佐久間 美波
334 lines
14 KiB
Python
Executable File
334 lines
14 KiB
Python
Executable File
#!/usr/bin/env python
|
|
# ./dump2cube_edge_corner.py -i 050Li3PS4-050LiI.lammpstrj -m 160 160 160 -cut 8
|
|
import numpy as np
|
|
import argparse
|
|
import re
|
|
import os
|
|
import time
|
|
|
|
description = """This is a test program"""
|
|
par = argparse.ArgumentParser(description=description)
|
|
|
|
par.add_argument('-i', '--trjfile', default="", required=True,
|
|
help='input trjfile')
|
|
par.add_argument('-m', '--mesh', default=(30, 30, 30), required=False,
|
|
nargs=3, type=int, help='mesh grid')
|
|
par.add_argument('-cut', '--cutoff', default=7, required=False,
|
|
type=float, help='mesh grid')
|
|
|
|
args = par.parse_args()
|
|
ang_borr = 0.5291772109217
|
|
dirname = os.path.dirname(__file__)
|
|
|
|
|
|
class LammpsTrj():
|
|
def __init__(self):
|
|
"""
|
|
trjファイルを読み込んで、原子数、lattice、ステップ数を格納
|
|
"""
|
|
with open(args.trjfile) as o:
|
|
data = o.read().split()
|
|
self.atoms = int(data[7]) # 原子数
|
|
data = np.array(data).reshape(-1, self.atoms*7+32)
|
|
self.lattices = data[:, 17:23].astype(float) # (step, 6)
|
|
self.data = data[:, 32:] # 座標データ
|
|
self.steps = data.shape[0]
|
|
self.mesh = args.mesh
|
|
self.cutoff = args.cutoff
|
|
|
|
def setLattice(self, lat):
|
|
"""
|
|
latticeの形によって操作を分岐
|
|
self.M, self.M_を作成
|
|
"""
|
|
if lat.shape[0] == 6:
|
|
M = np.array([[lat[1]-lat[0], 0, 0],
|
|
[0, lat[3]-lat[2], 0],
|
|
[0, 0, lat[5]-lat[4]]]).astype(float)
|
|
if lat.shape[0] == 9:
|
|
xlo_bound, xhi_bound, xy = lat[0, 0], lat[0, 1], lat[0, 2]
|
|
ylo_bound, yhi_bound, xz = lat[1, 0], lat[1, 1], lat[1, 2]
|
|
zlo_bound, zhi_bound, yz = lat[2, 0], lat[2, 1], lat[2, 2]
|
|
xlo = xlo_bound - np.min([0.0, xy, xz, xy+xz])
|
|
xhi = xhi_bound - np.max([0.0, xy, xz, xy+xz])
|
|
ylo = ylo_bound - np.min([0.0, yz])
|
|
yhi = yhi_bound - np.max([0.0, yz])
|
|
zlo = zlo_bound
|
|
zhi = zhi_bound
|
|
lx = xhi - xlo
|
|
ly = yhi - ylo
|
|
lz = zhi - zlo
|
|
a = lx
|
|
b = np.sqrt(ly**2 + xy**2)
|
|
c = np.sqrt(lz**2 + xz**2 + yz**2)
|
|
alpha = np.arccos((xy*xz + ly*yz)/b/c)
|
|
beta = np.arccos(xz/c)
|
|
gamma = np.arccos(xy/b)
|
|
v1 = [a, 0, 0]
|
|
v2 = [b*np.cos(gamma), b*np.sin(gamma), 0]
|
|
v3 = [c*np.cos(beta),
|
|
c*(np.cos(alpha)-np.cos(beta)*np.cos(gamma))/np.sin(gamma),
|
|
c*np.sqrt(1+2*np.cos(alpha)*np.cos(beta)*np.cos(gamma)
|
|
- np.cos(alpha)**2-np.cos(beta)**2
|
|
- np.cos(gamma)**2 / np.sin(gamma))]
|
|
M = np.array([v1, v2, v3])
|
|
return M
|
|
|
|
def getOnestep(self, step):
|
|
"""
|
|
引数のstepにおける座標を、原子ごとにself.elems(辞書)に格納する
|
|
"""
|
|
step_data = self.data[step, :].reshape(self.atoms, -1) # (atoms, 6)
|
|
self.M = self.setLattice(self.lattices[step])
|
|
self.M_ = np.linalg.inv(self.M)
|
|
self.elems = {}
|
|
for e in np.unique(step_data[:, 2]):
|
|
d = step_data[step_data[:, 2] == e, 3:].astype(float)
|
|
dxyz = d[:, 0:3]
|
|
dxyz = dxyz @ self.M_
|
|
dxyz = dxyz - np.floor(dxyz)
|
|
d[:, 0:3] = dxyz
|
|
self.elems[e] = d
|
|
return self.elems
|
|
|
|
def makeCube(self, trjfile):
|
|
"""
|
|
P原子ごとに最も近い4つのI原子を選出し、Edge/Corner分類および回転を行う
|
|
"""
|
|
self.li_coords_list = []
|
|
self.i_coords_list = []
|
|
self.i_zero_coords_list = []
|
|
self.i_corner_coords_list = []
|
|
self.i_edge_coords_list = []
|
|
self.i_three_coords_list = []
|
|
|
|
self.li_hist = None
|
|
self.i_hist = None
|
|
self.i_hist_zero = None
|
|
self.i_hist_corner = None
|
|
self.i_hist_edge = None
|
|
self.i_hist_three = None
|
|
|
|
count_p = 0
|
|
I_S_CUTOFF = 4.7 # Edge/Corner判定用距離 (Angstrom)
|
|
|
|
for step in range(self.steps):
|
|
print(f"processing {step} step")
|
|
self.elems = self.getOnestep(step)
|
|
elems_ = {k: v.copy() for k, v in self.elems.items()}
|
|
|
|
for p_data in elems_["P"]:
|
|
|
|
# P原子に最も近い4つのI原子を特定
|
|
i_diffs = elems_["I"][:, 0:3] - p_data[0:3]
|
|
i_diffs = i_diffs - np.around(i_diffs)
|
|
i_diffs_abs = i_diffs @ self.M
|
|
distances = np.linalg.norm(i_diffs_abs, axis=1)
|
|
|
|
sorted_indices = np.argsort(distances)
|
|
closest_Is = elems_["I"][sorted_indices[:4]]
|
|
closer_Is = elems_["I"][sorted_indices[:15]]
|
|
|
|
nearest_I_coords = closest_Is[0]
|
|
|
|
# 着目P原子と同じPS4を構成するS原子を取得
|
|
s_data = elems_["S"][elems_["S"][:, 3] == p_data[3]]
|
|
|
|
# --- 距離によるSの配置決定 ---
|
|
si_diff = s_data[:, 0:3] - nearest_I_coords[0:3]
|
|
si_diff = si_diff - np.around(si_diff)
|
|
si_diff = np.linalg.norm(si_diff @ self.M, axis=1)
|
|
|
|
n_S_idx = np.argmax(si_diff)
|
|
s_indices = [0, 1, 2, 3]
|
|
s_indices.remove(n_S_idx)
|
|
n2_S_idx = s_indices[0]
|
|
|
|
s_xyz = s_data[:, 0:3] - p_data[0:3]
|
|
s_xyz = s_xyz - np.round(s_xyz)
|
|
s_xyz = s_xyz @ self.M
|
|
|
|
# --- 座標の回転行列を作成 ---
|
|
theta = np.arctan2(s_xyz[n_S_idx][0], s_xyz[n_S_idx][1])
|
|
self.Mat_z = np.array([[np.cos(-theta), np.sin(-theta), 0],
|
|
[-np.sin(-theta), np.cos(-theta), 0],
|
|
[0, 0, 1]])
|
|
s_xyz = (self.Mat_z @ s_xyz.T).T
|
|
|
|
theta2 = np.arctan2(s_xyz[n_S_idx][1], s_xyz[n_S_idx][2])
|
|
self.Mat_x = np.array([[1, 0, 0],
|
|
[0, np.cos(-theta2), np.sin(-theta2)],
|
|
[0, -np.sin(-theta2), np.cos(-theta2)]])
|
|
s_xyz = (self.Mat_x @ s_xyz.T).T
|
|
|
|
theta3 = np.arctan2(s_xyz[n2_S_idx][0], s_xyz[n2_S_idx][1])
|
|
self.Mat_z2 = np.array([[np.cos(-theta3), np.sin(-theta3), 0],
|
|
[-np.sin(-theta3), np.cos(-theta3), 0],
|
|
[0, 0, 1]])
|
|
s_xyz = (self.Mat_z2 @ s_xyz.T).T
|
|
self.s_xyz = s_xyz
|
|
|
|
p_xyz = np.array([0, 0, 0])
|
|
self.ps4_coord = np.vstack((p_xyz, s_xyz)) / ang_borr
|
|
|
|
def rotate_coords(coords_fractional):
|
