wrong file was selected during last commit

examples/SpectralMethod/tensionX.load

@@ -1 +1,2 @@
-fdot 1.0e-3 0 0  0 * 0   0 * 0   stress  * * *   * 0 *   * 0 *   time  1  incs   4 freq  40
+fdot 1.0e-3 0 0  0 * 0   0 * 0   stress  * * *   * 0 *   * 0 *   time  10  incs   40 freq  4
+fdot 1.0e-3 0 0  0 * 0   0 * 0   stress  * * *   * 0 *   * 0 *   time  60  incs   60

lib/damask/test/test.py

@@ -39,6 +39,7 @@ class Test():
     if len(update)   == 0 and self.options.update: print ' This test has no reference to update'
     if len(variants) == 0: variants = xrange(len(self.variants))       # iterate over all variants
     self.clean()
+    self.prepareAll()
     for variant in variants:
       try:
         self.prepare(variant)
@@ -72,7 +73,12 @@ class Test():
       status = status and False
 
     return status
-
+    
+  def prepareAll(self):
+    '''
+    Do all necessary preparations for the whole test
+    '''
+    return True
 
   def prepare(self,variant):
     '''
@@ -118,7 +124,12 @@ class Test():
     '''
     '''
     return os.path.normpath(os.path.join(self.dirBase,'current/'))
-
+  
+  def dirProof(self):
+    '''
+    '''
+    return os.path.normpath(os.path.join(self.dirBase,'proof/'))
+    
   def fileInReference(self,file):
     '''
     '''
@@ -128,7 +139,12 @@ class Test():
     '''
     '''
     return os.path.join(self.dirCurrent(),file)
-
+  
+  def fileInProof(self,file):
+    '''
+    '''
+    return os.path.join(self.dirProof(),file)
+    
   def copy_Reference2Current(self,sourcefiles=[],targetfiles=[]):
     
     if len(targetfiles) == 0: targetfiles = sourcefiles
@@ -146,7 +162,16 @@ class Test():
         shutil.copy2(self.fileInCurrent(file),self.fileInReference(targetfiles[i]))  
       except:
         print 'Current2Reference: Unable to copy file ', 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:
+        print 'Proof2Current: Unable to copy file ', file
+        
   def copy_Current2Current(self,sourcefiles=[],targetfiles=[]):
     
     for i,file in enumerate(sourcefiles):
@@ -186,7 +211,6 @@ class Test():
     else:
        raise Exception('mismatch in array size to compare')
 
-      
   def compare_ArrayRefCur(self,ref,cur=''):
     
     if cur =='': cur = ref
@@ -194,36 +218,44 @@ class Test():
     curName = self.fileInCurrent(cur)
     return self.compare_Array(refName,curName)
     
-  def compare_TableRefCur(self,headingsRef,ref,headingsCur='',cur=''):
+  def compare_ArrayCurCur(self,cur0,cur1):
     
-    if headingsCur == '': headingsCur = headingsRef
+    cur0Name = self.fileInCurrent(cur0)
-    if cur == '': cur = ref
+    cur1Name = self.fileInCurrent(cur1)
-    refName = self.fileInReference(ref)
+    return self.compare_Array(cur0Name,cur1Name)
-    curName = self.fileInCurrent(cur)
+
-    return self.compare_Table(headingsRef,refName,headingsCur,curName)
+  def compare_Table(self,headings0,file0,headings1,file1,normHeadings='',normType=None,\
-    
+                                     absoluteTolerance=False,perLine=False,skipLines=[]):
-  def compare_Table(self,headings0,file0,headings1,file1):
     
     import numpy
     print 'comparing ASCII Tables\n' , file0,'\n', file1
+    if normHeadings == '': normHeadings = headings0
 
-    if len(headings0) == len(headings1):                                                             #check if comparison is possible and determine lenght of columns
+    if len(headings0) == len(headings1) == len(normHeadings):                                         #check if comparison is possible and determine lenght of columns
       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)]
-      maxNorm      = [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 when comparing ', headings0[i]['label'], ' with ', headings1[i]['label'])
         shape[i] = headings0[i]['shape']
         for j in xrange(numpy.shape(shape[i])[0]):
           length[i] *= shape[i][j]
+        normShape[i] = normHeadings[i]['shape']
+        for j in xrange(numpy.shape(normShape[i])[0]):
+          normLength[i] *= normShape[i][j]
     else:
-      raise Exception('trying to compare ', len(headings0), ' with ', len(headings1), ' data sets')
+      raise Exception('trying to compare ', len(headings0), ' with ', len(headings1), ' normed by ', len(normHeadings),' data sets')
 
     table0 = damask.ASCIItable(open(file0))
     table0.head_read()
@@ -231,51 +263,78 @@ class Test():
     table1.head_read()   
 
