mirror of https://github.com/abinit/abipy.git
Comment unused code
This commit is contained in:
gmatteo
parent
a3be17f57f
commit
1f8d8270a5
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@ -8,7 +8,7 @@ jobs:
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strategy:
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max-parallel: 4
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matrix:
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python-version: [3.8]
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python-version: [3.6]
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steps:
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- uses: actions/checkout@v1
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@ -32,9 +32,9 @@ jobs:
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# Replace dep1 dep2 ... with your dependencies
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conda create -q -n test-environment python=${{ matrix.python-version }}
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source activate test-environment
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conda install abinit -c abinit
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abinit -v
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abinit -b
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#conda install abinit -c abinit
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#`abinit -v
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#abinit -b
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- name: Install Python dependencies
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run: |
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python -m pip install --upgrade pip
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@ -536,7 +536,7 @@ class AbinitInputParser(object):
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This function is not recursive hence expr like sqrt(1/2) are not supported
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"""
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import math # flake8: noqa
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import math # noqa: F401
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import re
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re_sqrt = re.compile(r"[+|-]?sqrt\((.+)\)")
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@ -211,7 +211,8 @@ def build_bench_main_parser():
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parser.add_argument("--min-eff", default=None, type=float, help="Minimum parallel efficiency accepted. Default None.")
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parser.add_argument('--paw', default=False, action="store_true", help="Run PAW calculation if available")
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parser.add_argument("-a", '--abivalidate', default=False, action="store_true", help="Call Abinit to validate input files and return")
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parser.add_argument("-a", '--abivalidate', default=False, action="store_true",
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help="Call Abinit to validate input files and return")
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parser.add_argument("-i", '--info', default=False, action="store_true", help="Show benchmark info and exit")
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parser.add_argument("-r", "--remove", default=False, action="store_true", help="Remove old flow workdir")
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@ -19,7 +19,7 @@ def make_inputs(paw=False):
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# N=9
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# Supercell and atoms
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xcart= np.fromstring("""
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xcart = np.fromstring("""
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0.0000000000E+00 0.0000000000E+00 -4.2633349730E+00
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3.7794522658E+00 3.7794522658E+00 -3.2803418097E+00
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0.0000000000E+00 3.7794522658E+00 -3.6627278067E+00
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@ -55,7 +55,7 @@ def make_inputs(paw=False):
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structure = abilab.Structure.from_abivars(
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#acell="4.0 4.0 28.0 Angstrom",
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acell=abilab.ArrayWithUnit([4.0, 4.0, 28], "ang").to("bohr"),
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rprim=np.eye(3),
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rprim=np.eye(3),
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typat=[int(i) for i in "3 3 2 3 3 2 1 3 3 3 2 1 3 3 3 2 1 3 3 3 2 1 3 3 3 2 3 3 2".split()],
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znucl=[56, 22, 8],
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xcart=xcart,
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@ -135,7 +135,7 @@ def main(options):
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if options.info:
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# print doc string and exit.
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print(__doc__)
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return
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return
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return build_flow(options)
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@ -42,7 +42,7 @@ def make_input(): # pragma: no cover
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2.9570301511E+00 5.5992672027E-02 -1.3560839453E-01""", sep=" ").reshape((-1,3))
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structure = abilab.Structure.from_abivars(
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acell = abilab.ArrayWithUnit([10, 5, 5], "ang").to("bohr"),
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acell=abilab.ArrayWithUnit([10, 5, 5], "ang").to("bohr"),
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rprim=np.eye(3),
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typat=[1, 3, 3, 2, 3, 3, 3, 3], # Type of atoms (H2O + NH3 + H)
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znucl=[8.0, 7.0, 1.0],
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@ -136,8 +136,7 @@ def build_flow(options): # pragma: no cover
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# print("wfoptalg:", wfoptalg, "done with MPI_PROCS:", mpi_procs, "and:", d)
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# inp = template.new_with_vars(d)
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# work.register_scf_task(inp, manager=manager)
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#flow.register_work(work)
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#flow.register_work(work)
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return flow.allocate()
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@ -44,7 +44,6 @@ def make_inputs(paw=False):
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0.5, 0.5, 0.5]
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)
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multi[0].set_vars(
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kptopt=1, # Automatic generation of k points with symmetries.
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tolvrs=1.0e-6,
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@ -82,7 +82,7 @@ def make_flow_ephinp(options):
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# q-path for phonons and phonon linewidths.
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ph_ndivsm=20,
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ph_nqpath=3,
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ph_qpath= [
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ph_qpath=[
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0 , 0 , 0,
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0.5, 0 , 0,
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0.5, 0.5, 0,],
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@ -194,7 +194,7 @@ def build_flow(options):
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pconfs = [
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dict(npkpt=1, npband=13, npfft=10), # 130
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dict(npkpt=1, npband=26, npfft=10), # 260
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dict(npkpt=1, npband=65, npfft=8 ), # 520
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dict(npkpt=1, npband=65, npfft=8), # 520
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dict(npkpt=1, npband=65, npfft=16), # 1040
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]
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@ -61,6 +61,7 @@ global_vars = dict(
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#iomode=3
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)
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def make_inputs(options):
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structure = abilab.Structure.from_abivars(unit_cell)
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@ -1,6 +1,9 @@
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#!/usr/bin/env python
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"""Analyze the parallel efficiency of the MPI-FFT algorithsm in in the GS part.
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Use paral_kgb=1 and fftalg_list = [312, 402, 401]"""
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"""
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Analyze the parallel efficiency of the MPI-FFT algorithsm in in the GS part.
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Use paral_kgb=1 and fftalg_list = [312, 402, 401]
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"""
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import sys
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import abipy.abilab as abilab
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import abipy.flowtk as flowtk
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@ -25,7 +28,7 @@ def make_input(paw=False):
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ecut = 24
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inp.set_vars(
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ecut=ecut,
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pawecutdg=ecut*2 if paw else None,
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pawecutdg=ecut * 2 if paw else None,
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paral_kgb=1,
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nsppol=1,
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nband=28,
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@ -19,8 +19,7 @@ def make_input(paw=False):
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Build and return an input file for GS calculations with paral_kgb=1
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"""
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pseudos = abidata.pseudos("14si.pspnc", "8o.pspnc")
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#if not paw else
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#abidata.pseudos("Si.GGA_PBE-JTH-paw.xml")
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#if not paw else abidata.pseudos("Si.GGA_PBE-JTH-paw.xml")
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structure = abidata.structure_from_ucell("SiO2-alpha")
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inp = abilab.AbinitInput(structure, pseudos)
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@ -341,7 +341,7 @@ def build_flow(options):
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# Processor distribution.
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pconfs = [
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dict(npkpt=2, npband=8 , npfft=8 ), # 128
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dict(npkpt=2, npband=8 , npfft=8), # 128
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dict(npkpt=2, npband=8 , npfft=16), # 256
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dict(npkpt=2, npband=16, npfft=16), # 512
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dict(npkpt=2, npband=16, npfft=32), # 1024
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@ -194,8 +194,8 @@ def build_flow(options):
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# Processor distribution.
