X-Git-Url: https://www.fleuret.org/cgi-bin/gitweb/gitweb.cgi?p=pom.git;a=blobdiff_plain;f=normal_law.cc;fp=normal_law.cc;h=02278d82e1a2b0793334f5005759c0f81862480c;hp=0000000000000000000000000000000000000000;hb=97a7e68f234cc09807d2d55f550e2516be0e9093;hpb=48c9926a2ed03737a3b024a85cda348caebf4cfe

diff --git a/normal_law.cc b/normal_law.cc
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+
+//////////////////////////////////////////////////////////////////////////////////
+// This program is free software: you can redistribute it and/or modify         //
+// it under the terms of the version 3 of the GNU General Public License        //
+// as published by the Free Software Foundation.                                //
+//                                                                              //
+// This program 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             //
+// General Public License for more details.                                     //
+//                                                                              //
+// You should have received a copy of the GNU General Public License            //
+// along with this program. If not, see <http://www.gnu.org/licenses/>.         //
+//                                                                              //
+// Written by Francois Fleuret                                                  //
+// (C) Ecole Polytechnique Federale de Lausanne                                 //
+// Contact <pom@epfl.ch> for comments & bug reports                             //
+//////////////////////////////////////////////////////////////////////////////////
+
+#include "normal_law.h"
+#include <cmath>
+
+NormalLaw::~NormalLaw() { }
+
+scalar_t NormalLaw::log_proba(scalar_t x) {
+  return normalizer - sq(x - expectation)/(2*variance);
+}
+
+scalar_t NormalLaw::proba(scalar_t x) {
+  return exp(normalizer - sq(x - expectation)/(2*variance));
+}
+
+void NormalLaw::set(scalar_t e, scalar_t v) {
+  expectation = e;
+  variance = v;
+  normalizer = - 0.5 * log(variance * 2 * M_PI);
+}