Пример #1
0
def s_order(job):
    dim = 1
    box_range = [0.167, 1.167]
    pore_center = (box_range[1]-box_range[0])/2 + box_range[0]
    fig, ax = plt.subplots()
    s_list = list()
    for trj in md.iterload(os.path.join(job.ws, 'nvt.dcd'), top=os.path.join(job.ws, 'init.mol2'), chunk=9000, skip=2001):
        water_bonds = get_bond_array(trj)
        bins, s_values = compute_s(trj,
                                   dim,
                                   pore_center=pore_center,
                                   bond_array=water_bonds)
        s_list.append(s_values)

    s_mean = np.mean(s_list, axis=0)
    s_std = np.std(s_list, axis=0)

    plt.plot(bins, s_mean)
    plt.fill_between(bins, s_mean + s_std, s_mean - s_std, alpha=0.2)
    plt.xlabel('z-position (nm)')
    plt.ylabel('S')

    with job:
        plt.savefig('s_order.pdf')

        np.savetxt('s_order.txt', np.transpose(np.vstack([bins, s_mean, s_std])),
                   header='Bins\tS_mean\tS_std')
    np.savetxt(f'data/{job.sp.nwater}_mol_s_order.txt', np.transpose(np.vstack([bins, s_mean, s_std])),
               header='Bins\tS_mean\tS_std')
Пример #2
0
def s_order(job, symmetrize=False):
    dim = 1
    box_range = [0.167, 1.167]
    pore_center = (box_range[1] - box_range[0]) / 2 + box_range[0]
    fig, ax = plt.subplots()
    s_list = list()
    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, "init.mol2"),
            chunk=5000,
            skip=skip,
    ):
        water_bonds = get_bond_array(trj)
        bins, s_values = compute_s(
            trj,
            dim,
            pore_center=pore_center,
            bond_array=water_bonds,
            symmetrize=symmetrize,
        )
        s_list.append(s_values)

    s_mean = np.mean(s_list, axis=0)
    s_std = np.std(s_list, axis=0)

    plt.plot(bins, s_mean)
    plt.fill_between(bins, s_mean + s_std, s_mean - s_std, alpha=0.2)
    plt.xlabel("z-position (nm)")
    plt.ylabel("S")

    if symmetrize == True:
        extension = "_symmetrize"
    else:
        extension = ""
    with job:
        plt.savefig(f"s_order{extension}.pdf")

        np.savetxt(
            f"s_order{extension}.txt",
            np.transpose(np.vstack([bins, s_mean, s_std])),
            header="Bins\tS_mean\tS_std",
        )
    np.savetxt(
        f"data/{job.sp.nwater}_mol_s_order{extension}.txt",
        np.transpose(np.vstack([bins, s_mean, s_std])),
        header="Bins\tS_mean\tS_std",
    )
Пример #3
0
def s_order(job):
    dim = 1
    box_range = [0.837, 2.837]
    pore_center = (box_range[1] - box_range[0]) / 2 + box_range[0]
    fig, ax = plt.subplots()
    s_list = list()
    for trj in md.iterload(
            os.path.join(job.ws, "nvt.trr"),
            top=os.path.join(job.ws, "init.mol2"),
            chunk=5000,
            skip=5001,
    ):
        water_bonds = get_bond_array(trj)
        bins, s_values = compute_s(trj,
                                   dim,
                                   pore_center=pore_center,
                                   bond_array=water_bonds)
        s_list.append(s_values)

    s_mean = np.mean(s_list, axis=0)
    s_std = np.std(s_list, axis=0)

    plt.plot(bins, s_mean)
    plt.fill_between(bins, s_mean + s_std, s_mean - s_std, alpha=0.2)
    plt.xlabel("z-position (nm)")
    plt.ylabel("S")
    plt.ylim((-0.45, 0.45))

    with job:
        plt.savefig("s_order.pdf")

        np.savetxt(
            "s_order.txt",
            np.transpose(np.vstack([bins, s_mean, s_std])),
            header="Bins\tS_mean\tS_std",
        )
    np.savetxt(
        f"data/{job.sp.nwater}_mol_s_order.txt",
        np.transpose(np.vstack([bins, s_mean, s_std])),
        header="Bins\tS_mean\tS_std",
    )
def angle_dist(job):
    dim = 1
    #box_range = [0.167, 1.167]
    box_range = [0.5, 0.8]
    pore_center = (box_range[1] - box_range[0]) / 2 + box_range[0]
    fig, ax = plt.subplots()
    cos_angle_list = list()
    all_cos_angle_list = list()
    for trj in md.iterload(
            os.path.join(job.ws, "nvt.trr"),
            top=os.path.join(job.ws, "init.mol2"),
            chunk=5000,
            skip=1,
    ):

