# -*- coding: UTF-8 no BOM -*- import os,sys,shutil import logging,logging.config import damask import numpy as np from collections import Iterable from optparse import OptionParser class Test(): """ General class for testing. Is sub-classed by the individual tests. """ variants = [] def __init__(self,description = ''): fh = logging.FileHandler('test.log') # create file handler which logs even debug messages fh.setLevel(logging.DEBUG) fh.setFormatter(logging.Formatter('%(asctime)s - %(levelname)s: \n%(message)s')) ch = logging.StreamHandler(stream=sys.stdout) # create console handler with a higher log level ch.setLevel(logging.INFO) ch.setFormatter(logging.Formatter('%(message)s')) logger = logging.getLogger() logger.addHandler(fh) logger.addHandler(ch) logger.setLevel(0) logging.info('\n'.join(['+'*40, '-'*40, '| '+description, '-'*40, ])) self.dirBase = os.path.dirname(os.path.realpath(sys.modules[self.__class__.__module__].__file__)) self.parser = OptionParser(description = '{} (using class: {})'.format(description,damask.version), usage = './test.py [options]') self.parser.add_option("-d", "--debug", action = "store_true", dest = "debug", help = "debug run, don't calculate but use existing results") self.parser.add_option("-p", "--pass", action = "store_true", dest = "accept", help = "calculate results but always consider test as successfull") self.parser.add_option("-u", "--update", action = "store_true", dest = "update", help = "use current test results as new reference" ) self.parser.set_defaults(debug = False, accept = False, update = False, ) def execute(self): """Run all variants and report first failure.""" if self.options.debug: for variant in xrange(len(self.variants)): try: self.postprocess(variant) if not self.compare(variant): return variant+1 # return culprit except Exception as e : logging.critical('\nWARNING:\n {}\n'.format(e)) return variant+1 # return culprit return 0 else: if not self.feasible(): return -1 self.clean() self.prepareAll() for variant,name in enumerate(self.variants): try: self.prepare(variant) self.run(variant) self.postprocess(variant) if self.options.update: # update requested self.update(variant) elif not (self.options.accept or self.compare(variant)): # no update, do comparison return variant+1 # return culprit except Exception as e : logging.critical('\nWARNING:\n {}\n'.format(e)) return variant+1 # return culprit return 0 def feasible(self): """Check whether test is possible or not (e.g. no license available).""" return True def clean(self): """Delete directory tree containing current results.""" status = True try: shutil.rmtree(self.dirCurrent()) except: logging.warning('removal of directory "{}" not possible...'.format(self.dirCurrent())) status = status and False try: os.mkdir(self.dirCurrent()) except: logging.critical('creation of directory "{}" failed...'.format(self.dirCurrent())) status = status and False return status def prepareAll(self): """Do all necessary preparations for the whole test""" return True def prepare(self,variant): """Do all necessary preparations for the run of each test variant""" return True def run(self,variant): """Execute the requested test variant.""" return True def postprocess(self,variant): """Perform post-processing of generated results for this test variant.""" return True def compare(self,variant): """Compare reference to current results.""" return True def update(self,variant): """Update reference with current results.""" logging.debug('Update not necessary') return True def dirReference(self): """Directory containing reference results of the test.""" return os.path.normpath(os.path.join(self.dirBase,'reference/')) def dirCurrent(self): """Directory containing current results of the test.""" return os.path.normpath(os.path.join(self.dirBase,'current/')) def dirProof(self): """Directory containing human readable proof of correctness for the test.""" return os.path.normpath(os.path.join(self.dirBase,'proof/')) def fileInRoot(self,dir,file): """Path to a file in the root directory of DAMASK.""" return os.path.join(damask.Environment().rootDir(),dir,file) def fileInReference(self,file): """Path to a file in the refrence directory for the test.""" return os.path.join(self.dirReference(),file) def fileInCurrent(self,file): """Path to a file in the current results directory for the test.""" return os.path.join(self.dirCurrent(),file) def fileInProof(self,file): """Path to a file in the proof directory for the test.""" return os.path.join(self.dirProof(),file) def copy(self, mapA, mapB, A = [], B = []): """ copy list of files from (mapped) source to target. mapA/B is one of self.fileInX. """ if not B or len(B) == 0: B = A for