Shows how to calculate the SLF34 features subset using using pyslic

img2features.py

# Author: Ivan E. Cao-Berg (icaoberg@scs.cmu.edu)
#
# Copyright (C) 2012 Murphy Lab
# Lane Center for Computational Biology
# School of Computer Science
# Carnegie Mellon University
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published
# by the Free Software Foundation; either version 2 of the License,
# or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
# General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
# 02110-1301, USA.
#
# For additional information visit http://murphylab.web.cmu.edu or
# send email to murphy@cmu.edu

import Image #Python Image Library
import numpy
import pyslic

#Important info
name = 12345
scale = 0.67

#Reference Channel
dna = Image.open( "E43_dna.png" )
dna = numpy.asarray( dna )

#Protein Channel
protein = Image.open( "E43_styryl.png" )
protein = numpy.asarray( protein )

#make pyslic image container
img=pyslic.Image()
img.label = name
img.scale = scale
img.channels[ 'protein' ] = 0
img.channels[ 'dna' ] = 1
img.channeldata[ 'protein' ] = protein
img.channeldata[ 'dna' ] = dna
img.loaded = True

#SLF34
features = pyslic.computefeatures(img,'field-dna+')

#save features
numpy.save( "features.npy", features )