casa6
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xxxxxxxxxx//# LinearEquation.h: this defines LinearEquation//# Copyright (C) 1996,1997,1999,2000//# Associated Universities, Inc. Washington DC, USA.//#//# This library is free software; you can redistribute it and/or modify it//# under the terms of the GNU Library General Public License as published by//# the Free Software Foundation; either version 2 of the License, or (at your//# option) any later version.//#//# This library 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 Library General Public//# License for more details.//#//# You should have received a copy of the GNU Library General Public License//# along with this library; if not, write to the Free Software Foundation,//# Inc., 675 Massachusetts Ave, Cambridge, MA 02139, USA.//#//# Correspondence concerning AIPS++ should be addressed as follows://# Internet email: aips2-request@nrao.edu.//# Postal address: AIPS++ Project Office//# National Radio Astronomy Observatory//# 520 Edgemont Road//# Charlottesville, VA 22903-2475 USA//#//#//# $Id$namespace casa { //# NAMESPACE CASA - BEGIN// <summary> defines a relationship between Domain and Range objects </summary>// <use visibility=export>// <reviewed reviewer="" date="yyyy/mm/dd" tests="" demos="">// </reviewed>// <prerequisite> // This class should be read in conjunction with: // <li> <linkto class="LinearModel">LinearModel</linkto>// <li> <linkto class="ResidualEquation">ResidualEquation</linkto>// </prerequisite>//// <etymology>// LinearEquation was originally conceived for implementing linear// equations (like Ax=b) but was in hindsight found to be more general.// </etymology>//// <synopsis>// This abstract class defines the basic functions used for forward// modelling of measured data of "Range" data type. It defines the// functions used to transform a model, of "Domain" data type to predicted// data. It can also compare the predicted data with the measured data and// return residuals to classes derived from LinearModel which can then be// used to update the model.// </synopsis>//// <example>// I'll pass this class into a subroutine as an actual instance of an// abstract class cannot be constructed. // <srcblock>// void foo(LinearModel< Image<casacore::Float> > mod, // LinearEquation<Image<casacore::Float>, VisibilitySet>)// VisibilitySet predictedVisibility;// eqn.evaluate(predictedVisibility, mod); // </srcblock>// </example>//// <motivation>// This class was originally conceived to be used in implementing// deconvolution algorithms. I would not be surprised if it found wider// applicability. // </motivation>//// <templating arg=Domain>// I do not see any restrictions on the Domain class. Its up to the derived// class to handle the the appropriate Domain.// </templating>// <templating arg=Range>// In order to calculate residuals it will probably be necessary for// subtraction to be defined on the Range class, as well as some way for// data in the Range data type to be converted back into the Domain data