def load_data_local(self):
source_path = QAanalyzer.run_info.source_path
data_sources = self.info.data_sources
files = self.info.files
if 'stat' in data_sources:
filepath = os.path.join(source_path, files.stat)
hr = HDFreader(filepath)
if not hr._success:
self.warn(
' hdf file seems to be corrupted, skipping contents:\n '
+ filepath)
#end if
hdf = hr.obj
self.data = QAHDFdata()
self.data.transfer_from(hdf)
#end if
remove = []
for name, value in self.iteritems():
if isinstance(value, HDFAnalyzer):
value.load_data_local(self.data)
value.info.data_loaded = True
if value.info.should_remove:
remove.append(name)
#end if
#end if
#end for
for name in remove:
del self[name]
def load_data_local(self):
source_path = QAanalyzer.run_info.source_path
data_sources = self.info.data_sources
files = self.info.files
if 'stat' in data_sources:
filepath = os.path.join(source_path,files.stat)
hr = HDFreader(filepath)
if not hr._success:
self.warn(' hdf file seems to be corrupted, skipping contents:\n '+filepath)
#end if
hdf = hr.obj
self.data = QAHDFdata()
self.data.transfer_from(hdf)
#end if
remove = []
for name,value in self.iteritems():
if isinstance(value,HDFAnalyzer):
value.load_data_local(self.data)
value.info.data_loaded = True
if value.info.should_remove:
remove.append(name)
#end if
#end if
#end for
for name in remove:
del self[name]
def load_data_local(self,data=None):
if data==None:
self.error('attempted load without data')
#end if
exclude = self.info.exclude
self.data = QAHDFdata()
for var in data.keys():
if not var in exclude and not str(var)[0]=='_':
self.data[var] = data[var]
del data[var]
#end if
#end for
corrvars = ['LocalEnergy','ElecElec','MPC','KEcorr']
if set(corrvars)<set(self.data.keys()):
Ed,Ved,Vmd,Kcd = self.data.tuple(*corrvars)
E,E2 = Ed.value,Ed.value_squared
Ve,Ve2 = Ved.value,Ved.value_squared
Vm,Vm2 = Vmd.value,Vmd.value_squared
Kc,Kc2 = Kcd.value,Kcd.value_squared
self.data.LocalEnergy_mpc_kc = obj(
value = E-Ve+Vm+Kc,
value_squared = E2+Ve2+Vm2+Kc2 + 2*(E*(-Ve+Vm+Kc)-Ve*(Vm+Kc)+Vm*Kc)
)
class MethodAnalyzer(QAanalyzer):
def __init__(self, series=None, calc=None, input=None):
QAanalyzer.__init__(self)
if series != None and calc != None and input != None:
self.init_sub_analyzers(series, calc, input)
#end if
#end def __init__
def init_sub_analyzers(self, series, calc, input):
request = QAanalyzer.request
run_info = QAanalyzer.run_info
source_path = run_info.source_path
file_prefix = run_info.file_prefix + '.s' + str(series).zfill(3)
method = calc.method
files = obj()
outfiles = os.listdir(source_path)
for file in outfiles:
if file.startswith(file_prefix):
if file.endswith('scalar.dat'):
files.scalar = file
elif file.endswith('stat.h5'):
files.stat = file
elif file.endswith('storeConfig.h5'):
files.storeconfig = file
elif file.endswith('opt.xml'):
files.opt = file
elif file.endswith('dmc.dat'):
files.dmc = file
#end if
#end if
#end for
data_sources = request.data_sources & set(files.keys())
method_info = obj(method=method,
series=series,
file_prefix=file_prefix,
files=files,
data_sources=data_sources,
method_input=calc.copy(),
nblocks_exclude=0)
self.info.transfer_from(method_info)
self.set_global_info()
analyzers = self.capabilities.analyzers
if 'scalar' in data_sources:
filepath = os.path.join(source_path, files.scalar)
self.scalars = analyzers.scalars_dat(filepath,
equilibration='LocalEnergy')
#end if
if 'stat' in data_sources:
#determine scalars and analyzer quantities
analyzer_quantities = self.capabilities.analyzer_quantities
analyzer_quants = obj()
ignored_quantities = set()
ham = input.get('hamiltonian')
ham = ham.get_single('h0')
ham_est = ham.get('estimator')