source,target in zip(map(mapA,A),map(mapB,B)): try: shutil.copy2(source,target) except: logging.critical('error copying {} to {}'.format(source,target)) def copy_Reference2Current(self,sourcefiles=[],targetfiles=[]): if len(targetfiles) == 0: targetfiles = sourcefiles for i,file in enumerate(sourcefiles): try: shutil.copy2(self.fileInReference(file),self.fileInCurrent(targetfiles[i])) except: logging.critical('Reference2Current: Unable to copy file "{}"'.format(file)) def copy_Base2Current(self,sourceDir,sourcefiles=[],targetfiles=[]): source=os.path.normpath(os.path.join(self.dirBase,'../../..',sourceDir)) if len(targetfiles) == 0: targetfiles = sourcefiles for i,file in enumerate(sourcefiles): try: shutil.copy2(os.path.join(source,file),self.fileInCurrent(targetfiles[i])) except: logging.error(os.path.join(source,file)) logging.critical('Base2Current: Unable to copy file "{}"'.format(file)) def copy_Current2Reference(self,sourcefiles=[],targetfiles=[]): if len(targetfiles) == 0: targetfiles = sourcefiles for i,file in enumerate(sourcefiles): try: shutil.copy2(self.fileInCurrent(file),self.fileInReference(targetfiles[i])) except: logging.critical('Current2Reference: Unable to copy file "{}"'.format(file)) def copy_Proof2Current(self,sourcefiles=[],targetfiles=[]): if len(targetfiles) == 0: targetfiles = sourcefiles for i,file in enumerate(sourcefiles): try: shutil.copy2(self.fileInProof(file),self.fileInCurrent(targetfiles[i])) except: logging.critical('Proof2Current: Unable to copy file "{}"'.format(file)) def copy_Current2Current(self,sourcefiles=[],targetfiles=[]): for i,file in enumerate(sourcefiles): try: shutil.copy2(self.fileInReference(file),self.fileInCurrent(targetfiles[i])) except: logging.critical('Current2Current: Unable to copy file "{}"'.format(file)) def execute_inCurrentDir(self,cmd,streamIn=None): logging.info(cmd) out,error = damask.util.execute(cmd,streamIn,self.dirCurrent()) logging.info(error) logging.debug(out) return out,error def compare_Array(self,File1,File2): import numpy as np logging.info('\n '.join(['comparing',File1,File2])) table1 = damask.ASCIItable(name=File1,readonly=True) table1.head_read() len1=len(table1.info)+2 table2 = damask.ASCIItable(name=File2,readonly=True) table2.head_read() len2=len(table2.info)+2 refArray = np.nan_to_num(np.genfromtxt(File1,missing_values='n/a',skip_header = len1,autostrip=True)) curArray = np.nan_to_num(np.genfromtxt(File2,missing_values='n/a',skip_header = len2,autostrip=True)) if len(curArray) == len(refArray): refArrayNonZero = refArray[refArray.nonzero()] curArray = curArray[refArray.nonzero()] max_err=np.max(abs(refArrayNonZero[curArray.nonzero()]/curArray[curArray.nonzero()]-1.)) max_loc=np.argmax(abs(refArrayNonZero[curArray.nonzero()]/curArray[curArray.nonzero()]-1.)) refArrayNonZero = refArrayNonZero[curArray.nonzero()] curArray = curArray[curArray.nonzero()] print(' ********\n * maximum relative error {} between {} and {}\n ********'.format(max_err, refArrayNonZero[max_loc], curArray[max_loc])) return max_err else: raise Exception('mismatch in array size to compare') def compare_ArrayRefCur(self,ref,cur=''): if cur =='': cur = ref refName = self.fileInReference(ref) curName = self.fileInCurrent(cur) return self.compare_Array(refName,curName) def compare_ArrayCurCur(self,cur0,cur1): cur0Name = self.fileInCurrent(cur0) cur1Name = self.fileInCurrent(cur1) return self.compare_Array(cur0Name,cur1Name) def compare_Table(self,headings0,file0,headings1,file1,normHeadings='',normType=None, absoluteTolerance=False,perLine=False,skipLines=[]): import numpy as np logging.info('\n '.join(['comparing ASCII Tables',file0,file1])) if normHeadings == '': normHeadings = headings0 # check if comparison is possible and determine lenght of columns if len(headings0) == len(headings1) == len(normHeadings): dataLength = len(headings0) length = [1 for i in xrange(dataLength)] shape = [[] for i in xrange(dataLength)] data = [[] for i in xrange(dataLength)] maxError = [0.0 for i in xrange(dataLength)] absTol = [absoluteTolerance for i in xrange(dataLength)] column = [[1 for i in xrange(dataLength)] for j in xrange(2)] norm = [[] for i in xrange(dataLength)] normLength = [1 for i in xrange(dataLength)] normShape = [[] for i in xrange(dataLength)] normColumn = [1 for i in xrange(dataLength)] for i in xrange(dataLength): if headings0[i]['shape'] != headings1[i]['shape']: raise Exception('shape mismatch between {} and {} '.format(headings0[i]['label'],headings1[i]['label'])) shape[i] = headings0[i]['shape'] for j in xrange(np.shape(shape[i])[0]): length[i] *= shape[i][j] normShape[i] = normHeadings[i]['shape'] for j in xrange(np.shape(normShape[i])[0]): normLength[i] *= normShape[i][j] else: raise Exception('trying to compare {} with {} normed by {} data sets'.format(len(headings0), len(headings1), len(normHeadings))) table0 = damask.ASCIItable(name=file0,readonly=True) table0.head_read() table1 = damask.ASCIItable(name=file1,readonly=True) table1.head_read() for i in xrange(dataLength): key0 = ('1_' if length[i]>1 else '') + headings0[i]['label'] key1 = ('1_' if length[i]>1 else '') + headings1[i]['label'] normKey = ('1_' if normLength[i]>1 else '') + normHeadings[i]['label'] if key0 not in table0.labels(raw = True): raise Exception('column {} not found in 1. table...