222 lines
8.5 KiB
Plaintext
222 lines
8.5 KiB
Plaintext
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#!/usr/bin/python
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import os,re,sys,math,string
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from optparse import OptionParser, Option
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# -----------------------------
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class extendableOption(Option):
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# -----------------------------
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# used for definition of new option parser action 'extend', which enables to take multiple option arguments
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# taken from online tutorial http://docs.python.org/library/optparse.html
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ACTIONS = Option.ACTIONS + ("extend",)
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STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
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TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
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ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)
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def take_action(self, action, dest, opt, value, values, parser):
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if action == "extend":
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lvalue = value.split(",")
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values.ensure_value(dest, []).extend(lvalue)
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else:
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Option.take_action(self, action, dest, opt, value, values, parser)
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def location(idx,res):
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return ( idx % res[0], \
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(idx // res[0]) % res[1], \
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(idx // res[0] // res[1]) % res[2] )
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def index(location,res):
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return ( location[0] % res[0] + \
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(location[1] % res[1]) * res[0] + \
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(location[2] % res[2]) * res[0] * res[1] )
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def prefixMultiply(what,len):
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return {True: ['%i_%s'%(i+1,what) for i in range(len)],
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False:[what]}[len>1]
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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FDcoefficients = [ \
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[1.0/2.0, 0.0, 0.0, 0.0],\
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[2.0/3.0,-1.0/12.0, 0.0, 0.0],\
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[3.0/4.0,-3.0/20.0,1.0/ 60.0, 0.0],\
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[4.0/5.0,-1.0/ 5.0,4.0/105.0,-1.0/280.0],\
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]
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parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
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Add column(s) containing divergence of requested column(s).
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Operates on periodic ordered three-dimensional data sets.
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Deals with both vector- and tensor-valued fields.
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$Id: addDivergence 264 2011-05-25 17:43:45Z MPIE\p.eisenlohr $
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""")
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parser.add_option('-a','--accuracy', dest='accuracy', type='int', \
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help='degree of central difference accuracy [%default]')
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parser.add_option('-v','--vector', dest='vector', action='extend', type='string', \
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help='heading of columns containing vector field values')
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parser.add_option('-t','--tensor', dest='tensor', action='extend', type='string', \
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help='heading of columns containing tensor field values')
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parser.add_option('-d','--dimension', dest='dim', type='float', nargs=3, \
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help='physical dimension of data set in x (fast) y z (slow) [%default]')
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parser.add_option('-r','--resolution', dest='res', type='int', nargs=3, \
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help='resolution of data set in x (fast) y z (slow)')
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parser.set_defaults(accuracy = 8)
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parser.set_defaults(vector = [])
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parser.set_defaults(tensor = [])
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parser.set_defaults(dim = [1.0,1.0,1.0])
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accuracyChoices = [2,4,6,8]
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(options,filenames) = parser.parse_args()
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if len(options.vector) + len(options.tensor) == 0:
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parser.error('no data column specified...')
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if len(options.dim) < 3:
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parser.error('improper dimension specification...')
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if not options.res or len(options.res) < 3:
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parser.error('improper resolution specification...')