calc_est = calc.get('estimator')
estimators = obj()
if ham_est != None:
estimators.transfer_from(ham_est)
#end if
if calc_est != None:
estimators.transfer_from(calc_est)
#end if
for estname, est in estimators.iteritems():
has_type = 'type' in est
has_name = 'name' in est
if has_type and has_name:
type = est.type
name = est.name
elif has_name:
type = est.name
name = est.name
elif has_type:
type = est.type
name = est.type
else:
self.error('estimator ' + estname + ' has no type or name')
#end if
cname = self.condense_name(name)
ctype = self.condense_name(type)
if ctype == 'density' and not has_name:
name = 'any'
#end if
if ctype in analyzer_quantities:
analyzer_quants[name] = self.condense_name(type)
#end if
#end for
not_scalars = set(analyzer_quants.keys())
self.scalars_hdf = analyzers.scalars_hdf(not_scalars)
analyzer_quantities = analyzer_quantities & request.quantities
for name, type in analyzer_quants.iteritems():
if type in analyzer_quantities:
if type in analyzers:
qqa = analyzers[type](name)
qqa.init_sub_analyzers()
self[name] = qqa
else:
ignored_quantities.add(name)
#end if
#end if
#end for
self.info.ignored_quantities = ignored_quantities
#end if
if 'dmc' in data_sources:
filepath = os.path.join(source_path, files.dmc)
self.dmc = analyzers.dmc_dat(filepath)
#end if
self.unset_global_info()
return
#end def init_sub_analyzers
def load_data_local(self):
source_path = QAanalyzer.run_info.source_path
data_sources = self.info.data_sources
files = self.info.files
if 'stat' in data_sources:
filepath = os.path.join(source_path, files.stat)
hr = HDFreader(filepath)
if not hr._success:
self.warn(
' hdf file seems to be corrupted, skipping contents:\n '
+ filepath)
#end if
hdf = hr.obj
self.data = QAHDFdata()
self.data.transfer_from(hdf)
#end if
remove = []
for name, value in self.iteritems():
if isinstance(value, HDFAnalyzer):
value.load_data_local(self.data)
value.info.data_loaded = True
if value.info.should_remove:
remove.append(name)
#end if
#end if
#end for
for name in remove:
del self[name]
#end for
#end def load_data_local
def set_global_info(self):
QAanalyzer.method_info = self.info
#end def set_global_info
def unset_global_info(self):
QAanalyzer.method_info = None
class ScalarsHDFAnalyzer(HDFAnalyzer):
corrections = obj(
mpc = obj(ElecElec=-1,MPC=1),
kc = obj(KEcorr=1)
)
def __init__(self,exclude):
HDFAnalyzer.__init__(self)
self.info.exclude = exclude
#end def
def load_data_local(self,data=None):
if data==None:
self.error('attempted load without data')
#end if
exclude = self.info.exclude
self.data = QAHDFdata()
for var in data.keys():
if not var in exclude and not str(var)[0]=='_':
self.data[var] = data[var]
del data[var]
#end if
#end for
corrvars = ['LocalEnergy','ElecElec','MPC','KEcorr']
if set(corrvars)<set(self.data.keys()):
Ed,Ved,Vmd,Kcd = self.data.tuple(*corrvars)
E,E2 = Ed.value,Ed.value_squared
Ve,Ve2 = Ved.value,Ved.value_squared
Vm,Vm2 = Vmd.value,Vmd.value_squared
Kc,Kc2 = Kcd.value,Kcd.value_squared
self.data.LocalEnergy_mpc_kc = obj(
value = E-Ve+Vm+Kc,
value_squared = E2+Ve2+Vm2+Kc2 + 2*(E*(-Ve+Vm+Kc)-Ve*(Vm+Kc)+Vm*Kc)
)
#end if
#end def load_data_local
def analyze_local(self):
nbe = QAanalyzer.method_info.nblocks_exclude
self.info.nblocks_exclude = nbe
for varname,val in self.data.iteritems():
(mean,var,error,kappa)=simstats(val.value[nbe:,...].ravel())
self[varname] = obj(
mean = mean,
variance = val.value_squared[nbe:,...].mean()-mean**2,
sample_variance = var,
error = error,
kappa = kappa
)
#end for
self.correct('mpc','kc')
#end def analyze_local
def correct(self,*corrections):
corrkey=''
for corr in corrections:
corrkey+=corr+'_'
#end for
corrkey=corrkey[:-1]
