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Change codestyle in order to make the world a better place
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Milan Jelisavcic committed Aug 5, 2017
1 parent 5994087 commit dee7e6b
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1,262 changes: 707 additions & 555 deletions cpp/revolve/gazebo/brain/NeuralNetwork.cpp
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292 changes: 151 additions & 141 deletions cpp/revolve/gazebo/brain/NeuralNetwork.h
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// (bias, tau, gain) or (phase offset, period, gain)
#define MAX_NEURON_PARAMS 3

namespace revolve {
namespace gazebo {

typedef const boost::shared_ptr<revolve::msgs::ModifyNeuralNetwork const> ConstModifyNeuralNetworkPtr;
namespace revolve
{
namespace gazebo
{
typedef const boost::shared_ptr< revolve::msgs::ModifyNeuralNetwork const >
ConstModifyNeuralNetworkPtr;

/*
* Copied from NeuronRepresentation.h
*/
enum neuronType
{
INPUT,
SIMPLE,
SIGMOID,
CTRNN_SIGMOID,
OSCILLATOR,
SUPG
};

class NeuralNetwork: public Brain {
public:
/**
* @param Name of the robot
* @param The brain node
* @param Reference to motor list, which might be reordered
* @param Reference to the sensor list, which might be reordered
*/
NeuralNetwork(std::string modelName,
sdf::ElementPtr node,
std::vector< MotorPtr > & motors,
std::vector< SensorPtr > & sensors);
virtual ~NeuralNetwork();

/**
* @param Motor list
* @param Sensor list
*/
virtual void update(const std::vector< MotorPtr > & motors,
const std::vector< SensorPtr > & sensors,
double t,
double step);

protected:
/**
* Steps the neural network
*/
void step(double time);

/**
* Request handler to modify the neural network
*/
void modify(ConstModifyNeuralNetworkPtr &req);

// Mutex for stepping / updating the network
boost::mutex networkMutex_;

/**
* Transport node
*/
::gazebo::transport::NodePtr node_;

/**
* Network modification subscriber
*/
::gazebo::transport::SubscriberPtr alterSub_;

/*
* Connection weights, separated into three arrays for convenience. Note
* that only output and hidden neurons are weight targets.
*
* Weights are stored with gaps, meaning that every neuron holds entries for
* the maximum possible number of connections. This makes restructuring the
* weights arrays when a hidden neuron is removed slightly less cumbersome.
*/
double inputWeights_[MAX_INPUT_NEURONS * (MAX_OUTPUT_NEURONS + MAX_HIDDEN_NEURONS)];
double outputWeights_[MAX_OUTPUT_NEURONS * (MAX_OUTPUT_NEURONS + MAX_HIDDEN_NEURONS)];
double hiddenWeights_[MAX_HIDDEN_NEURONS * (MAX_OUTPUT_NEURONS + MAX_HIDDEN_NEURONS)];

// Unlike weights, types, params and current states are stored without
// gaps, meaning the first `m` entries are for output neurons, followed
// by `n` entries for hidden neurons. If a hidden neuron is removed,
// the items beyond it are moved back.
/**
* Type of each non-input neuron
*/
unsigned int types_[(MAX_OUTPUT_NEURONS + MAX_HIDDEN_NEURONS)];

/*
* Params for hidden and output neurons, quantity depends on the type of
* neuron
*/
double params_[MAX_NEURON_PARAMS * (MAX_OUTPUT_NEURONS + MAX_HIDDEN_NEURONS)];

/*
* Output states arrays for the current state and the next state.
*/
double state1_[MAX_OUTPUT_NEURONS + MAX_HIDDEN_NEURONS];
double state2_[MAX_OUTPUT_NEURONS + MAX_HIDDEN_NEURONS];

/**
* One input state for each input neuron
*/
double input_[MAX_INPUT_NEURONS];

/**
* Used to determine the current state array. False = state1,
* true = state2.
*/
bool flipState_;

/**
* Stores the type of each neuron ID
*/
std::map<std::string, std::string> layerMap_;

/**
* Stores the position of each neuron ID, relative to its type
*/
std::map<std::string, unsigned int> positionMap_;

/**
* The number of inputs
*/
unsigned int nInputs_;

/**
* The number of outputs
*/
unsigned int nOutputs_;

/**
* The number of hidden units
*/
unsigned int nHidden_;

/**
* The number of non-inputs (i.e. nOutputs + nHidden)
*/
unsigned int nNonInputs_;

private: void connectionHelper(const std::string &src,
const std::string &dst,
double weight);
};

} /* namespace gazebo */
enum neuronType
{
INPUT,
SIMPLE,
SIGMOID,
CTRNN_SIGMOID,
OSCILLATOR,
SUPG
};

class NeuralNetwork
: public Brain
{
public:
/**
* @param Name of the robot
* @param The brain node
* @param Reference to motor list, which might be reordered
* @param Reference to the sensor list, which might be reordered
*/
NeuralNetwork(std::string modelName,
sdf::ElementPtr node,
std::vector< MotorPtr > &motors,
std::vector< SensorPtr > &sensors);

virtual ~NeuralNetwork();

