564 lines
22 KiB
Python
564 lines
22 KiB
Python
# -*- coding: UTF-8 no BOM -*-
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import os,sys,shutil
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import logging,logging.config
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import damask
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import numpy as np
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from collections import Iterable
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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, **kwargs):
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defaults = {'description': '',
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'keep': False,
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'accept': False,
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'update': False,
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}
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for arg in defaults.keys():
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setattr(self,arg,kwargs.get(arg) if kwargs.get(arg) else defaults[arg])
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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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fh.setFormatter(logging.Formatter('%(asctime)s - %(levelname)s: \n%(message)s'))
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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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ch.setFormatter(logging.Formatter('%(message)s'))
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logger = logging.getLogger()
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logger.addHandler(fh)
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logger.addHandler(ch)
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logger.setLevel(0)
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logging.info('\n'.join(['+'*40,
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'-'*40,
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'| '+self.description,
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'-'*40,
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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(description = '{} (Test class version: {})'.format(self.description,damask.version),
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usage = './test.py [options]')
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self.parser.add_option("-k", "--keep",
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action = "store_true",
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dest = "keep",
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help = "keep current results, just run postprocessing")
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self.parser.add_option("--ok", "--accept",
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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(keep = self.keep,
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accept = self.accept,
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update = self.update,
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)
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def execute(self):
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"""Run all variants and report first failure."""
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if not self.options.keep:
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if not self.feasible(): return -1
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self.clean()
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self.prepareAll()
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for variant,name in enumerate(self.variants):
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try:
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if not self.options.keep:
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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.options.update and not self.update(variant):
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logging.critical('update for "{}" failed.'.format(name))
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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('exception during variant execution: {}'.format(e))
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return variant+1 # return culprit
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return 0
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def feasible(self):
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"""Check whether test is possible or not (e.g. no license available)."""
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return True
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def clean(self):
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"""Delete directory tree containing current results."""
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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 "{}" not possible...'.format(self.dirCurrent()))
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try:
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os.mkdir(self.dirCurrent())
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return True
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except:
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logging.critical('creation of directory "{}" failed.'.format(self.dirCurrent()))
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return False
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def prepareAll(self):
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"""Do all necessary preparations for the whole test"""
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return True
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def prepare(self,variant):
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"""Do all necessary preparations for the run of each test variant"""
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return True
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def run(self,variant):
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"""Execute the requested test variant."""
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return True
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def postprocess(self,variant):
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"""Perform post-processing of generated results for this test variant."""
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return True
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def compare(self,variant):
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"""Compare reference to current results."""
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return True
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def update(self,variant):
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"""Update reference with current results."""
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logging.critical('update not supported.')
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return False
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def dirReference(self):
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"""Directory containing reference results of the test."""
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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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"""Directory containing current results of the test."""
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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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"""Directory containing human readable proof of correctness for the test."""
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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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"""Path to a file in the root directory of DAMASK."""
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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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"""Path to a file in the refrence directory for the test."""
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return os.path.join(self.dirReference(),file)
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def fileInCurrent(self,file):
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"""Path to a file in the current results directory for the test."""
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return os.path.join(self.dirCurrent(),file)
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def fileInProof(self,file):
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"""Path to a file in the proof directory for the test."""