if set(corrections)>set(self.corrections.keys()):
self.warn('correction '+corrkey+' is unknown and cannot be applied')
return
#end if
if not 'data' in self:
self.warn('correction '+corrkey+' cannot be applied because data is not present')
return
#end if
varname = 'LocalEnergy_'+corrkey
if varname in self and varname in self.data:
return
#end if
corrvars = ['LocalEnergy']
signs = [1]
for corr in corrections:
for var,sign in self.corrections[corr].iteritems():
corrvars.append(var)
signs.append(sign)
#end for
#end for
missing = list(set(corrvars)-set(self.data.keys()))
if len(missing)>0:
self.warn('correction '+corrkey+' cannot be applied because '+str(missing)+' are missing')
return
#end if
le = self.data.LocalEnergy
E,E2 = 0*le.value,0*le.value_squared
n = len(corrvars)
for i in range(n):
ed = self.data[corrvars[i]]
e,e2 = ed.value,ed.value_squared
s = signs[i]
E += s*e
E2 += e2
for j in range(i+1,n):
eo = self.data[corrvars[j]].value
so = signs[j]
E2 += 2*s*e*so*eo
#end for
#end for
val = obj(value=E,value_squared=E2)
self.data[varname] = val
nbe = self.info.nblocks_exclude
(mean,var,error,kappa)=simstats(val.value[nbe:,...].ravel())
self[varname] = obj(
mean = mean,
variance = val.value_squared[nbe:,...].mean()-mean**2,
sample_variance = var,
error = error,
kappa = kappa
)
class MethodAnalyzer(QAanalyzer):
def __init__(self,series=None,calc=None,input=None,nindent=0):
QAanalyzer.__init__(self,nindent=nindent)
if series!=None and calc!=None and input!=None:
self.init_sub_analyzers(series,calc,input)
#end if
#end def __init__
def init_sub_analyzers(self,series,calc,input):
request = QAanalyzer.request
run_info = QAanalyzer.run_info
source_path = run_info.source_path
file_prefix = run_info.file_prefix+'.s'+str(series).zfill(3)
method = calc.method
files = obj()
outfiles = os.listdir(source_path)
self.vlog('looking for file prefix: '+file_prefix,n=2)
matched = False
for file in outfiles:
if file.startswith(file_prefix):
local_match = True
if file.endswith('scalar.dat'):
files.scalar = file
elif file.endswith('stat.h5'):
files.stat = file
elif file.endswith('storeConfig.h5'):
files.storeconfig = file
elif file.endswith('opt.xml'):
files.opt = file
elif file.endswith('dmc.dat') and method=='dmc':
files.dmc = file
elif '.traces.' in file:
if not 'traces' in files:
files.traces = []
#end if
files.traces.append(file)
else:
local_match = False
#end if
matched = matched or local_match
self.vlog('match found: '+file,n=3)
#end if
#end for
equil = request.equilibration
nblocks_exclude = -1
if isinstance(equil,int):
nblocks_exclude = equil
elif isinstance(equil,(dict,obj)):
if series in equil:
nblocks_exclude = equil[series]
#end if
elif equil!=None:
self.error('invalid input for equilibration which must be an int, dict, or obj\n you provided: {0}\n with type {1}'.format(equil,equil.__class__.__name__))
#end if
data_sources = request.data_sources & set(files.keys())
method_info = obj(
method = method,
series = series,
file_prefix = file_prefix,
files = files,
data_sources = data_sources,
method_input = calc.copy(),
nblocks_exclude = nblocks_exclude,
complete = matched
)
self.info.transfer_from(method_info)
self.vlog('requested sources = '+str(list(request.data_sources)),n=2)
self.vlog('files available = '+str(files.keys()),n=2)
self.vlog('available sources = '+str(list(data_sources)),n=2)
if not matched:
msg = 'no data files found\n file prefix used for matching: {0}\n checked all files in directory: {1}'.format(file_prefix,source_path)
#self.error(msg,trace=False)
#self.warn(msg)
return
#end if
self.set_global_info()
analyzers = self.capabilities.analyzers
if 'scalar' in data_sources:
