def _test_flip_de_AlCutetra(self):
"""
flip de を total energy の変化量と比較
single サイト
"""
fcc = FCCXtal.from_pickle_ecis(
os.path.join(self.PATH, "AlCu/tetra_stress30/cluster.pickle"),
arrange='FCC_A', size=6)
fcc.cell[1, 2, 1, 3] = 0
fcc.cell[1, 1, 1, 3] = 0
fcc.cell[2, 2, 1, 0] = 0
fcc.cell[1, 2, 1, 0] = 0
pred_de = fcc.get_flip_de()[2, 2, 1, 3]/fcc.size**3/4
print("before")
before = fcc.get_energy()
print(before)
fcc.cell[2, 2, 1, 3] = 0
# fcc.cell[1, 2, 1, 2] = 0
print((fcc.get_flip_de() == np.min(fcc.get_flip_de())).sum())
after = fcc.get_energy()
print(after)
print("de")
de = after - before
print(de)
print("Predict de")
print(pred_de)
print((de - pred_de) ** 2 < 1e-6)
def exe(size, conc, restart):
"""
LW MonteCarlo を実行
"""
#システム生成
# path = "/Users/enoki/Researches/Analysis/Codes/01_testRun/montecarlo/AlCu/voldep/4.0"
# path = "/Users/enoki/Researches/Analysis/Codes/01_testRun/montecarlo/AlCu/wien/TO/"
# fcc = FCCXtal.from_pickle_ecis(os.path.join(path, 'cluster.pickle'),
# arrange='random', conc=0.25, size=4)
fcc = FCCXtal.from_pickle_ecis('cluster.pickle',
arrange='random', conc=conc, size=size)
fcc.adjast_conc_fine(conc)
x = System(fcc)
#収束計算の許容範囲
eps_log_modification_factor = 10 ** (-8)
#状態密度計算
if restart:
fname = "work/save.pickle"
with open(fname, 'rb') as rbfile:
restart = pickle.load(rbfile)
x.state.cell = restart["current_state"]
x.state.energy = x.state.get_energy()
log_density_of_state = EstimateDOS(x, eps_log_modification_factor, restart)
print(log_density_of_state)
def _test_get_entropy_TO(self):
"""
de を記録して entropy を算出する
"""
path = os.path.join(self.PATH, "AlCu/wien/TO")
fcc = FCCXtal.from_pickle_ecis(os.path.join(path, 'cluster.pickle'),
arrange='random', conc=0.25, size=30)
mc = MonteCarlo(fcc, T=10000)
mc.loop_fcc_micro_single(2000)
def _test_order_AlCu_TO(self):
"""
規則相のエネルギーを icvm と比較
null clucter は含まれていないので注意
"""
path = os.path.join(self.PATH, "AlCu/wien/TO")
fcc = FCCXtal.from_pickle_ecis(os.path.join(path, 'cluster.pickle'),
arrange='L12_A', size=10)
print("L12_A3B: -40.7461")
print(fcc.get_energy())
fcc = FCCXtal.from_pickle_ecis(os.path.join(path, 'cluster.pickle'),
arrange='L10', size=10)
print("L10_AB -148.668")
print(fcc.get_energy())
fcc = FCCXtal.from_pickle_ecis(os.path.join(path, 'cluster.pickle'),
arrange='L12_B', size=10)
print("L12_AB3 -183.749")
print(fcc.get_energy())
def _test_AlCu_mc_grand_TO(self):
"""
グランドカノニカルの計算テスト TO 近似
"""
fcc = FCCXtal.from_pickle_ecis(
os.path.join(self.PATH, "cluster_AlCu_TO.pickle"),
arrange='random', conc=0.6, size=30)
# fcc.from_pickle_cell(os.path.join(self.PATH, 'AlCu.pickle'))
mc = MonteCarlo(fcc, T=1000)
mc.loop_fcc_grand(100)
fcc.make_poscar(os.path.join(self.PATH, 'POSCAR'))
fcc.save_cell(os.path.join(self.PATH, 'AlCu'))
def _test_mc_fcc_micoro_single(self):
"""
loop_fcc_mciro_single の テスト
benchmarker で速度計測
"""
# path = os.path.join(self.PATH, "AlCu/voldep/4.0/")
path = os.path.join(self.PATH, "AlCu/wien/")
fcc = FCCXtal.from_pickle_ecis(os.path.join(path, 'cluster.pickle'),
arrange='random', conc=0.90, size=10)
print(len(fcc.ecis))
mc = MonteCarlo(fcc, T=300)
with Benchmarker(width=20, loop=3) as bench:
@bench("simple")
def _(bm): #pylint: disable=W0613,C0111
mc.loop_fcc_micro_single(10)
def _test_AlCu_mc_grand(self):
"""
グランドカノニカルの計算テスト
"""
fcc = FCCXtal.from_pickle_ecis(
os.path.join(self.PATH, "cluster_AlCu_09.pickle"),
arrange='random', conc=0.05, size=10)
# fcc.from_pickle_cell(os.path.join(self.PATH, 'AlCu.pickle'))
# eci_point = - 454.351346
# -3250 @ 1500
# -3800 @ 8000 0.92
# -4000 @ 10000 0.92
# -4700 @ 13500
fcc.eci_point = 89.45
mc = MonteCarlo(fcc, T=0)
mc.loop_fcc_grand(20)
fcc.make_poscar(os.path.join(self.PATH, 'POSCAR'))
fcc.save_cell(os.path.join(self.PATH, 'AlCu'))
def _test_gs(self):
"""
基底状態探索
エネルギーのみを出力
"""
path = os.path.join(self.PATH, "AlCu/voldep/4.0/")
fcc = FCCXtal.from_pickle_ecis(os.path.join(path, 'cluster.pickle'),
arrange='random', conc=0.90, size=10)
fcc.from_pickle_cell(os.path.join(path, 'AlCu.pickle'))
# mc = MonteCarlo(fcc, T=500)
# mc.loop_fcc_micro_single(500)
# 90 300
mc = MonteCarlo(fcc, T=20)
mc.loop_fcc_micro_single(10000)
fcc.make_poscar(os.path.join(path, 'POSCAR'))
fcc.save_cell(os.path.join(path, 'AlCu'))
def _test_flip_de_fcc(self):
"""
flip de を total energy の変化量と比較
一致すれば O.K.
