def avg_hist_2(filename,filename2,num_files):
for i in range(num_files):
walk = np.load(f'{filename}/{filename2}_{i}.npy',allow_pickle=True)
plt.figure(i)
plt.xlabel('Walker Oxygen Bond Angle')
plt.ylabel('Density')
plt.title(f'Wave Function of Oxygen Angles at {i+1} million steps')
plt.bar(align='edge', width=1.5, linewidth=0, **lib.avg_hist(walk),alpha=.6)
plt.show()
def avg_hist(filename,filename2,num_files):
walkers = []
for i in range(num_files):
walk = np.load(f'{filename}/{filename2}_{i}.npy',allow_pickle=True)
for j in range(len(walk)):
walkers.append(walk[j])
plt.figure(i)
plt.xlabel('Walker Oxygen Bond Angle')
plt.ylabel('Density')
plt.title(f'Wave Function of Oxygen Angles after {i+1} million steps')
plt.bar(align='edge', width=1.5, **lib.avg_hist(walkers))
plt.show()
# Array axes are walkers, molecules, atoms, coordinates
#walkers = (np.random.rand(n_walkers, num_molecules, lib.atomic_masses.shape[0],lib.coord_const) - .5)
# Uncomment this line if loading in an already equliibrated walker array
#walkers = np.load('5000_walker.npy')
#######################################################################################
# Simulation
start = time.time()
# Equilibriate Walkers
#walkers = lib.sim_loop(walkers,equilibriation_phase,dt)['w']
ref_energy = lib.sim_loop(walkers,
sim_length,
dt,
wf_save=wave_func_interval,
output_filename=output_filename)['r']
np.savetxt(f'{output_filename}_cr_ref',
[np.mean(ref_energy[int(sim_length / 2):sim_length])])
#np.save(f'dt{dt}_sim{sim_length}_walk{n_walkers}',wave_func_out)
sys.exit(0)
# Simulation loop for descentdent weighting
'''
sim_out = lib.sim_loop(walkers,sim_length,dt,dw_save=prop_interval)
walkers, reference_energy, num_walkers, snapshots = [sim_out[k] for k in 'wrns']
'''
# Imports
import numpy as np
import itertools as it
import DMC_rs_lib as lib
import sys
# Start of validation here, everything above is solely from copied files to keep the same PE functions
# INPUT is filename, number of molecules for trimer/dimer/monomer
filename = sys.argv[1]
num_mol = int(sys.argv[2])
# load the walker array
walk_array = np.load(filename + '.npy')
# reshape the walker array
walk_reshape = np.reshape(walk_array, (walk_array.shape[0], num_mol, 3, 3))
intra_PE = lib.intra_pe(walk_reshape)
if num_mol > 1:
inter_PE, _, _, = lib.inter_pe(walk_reshape)
total_PE = lib.total_pe(walk_reshape)
np.savetxt(filename + '_intra', intra_PE)
if num_mol > 1:
np.savetxt(filename + '_inter', inter_PE)
np.savetxt(filename + '_total', total_PE)
prop_amount = .5
walkers, num_molecules = out.gen_walker_array(filename, n_walkers, prop_amount,
num_molecules)
# Uncomment the code below if doing an initialization within a random range
# Initial 4D walker array
# Returns a uniform distribution cenetered at the given bond length
# Array axes are walkers, molecules, atoms, coordinates
#walkers = (np.random.rand(n_walkers, num_molecules, lib.atomic_masses.shape[0],lib.coord_const) - .5)
# Uncomment this line if loading in an already equliibrated walker array
#walkers = np.load('5000_walker.npy')
#######################################################################################
# Simulation
'''
start = time.time()
# Equilibriate Walkers
walkers = lib.sim_loop(walkers,equilibriation_phase,dt)['w']
lib.sim_loop(walkers,sim_length,dt,wf_save=wave_func_interval,output_filename=output_filename)
#np.save(f'dt{dt}_sim{sim_length}_walk{n_walkers}',wave_func_out)
print(f'Total time: {time.time()-start:.1f}')
sys.exit(0)
'''
# Simulation loop for descentdent weighting
'''
sim_out = lib.sim_loop(walkers,sim_length,dt,dw_save=prop_interval)
prop_period = 20
prop_steps = int(prop_period / dt)
# Number of times we run DW simulation loop
prop_reps = 5
####################################################################################
# Molecule Model Constants
# Number of molecules in each walker
# Used to initialize the walker array
num_molecules = 1
# Initialize the walker array depending on the method inputted
if method == 'one_atom_random':
walkers = lib.init_one_atom_random(n_walkers, prop_range, num_molecules,
input_file)
elif method == 'one_atom_normal':
walkers = lib.init_one_atom_normal(n_walkers, prop_range, num_molecules,
input_file)
elif method == 'equil_random':
walkers = lib.init_equil_random(n_walkers, prop_range, num_molecules,
input_file)
elif method == 'equil_normal':
walkers = lib.init_equil_normal(n_walkers, prop_range, num_molecules,
input_file)
elif method == 'normal':
walkers = lib.init_normal(n_walkers, num_molecules, prop_range)