458 lines
17 KiB
Python
458 lines
17 KiB
Python
# -*- coding: UTF-8 no BOM -*-
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# $Id$
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import os, sys, shlex, inspect
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import subprocess,shutil,string
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import logging, logging.config
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import damask
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from optparse import OptionParser
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class Test():
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'''
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General class for testing.
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Is sub-classed by the individual tests.
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'''
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variants = []
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def __init__(self,test_description):
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logger = logging.getLogger()
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logger.setLevel(0)
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fh = logging.FileHandler('test.log') # create file handler which logs even debug messages
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fh.setLevel(logging.DEBUG)
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full = logging.Formatter('%(asctime)s - %(levelname)s: \n%(message)s')
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fh.setFormatter(full)
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ch = logging.StreamHandler(stream=sys.stdout) # create console handler with a higher log level
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ch.setLevel(logging.INFO)
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# create formatter and add it to the handlers
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plain = logging.Formatter('%(message)s')
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ch.setFormatter(plain)
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# add the handlers to the logger
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logger.addHandler(fh)
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logger.addHandler(ch)
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logging.info('!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n\n' \
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+'----------------------------------------------------------------\n' \
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+'| '+test_description+'\n' \
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+'----------------------------------------------------------------')
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self.dirBase = os.path.dirname(os.path.realpath(sys.modules[self.__class__.__module__].__file__))
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self.parser = OptionParser(
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description = test_description+' (using class: $Id run_test.py 1285 2012-02-09 08:54:09Z MPIE\m.diehl $)',
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usage='./test.py [options]')
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self.updateRequested = False
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def execute(self):
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'''
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Run all variants and report first failure.
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'''
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if not self.testPossible(): return -1
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self.clean()
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self.prepareAll()
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for variant in xrange(len(self.variants)):
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try:
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self.prepare(variant)
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self.run(variant)
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self.postprocess(variant)
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if self.updateRequested: # update requested
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self.update(variant)
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elif not self.compare(variant): # no update, do comparison
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return variant+1 # return culprit
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except Exception as e :
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logging.critical('\nWARNING:\n %s\n'%e)
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return variant+1 # return culprit
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return 0
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def testPossible(self):
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'''
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Check if test is possible or not (e.g. no license available).
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'''
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return True
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def clean(self):
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'''
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Delete directory tree containing current results.
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'''
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status = True
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try:
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shutil.rmtree(self.dirCurrent())
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except:
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logging.warning('removal of directory "%s" not possible...'%(self.dirCurrent()))
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status = status and False
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try:
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os.mkdir(self.dirCurrent())
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except:
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logging.critical('creation of directory "%s" failed...'%(self.dirCurrent()))
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status = status and False
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return status
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def prepareAll(self):
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'''
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Do all necessary preparations for the whole test
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'''
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return True
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def prepare(self,variant):
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'''
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Do all necessary preparations for the run of each test variant
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'''
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return True
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def run(self,variant):
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'''
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Execute the requested test variant.
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'''
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return True
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def postprocess(self,variant):
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'''
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Perform post-processing of generated results for this test variant.
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'''
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return True
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def compare(self,variant):
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'''
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Compare reference to current results.
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'''
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return True
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def update(self,variant):
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'''
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Update reference with current results.
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'''
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logging.debug('Update not necessary')
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return True
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def dirReference(self):
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'''
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Directory containing reference results of the test.
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'''
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return os.path.normpath(os.path.join(self.dirBase,'reference/'))
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def dirCurrent(self):
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'''
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Directory containing current results of the test.
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'''
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return os.path.normpath(os.path.join(self.dirBase,'current/'))
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def dirProof(self):
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'''
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Directory containing human readable proof of correctness for the test.
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'''
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return os.path.normpath(os.path.join(self.dirBase,'proof/'))
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def fileInReference(self,file):
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'''
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Path to a file in the refrence directory for the test.
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'''
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return os.path.join(self.dirReference(),file)
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def fileInCurrent(self,file):
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'''
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Path to a file in the current results directory for the test.
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'''
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return os.path.join(self.dirCurrent(),file)
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def fileInProof(self,file):
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'''
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Path to a file in the proof directory for the test.
