[fplll] 01/01: Backport an upstream commit that fixes tests on 32-bit systems
Ximin Luo
infinity0 at debian.org
Mon Aug 7 19:59:03 UTC 2017
This is an automated email from the git hooks/post-receive script.
infinity0 pushed a commit to branch master
in repository fplll.
commit 87052bd2a4786a0f290f8163d3ca5aa7d54ec275
Author: Ximin Luo <infinity0 at debian.org>
Date: Mon Aug 7 21:54:09 2017 +0200
Backport an upstream commit that fixes tests on 32-bit systems
---
debian/changelog | 4 +
...s-in-test_pruner-now-tolerates-small-nume.patch | 152 +++++++++++++++++++++
debian/patches/series | 1 +
3 files changed, 157 insertions(+)
diff --git a/debian/changelog b/debian/changelog
index 86b5152..f25f642 100644
--- a/debian/changelog
+++ b/debian/changelog
@@ -1,8 +1,12 @@
fplll (5.1.0-3) UNRELEASED; urgency=medium
+ [ Julien Puydt ]
* Improved the strategies patch (Closes: #870698).
* Bump standards-version to 4.0.0.
+ [ Ximin Luo ]
+ * Backport an upstream commit that fixes tests on 32-bit systems.
+
-- Julien Puydt <julien.puydt at laposte.net> Fri, 04 Aug 2017 10:00:39 +0200
fplll (5.1.0-2) experimental; urgency=medium
diff --git a/debian/patches/0001-Inequalities-in-test_pruner-now-tolerates-small-nume.patch b/debian/patches/0001-Inequalities-in-test_pruner-now-tolerates-small-nume.patch
new file mode 100644
index 0000000..5aa1c73
--- /dev/null
+++ b/debian/patches/0001-Inequalities-in-test_pruner-now-tolerates-small-nume.patch
@@ -0,0 +1,152 @@
+From ddbc48d3c749ed8c2da51a4366eebd18fcd65730 Mon Sep 17 00:00:00 2001
+From: Leo Ducas <ducas at cwi.nl>
+Date: Wed, 24 May 2017 09:33:34 +0200
+Subject: [PATCH] Inequalities in test_pruner now tolerates small numerical
+ errors
+
+---
+ tests/test_pruner.cpp | 30 +++++++++++++++---------------
+ 1 file changed, 15 insertions(+), 15 deletions(-)
+
+diff --git a/tests/test_pruner.cpp b/tests/test_pruner.cpp
+index 476f043..0227745 100644
+--- a/tests/test_pruner.cpp
++++ b/tests/test_pruner.cpp
+@@ -337,7 +337,7 @@ template <class FT> int test_auto_prune(size_t n)
+ print_status(status);
+ status += !(pruning.expectation < 100.0);
+ print_status(status);
+- status += !(pruning.radius_factor >= 1.0);
++ status += !(pruning.radius_factor >= .999);
+ print_status(status);
+ status += !(pruning.coefficients[0] == 1.0);
+ print_status(status);
+@@ -354,7 +354,7 @@ template <class FT> int test_auto_prune(size_t n)
+ cerr << "radius " << radius_d << endl;
+ prune<FT>(pruning, radius_d, overhead, 0.3, r, PRUNER_METHOD_GRADIENT,
+ PRUNER_METRIC_PROBABILITY_OF_SHORTEST, true);
+- status += !(pruning.expectation <= 1.0);
++ status += !(pruning.expectation <= 1.001);
+ print_status(status);
+ cerr << "Probability " << pruning.expectation << endl;
+ cost = 0.;
+@@ -368,7 +368,7 @@ template <class FT> int test_auto_prune(size_t n)
+
+ status += !(pruning.expectation > 0.0);
+ print_status(status);
+- status += !(pruning.radius_factor >= 1.0);
++ status += !(pruning.radius_factor >= .999);
+ print_status(status);
+ status += !(pruning.coefficients[0] == 1.0);
+ print_status(status);
+@@ -377,7 +377,7 @@ template <class FT> int test_auto_prune(size_t n)
+ cerr << "radius " << radius_d << endl;
+ prune<FT>(pruning, radius_d, overhead, 0.01, r, PRUNER_METHOD_GRADIENT,
+ PRUNER_METRIC_PROBABILITY_OF_SHORTEST, false);
+- status += !(pruning.expectation <= 1.0);
++ status += !(pruning.expectation <= 1.001);
+ print_status(status);
+ cerr << "Probability " << pruning.expectation << endl;
+ cost = 0.;
+@@ -390,7 +390,7 @@ template <class FT> int test_auto_prune(size_t n)
+ cerr << endl << "Predicted Total Cost " << cost << endl;
+ status += !(pruning.expectation > 0.0);
+ print_status(status);
+- status += !(pruning.radius_factor >= 1.0);
++ status += !(pruning.radius_factor >= .999);
+ print_status(status);
+ status += !(pruning.coefficients[0] == 1.0);
+ print_status(status);
+@@ -399,7 +399,7 @@ template <class FT> int test_auto_prune(size_t n)
+ cerr << "radius " << radius_d << endl;
+ prune<FT>(pruning, radius_d, overhead, 0.3, r, PRUNER_METHOD_NM,
+ PRUNER_METRIC_PROBABILITY_OF_SHORTEST, true);
