1 files changed, 0 insertions, 108 deletions
diff --git a/src/Kernels/include/gudhi/PSS.h b/src/Kernels/include/gudhi/PSS.h
deleted file mode 100644
index 5111a09f..00000000
--- a/src/Kernels/include/gudhi/PSS.h
+++ /dev/null
@@ -1,108 +0,0 @@
-/*    This file is part of the Gudhi Library. The Gudhi library
- *    (Geometric Understanding in Higher Dimensions) is a generic C++
- *    library for computational topology.
- *
- *    Author(s):       Mathieu Carrière
- *
- *    Copyright (C) 2017  INRIA (France)
- *
- *    This program is free software: you can redistribute it and/or modify
- *    it under the terms of the GNU General Public License as published by
- *    the Free Software Foundation, either version 3 of the License, or
- *    (at your option) any later version.
- *
- *    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/>.
- */
-
-#ifndef PSS_H_
-#define PSS_H_
-
-#define NUMPI 3.14159265359
-
-#include <stdlib.h>
-#include <stdio.h>
-#include <cstdlib>
-#include <cstdio>
-#include <iomanip>
-
-#include <string>
-#include <iostream>
-#include <sstream>
-#include <fstream>
-
-#include <set>
-#include <map>
-#include <vector>
-#include <algorithm>
-#include <limits>
-#include <assert.h>
-
-#include <cmath>
-#include <math.h>
-
-#include <memory>
-#include <stdexcept>
-#include <omp.h>
-
-#include <gmp.h>
-#include <gmpxx.h>
-#include <random>
-#include <chrono>
-#include <ctime>
-
-#include "figtree.h"
-#include "ANN.h"
-
-using PD = std::vector<std::pair<double,double> >;
-
-namespace Gudhi {
-namespace persistence_scale_space {
-
-double compute_exact_pss(PD PD1, PD PD2, double sigma = 1){
-  double k = 0;
-  for(int i = 0; i < PD1.size(); i++){
-    for(int j = 0; j < PD2.size(); j++){
-      k += exp(  -(    pow(PD1[i].first - PD2[j].first,  2)  +  pow(PD1[i].second - PD2[j].second, 2)     )/(8*sigma))   -\
-           exp(  -(    pow(PD1[i].first - PD2[j].second, 2)  +  pow(PD1[i].second - PD2[j].first,  2)     )/(8*sigma));
-    }
-  }
-  return k/(8*NUMPI*sigma);
-}
-
-double compute_approximate_pss(PD PD1, PD PD2, double sigma = 1, double error = 1e-2){
-
-  double k = 0;
-
-  int d = 2; int N = PD1.size(); int M = PD2.size(); double h = std::sqrt(8*sigma);
-  double* x = new double[2*N]; double* y = new double[2*M]; double* q = new double[N];
-  for(int i = 0; i < N; i++){
-    q[i] = 1.0/(8*NUMPI*sigma);
-    x[2*i] = PD1[i].first; x[2*i+1] = PD1[i].second;
-  }
-  for(int i = 0; i < M; i++){  y[2*i] = PD2[i].first; y[2*i+1] = PD2[i].second;  }
-  double* g_auto = new double[M];
-  memset(g_auto, 0, sizeof(double)*M);
-
-  figtree(d, N, M, 1, x, h, q, y, error, g_auto);
-  for(int i = 0; i < M; i++)  k += g_auto[i];
-
-  for(int i = 0; i < M; i++){  y[2*i] = PD2[i].second; y[2*i+1] = PD2[i].first;  }
-
-  figtree(d, N, M, 1, x, h, q, y, error, g_auto);
-  for(int i = 0; i < M; i++)  k -= g_auto[i];
-
-  delete[] x; delete[] y; delete[] q; delete[] g_auto;
-  return k;
-}
-
-} // namespace persistence_scale_space
-
-} // namespace Gudhi
-
-#endif // PSS_H_