def __init__(self, parent, flow, **kwargs):
"""
Args:
parent:
Parent window.
flow:
`AbinitFlow` with the list of `Workflow` objects.
"""
if "title" not in kwargs:
kwargs["title"] = self.codename
super(FlowViewerFrame, self).__init__(parent, -1, **kwargs)
# This combination of options for config seems to work on my Mac.
self.config = wx.FileConfig(appName=self.codename, localFilename=self.codename + ".ini",
style=wx.CONFIG_USE_LOCAL_FILE)
# Build menu, toolbar and status bar.
self.SetMenuBar(self.makeMenu())
self.makeToolBar()
self.statusbar = self.CreateStatusBar()
self.Centre()
self.flow = flow
# Disable launch mode if we already executing the flow with the scheduler.
self.check_launcher_file()
# Build UI
self.panel = panel = wx.Panel(self, -1)
self.main_sizer = main_sizer = wx.BoxSizer(wx.VERTICAL)
# Here we create a panel and a notebook on the panel
self.notebook = FlowNotebook(panel, self.flow)
main_sizer.Add(self.notebook, 1, wx.EXPAND, 5)
submit_button = wx.Button(panel, -1, label='Submit')
submit_button.Bind(wx.EVT_BUTTON, self.OnSubmitButton)
text = wx.StaticText(panel, -1, "Max nlaunch:")
text.Wrap(-1)
text.SetToolTipString("Maximum number of tasks that can be submitted. Use -1 for unlimited launches.")
self.max_nlaunch = wx.SpinCtrl(panel, -1, value=str(get_ncpus()), min=-1)
hsizer = wx.BoxSizer(wx.HORIZONTAL)
hsizer.Add(submit_button, 0, wx.ALL | wx.ALIGN_CENTER_HORIZONTAL, 5)
hsizer.Add(text, 0, wx.ALL | wx.ALIGN_CENTER_HORIZONTAL, 5)
hsizer.Add(self.max_nlaunch, 0, wx.ALL | wx.ALIGN_CENTER_HORIZONTAL, 5)
main_sizer.Add(hsizer, 0, wx.ALL | wx.ALIGN_CENTER_HORIZONTAL, 5)
panel.SetSizerAndFit(main_sizer)
# Register this event when the GUI is IDLE
# Not used anymore since the Yaml parser
# is very slow when we use the pure python version.
self.last_refresh = time.time()
def __init__(self, parent, flow, **kwargs):
"""
Args:
parent:
Parent window.
flow:
`AbinitFlow` with the list of `Workflow` objects.
"""
if "title" not in kwargs:
kwargs["title"] = self.codename
super(FlowViewerFrame, self).__init__(parent, -1, **kwargs)
# This combination of options for config seems to work on my Mac.
self.config = wx.FileConfig(appName=self.codename, localFilename=self.codename + ".ini",
style=wx.CONFIG_USE_LOCAL_FILE)
# Build menu, toolbar and status bar.
self.SetMenuBar(self.makeMenu())
self.makeToolBar()
self.statusbar = self.CreateStatusBar()
self.Centre()
self.flow = flow
# Disable launch mode if we already executing the flow with the scheduler.
self.check_launcher_file()
# Build UI
self.panel = panel = wx.Panel(self, -1)
self.main_sizer = main_sizer = wx.BoxSizer(wx.VERTICAL)
# Here we create a panel and a notebook on the panel
self.notebook = FlowNotebook(panel, self.flow)
main_sizer.Add(self.notebook, 1, wx.EXPAND, 5)
submit_button = wx.Button(panel, -1, label='Submit')
submit_button.Bind(wx.EVT_BUTTON, self.OnSubmitButton)
text = wx.StaticText(panel, -1, "Max nlaunch:")
text.Wrap(-1)
text.SetToolTipString("Maximum number of tasks that can be submitted. Use -1 for unlimited launches.")
