Container for a model function, cost function and Least-Squares function. And derivatives.  
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| virtual MeasureType  | calcModelValue (const MeasureType *parameters, MeasureType time)=0 | 
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| virtual void  | calcLSResiduals (const MeasureType *parameters, MeasureType *residuals)=0 | 
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| virtual MeasureType  | calcCostValue (const MeasureType *parameters)=0 | 
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| virtual void  | calcCostDerivative (const MeasureType *parameters, MeasureType *derivative)=0 | 
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| virtual void  | calcLSJacobian (const MeasureType *parameters, MeasureType *jacobian)=0 | 
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virtual int  | getNSamples () | 
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virtual const MeasureType *  | getInvTimes () const  | 
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virtual const MeasureType *  | getEchoTimes () const  | 
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virtual const MeasureType *  | getRepTimes () const  | 
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virtual const MeasureType *  | getRelAcqTimes () const  | 
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virtual const MeasureType *  | getSignal () const  | 
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virtual int  | getNDims () | 
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void  | setNSamples (int _nSamples) | 
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virtual void  | setInvTimes (const MeasureType *_InvTimes) | 
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virtual void  | setEchoTimes (const MeasureType *_EchoTimes) | 
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virtual void  | setRepTimes (const MeasureType *_RepTimes) | 
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virtual void  | setRelAcqTimes (const MeasureType *_RelAcqTimes) | 
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virtual void  | setSignal (const MeasureType *_Signal) | 
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virtual std::string  | getNthParamName (int nthParam) | 
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virtual void  | disp () | 
|   | show me your ModelT1 
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void  | setAllPointersToNull () | 
|   | set all the pointers to zero 
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  | Model () | 
|   | constructor 
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|   | Model (const Model &old) | 
|   | copy constructor keeps only _nSamples and _nDims  More...
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| virtual Model< MeasureType > *  | newByCloning ()=0 | 
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virtual  | ~Model () | 
|   | do not forget about the virtual destructor, see https://stackoverflow.com/questions/461203/when-to-use-virtual-destructors 
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template<typename MeasureType>
class Ox::Model< MeasureType >
Container for a model function, cost function and Least-Squares function. And derivatives. 
Here model function is defined - calcModelValue(). Fitting algorithms based on optimisation need a cost function - calcCostValue(). Fitting algorithms based on least squares need a residuals calculation - calcLSResiduals(). Some fitting algorithms use derivatives, hence calcLSJacobian() and calcCostDerivative(). The member variables are pointers to c-arrays, we need to know how many samples we want to process. That's the nSamples defined in the constructor. 
- Template Parameters
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