def load_imagedata(self):
try:
dir = self.shot[self.shot.index(":\\") + 2 : self.shot.rindex("\\") + 1]
shotnum = self.shot[self.shot.rindex("_") + 1 : self.shot.rindex(".ascii")]
except ValueError:
print " *** Not a valid column density path *** "
return None
# Set data path
# Prepare PlotData object
print dir
print shotnum
return load(dir, shotnum)
def load_imagedata(self):
try:
directory = self.shotdir
if self.selectedshot == []:
filename = self.shots[0]
else:
filename = self.selectedshot[0]
#shotnum = filename[filename.rindex('_')+1:filename.rindex('.ascii')]
shotnum = filename[:filename.index('_')]
except ValueError:
print " *** Not a valid path *** "
return None
# Set data path
# Prepare PlotData object
print "Loading file #%s from %s" % (filename,directory)
return import_data.load(directory,filename), import_data.load_report(directory,shotnum)
def fitfermi2d(data):
params = moments(data)
errorfunction = lambda p: ravel( numpy.vectorize(fermi2d(*p))(*indices(data.shape)) - data)
p, success = optimize.leastsq(errorfunction, params)
return p, numpy.vectorize(fermi2d(*p))(*indices(data.shape))
#def fitgaus2d(data):
# params = del moments(data)[1] #Was trying to get moments withouth the BetaMu parameter, because the gaussian fit doesn't care about the fugacity.
# errorfunction = lambda p: ravel( numpy.vectorize(gaus2d(*p))(*indices(data.shape)) - data)
# p, success = optimize.leastsq(errorfunction, params)
# return p, numpy.vectorize(fermi2d(*p))(*indices(data.shape))
if __name__ == '__main__':
#Data matrix
data = import_data.load('','6043')
data = crop(data)
print data.shape
Xin,Yin = mgrid[0:512,0:512]
t0=time.time()
#Fake result
p=[2e6, -1., 50., 100. ,256.,256., 0.5, 0.01, 0.01] #starting parameters for the fit
# atom number, BetaMu, radius along g, radius along y, center along g, center along y
#fitdata = numpy.vectorize(fermi2d(*p))(Xin, Yin)
errs=(errorfunc(data))(p)