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pconfs = [
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dict(npkpt=2, npband=8 , npfft=8 ), # 128 processeurs
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dict(npkpt=2, npband=16, npfft=8 ), # 256 processeurs
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dict(npkpt=2, npband=8 , npfft=8), # 128 processeurs
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dict(npkpt=2, npband=16, npfft=8), # 256 processeurs
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dict(npkpt=2, npband=16, npfft=16), # 512 processeurs
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dict(npkpt=2, npband=16, npfft=32), # 1024 processeurs
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]
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@ -33,7 +33,7 @@ def make_inputs(paw=False):
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gs, nscf, scr, sigma = multi.split_datasets()
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# This grid is the most economical, but does not contain the Gamma point.
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ngkpt=[5, 5, 5]
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ngkpt = [5, 5, 5]
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gs_kmesh = dict(
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ngkpt=ngkpt,
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shiftk=[0.5, 0.5, 0.5,
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@ -30,7 +30,6 @@ def make_inputs(paw=False):
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paral_kgb=0,
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)
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multi.set_kmesh(
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ngkpt=[6,6,6],
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shiftk=[0.0, 0.0, 0.0],
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@ -26,7 +26,6 @@ def make_inputs(paw=False):
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timopt=-1,
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)
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multi.set_kmesh(ngkpt=[4,4,3], shiftk=[0.0, 0.0, 0.0])
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gs, nscf, scr, sigma = multi.split_datasets()
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@ -111,30 +111,30 @@ class ElectronInterpolator(metaclass=abc.ABCMeta):
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print("Trying to access valence band index with occtype:", self.occtype)
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return int(self.nelect // 2 - 1)
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def set_fermie(self, fermie, kmesh, is_shift=None):
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"""
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Change the Fermi level. Use the IDOS computed on the k-grid specifined by
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`kmesh` and `is_shift` to recompute the total number of electrons.
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#def set_fermie(self, fermie, kmesh, is_shift=None):
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# """
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# Change the Fermi level. Use the IDOS computed on the k-grid specifined by
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# `kmesh` and `is_shift` to recompute the total number of electrons.
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Args:
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fermie: New Fermi level in eV
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kmesh: Three integers with the number of divisions along the reciprocal primitive axes.
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is_shift: three integers (spglib API). When is_shift is not None, the kmesh is shifted along
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the axis in half of adjacent mesh points irrespective of the mesh numbers. None means unshited mesh.
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# Args:
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# fermie: New Fermi level in eV
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# kmesh: Three integers with the number of divisions along the reciprocal primitive axes.
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# is_shift: three integers (spglib API). When is_shift is not None, the kmesh is shifted along
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# the axis in half of adjacent mesh points irrespective of the mesh numbers. None means unshited mesh.
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Return:
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New value of `self.nelect`.
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"""
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# Compute DOS
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edos = self._get_cached_edos(kmesh, is_shift)
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#if edos is None:
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# edos = self.get_edos(kmesh, is_shift=is_shift, method="gaussian", step=0.1, width=0.2, wmesh=None)
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# self._cache_edos(kmesh, is_shift, edos)
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# Return:
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# New value of `self.nelect`.
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# """
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# # Compute DOS
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# edos = self._get_cached_edos(kmesh, is_shift)
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# #if edos is None:
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# # edos = self.get_edos(kmesh, is_shift=is_shift, method="gaussian", step=0.1, width=0.2, wmesh=None)
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# # self._cache_edos(kmesh, is_shift, edos)
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self.fermie = fermie
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# Find number of electrons from new chemical potential from nelect.
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self.nelect = idos.spline(fermie)
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return self.nelect
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# self.fermie = fermie
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# # Find number of electrons from new chemical potential from nelect.
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# self.nelect = idos.spline(fermie)
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# return self.nelect
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#def set_nelect(self, nelect, kmesh, is_shift=None):
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# """
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@ -222,67 +222,67 @@ class ElectronInterpolator(metaclass=abc.ABCMeta):
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return dict2namedtuple(mesh=wmesh, values=values, integral=integral)
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#return ElectronDos(wmesh, values, integral, is_shift, method, step, width)
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def get_jdos_q0(self, kmesh, is_shift=None, method="gaussian", step=0.1, width=0.2, wmesh=None):
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r"""
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Compute the join density of states at q==0
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#def get_jdos_q0(self, kmesh, is_shift=None, method="gaussian", step=0.1, width=0.2, wmesh=None):
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# r"""
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# Compute the join density of states at q==0
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:math:`\sum_{kbv} f_{vk} (1 - f_{ck}) \delta(\omega - E_{ck} + E_{vk})`
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# :math:`\sum_{kbv} f_{vk} (1 - f_{ck}) \delta(\omega - E_{ck} + E_{vk})`
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Args:
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kmesh: Three integers with the number of divisions along the reciprocal primitive axes.
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is_shift: three integers (spglib API). When is_shift is not None, the kmesh is shifted along
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the axis in half of adjacent mesh points irrespective of the mesh numbers. None means unshited mesh.
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method: String defining the method.
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step: Energy step (eV) of the linear mesh.
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width: Standard deviation (eV) of the gaussian.
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wmesh: Frequency mesh to use. If None, the mesh is computed automatically from the eigenvalues.
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# Args:
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# kmesh: Three integers with the number of divisions along the reciprocal primitive axes.
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# is_shift: three integers (spglib API). When is_shift is not None, the kmesh is shifted along
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# the axis in half of adjacent mesh points irrespective of the mesh numbers. None means unshited mesh.
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# method: String defining the method.
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# step: Energy step (eV) of the linear mesh.
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# width: Standard deviation (eV) of the gaussian.
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# wmesh: Frequency mesh to use. If None, the mesh is computed automatically from the eigenvalues.
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Returns:
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"""
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k = self.get_sampling(kmesh, is_shift)
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# Returns:
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# """
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# k = self.get_sampling(kmesh, is_shift)
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# Interpolate eigenvalues in the IBZ.
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eigens = self._get_cached_eigens(kmesh, is_shift, "ibz")
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if eigens is None:
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eigens = self.interp_kpts(k.ibz).eigens
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self._cache_eigens(kmesh, is_shift, eigens, "ibz")
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# # Interpolate eigenvalues in the IBZ.
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# eigens = self._get_cached_eigens(kmesh, is_shift, "ibz")
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# if eigens is None:
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# eigens = self.interp_kpts(k.ibz).eigens
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# self._cache_eigens(kmesh, is_shift, eigens, "ibz")
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wmesh, step = self._get_w2mesh_step(eigens, wmesh, step)
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nw = len(wmesh)
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values = np.zeros((self.nsppol, nw))
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# wmesh, step = self._get_w2mesh_step(eigens, wmesh, step)
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# nw = len(wmesh)
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# values = np.zeros((self.nsppol, nw))
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if self.occtype == "insulator":
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if method == "gaussian":
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for spin in range(self.nsppol):
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for ik, wtk in enumerate(k.weights):
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for icb in range(self.val_ib + 1, self.nband):
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ec = eigens[spin, ik, icb]
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for icv in range(self.val_ib):
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ev = eigens[spin, ik, icv]
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values[spin] += wtk * gaussian(wmesh, width, center=ec-ev)
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else:
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raise ValueError("Method %s is not supported" % method)
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# if self.occtype == "insulator":
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# if method == "gaussian":
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# for spin in range(self.nsppol):
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# for ik, wtk in enumerate(k.weights):
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# for icb in range(self.val_ib + 1, self.nband):
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# ec = eigens[spin, ik, icb]
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# for icv in range(self.val_ib):
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# ev = eigens[spin, ik, icv]
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# values[spin] += wtk * gaussian(wmesh, width, center=ec-ev)
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# else:
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# raise ValueError("Method %s is not supported" % method)
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else:
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#occfacts = self.