|
if len(coords_fractional) == 0:
|
|
return np.array([])
|
|
rot_xyz = coords_fractional[:, 0:3] - p_data[0:3]
|
|
rot_xyz = rot_xyz - np.round(rot_xyz)
|
|
rot_xyz = rot_xyz @ self.M
|
|
rot_xyz = (self.Mat_z @ rot_xyz.T).T
|
|
rot_xyz = (self.Mat_x @ rot_xyz.T).T
|
|
rot_xyz = (self.Mat_z2 @ rot_xyz.T).T
|
|
return rot_xyz
|
|
|
|
# --- I原子のEdge/Corner判定と振り分け ---
|
|
zero_Is = []
|
|
edge_Is = []
|
|
corner_Is = []
|
|
three_Is = []
|
|
other_Is = []
|
|
|
|
for i_coord in closer_Is:
|
|
diff_si = s_data[:, 0:3] - i_coord[0:3]
|
|
diff_si = diff_si - np.around(diff_si)
|
|
diff_si_abs = diff_si @ self.M
|
|
dists = np.linalg.norm(diff_si_abs, axis=1)
|
|
|
|
# 距離がCUTOFF以下のS原子の数をカウント
|
|
close_S_count = np.sum(dists <= I_S_CUTOFF)
|
|
|
|
if close_S_count == 0:
|
|
zero_Is.append(i_coord)
|
|
elif close_S_count == 1:
|
|
corner_Is.append(i_coord)
|
|
elif close_S_count == 2:
|
|
edge_Is.append(i_coord)
|
|
elif close_S_count == 3:
|
|
three_Is.append(i_coord)
|
|
elif close_S_count > 3:
|
|
other_Is.append(i_coord)
|
|
|
|
# 判定結果に基づいてそれぞれのリストに追加
|
|
if len(zero_Is) > 0:
|
|
self.i_zero_coords_list.extend(
|
|
rotate_coords(np.array(zero_Is)).tolist())
|
|
if len(edge_Is) > 0:
|
|
self.i_edge_coords_list.extend(
|
|
rotate_coords(np.array(edge_Is)).tolist())
|
|
|
|
if len(corner_Is) > 0:
|
|
self.i_corner_coords_list.extend(
|
|
rotate_coords(np.array(corner_Is)).tolist())
|
|
|
|
if len(three_Is) > 0:
|
|
self.i_three_coords_list.extend(
|
|
rotate_coords(np.array(three_Is)).tolist())
|
|
|
|
# 全体のI用リストにも追加
|
|
self.i_coords_list.extend(rotate_coords(closest_Is).tolist())
|
|
|
|
count_p += 1
|
|
|
|
print("Calculating Histograms...")
|
|
volume = (self.cutoff*2)**3
|
|
bounds = [[-(self.cutoff)/ang_borr, (self.cutoff)/ang_borr]] * 3
|
|
|
|
# I (全体のI原子数で割ることで、Edge/Cornerの比率も反映させる)
|
|
total_I_num = len(self.i_coords_list)
|
|
|
|
if total_I_num > 0:
|
|
# I (All)
|
|
print("num_I_all: ", total_I_num)
|
|
i_arr = np.array(self.i_coords_list) / ang_borr
|
|
i_hist, _ = np.histogramdd(i_arr, bins=self.mesh, range=bounds)
|
|
self.i_hist = i_hist.ravel() / total_I_num / volume
|
|
|
|
# I (zero)
|
|
if len(self.i_zero_coords_list) > 0:
|
|
print("num_I_zero: ", len(self.i_zero_coords_list))
|
|
i_arr_zero = np.array(self.i_zero_coords_list) / ang_borr
|
|
i_hist_zero, _ = np.histogramdd(
|
|
i_arr_zero, bins=self.mesh, range=bounds)
|
|
self.i_hist_zero = i_hist_zero.ravel() / total_I_num / volume
|
|
|
|
# I (Corner)
|
|
if len(self.i_corner_coords_list) > 0:
|
|
print("num_I_corner: ", len(self.i_corner_coords_list))
|
|
i_arr_corner = np.array(self.i_corner_coords_list) / ang_borr
|
|
i_hist_corner, _ = np.histogramdd(
|
|
i_arr_corner, bins=self.mesh, range=bounds)
|
|
self.i_hist_corner = i_hist_corner.ravel() / total_I_num / volume
