.3);
	t->Draw("output:input1*input2","","same");
	
	// Draw markers at training points
	for(int i=0; i<=3; i++){
		for(int j=i; j<=3; j++){
			double x = (double)i*(double)j;
			TMarker *m = new TMarker(x, x, 22);
			m->SetMarkerColor(kMagenta);
			m->SetMarkerSize(1.25);
			m->Draw();
			if(i==0 && j==0)leg->AddEntry(m, "Training point");
		}
	}
	
	leg->Draw();

	c1->SaveAs("output_vs_actual.pdf");
	c1->SaveAs("output_vs_actual.png");
}