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if method == "gaussian":
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for spin in range(self.nsppol):
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for ik, wtk in enumerate(k.weights):
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for icb in conduction:
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ec = eigens[spin, ik, icb]
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fc = 1.0 - occfacts[spin, ik, icb]
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for icv in valence:
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ev = eigens[spin, ik, icv]
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fv = occfacts[spin, ik, icv]
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fact = wtk * fv * fc
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values[spin] += fact * gaussian(wmesh, width, center=ec-ev)
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else:
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raise ValueError("Method %s is not supported" % method)
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# else:
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# raise NotImplementedError("not insulator")
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# #if method == "gaussian":
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# # for spin in range(self.nsppol):
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# # for ik, wtk in enumerate(k.weights):
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# # for icb in conduction:
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# # ec = eigens[spin, ik, icb]
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# # fc = 1.0 - occfacts[spin, ik, icb]
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# # for icv in valence:
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# # ev = eigens[spin, ik, icv]
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# # fv = occfacts[spin, ik, icv]
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# # fact = wtk * fv * fc
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# # values[spin] += fact * gaussian(wmesh, width, center=ec-ev)
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# #else:
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# # raise ValueError("Method %s is not supported" % method)
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if self.nsppol == 1: values *= 2.0
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integral = scipy.integrate.cumtrapz(values, x=wmesh, initial=0.0)
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# if self.nsppol == 1: values *= 2.0
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# integral = scipy.integrate.cumtrapz(values, x=wmesh, initial=0.0)
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return dict2namedtuple(mesh=wmesh, values=values, integral=integral)
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# return dict2namedtuple(mesh=wmesh, values=values, integral=integral)
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#def get_jdos_qpts(self, qpoints, kmesh, is_shift=None, method="gaussian", step=0.1, width=0.2, wmesh=None):
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# qpoints = np.reshape(qpoints, (-1, 3))
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|
|
@ -307,44 +307,44 @@ class ElectronInterpolator(metaclass=abc.ABCMeta):
|
|||
# jdos_sqw *= 1. / k.nbz
|
||||
# return jdos_sqw
|
||||
|
||||
def get_nesting_at_e0(self, qpoints, kmesh, e0, width=0.2, is_shift=None):
|
||||
"""
|
||||
Compute the nesting factor with gaussian broadening for an arbitrary list of q-points.
|
||||
#def get_nesting_at_e0(self, qpoints, kmesh, e0, width=0.2, is_shift=None):
|
||||
# """
|
||||
# Compute the nesting factor with gaussian broadening for an arbitrary list of q-points.
|
||||
|
||||
Args:
|
||||
qpoints: List of q-points in reduced coordinates.
|
||||
kmesh: Three integers with the number of divisions along the reciprocal primitive axes.
|
||||
e0: Energy level in eV.
|
||||
width: Standard deviation (eV) of the gaussian.
|
||||
is_shift: three integers (spglib API). When is_shift is not None, the kmesh is shifted along
|
||||
the axis in half of adjacent mesh points irrespective of the mesh numbers. None means unshited mesh.
|
||||
# Args:
|
||||
# qpoints: List of q-points in reduced coordinates.
|
||||
# kmesh: Three integers with the number of divisions along the reciprocal primitive axes.
|
||||
# e0: Energy level in eV.
|
||||
# width: Standard deviation (eV) of the gaussian.
|
||||
# is_shift: three integers (spglib API). When is_shift is not None, the kmesh is shifted along
|
||||
# the axis in half of adjacent mesh points irrespective of the mesh numbers. None means unshited mesh.
|
||||
|
||||
Returns:
|
||||
numpy array of shape [self.nsppol, len(qpoints)]
|
||||
"""
|
||||
qpoints = np.reshape(qpoints, (-1, 3))
|
||||
k = self.get_sampling(kmesh, is_shift)
|
||||
# Returns:
|
||||
# numpy array of shape [self.nsppol, len(qpoints)]
|
||||
# """
|
||||
# qpoints = np.reshape(qpoints, (-1, 3))
|
||||
# k = self.get_sampling(kmesh, is_shift)
|
||||
|
||||
# Interpolate eigenvalues in the full BZ.
|
||||
eigens_kbz = self._get_cached_eigens(kmesh, is_shift, "bz")
|
||||
if eigens is None:
|
||||
eigens_kbz = self.interp_kpts(k.bz).eigens
|
||||
self._cache_eigens(kmesh, is_shift, eigens_kbz, "bz")
|
||||
# # Interpolate eigenvalues in the full BZ.
|
||||
# eigens_kbz = self._get_cached_eigens(kmesh, is_shift, "bz")
|
||||
# if eigens_kbz is None:
|
||||
# eigens_kbz = self.interp_kpts(k.bz).eigens
|
||||
# self._cache_eigens(kmesh, is_shift, eigens_kbz, "bz")
|
||||
|
||||
eigens_kbz = eigens_kbz - e0
|
||||
g_skb = gaussian(eigens_kbz, width)
|
||||
# eigens_kbz = eigens_kbz - e0
|
||||
# g_skb = gaussian(eigens_kbz, width)
|
||||
|
||||
# TODO: One could reduce the sum to IBZ(q) with appropriate weight.
|
||||
nest_sq = np.zeros((self.nsppol, len(qpoints)))
|
||||
for iq, qpt in enumerate(qpoints):
|
||||
kpq_bz = kbz + qpt
|
||||
eigens_kqbz = self.interp_kpts(kpq_bz).eigens - e0
|
||||
g_skqb = gaussian(eigens_kqbz, width)
|
||||
vals = g_skb * g_skqb
|
||||
nest_sq[:, iq] = vals.sum(axis=(1, 2))
|
||||
# # TODO: One could reduce the sum to IBZ(q) with appropriate weight.
|
||||
# nest_sq = np.zeros((self.nsppol, len(qpoints)))
|
||||
# for iq, qpt in enumerate(qpoints):
|
||||
# kpq_bz = kbz + qpt
|
||||
# eigens_kqbz = self.interp_kpts(kpq_bz).eigens - e0
|
||||
# g_skqb = gaussian(eigens_kqbz, width)
|
||||
# vals = g_skb * g_skqb
|
||||
# nest_sq[:, iq] = vals.sum(axis=(1, 2))
|
||||
|
||||
nest_sq *= 1. / k.nbz
|
||||
return nest_sq
|
||||
# nest_sq *= 1. / k.nbz
|
||||
# return nest_sq
|
||||
|
||||
def _get_wmesh_step(self, eigens, wmesh, step):
|
||||
if wmesh is not None:
|
||||
|
|
@ -467,112 +467,112 @@ class ElectronInterpolator(metaclass=abc.ABCMeta):
|
|||
|
||||
return fig
|
||||
|
||||
@add_fig_kwargs
|
||||
def plot_jdosq0_vs_kmeshes(self, kmeshes, is_shift=None, method="gaussian", step=0.1, width=0.2,
|
||||
ax=None, fontsize=12, **kwargs):
|
||||
"""
|
||||
Plot (interpolated) Joint DOSes at q=0 computed with different meshes.
