def get_pseudotable(options):
"""Return PseudoTable object."""
if options.pseudos is not None:
from abipy.flowtk import PseudoTable
return PseudoTable.as_table(options.pseudos)
try:
from pseudo_dojo import OfficialTables
except ImportError as exc:
print(
"PseudoDojo package not installed. Please install it with `pip install pseudo_dojo`"
)
print(
"or use `--pseudos FILE_LIST` to specify the pseudopotentials to use."
)
raise exc
dojo_tables = OfficialTables()
if options.usepaw:
raise NotImplementedError("PAW table is missing")
#pseudos = dojo_tables["ONCVPSP-PBE-PDv0.2-accuracy"]
else:
pseudos = dojo_tables["ONCVPSP-PBE-PDv0.2-accuracy"]
print("Using pseudos from PseudoDojo table", repr(pseudos))
return pseudos
def dataframe_from_pseudos(pseudos, index=None):
"""
Build pandas dataframe with the most important info associated to
a list of pseudos or a list of objects that can be converted into pseudos.
Args:
pseudos: List of objects that can be converted to pseudos.
index: Index of the dataframe.
Return:
pandas Dataframe.
"""
from abipy.flowtk import PseudoTable
pseudos = PseudoTable.as_table(pseudos)
import pandas as pd
from collections import OrderedDict
attname = [
"Z_val", "l_max", "l_local", "nlcc_radius", "xc", "supports_soc",
"type"
]
rows = []
for p in pseudos:
row = OrderedDict([(k, getattr(p, k, None)) for k in attname])
row["ecut_normal"], row["pawecutdg_normal"] = None, None
if p.has_hints:
hint = p.hint_for_accuracy(accuracy="normal")
row["ecut_normal"] = hint.ecut
if hint.pawecutdg: row["pawecutdg_normal"] = hint.pawecutdg
rows.append(row)
return pd.DataFrame(rows,
index=index,
columns=list(rows[0].keys()) if rows else None)
def dataframe_from_pseudos(pseudos, index=None):
"""
Build pandas dataframe with the most important info associated to
a list of pseudos or a list of objects that can be converted into pseudos.
Args:
pseudos: List of objects that can be converted to pseudos.
index: Index of the dataframe.
Return:
pandas Dataframe.
"""
from abipy.flowtk import PseudoTable
pseudos = PseudoTable.as_table(pseudos)
import pandas as pd
attname = ["Z_val", "l_max", "l_local", "nlcc_radius", "xc", "supports_soc", "type"]
rows = []
for p in pseudos:
row = OrderedDict([(k, getattr(p, k, None)) for k in attname])
row["ecut_normal"], row["pawecutdg_normal"] = None, None
if p.has_hints:
hint = p.hint_for_accuracy(accuracy="normal")
row["ecut_normal"] = hint.ecut
if hint.pawecutdg: row["pawecutdg_normal"] = hint.pawecutdg
rows.append(row)
return pd.DataFrame(rows, index=index, columns=list(rows[0].keys()) if rows else None)
def __init__(self, pseudos, pseudo_dir="", structure=None, ndtset=1, comment="", decorators=None):
"""
Args:
pseudos: String or list of string with the name of the pseudopotential files.
pseudo_dir: Name of the directory where the pseudopotential files are located.
structure: file with the structure, :class:`Structure` object or dictionary with ABINIT geo variable
ndtset: Number of datasets.
comment: Optional string with a comment that will be placed at the beginning of the file.
decorators: List of `AbinitInputDecorator` objects.
"""
# Dataset[0] contains the global variables common to the different datasets
# Dataset[1:ndtset+1] stores the variables specific to the different datasets.
self._ndtset = ndtset
self._datasets = []
for i in range(ndtset+1):
dt0 = None
if i > 0: dt0 = self._datasets[0]
self._datasets.append(Dataset(index=i, dt0=dt0))
self._datasets[0]["ndtset"] = ndtset
# Setup of the pseudopotential files.
if isinstance(pseudos, PseudoTable):
self._pseudos = pseudos
elif all(isinstance(p, Pseudo) for p in pseudos):
self._pseudos = PseudoTable(pseudos)
else:
# String(s)
pseudo_dir = os.path.abspath(pseudo_dir)
pseudo_paths = [os.path.join(pseudo_dir, p) for p in list_strings(pseudos)]
missing = [p for p in pseudo_paths if not os.path.exists(p)]
if missing:
raise self.Error("Cannot find the following pseudopotential files:\n%s" % str(missing))
self._pseudos = PseudoTable(pseudo_paths)
if structure is not None: self.set_structure(structure)
if comment is not None: self.set_comment(comment)
self._decorators = [] if not decorators else decorators
def get_pseudotable(options):
"""Return PseudoTable object."""
if options.pseudos is not None:
from abipy.flowtk import PseudoTable
return PseudoTable.as_table(options.pseudos)
try:
from pseudo_dojo import OfficialTables
except ImportError as exc:
print("PseudoDojo package not installed. Please install it with `pip install pseudo_dojo`")
print("or use `--pseudos FILE_LIST` to specify the pseudopotentials to use.")
raise exc
dojo_tables = OfficialTables()
if options.usepaw:
raise NotImplementedError("PAW table is missing")
#pseudos = dojo_tables["ONCVPSP-PBE-PDv0.2-accuracy"]
else:
pseudos = dojo_tables["ONCVPSP-PBE-PDv0.2-accuracy"]
print("Using pseudos from PseudoDojo table", repr(pseudos))
return pseudos
def pseudos(*filenames):
"""Returns a PseudoTable constructed from the input filenames located in tests/data/pseudos."""
pseudos = list(map(pseudo, filenames))
return PseudoTable(pseudos)
from __future__ import unicode_literals, division, print_function, absolute_import
import os
_root = os.path.dirname(__file__)
_paths = [f for f in os.listdir(_root) if f.endswith("hgh")]
# Need one pseudo for element
d = {}
for p in _paths:
i = p.index(".")
head, tail = p[:i], p[i:]
d[head] = tail
_paths = [k + v for k, v in d.items()]
_paths = [os.path.join(_root, f) for f in _paths]
del d
from abipy.flowtk import PseudoTable
HGH_TABLE = PseudoTable(_paths)
# Add fake hints.
for pseudo in HGH_TABLE:
pseudo.dojo_report = {}
pseudo.dojo_report["hints"] = {}
for accuracy in ["low", "normal", "high"]:
pseudo.dojo_report["hints"][accuracy] = {"ecut": 50}
#assert pseudo.has_hints