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DAMASK_EICMD
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added optional weighting column

This commit is contained in:
Philip Eisenlohr 2014-07-25 16:38:04 +00:00
parent 1dba332083
commit bee6e0b09b
1 changed files with 13 additions and 7 deletions
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20
processing/post/binXY.py
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@ -39,6 +39,8 @@ Produces a binned grid of two columns from an ASCIItable, i.e. a two-dimensional
parser.add_option('-d','--data', dest='data', nargs=2, type='int',
help='columns containing x and y')
parser.add_option('-w','--weight', dest='weight', type='int',
help='column containing weight of (x,y) point')
parser.add_option('-b','--bins', dest='bins', nargs=2, type='int',
help='number of bins in x and y direction')
parser.add_option('-t','--type', dest='type', nargs=3, type='string',
@ -53,6 +55,7 @@ parser.add_option('-i','--invert', dest='invert', action='store_true',
help='invert probability density')
parser.set_defaults(data = [1,2])
parser.set_defaults(weight = None)
parser.set_defaults(bins = [10,10])
parser.set_defaults(type = ['linear','linear','linear'])
parser.set_defaults(xrange = [0.0,0.0])
@ -81,7 +84,10 @@ else:
if os.path.exists(name):
files.append({'name': name,
'input': open(name),
'output': open(os.path.splitext(name)[0]+'_binned%i-%i'%(options.data[0],options.data[1])+os.path.splitext(name)[1],'w'),
'output': open(os.path.splitext(name)[0]+ \
'_binned%i-%i'%(options.data[0],options.data[1])+ \
('_weighted%i'%(options.weight) if options.weight != None else '')+ \
os.path.splitext(name)[1],'w'),
'croak': sys.stderr,
})
@ -93,21 +99,21 @@ for file in files:
skip = int(file['input'].readline().split()[0])
for i in xrange(skip): headers = file['input'].readline().split()
data = numpy.loadtxt(file['input'],usecols=numpy.array(options.data)-1)
data = numpy.loadtxt(file['input'],usecols=numpy.array(options.data+([options.weight] if options.weight != None else [])-1))
file['input'].close() # close input ASCII table
for i in (0,1):
for i in (0,1): # check data range for x and y
if (range[i] == 0.0).all(): range[i] = [data[:,i].min(),data[:,i].max()]
if options.type[i].lower() == 'log':
data[:,i] = numpy.log(data[:,i])
range[i] = numpy.log(range[i])
if options.type[i].lower() == 'log': # if log scale
data[:,i] = numpy.log(data[:,i]) # change x,y coordinates to log
range[i] = numpy.log(range[i]) # change range to log, too
delta = range[:,1]-range[:,0]
for i in xrange(len(data)):
x = int(options.bins[0]*(data[i,0]-range[0,0])/delta[0])
y = int(options.bins[1]*(data[i,1]-range[1,0])/delta[1])
if x >=0 and x < options.bins[0] and y >= 0 and y < options.bins[1]: grid[x,y] += 1
if x >=0 and x < options.bins[0] and y >= 0 and y < options.bins[1]: grid[x,y] += 1 if options.weight == None else data[i,2]
if (range[2] == 0.0).all(): range[2] = [grid.min(),grid.max()]
if (range[2] == 0.0).all(): # no data in grid?