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map2img.py
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Fri, Jun 28, 20:43

map2img.py
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#!/usr/bin/env python
import sys
import numpy
import pylab
import Image
import fortranfile
from optparse import OptionParser
def main():
# Parse command line arguments
parser = OptionParser()
parser.usage = "%prog [options] map_file"
parser.add_option('-l','--logscale',dest='logscale', action='store_true', \
help='use log color scaling', default=False)
parser.add_option("-o","--output", dest="outfile", metavar="FILE", \
help='output image file [default: <map_file>.png]', default=None)
parser.add_option("-m","--min", dest="min", metavar="VALUE", \
help='min value', default=None)
parser.add_option("-M","--max", dest="max", metavar="VALUE", \
help='max value', default=None)
parser.add_option('-a','--autorange',dest='autorange', action='store_true', \
help='use automatic dynamic range (overrides min & max)', default=False)
parser.add_option('--big-endian',dest='big_endian', action='store_true', \
help='input binary data is stored as big endian', default=False)
parser.add_option('-c','--colormap',dest='cmap_str', metavar='CMAP', \
help='matplotlib color map to use', default="jet")
(opts,args)=parser.parse_args()
# Parse input and output
try:
infile = args[0]
except:
print parser.print_help()
return 1
if(opts.outfile==None):
outfile=infile+'.tif'
else:
outfile=opts.outfile
# Endianness
if(opts.big_endian):
endianness = ">"
else:
endianness = "="
# Read image data
print "Reading raw Fortran data..."
f = fortranfile.FortranFile(infile)
[nx,ny] = f.read_fortran_record('i4', endian=endianness)
dat = f.read_fortran_record('f4', endian=endianness)
f.close()
if(opts.logscale):
dat = numpy.array(dat)+1e-12
rawmin = numpy.amin(dat)
rawmax = numpy.amax(dat)
print ' Image map size : ',(nx, ny)
print ' Data bounds : ',(rawmin,rawmax)
print "Scaling data and processing colormap..."
# Bounds
if opts.min==None:
plotmin = rawmin
else:
plotmin = float(opts.min)
if opts.max==None:
plotmax = rawmax
else:
plotmax = float(opts.max)
# Log scale?
if(opts.logscale):
dat = numpy.log10(dat)
rawmin = numpy.log10(rawmin)
rawmax = numpy.log10(rawmax)
plotmin = numpy.log10(plotmin)
plotmax = numpy.log10(plotmax)
# Auto-adjust dynamic range?
if(opts.autorange):
print "Computing dynamic range..."
# Overrides any provided bounds
NBINS = 200
# Compute histogram
(hist,bins) = numpy.histogram(dat, NBINS, (rawmin,rawmax), normed=True)
chist = numpy.cumsum(hist); chist = chist / numpy.amax(chist)
# Compute black and white point
clip_k = chist.searchsorted(0.05)
plotmin = bins[clip_k]
plotmax = rawmax
if(plotmax-plotmin>0):
dat = numpy.clip((dat-plotmin)/(plotmax-plotmin), 0.0, 1.0)
else:
dat = 0.5*dat/plotmax
if(opts.logscale):
print ' Color bounds : ',(10**plotmin,10**plotmax)
else:
print ' Color bounds : ',(plotmin,plotmax)
# Apply chosen color map
color_map = pylab.cm.get_cmap(opts.cmap_str)
dat = color_map(dat)*255
# Convert to int
dat = numpy.array(dat, dtype='i')
# Output to file
print "Saving image to file..."
R_band = Image.new("L",(nx,ny))
R_band.putdata(dat[:,0])
G_band = Image.new("L",(nx,ny))
G_band.putdata(dat[:,1])
B_band = Image.new("L",(nx,ny))
B_band.putdata(dat[:,2])
out_img = Image.merge("RGB", (R_band, G_band, B_band)).transpose(Image.FLIP_TOP_BOTTOM)
out_img.save(outfile)
if __name__ == '__main__':
main()

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