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/*********************************************************************
MLDemos: A User-Friendly visualization toolkit for machine learning
Copyright (C) 2010 Basilio Noris
Contact: mldemos@b4silio.com
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public License,
version 3 as published by the Free Software Foundation.
This library is distributed in the hope that it will be useful, but
WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free
Software Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
*********************************************************************/
#include "interfaceGBRegress.h"
#include <QPixmap>
#include <QBitmap>
#include <QPainter>
using namespace std;
RegrGB::RegrGB()
{
params = new Ui::ParametersGBRegress();
params->setupUi(widget = new QWidget());
}
RegrGB::~RegrGB()
{
delete params;
}
void RegrGB::SetParams(Regressor *regressor)
{
if(!regressor) return;
// hHH ere we gather the different hyperparameters from the interface
int boostIters = params->boostIters->value();
int boostLossType = params->boostLossType->currentIndex()+1;
int boostTreeDepths = params->boostTreeDepths->value();
((RegressorGB *)regressor)->SetParams(boostIters,boostLossType,boostTreeDepths);
}
fvec RegrGB::GetParams()
{
int boostIters = params->boostIters->value();
int boostLossType = params->boostLossType->currentIndex();
int boostTreeDepths = params->boostTreeDepths->value();
fvec par(3);
par[0] = boostIters;
par[1] = boostLossType;
par[2] = boostTreeDepths;
return par;
}
void RegrGB::SetParams(Regressor *regressor, fvec parameters)
{
if(!regressor) return;
int boostIters = parameters.size() > 0 ? parameters[0] : 1;
int boostLossType = parameters.size() > 1 ? parameters[1] : 1;
int boostTreeDepths = parameters.size() > 2 ? parameters[2] : 1;
((RegressorGB *)regressor)->SetParams(boostIters,boostLossType+1,boostTreeDepths);
}
void RegrGB::GetParameterList(std::vector<QString> ¶meterNames,
std::vector<QString> ¶meterTypes,
std::vector< std::vector<QString> > ¶meterValues)
{
parameterNames.clear();
parameterTypes.clear();
parameterValues.clear();
parameterNames.push_back("Iterations (WL count)");
parameterNames.push_back("Loss Type");
parameterNames.push_back("Tree Depth");
parameterTypes.push_back("Integer");
parameterTypes.push_back("List");
parameterTypes.push_back("Integer");
parameterValues.push_back(vector<QString>());
parameterValues.back().push_back("1");
parameterValues.back().push_back("999999");
parameterValues.push_back(vector<QString>());
parameterValues.back().push_back("Squared Loss");
parameterValues.back().push_back("Absolute Loss");
parameterValues.back().push_back("Huber Loss");
parameterValues.push_back(vector<QString>());
parameterValues.back().push_back("1");
parameterValues.back().push_back("999999");
}
QString RegrGB::GetAlgoString()
{
int boostIters = params->boostIters->value();
int boostLossType = params->boostLossType->currentIndex()+1;
int boostTreeDepths = params->boostTreeDepths->value();
QString algo = QString("MyExample %1 %2 %3").arg(boostIters).arg(boostLossType).arg(boostTreeDepths);
return algo;
}
Regressor *RegrGB::GetRegressor()
{
RegressorGB *regressor = new RegressorGB();
SetParams(regressor);
return regressor;
}
void RegrGB::DrawConfidence(Canvas *canvas, Regressor *regressor)
{
canvas->maps.confidence = QPixmap();
}
void RegrGB::DrawModel(Canvas *canvas, QPainter &painter, Regressor *regressor)
{
if(!regressor || !canvas) return;
painter.setRenderHint(QPainter::Antialiasing, true);
int xIndex = canvas->xIndex;
int w = canvas->width();
fvec sample = canvas->toSampleCoords(0,0);
int dim = sample.size();
if(dim > 2) return;
int steps = w;
QPointF oldPoint(-FLT_MAX,-FLT_MAX);
FOR(x, steps)
{
sample = canvas->toSampleCoords(x,0);
fvec res = regressor->Test(sample);
if(res[0] != res[0]) continue; // NaN!
QPointF point = canvas->toCanvasCoords(sample[xIndex], res[0]);
if(x)
{
painter.setPen(QPen(Qt::black, 1));
painter.drawLine(point, oldPoint);
}
oldPoint = point;
}
}
void RegrGB::SaveOptions(QSettings &settings)
{
// HH we save to the system registry each parameter value
settings.setValue("boostIters", params->boostIters->value());
settings.setValue("boostLossType", params->boostLossType->currentIndex());
settings.setValue("boostTreeDepths", params->boostTreeDepths->value());
}
bool RegrGB::LoadOptions(QSettings &settings)
{
// HH we load the parameters from the registry so that when we launch the program we keep all values
if(settings.contains("boostIters")) params->boostIters->setValue(settings.value("boostIters").toInt());
if(settings.contains("boostLossType")) params->boostLossType->setCurrentIndex(settings.value("boostLossType").toInt());
if(settings.contains("boostTreeDepths")) params->boostTreeDepths->setValue(settings.value("boostTreeDepths").toInt());
return true;
}
void RegrGB::SaveParams(QTextStream &file)
{
// HH same as above but for files/string saving
file << "regressionOptions" << ":" << "boostIters" << " " << params->boostIters->value() << "\n";
file << "regressionOptions" << ":" << "boostLossType" << " " << params->boostLossType->currentIndex() << "\n";
file << "regressionOptions" << ":" << "boostTreeDepths" << " " << params->boostTreeDepths->value() << "\n";
}
bool RegrGB::LoadParams(QString name, float value)
{
// HH
if(name.endsWith("boostIters")) params->boostIters->setValue((int)value);
if(name.endsWith("boostLossType")) params->boostLossType->setCurrentIndex((int)value);
if(name.endsWith("boostTreeDepths")) params->boostTreeDepths->setValue((int)value);
return true;
}
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