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MC.py
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# coding: utf-8
import numpy as np
from numpy.random import uniform, rand
from heiheihei import *
bv_dict = {'Ag1': {'O-2': 1.805, 'S-2': 2.119, 'F-1': 1.80, 'Cl-1': 2.09}, \
'Al3': {'O-2': 1.651, 'S-2': 2.13, 'Se-2': 2.27, 'Te-2': 2.48, 'F-1': 1.545, 'Cl-1': 2.032, 'Br-1': 2.20, 'I-1': 2.41, 'N-3': 1.79, 'P-3': 2.24, 'As-3': 2.30, 'H-1': 1.45}, \
'As3': {'O-2': 1.789, 'S-2': 2.272, 'F-1': 1.70, 'Cl-1': 2.16, 'C-4': 1.93}, 'As5': {'O-2': 1.767, 'F-1': 1.620, 'Cl-1': 2.14}, \
'C4': {'O-2': 1.390, 'C4': 1.54, 'S-2': 1.80, 'F-1': 1.32, 'Cl-1': 1.76, 'Br-1': 1.91, 'N-3': 1.442}, \
'Cd2': {'O-2': 1.904, 'S-2': 2.304, 'Se-2': 2.40, 'Te-2': 2.59, 'F-1': 1.811, 'Cl-1': 2.23, 'Br-1': 2.35, 'I-1': 2.57, 'N-3': 1.96, 'P-3': 2.34, 'As-3': 2.43, 'H-1': 1.66}, \
'Co2': {'O-2': 1.692, 'S-2': 1.94, 'F-1': 1.64, 'Cl-1': 2.01}, 'Co3': {'O-2': 1.70, 'S-2': 2.02, 'F-1': 1.62, 'Cl-1': 2.05, 'N-3': 1.69, 'C2': 1.634}, 'Co4': {'O-2': 1.72, 'F-1': 1.55}, \
'Cr2': {'O-2': 1.73, 'F-1': 1.67, 'Cl-1': 2.09, 'Br-1': 2.26, 'I-1': 2.48, 'N-3': 1.80}, 'Cr3': {'O-2': 1.724, 'S-2': 2.162, 'F-1': 1.64, 'Cl-1': 2.08, 'Br-1': 2.28, 'N-3': 1.78}, \
'Cr4': {'O-2': 1.783, 'F-1': 1.56}, 'Cr6': {'O-2': 1.794, 'F-1': 1.74, 'Cl-1': 2.12}, \
'Cu1': {'O-2': 1.504, 'S-2': 1.811, 'Se-2': 1.90, 'F-1': 1.6, 'Cl-1': 1.858, 'Br-1': 2.03, 'I-1': 2.155, 'N-3': 1.520, 'P-3': 1.774, 'As-3': 1.856, 'C-4': 1.446}, \
'Cu2': {'O-2': 1.679, 'S-2': 2.054, 'Se-2': 2.02, 'Te-2': 2.27, 'F-1': 1.594, 'Cl-1': 2.00, 'Br-1': 1.99, 'I-1': 2.16, 'N-3': 1.61, 'P-3': 1.97, 'As-3': 2.08, 'C-4': 1.72, 'H-1': 1.21}, \
'Fe2': {'O-2': 1.713, 'S-2': 2.125, 'F-1': 1.65, 'Cl-1': 2.06, 'Br-1': 2.21, 'I-1': 2.47, 'N-3': 1.769}, \
'Fe3': {'O-2': 1.759, 'S-2': 2.149, 'F-1': 1.679, 'Cl-1': 2.09, 'Br-1': 2.22, 'N-3': 1.815, 'C2': 1.689}, \
'Ga3': {'O-2': 1.730, 'S-2': 2.163, 'F-1': 1.62, 'Cl-1': 2.07, 'Br-1': 2.20, 'I-1': 2.46}, \
'Ge4': {'O-2': 1.748, 'S-2': 2.217, 'Se-2': 2.35, 'F-1': 1.66, 'Cl-1': 2.14}, 'Hg1': {'O-2': 1.90, 'F-1': 1.81, 'Cl-1': 2.28}, \
