PLearn 0.1
TMatTest.cc
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00001 // -*- C++ -*-
00002 
00003 // TMatTest.cc
00004 //
00005 // Copyright (C) 2005-2006 Olivier Delalleau 
00006 // 
00007 // Redistribution and use in source and binary forms, with or without
00008 // modification, are permitted provided that the following conditions are met:
00009 // 
00010 //  1. Redistributions of source code must retain the above copyright
00011 //     notice, this list of conditions and the following disclaimer.
00012 // 
00013 //  2. Redistributions in binary form must reproduce the above copyright
00014 //     notice, this list of conditions and the following disclaimer in the
00015 //     documentation and/or other materials provided with the distribution.
00016 // 
00017 //  3. The name of the authors may not be used to endorse or promote
00018 //     products derived from this software without specific prior written
00019 //     permission.
00020 // 
00021 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
00022 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
00023 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
00024 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
00025 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
00026 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
00027 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
00028 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
00029 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
00030 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
00031 // 
00032 // This file is part of the PLearn library. For more information on the PLearn
00033 // library, go to the PLearn Web site at www.plearn.org
00034 
00035 /* *******************************************************      
00036    * $Id: .pyskeleton_header 544 2003-09-01 00:05:31Z plearner $ 
00037    ******************************************************* */
00038 
00039 // Authors: Olivier Delalleau
00040 
00044 #include "TMatTest.h"
00045 #include <plearn/math/PRandom.h>
00046 #include <plearn/math/TMat_maths.h>
00047 #include <plearn/math/TMat_maths_specialisation.h>
00048 
00049 namespace PLearn {
00050 using namespace std;
00051 
00052 PLEARN_IMPLEMENT_OBJECT(
00053     TMatTest,
00054     "Test TMat mathematical functions.",
00055     ""
00056 );
00057 
00059 // TMatTest //
00061 TMatTest::TMatTest():
00062     bound(10),
00063     mat_length(2),
00064     mat_width(3),
00065     vec_length(10)
00066 {}
00067 
00069 // build //
00071 void TMatTest::build()
00072 {
00073     inherited::build();
00074     build_();
00075 }
00076 
00078 // makeDeepCopyFromShallowCopy //
00080 void TMatTest::makeDeepCopyFromShallowCopy(CopiesMap& copies)
00081 {
00082     inherited::makeDeepCopyFromShallowCopy(copies);
00083 
00084     // ### Call deepCopyField on all "pointer-like" fields 
00085     // ### that you wish to be deepCopied rather than 
00086     // ### shallow-copied.
00087     // ### ex:
00088     // deepCopyField(trainvec, copies);
00089 
00090     // ### Remove this line when you have fully implemented this method.
00091     PLERROR("TMatTest::makeDeepCopyFromShallowCopy not fully (correctly) implemented yet!");
00092 }
00093 
00095 // declareOptions //
00097 void TMatTest::declareOptions(OptionList& ol)
00098 {
00099     declareOption(ol, "vec_length", &TMatTest::vec_length,
00100         OptionBase::buildoption,
00101         "Length of the vector on which the TMat functions are to be applied.");
00102 
00103     declareOption(ol, "mat_length", &TMatTest::mat_length,
00104         OptionBase::buildoption,
00105         "Length of the matrix on which the TMat functions are to be applied.");
00106 
00107     declareOption(ol, "mat_width", &TMatTest::mat_width,
00108         OptionBase::buildoption,
00109         "Width of the matrix on which the TMat functions are to be applied.");
00110 
00111     declareOption(ol, "bound", &TMatTest::bound,
00112         OptionBase::buildoption,
00113         "Bound for the (real) values sampled in the vector.");
00114 
00115     declareOption(ol, "mat_options",  &TMatTest::mat_options,
00116         OptionBase::learntoption,
00117         "Matrices.");
00118         
00119     declareOption(ol, "real_options", &TMatTest::real_options,
00120         OptionBase::learntoption,
00121         "Real numbers");
00122 
00123     declareOption(ol, "vec_options",  &TMatTest::vec_options,
00124         OptionBase::learntoption,
00125         "Vectors");
00126 
00127     // Now call the parent class' declareOptions
00128     inherited::declareOptions(ol);
00129 }
00130 
00132 // build_ //
00134 void TMatTest::build_()
00135 {
00136     // ### This method should do the real building of the object,
00137     // ### according to set 'options', in *any* situation. 
00138     // ### Typical situations include:
00139     // ###  - Initial building of an object from a few user-specified options
00140     // ###  - Building of a "reloaded" object: i.e. from the complete set of all serialised options.
00141     // ###  - Updating or "re-building" of an object after a few "tuning" options have been modified.
00142     // ### You should assume that the parent class' build_() has already been called.