|
||||
#@add_fig_kwargs
|
||||
#def plot_jdosq0_vs_kmeshes(self, kmeshes, is_shift=None, method="gaussian", step=0.1, width=0.2,
|
||||
# ax=None, fontsize=12, **kwargs):
|
||||
# """
|
||||
# Plot (interpolated) Joint DOSes at q=0 computed with different meshes.
|
||||
|
||||
Args:
|
||||
kmeshes: List of kmeshes. Each item is given by three integers with the number of
|
||||
divisions along the reciprocal primitive axes.
|
||||
is_shift: three integers (spglib API). If None, the kmesh is shifted along
|
||||
the axis in half of adjacent mesh points irrespective of the mesh numbers. None means unshited mesh.
|
||||
method: String defining the method for the computation of the DOS.
|
||||
step: Energy step (eV) of the linear mesh.
|
||||
width: Standard deviation (eV) of the gaussian.
|
||||
ax: |matplotlib-Axes| or None if a new figure should be created.
|
||||
fontsize: Legend and title fontsize.
|
||||
# Args:
|
||||
# kmeshes: List of kmeshes. Each item is given by three integers with the number of
|
||||
# divisions along the reciprocal primitive axes.
|
||||
# is_shift: three integers (spglib API). If None, the kmesh is shifted along
|
||||
# the axis in half of adjacent mesh points irrespective of the mesh numbers. None means unshited mesh.
|
||||
# method: String defining the method for the computation of the DOS.
|
||||
# step: Energy step (eV) of the linear mesh.
|
||||
# width: Standard deviation (eV) of the gaussian.
|
||||
# ax: |matplotlib-Axes| or None if a new figure should be created.
|
||||
# fontsize: Legend and title fontsize.
|
||||
|
||||
Returns: |matplotlib-Figure|
|
||||
"""
|
||||
ax, fig, plt = get_ax_fig_plt(ax=ax)
|
||||
kmeshes = np.reshape(np.asarray(kmeshes, dtype=np.int), (-1, 3))
|
||||
for kmesh in kmeshes:
|
||||
jdos = self.get_jdos_q0(kmesh, is_shift=is_shift, method=method, step=step, width=width)
|
||||
for spin in range(self.nsppol):
|
||||
spin_sign = +1 if spin == 0 else -1
|
||||
ax.plot(jdos.mesh, jdos.values[spin] * spin_sign, label=str(kmesh) if spin == 0 else None)
|
||||
# Returns: |matplotlib-Figure|
|
||||
# """
|
||||
# ax, fig, plt = get_ax_fig_plt(ax=ax)
|
||||
# kmeshes = np.reshape(np.asarray(kmeshes, dtype=np.int), (-1, 3))
|
||||
# for kmesh in kmeshes:
|
||||
# jdos = self.get_jdos_q0(kmesh, is_shift=is_shift, method=method, step=step, width=width)
|
||||
# for spin in range(self.nsppol):
|
||||
# spin_sign = +1 if spin == 0 else -1
|
||||
# ax.plot(jdos.mesh, jdos.values[spin] * spin_sign, label=str(kmesh) if spin == 0 else None)
|
||||
|
||||
ax.grid(True)
|
||||
ax.set_xlabel("Energy (eV)")
|
||||
ax.set_ylabel('JDOS (states/eV)')
|
||||
ax.legend(loc="best", fontsize=fontsize, shadow=True)
|
||||
# ax.grid(True)
|
||||
# ax.set_xlabel("Energy (eV)")
|
||||
# ax.set_ylabel('JDOS (states/eV)')
|
||||
# ax.legend(loc="best", fontsize=fontsize, shadow=True)
|
||||
|
||||
return fig
|
||||
# return fig
|
||||
|
||||
@add_fig_kwargs
|
||||
def plot_nesting_vs_widths(self, widths, kmesh, e0=None, qvertices_names=None,
|
||||
line_density=20, is_shift=None, ax=None, fontsize=12, **kwargs):
|
||||
"""
|
||||
Plot (interpolated) nesting factor computed with different broadening.
|
||||
#@add_fig_kwargs
|
||||
#def plot_nesting_vs_widths(self, widths, kmesh, e0=None, qvertices_names=None,
|
||||
# line_density=20, is_shift=None, ax=None, fontsize=12, **kwargs):
|
||||
# """
|
||||
# Plot (interpolated) nesting factor computed with different broadening.
|
||||
|
||||
Args:
|
||||
widths: List of standard deviations (eV) of the gaussian.
|
||||
kmeshes: List of kmeshes. Each item is given by three integers with the number of
|
||||
divisions along the reciprocal primitive axes.
|
||||
e0: Energy level in eV.
|
||||
qvertices_names
|
||||
line_density:
|
||||
is_shift: three integers (spglib API). When is_shift is not None, the kmesh is shifted along
|
||||
the axis in half of adjacent mesh points irrespective of the mesh numbers. None means unshited mesh.
|
||||
ax: |matplotlib-Axes| or None if a new figure should be created.
|
||||
fontsize: Legend and title fontsize.