self.max_nlaunch = wx.SpinCtrl(panel, -1, value=str(get_ncpus()), min=-1)
hsizer = wx.BoxSizer(wx.HORIZONTAL)
hsizer.Add(submit_button, 0, wx.ALL | wx.ALIGN_CENTER_HORIZONTAL, 5)
hsizer.Add(text, 0, wx.ALL | wx.ALIGN_CENTER_HORIZONTAL, 5)
hsizer.Add(self.max_nlaunch, 0, wx.ALL | wx.ALIGN_CENTER_HORIZONTAL, 5)
main_sizer.Add(hsizer, 0, wx.ALL | wx.ALIGN_CENTER_HORIZONTAL, 5)
panel.SetSizerAndFit(main_sizer)
# Register this event when the GUI is IDLE
# Not used anymore since the Yaml parser
# is very slow when we use the pure python version.
self.last_refresh = time.time()
def anacompare_phdos(self, nqsmalls, asr=2, chneut=1, dipdip=1, dos_method="tetra", ngqpt=None,
num_cpus=None, stream=sys.stdout):
"""
Args:
nqsmalls: List of integers defining the q-mesh for the DOS. Each integer gives
the number of divisions to be used to sample the smallest reciprocal lattice vector.
asr, chneut, dipdp: Anaddb input variable. See official documentation.
dos_method: Technique for DOS computation in Possible choices: "tetra", "gaussian" or "gaussian:0.001 eV".
In the later case, the value 0.001 eV is used as gaussian broadening
ngqpt: Number of divisions for the q-mesh in the DDB file. Auto-detected if None (default)
num_cpus: Number of CPUs (threads) used to parallellize the calculation of the DOSes. Autodetected if None.
stream: File-like object used for printing.
Return:
`namedtuple` with the following attributes:
phdoses: List of :class:`PhononDos` objects
plotter: :class:`PhononDosPlotter` object. Use plotter.plot() to visualize the results.
"""
num_cpus = get_ncpus() if num_cpus is None else num_cpus
if num_cpus <= 0: num_cpus = 1
num_cpus = min(num_cpus, len(nqsmalls))
# TODO: anaget_phdos
def do_work(nqsmall):
_, phdos_file = self.anaget_phbst_and_phdos_files(
nqsmall=nqsmall, ndivsm=1, asr=asr, chneut=chneut, dipdip=dipdip, dos_method=dos_method, ngqpt=ngqpt)
return phdos_file.phdos
if num_cpus == 1:
# Sequential version
phdoses = [do_work(nqs) for nqs in nqsmalls]
else:
# Threads
print("Computing %d phonon DOS with %d threads" % (len(nqsmalls), num_cpus) )
phdoses = [None] * len(nqsmalls)
def worker():
while True:
nqsm, phdos_index = q.get()
phdos = do_work(nqsm)
phdoses[phdos_index] = phdos
q.task_done()
from threading import Thread
try:
from Queue import Queue # py2k
except ImportError:
from queue import Queue # py3k
q = Queue()
for i in range(num_cpus):
t = Thread(target=worker)
t.daemon = True
t.start()
for i, nqsmall in enumerate(nqsmalls):
q.put((nqsmall, i))
# block until all tasks are done
q.join()
# Compute relative difference wrt last phonon DOS. Be careful because the DOSes may be defined
# on different frequency meshes ==> spline on the mesh of the last DOS.
last_mesh, converged = phdoses[-1].mesh, False
for i, phdos in enumerate(phdoses[:-1]):
splined_dos = phdos.spline_on_mesh(last_mesh)
abs_diff = (splined_dos - phdoses[-1]).abs()
print(" Delta(Phdos[%d] - Phdos[%d]) / Phdos[%d]: %f" %
(i, len(phdoses)-1, len(phdoses)-1, abs_diff.integral().values[-1]), file=stream)
# Fill the plotter.
plotter = PhononDosPlotter()
for nqsmall, phdos in zip(nqsmalls, phdoses):
plotter.add_phdos(label="nqsmall %d" % nqsmall, phdos=phdos)
return dict2namedtuple(phdoses=phdoses, plotter=plotter)
def test_get_ncpus(self):
self.assertEqual(get_ncpus(), multiprocessing.cpu_count())
def test_get_ncpus(self):
self.assertEqual(get_ncpus(), multiprocessing.cpu_count())