/**
* @param Motor list
* @param Sensor list
*/
virtual void update(const std::vector< MotorPtr > &motors,
const std::vector< SensorPtr > &sensors,
double t,
double step);

protected:
/**
* Steps the neural network
*/
void step(double time);

/**
* Request handler to modify the neural network
*/
void modify(ConstModifyNeuralNetworkPtr &req);

// Mutex for stepping / updating the network
boost::mutex networkMutex_;

/**
* Transport node
*/
::gazebo::transport::NodePtr node_;

/**
* Network modification subscriber
*/
::gazebo::transport::SubscriberPtr alterSub_;

/*
* Connection weights, separated into three arrays for convenience. Note
* that only output and hidden neurons are weight targets.
*
* Weights are stored with gaps, meaning that every neuron holds entries
* for the maximum possible number of connections. This makes
* restructuring the weights arrays when a hidden neuron is removed
* slightly less cumbersome.
*/
double inputWeights_[MAX_INPUT_NEURONS
* (MAX_OUTPUT_NEURONS + MAX_HIDDEN_NEURONS)];
double outputWeights_[MAX_OUTPUT_NEURONS
* (MAX_OUTPUT_NEURONS + MAX_HIDDEN_NEURONS)];
double hiddenWeights_[MAX_HIDDEN_NEURONS
* (MAX_OUTPUT_NEURONS + MAX_HIDDEN_NEURONS)];

// Unlike weights, types, params and current states are stored without
// gaps, meaning the first `m` entries are for output neurons, followed
// by `n` entries for hidden neurons. If a hidden neuron is removed,
// the items beyond it are moved back.
/**
* Type of each non-input neuron
*/
unsigned int types_[(MAX_OUTPUT_NEURONS + MAX_HIDDEN_NEURONS)];

/*
* Params for hidden and output neurons, quantity depends on the type of
* neuron
*/
double params_[
MAX_NEURON_PARAMS * (MAX_OUTPUT_NEURONS + MAX_HIDDEN_NEURONS)];

/*
* Output states arrays for the current state and the next state.
*/
double state1_[MAX_OUTPUT_NEURONS + MAX_HIDDEN_NEURONS];
double state2_[MAX_OUTPUT_NEURONS + MAX_HIDDEN_NEURONS];

/**
* One input state for each input neuron
*/
double input_[MAX_INPUT_NEURONS];

/**
* Used to determine the current state array. False = state1,
* true = state2.
*/
bool flipState_;

/**
* Stores the type of each neuron ID
*/
std::map< std::string, std::string > layerMap_;

/**
* Stores the position of each neuron ID, relative to its type
*/
std::map< std::string, unsigned int > positionMap_;

/**
* The number of inputs
*/
unsigned int nInputs_;

/**
* The number of outputs
*/
unsigned int nOutputs_;

/**
* The number of hidden units
*/
unsigned int nHidden_;

/**
* The number of non-inputs (i.e. nOutputs + nHidden)
*/
unsigned int nNonInputs_;

private:
void connectionHelper(const std::string &src,
const std::string &dst,
double weight);
};
} /* namespace gazebo */
} /* namespace revolve */

#endif /* REVOLVE_GAZEBO_BRAIN_NEURALNETWORK_H_ */
62 changes: 34 additions & 28 deletions cpp/revolve/gazebo/motors/JointMotor.cpp
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*
*/

#include <string>

#include <revolve/gazebo/motors/JointMotor.h>

namespace gz = gazebo;

namespace revolve {
namespace gazebo {

JointMotor::JointMotor(gz::physics::ModelPtr model,
std::string partId,
std::string motorId,
sdf::ElementPtr motor,
unsigned int outputs)
: Motor(model, partId, motorId, outputs)
namespace revolve
{
if (not motor->HasAttribute("joint")) {
std::cerr << "JointMotor requires a `joint` attribute." << std::endl;
throw std::runtime_error("Motor error");
}

auto jointName = motor->GetAttribute("joint")->GetAsString();
joint_ = model->GetJoint(jointName);
if (not joint_) {
std::cerr << "Cannot locate joint motor `" << jointName << "`" << std::endl;
throw std::runtime_error("Motor error");
}

jointName_ = joint_->GetScopedName();
}

JointMotor::~JointMotor() {}

} /* namespace gazebo */
} /* namespace revolve */
namespace gazebo
{
JointMotor::JointMotor(gz::physics::ModelPtr model,
std::string partId,
std::string motorId,
sdf::ElementPtr motor,
unsigned int outputs)
: Motor(model, partId, motorId, outputs)
{
if (not motor->HasAttribute("joint"))
{
std::cerr << "JointMotor requires a `joint` attribute." << std::endl;
throw std::runtime_error("Motor error");
}

auto jointName = motor->GetAttribute("joint")->GetAsString();
joint_ = model->GetJoint(jointName);
if (not joint_)
{
std::cerr << "Cannot locate joint motor `" << jointName
<< "`" << std::endl;
throw std::runtime_error("Motor error");
}

jointName_ = joint_->GetScopedName();
}

JointMotor::~JointMotor()
{}
} /* namespace gazebo */
} /* namespace revolve */
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