+- status += !(pruning.expectation <= 1.0);
++ status += !(pruning.expectation <= 1.001);
+ print_status(status);
+ cerr << "Probability " << pruning.expectation << endl;
+ cost = 0.;
+@@ -412,7 +412,7 @@ template <class FT> int test_auto_prune(size_t n)
+ cerr << endl << "Predicted Total Cost " << cost << endl;
+ status += !(pruning.expectation > 0.0);
+ print_status(status);
+- status += !(pruning.radius_factor >= 1.0);
++ status += !(pruning.radius_factor >= .999);
+ print_status(status);
+ status += !(pruning.coefficients[0] == 1.0);
+ print_status(status);
+@@ -421,7 +421,7 @@ template <class FT> int test_auto_prune(size_t n)
+ cerr << "radius " << radius_d << endl;
+ prune<FT>(pruning, radius_d, overhead, 0.01, r, PRUNER_METHOD_GRADIENT,
+ PRUNER_METRIC_PROBABILITY_OF_SHORTEST, false);
+- status += !(pruning.expectation <= 1.0);
++ status += !(pruning.expectation <= 1.001);
+ print_status(status);
+ cerr << "Probability " << pruning.expectation << endl;
+ cost = 0.;
+@@ -434,7 +434,7 @@ template <class FT> int test_auto_prune(size_t n)
+ cerr << endl << "Predicted Total Cost " << cost << endl;
+ status += !(pruning.expectation > 0.0);
+ print_status(status);
+- status += !(pruning.radius_factor >= 1.0);
++ status += !(pruning.radius_factor >= .999);
+ print_status(status);
+ status += !(pruning.coefficients[0] == 1.0);
+ print_status(status);
+@@ -443,7 +443,7 @@ template <class FT> int test_auto_prune(size_t n)
+ cerr << "radius " << radius_d << endl;
+ prune<FT>(pruning, radius_d, overhead, 0.3, r, PRUNER_METHOD_HYBRID,
+ PRUNER_METRIC_PROBABILITY_OF_SHORTEST, true);
+- status += !(pruning.expectation <= 1.0);
++ status += !(pruning.expectation <= 1.001);
+ print_status(status);
+ cerr << "Probability " << pruning.expectation << endl;
+ cost = 0.;
+@@ -456,7 +456,7 @@ template <class FT> int test_auto_prune(size_t n)
+ cerr << endl << "Predicted Total Cost " << cost << endl;
+ status += !(pruning.expectation > 0.0);
+ print_status(status);
+- status += !(pruning.radius_factor >= 1.0);
++ status += !(pruning.radius_factor >= .999);
+ print_status(status);
+ status += !(pruning.coefficients[0] == 1.0);
+ print_status(status);
+@@ -465,7 +465,7 @@ template <class FT> int test_auto_prune(size_t n)
+ cerr << "radius " << radius_d << endl;
+ prune<FT>(pruning, radius_d, overhead, 0.01, r, PRUNER_METHOD_GRADIENT,
+ PRUNER_METRIC_PROBABILITY_OF_SHORTEST, false);
+- status += !(pruning.expectation <= 1.0);
++ status += !(pruning.expectation <= 1.001);
+ print_status(status);
+ cerr << "Probability " << pruning.expectation << endl;
+ cost = 0.;
+@@ -478,7 +478,7 @@ template <class FT> int test_auto_prune(size_t n)
+ cerr << endl << "Predicted Total Cost " << cost << endl;
+ status += !(pruning.expectation > 0.0);
+ print_status(status);
+- status += !(pruning.radius_factor >= 1.0);
++ status += !(pruning.radius_factor >= .999);
+ print_status(status);
+ status += !(pruning.coefficients[0] == 1.0);
+ print_status(status);
+@@ -486,7 +486,7 @@ template <class FT> int test_auto_prune(size_t n)
+ cerr << endl << "Reprune Hybrid " << endl;
+ prune<FT>(pruning, radius_d, overhead, 0.3, r, PRUNER_METHOD_GRADIENT,
+ PRUNER_METRIC_PROBABILITY_OF_SHORTEST, false);
+- status += !(pruning.expectation <= 1.0);
++ status += !(pruning.expectation <= 1.001);
+ print_status(status);
+ cerr << "Probability " << pruning.expectation << endl;
+ cost = 0.;
+@@ -499,7 +499,7 @@ template <class FT> int test_auto_prune(size_t n)
+ cerr << endl << "Predicted Total Cost " << cost << endl;
+ status += !(pruning.expectation > 0.0);
+ print_status(status);
+- status += !(pruning.radius_factor >= 1.0);
++ status += !(pruning.radius_factor >= .999);
+ print_status(status);
+ status += !(pruning.coefficients[0] == 1.0);
+ print_status(status);
+--
+2.13.2
+
diff --git a/debian/patches/series b/debian/patches/series
index 104b9a3..e543ce2 100644
--- a/debian/patches/series
+++ b/debian/patches/series
@@ -1 +1,2 @@
+0001-Inequalities-in-test_pruner-now-tolerates-small-nume.patch
versioned_strategies_path
--
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