def __init__(self, temperatures, energies):
if len(temperatures) != len(energies):
print("Gibbs: data size are different !")
exit()
data = []
for temp, ene in zip(temperatures, energies):
data.append({'temp': float(temp), 'gibbs': float(ene)})
DataBox.__init__(self, data)
def __init__(self, dos):
DataBox.__init__(self, [])
self.dos_lines = Cabinet.read_file(dos)
self.num_atoms = self.get_num_atoms(self.dos_lines[0])
(self.num_energy,
self.fermi_energy) = self.get_parameters(self.dos_lines[5])
print(self.get_parameters(self.dos_lines[5]))
self.dos_data = self.__prep_dos_data(self.num_atoms,
self.labels_orbital)
def __init__(self, data):
"""
DataBox の labels
label: クラスターのラベル R*N*
MxCls: MaxCluster の個数
CV_score: CV score
"""
DataBox.__init__(self, data)
self.output_keys = []
def __init__(self, temps, fit_params):
data = []
for temp, param in zip(temps, fit_params):
[G, B, B1, V0] = param
data.append({'temp': float(temp), 'G_P0': float(G),
'gibbs': float(G),
'B': float(B), 'B1': float(B1), 'V0': float(V0)})
DataBox.__init__(self, data)
self.is_per_atom = False
self.pressure = 0
def __init__(self, compound, refs):
if (compound.murnaghan['temp'] != refs.temp).all():
print('Enthalpy: Temperatures are different !')
exit()
temp = [{'temp': x} for x in refs.temp]
self.compound = compound
self.murnaghan = compound.murnaghan
self.refs = refs
self.comp = compound.comp
DataBox.__init__(self, temp)
self['enthalpy'] = self.enthalpy()
def __init__(self, path_list, poscar='POSCAR', output='OSZICAR'):
"""
initialize
"""
if not path_list:
print("path_list is empty !!!")
self.filetype = {'poscar': poscar, 'output': output}
self.path_list = path_list
DataBox.__init__(self, self.get_data())
#self.data, self.comp = self.get_data()
#self.trim_bool(self.data, self.data['bool'], 'energy', 'mag')
self.output_keys = []
def __init__(self, procar):
"""
self.dataの構成
'kpoint_id', 'orbitals_phase', 'kpoint', 'energy', 'spin'
'orbitals_tot', 'occupancy'
"""
flow_procar = open(procar)
line = flow_procar.readline()
line = flow_procar.readline()
(self.num_kpoints,
self.num_bands,
self.num_atoms) = self.get_meta(line)
print(self.get_meta(line))
DataBox.__init__(self, self.get_data(flow_procar))
def table_combi(self, sites, out_key):
"""
self.dataをcombi用のtableに整形
POSCARでのcombiの元素位置をsiteに指定
__str__()でx:site[0], y:site[1]の元素でtableが出力
"""
data_list = self.separate_data('elements', sites[1])
tmp_table = []
tmp_key = [x[sites[0]] for x in self['elements']]
keys = sorted(set(tmp_key), key=tmp_key.index)
for data in data_list:
add_dict = {out_key: data.data[1]['elements'][sites[1]]}
add_dict.update({x['elements'][sites[0]]: x[out_key]
for x in data.data})
tmp_table.append(add_dict)
table = DataBox(tmp_table)
table.output_keys = [out_key] + keys
return table
def __init__(self, procar, poscar=None):
"""
self.dataの構成
'kpoint_id', 'orbitals_phase', 'kpoint', 'energy', 'spin'
'orbitals_tot', 'occupancy'
'dk', 'xaxis'を追加
'dk'は前のk点からのk空間上の距離,
'xaxis'はそれを積算したものでband描写の横軸に用いる
poscarを読み込ませることで逆格子cellの各軸の長さを反映させて,
bandの横軸の長さを対応させることができる
defaultではposcarは読まずに、a*, b*, c*の長さは全て1
"""
with open(procar, 'r') as flow_procar:
line = flow_procar.readline()
line = flow_procar.readline()
(self.num_kpoints,
self.num_bands,
self.num_atoms) = self.get_meta(line)
print(self.get_meta(line))
DataBox.__init__(self, self.get_data(flow_procar))
def md_voldep(cutoff, wo_fit, vrange):
"""
md 計算の体積依存性を plot する
"""
path = "voldep/*/OSZICAR"
dir_list = [os.path.dirname(x) for x in glob.glob(path)]
average = []
sb_dark = seaborn.dark_palette("skyblue", 10, reverse=True)
# sb_dark = seaborn.dark_palette("seagreen", 10, reverse=True)
# sb_dark = seaborn.dark_palette("purple", 10, reverse=True)
seaborn.set(palette=sb_dark)
fig, axes = pylab.subplots(2, 1, figsize=(5, 10))
for dirc in dir_list:
with open(os.path.join(dirc, 'OUTCAR')) as wfile:
lines = wfile.readlines()
meta = re.compile(r".*external pressure = \s*(.*)\s+kB.+")
pressure = []
for line in lines:
match = meta.match(line)
if match:
pressure.append(float(match.group(1)))
with open(os.path.join(dirc, 'OSZICAR')) as wfile:
lines = wfile.readlines()
meta = re.compile(r".+T=\s*(.*)\s+E=\s*(.*)\s+F=.+")
energy = []
for line in lines:
match = meta.match(line)
if match:
energy.append(float(match.group(2)))
data = [{'energy':e, 'pressure':p} for e, p in zip(energy, pressure)]
dbox = DataBox(data)
volume = float(dirc.split('_')[1])
press_ave = dbox['pressure'][cutoff:].mean()
energy_ave = dbox['energy'][cutoff:].mean()
average.append({'volume':volume, 'p': press_ave, 'e': energy_ave})
label = "V={0:.0f}".format(float(dirc.split("_")[-1]))
seaborn.distplot(dbox['pressure'][cutoff:], label=label, ax=axes[0])
axes[0].legend(loc='upper left')
axes[0].set_ylabel("Frequency")
axes[0].set_xlabel("Pressuer (kbar)")
average_data = DataBox(average)
average_data.sorted('volume')
if vrange != (0, 0):
average_data = average_data.trim_data_within_range('volume', vrange)
axes[1].plot(average_data['volume'],
average_data['p'], 'p', color=sb_dark[-1])
axes[1].set_ylabel(r"Pressuer (kbar)")
axes[1].set_xlabel(r"Volume ($\AA^3$)")
fig.subplots_adjust(left=0.20)
if not wo_fit:
xi, yi = FitData.Stineman_interp_fit(average_data['volume'],
average_data['p'])
axes[1].plot(xi, yi)
idx = np.abs(yi).argmin()
print("v0: {0}, p0: {1}".format(xi[idx], yi[idx]))
print("v0**(1/3): {0}".format(xi[idx]**(1/3)))
axes[1].plot(xi[idx], yi[idx], 'o')
pylab.savefig("pressure.eps")
def __init__(self, path_list):
self.path_list = path_list
DataBox.__init__(self, self.get_data())
self.output_keys = []
def __init__(self, data):
DataBox.__init__(self, data)
def __init__(self, data):
DataBox.__init__(self, data)
self.output_keys = []
def __init__(self, temperatures, bulk_mods):
data = []
for temp, bulk in zip(temperatures, bulk_mods):
data.append({'temp': float(temp), 'bulk': float(bulk)})
DataBox.__init__(self, data)
