From 68b93015eaf44d45a3a85747b4f3c53bb755e8af Mon Sep 17 00:00:00 2001
From: mcarrier <mcarrier@636b058d-ea47-450e-bf9e-a15bfbe3eedb>
Date: Mon, 11 Jun 2018 02:50:07 +0000
Subject: small change in bootstrap code

git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/Nerve_GIC@3577 636b058d-ea47-450e-bf9e-a15bfbe3eedb

Former-commit-id: da8a421316d545b400f82eca3f426912b4767a8d
---
 src/Nerve_GIC/include/gudhi/GIC.h | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

(limited to 'src/Nerve_GIC')

diff --git a/src/Nerve_GIC/include/gudhi/GIC.h b/src/Nerve_GIC/include/gudhi/GIC.h
index 4bd2c849..2a50acd7 100644
--- a/src/Nerve_GIC/include/gudhi/GIC.h
+++ b/src/Nerve_GIC/include/gudhi/GIC.h
@@ -1184,8 +1184,8 @@ class Cover_complex {
         }
 
         Cboot.set_graph_from_automatic_rips(Gudhi::Euclidean_distance());
-        Cboot.set_automatic_resolution();
         Cboot.set_gain();
+        Cboot.set_automatic_resolution();
         Cboot.set_cover_from_function();
         Cboot.find_simplices();
         Cboot.compute_PD();
@@ -1206,7 +1206,9 @@ class Cover_complex {
    */
   double compute_distance_from_confidence_level(double alpha) {
     unsigned int N = distribution.size();
-    return distribution[std::floor(alpha * N)];
+    double d = distribution[std::floor(alpha * N)];
+    if (verbose)  std::cout << "Distance corresponding to confidence " << alpha << " is " << d << std::endl;
+    return d;
   }
 
  public:
@@ -1220,6 +1222,7 @@ class Cover_complex {
     double level = 1;
     for (unsigned int i = 0; i < N; i++)
       if (distribution[i] > d){ level = i * 1.0 / N; break; }
+    if (verbose)  std::cout << "Confidence level of distance " << d << " is " << level << std::endl;
     return level;
   }
 
@@ -1231,7 +1234,7 @@ class Cover_complex {
   double compute_p_value() {
     double distancemin = -std::numeric_limits<double>::lowest();
     int N = PD.size();
-    for (int i = 0; i < N; i++) distancemin = std::min(distancemin, 0.5 * (PD[i].second - PD[i].first));
+    for (int i = 0; i < N; i++) distancemin = std::min(distancemin, 0.5 * std::abs(PD[i].second - PD[i].first));
     double p_value = 1 - compute_confidence_level_from_distance(distancemin);
     if (verbose)  std::cout << "p value = " << p_value << std::endl;
     return p_value;
-- 
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