def compute_high_low_q_correlation():
dcdfile = "/project/palmer/Jingxiang/Trajectories/Publication_mWAC/3375_run2.dcd"
total_atoms, total_frames = IO.reader.call_read_header(dcdfile)
keyword = "HDL-HDL"
# convert Angstrom to nm
An_to_nm = 10
num_bins_q_dist = 300
num_bins_rdf = 250
# initialize q tetrahedral histogram
q_tetra_hist, q_interval, q_range = initialize_hist(num_bins_q_dist, -3.0, 1.0)
# get box size
xyz, box = IO.reader.call_read_dcd_xyz_box(dcdfile, 1, total_atoms, return_numpy=True)
half_box_size = box.min()/2.0/An_to_nm
# initialize pair_correlation histogram
RDF_hist, rdf_interval, rdf_range = initialize_hist(num_bins_rdf, 0.0, half_box_size)
frame_counter = 0
for i in range(total_frames):
# read xyz coordinates
xyz, box = IO.reader.call_read_dcd_xyz_box(dcdfile, i+1, total_atoms, return_numpy=False)
# compute q tetrahedral order parameter
q_sorted_indx, q_tetra = compute_q_tetra(total_atoms, xyz, box)
# update q distribution
q_tetra_hist = update_hist(total_atoms, q_tetra, q_interval, -3.0, 1.0, num_bins_q_dist, q_tetra_hist)
# compute the pair correlation between species
new_hist, norm_atom = compute_pair_correl(keyword, num_bins_rdf, total_atoms, xyz, box, q_sorted_indx)
# update pair correlation distribution
update_pair_correl_hist(num_bins_rdf, new_hist, RDF_hist)
frame_counter += 1
r_mid, q_norm = normalize_hist(q_range, num_bins_q_dist, q_interval, q_tetra_hist)
r2hr, gr = normalize_pair_correl_hist(RDF_hist, num_bins_rdf, half_box_size, norm_atom, frame_counter, box)
np.savetxt("r2hr.txt", np.c_[r2hr])
np.savetxt("q_normalized_3375.txt", np.c_[r_mid, q_norm])
return None
def compute_high_low_q_correlation(T, dcdfile):
total_atoms, total_frames = IO.reader.call_read_header(dcdfile)
keyword = "LDL_LDL"
# convert Angstrom to nm
An_to_nm = 10
num_bins_q_dist = 300
num_bins_rdf = 250
# initialize q tetrahedral histogram
q_tetra_hist, q_interval, q_range = initialize_hist(
num_bins_q_dist, -3.0, 1.0)
# get box size
xyz, box = IO.reader.call_read_dcd_xyz_box(dcdfile,
1,
total_atoms,
return_numpy=True)
half_box_size = box.min() / (2.0 * An_to_nm)
# initialize pair_correlation histogram
RDF_hist, rdf_interval, rdf_range = initialize_hist(
num_bins_rdf, 0.0, half_box_size)
# set the frame counter to count number of configurations used
frame_counter = 0
# loop over all frames
for i in range(total_frames):
# read xyz coordinates
xyz, box = IO.reader.call_read_dcd_xyz_box(dcdfile,
i + 1,
total_atoms,
return_numpy=False)
# compute q tetrahedral order parameter
q_sorted_indx, q_tetra = compute_q_tetra(total_atoms, xyz, box)
# update q distribution
q_tetra_hist = update_hist(total_atoms, q_tetra, q_interval, -3.0, 1.0,
num_bins_q_dist, q_tetra_hist)
# compute the pair correlation between species
#new_hist, norm_atom = compute_pair_correl(keyword, num_bins_rdf, total_atoms, xyz, box, q_sorted_indx)
# update pair correlation distribution
#update_pair_correl_hist(num_bins_rdf, new_hist, RDF_hist)
frame_counter += 1
# normalize q tetrahedral order parameter distribution
r_mid, q_norm = normalize_hist(q_range, num_bins_q_dist, q_interval,
q_tetra_hist)
# normalize the RDF
#r2hr, gr = normalize_pair_correl_hist(RDF_hist, num_bins_rdf, half_box_size, norm_atom, frame_counter, box)
# write out the RDF histogram for different
#write_hist_file(keyword, total_atoms, box, frame_counter, rdf_interval, num_bins_rdf, RDF_hist)
# write out the normalized r2hr
#np.savetxt("r2hr.txt", np.c_[r2hr])
# write q tetrahedral distribution
np.savetxt("q_normalized_%d_run2.txt" % T, np.c_[r_mid, q_norm])
return None