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//******************************************************************************
//
// File: SpinSignalDifference.java
// Package: edu.rit.mri
// Unit: Class edu.rit.mri.SpinSignalDifference
//
// This Java source file is copyright (C) 2008 by Alan Kaminsky. All rights
// reserved. For further information, contact the author, Alan Kaminsky, at
// ark@cs.rit.edu.
//
// This Java source file is part of the Parallel Java Library ("PJ"). PJ is free
// software; you can redistribute it and/or modify it under the terms of the GNU
// General Public License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// PJ 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 General Public License for more details.
//
// Linking this library statically or dynamically with other modules is making a
// combined work based on this library. Thus, the terms and conditions of the
// GNU General Public License cover the whole combination.
//
// As a special exception, the copyright holders of this library give you
// permission to link this library with independent modules to produce an
// executable, regardless of the license terms of these independent modules, and
// to copy and distribute the resulting executable under terms of your choice,
// provided that you also meet, for each linked independent module, the terms
// and conditions of the license of that module. An independent module is a
// module which is not derived from or based on this library. If you modify this
// library, you may extend this exception to your version of the library, but
// you are not obligated to do so. If you do not wish to do so, delete this
// exception statement from your version.
//
// A copy of the GNU General Public License is provided in the file gpl.txt. You
// may also obtain a copy of the GNU General Public License on the World Wide
// Web at http://www.gnu.org/licenses/gpl.html.
//
//******************************************************************************
package edu.rit.mri;
import edu.rit.numeric.Series;
import edu.rit.numeric.VectorFunction;
import edu.rit.numeric.XYSeries;
/**
* Class SpinSignalDifference provides an object that computes the difference
* between a measured spin signal and a model spin signal. Class
* SpinSignalDifference implements interface {@linkplain
* edu.rit.numeric.VectorFunction VectorFunction}.
* <P>
* An instance of class SpinSignalDifference is constructed with two data
* series, each an instance of class {@linkplain edu.rit.numeric.Series Series}.
* The first data series contains the measurement times
* <I>t</I><SUB><I>i</I></SUB>. The second data series contains the measured
* spin signals <I>S</I>(<I>t</I><SUB><I>i</I></SUB>). The vector function's
* result vector length, <I>M</I>, is the same as the length of the data series.
* <P>
* The vector function's argument vector <B>x</B> gives parameters for the model
* spin signal. The argument vector consists of one or more pairs of consecutive
* values. Each pair of consecutive values corresponds to one tissue. The first
* value of the pair is <I>ρ</I><SUB><I>j</I></SUB>, the spin density for
* tissue <I>j</I>. The second value of the pair is <I>R</I><SUB><I>j</I></SUB>,
* the spin relaxation rate for tissue <I>j</I>. The number of tissues is
* specified as a constructor parameter. The vector function's argument vector
* length, <I>N</I>, is twice the number of tissues.
* <P>
* The vector function is calculated as follows. For each <I>i</I>, 0 <=
* <I>i</I> <= <I>M</I>−1:
* <CENTER>
* <I>f</I><SUB><I>i</I></SUB>(<B>x</B>) = Model <I>S</I>(<I>t</I><SUB><I>i</I></SUB>;<B>x</B>) − Measured <I>S</I>(<I>t</I><SUB><I>i</I></SUB>)
* </CENTER>
* <P>
* The model spin signal is defined as follows:
* <CENTER>
* Model <I>S</I>(<I>t</I><SUB><I>i</I></SUB>;<B>x</B>) = Σ<SUB><I>j</I></SUB> <I>ρ</I><SUB><I>j</I></SUB> [1 − 2 exp(−<I>R</I><SUB><I>j</I></SUB> <I>t</I><SUB><I>i</I></SUB>)]
* </CENTER>
* <P>
* To find the model spin signal parameters <B>x</B> that best fit the measured
* spin signal, use an instance of class SpinSignalDifference with the nonlinear
* least squares algorithm in class {@linkplain
* edu.rit.numeric.NonLinearLeastSquares NonLinearLeastSquares}.
*
* @author Alan Kaminsky
* @version 11-Jun-2008
*/
public class SpinSignalDifference
implements VectorFunction
{
// Hidden data members.
private int M;
private int L;
private Series t_series;
private Series S_series;
// Exported constructors.
/**
* Construct a new spin signal difference function.
*
* @param data_series X-Y series of measured time values (X) and measured
* spin signal values (Y).
* @param L Number of tissues in the model spin signal.
*
* @exception NullPointerException
* (unchecked exception) Thrown if <TT>data_series</TT> is null.
* @exception IllegalArgumentException
* (unchecked exception) Thrown if the series' length is 0. Thrown if
* <TT>L</TT> <= 0.
