185 lines
7.6 KiB
Python
Executable File
185 lines
7.6 KiB
Python
Executable File
#!/usr/bin/env python
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# -*- coding: UTF-8 no BOM -*-
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import os,sys,string
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import numpy as np
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from optparse import OptionParser
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from PIL import Image, ImageDraw, ImageOps
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import damask
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scriptID = string.replace('$Id$','\n','\\n')
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scriptName = os.path.splitext(scriptID.split()[1])[0]
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
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Generate PNG image from data in given column (or 2D data of overall table).
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""", version = scriptID)
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parser.add_option('-l','--label',
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dest = 'label',
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type = 'string', metavar = 'string',
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help = 'column containing data [all]')
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parser.add_option('-r','--range',
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dest = 'range',
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type = 'float', nargs = 2, metavar = 'float float',
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help = 'data range (min max) [auto]')
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parser.add_option('--gap', '--transparent',
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dest = 'gap',
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type = 'float', metavar = 'float',
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help = 'value to treat as transparent [%default]')
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parser.add_option('-d','--dimension',
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dest = 'dimension',
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type = 'int', nargs = 2, metavar = 'int int',
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help = 'data dimension (width height) [native]')
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parser.add_option('--color',
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dest = 'color',
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type = 'string', metavar = 'string',
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help = 'color scheme [%default]')
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parser.add_option('--invert',
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dest = 'invert',
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action = 'store_true',
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help = 'invert color scheme')
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parser.add_option('--abs',
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dest = 'abs',
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action = 'store_true',
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help = 'magnitude of values')
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parser.add_option('--log',
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dest = 'log',
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action = 'store_true',
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help = 'log10 of values')
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parser.add_option('--fliplr',
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dest = 'flipLR',
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action = 'store_true',
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help = 'flip around vertical axis')
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parser.add_option('--flipud',
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dest = 'flipUD',
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action = 'store_true',
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help = 'flip around horizontal axis')
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parser.add_option('--crop',
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dest = 'crop',
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type = 'int', nargs = 4, metavar = 'int int int int',
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help = 'pixels cropped on left, right, top, bottom')
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parser.add_option('-N','--pixelsize',
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dest = 'pixelsize',
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type = 'int', metavar = 'int',
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help = 'pixel per data point')
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parser.add_option('-x','--pixelsizex',
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dest = 'pixelsizex',
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type = 'int', metavar = 'int',
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help = 'pixel per data point along x')
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parser.add_option('-y','--pixelsizey',
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dest = 'pixelsizey',
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type = 'int', metavar = 'int',
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help = 'pixel per data point along y')
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parser.add_option('--show',
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dest = 'show',
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action = 'store_true',
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help = 'show resulting image')
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parser.set_defaults(label = None,
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range = [0.0,0.0],
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gap = None,
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dimension = [],
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abs = False,
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log = False,
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flipLR = False,
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flipUD = False,
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color = "gray",
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invert = False,
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crop = [0,0,0,0],
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pixelsize = 1,
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pixelsizex = 1,
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pixelsizey = 1,
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show = False,
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)
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(options,filenames) = parser.parse_args()
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if options.pixelsize > 1: (options.pixelsizex,options.pixelsizey) = [options.pixelsize]*2
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# --- color palette ---------------------------------------------------------------------------------
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theMap = damask.Colormap(predefined = options.color)
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if options.invert: theMap = theMap.invert()
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theColors = np.uint8(np.array(theMap.export(format = 'list',steps = 256))*255)
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# --- loop over input files -------------------------------------------------------------------------
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if filenames == []: filenames = [None]
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for name in filenames:
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try:
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table = damask.ASCIItable(name = name,
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buffered = False,
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labeled = options.label != None,
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readonly = True)
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except: continue
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table.croak('\033[1m'+scriptName+'\033[0m'+(': '+name if name else ''))
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# ------------------------------------------ read header ------------------------------------------
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table.head_read()
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# ------------------------------------------ process data ------------------------------------------
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missing_labels = table.data_readArray(options.label)
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if len(missing_labels) > 0:
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table.croak('column {} not found.'.format(options.label))
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table.close(dismiss = True) # close ASCIItable and remove empty file
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continue
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# convert data to values between 0 and 1 and arrange according to given options
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if options.dimension != []: table.data = table.data.reshape(options.dimension[1],options.dimension[0])
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if options.abs: table.data = np.abs(table.data)
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if options.log: table.data = np.log10(table.data);options.range = np.log10(options.range)
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if options.flipLR: table.data = np.fliplr(table.data)
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if options.flipUD: table.data = np.flipud(table.data)
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mask = np.where(table.data != options.gap,True,False) if options.gap != None else np.ones_like(table.data,dtype = 'bool')
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if np.all(np.array(options.range) == 0.0):
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options.range = [table.data[mask].min(),
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table.data[mask].max()]
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table.croak('data range: {0} – {1}'.format(*options.range))
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delta = max(options.range) - min(options.range)
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avg = 0.5*(max(options.range) + min(options.range))
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if delta * 1e8 <= avg: # delta around numerical noise
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options.range = [min(options.range) - 0.5*avg, max(options.range) + 0.5*avg] # extend range to have actual data centered within
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table.data = (table.data - min(options.range)) / \
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(max(options.range) - min(options.range))
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table.data = np.clip(table.data,0.0,1.0).\
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repeat(options.pixelsizex,axis = 1).\
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repeat(options.pixelsizey,axis = 0)
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mask = mask.\
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repeat(options.pixelsizex,axis = 1).\
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repeat(options.pixelsizey,axis = 0)
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(height,width) = table.data.shape
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table.croak('image dimension: {0} x {1}'.format(width,height))
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im = Image.fromarray(np.dstack((theColors[np.array(255*table.data,dtype = np.uint8)],
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255*mask.astype(np.uint8))), 'RGBA').\
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crop(( options.crop[0],
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options.crop[2],
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width -options.crop[1],
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height-options.crop[3]))
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# ------------------------------------------ output result -----------------------------------------
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im.save(sys.stdout if name else
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os.path.splitext(name)[0]+ \
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('' if options.label == None else '_'+options.label)+ \
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'.png',
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format = "PNG")
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table.close() # close ASCII table
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if options.show: im.show()
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