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DAMASK_EICMD
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standard name for numpy is np

This commit is contained in:
Martin Diehl 2015-08-12 18:32:28 +00:00
parent cd9a802a2b
commit a29240242b
1 changed files with 20 additions and 20 deletions
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40
lib/damask/test/test.py
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@ -245,8 +245,8 @@ class Test():
def compare_Array(self,File1,File2):
import numpy
import numpy as np
logging.info('comparing\n '+File1+'\n '+File2)
table1 = damask.ASCIItable(File1,readonly=True)
table1.head_read()
@ -255,14 +255,14 @@ class Test():
table2.head_read()
len2=len(table2.info)+2
refArray = numpy.nan_to_num(numpy.genfromtxt(File1,missing_values='n/a',skip_header = len1,autostrip=True))
curArray = numpy.nan_to_num(numpy.genfromtxt(File2,missing_values='n/a',skip_header = len2,autostrip=True))
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=numpy.max(abs(refArrayNonZero[curArray.nonzero()]/curArray[curArray.nonzero()]-1.))
max_loc=numpy.argmax(abs(refArrayNonZero[curArray.nonzero()]/curArray[curArray.nonzero()]-1.))
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 %e for %e and %e\n ********'
@ -289,7 +289,7 @@ class Test():
def compare_Table(self,headings0,file0,headings1,file1,normHeadings='',normType=None,\
absoluteTolerance=False,perLine=False,skipLines=[]):
import numpy
import numpy as np
logging.info('comparing ASCII Tables\n %s \n %s'%(file0,file1))
if normHeadings == '': normHeadings = headings0
@ -311,17 +311,17 @@ class Test():
if headings0[i]['shape'] != headings1[i]['shape']:
raise Exception('shape mismatch when comparing %s with %s '%(headings0[i]['label'],headings1[i]['label']))
shape[i] = headings0[i]['shape']
for j in xrange(numpy.shape(shape[i])[0]):
for j in xrange(np.shape(shape[i])[0]):
length[i] *= shape[i][j]
normShape[i] = normHeadings[i]['shape']
for j in xrange(numpy.shape(normShape[i])[0]):
for j in xrange(np.shape(normShape[i])[0]):
normLength[i] *= normShape[i][j]
else:
raise Exception('trying to compare %i with %i normed by %i data sets'%(len(headings0),len(headings1),len(normHeadings)))
table0 = damask.ASCIItable(file0)
table0 = damask.ASCIItable(file0,readonly=True)
table0.head_read()
table1 = damask.ASCIItable(file1)
table1 = damask.ASCIItable(file1,readonly=True)
table1.head_read()
for i in xrange(dataLength):
@ -346,20 +346,20 @@ class Test():
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]:\
myData = np.array(map(float,table0.data[column[0][i]:\
column[0][i]+length[i]]),'d')
normData = numpy.array(map(float,table0.data[normColumn[i]:\
normData = np.array(map(float,table0.data[normColumn[i]:\
normColumn[i]+normLength[i]]),'d')
data[i] = numpy.append(data[i],numpy.reshape(myData,shape[i]))
data[i] = np.append(data[i],np.reshape(myData,shape[i]))
if normType == 'pInf':
norm[i] = numpy.append(norm[i],numpy.max(numpy.abs(normData)))
norm[i] = np.append(norm[i],np.max(np.abs(normData)))
else:
norm[i] = numpy.append(norm[i],numpy.linalg.norm(numpy.reshape(normData,normShape[i]),normType))
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] = [numpy.max(norm[i]) for j in xrange(line0-len(skipLines))]
data[i] = numpy.reshape(data[i],[line0-len(skipLines),length[i]])
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
@ -372,9 +372,9 @@ class Test():
while table1.data_read(): # read next data line of ASCII table
if line1 not in skipLines:
for i in xrange(dataLength):
myData = numpy.array(map(float,table1.data[column[1][i]:\
myData = np.array(map(float,table1.data[column[1][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]))/
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