iCub-main
DummyLearner.cpp
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1 /*
2  * Copyright (C) 2007-2011 RobotCub Consortium, European Commission FP6 Project IST-004370
3  * author: Arjan Gijsberts
4  * email: arjan.gijsberts@iit.it
5  * website: www.robotcub.org
6  * Permission is granted to copy, distribute, and/or modify this program
7  * under the terms of the GNU General Public License, version 2 or any
8  * later version published by the Free Software Foundation.
9  *
10  * A copy of the license can be found at
11  * http://www.robotcub.org/icub/license/gpl.txt
12  *
13  * This program is distributed in the hope that it will be useful, but
14  * WITHOUT ANY WARRANTY; without even the implied warranty of
15  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
16  * Public License for more details
17  */
18 
19 #include <iostream>
20 
23 
25 
26 namespace iCub {
27 namespace learningmachine {
28 
29 // just here for debugging, since Vector.toString() cannot be applied to const Vector :(
30 std::string printVector(const yarp::sig::Vector& v) {
31  std::ostringstream output;
32  output << "[";
33  for(size_t i = 0; i < v.size(); i++) {
34  if(i > 0) output << ",";
35  output << v[i];
36  }
37  output << "]";
38  return output.str();
39 }
40 
41 void DummyLearner::feedSample(const yarp::sig::Vector& input, const yarp::sig::Vector& output) {
42  // call parent method to let it do some validation and processing with the transformers for us
43  this->IFixedSizeLearner::feedSample(input, output);
44 
45  std::cout << "Received a sample: " << printVector(input) << " => " << printVector(output) << std::endl;
46 
47  this->inputs.push_back(input);
48  this->outputs.push_back(input);
49 }
50 
52  this->sampleCount = this->inputs.size();
53  this->trainCount++;
54 }
55 
56 Prediction DummyLearner::predict(const yarp::sig::Vector& input) {
57  this->checkDomainSize(input);
58  std::cout << "Received a prediction sample: " << printVector(input) << " => ";
59  yarp::sig::Vector output = input;
60  output.resize(this->getCoDomainSize());
61  for(size_t i = 0; i < output.size(); i++)
62  output[i] += this->sampleCount;
63  std::cout << "(" << printVector(output) << ")" << std::endl;
64  return Prediction(output);
65 }
66 
68  this->sampleCount = 0;
69  this->trainCount = 0;
70  this->inputs.clear();
71  this->outputs.clear();
72 }
73 
74 std::string DummyLearner::getInfo() {
75  std::ostringstream buffer;
76  buffer << this->IFixedSizeLearner::getInfo();
77  buffer << "Training Samples: " << this->sampleCount << std::endl;
78  buffer << "Training Iterations: " << this->trainCount << std::endl;
79  buffer << "Collected Samples: " << this->inputs.size() << std::endl;
80  return buffer.str();
81 }
82 
83 void DummyLearner::writeBottle(yarp::os::Bottle& bot) const {
84  bot << this->sampleCount << this->trainCount;
85  // make sure to call the superclass's method
87 }
88 
89 void DummyLearner::readBottle(yarp::os::Bottle& bot) {
90  // make sure to call the superclass's method
92  bot >> this->trainCount >> this->sampleCount;
93 }
94 
95 
96 } // learningmachine
97 } // iCub
virtual void writeBottle(yarp::os::Bottle &bot) const
Writes a serialization of the machine into a bottle.
virtual void train()
Train the learning machine on the examples that have been supplied so far.
void reset()
Forget everything and start over.
std::string getInfo()
Asks the learning machine to return a string containing information on its operation so far.
virtual void feedSample(const yarp::sig::Vector &input, const yarp::sig::Vector &output)
Provide the learning machine with an example of the desired mapping.
Prediction predict(const yarp::sig::Vector &input)
Ask the learning machine to predict the output for a given input.
virtual void readBottle(yarp::os::Bottle &bot)
Unserializes a machine from a bottle.
virtual void writeBottle(yarp::os::Bottle &bot) const
Writes a serialization of the machine into a bottle.
virtual void feedSample(const yarp::sig::Vector &input, const yarp::sig::Vector &output)
Provide the learning machine with an example of the desired mapping.
virtual void readBottle(yarp::os::Bottle &bot)
Unserializes a machine from a bottle.
virtual std::string getInfo()
Asks the learning machine to return a string containing information on its operation so far.
A class that represents a prediction result.
Definition: Prediction.h:44
static int v
Definition: iCub_Sim.cpp:42
PortablePair< Vector, Vector > Prediction
Definition: test.cpp:52
std::string printVector(const yarp::sig::Vector &v)
This file contains the definition of unique IDs for the body parts and the skin parts of the robot.