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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 "{}"'.format(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 "{}"'.format(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 "{}"'.format(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 "{}"'.format(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 "{}"'.format(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('\n '.join(['comparing',File1,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 {} between {} and {}\n ********'.format(max_err,
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refArrayNonZero[max_loc],
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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('\n '.join(['comparing ASCII Tables',file0,file1]))
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if normHeadings == '': normHeadings = headings0
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# check if comparison is possible and determine lenght of columns
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if len(headings0) == len(headings1) == len(normHeadings):
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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 between {} and {} '.format(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 {} with {} normed by {} data sets'.format(len(headings0),
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len(headings1),
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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 = ('1_' if length[i]>1 else '') + headings0[i]['label']
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key1 = ('1_' if length[i]>1 else '') + headings1[i]['label']
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normKey = ('1_' if normLength[i]>1 else '') + normHeadings[i]['label']
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if key0 not in table0.labels(raw = True):
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raise Exception('column {} not found in 1. table...\n'.format(key0))
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elif key1 not in table1.labels(raw = True):
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raise Exception('column {} not found in 2. table...\n'.format(key1))
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elif normKey not in table0.labels(raw = True):
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raise Exception('column {} not found in 1. table...\n'.format(normKey))
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else:
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column[0][i] = table0.label_index(key0)
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column[1][i] = table1.label_index(key1)
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normColumn[i] = table0.label_index(normKey)
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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 {} in 1. table is 0.0, using absolute tolerance'.format(headings0[i]['label']))
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else:
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logging.warning('Maximum norm of {} in 1. table is 0.0, using absolute tolerance'.format(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 {} lines in 1. table but {} in 2. table'.format(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 {} between {} and {}'.format(maxError[i],
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headings0[i]['label'],
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headings1[i]['label']))
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else:
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logging.info(' * maximum relative error {} between {} and {}'.format(maxError[i],
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headings0[i]['label'],
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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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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(raw = True) # 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}'.format(mean))
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logging.info('std: {:f}'.format(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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debug = False):
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"""compare multiple tables with np.allclose"""
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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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if len(files) < 2: return True # single table is always close to itself...
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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(raw = False) # if no column is given, use 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 \
|
|
([columns[i]] if not (isinstance(columns[i], Iterable) and not isinstance(columns[i], str)) else \
|
|
columns[i]
|
|
)
|
|
logging.info(files[i]+': '+','.join(columns[i]))
|
|
|
|
dimensions = tables[0].label_dimension(columns[0]) # width of each requested column
|
|
maximum = np.zeros_like(columns[0],dtype=float) # one magnitude per column entry
|
|
data = [] # list of feature table extracted from each file (ASCII table)
|
|
|
|
for i,(table,labels) in enumerate(zip(tables,columns)):
|
|
if np.any(dimensions != table.label_dimension(labels)): # check data object consistency
|
|
logging.critical('Table {} differs in data layout.'.format(files[i]))
|
|
return False
|
|
table.data_readArray(labels) # read data, ...
|
|
data.append(table.data) # ... store, ...
|
|
table.close() # ... close
|
|
|
|
for j,label in enumerate(labels): # iterate over object labels
|
|
maximum[j] = np.maximum(\
|
|
maximum[j],
|
|
np.amax(np.linalg.norm(table.data[:,table.label_indexrange(label)],
|
|
axis=1))
|
|
) # find maximum Euclidean norm across rows
|
|
|
|
maximum = np.where(maximum > 0.0, maximum, 1.0) # avoid div by zero for zero columns
|
|
maximum = np.repeat(maximum,dimensions) # spread maximum over columns of each object
|
|
|
|
for i in xrange(len(data)):
|
|
data[i] /= maximum # normalize each table
|
|
|
|
if debug:
|
|
logging.debug(str(maximum))
|
|
allclose = np.absolute(data[0]-data[1]) <= (atol + rtol*np.absolute(data[1]))
|
|
for ok,valA,valB in zip(allclose,data[0],data[1]):
|
|
logging.debug('{}:\n{}\n{}'.format(ok,valA,valB))
|
|
|
|
allclose = True # start optimistic
|
|
for i in xrange(1,len(data)):
|
|
allclose &= np.allclose(data[i-1],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):
|
|
|
|
ret = culprit
|
|
|
|
if culprit == 0:
|
|
msg = 'The test passed' if len(self.variants) == 1 \
|
|
else 'All {} tests passed.'.format(len(self.variants))
|
|
elif culprit == -1:
|
|
msg = 'Warning: Could not start test...'
|
|
ret = 0
|
|
else:
|
|
msg = ' * Test "{}" failed.'.format(self.variants[culprit-1])
|
|
|
|
logging.critical('\n'.join(['*'*40,msg,'*'*40]) + '\n')
|
|
return ret
|