PLearn 0.1
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00001 // -*- C++ -*- 00002 00003 // PLMathTest.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 "PLMathTest.h" 00045 #include <plearn/math/pl_math.h> 00046 #include <plearn/math/PRandom.h> 00047 00048 namespace PLearn { 00049 using namespace std; 00050 00051 PLEARN_IMPLEMENT_OBJECT( 00052 PLMathTest, 00053 "Test various mathematical functions defined in pl_math.", 00054 "" 00055 ); 00056 00058 // PLMathTest // 00060 PLMathTest::PLMathTest() 00061 /* ### Initialize all fields to their default value */ 00062 { 00063 // ... 00064 00065 // ### You may (or not) want to call build_() to finish building the object 00066 // ### (doing so assumes the parent classes' build_() have been called too 00067 // ### in the parent classes' constructors, something that you must ensure) 00068 } 00069 00071 // build // 00073 void PLMathTest::build() 00074 { 00075 inherited::build(); 00076 build_(); 00077 } 00078 00080 // makeDeepCopyFromShallowCopy // 00082 void PLMathTest::makeDeepCopyFromShallowCopy(CopiesMap& copies) 00083 { 00084 inherited::makeDeepCopyFromShallowCopy(copies); 00085 00086 // ### Call deepCopyField on all "pointer-like" fields 00087 // ### that you wish to be deepCopied rather than 00088 // ### shallow-copied. 00089 // ### ex: 00090 // deepCopyField(trainvec, copies); 00091 00092 // ### Remove this line when you have fully implemented this method. 00093 PLERROR("PLMathTest::makeDeepCopyFromShallowCopy not fully (correctly) implemented yet!"); 00094 } 00095 00097 // declareOptions // 00099 void PLMathTest::declareOptions(OptionList& ol) 00100 { 00101 // ### Declare all of this object's options here 00102 // ### For the "flags" of each option, you should typically specify 00103 // ### one of OptionBase::buildoption, OptionBase::learntoption or 00104 // ### OptionBase::tuningoption. Another possible flag to be combined with 00105 // ### is OptionBase::nosave 00106 00107 declareOption(ol, "results", &PLMathTest::results, OptionBase::buildoption, 00108 "Map storing all test results."); 00109 00110 // Now call the parent class' declareOptions 00111 inherited::declareOptions(ol); 00112 } 00113 00115 // build_ // 00117 void PLMathTest::build_() 00118 { 00119 // ### This method should do the real building of the object, 00120 // ### according to set 'options', in *any* situation. 00121 // ### Typical situations include: 00122 // ### - Initial building of an object from a few user-specified options 00123 // ### - Building of a "reloaded" object: i.e. from the complete set of all serialised options. 00124 // ### - Updating or "re-building" of an object after a few "tuning" options have been modified. 00125 // ### You should assume that the parent class' build_() has already been called. 00126 } 00127 00129 // perform // 00131 void PLMathTest::perform() 00132 { 00133 int n = 20; 00134 TVec<int> bounds; 00135 string bounds_str = "[ 1 10 50 1000 ]"; 00136 PStream read_bounds = openString(bounds_str, PStream::plearn_ascii); 00137 read_bounds >> bounds; 00138 read_bounds.flush(); 00139 Vec samples; 00140 Vec vec(n); 00141 for (int i = 0; i < bounds.length(); i++) { 00142 PRandom::common(false)->fill_random_uniform(vec,-bounds[i],bounds[i]); 00143 samples.append(vec); 00144 } 00145 samples.append(0); 00146 samples.append(1); 00147 samples.append(-1); 00148 samples.append(MISSING_VALUE); 00149 samples.append(INFINITY); 00150 samples.append(-INFINITY); 00151 PP<ProgressBar> pb = new ProgressBar("Performing tests", samples.length()); 00152 for (int i = 0; i < samples.length(); i++) { 00153 int j; 00154 real x = samples[i]; 00155 results["data"].append(x); 00156 DOUBLE_TO_INT(x, j); 00157 results["DOUBLE_TO_INT"].append(j); 00158 results["sign"].append(sign(x)); 00159 results["positive"].append(positive(x)); 00160 results["negative"].append(negative(x)); 00161 results["is_equal_1.00000001"].append(is_equal(x, x * 1.00000001)); 00162 results["is_equal_1.001"].append(is_equal(x, x * 1.001)); 00163 results["square"].append(square(x)); 00164 results["hinge_loss_1"].append(hinge_loss(x, 1)); 00165 results["d_hinge_loss_1"].append(d_hinge_loss(x, 1)); 00166 results["is_missing"].append(is_missing(x)); 00167 results["is_integer"].append(is_integer(x)); 00168 results["FABS"].append(FABS(x)); 00169 results["mypow"].append(mypow(x,x)); 00170 if (int(x) >= 0) { 00171 results["ipow_real"].append(ipow(x,int(x))); 00172 results["ipow_int"].append(ipow(int(x),int(x))); 00173 } else { 00174 results["ipow_real"].append(0); 00175 results["ipow_int"].append(0); 00176 } 00177 results["sigmoid"].append(sigmoid(x)); 00178 results["is_positive"].append(is_positive(x)); 00179 if (x >= 0 && x <= 1) 00180 results["inverse_sigmoid"].append(inverse_sigmoid(x)); 00181 else 00182 results["inverse_sigmoid"].append(0); 00183 results["softplus"].append(softplus(x)); 00184 results["inverse_softplus"].append(inverse_softplus(x)); 00185 results["hard_slope"].append(hard_slope(x)); 00186 results["soft_slope"].append(soft_slope(x)); 00187 results["d_soft_slope"].append(d_soft_slope(x)); 00188 results["n_choose"].append(n_choose(int(x), int(x) + 2)); 00189 if (x >= 0) { 00190 results["safelog"].append(safelog(x)); 00191 results["safeflog"].append(safeflog(x)); 00192 results["safeflog"].append(safeflog(x, x + 3)); 00193 results["safeflog2"].append(safeflog2(x)); 00194 } else { 00195 results["safelog"].append(0); 00196 results["safeflog"].append(0); 00197 results["safeflog"].append(0); 00198 results["safeflog2"].append(0); 00199 } 00200 results["sqrt"].append(sqrt(x)); 00201 results["tanh"].append(tanh(x)); 00202 results["exp"].append(exp(x)); 00203 results["safeexp"].append(safeexp(x)); 00204 results["pl_log"].append(pl_log(x)); 00205 results["log_a_b"].append(log(x, x + 3)); 00206 results["logtwo"].append(logtwo(x)); 00207 results["logadd"].append(logadd(x, x + 2)); 00208 if (!is_missing(x) && !isinf(x)) { 00209 results["logsub"].append(logsub(x, x - 1)); 00210 results["dilogarithm"].append(dilogarithm(x)); 00211 results["fasttanh"].append(fasttanh(x)); 00212 results["fastsigmoid"].append(fastsigmoid(x)); 00213 results["ultrafasttanh"].append(ultrafasttanh(x)); 00214 results["ultrafastsigmoid"].append(ultrafastsigmoid(x)); 00215 results["tabulated_softplus"].append(tabulated_softplus(x)); 00216 results["tabulated_soft_slope"].append(tabulated_soft_slope(x)); 00217 } else { 00218 results["logsub"].append(0); 00219 results["dilogarithm"].append(0); 00220 results["fasttanh"].append(0); 00221 results["fastsigmoid"].append(0); 00222 results["ultrafasttanh"].append(0); 00223 results["ultrafastsigmoid"].append(0); 00224 results["tabulated_softplus"].append(0); 00225 results["tabulated_soft_slope"].append(0); 00226 } 00227 if (FABS(x) < 100) { 00228 results["softplus_primitive"].append(softplus_primitive(x)); 00229 results["tabulated_softplus_primitive"].append(tabulated_softplus_primitive(x)); 00230 results["hard_slope_integral"].append(hard_slope_integral(x)); 00231 results["soft_slope_integral"].append(soft_slope_integral(x)); 00232 results["tabulated_soft_slope_integral"].append(tabulated_soft_slope_integral(x)); 00233 } else { 00234 results["softplus_primitive"].append(0); 00235 results["tabulated_softplus_primitive"].append(0); 00236 results["hard_slope_integral"].append(0); 00237 results["soft_slope_integral"].append(0); 00238 results["tabulated_soft_slope_integral"].append(0); 00239 } 00240 if (pb) 00241 pb->update(i + 1); 00242 } 00243 } 00244 00245 } // end of namespace PLearn 00246 00247 00248 /* 00249 Local Variables: 00250 mode:c++ 00251 c-basic-offset:4 00252 c-file-style:"stroustrup" 00253 c-file-offsets:((innamespace . 0)(inline-open . 0)) 00254 indent-tabs-mode:nil 00255 fill-column:79 00256 End: 00257 */ 00258 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :