def make_stuff_for_part_2():
''' Find C/N vs. n '''
#===============================================================================
# Adjustable parameters for the problem
J = 1.5
n_list = [5, 10, 20, 30, 50, 75, 100, 200, 500] #TODO: make this array-able... in B) we need to compare results for different n.
# TODO: comment out the following
# n_list = [10]
kT_min = 1.5
kT_max = 4.5
kT_step = 0.1
#===============================================================================
# make array of temps
kT_array = np.arange( kT_min, kT_max + kT_step, kT_step )
# make an empty array to store lattice simulations
lattices = []
for n in n_list:
n_steps = int( ( n ** 2 ) * 100 )
lattice = Lattice( J, n, n_steps, kT_array )
lattice.run_metropolous_algorithm()
lattices.append( lattice )
# save the list of lattice simulations to a pickle:
fp = filepath_for_now( local_data_directory )
print "Save to "
print fp
pickle.dump( lattices, open( fp + '.p' , "wb" ) )
def make_stuff_for_part_1():
''' Find M vs. T '''
#===============================================================================
# Adjustable parameters for the problem
J = 1.5
n = 50 #TODO: make this array-able... in B) we need to compare results for different n.
n_steps = 20000
kT_min = 1.0
kT_max = 6.0
kT_step = 0.1
#===============================================================================
kT_array = np.arange( kT_min, kT_max, kT_step )
lattice = Lattice( J, n, n_steps, kT_array )
lattice.run_metropolous_algorithm()
fp = filepath_for_now( local_data_directory )
print "Save to "
print fp
pickle.dump( lattice, open( fp + '.p' , "wb" ) )