'Hg2': {'O-2': 1.93, 'S-2': 2.308, 'F-1': 1.90, 'Cl-1': 2.25, 'Br-1': 2.38, 'I-1': 2.62}, 'I5': {'O-2': 1.992, 'F-1': 1.90}, \
'I7': {'O-2': 1.93, 'F-1': 1.83, 'Cl-1': 2.31}, 'In3': {'O-2': 1.902, 'S-2': 2.370, 'F-1': 1.792, 'Cl-1': 2.28, 'Br-1': 2.51, 'I-1': 2.63}, \
'K1': {'O-2': 2.132, 'S-2': 2.59, 'Se-2': 2.72, 'Te-2': 2.93, 'F-1': 1.992, 'Cl-1': 2.519, 'Br-1': 2.66, 'I-1': 2.88, 'N-3': 2.26, 'P-3': 2.64, 'As-3': 2.83}, \
'Li1': {'O-2': 1.466, 'S-2': 1.94, 'Se-2': 2.09, 'Te-2': 2.30, 'F-1': 1.360, 'Cl-1': 1.91, 'Br-1': 2.02, 'I-1': 2.22, 'N-3': 1.61}, \
'Mg2': {'O-2': 1.693, 'S-2': 2.18, 'Se-2': 2.32, 'Te-2': 2.53, 'F-1': 1.578, 'Cl-1': 2.08, 'Br-1': 2.28, 'I-1': 2.46, 'N-3': 1.85, 'P-3': 2.29, 'As-3': 2.38}, \
'Mn2': {'O-2': 1.790, 'S-2': 2.22, 'F-1': 1.698, 'Cl-1': 2.133, 'Br-1': 2.34, 'I-2': 2.52, 'N-3': 1.849}, \
'Mn3': {'O-2': 1.760, 'F-1': 1.66, 'Cl-1': 2.14, 'N-3': 1.837}, 'Mn4': {'O-2': 1.753, 'F-1': 1.71, 'Cl-1': 2.13, 'N-3': 1.822}, \
'Mo4': {'O-2': 1.886, 'S-2': 2.235, 'F-1': 1.80, 'N-3': 2.043}, 'Mo6': {'O-2': 1.907, 'S-2': 2.331, 'F-1': 1.81, 'Cl-1': 2.28, 'N-3': 2.009}, \
'N3': {'O-2': 1.361, 'S-2': 1.73, 'F-1': 1.37, 'Cl-1': 1.75}, 'N5': {'O-2': 1.432, 'F-1': 1.36, 'Cl-1': 1.80}, \
'Na1': {'O-2': 1.803, 'S-2': 2.28, 'Se-2': 2.41, 'Te-2': 2.64, 'F-1': 1.677, 'Cl-1': 2.15, 'Br-1': 2.33, 'I-1': 2.56, 'N-3': 1.93, 'P-3': 2.36, 'As-3': 2.53, 'H-1': 1.68}, \
'Nb5': {'O-2': 1.911, 'F-1': 1.87, 'Cl-1': 2.27, 'I-1': 2.77}, 'Ni3': {'O-2': 1.75, 'S-2': 2.040, 'F-1': 1.58, 'N-3': 1.731}, \
'Ni2': {'O-2': 1.675, 'S-2': 1.937, 'F-1': 1.596, 'Cl-1': 2.02, 'Br-1': 2.20, 'I-1': 2.40, 'N-3': 1.647}, \
'P3': {'O-2': 1.655, 'S-2': 2.12, 'Se-2': 2.24}, 'P5': {'O-2': 1.617, 'S-2': 2.145, 'F-1': 1.54, 'Cl-1': 2.02, 'N-3': 1.704}, \
'Pb2': {'O-2': 2.112, 'S-2': 2.541, 'Se-2': 2.69, 'F-1': 2.03, 'Cl-1': 2.53, 'Br-1': 2.68, 'I-1': 2.83, 'N-3': 2.18}, \
'Pb4': {'O-2': 2.042, 'F-1': 1.94, 'Cl-1': 2.43}, 'Ru4': {'O-2': 1.834, 'S-2': 2.21, 'F-1': 1.74, 'Cl-1': 2.21}, \
'S2': {'O-2': 1.74, 'S-2': 2.03, 'N-2': 1.597, 'N-3': 1.682}, 'S4': {'O-2': 1.644, 'S-4': 2.35, 'F-1': 1.60, 'Cl-1': 2.02, 'N-3': 1.762}, \
'S6': {'O-2': 1.624, 'F-1': 1.56, 'Cl-1': 2.03, 'N-3': 1.72}, 'Sb3': {'O-2': 1.955, 'S-2': 2.474, 'Se-2': 2.60, 'F-1': 1.90, 'Cl-1': 2.35, 'Br-1': 2.51, 'I-1': 2.76, 'N-3': 2.108}, \
'Sb5': {'O-2': 1.912, 'F-1': 1.797, 'Cl-1': 2.30, 'Br-1': 2.48}, 'Sc3': {'O-2': 1.849, 'S-2': 2.321, 'Se-2': 2.44, 'Te-2': 2.64, 'F-1': 1.76, 'Cl-1': 2.23, 'Br-1': 2.38, 'I-1': 2.59, 'N-3': 1.98, 'P-3': 2.40, 'As-3': 2.48, 'H-1': 1.68}, \
'Se2': {'S-2': 2.21, 'Se-2': 2.33}, 'Se4': {'O-2': 1.811, 'F-1': 1.73, 'Cl-1': 2.22, 'Br-1': 2.43}, 'Se6': {'O-2': 1.788, 'F-1': 1.69, 'Cl-1': 2.16, 'N-3': 1.90}, \
'Si4': {'O-2': 1.624, 'S-2': 2.126, 'Se-2': 2.26, 'Te-2': 2.49, 'F-1': 1.58, 'Cl-1': 2.03, 'Br-1': 2.20, 'I-1': 2.41, 'C-4': 1.883, 'N-3': 1.724, 'P-3': 2.23, 'As-3': 2.31, 'H-1': 1.47}, \
'Sn2': {'O-2': 1.984, 'S-2': 2.423, 'Se-2': 2.476, 'Te-2': 2.747, 'F-1': 1.925, 'Cl-1': 2.36, 'Br-1': 2.50, 'I-1': 2.752, 'N-3': 2.046, 'P-3': 2.488, 'As-3': 2.585, 'C-4': 2.077}, \
'Sn4': {'O-2': 1.905, 'S-2': 2.399, 'Se-2': 2.524, 'F-1': 1.843, 'Cl-1': 2.276, 'Br-1': 2.444, 'I-1': 2.70, 'N-3': 2.024}, \
'Ta4': {'O-2': 2.29}, 'Ta5': {'O-2': 1.92, 'S-2': 2.47, 'F-1': 1.88, 'Cl-1': 2.30}, 'Te4': {'O-2': 1.977, 'S-2': 2.44, 'F-1': 1.87, 'Cl-1': 2.37, 'Br-1': 2.55, 'I-1': 2.782}, \
'Te6': {'O-2': 1.917, 'F-1': 1.82, 'Cl-1': 2.30}, 'Ti2': {'F-1': 2.15, 'Cl-1': 2.31, 'Br-1': 2.49}, 'Ti3': {'O-2': 1.791, 'S-2': 2.11, 'F-1': 1.723, 'Cl-1': 2.17, 'I-1': 2.52}, \
'Ti4': {'O-2': 1.815, 'S-2': 2.29, 'F-1': 1.76, 'Cl-1': 2.19, 'Br-1': 2.36}, 'V2': {'O-2': 1.70, 'S-2': 2.11, 'F-1': 2.16, 'Cl-1': 2.44}, \
'V3': {'O-2': 1.743, 'S-2': 2.185, 'F-1': 1.702, 'Cl-1': 2.19, 'N-3': 1.813}, 'V4': {'O-2': 1.784, 'S-2': 2.226, 'F-1': 1.70, 'Cl-1': 2.16, 'N-3': 1.875}, \
'V5': {'O-2': 1.803, 'S-2': 2.25, 'F-1': 1.70, 'Cl-1': 2.16}, 'Zn2': {'O-2': 1.704, 'S-2': 2.09, 'Se-2': 2.22, 'Te-2': 2.45, 'F-1': 1.62, 'Cl-1': 2.01, 'Br-1': 2.15, 'I-1': 2.36, 'N-3': 1.77, 'P-3': 2.15, 'As-3': 2.24, 'H-1': 1.42}, \
'Zr2': {'O-2': 2.34, 'F-1': 2.24, 'Cl-1': 2.58}, 'Zr4': {'O-2': 1.928, 'S-2': 2.41, 'Se-2': 2.53, 'Te-2': 2.67, 'F-1': 1.846, 'Cl-1': 2.33, 'Br-1': 2.48, 'I-1': 2.69, 'N-3': 2.11, 'P-3': 2.52, 'As-3': 2.57, 'H-1': 1.79}, \
