diff --git a/PRIVATE b/PRIVATE index 1c1e80084..bdbf2da71 160000 --- a/PRIVATE +++ b/PRIVATE @@ -1 +1 @@ -Subproject commit 1c1e8008489d81773a13a247604144a8d7ee3723 +Subproject commit bdbf2da71cd9e0825d17f673ec2fbabc2c8027f8 diff --git a/lib/damask/test/test.py b/lib/damask/test/test.py index cbf330044..341a85c97 100644 --- a/lib/damask/test/test.py +++ b/lib/damask/test/test.py @@ -109,7 +109,7 @@ class Test(): except Exception as e: logging.critical('exception during variant execution: "{}"'.format(str(e))) - return variant+1 # return culprit + return variant+1 # return culprit return 0 def feasible(self): diff --git a/processing/post/addCurl.py b/processing/post/addCurl.py index 506b14282..01499b672 100755 --- a/processing/post/addCurl.py +++ b/processing/post/addCurl.py @@ -66,7 +66,7 @@ parser.add_option('-p','--pos','--periodiccellcenter', dest = 'pos', type = 'string', metavar = 'string', help = 'label of coordinates [%default]') -parser.add_option('-d','--data', +parser.add_option('-l','--label', dest = 'data', action = 'extend', metavar = '', help = 'label(s) of field values') diff --git a/processing/post/addDivergence.py b/processing/post/addDivergence.py index 232b5bc21..d7905630e 100755 --- a/processing/post/addDivergence.py +++ b/processing/post/addDivergence.py @@ -9,36 +9,43 @@ import damask scriptName = os.path.splitext(os.path.basename(__file__))[0] scriptID = ' '.join([scriptName,damask.version]) +def merge_dicts(*dict_args): + """Given any number of dicts, shallow copy and merge into a new dict, with precedence going to key value pairs in latter dicts.""" + result = {} + for dictionary in dict_args: + result.update(dictionary) + return result + def divFFT(geomdim,field): - shapeFFT = np.array(np.shape(field))[0:3] - grid = np.array(np.shape(field)[2::-1]) - N = grid.prod() # field size - n = np.array(np.shape(field)[3:]).prod() # data size + """Calculate divergence of a vector or tensor field by transforming into Fourier space.""" + shapeFFT = np.array(np.shape(field))[0:3] + grid = np.array(np.shape(field)[2::-1]) + N = grid.prod() # field size + n = np.array(np.shape(field)[3:]).prod() # data size - if n == 3: dataType = 'vector' - elif n == 9: dataType = 'tensor' + field_fourier = np.fft.rfftn(field,axes=(0,1,2),s=shapeFFT) + div_fourier = np.empty(field_fourier.shape[0:len(np.shape(field))-1],'c16') - field_fourier = np.fft.rfftn(field,axes=(0,1,2),s=shapeFFT) - div_fourier = np.empty(field_fourier.shape[0:len(np.shape(field))-1],'c16') + # differentiation in Fourier space + TWOPIIMG = 2.0j*math.pi + einsums = { + 3:'ijkl,ijkl->ijk', # vector, 3 -> 1 + 9:'ijkm,ijklm->ijkl', # tensor, 3x3 -> 3 + } + k_sk = np.where(np.arange(grid[2])>grid[2]//2,np.arange(grid[2])-grid[2],np.arange(grid[2]))/geomdim[0] + if grid[2]%2 == 0: k_sk[grid[2]//2] = 0 # Nyquist freq=0 for even grid (Johnson, MIT, 2011) -# differentiation in Fourier space - TWOPIIMG = 2.0j*math.pi - k_sk = np.where(np.arange(grid[2])>grid[2]//2,np.arange(grid[2])-grid[2],np.arange(grid[2]))/geomdim[0] - if grid[2]%2 == 0: k_sk[grid[2]//2] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) - - k_sj = np.where(np.arange(grid[1])>grid[1]//2,np.arange(grid[1])-grid[1],np.arange(grid[1]))/geomdim[1] - if grid[1]%2 == 0: k_sj[grid[1]//2] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) + k_sj = np.where(np.arange(grid[1])>grid[1]//2,np.arange(grid[1])-grid[1],np.arange(grid[1]))/geomdim[1] + if grid[1]%2 == 0: k_sj[grid[1]//2] = 0 # Nyquist freq=0 for even grid (Johnson, MIT, 2011) - k_si = np.arange(grid[0]//2+1)/geomdim[2] - - kk, kj, ki = np.meshgrid(k_sk,k_sj,k_si,indexing = 'ij') - k_s = np.concatenate((ki[:,:,:,None],kj[:,:,:,None],kk[:,:,:,None]),axis = 3).astype('c16') - if dataType == 'tensor': # tensor, 3x3 -> 3 - div_fourier = np.einsum('ijklm,ijkm->ijkl',field_fourier,k_s)*TWOPIIMG - elif dataType == 'vector': # vector, 3 -> 1 - div_fourier = np.einsum('ijkl,ijkl->ijk',field_fourier,k_s)*TWOPIIMG - - return np.fft.irfftn(div_fourier,axes=(0,1,2),s=shapeFFT).reshape([N,n/3]) + k_si = np.arange(grid[0]//2+1)/geomdim[2] + + kk, kj, ki = np.meshgrid(k_sk,k_sj,k_si,indexing = 'ij') + k_s = np.concatenate((ki[:,:,:,None],kj[:,:,:,None],kk[:,:,:,None]),axis = 3).astype('c16') + + div_fourier = np.einsum(einsums[n],k_s,field_fourier)*TWOPIIMG + + return np.fft.irfftn(div_fourier,axes=(0,1,2),s=shapeFFT).reshape([N,n/3]) # -------------------------------------------------------------------- @@ -46,32 +53,38 @@ def divFFT(geomdim,field): # -------------------------------------------------------------------- parser = OptionParser(option_class=damask.extendableOption, usage='%prog option(s) [ASCIItable(s)]', description = """ -Add column(s) containing divergence of requested column(s). -Operates on periodic ordered three-dimensional data sets. -Deals with both vector- and tensor-valued fields. - +Add column(s) containing curl of requested column(s). +Operates on periodic ordered three-dimensional data sets +of vector and tensor fields. """, version = scriptID) parser.add_option('-p','--pos','--periodiccellcenter', dest = 'pos', type = 'string', metavar = 'string', help = 'label of coordinates [%default]') -parser.add_option('-v','--vector', - dest = 'vector', +parser.add_option('-l','--label', + dest = 'data', action = 'extend', metavar = '', - help = 'label(s) of vector field values') -parser.add_option('-t','--tensor', - dest = 'tensor', - action = 'extend', metavar = '', - help = 'label(s) of tensor field values') + help = 'label(s) of field values') parser.set_defaults(pos = 'pos', ) + (options,filenames) = parser.parse_args() -if options.vector is None and options.tensor is None: - parser.error('no data column specified.') +if options.data is None: parser.error('no data column specified.') + +# --- define possible data types ------------------------------------------------------------------- + +datatypes = { + 3: {'name': 'vector', + 'shape': [3], + }, + 9: {'name': 'tensor', + 'shape': [3,3], + }, + } # --- loop over input files ------------------------------------------------------------------------ @@ -82,30 +95,27 @@ for name in filenames: except: continue damask.util.report(scriptName,name) -# ------------------------------------------ read header ------------------------------------------ +# --- interpret header ---------------------------------------------------------------------------- table.head_read() -# ------------------------------------------ sanity checks ---------------------------------------- - - items = { - 'tensor': {'dim': 9, 'shape': [3,3], 'labels':options.tensor, 'active':[], 'column': []}, - 'vector': {'dim': 3, 'shape': [3], 'labels':options.vector, 'active':[], 'column': []}, - } - errors = [] remarks = [] - column = {} - - if table.label_dimension(options.pos) != 3: errors.append('coordinates {} are not a vector.'.format(options.pos)) - else: colCoord = table.label_index(options.pos) + errors = [] + active = [] - for type, data in items.iteritems(): - for what in (data['labels'] if data['labels'] is not None else []): - dim = table.label_dimension(what) - if dim != data['dim']: remarks.append('column {} is not a {}.'.format(what,type)) - else: - items[type]['active'].append(what) - items[type]['column'].append(table.label_index(what)) + coordDim = table.label_dimension(options.pos) + if coordDim != 3: + errors.append('coordinates "{}" must be three-dimensional.'.format(options.pos)) + else: coordCol = table.label_index(options.pos) + + for me in options.data: + dim = table.label_dimension(me) + if dim in datatypes: + active.append(merge_dicts({'label':me},datatypes[dim])) + remarks.append('differentiating {} "{}"...'.format(datatypes[dim]['name'],me)) + else: + remarks.append('skipping "{}" of dimension {}...'.format(me,dim) if dim != -1 else \ + '"{}" not found...'.format(me) ) if remarks != []: damask.util.croak(remarks) if errors != []: @@ -116,17 +126,17 @@ for name in filenames: # ------------------------------------------ assemble header -------------------------------------- table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:])) - for type, data in items.iteritems(): - for label in data['active']: - table.labels_append(['divFFT({})'.format(label) if type == 'vector' else - '{}_divFFT({})'.format(i+1,label) for i in range(data['dim']//3)]) # extend ASCII header with new labels + for data in active: + table.labels_append(['divFFT({})'.format(data['label']) if data['shape'] == [3] \ + else '{}_divFFT({})'.format(i+1,data['label']) + for i in range(np.prod(np.array(data['shape']))//3)]) # extend ASCII header with new labels table.head_write() # --------------- figure out size and grid --------------------------------------------------------- table.data_readArray() - coords = [np.unique(table.data[:,colCoord+i]) for i in range(3)] + coords = [np.unique(table.data[:,coordCol+i]) for i in range(3)] mincorner = np.array(map(min,coords)) maxcorner = np.array(map(max,coords)) grid = np.array(map(len,coords),'i') @@ -136,12 +146,11 @@ for name in filenames: # ------------------------------------------ process value field ----------------------------------- stack = [table.data] - for type, data in items.iteritems(): - for i,label in enumerate(data['active']): - # we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation - stack.append(divFFT(size[::-1], - table.data[:,data['column'][i]:data['column'][i]+data['dim']]. - reshape(grid[::-1].tolist()+data['shape']))) + for data in active: + # we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation + stack.append(divFFT(size[::-1], + table.data[:,table.label_indexrange(data['label'])]. + reshape(grid[::-1].tolist()+data['shape']))) # ------------------------------------------ output result ----------------------------------------- diff --git a/processing/post/addGradient.py b/processing/post/addGradient.py index 4b9ef5a22..5a73af3a3 100755 --- a/processing/post/addGradient.py +++ b/processing/post/addGradient.py @@ -63,7 +63,7 @@ parser.add_option('-p','--pos','--periodiccellcenter', dest = 'pos', type = 'string', metavar = 'string', help = 'label of coordinates [%default]') -parser.add_option('-d','--data', +parser.add_option('-l','--label', dest = 'data', action = 'extend', metavar = '', help = 'label(s) of field values')