DAMASK_EICMD/processing/post/imageData.py

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