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if options.accuracy not in accuracyChoices:
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parser.error('accuracy must be chosen from %s...'%(', '.join(accuracyChoices)))
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accuracy = options.accuracy//2-1
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datainfo = { # list of requested labels per datatype
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'vector': {'len':3,
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'label':[]},
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'tensor': {'len':9,
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'label':[]},
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}
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if options.vector != None: datainfo['vector']['label'] += options.vector
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if options.tensor != None: datainfo['tensor']['label'] += options.tensor
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# ------------------------------------------ setup file handles ---------------------------------------
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files = []
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if filenames == []:
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files.append({'name':'STDIN', 'handle':sys.stdin})
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else:
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for name in filenames:
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if os.path.exists(name):
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files.append({'name':name, 'handle':open(name)})
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# ------------------------------------------ loop over input files ---------------------------------------
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for file in files:
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print file['name']
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content = file['handle'].readlines()
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file['handle'].close()
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# get labels by either read the first row, or - if keyword header is present - the last line of the header
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headerlines = 1
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m = re.search('(\d+)\s*head', content[0].lower())
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if m:
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headerlines = int(m.group(1))
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passOn = content[1:headerlines]
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headers = content[headerlines].split()
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data = content[headerlines+1:]
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regexp = re.compile('1_\d+_')
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for i,l in enumerate(headers):
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if regexp.match(l):
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headers[i] = l[2:]
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active = {}
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column = {}
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values = {}
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head = []
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for datatype,info in datainfo.items():
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for label in info['label']:
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key = {True :'1_%s',
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False:'%s' }[info['len']>1]%label
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if key not in headers:
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print 'column %s not found...'%key
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else:
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if datatype not in active: active[datatype] = []
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if datatype not in column: column[datatype] = {}
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if datatype not in values: values[datatype] = {}
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active[datatype].append(label)
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column[datatype][label] = headers.index(key)
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values[datatype][label] = [[0.0 for i in range(datainfo[datatype]['len'])] \
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for j in range(options.res[0]*options.res[1]*options.res[2])]
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head += prefixMultiply('div%i(%s)'%(options.accuracy,label),datainfo[datatype]['len']/3)
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# ------------------------------------------ assemble header ---------------------------------------
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output = '%i\theader'%(headerlines+1) + '\n' + \
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''.join(passOn) + \
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string.replace('$Id: addDivergence 264 2011-05-25 17:43:45Z MPIE\p.eisenlohr $','\n','\\n')+ '\t' + \
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' '.join(sys.argv[1:]) + '\n' + \
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'\t'.join(headers + head) + '\n' # build extended header
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# ------------------------------------------ read value field ---------------------------------------
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idx = 0
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for line in data:
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items = line.split()[:len(headers)]
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if len(items) < len(headers):
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continue
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for datatype,labels in active.items():
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for label in labels:
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values[datatype][label][idx] = map(float,items[column[datatype][label]:
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column[datatype][label]+datainfo[datatype]['len']])
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idx += 1
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# ------------------------------------------ read file ---------------------------------------
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idx = 0
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for line in data:
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items = line.split()[:len(headers)]
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if len(items) < len(headers):
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continue
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output += '\t'.join(items)
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(x,y,z) = location(idx,options.res)
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for datatype,labels in active.items():
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for label in labels:
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for k in range(datainfo[datatype]['len']/3): # formulas from Mikhail Itskov: Tensor Algebra and Tensor Analysis for Engineers, Springer 2009, p 52
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theDiv = 0.0
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for a in range(1+accuracy):
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theDiv += FDcoefficients[accuracy][a] * \
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( \
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(values[datatype][label][index([x+1+a,y,z],options.res)][k*3+0] - \
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values[datatype][label][index([x-1-a,y,z],options.res)][k*3+0]) * options.res[0] / options.dim[0] + \
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(values[datatype][label][index([x,y+1+a,z],options.res)][k*3+1] - \
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values[datatype][label][index([x,y-1-a,z],options.res)][k*3+1]) * options.res[1] / options.dim[1] + \
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(values[datatype][label][index([x,y,z+1+a],options.res)][k*3+2] - \
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values[datatype][label][index([x,y,z-1-a],options.res)][k*3+2]) * options.res[2] / options.dim[2] \
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)
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output += '\t%f'%theDiv
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output += '\n'
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idx += 1
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# ------------------------------------------ output result ---------------------------------------
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if file['name'] == 'STDIN':
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print output
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else:
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file['handle'] = open(file['name']+'_tmp','w')
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try:
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file['handle'].write(output)
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file['handle'].close()
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os.rename(file['name']+'_tmp',file['name'])
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except:
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print 'error during writing',file['name']+'_tmp'
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