filepath = os.path.join(source_path,files.scalar)
self.scalars = analyzers.scalars_dat(filepath,equilibration='LocalEnergy',nindent=self.subindent())
#end if
if 'stat' in data_sources:
#determine scalars and analyzer quantities
analyzer_quantities = self.capabilities.analyzer_quantities
analyzer_quants = obj()
ignored_quantities = set()
ham = input.get('hamiltonian')
ham = ham.get_single('h0')
ham_est = ham.get('estimator')
calc_est = calc.get('estimator')
estimators = obj()
if ham_est!=None:
estimators.transfer_from(ham_est)
#end if
if calc_est!=None:
estimators.transfer_from(calc_est)
#end if
for estname,est in estimators.iteritems():
if est==None:
self.error('estimators have not been read properly by QmcpackInput',trace=False)
#end if
has_type = 'type' in est
has_name = 'name' in est
if has_type and has_name:
type = est.type
name = est.name
elif has_name:
type = est.name
name = est.name
elif has_type:
type = est.type
name = est.type
else:
self.error('estimator '+estname+' has no type or name')
#end if
cname = self.condense_name(name)
ctype = self.condense_name(type)
if ctype=='density' and not has_name:
name = 'any'
#end if
if ctype in analyzer_quantities:
analyzer_quants[name] = self.condense_name(type)
#end if
#end for
not_scalars = set(analyzer_quants.keys())
self.scalars_hdf = analyzers.scalars_hdf(not_scalars,nindent=self.subindent())
analyzer_quantities = analyzer_quantities & request.quantities
for name,type in analyzer_quants.iteritems():
if type in analyzer_quantities:
if type in analyzers:
qqa = analyzers[type](name,nindent=self.subindent())
qqa.init_sub_analyzers()
self[name] = qqa
else:
ignored_quantities.add(name)
#end if
#end if
#end for
self.info.ignored_quantities = ignored_quantities
#end if
if 'dmc' in data_sources:
filepath = os.path.join(source_path,files.dmc)
self.dmc = analyzers.dmc_dat(filepath,nindent=self.subindent())
#end if
if 'traces' in data_sources and 'traces' in files:
self.traces = analyzers.traces(source_path,files.traces,nindent=self.subindent())
#end if
self.unset_global_info()
return
#end def init_sub_analyzers
def load_data_local(self):
source_path = QAanalyzer.run_info.source_path
data_sources = self.info.data_sources
files = self.info.files
if 'stat' in data_sources:
filepath = os.path.join(source_path,files.stat)
hr = HDFreader(filepath)
if not hr._success:
self.warn(' hdf file seems to be corrupted, skipping contents:\n '+filepath)
#end if
hdf = hr.obj
self.data = QAHDFdata()
self.data.transfer_from(hdf)
#end if
remove = []
for name,value in self.iteritems():
if isinstance(value,HDFAnalyzer):
value.load_data_local(self.data)
value.info.data_loaded = True
if value.info.should_remove:
remove.append(name)
#end if
#end if
#end for
for name in remove:
del self[name]
#end for
#end def load_data_local
def set_global_info(self):
QAanalyzer.method_info = self.info
#end def set_global_info
def unset_global_info(self):
QAanalyzer.method_info = None
#end def unset_global_info
def check_traces(self,pad=None):
verbose = pad!=None
method = self.info.method
series = self.info.series
if verbose:
desc = 'method {0} series {1}'.format(method,series)
#end if
if 'traces' in self:
check = {None:True,False:False,True:True}
if verbose:
self.log(pad+'Checking traces in '+desc)
#end if
scalars = None
scalars_hdf = None
dmc = None
if 'scalars' in self and 'data' in self.scalars:
scalars = self.scalars.data
#end if
if 'scalars_hdf' in self and 'data' in self.scalars_hdf:
scalars_hdf = self.scalars_hdf.data
#end if
if 'dmc' in self and 'data' in self.dmc:
dmc = self.dmc.data
#end if
checks = Checks('traces')
checks.exclude(None)
traces = self.traces
traces.form_diagnostic_data()