'As-3': {'Al3': 2.30, 'Cd2': 2.43, 'Cu1': 1.856, 'Cu2': 2.08, 'K1': 2.83, 'Mg2': 2.38, 'Na1': 2.53, 'Sc3': 2.48, 'Si4': 2.585, 'Sn2': 2.585, 'Zn2': 2.24, 'Zr2': 2.57}, \
'Br-1': {'Al3': 2.20, 'C4': 1.91, 'Cd2': 2.35, 'Cr2': 2.26, 'Cr3': 2.28, 'Cu1': 2.03, 'Cu2': 1.99, 'Fe2': 2.21, 'Fe3': 2.22, 'Ga3': 2.20, 'Hg2': 2.38, 'In3': 2.51, 'K1': 2.66, \
'Li1': 2.02, 'Mg2': 2.28, 'Mn2': 2.34, 'Na1': 2.33, 'Ni2': 2.20, 'Pb2': 2.68, 'Sb3': 2.51, 'Sb5': 2.48, 'Sc3': 2.38, 'Se4': 2.43, 'Si4': 2.20, 'Sn4': 2.444, 'Zn2': 2.15, 'Zr4': 2.48}, \
'Cl-1': {'Ag1': 2.09, 'Al3': 2.032, 'As3': 2.16, 'As5': 2.14, 'C4': 1.76, 'Cd2': 2.23, 'Co2': 2.01, 'Co3': 2.05, 'Cr2': 2.09, 'Cr3': 2.08, 'Cr6': 2.12, 'Cu1': 1.858, 'Cu2': 2.00, \
'Fe2': 2.06, 'Fe3': 2.09, 'Ga3': 2.07, 'Ge4': 2.14, 'Hg1': 2.28, 'Hg2': 2.25, 'I7': 2.31, 'In3': 2.28, 'K1': 2.519, 'Li1': 1.91, 'Mg2': 2.08, 'Mn2': 2.133, 'Mn3': 2.14, \
'Mn4': 2.13, 'Mo6': 2.28, 'N3': 1.75, 'N5': 1.80, 'Na1': 2.15, 'Nb5': 2.27, 'Ni2': 2.02, 'P5': 2.02, 'Pb2': 2.53, 'Pb4': 2.43, 'Ru4': 2.21, 'S4': 2.02, 'S6': 2.03, \
'Sb3': 2.35, 'Sb5': 2.30, 'Sc3': 2.23, 'Se4': 2.22, 'Se6': 2.16, 'Si4': 2.03, 'Sn2': 2.36, 'Sn4': 2.276, 'Ta5': 2.30, 'Te4': 2.37, 'Te6': 2.30, 'Ti2': 2.31, 'Ti3': 2.17, \
'Ti4': 2.19, 'V2': 2.44, 'V3': 2.19, 'V4': 2.16, 'V5': 2.16, 'Zn2': 2.01, 'Zr2': 2.58, 'Zr4': 2.33}, \
'F-1': {'Ag1': 1.80, 'Al3': 1.545, 'As3': 1.70, 'As5': 1.620, 'C4': 1.32, 'Cd2': 1.811, 'Co2': 1.64, 'Co3': 1.62, 'Co4': 1.55, 'Cr2': 1.67, 'Cr3': 1.64, 'Cr4': 1.56, 'Cr6': 1.74, \
'Cu1': 1.6, 'Cu2': 1.594, 'Fe2': 1.65, 'Fe3': 1.679, 'Ga3': 1.62, 'Ge4': 1.66, 'Hg1': 1.81, 'Hg2': 1.90, 'I5': 1.90, 'I7': 1.83, 'In3': 1.792, 'Li1': 1.360, 'Mg2': 1.578, \
'Mn2': 1.698, 'Mn3': 1.66, 'Mn4': 1.71, 'Mo4': 1.80, 'Mo6': 1.81, 'N3': 1.37, 'N5': 1.36, 'Na1': 1.677, 'Nb5': 1.87, 'Ni3': 1.58, 'Ni2': 1.596, 'P5': 1.54, 'Pb2': 2.03, \
'Pb4': 1.94, 'Ru4': 1.74, 'S4': 1.60, 'S6': 1.56, 'Sb3': 1.90, 'Sb5': 1.797, 'Sc3': 1.76, 'Se4': 1.73, 'Se6': 1.69, 'Si4': 1.58, 'Sn2': 1.925, 'Sn4': 1.843, 'Ta5': 1.88, \
