# this import is needed for the runner
from fastlmm.association.tests.test_single_snp_select import TestSingleSnpSelect
suites = unittest.TestSuite([getTestSuite()])
if True: #Standard test run
r = unittest.TextTestRunner(failfast=False)
r.run(suites)
else: #Cluster test run
from fastlmm.util.runner import Local, HPC, LocalMultiProc
logging.basicConfig(level=logging.INFO)
from fastlmm.util.distributabletest import DistributableTest
#runner = HPC(10, 'RR1-N13-09-H44',r'\\msr-arrays\Scratch\msr-pool\Scratch_Storage4\Redmond',
# remote_python_parent=r"\\msr-arrays\Scratch\msr-pool\Scratch_Storage4\REDMOND\carlk\Source\carlk\july_7_14\tests\runs\2014-07-24_15_02_02_554725991686\pythonpath",
# update_remote_python_parent=True,
# priority="AboveNormal",mkl_num_threads=1)
runner = Local()
#runner = LocalMultiProc(taskcount=20,mkl_num_threads=5)
#runner = LocalInParts(1,2,mkl_num_threads=1) # For debugging the cluster runs
#runner = Hadoop(100, mapmemory=8*1024, reducememory=8*1024, mkl_num_threads=1, queue="default")
distributable_test = DistributableTest(suites,"temp_test")
print(runner.run(distributable_test))
logging.info("done with testing")
# this import is needed for the runner
from fastlmm.association.tests.test_single_snp_select import TestSingleSnpSelect
suites = unittest.TestSuite([getTestSuite()])
if True: #Standard test run
r = unittest.TextTestRunner(failfast=False)
r.run(suites)
else: #Cluster test run
from fastlmm.util.runner import Local, HPC, LocalMultiProc
logging.basicConfig(level=logging.INFO)
from fastlmm.util.distributabletest import DistributableTest
#runner = HPC(10, 'RR1-N13-09-H44',r'\\msr-arrays\Scratch\msr-pool\Scratch_Storage4\Redmond',
# remote_python_parent=r"\\msr-arrays\Scratch\msr-pool\Scratch_Storage4\REDMOND\carlk\Source\carlk\july_7_14\tests\runs\2014-07-24_15_02_02_554725991686\pythonpath",
# update_remote_python_parent=True,
# priority="AboveNormal",mkl_num_threads=1)
runner = Local()
#runner = LocalMultiProc(taskcount=20,mkl_num_threads=5)
#runner = LocalInParts(1,2,mkl_num_threads=1) # For debugging the cluster runs
#runner = Hadoop(100, mapmemory=8*1024, reducememory=8*1024, mkl_num_threads=1, queue="default")
distributable_test = DistributableTest(suites,"temp_test")
print runner.run(distributable_test)
logging.info("done with testing")
if __name__ == '__main__':
# this import is needed for the runner
from fastlmm.association.tests.test_single_snp_select import TestSingleSnpSelect
suites = unittest.TestSuite([getTestSuite()])
if True: #Standard test run
r = unittest.TextTestRunner(failfast=False)
r.run(suites)
else: #Cluster test run
from fastlmm.util.runner import Local, HPC, LocalMultiProc
logging.basicConfig(level=logging.INFO)
from fastlmm.util.distributabletest import DistributableTest
#runner = HPC(10, 'RR1-N13-09-H44',r'\\msr-arrays\Scratch\msr-pool\Scratch_Storage4\Redmond',
# remote_python_parent=r"\\msr-arrays\Scratch\msr-pool\Scratch_Storage4\REDMOND\carlk\Source\carlk\july_7_14\tests\runs\2014-07-24_15_02_02_554725991686\pythonpath",
# update_remote_python_parent=True,
# priority="AboveNormal",mkl_num_threads=1)
runner = Local()
#runner = LocalMultiProc(taskcount=20,mkl_num_threads=5)
#runner = LocalInParts(1,2,mkl_num_threads=1) # For debugging the cluster runs
#runner = Hadoop(100, mapmemory=8*1024, reducememory=8*1024, mkl_num_threads=1, queue="default")
distributable_test = DistributableTest(suites, "temp_test")
print runner.run(distributable_test)
logging.info("done with testing")
