From a29240242b216be01fb95783325bc457e339be1f Mon Sep 17 00:00:00 2001 From: Martin Diehl Date: Wed, 12 Aug 2015 18:32:28 +0000 Subject: [PATCH] standard name for numpy is np --- lib/damask/test/test.py | 40 ++++++++++++++++++++-------------------- 1 file changed, 20 insertions(+), 20 deletions(-) diff --git a/lib/damask/test/test.py b/lib/damask/test/test.py index 0c5fa8423..1820a2d5e 100644 --- a/lib/damask/test/test.py +++ b/lib/damask/test/test.py @@ -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