        water_bonds = get_bond_array(trj)
        bins, cos_angle_values, all_cos_angles = compute_angle(
            trj, dim, pore_center=pore_center, bond_array=water_bonds)
        cos_angle_list.append(cos_angle_values)
        all_cos_angle_list.extend(all_cos_angles)
    cos_angle_mean = np.mean(cos_angle_list, axis=0)
    cos_angle_std = np.std(cos_angle_list, axis=0)

    plt.plot(bins, cos_angle_mean)
    plt.fill_between(bins,
                     cos_angle_mean + cos_angle_std,
                     cos_angle_mean - cos_angle_std,
                     alpha=0.2)
    plt.xlabel("z-position (nm)")
    plt.ylabel("cos(angle)")

    with job:
        plt.savefig(
            project.root_directory() +
            "/data/{}_mol_angle_profile.pdf".format(str(job.sp.nwater)))

        np.savetxt(
            project.root_directory() +
            "/data/{}_mol_angle_profile.txt".format(str(job.sp.nwater)),
            np.transpose(np.vstack([bins, cos_angle_mean, cos_angle_std])),
            header="Bins\tcos_angle_mean\tcos_angle_std",
        )

    plt.figure()
    all_cos_angle_list = np.asarray(all_cos_angle_list)
    all_angle_list = (180 / np.pi) * np.arccos(all_cos_angle_list)
    counts, cos_angle_bins, bars = plt.hist(all_cos_angle_list,
                                            bins=60,
                                            alpha=0.5,
                                            density=True)
    cos_angle_bins_center = (cos_angle_bins[:-1] + cos_angle_bins[1:]) / 2
    plt.xlabel("cos(angle)")
    plt.ylabel("Relative frequency")
    with job:
        plt.savefig(
            project.root_directory() +
            "/data/{}_mol_cos_angle_dist.pdf".format(str(job.sp.nwater)))

        np.savetxt(
            project.root_directory() +
            "/data/{}_mol_cos_angle_dist.txt".format(str(job.sp.nwater)),
            np.transpose(np.vstack([cos_angle_bins_center, counts])),
            header="cos_Angle_bins\tRelativeFreq",
        )
    plt.figure()
    bins = np.linspace(0, 180, num=61)
    counts, angle_bins, bars = plt.hist(all_angle_list,
                                        bins=bins,
                                        alpha=0.5,
                                        density=True)
    plt.xlabel("Angle (degress)")
    plt.ylabel("Relative frequency")
    plt.title("Unnormalized distribution")
    angle_bins_center = (angle_bins[:-1] + angle_bins[1:]) / 2
    with job:
        plt.savefig(project.root_directory() +
                    "/data/{}_mol_angle_dist_unnormalized.pdf".format(
                        str(job.sp.nwater)))

        np.savetxt(
            project.root_directory() +
            "/data/{}_mol_angle_dist_unnormalized.txt".format(
                str(job.sp.nwater)),
            np.transpose(np.vstack([angle_bins_center, counts])),
            header="Angle_bins\tRelativeFreq",
        )

    plt.figure()
    normalized_counts = np.divide(
        counts, abs(np.sin((np.pi / 180) * angle_bins_center)))
    # Adjust so uniform corresponds to 1
    normalized_counts /= np.sum(normalized_counts)
    normalized_counts *= 60
    arr = plt.hist(angle_bins_center,
                   weights=normalized_counts,
                   bins=np.linspace(0, 180, num=61),
                   density=False)
    plt.xlabel("Angle (degress)")
    plt.ylabel("Relative frequency")
    plt.title("Normalized distribution")
    with job:
        plt.savefig(project.root_directory() +
                    "/data/{}_mol_angle_dist_normalized.pdf".format(
                        str(job.sp.nwater)))

        np.savetxt(
            project.root_directory() +
            "/data/{}_mol_angle_dist_normalized.txt".format(str(
                job.sp.nwater)),
            np.transpose(np.vstack([angle_bins_center, normalized_counts])),
            header="Angle_bins\tRelativeFreq",
        )