DAMASK_EICMD/processing/post/binXY.py

123 lines
5.3 KiB
Python
Executable File

#!/usr/bin/env python
# -*- coding: UTF-8 no BOM -*-
import os,sys,string,numpy
from optparse import OptionParser, Option
# -----------------------------
class extendableOption(Option):
# -----------------------------
# used for definition of new option parser action 'extend', which enables to take multiple option arguments
# taken from online tutorial http://docs.python.org/library/optparse.html
ACTIONS = Option.ACTIONS + ("extend",)
STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)
def take_action(self, action, dest, opt, value, values, parser):
if action == "extend":
lvalue = value.split(",")
values.ensure_value(dest, []).extend(lvalue)
else:
Option.take_action(self, action, dest, opt, value, values, parser)
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
Produces a binned grid of two columns from an ASCIItable, i.e. a two-dimensional probability density map.
""" + string.replace('$Id$','\n','\\n')
)
parser.add_option('-d','--data', dest='data', nargs=2, type='int',
help='columns containing x and y')
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',
help='type of x, y, and z axis [linear]')
parser.add_option('-x','--xrange', dest='xrange', nargs=2, type='float',
help='value range in x direction [auto]')
parser.add_option('-y','--yrange', dest='yrange', nargs=2, type='float',
help='value range in y direction [auto]')
parser.add_option('-z','--zrange', dest='zrange', nargs=2, type='float',
help='value range in z direction [auto]')
parser.add_option('-i','--invert', dest='invert', action='store_true',
help='invert probability density')
parser.set_defaults(data = [1,2])
parser.set_defaults(bins = [10,10])
parser.set_defaults(type = ['linear','linear','linear'])
parser.set_defaults(xrange = [0.0,0.0])
parser.set_defaults(yrange = [0.0,0.0])
parser.set_defaults(zrange = [0.0,0.0])
parser.set_defaults(invert = False)
(options,filenames) = parser.parse_args()
range = numpy.array([numpy.array(options.xrange),
numpy.array(options.yrange),
numpy.array(options.zrange)])
grid = numpy.zeros(options.bins,'i')
result = numpy.zeros((options.bins[0]*options.bins[1],3),'f')
# ------------------------------------------ setup file handles ---------------------------------------
files = []
if filenames == []:
files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout})
else:
for name in filenames:
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')})
# ------------------------------------------ loop over input files ---------------------------------------
for file in files:
if file['name'] != 'STDIN': print file['name']
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)
file['input'].close() # close input ASCII table
for i in (0,1):
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])
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 (range[2] == 0.0).all(): range[2] = [grid.min(),grid.max()]
if options.type[2].lower() == 'log':
grid = numpy.log(grid)
range[2] = numpy.log(range[2])
delta[2] = range[2,1]-range[2,0]
i = 0
for x in xrange(options.bins[0]):
for y in xrange(options.bins[1]):
result[i,:] = [range[0,0]+delta[0]/options.bins[0]*(x+0.5),\
range[1,0]+delta[1]/options.bins[1]*(y+0.5),\
min(1.0,max(0.0,(grid[x,y]-range[2,0])/delta[2]))]
if options.type[0].lower() == 'log': result[i,0] = numpy.exp(result[i,0])
if options.type[1].lower() == 'log': result[i,1] = numpy.exp(result[i,1])
if options.invert: result[i,2] = 1.0-result[i,2]
i += 1
file['output'].write('1\thead\n')
file['output'].write('bin_%s\tbin_%s\tz\n'%(headers[options.data[0]-1],headers[options.data[1]-1]))
numpy.savetxt(file['output'],result)
file['output'].close() # close output ASCII table