|
||||
# Args:
|
||||
# widths: List of standard deviations (eV) of the gaussian.
|
||||
# kmeshes: List of kmeshes. Each item is given by three integers with the number of
|
||||
# divisions along the reciprocal primitive axes.
|
||||
# e0: Energy level in eV.
|
||||
# qvertices_names
|
||||
# line_density:
|
||||
# is_shift: three integers (spglib API). When is_shift is not None, the kmesh is shifted along
|
||||
# the axis in half of adjacent mesh points irrespective of the mesh numbers. None means unshited mesh.
|
||||
# ax: |matplotlib-Axes| or None if a new figure should be created.
|
||||
# fontsize: Legend and title fontsize.
|
||||
|
||||
Returns: |matplotlib-Figure|
|
||||
"""
|
||||
ax, fig, plt = get_ax_fig_plt(ax=ax)
|
||||
qpoints = self._get_kpts_kticks_klabels(ax, qvertices_names, line_density)
|
||||
# Returns: |matplotlib-Figure|
|
||||
# """
|
||||
# ax, fig, plt = get_ax_fig_plt(ax=ax)
|
||||
# qpoints = self._get_kpts_kticks_klabels(ax, qvertices_names, line_density)
|
||||
|
||||
e0 = self.interpolated_fermie if e0 is None else e0
|
||||
for width in np.asarray(widths):
|
||||
nest_sq = self.get_nesting_at_e0(qpoints, kmesh, e0, width=width, is_shift=is_shift)
|
||||
for spin in range(self.nsppol):
|
||||
spin_sign = +1 if spin == 0 else -1
|
||||
ax.plot(nest_sq[spin] * spin_sign, label=str(kmesh) if spin == 0 else None)
|
||||
# e0 = self.interpolated_fermie if e0 is None else e0
|
||||
# for width in np.asarray(widths):
|
||||
# nest_sq = self.get_nesting_at_e0(qpoints, kmesh, e0, width=width, is_shift=is_shift)
|
||||
# for spin in range(self.nsppol):
|
||||
# spin_sign = +1 if spin == 0 else -1
|
||||
# ax.plot(nest_sq[spin] * spin_sign, label=str(kmesh) if spin == 0 else None)
|
||||
|
||||
ax.grid(True)
|
||||
ax.set_ylabel('Nesting factor')
|
||||
ax.legend(loc="best", fontsize=fontsize, shadow=True)
|
||||
# ax.grid(True)
|
||||
# ax.set_ylabel('Nesting factor')
|
||||
# ax.legend(loc="best", fontsize=fontsize, shadow=True)
|
||||
|
||||
return fig
|
||||
# return fig
|
||||
|
||||
@add_fig_kwargs
|
||||
def plot_nesting_vs_kmeshes(self, width, kmeshes, e0=None, qvertices_names=None, line_density=20,
|
||||
is_shift=None, ax=None, fontsize=12, **kwargs):
|
||||
"""
|
||||
Plot (interpolated) nesting factor computed with different k-meshes.
|
||||
#@add_fig_kwargs
|
||||
#def plot_nesting_vs_kmeshes(self, width, kmeshes, e0=None, qvertices_names=None, line_density=20,
|
||||
# is_shift=None, ax=None, fontsize=12, **kwargs):
|
||||
# """
|
||||
# Plot (interpolated) nesting factor computed with different k-meshes.
|
||||
|
||||
Args:
|
||||
width: Gaussian broadening (eV).
|
||||
kmeshes: List of kmeshes. Each item is given by three integers with the number of
|
||||
divisions along the reciprocal primitive axes.
|
||||
e0: Energy level in eV.
|
||||
qvertices_names
|
||||
line_density:
|
||||
is_shift: three integers (spglib API). When is_shift is not None, the kmesh is shifted along
|
||||
the axis in half of adjacent mesh points irrespective of the mesh numbers. None means unshited mesh.
|
||||
ax: |matplotlib-Axes| or None if a new figure should be created.
|
||||
fontsize: legend and title fontsize.
|
||||
# Args:
|
||||
# width: Gaussian broadening (eV).
|
||||
# kmeshes: List of kmeshes. Each item is given by three integers with the number of
|
||||
# divisions along the reciprocal primitive axes.
|
||||
# e0: Energy level in eV.
|
||||
# qvertices_names
|
||||
# line_density:
|
||||
# is_shift: three integers (spglib API). When is_shift is not None, the kmesh is shifted along
|
||||
# the axis in half of adjacent mesh points irrespective of the mesh numbers. None means unshited mesh.
|
||||
# ax: |matplotlib-Axes| or None if a new figure should be created.
|
||||
# fontsize: legend and title fontsize.
|
||||
|
||||
Returns: |matplotlib-Figure|
|
||||
"""
|
||||
ax, fig, plt = get_ax_fig_plt(ax=ax)
|
||||
qpoints = self._get_kpts_kticks_klabels(ax, qvertices_names, line_density)
|
||||
# Returns: |matplotlib-Figure|
|
||||
# """
|
||||
# ax, fig, plt = get_ax_fig_plt(ax=ax)
|
||||
# qpoints = self._get_kpts_kticks_klabels(ax, qvertices_names, line_density)
|
||||
|
||||
kmeshes = np.reshape(np.asarray(kmeshes, dtype=np.int), (-1, 3))
|
||||
e0 = self.interpolated_fermie if e0 is None else e0
|
||||
for kmesh in kmeshes:
|
||||
nest_sq = self.get_nesting_at_e0(qpoints, kmesh, e0, width=width, is_shift=is_shift)
|
||||
for spin in range(self.nsppol):
|
||||
spin_sign = +1 if spin == 0 else -1
|
||||
ax.plot(nest_sq[spin] * spin_sign, label=str(kmesh) if spin == 0 else None)
|
||||
# kmeshes = np.reshape(np.asarray(kmeshes, dtype=np.int), (-1, 3))
|
||||
# e0 = self.interpolated_fermie if e0 is None else e0
|
||||
# for kmesh in kmeshes:
|
||||
# nest_sq = self.get_nesting_at_e0(qpoints, kmesh, e0, width=width, is_shift=is_shift)
|
||||
# for spin in range(self.nsppol):
|
||||
# spin_sign = +1 if spin == 0 else -1
|
||||
# ax.plot(nest_sq[spin] * spin_sign, label=str(kmesh) if spin == 0 else None)
|
||||
|
||||
ax.grid(True)
|
||||
ax.set_ylabel('Nesting factor')
|
||||
ax.legend(loc="best", fontsize=fontsize, shadow=True)
|
||||
# ax.grid(True)
|
||||
# ax.set_ylabel('Nesting factor')
|
||||
# ax.legend(loc="best", fontsize=fontsize, shadow=True)
|
||||
|
||||
return fig
|
||||
# return fig
|
||||
|
||||
#@add_fig_kwargs
|
||||
#def plot_group_velocites(self, vertices_names=None, line_density=20, ax=None, **kwargs):
|
||||
|
|
|
|||
|
|
@ -62,7 +62,7 @@ class TestSkwInterpolator(AbipyTest):
|
|||
|
||||
# Test interpolation routines (high-level API).
|
||||
edos = skw.get_edos(kmesh, is_shift=None, method="gaussian", step=0.1, width=0.2, wmesh=None)
|
||||
jdos = skw.get_jdos_q0(kmesh, is_shift=None, method="gaussian", step=0.1, width=0.2, wmesh=None)
|
||||
#jdos = skw.get_jdos_q0(kmesh, is_shift=None, method="gaussian", step=0.1, width=0.2, wmesh=None)
|
||||
#nest = skw.get_nesting_at_e0(qpoints, kmesh, e0, width=0.2, is_shift=None)
|
||||
|
||||
# Test pickle
|
||||
|
|
@ -76,7 +76,7 @@ class TestSkwInterpolator(AbipyTest):
|
|||
widths = [0.2, 0.3]
|
||||
is_shift = None
|
||||
assert skw.plot_dos_vs_kmeshes(kmeshes, is_shift=is_shift, show=False)
|
||||
assert skw.plot_jdosq0_vs_kmeshes(kmeshes, is_shift=is_shift, show=False)
|
||||
#assert skw.plot_jdosq0_vs_kmeshes(kmeshes, is_shift=is_shift, show=False)
|
||||
|
||||
#assert skw.plot_nesting_vs_widths(widths=widths, kmesh=[4, 4, 4], e0=None, qvertices_names=None,
|
||||
# line_density=5, is_shift=is_shift, show=False)
|
||||
|
|
|
|||
|
|
@ -17,6 +17,7 @@ import abipy.flowtk as flowtk
|
|||
def build_flow(options):
|
||||
# Working directory (default is the name of the script with '.py' removed and "run_" replaced by "flow_")
|
||||
if not options.workdir:
|
||||
__file__ = os.path.join(os.getcwd(), "run_eph_al.py")
|
||||
options.workdir = os.path.basename(__file__).replace(".py", "").replace("run_", "flow_")