*/
public SpinSignalDifference
(XYSeries data_series,
int L)
{
this (data_series.xSeries(), data_series.ySeries(), L);
}
/**
* Construct a new spin signal difference function.
*
* @param t_series Series of measured time values.
* @param S_series Series of measured spin signal values.
* @param L Number of tissues in the model spin signal.
*
* @exception NullPointerException
* (unchecked exception) Thrown if <TT>t_series</TT> is null or
* <TT>S_series</TT> is null.
* @exception IllegalArgumentException
* (unchecked exception) Thrown if either series' length is 0. Thrown if
* the two series have different lengths. Thrown if <TT>L</TT> <= 0.
*/
public SpinSignalDifference
(Series t_series,
Series S_series,
int L)
{
if (t_series == null)
{
throw new NullPointerException
("SpinSignalDifference(): t_series is null");
}
if (S_series == null)
{
throw new NullPointerException
("SpinSignalDifference(): S_series is null");
}
if (t_series.length() == 0)
{
throw new IllegalArgumentException
("SpinSignalDifference(): t_series is zero length, illegal");
}
if (S_series.length() == 0)
{
throw new IllegalArgumentException
("SpinSignalDifference(): S_series is zero length, illegal");
}
if (t_series.length() != S_series.length())
{
throw new IllegalArgumentException
("SpinSignalDifference(): t_series and S_series have different lengths, illegal");
}
if (L <= 0)
{
throw new IllegalArgumentException
("SpinSignalDifference(): L (= "+L+") <= 0, illegal");
}
this.M = t_series.length();
this.L = L;
this.t_series = t_series;
this.S_series = S_series;
}
// Exported operations.
/**
* Returns the length of the result vector, <I>M</I>.
*
* @return <I>M</I>.
*/
public int resultLength()
{
return M;
}
/**
* Returns the length of the argument vector, <I>N</I>.
*
* @return <I>N</I>.
*/
public int argumentLength()
{
return L<<1;
}
/**
* Evaluate this function with the given argument vector. The result is
* stored in the vector <TT>y</TT>. Specifically, for <I>i</I> = 0 to
* <I>M</I>−1, <I>y</I><SUB><I>i</I></SUB> =
* <I>f</I><SUB><I>i</I></SUB>(<B>x</B>).
*
* @param x Argument vector (input). Must be an <I>N</I>-element array.
* @param y Result vector (output). Must be an <I>M</I>-element array.
*
* @exception DomainException
* (unchecked exception) Thrown if any argument in <TT>x</TT> is outside
* the allowed set of values for this function.
* @exception RangeException
* (unchecked exception) Thrown if any element of the result vector is
* outside the range of type <TT>double</TT>.
*/
public void f
(double[] x,
double[] y)
{
// Subtract out the measured spin signal.
for (int i = 0; i < M; ++ i)
{
y[i] = -S_series.x(i);
}
// Add in the model spin signal.
for (int i = 0; i < M; ++ i)
{
double t_i = t_series.x(i);
for (int j = 0; j < L; ++ j)
{
double dens_j = x[(j<<1)];
double rate_j = x[(j<<1)+1];
y[i] += SpinSignal.S (dens_j, rate_j, t_i);
}
}
}
/**
* Calculate this function's Jacobian matrix with the given argument vector.
* The result is stored in the matrix <TT>dydx</TT>. Specifically, for
* <I>i</I> = 0 to <I>M</I>−1 and <I>j</I> = 0 to <I>N</I>−1,
* <I>dydx</I><SUB><I>i,j</I></SUB> =
* ∂<I>f</I><SUB><I>i</I></SUB>(<B>x</B>) ⁄ ∂<I>x</I><SUB><I>j</I></SUB> .
*
* @param x Argument vector (input). Must be an <I>N</I>-element array.
* @param dydx Jacobian matrix (output). Must be an
* <I>M</I>×<I>N</I>-element matrix.
*
* @exception DomainException
* (unchecked exception) Thrown if any argument in <TT>x</TT> is outside
* the allowed set of values for this function.
* @exception RangeException
* (unchecked exception) Thrown if any element of the Jacobian matrix is
* outside the range of type <TT>double</TT>.
*/
public void df
(double[] x,
double[][] dydx)
{
for (int i = 0; i < M; ++ i)
{
double t_i = t_series.x(i);
double[] dydx_i = dydx[i];
for (int j = 0; j < L; ++ j)
{
double dens_j = x[(j<<1)];
double rate_j = x[(j<<1)+1];
double twoexp = 2.0*Math.exp(-rate_j*t_i);
dydx_i[(j<<1)] = 1.0 - twoexp;
dydx_i[(j<<1)+1] = dens_j*t_i*twoexp;
}
}
}
}
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