def thermodynamic_integration(x,y,yerr,N=1000):
""" Performs the integration using Simpson's rule after bootstrapping the y values.
"""
Q=np.zeros(N)
y_bstrap=eh.resampling(y,yerr,N)
for i in xrange(N):
Q[i]=simps(y_bstrap[:,i],x,even='avg')
return Q
parser.add_argument('--magnsusc','-m',action='store_true')
parser.add_argument('--verbose','-v',action='store_true')
args=parser.parse_args()
def energy_flucs(e, e2, beta):
return (e2 - e**2 ) * beta**2
def magn_flucs(e, e2, beta):
return (e2 - e**2 ) * beta
path=os.path.dirname(args.infile)
prefix=os.path.basename(args.infile)
N=args.N
dataG = eh.read_results_from_file(path, prefix, args.X, args.quantity)
if args.verbose:
print dataG
if args.specheat:
dataG2 = eh.read_results_from_file(path, prefix, args.X, args.quantity+'2')
b, e, eerr = eh.convert_alps_dataset(dataG[0])
b, e2, e2err= eh.convert_alps_dataset(dataG2[0])
L = dataG[0].props['L']
for beta,en,enerr,en2,en2err in zip(b,e,eerr,e2,e2err):
cv, cverr = eh.bootstrap(energy_flucs, [en, en2, beta] , [enerr, en2err, 0.0], N=N)
print beta, cv, cverr
elif args.magnsusc:
if W!=L:
dofs = 2*factor[args.System] *L** (dim[args.System]-1) * W
if args.full:
dofs = 1
#print dofs
x=np.zeros((NIncSteps,NValues))
y=np.zeros((NIncSteps,NValues))
y_err=np.zeros((NIncSteps,NValues))
for schemes in renyi_dataG:
scheme=int(schemes.props['IncNo'])
x[scheme],y[scheme],y_err[scheme] = eh.convert_alps_dataset(schemes)
for k in range(3,NValues+1,args.Step):
for schemes in renyi_dataG:
scheme=int(schemes.props['IncNo'])
S[scheme]=thermodynamic_integration(x[scheme,:k],y[scheme,:k],y_err[scheme,:k]+1e-15,N)
if args.alternate:
gamma=np.array([args.Const-dofs * (S[0,l]-S[1,l]-S[2,l]+S[3,l]) for l in range(N)])
elif args.simple:
gamma=np.array([args.Const-dofs * (S[args.simple,l]-S[0,l]) for l in range(N)])
else:
gamma=1./(n-1)*np.array([args.Const-(n*factor[args.System] * L ** dim[args.System]) * (S[0,l]-2*S[1,l]+S[2,l]) for l in range(N)])