|
||||
|
||||
# Preparatory run for E-PH calculations.
|
||||
|
|
@ -43,20 +44,17 @@ def build_flow(options):
|
|||
gs_inp = abilab.AbinitInput(structure, pseudos)
|
||||
|
||||
gs_inp.set_vars(
|
||||
istwfk="*1",
|
||||
ecut=8.0,
|
||||
nband=5,
|
||||
occopt=7, # include metallic occupation function with a small smearing
|
||||
tsmear=0.04,
|
||||
tolvrs=1e-7,
|
||||
#timeopt=-1,
|
||||
)
|
||||
|
||||
# The kpoint grid is minimalistic to keep the calculation manageable.
|
||||
gs_inp.set_kmesh(
|
||||
ngkpt=[8, 8, 8],
|
||||
shiftk=[0.0, 0.0, 0.0],
|
||||
#kptopt=3,
|
||||
)
|
||||
|
||||
# Phonon calculation with 4x4x4
|
||||
|
|
@ -76,10 +74,10 @@ def build_flow(options):
|
|||
# Build input file for E-PH run.
|
||||
eph_inp = gs_inp.new_with_vars(
|
||||
optdriver=7,
|
||||
ddb_ngqpt=ddb_ngqpt, # q-mesh used to produce the DDB file (must be consistent with DDB data)
|
||||
eph_intmeth=2, # Tetra method
|
||||
eph_fsewin="0.8 eV", # Energy window around Ef
|
||||
eph_mustar=0.12, # mustar parameter
|
||||
ddb_ngqpt=ddb_ngqpt, # q-mesh used to produce the DDB file (must be consistent with DDB data)
|
||||
eph_intmeth=2, # Tetra method
|
||||
eph_fsewin="0.8 eV", # Energy window around Ef
|
||||
eph_mustar=0.12, # mustar parameter
|
||||
eph_ngqpt_fine=eph_ngqpt_fine, # Interpolate DFPT potentials if != ddb_ngqpt
|
||||
)
|
||||
|
||||
|
|
@ -98,11 +96,12 @@ def build_flow(options):
|
|||
|
||||
# This block generates the thumbnails in the Abipy gallery.
|
||||
# You can safely REMOVE this part if you are using this script for production runs.
|
||||
if os.getenv("GENERATE_SPHINX_GALLERY", False):
|
||||
if os.getenv("READTHEDOCS", False):
|
||||
__name__ = None
|
||||
import tempfile
|
||||
options = flowtk.build_flow_main_parser().parse_args(["-w", tempfile.mkdtemp()])
|
||||
build_flow(options).plot_networkx(tight_layout=True)
|
||||
build_flow(options).graphviz_imshow()
|
||||
#build_flow(options).plot_networkx(tight_layout=True)
|
||||
|
||||
|
||||
@flowtk.flow_main
|
||||
|
|
@ -2382,7 +2382,7 @@ class Task(Node, metaclass=abc.ABCMeta):
|
|||
self.history.info("Removed files: %s" % paths)
|
||||
return paths
|
||||
|
||||
def setup(self): # flake8: noqa
|
||||
def setup(self): # noqa: E731
|
||||
"""Base class does not provide any hook."""
|
||||
|
||||
#@check_spectator
|
||||
|
|
|
|||
|
|
@ -6,9 +6,9 @@ import numpy as np
|
|||
import pandas as pd
|
||||
|
||||
from pymatgen.core.tensors import Tensor, SquareTensor
|
||||
from pymatgen.analysis.elasticity.elastic import ElasticTensor # flake8: noqa
|
||||
from pymatgen.analysis.elasticity.elastic import ElasticTensor # noqa: F401
|
||||
from pymatgen.analysis.elasticity.stress import Stress as pmg_Stress
|
||||
from pymatgen.analysis.piezo import PiezoTensor # flake8: noqa
|
||||
from pymatgen.analysis.piezo import PiezoTensor # noqa: F401
|
||||
from abipy.iotools import ETSF_Reader
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,114 +0,0 @@
|
|||
#!/bin/bash
|
||||
|
||||
import netCDF4 as nc
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
import matplotlib.image as mpimg
|
||||
import copy
|
||||
from matplotlib.colors import LogNorm
|
||||
|
||||
class Hexc(object):
|
||||
|
||||
def __init__(self, nsppol, nkpt, nval, ncond, hsize, ham, kpt, vcks2t,lomo, homo,lumo,humo,diag):
|
||||
|
||||
self.nsppol = nsppol
|
||||
self.nkpt = nkpt
|
||||
self.nval = nval
|
||||
self.ncond = ncond
|
||||
self.hsize = hsize
|
||||
self.ham = ham
|
||||
self.vcks2t = vcks2t
|
||||
self.kpt = kpt
|
||||
|
||||
self.lomo = lomo
|
||||
self.lumo = lumo
|
||||
self.homo = homo
|
||||
self.humo = humo
|
||||
self.diag = diag
|
||||
|
||||
@classmethod
|
||||
def from_file(cls,filename):
|
||||
root = nc.Dataset(filename, 'r')
|
||||
nsppol = len(root.dimensions['number_of_spins'])
|
||||
nkpt = len(root.dimensions['number_of_kpoints'])
|
||||
nval = len(root.dimensions['max_number_of_valence_bands'])
|
||||
ncond = len(root.dimensions['max_number_of_conduction_bands'])
|
||||
hsize = len(root.dimensions['total_number_of_transitions'])
|
||||
|
||||
kpt = root.variables['reduced_coordinates_of_kpoints'][:,:] # Nkpt, 3
|
||||
ham = root.variables['hamiltonian'][:,:,:] # Itp, It, [0,1]
|
||||
|
||||
ham_c = np.vectorize(complex)(ham[:,:,0],ham[:,:,1])
|
||||
vcks2t = root.variables['vcks2t'][:,:,:,:] # S, K, C, V
|
||||
|
||||
lomo = root.variables['lomo'][:]
|
||||
homo = root.variables['homo'][:]
|
||||
lumo = root.variables['lumo'][:]
|
||||
humo = root.variables['humo'][:]
|
||||
diag = root.variables['diagonal'][:,:]
|
||||
diag_c = np.vectorize(complex)(diag[:,0],diag[:,1])
|
||||
|
||||
return cls(nsppol, nkpt, nval, ncond, hsize, ham_c, kpt, vcks2t, lomo, homo, lumo, humo, diag_c)
|
||||
|
||||
def plot(self,ic=None,iv=None,icp=None,ivp=None,list_ikpt=None, title=None):
|
||||
fullmat = None
|
||||
chk_bands = (ic is not None and iv is not None and icp is not None and ivp is not None)
|
||||
|
||||
if not chk_bands:
|
||||
fullmat = self.ham
|
||||
else:
|
||||
fullmat = np.zeros((self.nkpt,self.nkpt),dtype=np.complex)