checks.psums = traces.check_particle_sums()
if method=='dmc':
checks.dmc = traces.check_dmc(dmc)
else:
svalid,shvalid = traces.check_scalars(scalars,scalars_hdf)
checks.scalars = svalid
checks.scalars_hdf = shvalid
#end if
valid = checks.valid()
if verbose:
checks.write(pad+' ')
#end if
return valid
else:
if verbose:
self.log(pad+'No traces in '+desc)
#end if
return None
class MethodAnalyzer(QAanalyzer):
def __init__(self,series=None,calc=None,input=None):
QAanalyzer.__init__(self)
if series!=None and calc!=None and input!=None:
self.init_sub_analyzers(series,calc,input)
#end if
#end def __init__
def init_sub_analyzers(self,series,calc,input):
request = QAanalyzer.request
run_info = QAanalyzer.run_info
source_path = run_info.source_path
file_prefix = run_info.file_prefix+'.s'+str(series).zfill(3)
method = calc.method
files = obj()
outfiles = os.listdir(source_path)
for file in outfiles:
if file.startswith(file_prefix):
if file.endswith('scalar.dat'):
files.scalar = file
elif file.endswith('stat.h5'):
files.stat = file
elif file.endswith('storeConfig.h5'):
files.storeconfig = file
elif file.endswith('opt.xml'):
files.opt = file
elif file.endswith('dmc.dat'):
files.dmc = file
#end if
#end if
#end for
data_sources = request.data_sources & set(files.keys())
method_info = obj(
method = method,
series = series,
file_prefix = file_prefix,
files = files,
data_sources = data_sources,
method_input = calc.copy(),
nblocks_exclude = 0
)
self.info.transfer_from(method_info)
self.set_global_info()
analyzers = self.capabilities.analyzers
if 'scalar' in data_sources:
filepath = os.path.join(source_path,files.scalar)
self.scalars = analyzers.scalars_dat(filepath,equilibration='LocalEnergy')
#end if
if 'stat' in data_sources:
#determine scalars and analyzer quantities
analyzer_quantities = self.capabilities.analyzer_quantities
analyzer_quants = obj()
ignored_quantities = set()
ham = input.get('hamiltonian')
ham = ham.get_single('h0')
ham_est = ham.get('estimator')
calc_est = calc.get('estimator')
estimators = obj()
if ham_est!=None:
estimators.transfer_from(ham_est)
#end if
if calc_est!=None:
estimators.transfer_from(calc_est)
#end if
for estname,est in estimators.iteritems():
has_type = 'type' in est
has_name = 'name' in est
if has_type and has_name:
type = est.type
name = est.name
elif has_name:
type = est.name
name = est.name
elif has_type:
type = est.type
name = est.type
else:
self.error('estimator '+estname+' has no type or name')
#end if
cname = self.condense_name(name)
ctype = self.condense_name(type)
if ctype=='density' and not has_name:
name = 'any'
#end if
if ctype in analyzer_quantities:
analyzer_quants[name] = self.condense_name(type)
#end if
#end for
not_scalars = set(analyzer_quants.keys())
self.scalars_hdf = analyzers.scalars_hdf(not_scalars)
analyzer_quantities = analyzer_quantities & request.quantities
for name,type in analyzer_quants.iteritems():
if type in analyzer_quantities:
if type in analyzers:
qqa = analyzers[type](name)
qqa.init_sub_analyzers()
self[name] = qqa
else:
ignored_quantities.add(name)
#end if
#end if
#end for
self.info.ignored_quantities = ignored_quantities
#end if
if 'dmc' in data_sources:
filepath = os.path.join(source_path,files.dmc)
self.dmc = analyzers.dmc_dat(filepath)
#end if
self.unset_global_info()
return
#end def init_sub_analyzers
def load_data_local(self):
source_path = QAanalyzer.run_info.source_path
data_sources = self.info.data_sources
files = self.info.files
if 'stat' in data_sources:
filepath = os.path.join(source_path,files.stat)
hr = HDFreader(filepath)
if not hr._success:
self.warn(' hdf file seems to be corrupted, skipping contents:\n '+filepath)
#end if
