delta = delta / temperature
if metropolis(delta): # Accept Metropolis test
total = total + partial_new - partial_old # Update total values
total_spr = total_spr + partial_new_spr - partial_old_spr # Update quantum system potential
r[k, i, :] = rki # Update position
r_moves = r_moves + 1 # Increment move counter
r_ratio = r_moves / (n * p)
c_ratio = c_moves / n
blk_add(calc_variables())
blk_end(blk) # Output block averages
sav_tag = str(blk).zfill(
3) if blk < 1000 else 'sav' # Number configuration by block
for k in range(p):
write_cnf_atoms(cnf_prefix + str(k).zfill(2) + '.' + sav_tag, n, box,
r[k, :, :] * box) # Save configuration
run_end(calc_variables())
total = potential(box, r_cut, r) # Double check book-keeping
assert not total.ovr, 'Overlap in final configuration'
total_spr = spring(box, k_spring, r)
for k in range(p):
write_cnf_atoms(cnf_prefix + str(k).zfill(2) + '.' + out_tag, n, box,
r[k, :, :] * box) # Save configuration
conclusion()
kin = 0.5*np.sum(v**2) / n
print("{:40}{:15.6f}".format('Kinetic energy',kin) )
if np.fabs(delta_rho) < tol and np.fabs(delta_kin) < tol:
print('No changes requested')
else:
if np.fabs(delta_rho) > tol:
assert rho+delta_rho > 0.0, 'New requested density would be negative'
scale = ( rho / (rho+delta_rho) )**(1.0/3.0)
box = box * scale
r = r * scale
rho = n / box**3
print("{:40}{:15.6f}".format('Density',rho) )
if np.fabs(delta_kin) > tol:
assert kin+delta_kin > 0.0, 'New requested kinetic energy would be negative'
scale = np.sqrt ( (kin+delta_kin) / kin )
v = v * scale
kin = 0.5*np.sum(v**2) / n
print("{:40}{:15.6f}".format('New kinetic energy',kin) )
if atomic:
if velocities:
write_cnf_atoms ( filename, n, box, r, v )
else:
write_cnf_atoms ( filename, n, box, r )
else:
if velocities:
write_cnf_mols ( filename, n, box, r, e, v, w )
else:
write_cnf_mols ( filename, n, box, r, e )
if accepted:
n_acc = n_acc + 1
q_min, q_max = update_histogram(q, q_min, q_max)
c_ratio = n_acc / n_crank
blk_add(calc_variables())
blk_end(blk) # Output block averages
flat = histogram_flat(flatness, q_min, q_max, h) # Check for flatness
if flat: # End of this stage
print("{:63}".format('-' * 63))
print("{:5}{:3d}{:22}{:3d}{:3d}{:3d}".format(
'stage', stage, ' q_min q_max q_count =', q_min, q_max,
np.count_nonzero(h[q_min:q_max + 1] > 0.5)))
print("{:63}".format('-' * 63))
sav_tag = str(stage).zfill(
3) if stage < 1000 else 'sav' # Number configuration by stage
write_cnf_atoms(cnf_prefix + sav_tag, n, bond, r) # Save configuration
write_histogram(his_prefix + sav_tag) # Save histogram
stage = stage + 1 # Ready for next stage
ds = ds / 2.0 # Entropy change reduction
run_end(calc_variables()
) # Output run averages, although these are really not relevant
write_results() # Specimen results at selected temperatures
write_cnf_atoms(cnf_prefix + out_tag, n, bond, r) # Save configuration
conclusion()
if k == i or k == j or partner[k] == i or partner[k] == j:
coltime[k], partner[k] = update(k, box, r[k:, :], v[k:, :])
# Search for partners <i
if i > 0:
coltime[:i], partner[:i] = dndate(i, box, r[:i + 1, :],
v[:i + 1, :], coltime[:i],
partner[:i])
if j > 0:
coltime[:j], partner[:j] = dndate(j, box, r[:j + 1, :],
v[:j + 1, :], coltime[:j],
partner[:j])
ncoll = ncoll + col_sum
# Calculate and accumulate variables for this step
blk_add(calc_variables())
blk_end(blk) # Output block averages
sav_tag = str(blk).zfill(
3) if blk < 1000 else 'sav' # Number configuration by block
write_cnf_atoms(cnf_prefix + sav_tag, n, box, r * box,
v) # Save configuration
run_end(calc_variables())
print("{:40}{:15d} ".format('Total collisions', ncoll))
assert not overlap(box, r), 'Particle overlap in final configuration'
write_cnf_atoms(cnf_prefix + out_tag, n, box, r * box, v) # Save configuration
conclusion()
total2 = total2_new # Update total values
box1 = box1_new # Update box lengths
box2 = box2_new # Update box lengths
v_ratio = 1.0 # Set move counter
blk_add(calc_variables())
rho_vals[stp, :] = [n1 / box1**3, n2 / box2**3]
eng_vals[stp, :] = [
1.5 * temperature + total1.pot / n1,
1.5 * temperature + total2.pot / n2
]
blk_end(blk) # Output block averages
sav_tag = str(blk).zfill(
3) if blk < 1000 else 'sav' # Number configuration by block
write_cnf_atoms(cnf1_prefix + sav_tag, n1, box1,
r1 * box1) # Save configuration
write_cnf_atoms(cnf2_prefix + sav_tag, n2, box2,
r2 * box2) # Save configuration
# Increment histograms
rho_h, rho_bins = np.histogram(rho_vals, bins=nh, range=(rho_min, rho_max))
eng_h, eng_bins = np.histogram(eng_vals, bins=nh, range=(eng_min, eng_max))
rho_hist = rho_hist + rho_h
eng_hist = eng_hist + eng_h
run_end(calc_variables())
# Write out histograms
norm = 2 * nstep * nblock * (rho_bins[1] - rho_bins[0])
rho_hist = rho_hist / norm
norm = 2 * nstep * nblock * (eng_bins[1] - eng_bins[0])