|
||||
for is1 in np.arange(self.nsppol):
|
||||
for is2 in np.arange(self.nsppol):
|
||||
for ik in np.arange(self.nkpt):
|
||||
for ikp in np.arange(self.nkpt):
|
||||
it = self.vcks2t[is1,ik,ic-self.lumo[is1],iv-self.lomo[is1]]-1
|
||||
itp = self.vcks2t[is2,ikp,icp-self.lumo[is2],ivp-self.lomo[is2]]-1
|
||||
fullmat[ik,ikp] = self.ham[it,itp] # Fortran -> python
|
||||
|
||||
mymat = None
|
||||
if list_ikpt is None:
|
||||
mymat = fullmat
|
||||
else:
|
||||
nkpt2 = len(list_ikpt)
|
||||
mymat = np.zeros((nkpt2,nkpt2),dtype=np.complex)
|
||||
if chk_bands:
|
||||
for ik1 in np.arange(nkpt2):
|
||||
for ik2 in np.arange(nkpt2):
|
||||
mymat[ik1,ik2] = fullmat[list_ikpt[ik1],list_ikpt[ik2]]
|
||||
else:
|
||||
mymat = np.zeros((self.nval*self.ncond*nkpt2,self.nval*self.ncond*nkpt2))
|
||||
it2 = 0
|
||||
for is1 in np.arange(self.nsppol):
|
||||
for ik in np.arange(nkpt2):
|
||||
for ic in np.arange(self.lumo,self.humo+1):
|
||||
for iv in np.arange(self.lomo,self.homo+1):
|
||||
itp2 = 0
|
||||
for is2 in np.arange(self.nsppol):
|
||||
for ikp in np.arange(nkpt2):
|
||||
for icp in np.arange(self.lumo,self.humo+1):
|
||||
for ivp in np.arange(self.lomo,self.homo+1):
|
||||
it = self.vcks2t[is1,list_ikpt[ik],ic-self.lumo[is1],iv-self.lomo[is1]]-1
|
||||
itp = self.vcks2t[is2,list_ikpt[ikp],icp-self.lumo[is2],ivp-self.lomo[is2]]-1
|
||||
mymat[it2,itp2] = self.ham[it,itp] # Fortran -> python
|
||||
itp2 += 1
|
||||
it2 += 1
|
||||
|
||||
fig = plt.figure()
|
||||
imgplot = plt.imshow(np.abs(mymat)*self.nkpt,norm=LogNorm(vmin=1e-5,vmax=10),interpolation='none')
|
||||
if title is not None:
|
||||
plt.title(title)
|
||||
plt.colorbar()
|
||||
|
||||
def get_filtered_kpt(self,xval=None,yval=None,zval=None):
|
||||
|
||||
list_ikpt = []
|
||||
|
||||
for ikpt in np.arange(self.nkpt):
|
||||
if ( (xval is None or np.abs(self.kpt[ikpt,0]-xval) < 1e-8)
|
||||
and (yval is None or np.abs(self.kpt[ikpt,1]-yval) < 1e-8)
|
||||
and (zval is None or np.abs(self.kpt[ikpt,2]-zval) < 1e-8)):
|
||||
list_ikpt.append(ikpt)
|
||||
|
||||
return list_ikpt
|
||||
|
||||
|
|
@ -1,51 +0,0 @@
|
|||
#!/bin/bash
|
||||
|
||||
import netCDF4 as nc
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
import matplotlib.image as mpimg
|
||||
import copy
|
||||
from hexc import Hexc
|
||||
|
||||
if __name__ == '__main__':
|
||||
ham2 = Hexc.from_file('t31o_DS3_HEXC.nc')
|
||||
ham3 = Hexc.from_file('t31o_DS5_HEXC.nc')
|
||||
ham4 = Hexc.from_file('t32o_DS1_HEXC_I.nc')
|
||||
ham5 = Hexc.from_file('t33o_DS1_HEXC_I.nc')
|
||||
ham6 = Hexc.from_file('t34o_DS1_HEXC_I.nc')
|
||||
|
||||
list_ikpt2 = None
|
||||
list_ikpt3 = None
|
||||
list_ikpt4 = None
|
||||
list_ikpt5 = None
|
||||
list_ikpt6 = None
|
||||
|
||||
#yval = 0.06
|
||||
#zval = 0.065
|
||||
|
||||
#list_ikpt2 = ham2.get_filtered_kpt(yval=yval,zval=zval)
|
||||
#list_ikpt3 = ham3.get_filtered_kpt(yval=yval,zval=zval)
|
||||
#list_ikpt4 = ham4.get_filtered_kpt(yval=yval,zval=zval)
|
||||
#list_ikpt5 = ham5.get_filtered_kpt(yval=yval,zval=zval)
|
||||
#list_ikpt6 = ham6.get_filtered_kpt(yval=yval,zval=zval)
|
||||
|
||||
ham2.ham[:,:] = ham2.ham[:,:] - np.diag(ham2.diag[:])
|
||||
ham3.ham[:,:] = ham3.ham[:,:] - np.diag(ham3.diag[:])
|
||||
|
||||
icval = 4
|
||||
ivval = 1
|
||||
icpval = 4
|
||||
ivpval = 1
|
||||
|
||||
ham2.plot(ic=icval,iv=ivval,icp=icpval,ivp=ivpval,list_ikpt=list_ikpt2,title='Coarse')
|
||||
ham3.plot(ic=icval,iv=ivval,icp=icpval,ivp=ivpval,list_ikpt=list_ikpt3,title='Dense')
|
||||
ham4.plot(ic=icval,iv=ivval,icp=icpval,ivp=ivpval,list_ikpt=list_ikpt4,title='M1')
|
||||
ham5.plot(ic=icval,iv=ivval,icp=icpval,ivp=ivpval,list_ikpt=list_ikpt5,title='M2')
|
||||
ham6.plot(ic=icval,iv=ivval,icp=icpval,ivp=ivpval,list_ikpt=list_ikpt6,title='M3')
|
||||
|
||||
plt.show()
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
|
@ -1,147 +0,0 @@
|
|||
"""
|
||||
This module installs a hook for the built-in open so that one can detect if there are
|
||||
files that have not been closed. To install the hook, import the module in the script
|
||||
and call install. Example
|
||||
|
||||
import open_hook
|
||||
|
||||
# Install the hook
|
||||
open_hook.install()
|
||||
|
||||
# Show open files.
|
||||
open_hook.print_open_files()
|
||||
|
||||
# Remove the hook
|
||||
open_hook.remove()
|
||||
|
||||
Initial version taken from
|
||||
http://stackoverflow.com/questions/2023608/check-what-files-are-open-in-python
|
||||
"""
|
||||
from __future__ import print_function, division, unicode_literals
|
||||
|
||||
import sys
|
||||
try:
|
||||
import __builtin__
|
||||
except ImportError:
|
||||
# Py3k
|
||||
import builtins as __builtin__
|
||||
|
||||
# Save the builtin version (do not change!)
|
||||
_builtin_file = __builtin__.file
|
||||
_builtin_open = __builtin__.open
|
||||
|
||||
# Global variables used to control the logging volume and the log file.
|
||||
_VERBOSE = 1
|
||||
_LOGFILE = sys.stdout
|
||||
|
||||
|
||||
def set_options(**kwargs):
|
||||
"""Set the value of verbose and logfile."""