\n'.format(key0)) elif key1 not in table1.labels(raw = True): raise Exception('column {} not found in 2. table...\n'.format(key1)) elif normKey not in table0.labels(raw = True): raise Exception('column {} not found in 1. table...\n'.format(normKey)) else: column[0][i] = table0.label_index(key0) column[1][i] = table1.label_index(key1) normColumn[i] = table0.label_index(normKey) line0 = 0 while table0.data_read(): # read next data line of ASCII table if line0 not in skipLines: for i in xrange(dataLength): myData = np.array(map(float,table0.data[column[0][i]:\ column[0][i]+length[i]]),'d') normData = np.array(map(float,table0.data[normColumn[i]:\ normColumn[i]+normLength[i]]),'d') data[i] = np.append(data[i],np.reshape(myData,shape[i])) if normType == 'pInf': norm[i] = np.append(norm[i],np.max(np.abs(normData))) else: norm[i] = np.append(norm[i],np.linalg.norm(np.reshape(normData,normShape[i]),normType)) line0 += 1 for i in xrange(dataLength): if not perLine: norm[i] = [np.max(norm[i]) for j in xrange(line0-len(skipLines))] data[i] = np.reshape(data[i],[line0-len(skipLines),length[i]]) if any(norm[i]) == 0.0 or absTol[i]: norm[i] = [1.0 for j in xrange(line0-len(skipLines))] absTol[i] = True if perLine: logging.warning('At least one norm of {} in 1. table is 0.0, using absolute tolerance'.format(headings0[i]['label'])) else: logging.warning('Maximum norm of {} in 1. table is 0.0, using absolute tolerance'.format(headings0[i]['label'])) line1 = 0 while table1.data_read(): # read next data line of ASCII table if line1 not in skipLines: for i in xrange(dataLength): myData = np.array(map(float,table1.data[column[1][i]:\ column[1][i]+length[i]]),'d') maxError[i] = max(maxError[i],np.linalg.norm(np.reshape(myData-data[i][line1-len(skipLines),:],shape[i]))/ norm[i][line1-len(skipLines)]) line1 +=1 if (line0 != line1): raise Exception('found {} lines in 1. table but {} in 2. table'.format(line0,line1)) logging.info(' ********') for i in xrange(dataLength): if absTol[i]: logging.info(' * maximum absolute error {} between {} and {}'.format(maxError[i], headings0[i]['label'], headings1[i]['label'])) else: logging.info(' * maximum relative error {} between {} and {}'.format(maxError[i], headings0[i]['label'], headings1[i]['label'])) logging.info(' ********') return maxError def compare_TablesStatistically(self, files = [None,None], # list of file names columns = [None], # list of list of column labels (per file) meanTol = 1.0e-4, stdTol = 1.0e-6, preFilter = 1.0e-9): """ calculate statistics of tables threshold can be used to ignore small values (a negative number disables this feature) """ if not (isinstance(files, Iterable) and not isinstance(files, str)): # check whether list of files is requested files = [str(files)] tables = [damask.ASCIItable(name = filename,readonly = True) for filename in files] for table in tables: table.head_read() columns += [columns[0]]*(len(files)-len(columns)) # extend to same length as files columns = columns[:len(files)] # truncate to same length as files for i,column in enumerate(columns): if column is None: columns[i] = tables[i].labels(raw = True) # if no column is given, read all logging.info('comparing ASCIItables statistically') for i in xrange(len(columns)): 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])) if len(files) < 2: return True # single table is always close to itself... data = [] for table,labels in zip(tables,columns): table.data_readArray(labels) data.append(table.data) table.close() for i in xrange(1,len(data)): delta = data[i]-data[i-1] normBy = (np.abs(data[i]) + np.abs(data[i-1]))*0.5 normedDelta = np.where(normBy>preFilter,delta/normBy,0.0) mean = np.amax(np.abs(np.mean(normedDelta,0))) std = np.amax(np.std(normedDelta,0)) logging.info('mean: {:f}'.format(mean)) logging.info('std: {:f}'.format(std)) return (mean 0.0, maximum, 1) # avoid div by zero for empty columns # normalize each table for i in xrange(len(data)): data[i] /= maximum 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{}\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