PLearn 0.1
VMat_basic_stats.h
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00001 // -*- C++ -*-
00002 
00003 // VMat_basic_stats.h
00004 //
00005 // Copyright (C) 2004 Pascal Vincent
00006 // Copyright (C) 2005 University of Montreal
00007 //
00008 // Redistribution and use in source and binary forms, with or without
00009 // modification, are permitted provided that the following conditions are met:
00010 //
00011 //  1. Redistributions of source code must retain the above copyright
00012 //     notice, this list of conditions and the following disclaimer.
00013 //
00014 //  2. Redistributions in binary form must reproduce the above copyright
00015 //     notice, this list of conditions and the following disclaimer in the
00016 //     documentation and/or other materials provided with the distribution.
00017 //
00018 //  3. The name of the authors may not be used to endorse or promote
00019 //     products derived from this software without specific prior written
00020 //     permission.
00021 //
00022 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
00023 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
00024 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
00025 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
00026 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
00027 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
00028 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
00029 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
00030 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
00031 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
00032 //
00033 // This file is part of the PLearn library. For more information on the PLearn
00034 // library, go to the PLearn Web site at www.plearn.org
00035 
00036 /* *******************************************************
00037  * $Id: VMat_basic_stats.h 7308 2007-05-24 16:50:41Z dumitruerhan $
00038  ******************************************************* */
00039 
00040 // Authors: Pascal Vincent
00041 
00045 #ifndef VMat_basic_stats_INC
00046 #define VMat_basic_stats_INC
00047 
00048 // Put includes here
00049 #include <plearn/math/TVec.h>
00050 #include <plearn/math/TMat.h>
00051 #include <plearn/base/Array.h>
00052 
00053 namespace PLearn {
00054 using namespace std;
00055 
00056 class VMat;
00057 
00058 #define MEAN_ROW 0
00059 #define STDDEV_ROW 1
00060 #define MIN_ROW 2
00061 #define MAX_ROW 3
00062 #define NMISSING_ROW 4
00063 #define NZERO_ROW 5
00064 #define NPOSITIVE_ROW 6
00065 #define NNEGATIVE_ROW 7
00066 #define MEANPOS_ROW 8
00067 #define STDDEVPOS_ROW 9
00068 
00081 Mat computeBasicStats(const VMat& m);
00082 
00084 void computeRowMean             (const VMat& d, Vec& meanvec);
00085 
00093 void computeMean                (const VMat& d, Vec& meanvec);
00094 void computeMeanAndVariance     (const VMat& d, Vec& meanvec, Vec& variancevec, real epsilon=0.0);
00095 void computeMeanAndStddev       (const VMat& d, Vec& meanvec, Vec& stddevvec,   real epsilon=0.0);
00096 void computeMeanAndCovar        (const VMat& d, Vec& meanvec, Mat& covarmat,    real epsilon=0.0);
00098 void computeCovar               (const VMat& d, const Vec& mu, Mat& covarmat,    real epsilon=0.0);
00099 void computeWeightedMean        (const Vec& weights, const VMat& d, Vec& meanvec);
00100 void computeWeightedMeanAndCovar(const Vec& weights, const VMat& d,
00101                                  Vec& meanvec, Mat& covarmat, real epsilon=0.0);
00102 void computeInputMean           (const VMat& d, Vec& meanvec);
00104 void computeInputCovar(const VMat& d, const Vec& mu, Mat& covarmat, real epsilon=0.0);
00105 void computeInputMeanAndCovar   (const VMat& d, Vec& meanvec, Mat& covarmat, real epsilon=0.0);
00106 void computeInputMeanAndVariance(const VMat& d, Vec& meanvec, Vec& var,      real epsilon=0.0);
00107 void computeInputMeanAndStddev  (const VMat& d, Vec& meanvec, Vec& stddev,   real epsilon=0.0);
00108 
00109 void autocorrelation_function(const VMat& data, Mat& acf);
00110 
00111 void computeRange(const VMat& d, Vec& minvec, Vec& maxvec);
00112 
00127 TVec<Mat> computeConditionalMeans(VMat trainset, int targetsize, Mat& basic_stats);
00128 
00134 VMat normalize(const VMat& d, const Vec& meanvec, const Vec& stddevvec);
00135 
00137 VMat normalize(const VMat& d, int inputsize, int ntrain);
00139 VMat normalize(const VMat& d, int inputsize);
00140 
00149 void correlations(const VMat& x, const VMat& y, Mat& r, Mat& pvalues, bool ignore_missing = false);
00150 
00151 } // end of namespace PLearn
00152 #endif
00153 
00154 
00155 /*
00156   Local Variables:
00157   mode:c++
00158   c-basic-offset:4
00159   c-file-style:"stroustrup"
00160   c-file-offsets:((innamespace . 0)(inline-open . 0))
00161   indent-tabs-mode:nil
00162   fill-column:79
00163   End:
00164 */
00165 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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