594 lines
23 KiB
Python
594 lines
23 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: $Id$)',
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usage='./test.py [options]')
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self.updateRequested = False
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self.parser.add_option("-d", "--debug", action="store_true",\
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dest="debug",\
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help="debug run, don't calculate but use existing results")
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self.parser.add_option("-p", "--pass", action="store_true",\
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dest="accept",\
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help="calculate results but always consider test as successfull")
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self.parser.set_defaults(debug=False,
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accept=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 self.options.debug:
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for variant in xrange(len(self.variants)):
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try:
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self.postprocess(variant)
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if not self.compare(variant):
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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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else:
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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.options.accept or 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 fileInRoot(self,dir,file):
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'''
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Path to a file in the root directory of DAMASK.
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'''
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return os.path.join(damask.Environment().rootDir(),dir,file)
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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(self, mapA, mapB,
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A = [], B = []):
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'''
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copy list of files from (mapped) source to target.
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mapA/B is one of self.fileInX.
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'''
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if not B or len(B) == 0: B = A
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for source,target in zip(map(mapA,A),map(mapB,B)):
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try:
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shutil.copy2(source,target)
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except:
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logging.critical('error copying {} to {}'.format(source,target))
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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(name=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(name=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(name=file0,readonly=True)
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table0.head_read()
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table1 = damask.ASCIItable(name=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_TablesStatistically(self,
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files = [None,None], # list of file names
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columns = [None], # list of list of column labels (per file)
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meanTol = 1.0e-4,
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stdTol = 1.0e-6,
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preFilter = 1.0e-9):
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'''
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calculate statistics of tables
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threshold can be used to ignore small values (a negative number disables this feature)
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'''
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import numpy as np
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from collections import Iterable
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if not (isinstance(files, Iterable) and not isinstance(files, str)): # check whether list of files is requested
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files = [str(files)]
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tables = [damask.ASCIItable(name = filename,readonly = True) for filename in files]
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for table in tables:
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table.head_read()
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columns += [columns[0]]*(len(files)-len(columns)) # extend to same length as files
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columns = columns[:len(files)] # truncate to same length as files
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for i,column in enumerate(columns):
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if column is None: columns[i] = tables[i].labels # if no column is given, read all
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logging.info('comparing ASCIItables statistically')
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for i in xrange(len(columns)):
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columns[i] = columns[0] if not columns[i] else \
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([columns[i]] if not (isinstance(columns[i], Iterable) and not isinstance(columns[i], str)) else \
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columns[i]
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)
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logging.info(files[i]+':'+','.join(columns[i]))
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if len(files) < 2: return True # single table is always close to itself...
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data = []
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for table,labels in zip(tables,columns):
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table.data_readArray(labels)
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data.append(table.data)
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table.close()
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for i in xrange(1,len(data)):
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delta = data[i]-data[i-1]
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normBy = (np.abs(data[i]) + np.abs(data[i-1]))*0.5
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normedDelta = np.where(normBy>preFilter,delta/normBy,0.0)
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mean = np.amax(np.abs(np.mean(normedDelta,0)))
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std = np.amax(np.std(normedDelta,0))
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logging.info('mean: %f'%mean)
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logging.info('std: %f'%std)
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return (mean<meanTol) & (std < stdTol)
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def compare_Tables(self,
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files = [None,None], # list of file names
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columns = [None], # list of list of column labels (per file)
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rtol = 1e-5,
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atol = 1e-8,
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preFilter = -1.0,
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postFilter = -1.0,
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debug = False):
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'''
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compare tables with np.allclose
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threshold can be used to ignore small values (a negative number disables this feature)
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'''
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import numpy as np
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from collections import Iterable
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if not (isinstance(files, Iterable) and not isinstance(files, str)): # check whether list of files is requested
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files = [str(files)]
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tables = [damask.ASCIItable(name = filename,readonly = True) for filename in files]
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for table in tables:
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table.head_read()
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columns += [columns[0]]*(len(files)-len(columns)) # extend to same length as files
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columns = columns[:len(files)] # truncate to same length as files
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for i,column in enumerate(columns):
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if column is None: columns[i] = tables[i].labels # if no column is given, read all
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logging.info('comparing ASCIItables')
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for i in xrange(len(columns)):
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columns[i] = columns[0] if not columns[i] else \
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([columns[i]] if not (isinstance(columns[i], Iterable) and not isinstance(columns[i], str)) else \
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columns[i]
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)
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logging.info(files[i]+':'+','.join(columns[i]))
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|
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if len(files) < 2: return True # single table is always close to itself...
