def number_density(job):
dim = 1
box_range = [0.5, 1.5]
pore_center = (box_range[1] - box_range[0]) / 2 + box_range[0]
o_densities = list()
h_densities = list()
fig, ax = plt.subplots()
for trj in md.iterload(
os.path.join(job.ws, "carbon_water-pos-1.pdb"),
top=os.path.join(job.ws, "init.mol2"),
chunk=5000,
skip=6000,
):
water_o = trj.atom_slice(trj.topology.select("name O"))
water_h = trj.atom_slice(trj.topology.select("name H"))
area = trj.unitcell_lengths[0][0] * trj.unitcell_lengths[0][2]
for water_trj in (water_o, water_h):
bins, density = compute_density(water_trj,
area,
dim,
pore_center=pore_center,
bin_width=0.01)
label_name = list(set([i.name for i in water_trj.topology.atoms]))
if label_name[0] == "O":
o_densities.append(density)
else:
h_densities.append(density)
o_mean = np.mean(o_densities, axis=0)
h_mean = np.mean(h_densities, axis=0)
o_std = np.std(o_densities, axis=0)
h_std = np.std(h_densities, axis=0)
plt.plot(bins, o_mean, label="O")
plt.fill_between(bins, o_mean + o_std, o_mean - o_std, alpha=0.2)
plt.plot(bins, h_mean, label="H")
plt.fill_between(bins, h_mean + h_std, h_mean - h_std, alpha=0.2)
plt.xlabel("z-position (nm)")
plt.ylabel("Number Density ($nm^-3$)")
plt.legend()
with job:
np.savetxt(
project.root_directory() +
"/data/{}/o_density.txt".format(str(job.sp.nwater) + "water_data"),
np.transpose(np.vstack([bins, o_mean, o_std])),
header="Bins\tDensity_mean\tDensity_std",
)
np.savetxt(
project.root_directory() +
"/data/{}/h_density.txt".format(str(job.sp.nwater) + "water_data"),
np.transpose(np.vstack([bins, h_mean, h_std])),
header="Bins\tDensity_mean\tDensity_std",
)
plt.savefig(project.root_directory() +
"/data/{}/numberdensity.pdf".format(
str(job.sp.nwater) + "water_data"))
def number_density(job):
dim = 1
box_range = [0.837, 2.837]
pore_center = (box_range[1] - box_range[0]) / 2 + box_range[0]
o_densities = list()
h_densities = list()
fig, ax = plt.subplots()
for trj in md.iterload(os.path.join(job.ws, 'nvt.dcd'),
top=os.path.join(job.ws, 'init.gro'),
chunk=1000,
skip=5001):
water_o = trj.atom_slice(trj.topology.select('name O'))
water_h = trj.atom_slice(trj.topology.select('name H'))
area = trj.unitcell_lengths[0][0] * trj.unitcell_lengths[0][2]
for water_trj in (water_o, water_h):
bins, density = compute_density(water_trj,
area,
dim,
pore_center=pore_center,
bin_width=0.01)
label_name = list(set([i.name for i in water_trj.topology.atoms]))
if label_name[0] == 'O':
o_densities.append(density)
else:
h_densities.append(density)
o_mean = np.mean(o_densities, axis=0)
h_mean = np.mean(h_densities, axis=0)
o_std = np.std(o_densities, axis=0)
h_std = np.std(h_densities, axis=0)
plt.plot(bins, o_mean, label='O')
plt.fill_between(bins, o_mean + o_std, o_mean - o_std, alpha=0.2)
plt.plot(bins, h_mean, label='H')
plt.fill_between(bins, h_mean + h_std, h_mean - h_std, alpha=0.2)
plt.xlabel('z-position (nm)')
plt.ylabel('Number Density ($nm^-3$)')
plt.legend()
with job:
np.savetxt('o_density.txt',
np.transpose(np.vstack([bins, o_mean, o_std])),
header='Bins\tDensity_mean\tDensity_std')
np.savetxt('h_density.txt',
np.transpose(np.vstack([bins, h_mean, h_std])),
header='Bins\tDensity_mean\tDensity_std')
plt.savefig('numberdensity.pdf')
np.savetxt(f'data/{job.sp.nwater}_mol_o_density.txt',
np.transpose(np.vstack([bins, o_mean, o_std])),
header='Bins\tDensity_mean\tDensity_std')
np.savetxt(f'data/{job.sp.nwater}_mol_h_density.txt',
np.transpose(np.vstack([bins, h_mean, h_std])),
header='Bins\tDensity_mean\tDensity_std')
def number_density(job, symmetrize=False):
dim = 1
box_range = [0.167, 1.167]
pore_center = (box_range[1] - box_range[0]) / 2 + box_range[0]
o_densities = list()
h_densities = list()
fig, ax = plt.subplots()
if job.sp.nwater == 1:
skip = 1
else:
skip = 5001
for trj in md.iterload(
os.path.join(job.ws, "nvt.trr"),
top=os.path.join(job.ws, "nvt.gro"),
chunk=5000,
