started to rework test class. Martin probably needs to check and continue improving on this.
This commit is contained in:
Philip Eisenlohr
parent
cef87db699
commit
a18a1066e2
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@ -39,7 +39,7 @@ class Test():
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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 run_test.py 1285 2012-02-09 08:54:09Z MPIE\m.diehl $)',
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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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@ -153,6 +153,13 @@ class 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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'''
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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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@ -174,6 +181,22 @@ class 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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@ -241,10 +264,10 @@ class Test():
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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(File1,readonly=True)
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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(File2,readonly=True)
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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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@ -279,7 +302,7 @@ class Test():
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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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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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@ -312,9 +335,9 @@ class Test():
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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(file0,readonly=True)
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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(file1,readonly=True)
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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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@ -383,41 +406,66 @@ class Test():
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return maxError
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def compare_Table2(self,file0,file1,headings0=None,headings1=None,rtol=1e-5,atol=1e-8,threshold = -1.0,debug=False):
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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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threshold = -1.0,
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debug = False):
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'''
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compare two tables with np.allclose
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threshold can be used to ignore small values (put any negative number to disable)
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table will be row-wise normalized
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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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#http://stackoverflow.com/questions/8904694/how-to-normalize-a-2-dimensional-numpy-array-in-python-less-verbose
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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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from collections import Iterable
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if headings1 == None: headings1=headings0
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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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table0 = damask.ASCIItable(file0,readonly=True)
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table0.head_read()
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table0.data_readArray(headings0)
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row_sums0 = table0.data.sum(axis=1)*table0.data.shape[0]
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table0.data /= row_sums0[:,np.newaxis]
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if isinstance(columns, (str,int,float)): # single item --> one copy per file
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columns = [str(columns)]*len(files)
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table1 = damask.ASCIItable(file1,readonly=True)
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table1.head_read()
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table1.data_readArray(headings1)
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row_sums1 = table1.data.sum(axis=1)*table1.data.shape[0]
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table1.data /= row_sums1[:,np.newaxis]
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columns += [None]*(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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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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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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if debug:
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t0 = np.where(np.abs(table0.data)<threshold,0.0,table0.data)
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t1 = np.where(np.abs(table1.data)<threshold,0.0,table1.data)
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print np.amin(np.abs(t1)*rtol+atol-np.abs(t0-t1))
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i = np.argmin(np.abs(t1)*rtol+atol-np.abs(t0-t1))
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print t0.flatten()[i],t1.flatten()[i]
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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.head_read()
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table.data_readArray(labels)
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data.append(table.data)
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maximum += np.abs(table.data).max(axis=0)
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table.close()
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maximum /= len(tables)
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for i in xrange(len(data)):
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data[i] /= maximum
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mask = np.zeros_like(table.data,dtype='bool')
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for table in data:
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mask |= np.where(np.abs(table)<threshold) # mask out (all) tiny values
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return np.allclose(np.where(np.abs(table0.data)<threshold,0.0,table0.data),
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np.where(np.abs(table1.data)<threshold,0.0,table1.data),rtol,atol)
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allclose = True # start optimistic
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for i in xrange(1,len(data)):
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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"
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return allclose
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def compare_TableRefCur(self,headingsRef,ref,headingsCur='',cur='',normHeadings='',normType=None,\
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