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")
