def makeVaricData_PF(i,l,s):
'''Input:
l[0] is a tuple (length, id)
Output:
If there is not a file
Length.Id.10.all.l.mat in /rigs/gic/aff, creates this
file, containing a matlab array named affdata
returns [filename]
'''
sfn="/rigs/gic/aff/%s.%i.10.all.l.xml" % (l[0][0], l[0][1])
tfn="/rigs/gic/aff/%s.%i.10.all.l.mat" % (l[0][0], l[0][1])
modfn="/rigs/gic/aff/%s.%i.10.all.l_model.mat" % (l[0][0], l[0][1])
if os.path.isfile(modfn):
s["Abort"]=True
return [modfn]
if not os.path.isfile(sfn):
s["Abort"]=True
return ["no data"]
import mien.nmpml
from mien.datafiles.filewriters import hash2mat
doc=mien.nmpml.readXML(sfn)
pts=None
for f in doc.getElements("Fiducial"):
npts=f.points
if pts==None:
pts=npts[:,:4]
else:
pts=concatenate([pts, npts[:,:4]])
hash2mat(tfn, {"affdata":pts})
print "writing %s" % tfn
return [tfn]
def normalizeAll(fns):
nmax=float(fns[0])
a=matArray(fns[1])
nfn=os.path.splitext(fns[1])[0]+'.normi%.4f.mat' % nmax
omax=a.sum()
a=a*nmax/omax
hash2mat(nfn, {"density":a})
def subtractFiles(fns):
efn=fns[0]
if os.path.exists(efn):
print "Refusing to overwrite %s" % efn
exit()
a=matArray(fns[1])
b=matArray(fns[2])
a=a-b
a=maximum(a, zeros(a.shape))
hash2mat(efn, {"density":a})
def addFiles(fns):
efn=fns[0]
if os.path.exists(efn):
print "Refusing to overwrite %s" % efn
exit()
a=matArray(fns[1])
for fn in fns[2:]:
b=matArray(fn)
a=a+b
hash2mat(efn, {"density":a})
def makeEstimate(files):
efn=files[0]
if os.path.exists(efn):
print "Refusing to overwrite %s" % efn
exit()
if files[1].endswith('.mat'):
fc=readmat(files[1])
dat=fc[-1]["affdata"]
else:
dat=getVaricosities(files[1:])
est=densityEstimate(dat)
hash2mat(efn, {"density":est})
def writeMatFile(files):
if os.path.exists(files[0]):
print "Refusing to overwrite %s" % files[0]
exit()
pts=getVaricosities(files[1:])
hash2mat(files[0], {"affdata":pts})