skip=skip,
):
water_o = trj.atom_slice(trj.topology.select("name O"))
water_h = trj.atom_slice(trj.topology.select("name H"))
area = trj.unitcell_lengths[0][0] * trj.unitcell_lengths[0][2]
for water_trj in (water_o, water_h):
bins, density = compute_density(
water_trj,
area,
dim,
pore_center=pore_center,
bin_width=0.01,
symmetrize=symmetrize,
)
label_name = list(set([i.name for i in water_trj.topology.atoms]))
if label_name[0] == "O":
o_densities.append(density)
else:
h_densities.append(density)
o_mean = np.mean(o_densities, axis=0)
h_mean = np.mean(h_densities, axis=0)
o_std = np.std(o_densities, axis=0)
h_std = np.std(h_densities, axis=0)
plt.plot(bins, o_mean, label="O")
plt.fill_between(bins, o_mean + o_std, o_mean - o_std, alpha=0.2)
plt.plot(bins, h_mean, label="H")
plt.fill_between(bins, h_mean + h_std, h_mean - h_std, alpha=0.2)
plt.xlabel("z-position (nm)")
plt.ylabel("Number Density ($nm^-3$)")
plt.legend()
if symmetrize == True:
extension = "_symmetrize"
else:
extension = ""
with job:
np.savetxt(
f"o_density{extension}.txt",
np.transpose(np.vstack([bins, o_mean, o_std])),
header="Bins\tDensity_mean\tDensity_std",
)
np.savetxt(
f"h_density{extension}.txt",
np.transpose(np.vstack([bins, h_mean, h_std])),
header="Bins\tDensity_mean\tDensity_std",
)
plt.savefig(f"numberdensity{extension}.pdf")
np.savetxt(
f"data/{job.sp.nwater}_mol_o_density{extension}.txt",
np.transpose(np.vstack([bins, o_mean, o_std])),
header="Bins\tDensity_mean\tDensity_std",
)
np.savetxt(
f"data/{job.sp.nwater}_mol_h_density{extension}.txt",
np.transpose(np.vstack([bins, h_mean, h_std])),
header="Bins\tDensity_mean\tDensity_std",
)
def main():
project = signac.get_project("../")
for nwater, group in project.groupby("nwater"):
# New dataframe to save the results
df = pd.DataFrame()
# Create pore system
pore_width = 1.0 * u.nm
filled_pore = mbuild.recipes.GraphenePoreSolvent(
pore_length=1.0,
pore_depth=1.1,
pore_width=pore_width.to_value("nm"),
n_sheets=1,
slit_pore_dim=2,
x_bulk=0,
solvent=spce_water,
n_solvent=nwater,
)
# Translate to centered at 0,0,0 and make box larger in z
box_center = filled_pore.periodicity / 2.0
filled_pore.translate(-box_center)
filled_pore.periodicity[2] = 2.0
xy_area = filled_pore.periodicity[0] * filled_pore.periodicity[1]
top = filled_pore.to_trajectory(residues=["RES", "SOL"])
# Load all trajectories and combine
for job in group:
run = job.sp.run
# Load in full trajectory
full_traj = md.load(job.fn("prod.nvt.out.xyz"), top=top)
# Add unit cell information
full_traj = md.Trajectory(
full_traj.xyz,
full_traj.top,
unitcell_lengths=np.tile(filled_pore.periodicity,
(full_traj.n_frames, 1)),
unitcell_angles=np.tile([90., 90., 90.],
(full_traj.n_frames, 1)),
)
# Keep only water
slice_water = full_traj.top.select("water and name O H")
traj = full_traj.atom_slice(slice_water)
slice_ow = traj.top.select("name O")
slice_hw = traj.top.select("name H")
traj_ow = traj.atom_slice(slice_ow)
traj_hw = traj.atom_slice(slice_hw)
# Compute the density
bin_centers_ow, density_ow = compute_density(traj_ow,
xy_area,
bin_width=0.005)
bin_centers_hw, density_hw = compute_density(traj_hw,
xy_area,
bin_width=0.005)
# Compute the s order parameter
bin_centers_s, s_results = compute_s(traj, bin_width=0.005)
assert np.allclose(bin_centers_ow, bin_centers_hw)
assert np.allclose(bin_centers_ow, bin_centers_s)
# Save results
tmp_df = pd.DataFrame()
tmp_df[f"run"] = run
tmp_df[f"z-loc_nm"] = bin_centers_ow
tmp_df[f"density-ow_nm^-3"] = density_ow
tmp_df[f"density-hw_nm^-3"] = density_hw
tmp_df[f"s_value"] = s_results
df = df.append(tmp_df)
# Compute mean/stdev and save to file
means = df.groupby("z-loc_nm").mean().drop(
columns=["run"]).add_suffix("_mean")
stds = df.groupby("z-loc_nm").std().drop(
columns=["run"]).add_suffix("_std")
combined = means.merge(stds, on="z-loc_nm")
combined.to_csv(f"results_{nwater}-water.csv")