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|
|
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maximum = np.zeros(len(columns[0]),dtype='f')
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data = []
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for table,labels in zip(tables,columns):
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table.data_readArray(labels)
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data.append(np.where(np.abs(table.data)<preFilter,np.zeros_like(table.data),table.data))
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maximum += np.abs(table.data).max(axis=0)
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table.close()
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|
|
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maximum /= len(tables)
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maximum = np.where(maximum >0.0, maximum, 1) # do not devide by zero for empty columns
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|
for i in xrange(len(data)):
|
|
data[i] /= maximum
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|
|
|
mask = np.zeros_like(table.data,dtype='bool')
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|
|
|
for table in data:
|
|
mask |= np.where(np.abs(table)<postFilter,True,False) # mask out (all) tiny values
|
|
|
|
|
|
allclose = True # start optimistic
|
|
for i in xrange(1,len(data)):
|
|
if debug:
|
|
t0 = np.where(mask,0.0,data[i-1])
|
|
t1 = np.where(mask,0.0,data[i ])
|
|
j = np.argmin(np.abs(t1)*rtol+atol-np.abs(t0-t1))
|
|
logging.info('%f'%np.amax(np.abs(t0-t1)/(np.abs(t1)*rtol+atol)))
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logging.info('%f %f'%((t0*maximum).flatten()[j],(t1*maximum).flatten()[j]))
|
|
allclose &= np.allclose(np.where(mask,0.0,data[i-1]),
|
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np.where(mask,0.0,data[i ]),rtol,atol) # accumulate "pessimism"
|
|
|
|
return allclose
|
|
|
|
|
|
def compare_TableRefCur(self,headingsRef,ref,headingsCur='',cur='',normHeadings='',normType=None,\
|
|
absoluteTolerance=False,perLine=False,skipLines=[]):
|
|
|
|
if cur == '': cur = ref
|
|
if headingsCur == '': headingsCur = headingsRef
|
|
refName = self.fileInReference(ref)
|
|
curName = self.fileInCurrent(cur)
|
|
return self.compare_Table(headingsRef,refName,headingsCur,curName,normHeadings,normType,
|
|
absoluteTolerance,perLine,skipLines)
|
|
|
|
|
|
def compare_TableCurCur(self,headingsCur0,Cur0,Cur1,headingsCur1='',normHeadings='',normType=None,\
|
|
absoluteTolerance=False,perLine=False,skipLines=[]):
|
|
|
|
if headingsCur1 == '': headingsCur1 = headingsCur0
|
|
cur0Name = self.fileInCurrent(Cur0)
|
|
cur1Name = self.fileInCurrent(Cur1)
|
|
return self.compare_Table(headingsCur0,cur0Name,headingsCur1,cur1Name,normHeadings,normType,
|
|
absoluteTolerance,perLine,skipLines)
|
|
|
|
|
|
def report_Success(self,culprit):
|
|
|
|
if culprit == 0:
|
|
logging.critical('%s passed.'%({False: 'The test',
|
|
True: 'All %i tests'%(len(self.variants))}[len(self.variants) > 1]))
|
|
logging.critical('\n!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n')
|
|
return 0
|
|
if culprit == -1:
|
|
logging.warning('Warning: Could not start test')
|
|
return 0
|
|
else:
|
|
logging.critical(' ********\n * Test %i failed...\n ********'%(culprit))
|
|
logging.critical('\n!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n')
|
|
return culprit
|