'Te4': 1.87, 'Te6': 1.82, 'Ti2': 2.15, 'Ti3': 1.723, 'Ti4': 1.76, 'V2': 2.16, 'V3': 1.702, 'V4': 1.70, 'V5': 1.70, 'Zn2': 1.62, 'Zr2': 2.24, 'Zr4': 1.846}, \
'H-1': {'Al3': 1.45, 'Cd2': 1.66, 'Cu2': 1.21, 'Na1': 1.68, 'Sc3': 1.68, 'Si4': 1.47, 'Zn2': 1.42, 'Zr4': 1.79}, \
'I-1': {'Al3': 2.41, 'Cd2': 2.57, 'Cr2': 2.48, 'Cu1': 2.155, 'Cu2': 2.16, 'Fe2': 2.47, 'Ga3': 2.46, 'Hg2': 2.62, 'In3': 2.63, 'K1': 2.88, 'Li1': 2.22, 'Mg2': 2.46, 'Mn2': 2.52, \
'Na1': 2.56, 'Nb5': 2.77, 'Ni2': 2.40, 'Pb2': 2.83, 'Sb3': 2.76, 'Si4': 2.41, 'Sn2': 2.752, 'Sn4': 2.70, 'Te4': 2.782, 'Ti3': 2.52, 'Zn2': 2.36, 'Zr4': 2.69}, \
'N-3': {'Al3': 1.79, 'C4': 1.442, 'Cd2': 1.96, 'Co3': 1.69, 'Cr2': 1.80, 'Cr3': 1.78, 'Cu1': 1.520, 'Cu2': 1.61, 'Fe2': 1.769, 'Fe3': 1.815, 'K1': 2.26, 'Li1': 1.61, \
'Mg2': 1.85, 'Mn2': 1.849, 'Mn3': 1.837, 'Mn4': 1.822, 'Mo4': 2.043, 'Mo6': 2.009, 'N-3': 1.44, 'Na1': 1.93, 'Ni3': 1.731, 'Ni2': 1.647, 'P5': 1.704, 'Pb2': 2.18, \
'S2': 1.682, 'S4': 1.762, 'S6': 1.72, 'Sb3': 2.108, 'Sc3': 1.98, 'Se6': 1.90, 'Si4': 1.724, 'Sn2': 2.046, 'Sn4': 2.024, 'V3': 1.813, 'V4': 1.875, 'Zn2': 1.77, 'Zr4': 2.11}, \
'O-2': {'Ag1': 1.805, 'Al3': 1.651, 'As3': 1.789, 'As5': 1.767, 'C4': 1.390, 'Cd2': 1.904, 'Co2': 1.692, 'Co3': 1.70, 'Co4': 1.72, 'Cr2': 1.73, 'Cr3': 1.724, 'Cr4': 1.783, \
'Cr6': 1.794, 'Cu1': 1.504, 'Cu2': 1.679, 'Fe2': 1.713, 'Fe3': 1.759, 'Ga3': 1.730, 'Ge4': 1.748, 'Hg1': 1.90, 'Hg2': 1.93, 'I5': 1.992, 'I7': 1.93, 'In3': 1.902, \
'K1': 2.132, 'Li1': 1.466, 'Mg2': 1.693, 'Mn2': 1.790, 'Mn3': 1.760, 'Mn4': 1.753, 'Mo4': 1.886, 'Mo6': 1.907, 'N3': 1.361, 'N5': 1.432, 'Na1': 1.803, 'Nb5': 1.911, \
'Ni3': 1.75, 'Ni2': 1.675, 'P3': 1.655, 'P5': 1.617, 'Pb2': 2.112, 'Pb4': 2.042, 'Ru4': 1.834, 'S2': 1.74, 'S4': 1.644, 'S6': 1.624, 'Sb3': 1.955, 'Sb5': 1.912, \
'Sc3': 1.849, 'Se4': 1.811, 'Se6': 1.788, 'Si4': 1.624, 'Sn2': 1.984, 'Sn4': 1.905, 'Ta4': 2.29, 'Ta5': 1.92, 'Te4': 1.977, 'Te6': 1.917, 'Ti3': 1.791, 'Ti4': 1.815, \
'V2': 1.70, 'V3': 1.743, 'V4': 1.784, 'V5': 1.803, 'Zn2': 1.704, 'Zr2': 2.34, 'Zr4': 1.928}, \