     for i in xrange(dataLength):
-      key0 = {True :'1_%s',
+      key0 =    {True :'1_%s',
-             False:'%s'   }[length[i]>1]%headings0[i]['label']
+                 False:'%s'   }[length[i]>1]%headings0[i]['label']
-      key1 = {True :'1_%s',
+      key1 =    {True :'1_%s',
-             False:'%s'   }[length[i]>1]%headings1[i]['label']
+                 False:'%s'   }[length[i]>1]%headings1[i]['label']
+      normKey = {True :'1_%s',
+                 False:'%s'   }[normLength[i]>1]%normHeadings[i]['label']
       if key0 not in table0.labels:
         raise Exception('column %s not found in 1. table...\n'%key0)
       elif key1 not in table1.labels:
         raise Exception('column %s not found in 2. table...\n'%key1)
+      elif normKey not in table0.labels:
+        raise Exception('column %s not found in 1. table...\n'%normKey)
       else:
-        column[0][i] = table0.labels.index(key0)                   # remember columns of requested data
+        column[0][i]  = table0.labels.index(key0)                                  # remember columns of requested data
-        column[1][i] = table1.labels.index(key1)                   # remember columns of requested data in second column
+        column[1][i]  = table1.labels.index(key1)                                  # remember columns of requested data in second column
-
+        normColumn[i] = table0.labels.index(normKey)                               # remember columns of requested data in second column
-    line0 = 0
-
-    while table0.data_read():                                                     # read next data line of ASCII table
-      line0 +=1
-      for i in xrange(dataLength):
-        myData = numpy.array(map(float,table0.data[column[0][i]:\
-                                                   column[0][i]+length[i]]),'d')
-        maxNorm[i] = max(maxNorm[i],numpy.linalg.norm(numpy.reshape(myData,shape[i])))
-        data[i]=numpy.append(data[i],myData)
- 
-    for i in xrange(dataLength):
-      data[i] = numpy.reshape(data[i],[line0,length[i]])
-      if maxNorm[i] == 0.0:
-        print 'Maximum norm of',headings0[i]['label'],'in 1. table is 0, using absolute tolerance'
-        maxNorm[i] = 1.0
     
+    line0 = 0
+    while table0.data_read():                                                     # read next data line of ASCII table
+      if line0 not in skipLines:
+        for i in xrange(dataLength):
+          myData = numpy.array(map(float,table0.data[column[0][i]:\
+                                                     column[0][i]+length[i]]),'d')
+          normData = numpy.array(map(float,table0.data[normColumn[i]:\
+                                                       normColumn[i]+normLength[i]]),'d')
+          data[i] = numpy.append(data[i],numpy.reshape(myData,shape[i]))
+          if normType == 'pInf':
+            norm[i] = numpy.append(norm[i],numpy.max(numpy.abs(normData)))
+          else:
+            norm[i] = numpy.append(norm[i],numpy.linalg.norm(numpy.reshape(normData,normShape[i]),normType))
+      line0 +=1
+    
+    for i in xrange(dataLength):
+      if not perLine: norm[i] = [numpy.max(norm[i]) for j in xrange(line0-len(skipLines))]
+      data[i] = numpy.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:
+          print 'At least one norm of',headings0[i]['label'],'in 1. table is 0.0, using absolute tolerance'
+        else:
+          print 'Maximum norm of',headings0[i]['label'],'in 1. table is 0.0, using absolute tolerance'
+
     line1 = 0
     while table1.data_read():                                                     # read next data line of ASCII table
-      for i in xrange(dataLength):
+      if line1 not in skipLines:
-        myData = numpy.array(map(float,table1.data[column[1][i]:\
+        for i in xrange(dataLength):
-                                                   column[1][i]+length[i]]),'d')
+          myData = numpy.array(map(float,table1.data[column[1][i]:\
-        maxError[i] = max(maxError[i],numpy.linalg.norm(numpy.reshape(myData-data[i][line1,:],shape[i])))
+                                                     column[1][i]+length[i]]),'d')
+          maxError[i] = max(maxError[i],numpy.linalg.norm(numpy.reshape(myData-data[i][line1-len(skipLines),:],shape[i]))/norm[i][line1-len(skipLines)])
       line1 +=1
 
     if (line0 != line1): raise Exception('found ', line0, ' lines in 1. table and ', line1, ' in 2. table')
 
     print ' ********'
     for i in xrange(dataLength):
-      maxError[i] = maxError[i]/maxNorm[i]
+      if absTol[i]:
-      print ' * maximum relative error ',maxError[i],' for ', headings0[i]['label'],' and ',headings1[i]['label']
+        print ' * maximum absolute error ',maxError[i],' for ', headings0[i]['label'],' and ',headings1[i]['label']
+      else:
+        print ' * maximum relative error ',maxError[i],' for ', headings0[i]['label'],' and ',headings1[i]['label']
     print ' ********'
     return maxError
-      
+    
+  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,skipLine)
+    
   def report_Success(self,culprit):
     
     if culprit < 0: