PLearn 0.1
VarUtilsTest.cc
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00001 // -*- C++ -*-
00002 
00003 // VarUtilsTest.cc
00004 //
00005 // Copyright (C) 2005 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 "VarUtilsTest.h"
00045 #include <plearn/math/PRandom.h>
00046 #include <plearn/var/VarArray.h>
00047 #include <plearn/var/Var_utils.h>
00048 
00049 namespace PLearn {
00050 using namespace std;
00051 
00052 PLEARN_IMPLEMENT_OBJECT(
00053     VarUtilsTest,
00054     "Test various functions in Var_utils",
00055     ""
00056 );
00057 
00059 // VarUtilsTest //
00061 VarUtilsTest::VarUtilsTest() 
00062     /* ### Initialize all fields to their default value */
00063 {
00064     // ...
00065 
00066     // ### You may (or not) want to call build_() to finish building the object
00067     // ### (doing so assumes the parent classes' build_() have been called too
00068     // ### in the parent classes' constructors, something that you must ensure)
00069 }
00070 
00072 // build //
00074 void VarUtilsTest::build()
00075 {
00076     inherited::build();
00077     build_();
00078 }
00079 
00081 // makeDeepCopyFromShallowCopy //
00083 void VarUtilsTest::makeDeepCopyFromShallowCopy(CopiesMap& copies)
00084 {
00085     inherited::makeDeepCopyFromShallowCopy(copies);
00086 
00087     // ### Call deepCopyField on all "pointer-like" fields 
00088     // ### that you wish to be deepCopied rather than 
00089     // ### shallow-copied.
00090     // ### ex:
00091     // deepCopyField(trainvec, copies);
00092 
00093     // ### Remove this line when you have fully implemented this method.
00094     PLERROR("VarUtilsTest::makeDeepCopyFromShallowCopy not fully (correctly) implemented yet!");
00095 }
00096 
00098 // declareOptions //
00100 void VarUtilsTest::declareOptions(OptionList& ol)
00101 {
00102     declareOption(ol, "mat_results", &VarUtilsTest::mat_results,
00103         OptionBase::buildoption,
00104         "Test Mat results.");
00105 
00106     // Now call the parent class' declareOptions
00107     inherited::declareOptions(ol);
00108 }
00109 
00111 // build_ //
00113 void VarUtilsTest::build_()
00114 {
00115     // ### This method should do the real building of the object,
00116     // ### according to set 'options', in *any* situation. 
00117     // ### Typical situations include:
00118     // ###  - Initial building of an object from a few user-specified options
00119     // ###  - Building of a "reloaded" object: i.e. from the complete set of all serialised options.
00120     // ###  - Updating or "re-building" of an object after a few "tuning" options have been modified.
00121     // ### You should assume that the parent class' build_() has already been called.
00122 }
00123 
00125 // perform //
00127 void VarUtilsTest::perform()
00128 {
00129     int var_length = 10;
00130     int var_width = 5;
00131     int bound = 10;
00132     Var tmp;
00133     VarArray prop_path;
00134     Var mat_var(var_length, var_width);
00135     Var vec_var(var_length, 1);
00136     Var prob_mat_var(var_length, var_width);
00137     Var prob_vec_var(var_length, 1);
00138     Var scalar_var(1, 1);
00139     Var multi_index_var(var_width, 1);
00140     multi_index_var->matValue << "1 3 5 2 9";
00141     Var single_index_var(1, 1);
00142     single_index_var->matValue(0, 0) = 3;
00143     PRandom::common(false)->fill_random_uniform(mat_var->matValue, -bound, bound);
00144     PRandom::common(false)->fill_random_uniform(vec_var->matValue, -bound, bound);
00145     PRandom::common(false)->fill_random_uniform(prob_mat_var->matValue, 0, 1);
00146     PRandom::common(false)->fill_random_uniform(prob_vec_var->matValue, 0, 1);
00147     PRandom::common(false)->fill_random_uniform(scalar_var->matValue, -bound, bound);
00148 
00149     tmp = mean(mat_var);
00150     prop_path = propagationPath(tmp);
00151     prop_path.fprop();
00152     mat_results["mean"] = tmp->matValue;
00153 
00154     tmp = neg_log_pi(prob_vec_var, single_index_var);
00155     prop_path = propagationPath(tmp);
00156     prop_path.fprop();
00157     mat_results["neg_log_pi_vec"] = tmp->matValue;
00158 
00159     tmp = neg_log_pi(prob_mat_var, multi_index_var);
00160     prop_path = propagationPath(tmp);
00161     prop_path.fprop();
00162     mat_results["neg_log_pi_mat"] = tmp->matValue;
00163 
00164     tmp = softmax(prob_vec_var, 2);
00165     prop_path = propagationPath(tmp);
00166     prop_path.fprop();
00167     mat_results["softmax"] = tmp->matValue;
00168 
00169     tmp = pownorm(vec_var, 1.5);
00170     prop_path = propagationPath(tmp);
00171     prop_path.fprop();
00172     mat_results["pownorm"] = tmp->matValue;
00173 
00174     tmp = norm(vec_var, 1.5);
00175     prop_path = propagationPath(tmp);
00176     prop_path.fprop();
00177     mat_results["norm"] = tmp->matValue;
00178 
00179     tmp = entropy(vec_var);
00180     prop_path = propagationPath(tmp);
00181     prop_path.fprop();
00182     mat_results["entropy"] = tmp->matValue;
00183 
00184     tmp = distance(vec_var, prob_vec_var, 2);
00185     prop_path = propagationPath(tmp);
00186     prop_path.fprop();
00187     mat_results["distance"] = tmp->matValue;
00188 
00189     tmp = powdistance(vec_var, prob_vec_var, 2);
00190     prop_path = propagationPath(tmp);
00191     prop_path.fprop();
00192     mat_results["powdistance"] = tmp->matValue;
00193 }
00194 
00195 } // end of namespace PLearn
00196 
00197 
00198 /*
00199   Local Variables:
00200   mode:c++
00201   c-basic-offset:4
00202   c-file-style:"stroustrup"
00203   c-file-offsets:((innamespace . 0)(inline-open . 0))
00204   indent-tabs-mode:nil
00205   fill-column:79
00206   End:
00207 */
00208 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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