|
||||
verbose = kwargs.get("verbose", None)
|
||||
if verbose is not None:
|
||||
_VERBOSE = verbose
|
||||
|
||||
logfile = kwargs.get("logfile", None)
|
||||
if logfile is not None:
|
||||
_LOGFILE = logfile
|
||||
|
||||
|
||||
# Set of files that have been opened in the python code.
|
||||
_openfiles = set()
|
||||
|
||||
|
||||
def print_open_files(file=sys.stdout):
|
||||
"""Print the list of the files that are still open."""
|
||||
print("### %d OPEN FILES: [%s]" % (len(_openfiles), ", ".join(f._x for f in _openfiles)), file=file)
|
||||
|
||||
|
||||
def num_openfiles():
|
||||
"""Number of files in use."""
|
||||
return len(_openfiles)
|
||||
|
||||
|
||||
def clear_openfiles():
|
||||
"""Reinitialize the set of open files."""
|
||||
_openfiles = set()
|
||||
|
||||
|
||||
class _newfile(_builtin_file):
|
||||
def __init__(self, *args, **kwargs):
|
||||
self._x = args[0]
|
||||
|
||||
if _VERBOSE:
|
||||
print("### OPENING %s ###" % str(self._x), file=_LOGFILE)
|
||||
|
||||
_builtin_file.__init__(self, *args, **kwargs)
|
||||
_openfiles.add(self)
|
||||
|
||||
def close(self):
|
||||
if _VERBOSE:
|
||||
print("### CLOSING %s ###" % str(self._x), file=_LOGFILE)
|
||||
|
||||
_builtin_file.close(self)
|
||||
try:
|
||||
_openfiles.remove(self)
|
||||
except KeyError:
|
||||
print("File %s is not in openfiles set" % self)
|
||||
|
||||
|
||||
def _newopen(*args, **kwargs):
|
||||
"""Replacement for python open."""
|
||||
return _newfile(*args, **kwargs)
|
||||
|
||||
|
||||
def install():
|
||||
"""Install the hook."""
|
||||
__builtin__.file = _newfile
|
||||
__builtin__.open = _newopen
|
||||
|
||||
|
||||
def remove():
|
||||
"""Remove the hook."""
|
||||
__builtin__.file = _builtin_file = __builtin__.file
|
||||
__builtin__.open = _builtin_open = __builtin__.open
|
||||
|
||||
|
||||
def test_open_hook():
|
||||
"""Unit tests for open_hook"""
|
||||
import unittest
|
||||
import tempfile
|
||||
|
||||
py3k = False
|
||||
try:
|
||||
import __builtin__
|
||||
except ImportError:
|
||||
py3k = True
|
||||
import builtins as __builtin__
|
||||
|
||||
|
||||
@unittest.skipIf(py3k, "OpenHook not compatible with py3k")
|
||||
class OpenHookTest(unittest.TestCase):
|
||||
"""Test open_hook module."""
|
||||
def setUp(self):
|
||||
from abipy.tools import open_hook
|
||||
self.open_hook = open_hook
|
||||
self.open_hook.install()
|
||||
|
||||
def test_open(self):
|
||||
"""Test if open_hook detects open files."""
|
||||
self.assertEqual(self.open_hook.num_openfiles(), 0)
|
||||
|
||||
_, fname = tempfile.mkstemp()
|
||||
fh = open(fname)
|
||||
|
||||
self.open_hook.print_open_files()
|
||||
self.assertEqual(self.open_hook.num_openfiles(), 1)
|
||||
|
||||
def tearDown(self):
|
||||
self.open_hook.remove()
|
||||
# Here we should have the __builtin__ version
|
||||
|
||||
self.assertTrue(file is __builtin__.file)
|
||||
self.assertTrue(open is __builtin__.open)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import unittest
|
||||
unittest.main()
|
||||
|
|
@ -13,20 +13,20 @@ universal=1
|
|||
[nosetests]
|
||||
verbosity=0
|
||||
with-doctest=1
|
||||
exclude-dir=abipy/gui
|
||||
exclude-dir=abipy/gui
|
||||
|
||||
[pycodestyle]
|
||||
count = True
|
||||
max-line-length = 130
|
||||
statistics = True
|
||||
ignore = E116,E121,E122,E123,E124,E126,E128,E129,E131,E133,E201,E203,E226,E231,E241,E242,E261,E262,E265,E266,E306,E401,E402,E704,W503,W504,W505,E701,E702,E731,E741,W605
|
||||
exclude= .git,__pycache__,abipy/gui,abipy/abio/abivar_database,dev_scripts,docs,.ipynb_checkpoints,abipy/examples/flows/develop/,test_*.py,abipy/benchmarks,abipy/data/refs
|
||||
ignore = E114,E116,E121,E122,E123,E124,E126,E127,E128,E129,E131,E133,E201,E203,E226,E231,E241,E242,E261,E262,E265,E266,E306,E401,E402,E704,W503,W504,W505,E701,E702,E731,E741,W605
|
||||
exclude= .git,__pycache__,abipy/gui,abipy/abio/abivar_database,dev_scripts,docs,.ipynb_checkpoints,abipy/examples/flows/develop/,test_*.py,,abipy/data/refs
|
||||
|
||||
[flake8]
|
||||
# max-complexity = 10
|
||||
max-line-length = 130
|
||||
exclude= .git,__pycache__,abipy/gui,abipy/abio/abivar_database,dev_scripts,docs,.ipynb_checkpoints,abipy/examples/flows/develop/,test_*.py,abipy/benchmarks,abipy/data/refs,abilab.py
|
||||
extend_ignore = E116,E121,E122,E123,E124,E126,E128,E129,E131,E133,E201,E203,E226,E231,E241,E242,E261,E262,E265,E266,E306,E401,E402,E704,W503,W504,W505,E701,E702,E731,E741,W605,F841
|
||||
extend_ignore = E114,E116,E121,E122,E123,E124,E126,E127,E128,E129,E131,E133,E201,E203,E226,E231,E241,E242,E261,E262,E265,E266,E306,E401,E402,E704,W503,W504,W505,E701,E702,E731,E741,W605,F841
|
||||
|
||||
[pydocstyle]
|
||||
ignore = D105,D2,D4
|
||||
|
|
|
|||
Loading…
Reference in New Issue