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'''
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return os.path.join(self.dirProof(),file)
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def copy_Reference2Current(self,sourcefiles=[],targetfiles=[]):
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if len(targetfiles) == 0: targetfiles = sourcefiles
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for i,file in enumerate(sourcefiles):
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try:
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shutil.copy2(self.fileInReference(file),self.fileInCurrent(targetfiles[i]))
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except:
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logging.critical('Reference2Current: Unable to copy file %s'%file)
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def copy_Base2Current(self,sourceDir,sourcefiles=[],targetfiles=[]):
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source=os.path.normpath(os.path.join(self.dirBase,'../../'+sourceDir))
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if len(targetfiles) == 0: targetfiles = sourcefiles
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for i,file in enumerate(sourcefiles):
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try:
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shutil.copy2(os.path.join(source,file),self.fileInCurrent(targetfiles[i]))
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except:
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logging.error(os.path.join(source,file))
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logging.critical('Base2Current: Unable to copy file %s'%file)
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def copy_Current2Reference(self,sourcefiles=[],targetfiles=[]):
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if len(targetfiles) == 0: targetfiles = sourcefiles
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for i,file in enumerate(sourcefiles):
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try:
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shutil.copy2(self.fileInCurrent(file),self.fileInReference(targetfiles[i]))
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except:
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logging.critical('Current2Reference: Unable to copy file %s'%file)
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def copy_Proof2Current(self,sourcefiles=[],targetfiles=[]):
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if len(targetfiles) == 0: targetfiles = sourcefiles
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for i,file in enumerate(sourcefiles):
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try:
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shutil.copy2(self.fileInProof(file),self.fileInCurrent(targetfiles[i]))
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except:
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logging.critical('Proof2Current: Unable to copy file %s'%file)
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def copy_Current2Current(self,sourcefiles=[],targetfiles=[]):
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for i,file in enumerate(sourcefiles):
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try:
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shutil.copy2(self.fileInReference(file),self.fileInCurrent(targetfiles[i]))
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except:
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logging.critical('Current2Current: Unable to copy file %s'%file)
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def execute_inCurrentDir(self,cmd,streamIn=None):
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logging.info(cmd)
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out,error = damask.util.execute(cmd,streamIn,self.dirCurrent())
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logging.info(error)
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logging.debug(out)
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return out,error
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def compare_Array(self,File1,File2):
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import numpy as np
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logging.info('comparing\n '+File1+'\n '+File2)
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table1 = damask.ASCIItable(File1,readonly=True)
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table1.head_read()
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len1=len(table1.info)+2
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table2 = damask.ASCIItable(File2,readonly=True)
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table2.head_read()
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len2=len(table2.info)+2
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refArray = np.nan_to_num(np.genfromtxt(File1,missing_values='n/a',skip_header = len1,autostrip=True))
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curArray = np.nan_to_num(np.genfromtxt(File2,missing_values='n/a',skip_header = len2,autostrip=True))
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if len(curArray) == len(refArray):
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refArrayNonZero = refArray[refArray.nonzero()]
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curArray = curArray[refArray.nonzero()]
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max_err=np.max(abs(refArrayNonZero[curArray.nonzero()]/curArray[curArray.nonzero()]-1.))
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max_loc=np.argmax(abs(refArrayNonZero[curArray.nonzero()]/curArray[curArray.nonzero()]-1.))