cell size が 3 以上ならうまくいく
それより小さい場合は direct にエネルギーを求めた方が良い
"""
path = os.path.join(self.PATH, "AlCu/voldep/4.0/")
# path = os.path.join(self.PATH, "AlCu/wien/TO/")
fcc = FCCXtal.from_pickle_ecis(os.path.join(path, 'cluster.pickle'),
arrange='random', conc=0.8, size=3)
for _ in range(10):
# s=0, s=1 のサイトを無作為に抽出
print("random flip")
s0 = fcc.cell == 0
select_s0 = np.random.choice(range((s0).sum()), 1, replace=False)
site_s0 = (np.array(np.where(s0)))[:, select_s0[0]]
s1 = fcc.cell == 1
select_s1 = np.random.choice(
range((s1).sum()), 1, replace=False)
site_s1 = (np.array(np.where(s1)))[:, select_s1[0]]
print("before energy")
before = fcc.get_energy()
print(before)
pred_de = fcc.get_exchange_de_small(site_s0, site_s1)/fcc.size**3/4
pred_de = fcc.get_exchange_de(site_s0, site_s1)/fcc.size**3/4
fcc.cell[tuple(site_s0.T)] = 1
fcc.cell[tuple(site_s1.T)] = 0
after = fcc.get_energy()
print("after energy")
print(after)
print("de")
de = after - before
print(de)
print("Predict de")
print(pred_de)
assert (de - pred_de) ** 2 < 1e-6
def __test_poscar(self):
fname = 'POSCAR_ini'
path = '/Users/enoki/Dropbox/poscar'
path = '/Users/enoki/poscar2'
fcc = FCCXtal.from_pickle_ecis(os.path.join(path, 'cluster.pickle'),
arrange='random', conc=0.5, size=12)
fcc.load_poscar(os.path.join(path, fname), 0, 1)
fcc.get_histogram()
# fname = 'POSCAR_99'
# fcc.load_poscar(os.path.join(path, fname), 0, 1)
# fcc.get_histogram()
# fname = 'POSCAR_199'
# fcc.load_poscar(os.path.join(path, fname), 0, 1)
# fcc.get_histogram()
# fname = 'POSCAR_299'
# fcc.load_poscar(os.path.join(path, fname), 0, 1)
# fcc.get_histogram()
# fname = 'POSCAR_399'
# fcc.load_poscar(os.path.join(path, fname), 0, 1)
# fcc.get_histogram()
# fname = 'POSCAR_499'
# fcc.load_poscar(os.path.join(path, fname), 0, 1)
# fcc.get_histogram()
fname = 'POSCAR_4086'
fcc.load_poscar(os.path.join(path, fname), 0, 1)
fcc.get_histogram()
fname = 'POSCAR_699'
fcc.load_poscar(os.path.join(path, fname), 0, 1)
fcc.get_histogram()
pylab.show()
def calc_dos():
fname = "work/analysis/save.pickle"
with open(fname, 'rb') as rbfile:
conditions = pickle.load(rbfile)
path = "/Users/enoki/Researches/Analysis/Codes/01_testRun/montecarlo/AlCu/voldep/4.0"
system = FCCXtal.from_pickle_ecis(os.path.join(path, 'cluster.pickle'),
arrange='random', conc=0.5, size=4)
print(conditions['log_DOS'][:20])
print(max(conditions['log_DOS'][:20]))
ldos = [numpy.exp(x-max(conditions['log_DOS'][:20])) for x in conditions['log_DOS'][:20]]
print(ldos)
minimum = conditions['minimum_state'][0]
maximum = conditions['maximum_state'][0]
de = (maximum[0] - minimum[0])/(maximum[1] - minimum[1] - 1)
energies = numpy.array([minimum[0] + de * (i - 0.5) for i in range(len(ldos))])
print(energies)
print(minimum[0], maximum[0])
# index = [i + 1 for i in range(len(ldos))]
# width = 0.35
# pos = matplotlib.pyplot.bar(energies, ldos, width, color = 'r', align = 'center')
# matplotlib.pyplot.ylabel('Ratio(normalized)')
# matplotlib.pyplot.title('Density of states')
# matplotlib.pyplot.show()
def get_energy(T, kb=8.6171e-2):
beta = 1/(kb*T)
bunbo = ldos * numpy.exp(-beta*energies*32)
