def analyze_path( shot , args): atoms, noatoms = importfits(shot) out = atoms-noatoms shotnum = '%04d' % int(shot) if args.stats: analyze_stats( out, args.stats) try: CX = float(args.c.split(',')[0]) CY = float(args.c.split(',')[1]) args.Ccts = out[CY,CX] hs = args.size / 2 off = 0 out = out[ CY-hs-off:CY+hs-off, CX-hs-off:CX+hs-off ] args.X0 = CX-hs-off args.Y0 = CY-hs-off args.CX = CX args.CY = CY except: print "...Could not crop to specified center and size" print "... c = (%s), size = %d" % (args.c, args.size) exit(1) #All cropped data is saved in the data dir for averaging use numpy.savetxt(shot+'_bragg.dat', out, fmt='%d') #Results center = (CX,CY) inifile = "report" + shotnum + ".INI" report = ConfigObj(inifile) report['BRAGG'] = {} for boxsize in (2. ,4., 6., 8.): r = get_counts(out, args, boxsize) for key in r.keys(): report['BRAGG'][key] = r[key] report.write() if not os.path.exists(args.path): os.makedirs(args.path) pngprefix = args.path + shotnum + '_bragg' falsecolor.inspecpng( [out], \ r['row'], r['col'], out.min(), out.max(), \ falsecolor.my_grayscale, \ pngprefix, 100, origin = 'lower' , \ step=True, scale=10, \ interpolation='nearest', \ extratext='') return
#!/usr/bin/python import sys from numpy import loadtxt import falsecolor if __name__ == "__main__": # This program should be called as # inspect2d_ascii.py data.ascii fit.ascii inspec_row inspec_col prefix data = loadtxt(sys.argv[1]) fit = loadtxt(sys.argv[2]) row = sys.argv[3] col = sys.argv[4] prefix = sys.argv[5] falsecolor.inspecpng( [data, fit], row, col, data.min(), data.max(), \ falsecolor.my_rainbow, prefix, 100, origin = 'lower' )
import sys from numpy import loadtxt import falsecolor from matplotlib import cm if __name__ == "__main__": # This program should be called as # inspect2d_ascii.py data.ascii,fit1.ascii,fit2.ascii,fit3.ascii,... inspec_row inspec_col prefix list = sys.argv[1].split(',') imgs =[] for file in list: imgs.append( loadtxt (file) ) row = sys.argv[2] col = sys.argv[3] prefix = sys.argv[4] #colormap = falsecolor.my_rainbow colormap = cm.spectral falsecolor.inspecpng( imgs, row, col, imgs[0].min(), imgs[0].max(), \ colormap, prefix+'_multi', 100, origin = 'upper' )
#!/usr/bin/python import sys from numpy import loadtxt import falsecolor from matplotlib import cm if __name__ == "__main__": # This program should be called as # inspect2d_ascii.py data.ascii fit.ascii inspec_row inspec_col prefix data = loadtxt(sys.argv[1]) fit = loadtxt(sys.argv[2]) row = sys.argv[3] col = sys.argv[4] prefix = sys.argv[5] #colormap = falsecolor.my_rainbow colormap = cm.spectral falsecolor.inspecpng( [data, fit], row, col, data.min(), data.max(), \ colormap, prefix, 100, origin = 'lower' )
#!/usr/bin/python import sys from numpy import loadtxt import falsecolor from matplotlib import cm if __name__ == "__main__": # This program should be called as # inspect2d_ascii.py data.ascii,fit1.ascii,fit2.ascii,fit3.ascii,... inspec_row inspec_col prefix list = sys.argv[1].split(',') imgs = [] for file in list: imgs.append(loadtxt(file)) row = sys.argv[2] col = sys.argv[3] prefix = sys.argv[4] #colormap = falsecolor.my_rainbow colormap = cm.spectral falsecolor.inspecpng( imgs, row, col, imgs[0].min(), imgs[0].max(), \ colormap, prefix+'_multi', 100, origin = 'upper' )
def analyze_path( mantapath , args): shotnum = os.path.basename( mantapath ).split('atoms.manta')[0] shotnum = "%04d" % int(shotnum) print "\n%s" % shotnum, atomsfile = shotnum + 'atoms.manta' shot = atomsfile.split('atoms')[0] atoms = numpy.loadtxt( shot + 'atoms.manta') noatoms = numpy.loadtxt( shot + 'noatoms.manta') #atomsref = numpy.loadtxt( shot + 'atomsref.manta') #noatomsref= numpy.loadtxt( shot + 'noatomsref.manta') operation = 'PHC' try: if operation == 'ABS': out = (atoms - atomsref) / (noatoms - noatomsref) elif operation == 'PHC': out = atoms - noatoms #out = (atoms - atomsref) - (noatoms - noatomsref) else: print " --> Operation is not ABS or PHC. Program will exit" exit(1) except: print "...ERROR performing background and reference subtraction" return try: CX = float(args.c.split(',')[0]) CY = float(args.c.split(',')[1]) args.Ccts = out[CY,CX] hs = args.size / 2 off = 0 out = out[ CY-hs-off:CY+hs-off, CX-hs-off:CX+hs-off ] args.X0 = CX-hs-off args.Y0 = CY-hs-off args.CX = CX args.CY = CY except: print "...Could not crop to specified center and size" print "... c = (%s), size = %d" % (args.c, args.size) exit(1) #All cropped data is saved in the data dir for averaging use numpy.savetxt(shot+'_bragg.dat', out, fmt='%d') #Results center = (CX,CY) inifile = "report" + shotnum + ".INI" report = ConfigObj(inifile) report['BRAGG'] = {} for boxsize in (2. ,4., 6., 8.): r = get_counts(out, args, boxsize) for key in r.keys(): report['BRAGG'][key] = r[key] report.write() if not os.path.exists(args.path): os.makedirs(args.path) pngprefix = args.path + shotnum + '_bragg' falsecolor.inspecpng( [out], \ r['row'], r['col'], out.min(), out.max(), \ falsecolor.my_grayscale, \ pngprefix, 100, origin = 'upper' , \ step=True, scale=10, \ interpolation='nearest', \ extratext='') return
#!/usr/bin/python import sys from numpy import loadtxt import falsecolor from matplotlib import cm if __name__ == "__main__": # This program should be called as # inspect2d_ascii.py data.ascii fit.ascii inspec_row inspec_col prefix data = loadtxt(sys.argv[1]) fit = loadtxt(sys.argv[2]) row = sys.argv[3] col = sys.argv[4] prefix = sys.argv[5] # colormap = falsecolor.my_rainbow colormap = cm.spectral falsecolor.inspecpng([data, fit], row, col, data.min(), data.max(), colormap, prefix, 100, origin="lower")