diff options
| -rw-r--r-- | src/Nerve_GIC/include/gudhi/GIC.h | 9 |
1 files changed, 6 insertions, 3 deletions
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; |