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Revisions №61841

branch: master 「№61841」
Commited by: SM Bargeen Alam Turzo
GitHub commit link: 「61e9eb2e9ee33dd0」 「№5373」
Difference from previous tested commit:  code diff
Commit date: 2022-02-24 16:51:44
linux.clang linux.gcc linux.srlz mac.clang
debug
release
unit
PyRosetta4.notebook gcc-9.gcc.python37.PyRosetta4.unit linux.clang.cxx11thread.serialization.python37.PyRosetta4.unit linux.gcc.python36.PyRosetta4.unit m1.clang.python38.PyRosetta4.unit m1.clang.python39.PyRosetta4.unit mac.clang.python36.PyRosetta4.unit build.clean.debug alpine.gcc.build.debug clang-10.clang.cxx11thread.mpi.serialization.tensorflow.build.debug gcc-10.gcc.build.debug gcc-11.gcc.python39.build.debug gcc-9.gcc.build.debug linux.clang.bcl.build.debug linux.clang.hdf5.build.debug mysql postgres linux.clang.python36.build.debug linux.zeromq.debug linux.gcc.bcl.build.debug mpi mpi.serialization linux.icc.build.debug mac.clang.bcl.build.debug OpenCL mac.clang.python36.build.debug ubuntu.clang.bcl.build.debug ubuntu.gcc.bcl.build.debug build.header build.levels build.ninja_debug graphics static beautification code_quality.clang_analysis code_quality.clang_tidy code_quality.cppcheck code_quality.merge_size serialization code_quality.submodule_regression integration.mpi integration.release_debug integration.tensorflow integration.thread integration performance profile release.source scientific.RosettaCM scientific.sb_score12_docking scientific.simple_cycpep_predict linux.clang.score linux.gcc.score mac.clang.score linux.scripts.pyrosetta scripts.rosetta.parse scripts.rosetta.validate scripts.rosetta.verify linux.clang.unit.release linux.gcc.unit.release mac.clang.unit.release gcc-10.gcc.unit gcc-11.gcc.python39.unit gcc-9.gcc.unit m1.clang.python39.unit util.apps windows.build.debug windows.build.release

Merge pull request #5373 from RosettaCommons/smturzo/projection2dparcs Smturzo/projection2dparcs This merge introduces a method to calculate projection of a protein in a 2d grid (projection2d) and can be found in numeric/geometry. Next using this method, I created an application that predict collision cross section (from Ion Mobility experiments) and then used this to create a score term that can be used to rescore structures generated from ab initio and homology modeling.

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Test: linux.gcc.mpi.serialization.integration.mpi

Failed sub-tests (click for more details):
database_md5
Test: linux.clang.tensorflow.integration.tensorflow

Failed sub-tests (click for more details):
database_md5
Test: linux.gcc.cxx11thread.integration.thread

Failed sub-tests (click for more details):
database_md5
Test: linux.clang.scientific.sb_score12_docking

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