bunshi = energies*ldos*32 * numpy.exp(-beta*energies*32)
energy = bunshi.sum() / bunbo.sum()
print(T, energy)
print("energy")
for i in range(200):
get_energy(10*(i+1))
def test_mc_fcc_micoro_single(self):
"""
loop_fcc_mciro_single の テスト
benchmarker で速度計測
"""
# path = os.path.join(self.PATH, "AlCu/voldep/4.0/")
path = os.path.join(self.PATH, "AlCu/wien/")
fcc = FCCXtal.from_pickle_ecis(os.path.join(path, 'cluster.pickle'),
arrange='random', conc=0.50, size=5)
print(len(fcc.ecis))
mc = MonteCarlo(fcc, T=100)
# print(fcc._get_site_energy2())
print(fcc.get_energy())
# fcc.get_histogram()
# pylab.show()
# inter = fcc.get_histogram_inter(T=100)
# get_de = fcc.get_exchange_de2(inter)
# mc._loop_fcc_micro_single(10000, get_de)
# fcc.get_histogram()
# mc._loop_fcc_micro_single(10000, get_de)
# fcc.get_histogram()
# mc._loop_fcc_micro_single(10000, get_de)
# fcc.get_histogram()
# pylab.show()
with Benchmarker(width=20, loop=3) as bench:
@bench("simple")
def t(bm): #pylint: disable=W0613,C0111
for _ in range(50):
fcc.get_energy()
fcc.ecis = np.array(fcc.ecis).reshape(1, -1)
with Benchmarker(width=20, loop=3) as bench:
@bench("simple2")
def m(bm): #pylint: disable=W0613,C0111
for _ in range(50):
fcc.get_energy2()
def rerun():
fname = "work/analysis/save.pickle"
with open(fname, 'rb') as rbfile:
conditions = pickle.load(rbfile)
system = FCCXtal.from_pickle_ecis(os.path.join(path, 'cluster.pickle'),
arrange='random', conc=0.25, size=4)
def analysis():
fname = "work/analysis/save.pickle"
with open(fname, 'rb') as rbfile:
conditions = pickle.load(rbfile)
# path = "/Users/enoki/Researches/Analysis/Codes/01_testRun/montecarlo/AlCu/voldep/4.0"
# system = FCCXtal.from_pickle_ecis(os.path.join(path, 'cluster.pickle'),
# arrange='random', conc=0.5, size=2)
system = FCCXtal(size=2)
print(conditions['maximum_state'][0])
system.cell = conditions['maximum_state'][1]
system.make_poscar('work/analysis/POSCAR_max')
print(conditions['minimum_state'][0])
system.cell = conditions['minimum_state'][1]
# system.load_poscar('work/analysis/POSCAR_min2', 1, 0)
# system.load_poscar('work/analysis/POSCAR_min2', 0, 1)
# print(system.get_energy())
# mc = MonteCarlo(system, 0)
# mc.loop_fcc_micro_single(50000)
# print(system.get_energy())
system.make_poscar('work/analysis/POSCAR_min')
return
system.cell = conditions['current_state']
print(system.get_energy())
print(system.get_conc())
system.adjast_conc_fine(0.5)
print(system.get_energy())
print(system.get_conc())
system.cell[:, :, :, :] = 0
system.cell[:, :, 0, :] = 1
system.cell[:, :, 1, :] = 1
print(system.get_conc())
print(system.get_energy())
path = "/Users/enoki/Researches/Analysis/Codes/01_testRun/montecarlo/AlCu/voldep/4.0"
system = FCCXtal.from_pickle_ecis(os.path.join(path, 'cluster.pickle'),
arrange='random', conc=0.5, size=2)
system.cell[:, :, :, :] = 0
system.cell[:, :, 0, :] = 1
print(system.get_conc())
print(system.get_energy())
system.cell[:, :, :, :] = 0
system.cell[0, 0, 0, :] = 1
system.cell[1, 1, 0, :] = 1
print(system.get_conc())
print(system.get_energy())
system.make_poscar('work/analysis/POSCAR_top_state')
