def parallelization_test(self):
'''
simple test to check parallelization infrastructure
'''
dummy.parallel = main.parallel_function(dummy)
parallel_result = dummy.parallel([1,2])
assert numpy.array_equal(parallel_result[0][0], [2,3])
assert numpy.array_equal(parallel_result[0][1], [4,5])
assert numpy.array_equal(parallel_result[1][0], [4,6])
assert numpy.array_equal(parallel_result[1][1], [8,10])
def parallelization_test(self):
'''
simple test to check parallelization infrastructure
'''
dummy.parallel = main.parallel_function(dummy)
parallel_result = dummy.parallel([1, 2])
assert numpy.array_equal(parallel_result[0][0], [2, 3])
assert numpy.array_equal(parallel_result[0][1], [4, 5])
assert numpy.array_equal(parallel_result[1][0], [4, 6])
assert numpy.array_equal(parallel_result[1][1], [8, 10])
testNames.sort()
print('{} quality control checks have been found'.format(len(testNames)))
testNames = main.checkQCTestRequirements(testNames)
print('{} quality control checks are able to be run:'.format(
len(testNames)))
for testName in testNames:
print(' {}'.format(testName))
# Identify data files and create a profile list.
filenames = main.readInput('datafiles.json')
profiles = main.extractProfiles(filenames)
data.ds.profiles = profiles
print('\n{} file(s) will be read containing {} profiles'.format(
len(filenames), len(profiles)))
# Parallel processing.
print('\nPlease wait while QC is performed\n')
processFile.parallel = main.parallel_function(processFile, sys.argv[2])
parallel_result = processFile.parallel(filenames)
# Recombine results
truth, results, profileIDs = main.combineArrays(parallel_result)
# Print summary statistics and write output file.
main.printSummary(truth, results, testNames)
main.generateCSV(truth, results, testNames, profileIDs, sys.argv[1])
else:
print 'Please add command line arguments to name your output file and set parallelization:'
print 'python AutoQC myFile 4'
print 'will result in output written to results-myFile.csv, and will run the calculation parallelized across 4 cores.'
# Identify and import tests
testNames = main.importQC('qctests')
testNames.sort()
print('{} quality control checks have been found'.format(len(testNames)))
testNames = main.checkQCTestRequirements(testNames)
print('{} quality control checks are able to be run:'.format(len(testNames)))
for testName in testNames:
print(' {}'.format(testName))
# Identify data files and create a profile list.
filenames = main.readInput('datafiles.json')
profiles = main.extractProfiles(filenames)
data.ds.profiles = profiles
print('\n{} file(s) will be read containing {} profiles'.format(len(filenames), len(profiles)))
# Parallel processing.
print('\nPlease wait while QC is performed\n')
processFile.parallel = main.parallel_function(processFile, sys.argv[2])
parallel_result = processFile.parallel(filenames)
# Recombine results
truth, results, profileIDs = main.combineArrays(parallel_result)
# Print summary statistics and write output file.
main.printSummary(truth, results, testNames)
main.generateCSV(truth, results, testNames, profileIDs, sys.argv[1])
else:
print 'Please add command line arguments to name your output file and set parallelization:'
print 'python AutoQC myFile 4'
print 'will result in output written to results-myFile.csv, and will run the calculation parallelized across 4 cores.'
