118 lines
5.0 KiB
Python
118 lines
5.0 KiB
Python
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#!/usr/bin/env python
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import os,sys,string,numpy
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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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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
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Produces a binned grid of two columns from an ASCIItable, i.e. a two-dimensional probability density map.
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""" + string.replace('$Id: addCalculation.py 1355 2012-02-23 13:53:12Z MPIE\p.eisenlohr $','\n','\\n')
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)
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parser.add_option('-d','--data', dest='data', nargs=2, type='int', \
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help='columns containing x and y')
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parser.add_option('-b','--bins', dest='bins', nargs=2, type='int', \
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help='number of bins in x and y direction')
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parser.add_option('-t','--type', dest='type', nargs=3, type='string', \
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help='type of x, y, and z axis [linear]')
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parser.add_option('-x','--xrange', dest='xrange', nargs=2, type='float', \
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help='value range in x direction [auto]')
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parser.add_option('-y','--yrange', dest='yrange', nargs=2, type='float', \
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help='value range in y direction [auto]')
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parser.add_option('-z','--zrange', dest='zrange', nargs=2, type='float', \
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help='value range in z direction [auto]')
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parser.set_defaults(data = [1,2])
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parser.set_defaults(bins = [10,10])
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parser.set_defaults(type = ['linear','linear','linear'])
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parser.set_defaults(xrange = [0.0,0.0])
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parser.set_defaults(yrange = [0.0,0.0])
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parser.set_defaults(zrange = [0.0,0.0])
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(options,filenames) = parser.parse_args()
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range = numpy.array([numpy.array(options.xrange),
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numpy.array(options.yrange),
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numpy.array(options.zrange)])
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grid = numpy.zeros(options.bins,'i')
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result = numpy.zeros((options.bins[0]*options.bins[1],3),'f')
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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', 'input':sys.stdin, 'output':sys.stdout})
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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, 'input':open(name), 'output':open(os.path.splitext(name)[0]+'_binned'+os.path.splitext(name)[1],'w')})
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# ------------------------------------------ loop over input files ---------------------------------------
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for file in files:
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if file['name'] != 'STDIN': print file['name']
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skip = int(file['input'].readline().split()[0])
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print skip
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for i in xrange(skip): headers = file['input'].readline().split()
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print headers
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data = numpy.loadtxt(file['input'],usecols=numpy.array(options.data)-1)
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file['input'].close() # close input ASCII table
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for i in (0,1):
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if (range[i] == 0.0).all(): range[i] = [data[:,i].min(),data[:,i].max()]
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if options.type[i].lower() == 'log':
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data[:,i] = numpy.log(data[:,i])
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range[i] = numpy.log(range[i])
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delta = range[:,1]-range[:,0]
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for i in xrange(len(data)):
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x = int(options.bins[0]*(data[i,0]-range[0,0])/delta[0])
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y = int(options.bins[1]*(data[i,1]-range[1,0])/delta[1])
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if x >=0 and x < options.bins[0] and y >= 0 and y < options.bins[1]: grid[x,y] += 1
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if (range[2] == 0.0).all(): range[2] = [grid.min(),grid.max()]
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if options.type[2].lower() == 'log':
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grid = numpy.log(grid)
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range[2] = numpy.log(range[2])
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delta[2] = range[2,1]-range[2,0]
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i = 0
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for x in xrange(options.bins[0]):
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for y in xrange(options.bins[1]):
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result[i,:] = [range[0,0]+delta[0]/options.bins[0]*(x+0.5),\
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range[1,0]+delta[1]/options.bins[1]*(y+0.5),\
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min(1.0,max(0.0,(grid[x,y]-range[2,0])/delta[2]))]
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if options.type[0].lower() == 'log': result[i,0] = numpy.exp(result[i,0])
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if options.type[1].lower() == 'log': result[i,1] = numpy.exp(result[i,1])
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i += 1
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file['output'].write('1\thead\n')
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file['output'].write('bin_%s\tbin_%s\tz\n'%(headers[options.data[0]-1],headers[options.data[1]-1]))
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numpy.savetxt(file['output'],result)
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file['output'].close() # close output ASCII table
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