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Binary files a/CI/physmon/reference/trackrefitting_kf/performance_trackrefitting.root and b/CI/physmon/reference/trackrefitting_kf/performance_trackrefitting.root differ diff --git a/CI/physmon/workflows/physmon_trackrefitting_kf.py b/CI/physmon/workflows/physmon_trackrefitting_kf.py index d31879ae66a..f05baf8100a 100755 --- a/CI/physmon/workflows/physmon_trackrefitting_kf.py +++ b/CI/physmon/workflows/physmon_trackrefitting_kf.py @@ -26,6 +26,7 @@ outputDir=tp, reverseFilteringMomThreshold=float("inf"), reverseFilteringCovarianceScaling=100.0, + seed=1337, s=s, ) diff --git a/Examples/Framework/src/Framework/RandomNumbers.cpp b/Examples/Framework/src/Framework/RandomNumbers.cpp index 4313a5cce77..94b37035fad 100644 --- a/Examples/Framework/src/Framework/RandomNumbers.cpp +++ b/Examples/Framework/src/Framework/RandomNumbers.cpp @@ -10,6 +10,8 @@ #include "ActsExamples/Framework/AlgorithmContext.hpp" +#include + namespace ActsExamples { RandomNumbers::RandomNumbers(const Config& cfg) : m_cfg(cfg) {} @@ -20,7 +22,9 @@ RandomEngine RandomNumbers::spawnGenerator( } RandomSeed RandomNumbers::generateSeed(const AlgorithmContext& context) const { - return m_cfg.seed + context.eventNumber; + std::size_t seed = m_cfg.seed; + boost::hash_combine(seed, context.eventNumber); + return seed; } } // namespace ActsExamples diff --git a/Examples/Python/tests/root_file_hashes.txt b/Examples/Python/tests/root_file_hashes.txt index a8dd1ec74e9..a5ed3e67f21 100644 --- a/Examples/Python/tests/root_file_hashes.txt +++ b/Examples/Python/tests/root_file_hashes.txt @@ -1,54 +1,54 @@ -test_pythia8__particles.root: 82a4b1378dd5927e1f7841f67d49c34f6f69fb4a65a20aad01323e806d602261 -test_fatras__particles_simulation.root: 58706945a7537d4bbbaee6128019af50f6318c97355acb5a31f10f056d0849c4 -test_fatras__hits.root: f90e8b2d52925b27a6184031503e874c33586aa9a504d2ac9084d549f7f95114 -test_geant4__particles_simulation.root: 62768c51928f01f49e5f00614294d4822d986df37687b8f6ce5afb5088531979 -test_geant4__hits.root: 1587a3d2f025f49da043f5e1b21280bb5a3f3df3c02863b8ad12f512b5bdb016 -test_seeding__estimatedparams.root: 5d74560f95e924685436d511ded1c436dd41935dbe02f02e501c95ee12677251 +test_pythia8__particles.root: 291ed316ea673ce8b8dcc54bf5fa0b993ca987c48c678ac9113d505b6de68d1f +test_fatras__particles_simulation.root: de02f4281dec0145d2861e06c9ed0e868bdfbfe539e3cad33944fd664acaeeb3 +test_fatras__hits.root: bf6038b5abba34d86c0b2d3a4c6031aaf309d19b64b2e148153d39c00982cabd +test_geant4__particles_simulation.root: a1b88fe1660ef2e956e56a00792ab8b16855cd88b2005fd40ceba271109dc357 +test_geant4__hits.root: 5e57c8dbe3cdf8165d701f4d629348cff6738d2736eb8a3cd0b86fefb44bc7d3 +test_seeding__estimatedparams.root: dc311a4d737d88ce381b85a4479c9747510691abe79174de58e334de9494d92c test_seeding__performance_seeding.root: 992f9c611d30dde0d3f3ab676bab19ada61ab6a4442828e27b65ec5e5b7a2880 -test_seeding__particles.root: b74282c72164494b51e918dd355b382feb975c9139b93b0f7d858e9d4c77c9d0 -test_seeding__particles_simulation.root: 17ce662aedf8ea0596838a206c696d844b78d6f25a9bb1e29c7f388654f814c9 +test_seeding__particles.root: a0744d4373572ff91bf85d2f52ca18421c092325bb3ec1cf06f17211da5c649b +test_seeding__particles_simulation.root: 7fed798e6219f6c33698885ce5b5cb736b5f760f393d03378efb89666f018611 test_hashing_seeding__estimatedparams.root: 0b49f0d880121ded80ec3221153543b64a60d8226abb8ad738edda38a36aa311 -test_seeding_orthogonal__estimatedparams.root: 89f32f499f4a39b6a7493b8a413688e8e4cef61bf334564afc30a35067dbf921 +test_seeding_orthogonal__estimatedparams.root: dc311a4d737d88ce381b85a4479c9747510691abe79174de58e334de9494d92c test_seeding_orthogonal__performance_seeding.root: 60fbedcf5cb2b37cd8e526251940564432890d3a159d231ed819e915a904682c -test_seeding_orthogonal__particles.root: b74282c72164494b51e918dd355b382feb975c9139b93b0f7d858e9d4c77c9d0 -test_seeding_orthogonal__particles_simulation.root: 17ce662aedf8ea0596838a206c696d844b78d6f25a9bb1e29c7f388654f814c9 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d6043f7c898430a3bd73100f8b730c3d82a9d48bbc7609426811bd2ccfb56e98 +test_strip_spacepoints[odd]__strip_spacepoints.root: bfc72d8fff76f0af305134bcdb09f0a897a4853bff9ed453be5d3a4294f1d191 diff --git a/Examples/Scripts/Python/truth_tracking_kalman.py b/Examples/Scripts/Python/truth_tracking_kalman.py index fd383538e2f..ffd6eed937b 100755 --- a/Examples/Scripts/Python/truth_tracking_kalman.py +++ b/Examples/Scripts/Python/truth_tracking_kalman.py @@ -19,6 +19,7 @@ def runTruthTrackingKalman( decorators=[], reverseFilteringMomThreshold=0 * u.GeV, reverseFilteringCovarianceScaling=1, + seed: int = 42, s: acts.examples.Sequencer = None, ): from acts.examples.simulation import ( @@ -45,7 +46,7 @@ def runTruthTrackingKalman( for d in decorators: s.addContextDecorator(d) - rnd = acts.examples.RandomNumbers(seed=42) + rnd = acts.examples.RandomNumbers(seed=seed) outputDir = Path(outputDir) logger = acts.logging.getLogger("Truth tracking example") diff --git a/Examples/Scripts/Python/truth_tracking_kalman_refitting.py b/Examples/Scripts/Python/truth_tracking_kalman_refitting.py index 86c4381faf9..255eb8c3c8a 100755 --- a/Examples/Scripts/Python/truth_tracking_kalman_refitting.py +++ b/Examples/Scripts/Python/truth_tracking_kalman_refitting.py @@ -19,6 +19,7 @@ def runRefittingKf( energyLoss: bool = True, reverseFilteringMomThreshold=0 * u.GeV, reverseFilteringCovarianceScaling=1.0, + seed: int = 42, s: acts.examples.Sequencer = None, ): s = runTruthTrackingKalman( @@ -28,6 +29,7 @@ def runRefittingKf( outputDir=outputDir, reverseFilteringMomThreshold=reverseFilteringMomThreshold, reverseFilteringCovarianceScaling=reverseFilteringCovarianceScaling, + seed=seed, s=s, )