|
|
# I (Edge)
|
|
if len(self.i_edge_coords_list) > 0:
|
|
print("num_I_edge: ", len(self.i_edge_coords_list))
|
|
i_arr_edge = np.array(self.i_edge_coords_list) / ang_borr
|
|
i_hist_edge, _ = np.histogramdd(
|
|
i_arr_edge, bins=self.mesh, range=bounds)
|
|
self.i_hist_edge = i_hist_edge.ravel() / total_I_num / volume
|
|
|
|
# I (Three)
|
|
if len(self.i_three_coords_list) > 0:
|
|
print("num_I_three: ", len(self.i_three_coords_list))
|
|
i_arr_three = np.array(self.i_three_coords_list) / ang_borr
|
|
i_hist_three, _ = np.histogramdd(
|
|
i_arr_three, bins=self.mesh, range=bounds)
|
|
self.i_hist_three = i_hist_three.ravel() / total_I_num / volume
|
|
|
|
def outputCube(self):
|
|
output_start_time = time.time()
|
|
base = re.match(r"(\d{3}.*?LiI).*?",
|
|
args.trjfile.split("/")[-1]).group(1)
|
|
self.atomsDic = {'I': '53', 'Li': '3', 'P': '15', 'S': '16'}
|
|
|
|
def get_header():
|
|
body = f"created from {__file__}, {args}\n"
|
|
body += "Contains the selected quantity on a FFT grid\n"
|
|
origin = [-(self.cutoff)/ang_borr] * 3
|
|
body += "{:>5d}{:>12.7f}{:>12.7f}{:>12.7f}\n".format(5, *origin)
|
|
body += "{:>5d}{:>12.7f}{:>12.7f}{:>12.7f}\n".format(
|
|
self.mesh[0], (self.cutoff*2)/self.mesh[0]/ang_borr, 0, 0)
|
|
body += "{:>5d}{:>12.7f}{:>12.7f}{:>12.7f}\n".format(
|
|
self.mesh[1], 0, (self.cutoff*2)/self.mesh[1]/ang_borr, 0)
|
|
body += "{:>5d}{:>12.7f}{:>12.7f}{:>12.7f}\n".format(
|
|
self.mesh[2], 0, 0, (self.cutoff*2)/self.mesh[2]/ang_borr)
|
|
body += "{:>5d}{:>12.7f}{:>12.7f}{:>12.7f}{:>12.7f}\n".format(
|
|
int(self.atomsDic["P"]), float(self.atomsDic["P"]), *self.ps4_coord[0])
|
|
for s_coord in self.ps4_coord[1:5]:
|
|
body += "{:>5d}{:>12.7f}{:>12.7f}{:>12.7f}{:>12.7f}\n".format(
|
|
int(self.atomsDic["S"]), float(self.atomsDic["S"]), *s_coord)
|
|
return body
|
|
|
|
def save_cube(hist_data, suffix):
|
|
if hist_data is None:
|
|
return
|
|
body = get_header()
|
|
for idx, r in enumerate(hist_data):
|
|
if idx % 6 == 5:
|
|
body += "{:>13.5E}\n".format(r)
|
|
else:
|
|
body += "{:>13.5E}".format(r)
|
|
if idx % 6 != 5:
|
|
body += "\n" # 最後の行で改行がない場合用
|
|
|
|
outfile = f"{dirname}/{base}_PS4_{suffix}.cube"
|
|
with open(outfile, "w") as o:
|
|
o.write(body)
|
|
print(f"{outfile} was created.")
|
|
|
|
save_cube(self.li_hist, "Li")
|
|
save_cube(self.i_hist, "I_All")
|
|
save_cube(self.i_hist_zero, "I_zero")
|
|
save_cube(self.i_hist_corner, "I_corner")
|
|
save_cube(self.i_hist_edge, "I_edge")
|
|
save_cube(self.i_hist_three, "I_three")
|
|
|
|
output_end_time = time.time()
|
|
print(f"output_time : {output_end_time - output_start_time:.2f} s")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
trj = LammpsTrj()
|
|
trj.makeCube(args.trjfile)
|
|
trj.outputCube()
|