00143 }
00144 
00146 // perform //
00148 void TMatTest::perform()
00149 {
00150     PLASSERT( vec_length > 0 ); // TODO Make it work with vec_length == 0
00151     PLASSERT( bound > 0 );
00152     Vec vec( vec_length );
00153     PRandom::common(false)->fill_random_uniform(vec, -bound, bound);
00154     Mat mat(mat_length, mat_width);
00155     PRandom::common(false)->fill_random_uniform(mat, -bound, bound);
00156 
00157     pout << "Starting TMatTest with vector of length " << vec_length
00158          << " and matrix of size (" << mat_length << " x " << mat_width
00159          << ")" << flush;
00160 
00161     this->vec_options["vector"]                 = vec;
00162     
00163     this->vec_options ["sign"]                  = sign          ( vec );
00164 
00165     this->real_options["sum"]                   = sum           ( vec );
00166     this->real_options["sum (ignore missing)"]  = sum           ( vec, true );
00167 
00168     this->real_options["sumabs"]                = sumabs        ( vec );
00169     this->real_options["sumsquare"]             = sumsquare     ( vec );
00170     this->real_options["sum_of_log"]            = sum_of_log    ( vec );
00171     this->real_options["product"]               = product       ( vec );
00172 
00173     this->real_options["mean"]                  = mean          ( vec );
00174     this->real_options["mean (ignore missing)"] = mean          ( vec, true );
00175 
00176     this->real_options["harmonic_mean"]         = harmonic_mean ( vec );
00177     this->real_options["harmonic_mean (ignore_missing)"]
00178                                                 = harmonic_mean ( vec, true );
00179 
00180     this->real_options["min"]                   = min           ( vec );
00181     this->real_options["argmin"]                = argmin        ( vec );
00182 
00183     this->real_options["max"]                   = max           ( vec );
00184     this->real_options["argmax"]                = argmax        ( vec );
00185 
00186     this->real_options["norm"]                  = norm          ( vec );
00187     this->vec_options ["log"]                   = log           ( vec );
00188     this->vec_options ["sqrt"]                  = sqrt          ( vec );
00189     this->vec_options ["tanh"]                  = tanh          ( vec );
00190     this->vec_options ["fasttanh"]              = fasttanh      ( vec );
00191 
00192     this->vec_options ["inverted"]              = inverted      ( vec );
00193     this->vec_options ["square"]                = square        ( vec );
00194     this->vec_options ["squareroot"]            = squareroot    ( vec );
00195     this->vec_options ["remove_missing"]        = remove_missing( vec );
00196     this->vec_options ["softmax"]               = softmax       ( vec );
00197     this->vec_options ["exp"]                   = exp           ( vec );
00198     this->vec_options ["nonZeroIndices"]        = nonZeroIndices( vec );
00199     this->real_options["logadd"]                = logadd        ( vec );
00200     this->real_options["median"]                = median        ( vec );
00201 
00202     Vec scaled_vec = vec.copy();
00203     scaled_vec *= scaled_vec[0];
00204     this->vec_options["operator*=_vec"]         = scaled_vec;
00205 
00206     Vec multiply_acc_vec = vec.copy();
00207     multiplyAcc(multiply_acc_vec, vec, -scaled_vec[0]);
00208     this->vec_options["multiplyAcc_vec"]        = multiply_acc_vec;
00209 
00210     Mat scaled_mat = mat.copy();
00211     scaled_mat *= scaled_mat(0, 0);
00212     this->mat_options["operator*=_mat"]         = scaled_mat;
00213 
00214     Mat multiply_acc_mat = mat.copy();
00215     multiplyAcc(multiply_acc_mat, mat, -scaled_mat(0, 0));
00216     this->mat_options["multiplyAcc_mat"]        = multiply_acc_mat;
00217 
00218     // Now test a specific case where problems can occur: the multiplication of
00219     // a matrix (m x 0) by a vector of size 0. The result must be a vector of
00220     // size m, filled with 0.
00221     Vec vec_result(2, 1);
00222     Mat mat_m_by_zero(2, 0);
00223     Vec vec_zero;
00224     product(vec_result, mat_m_by_zero, vec_zero);
00225     this->vec_options["product_empty_matrix_by_empty_vector"] =
00226                                                             vec_result.copy();
00227 
00228     // Similar but with accumulation.
00229     vec_result.fill(1);
00230     productAcc(vec_result, mat_m_by_zero, vec_zero);
00231     this->vec_options["product_empty_matrix_by_empty_vector_acc"] = vec_result;
00232 
00233     // Similar tests with matrices.
00234     Mat mat_result(2, 1, 1);
00235     Mat mat_zero(0, 1);
00236     product(mat_result, mat_m_by_zero, mat_zero);
00237     this->mat_options["product_empty_matrix_by_empty_matrix"] =
00238                                                             mat_result.copy();
00239     mat_result.fill(1);
00240     productAcc(mat_result, mat_m_by_zero, mat_zero);
00241     this->mat_options["product_empty_matrix_by_empty_matrix_acc"] = mat_result;
00242 
00243     pout << "... DONE!" << endl;
00244 }
00245 
00246 } // end of namespace PLearn
00247 
00248 
00249 /*
00250   Local Variables:
00251   mode:c++
00252   c-basic-offset:4
00253   c-file-style:"stroustrup"
00254   c-file-offsets:((innamespace . 0)(inline-open . 0))
00255   indent-tabs-mode:nil
00256   fill-column:79
00257   End:
00258 */
00259 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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