/**
* Jungfraujoch
* API to control Jungfraujoch developed by the Paul Scherrer Institute (Switzerland). Jungfraujoch is a data acquisition and analysis system for pixel array detectors, primarly PSI JUNGFRAU. Jungfraujoch uses FPGA boards to acquire data at high data rates. 
*
* The version of the OpenAPI document: 1.0.0-rc.23
* Contact: filip.leonarski@psi.ch
*
* NOTE: This class is auto generated by OpenAPI Generator (https://openapi-generator.tech).
* https://openapi-generator.tech
* Do not edit the class manually.
*/


#include "Calibration_statistics_inner.h"
#include "Helpers.h"

#include <sstream>

namespace org::openapitools::server::model
{

Calibration_statistics_inner::Calibration_statistics_inner()
{
    m_Module_number = 0L;
    m_Storage_cell_number = 0L;
    m_Pedestal_g0_mean = 0.0f;
    m_Pedestal_g1_mean = 0.0f;
    m_Pedestal_g2_mean = 0.0f;
    m_Gain_g0_mean = 0.0f;
    m_Gain_g1_mean = 0.0f;
    m_Gain_g2_mean = 0.0f;
    m_Masked_pixels = 0L;
    
}

void Calibration_statistics_inner::validate() const
{
    std::stringstream msg;
    if (!validate(msg))
    {
        throw org::openapitools::server::helpers::ValidationException(msg.str());
    }
}

bool Calibration_statistics_inner::validate(std::stringstream& msg) const
{
    return validate(msg, "");
}

bool Calibration_statistics_inner::validate(std::stringstream& msg, const std::string& pathPrefix) const
{
    bool success = true;
    const std::string _pathPrefix = pathPrefix.empty() ? "Calibration_statistics_inner" : pathPrefix;

                                        
    return success;
}

bool Calibration_statistics_inner::operator==(const Calibration_statistics_inner& rhs) const
{
    return
    
    
    (getModuleNumber() == rhs.getModuleNumber())
     &&
    
    (getStorageCellNumber() == rhs.getStorageCellNumber())
     &&
    
    (getPedestalG0Mean() == rhs.getPedestalG0Mean())
     &&
    
    (getPedestalG1Mean() == rhs.getPedestalG1Mean())
     &&
    
    (getPedestalG2Mean() == rhs.getPedestalG2Mean())
     &&
    
    (getGainG0Mean() == rhs.getGainG0Mean())
     &&
    
    (getGainG1Mean() == rhs.getGainG1Mean())
     &&
    
    (getGainG2Mean() == rhs.getGainG2Mean())
     &&
    
    (getMaskedPixels() == rhs.getMaskedPixels())
    
    
    ;
}

bool Calibration_statistics_inner::operator!=(const Calibration_statistics_inner& rhs) const
{
    return !(*this == rhs);
}

void to_json(nlohmann::json& j, const Calibration_statistics_inner& o)
{
    j = nlohmann::json::object();
    j["module_number"] = o.m_Module_number;
    j["storage_cell_number"] = o.m_Storage_cell_number;
    j["pedestal_g0_mean"] = o.m_Pedestal_g0_mean;
    j["pedestal_g1_mean"] = o.m_Pedestal_g1_mean;
    j["pedestal_g2_mean"] = o.m_Pedestal_g2_mean;
    j["gain_g0_mean"] = o.m_Gain_g0_mean;
    j["gain_g1_mean"] = o.m_Gain_g1_mean;
    j["gain_g2_mean"] = o.m_Gain_g2_mean;
    j["masked_pixels"] = o.m_Masked_pixels;
    
}

void from_json(const nlohmann::json& j, Calibration_statistics_inner& o)
{
    j.at("module_number").get_to(o.m_Module_number);
    j.at("storage_cell_number").get_to(o.m_Storage_cell_number);
    j.at("pedestal_g0_mean").get_to(o.m_Pedestal_g0_mean);
    j.at("pedestal_g1_mean").get_to(o.m_Pedestal_g1_mean);
    j.at("pedestal_g2_mean").get_to(o.m_Pedestal_g2_mean);
    j.at("gain_g0_mean").get_to(o.m_Gain_g0_mean);
    j.at("gain_g1_mean").get_to(o.m_Gain_g1_mean);
    j.at("gain_g2_mean").get_to(o.m_Gain_g2_mean);
    j.at("masked_pixels").get_to(o.m_Masked_pixels);
    
}

int64_t Calibration_statistics_inner::getModuleNumber() const
{
    return m_Module_number;
}
void Calibration_statistics_inner::setModuleNumber(int64_t const value)
{
    m_Module_number = value;
}
int64_t Calibration_statistics_inner::getStorageCellNumber() const
{
    return m_Storage_cell_number;
}
void Calibration_statistics_inner::setStorageCellNumber(int64_t const value)
{
    m_Storage_cell_number = value;
}
float Calibration_statistics_inner::getPedestalG0Mean() const
{
    return m_Pedestal_g0_mean;
}
void Calibration_statistics_inner::setPedestalG0Mean(float const value)
{
    m_Pedestal_g0_mean = value;
}
float Calibration_statistics_inner::getPedestalG1Mean() const
{
    return m_Pedestal_g1_mean;
}
void Calibration_statistics_inner::setPedestalG1Mean(float const value)
{
    m_Pedestal_g1_mean = value;
}
float Calibration_statistics_inner::getPedestalG2Mean() const
{
    return m_Pedestal_g2_mean;
}
void Calibration_statistics_inner::setPedestalG2Mean(float const value)
{
    m_Pedestal_g2_mean = value;
}
float Calibration_statistics_inner::getGainG0Mean() const
{
    return m_Gain_g0_mean;
}
void Calibration_statistics_inner::setGainG0Mean(float const value)
{
    m_Gain_g0_mean = value;
}
float Calibration_statistics_inner::getGainG1Mean() const
{
    return m_Gain_g1_mean;
}
void Calibration_statistics_inner::setGainG1Mean(float const value)
{
    m_Gain_g1_mean = value;
}
float Calibration_statistics_inner::getGainG2Mean() const
{
    return m_Gain_g2_mean;
}
void Calibration_statistics_inner::setGainG2Mean(float const value)
{
    m_Gain_g2_mean = value;
}
int64_t Calibration_statistics_inner::getMaskedPixels() const
{
    return m_Masked_pixels;
}
void Calibration_statistics_inner::setMaskedPixels(int64_t const value)
{
    m_Masked_pixels = value;
}


} // namespace org::openapitools::server::model