'P-3': {'Al3': 2.24, 'Cd2': 2.34, 'Cu1': 1.774, 'Cu2': 1.97, 'K1': 2.64, 'Mg2': 2.29, 'Na1': 2.36, 'Sc3': 2.40, 'Si4': 2.23, 'Sn2': 2.488, 'Zn2': 2.15, 'Zr4': 2.52}, \
'S-2': {'Ag1': 2.119, 'Al3': 2.13, 'As3': 2.272, 'C4': 1.80, 'Cd2': 2.304, 'Co2': 1.94, 'Co3': 2.02, 'Cr3': 2.162, 'Cu1': 1.811, 'Cu2': 2.054, 'Fe2': 2.125, 'Fe3': 2.149, \
'Ga3': 2.163, 'Ge4': 2.217, 'Hg2': 2.308, 'In3': 2.370, 'K1': 2.59, 'Li1': 1.94, 'Mg2': 2.18, 'Mn2': 2.22, 'N3': 1.73, 'Na1': 2.28, 'Ni3': 2.040, 'Ni2': 1.937, \
'P5': 2.145, 'Pb2': 2.541, 'Ru4': 2.21, 'S2': 2.03, 'Sb3': 2.474, 'Sc3': 2.321, 'Se2': 2.21, 'Si4': 2.126, 'Sn2': 2.423, 'Sn4': 2.399, 'Ta5': 2.47, 'Te4': 2.44, \
'Ti4': 2.29, 'V2': 2.11, 'V3': 2.185, 'V4': 2.226, 'V5': 2.25, 'Zn2': 2.09, 'Zr4': 2.41}, \
'Se-2': {'Al3': 2.27, 'Cd2': 2.40, 'Cu1': 1.90, 'Cu2': 2.02, 'Ge4': 2.35, 'K1': 2.72, 'Li1': 2.09, 'Mg2': 2.32, 'Na1': 2.41, 'P3': 2.24, 'Pb2': 2.69, 'Sb3': 2.60, \
'Sc3': 2.44, 'Se2': 2.33, 'Si4': 2.26, 'Sn2': 2.476, 'Sn4': 2.524, 'Zn2': 2.22, 'Zr4': 2.53}, \
'Te-2': {'Al3': 2.48, 'Cd2': 2.59, 'Cu2': 2.27, 'K1': 2.93, 'Li1': 2.30, 'Mg2': 2.53, 'Na1': 2.64, 'Sc3': 2.64, 'Si4': 2.49, 'Sn2': 2.747, 'Zn2': 2.45, 'Zr4': 2.67}}
def symbol_abs_error(structure, bv_dict, symbol, expected_valence, cutoff):
abs_error = 0
indices_excluded = np.arange(len(structure.frac_positions))[np.array(structure.atomic_symbols) == symbol]
for center in structure.cart_positions[np.array(structure.atomic_symbols) == symbol]:
positions_in_sphere, distances_in_sphere, indices_in_sphere = structure.lattice.get_points_in_sphere(structure.frac_positions, center, cutoff)
bond_valence = 0
for d, i in zip(distances_in_sphere, indices_in_sphere):
if i in indices_excluded:
continue
elif structure.atomic_symbols[i] in bv_dict.keys():
R_0 = bv_dict[structure.atomic_symbols[i]]
bond_valence += S(R_0, d)
else:
continue
abs_error += abs(bond_valence - expected_valence)
return abs_error
def S(R_0, r):
return np.exp((R_0 - r) / 0.37)
def bv_mean_error_criterion(structure, element_valence):
mapping = {}
for element, valence in element_valence.items():
mapping[element] = element + str(valence)
total_error = 0
for symbol in np.unique(structure.atomic_symbols):
bv_para = {}
