# ****************************************************************************
# 
# ALPS Project: Algorithms and Libraries for Physics Simulations
# 
# ALPS Libraries
# 
# Copyright (C) 2009-2010 by Matthias Troyer <troyer@phys.ethz.ch> 
# 
# This software is part of the ALPS libraries, published under the ALPS
# Library License; you can use, redistribute it and/or modify it under
# the terms of the license, either version 1 or (at your option) any later
# version.
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# You should have received a copy of the ALPS Library License along with
# the ALPS Libraries; see the file LICENSE.txt. If not, the license is also
# available from http://alps.comp-phys.org/.
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# ****************************************************************************

import pyalps
import matplotlib.pyplot as plt
import pyalps.plot

#prepare the input parameters
parms = []
for t in [0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.25, 1.5, 1.75, 2.0]:
    parms.append(
        { 
          'LATTICE'        : "ladder", 
          'T'              : t,
          'J0'             : -1 ,
          'J1'             : -1 ,
          'THERMALIZATION' : 10000,
          'SWEEPS'         : 500000,
          'UPDATE'         : "cluster",
          'MODEL'          : "Heisenberg",
          'L'              : 60
        }
    )

#write the input file and run the simulation
input_file = pyalps.writeInputFiles('parm2b',parms)
pyalps.runApplication('spinmc',input_file,Tmin=5)

#load the susceptibility and collect it as function of temperature T
data = pyalps.loadMeasurements(pyalps.getResultFiles(prefix='parm2b'),'Susceptibility')
susceptibility = pyalps.collectXY(data,x='T',y='Susceptibility')

#make plot
plt.figure()
pyalps.plot.plot(susceptibility)
plt.xlabel('Temperature $T/J$')
plt.ylabel('Susceptibility $\chi J$')
plt.ylim(0,0.22)
plt.title('Heisenberg ladder')
plt.show()