improve functionality to compare ASCII tables
This commit is contained in:
Martin Diehl
parent
dbc26e5f25
commit
565713fecb
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@ -194,72 +194,84 @@ class Test():
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curName = self.fileInCurrent(cur)
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return self.compare_Array(refName,curName)
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def compare_TableRefCur(self,headings,ref,cur=''):
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if cur =='': cur = ref
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if len(headings) == 1 or type(headings) == dict: headings += headings
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if len(headings) != 2 : print 'headings should be array of length 1 or 2 containing dictionaries or a dictionary'
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if len(headings[0]) != len(headings[1]): print 'mismatch in headings to compare'
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def compare_TableRefCur(self,headingsRef,ref,headingsCur='',cur=''):
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if headingsCur == '': headingsCur = headingsRef
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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_Table(headings,refName,curName)
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return self.compare_Table(headingsRef,refName,headingsCur,curName)
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def compare_Table(self,headings,File1,File2):
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print 'comparing ASCII Tables\n' , File1,'\n', File2
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table1 = damask.ASCIItable(open(File1))
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table1.head_read()
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table2 = damask.ASCIItable(open(File2))
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table2.head_read()
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datainfo = { # list of requested labels per datatype
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'scalar': {'len':1,
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'label1':[],
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'label2':[]},
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'vector': {'len':3,
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'label1':[],
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'label2':[]},
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'tensor': {'len':9,
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'label1':[],
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'label2':[]},
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}
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for label in headings[0]:
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datainfo[headings[0][label]]['label1'] += [label]
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for label in headings[1]:
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datainfo[headings[1][label]]['label2'] += [label]
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active = [{},{}]
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column = [{},{}]
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for datatype,info in datainfo.items():
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for label in info['label1']:
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key = {True :'1_%s',
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False:'%s' }[info['len']>1]%label
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if key not in table1.labels:
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sys.stderr.write('column %s not found in 1. table...\n'%key)
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else:
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if datatype not in active[0]: active[0][datatype] = []
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if datatype not in column[0]: column[0][datatype] = {}
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active[0][datatype].append(label)
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column[0][datatype][label] = table1.labels.index(key) # remember columns of requested data
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for label in info['label2']:
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key = {True :'1_%s',
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False:'%s' }[info['len']>1]%label
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if key not in table2.labels:
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sys.stderr.write('column %s not found in 2. table...\n'%key)
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else:
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if datatype not in active[1]: active[1][datatype] = []
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if datatype not in column[1]: column[1][datatype] = {}
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active[1][datatype].append(label)
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column[1][datatype][label] = table2.labels.index(key) # remember columns of requested data
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def compare_Table(self,headings0,file0,headings1,file1):
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import numpy
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print 'comparing ASCII Tables\n' , file0,'\n', file1
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if len(headings0) == len(headings1): #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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maxNorm = [0.0 for i in xrange(dataLength)]
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column = [[length],[length]]
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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 ', headings0[i]['label'], ' with ', headings1[i]['label'])
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shape[i] = headings0[i]['shape']
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for j in xrange(numpy.shape(headings0[i]['shape'])[0]):
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length[i] = headings0[i]['shape'][j]
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else:
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raise Exception('trying to compare ', len(headings0), ' with ', len(headings1), ' data sets')
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table0 = damask.ASCIItable(open(file0))
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table0.head_read()
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table1 = damask.ASCIItable(open(file1))
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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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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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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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line0 = 0
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while table0.data_read(): # read next data line of ASCII table
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line0 +=1
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for i in xrange(dataLength):
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myData = numpy.array(map(float,table0.data[column[0][i]:\
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column[0][i]+length[i]]),'d')
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maxNorm[i] = max(maxNorm[i],numpy.linalg.norm(numpy.reshape(myData,shape[i])))
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data[i]=numpy.append(data[i],myData)
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for i in xrange(dataLength):
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data[i] = numpy.reshape(data[i],[line0,length[i]])
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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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for datatype,labels in active[0].items(): # loop over vector,tensor
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for label in labels: # loop over all requested norms
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data1[label] += numpy.array(map(float,table1.data[column[0][datatype][label]:
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column[0][datatype][label]+datainfo[datatype]['len']]),'d').reshape(3,3)
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print myData
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for i in xrange(dataLength):
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myData = numpy.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],numpy.linalg.norm(numpy.reshape(myData-data[i][line1,:],shape[i])))
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line1 +=1
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if (line0 != line1): raise Exception('found ', line0, ' lines in 1. table and ', line1, ' in 2. table')
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for i in xrange(dataLength):
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maxError[i] = maxError[i]/maxNorm[i]
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return maxError
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def report_Success(self,culprit):
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if culprit < 0:
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