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refArrayNonZero = refArrayNonZero[curArray.nonzero()]
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curArray = curArray[curArray.nonzero()]
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print(' ********\n * maximum relative error %e for %e and %e\n ********'
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%(max_err, refArrayNonZero[max_loc],curArray[max_loc]))
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return max_err
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else:
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raise Exception('mismatch in array size to compare')
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def compare_ArrayRefCur(self,ref,cur=''):
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if cur =='': cur = ref
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refName = self.fileInReference(ref)
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curName = self.fileInCurrent(cur)
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return self.compare_Array(refName,curName)
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def compare_ArrayCurCur(self,cur0,cur1):
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cur0Name = self.fileInCurrent(cur0)
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cur1Name = self.fileInCurrent(cur1)
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return self.compare_Array(cur0Name,cur1Name)
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def compare_Table(self,headings0,file0,headings1,file1,normHeadings='',normType=None,\
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absoluteTolerance=False,perLine=False,skipLines=[]):
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import numpy as np
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logging.info('comparing ASCII Tables\n %s \n %s'%(file0,file1))
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if normHeadings == '': normHeadings = headings0
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if len(headings0) == len(headings1) == len(normHeadings): #check if comparison is possible and determine lenght of columns
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dataLength = len(headings0)
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length = [1 for i in xrange(dataLength)]
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shape = [[] for i in xrange(dataLength)]
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data = [[] for i in xrange(dataLength)]
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maxError = [0.0 for i in xrange(dataLength)]
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absTol = [absoluteTolerance for i in xrange(dataLength)]
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column = [[1 for i in xrange(dataLength)] for j in xrange(2)]
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norm = [[] for i in xrange(dataLength)]
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normLength = [1 for i in xrange(dataLength)]
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normShape = [[] for i in xrange(dataLength)]
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normColumn = [1 for i in xrange(dataLength)]
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for i in xrange(dataLength):
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if headings0[i]['shape'] != headings1[i]['shape']:
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raise Exception('shape mismatch when comparing %s with %s '%(headings0[i]['label'],headings1[i]['label']))
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shape[i] = headings0[i]['shape']
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for j in xrange(np.shape(shape[i])[0]):
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length[i] *= shape[i][j]
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normShape[i] = normHeadings[i]['shape']
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for j in xrange(np.shape(normShape[i])[0]):
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normLength[i] *= normShape[i][j]
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else:
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raise Exception('trying to compare %i with %i normed by %i data sets'%(len(headings0),len(headings1),len(normHeadings)))
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table0 = damask.ASCIItable(file0,readonly=True)
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table0.head_read()
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table1 = damask.ASCIItable(file1,readonly=True)
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table1.head_read()
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for i in xrange(dataLength):
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key0 = {True :'1_%s',
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False:'%s' }[length[i]>1]%headings0[i]['label']
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key1 = {True :'1_%s',
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False:'%s' }[length[i]>1]%headings1[i]['label']
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normKey = {True :'1_%s',
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False:'%s' }[normLength[i]>1]%normHeadings[i]['label']
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if key0 not in table0.labels:
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raise Exception('column %s not found in 1. table...\n'%key0)
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elif key1 not in table1.labels:
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raise Exception('column %s not found in 2. table...\n'%key1)
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elif normKey not in table0.labels:
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raise Exception('column %s not found in 1. table...\n'%normKey)
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else:
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column[0][i] = table0.labels.index(key0) # remember columns of requested data
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column[1][i] = table1.labels.index(key1) # remember columns of requested data in second column
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normColumn[i] = table0.labels.index(normKey) # remember columns of requested data in second column
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line0 = 0
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while table0.data_read(): # read next data line of ASCII table
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if line0 not in skipLines:
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for i in xrange(dataLength):
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myData = np.array(map(float,table0.data[column[0][i]:\
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column[0][i]+length[i]]),'d')
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normData = np.array(map(float,table0.data[normColumn[i]:\
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normColumn[i]+normLength[i]]),'d')
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data[i] = np.append(data[i],np.reshape(myData,shape[i]))
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if normType == 'pInf':
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norm[i] = np.append(norm[i],np.max(np.abs(normData)))
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else:
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norm[i] = np.append(norm[i],np.linalg.norm(np.reshape(normData,normShape[i]),normType))
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line0 +=1
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for i in xrange(dataLength):
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if not perLine: norm[i] = [np.max(norm[i]) for j in xrange(line0-len(skipLines))]
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data[i] = np.reshape(data[i],[line0-len(skipLines),length[i]])
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if any(norm[i]) == 0.0 or absTol[i]:
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norm[i] = [1.0 for j in xrange(line0-len(skipLines))]
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absTol[i] = True
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if perLine:
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logging.warning('At least one norm of %s in 1. table is 0.0, using absolute tolerance'%headings0[i]['label'])
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else:
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logging.warning('Maximum norm of %s in 1. table is 0.0, using absolute tolerance'%headings0[i]['label'])
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line1 = 0
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while table1.data_read(): # read next data line of ASCII table
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if line1 not in skipLines:
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for i in xrange(dataLength):
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myData = np.array(map(float,table1.data[column[1][i]:\
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column[1][i]+length[i]]),'d')
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maxError[i] = max(maxError[i],np.linalg.norm(np.reshape(myData-data[i][line1-len(skipLines),:],shape[i]))/
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norm[i][line1-len(skipLines)])
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line1 +=1
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if (line0 != line1): raise Exception('found %s lines in 1. table and %s in 2. table'%(line0,line1))
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logging.info(' ********')
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for i in xrange(dataLength):
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if absTol[i]:
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logging.info(' * maximum absolute error %e for %s and %s'%(maxError[i],headings0[i]['label'],headings1[i]['label']))
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else:
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logging.info(' * maximum relative error %e for %s and %s'%(maxError[i],headings0[i]['label'],headings1[i]['label']))
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logging.info(' ********')
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return maxError
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def compare_Table2(self,file0,file1,headings0=None,headings1=None,rtol=1e-5,atol=1e-8,threshold = -1.0,debug=False):
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'''
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compare two tables with np.allclose
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threshold can be used to ignore small values (put any negative number to disable)
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table will be row-wise normalized
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'''
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#http://stackoverflow.com/questions/8904694/how-to-normalize-a-2-dimensional-numpy-array-in-python-less-verbose
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import numpy as np
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logging.info('comparing ASCII Tables\n %s \n %s'%(file0,file1))
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if headings1 == None: headings1=headings0
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table0 = damask.ASCIItable(file0,readonly=True)
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table0.head_read()
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table0.data_readArray(headings0)
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row_sums0 = table0.data.sum(axis=1)*table0.data.shape[0]
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table0.data /= row_sums0[:,np.newaxis]
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table1 = damask.ASCIItable(file1,readonly=True)
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table1.head_read()
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table1.data_readArray(headings1)
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row_sums1 = table1.data.sum(axis=1)*table1.data.shape[0]
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table1.data /= row_sums1[:,np.newaxis]
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if debug:
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t0 = np.where(np.abs(table0.data)<threshold,0.0,table0.data)
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t1 = np.where(np.abs(table1.data)<threshold,0.0,table1.data)
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print np.amin(np.abs(t1)*rtol+atol-np.abs(t0-t1))
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i = np.argmin(np.abs(t1)*rtol+atol-np.abs(t0-t1))
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print t0.flatten()[i],t1.flatten()[i]
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return np.allclose(np.where(np.abs(table0.data)<threshold,0.0,table0.data),
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np.where(np.abs(table1.data)<threshold,0.0,table1.data),rtol,atol)
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def compare_TableRefCur(self,headingsRef,ref,headingsCur='',cur='',normHeadings='',normType=None,\
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absoluteTolerance=False,perLine=False,skipLines=[]):
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if cur == '': cur = ref
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if headingsCur == '': headingsCur = headingsRef
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refName = self.fileInReference(ref)
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curName = self.fileInCurrent(cur)
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return self.compare_Table(headingsRef,refName,headingsCur,curName,normHeadings,normType,
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absoluteTolerance,perLine,skipLines)
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def compare_TableCurCur(self,headingsCur0,Cur0,Cur1,headingsCur1='',normHeadings='',normType=None,\
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absoluteTolerance=False,perLine=False,skipLines=[]):
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if headingsCur1 == '': headingsCur1 = headingsCur0
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cur0Name = self.fileInCurrent(Cur0)
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cur1Name = self.fileInCurrent(Cur1)
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return self.compare_Table(headingsCur0,cur0Name,headingsCur1,cur1Name,normHeadings,normType,
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absoluteTolerance,perLine,skipLines)
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def report_Success(self,culprit):
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if culprit == 0:
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logging.critical('%s passed.'%({False: 'The test',
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True: 'All %i tests'%(len(self.variants))}[len(self.variants) > 1]))
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logging.critical('\n!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n')
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return 0
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if culprit == -1:
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logging.warning('Warning: Could not start test')
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return 0
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else:
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logging.critical(' ********\n * Test %i failed...\n ********'%(culprit))
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logging.critical('\n!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n')
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return culprit
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