def init_sub_analyzers(self,request=None):
own_request = request==None
if request==None:
request = self.info.request
#end if
group_num = request.group_num
#determine if the run was bundled
if request.source.endswith('.xml'):
self.info.type = 'single'
else:
self.info.type = 'bundled'
self.bundle(request.source)
return
#end if
self.vlog('reading input file: '+request.source,n=1)
input = QmcpackInput(request.source)
input.pluralize()
input.unroll_calculations()
calculations = input.simulation.calculations
self.info.set(
input = input,
ordered_input = input.read_xml(request.source)
)
project,wavefunction = input.get('project','wavefunction')
wavefunction = wavefunction.get_single('psi0')
subindent = self.subindent()
self.wavefunction = WavefunctionAnalyzer(wavefunction,nindent=subindent)
self.vlog('project id: '+project.id,n=1)
file_prefix = project.id
if group_num!=None:
group_ext = '.g'+str(group_num).zfill(3)
if not file_prefix.endswith(group_ext):
file_prefix += group_ext
#end if
elif self.info.type=='single':
resdir,infile = os.path.split(request.source)
ifprefix = infile.replace('.xml','')
ls = os.listdir(resdir)
for filename in ls:
if filename.startswith(ifprefix) and filename.endswith('.qmc'):
group_tag = filename.split('.')[-2]
#file_prefix = 'qmc.'+group_tag
file_prefix = project.id+'.'+group_tag
break
#end if
#end for
#end if
if 'series' in project:
series_start = int(project.series)
else:
series_start = 0
#end if
self.vlog('data file prefix: '+file_prefix,n=1)
run_info = obj(
file_prefix = file_prefix,
series_start = series_start,
source_path = os.path.split(request.source)[0],
group_num = group_num,
system = input.return_system()
)
self.info.transfer_from(run_info)
self.set_global_info()
if len(request.calculations)==0:
request.calculations = set(series_start+arange(len(calculations)))
#end if
method_aliases = dict()
for method in self.opt_methods:
method_aliases[method]='opt'
#end for
for method in self.vmc_methods:
method_aliases[method]='vmc'
#end for
for method in self.dmc_methods:
method_aliases[method]='dmc'
#end for
method_objs = ['qmc','opt','vmc','dmc']
for method in method_objs:
self[method] = QAanalyzerCollection()
#end for
for index,calc in calculations.iteritems():
method = calc.method
if method in method_aliases:
method_type = method_aliases[method]
else:
self.error('method '+method+' is unrecognized')
#end if
if method_type in request.methods:
series = series_start + index
if series in request.calculations:
if method in self.opt_methods:
qma = OptAnalyzer(series,calc,input,nindent=subindent)
self.opt[series] = qma
elif method in self.vmc_methods:
qma = VmcAnalyzer(series,calc,input,nindent=subindent)
self.vmc[series] = qma
elif method in self.dmc_methods:
qma = DmcAnalyzer(series,calc,input,nindent=subindent)
self.dmc[series] = qma
#end if
self.qmc[series] = qma
#end if
#end if
#end for
for method in method_objs:
if len(self[method])==0:
del self[method]
#end if
#end for
#Check for multi-qmc results such as
# optimization or timestep studies
results = QAanalyzerCollection()
if 'opt' in self and len(self.opt)>0:
optres = OptimizationAnalyzer(input,self.opt,nindent=subindent)
results.optimization = optres
#end if
if 'dmc' in self and len(self.dmc)>1:
maxtime = 0
times = dict()
for series,dmc in self.dmc.iteritems():
blocks,steps,timestep = dmc.info.method_input.list('blocks','steps','timestep')
times[series] = blocks*steps*timestep
maxtime = max(times[series],maxtime)
#end for
dmc = QAanalyzerCollection()
for series,time in times.iteritems():
if abs(time-maxtime)/maxtime<.5:
dmc[series] = self.dmc[series]
#end if
#end for
if len(dmc)>1:
results.timestep_study = TimestepStudyAnalyzer(dmc,nindent=subindent)
#end if
#end if
if len(results)>0:
self.results = results
#end if
self.unset_global_info()
def init_sub_analyzers(self, request=None):
own_request = request == None
if request == None:
request = self.info.request
#end if
group_num = request.group_num
#determine if the run was bundled
if request.source.endswith('.xml'):
self.info.type = 'single'
else:
self.info.type = 'bundled'
self.bundle(request.source)
return
#end if
self.vlog('reading input file: ' + request.source, n=1)
input = QmcpackInput(request.source)
input.pluralize()
input.unroll_calculations()
calculations = input.simulation.calculations
self.info.set(input=input,
ordered_input=input.read_xml(request.source))
project, wavefunction = input.get('project', 'wavefunction')
wavefunction = wavefunction.get_single('psi0')
subindent = self.subindent()
self.wavefunction = WavefunctionAnalyzer(wavefunction,
nindent=subindent)
self.vlog('project id: ' + project.id, n=1)
file_prefix = project.id
if group_num != None:
group_ext = '.g' + str(group_num).zfill(3)
if not file_prefix.endswith(group_ext):
file_prefix += group_ext
#end if
elif self.info.type == 'single':
resdir, infile = os.path.split(request.source)
#ifprefix = infile.replace('.xml','')
ifprefix = infile.replace('.xml', '.')
ls = os.listdir(resdir)
for filename in ls:
if filename.startswith(ifprefix) and filename.endswith('.qmc'):
group_tag = filename.split('.')[-2]
#file_prefix = 'qmc.'+group_tag
file_prefix = project.id + '.' + group_tag
break
#end if
#end for
#end if
if 'series' in project:
series_start = int(project.series)
else:
series_start = 0
#end if
self.vlog('data file prefix: ' + file_prefix, n=1)
run_info = obj(file_prefix=file_prefix,
series_start=series_start,
source_path=os.path.split(request.source)[0],
group_num=group_num,
system=input.return_system())
self.info.transfer_from(run_info)
self.set_global_info()
if len(request.calculations) == 0:
request.calculations = set(series_start +
arange(len(calculations)))
#end if
method_aliases = dict()
for method in self.opt_methods:
method_aliases[method] = 'opt'
#end for
for method in self.vmc_methods:
method_aliases[method] = 'vmc'
#end for
for method in self.dmc_methods:
method_aliases[method] = 'dmc'
#end for
method_objs = ['qmc', 'opt', 'vmc', 'dmc']
for method in method_objs:
self[method] = QAanalyzerCollection()
#end for
for index, calc in calculations.iteritems():
method = calc.method
if method in method_aliases:
method_type = method_aliases[method]
else:
self.error('method ' + method + ' is unrecognized')
#end if
if method_type in request.methods:
series = series_start + index
if series in request.calculations:
if method in self.opt_methods:
qma = OptAnalyzer(series,
calc,
input,
nindent=subindent)
primary = self.opt
elif method in self.vmc_methods:
qma = VmcAnalyzer(series,
calc,
input,
nindent=subindent)
primary = self.vmc
elif method in self.dmc_methods:
qma = DmcAnalyzer(series,
calc,
input,
nindent=subindent)
primary = self.dmc
#end if
primary[series] = qma
self.qmc[series] = qma
#end if
#end if
#end for
for method in method_objs:
if len(self[method]) == 0:
del self[method]
#end if
#end for
#Check for multi-qmc results such as
# optimization or timestep studies
results = QAanalyzerCollection()
if 'opt' in self and len(self.opt) > 0:
optres = OptimizationAnalyzer(input, self.opt, nindent=subindent)
results.optimization = optres
#end if
if 'dmc' in self and len(self.dmc) > 1:
maxtime = 0
times = dict()
for series, dmc in self.dmc.iteritems():
blocks, steps, timestep = dmc.info.method_input.list(
'blocks', 'steps', 'timestep')
times[series] = blocks * steps * timestep
maxtime = max(times[series], maxtime)
#end for
dmc = QAanalyzerCollection()
for series, time in times.iteritems():
if abs(time - maxtime) / maxtime < .5:
dmc[series] = self.dmc[series]
#end if
#end for
if len(dmc) > 1:
results.timestep_study = TimestepStudyAnalyzer(
dmc, nindent=subindent)
#end if
#end if
if len(results) > 0:
self.results = results
#end if
self.unset_global_info()
