def elastic_chi(val,fresco,data,pot,term,var):
for i,j in zip(var,val):
fresco.change_pot(pot,term,i,str(j)) #Change potentials
fresco.update_all()
fresco.write('new_input')
fc.filerun('new_input')
cross = fc.read_cross('fort.201')
spline = cross_interpolate(cross)
theory = interpolate.splev(data.theta,spline)
exper = data.sigma
err = data.errx #Might need to consider aysmmetric data in future. Keep eye out.
chi_list = map(chi_sq,theory,exper,err)
return .5*np.sum(chi_list)
def read_data(filelist):
theta = []
sigma = []
for ele in filelist:
theta.append(float(ele[0]))
sigma.append(float(ele[1]))
graphline = fc.dataobject(theta,sigma)
return graphline
def __init__(self,files,data=None,q_name=None):
self.lines = []
#Create the list of lineobjects from file names given. If not given iterable it is assumed to be a single file.
#Can also pass list of lineobjects
if isinstance(files,tuple):
for ele in files:
self.lines.append(fc.read_cross(ele))
elif isinstance(files,str):
self.lines.append(fc.read_cross(files))
else:
for ele in files:
self.lines.append(ele)
self.data = data
#Initialize the plot
self.fig = plt.figure()
self.ax = self.fig.add_subplot(111)
def __init__(self,fresco,data,pot,term,var,percent_range=.2): #user selects what range they want to vary potentials within defualts to 20%
self.fresco = fc.FrescoInput(fresco)
self.data = fc.read_data(data)
self.f_args = (self.fresco,self.data,pot,term,var) #tuple of arguments to be passed to chi square function
self.x0 = [] #inital potential parameters
for ele in self.f_args[4]:
for line in self.fresco.sorted_pots[self.f_args[2]][self.f_args[3]]:#Just in case potential has two lines
if ele in line:
init = self.fresco.find_value(ele,line,'=')
self.x0.append(float(init))
self.x0 = np.asarray(self.x0)
self.init_chi = elastic_chi(self.x0,*self.f_args) #get inital chi square value
print "The initial chi squared value is ",self.init_chi
self.init_cs = fc.read_cross('fort.201') #the inital cross section data
self.iterations = 0 #number of basin hops completed
self.bounds = self.set_bounds(percent_range) #range we are allowed to jump around in. We will still sample, but auto rejected outside this range
#These are default parameters that can be set with set_basin
self.T = 1.0
self.steps = 50
self.step_size = .1
def readfres200(filelist):
#Initialize lists for angular information
theta = []
sigma = []
for ele in filelist:
#This picks out the cross section at each angle.
if len(ele) == 2 and ele[0] != '@legend' and ele[0] != '@subtitle':
theta.append(float(ele[0]))
sigma.append(float(ele[1]))
#looks for lab energy. Let this haunt your dreams until you think of a better way.
elif ele[0] == '@legend' or ele[0] == '#legend':
if 'energy' in ele:
energy = findall('[0-9.0]+',ele[6])
E = float(energy[0])
# End of file create the lineobject ask user for state information
elif ele[0] == 'END':
J,par = raw_input("What is the spin parity of the state?\n")
graphline = fc.lineobject(theta,sigma,E,J,par)
return graphline
def plot(self):
new_cs = fc.read_cross('fort.201') #the cross section for the fitted data
plot = fp.CrossSectionPlot([self.init_cs,new_cs],self.data) #create the plot with new_cs vs init_cs vs the data
plot.ax.set_title('Best Fit')
plot.plot()
