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.'