for k, v in mapping.items():
if bv_dict[mapping[symbol]].has_key(v):
bv_para[k] = bv_dict[mapping[symbol]][v]
total_error += symbol_abs_error(structure, bv_para, symbol, abs(element_valence[symbol]), cutoff = 10)
return total_error / len(structure.frac_positions)
def func(structure, element_valence, limit = 0, bond_dist = 1.8, radius = 0.05, criterion = 0.2, times = 200):
error = bv_mean_error_criterion(structure, element_valence)
print error
if error < criterion or limit > times:
return structure, error, limit
spg_symbol = structure.get_spacegroup()
spg = SpaceGroup(spg_symbol)
lattice = structure.lattice_vectors
indep_index = structure.get_independent_atoms()
fitted_positions = []
for index in indep_index:
index_positions = structure.frac_positions[structure.get_identical_atoms_and_operations()[0] == index]
mul = len(index_positions)
for pos in index_positions:
if spg.get_wyckoff_letter(pos) == special_positions(spg_symbol, mul, pos):
fitted_positions.append(pos)
break
indep_wyck = structure.atomic_wyckoff_letters()[indep_index]
indep_atoms = np.array(structure.atomic_symbols)[indep_index]
satisfied = False
while not satisfied:
relaxed_positions = []
for disturb in fitted_positions:
relaxed_positions.append(disturb + np.array([uniform(-1, 1), uniform(-1, 1), uniform(-1, 1)]) * radius)
relaxed_positions = np.array(relaxed_positions)
new_structure, satisfied = structure_generation_for_monte_carlo(spg_symbol, lattice, indep_wyck, indep_atoms, relaxed_positions, min_bond_dist = bond_dist)
limit += 1
print limit
new_error = bv_mean_error_criterion(new_structure, element_valence)
if new_error < error:
structure = new_structure
return func(structure, element_valence, limit, bond_dist, radius, criterion, times)
else:
probility = normal_distribution(new_error, error, 0.02)
if rand() < probility:
structure = new_structure
return func(structure, element_valence, limit, bond_dist, radius, criterion, times)
else:
return func(structure, element_valence, limit, bond_dist, radius, criterion, times)
def normal_distribution(x, miu, sigma):
return 0.5 * np.exp(-(x - miu) ** 2 / (2 * sigma ** 2))