hdf = hr.obj
self.data = QAHDFdata()
self.data.transfer_from(hdf)
#end if
remove = []
for name,value in self.iteritems():
if isinstance(value,HDFAnalyzer):
value.load_data_local(self.data)
value.info.data_loaded = True
if value.info.should_remove:
remove.append(name)
#end if
#end if
#end for
for name in remove:
del self[name]
#end for
#end def load_data_local
def set_global_info(self):
QAanalyzer.method_info = self.info
#end def set_global_info
def unset_global_info(self):
QAanalyzer.method_info = None
class MethodAnalyzer(QAanalyzer):
def __init__(self,series=None,calc=None,input=None,nindent=0):
QAanalyzer.__init__(self,nindent=nindent)
if series!=None and calc!=None and input!=None:
self.init_sub_analyzers(series,calc,input)
#end if
#end def __init__
def init_sub_analyzers(self,series,calc,input):
request = QAanalyzer.request
run_info = QAanalyzer.run_info
source_path = run_info.source_path
file_prefix = run_info.file_prefix+'.s'+str(series).zfill(3)
method = calc.method
files = obj()
outfiles = os.listdir(source_path)
self.vlog('looking for file prefix: '+file_prefix,n=2)
matched = False
for file in outfiles:
if file.startswith(file_prefix):
local_match = True
if file.endswith('scalar.dat'):
files.scalar = file
elif file.endswith('stat.h5'):
files.stat = file
elif file.endswith('storeConfig.h5'):
files.storeconfig = file
elif file.endswith('opt.xml'):
files.opt = file
elif file.endswith('dmc.dat'):
files.dmc = file
elif '.traces.' in file:
if not 'traces' in files:
files.traces = []
#end if
files.traces.append(file)
else:
local_match = False
#end if
matched = matched or local_match
self.vlog('match found: '+file,n=3)
#end if
#end for
if not matched:
msg = 'no data files found\n file prefix used for matching: {0}\n checked all files in directory: {1}'.format(file_prefix,source_path)
self.error(msg,trace=False)
#end if
equil = request.equilibration
nblocks_exclude = -1
if isinstance(equil,int):
nblocks_exclude = equil
elif isinstance(equil,(dict,obj)) and series in equil:
nblocks_exclude = equil[series]
elif equil!=None:
self.error('invalid input for equilibration which must be an int, dict, or obj\n you provided: {0}\n with type {1}'.format(equil,equil.__class__.__name__))
#end if
data_sources = request.data_sources & set(files.keys())
method_info = obj(
method = method,
series = series,
file_prefix = file_prefix,
files = files,
data_sources = data_sources,
method_input = calc.copy(),
nblocks_exclude = nblocks_exclude
)
self.info.transfer_from(method_info)
self.vlog('requested sources = '+str(list(request.data_sources)),n=2)
self.vlog('files available = '+str(files.keys()),n=2)
self.vlog('available sources = '+str(list(data_sources)),n=2)
self.set_global_info()
analyzers = self.capabilities.analyzers
if 'scalar' in data_sources:
filepath = os.path.join(source_path,files.scalar)
self.scalars = analyzers.scalars_dat(filepath,equilibration='LocalEnergy',nindent=self.subindent())
#end if
if 'stat' in data_sources:
#determine scalars and analyzer quantities
analyzer_quantities = self.capabilities.analyzer_quantities
analyzer_quants = obj()
ignored_quantities = set()
ham = input.get('hamiltonian')
ham = ham.get_single('h0')
ham_est = ham.get('estimator')
calc_est = calc.get('estimator')
estimators = obj()
if ham_est!=None:
estimators.transfer_from(ham_est)
#end if
if calc_est!=None:
estimators.transfer_from(calc_est)
#end if
for estname,est in estimators.iteritems():
if est==None:
self.error('estimators have not been read properly by QmcpackInput',trace=False)
#end if
has_type = 'type' in est
has_name = 'name' in est
if has_type and has_name:
type = est.type
name = est.name
elif has_name:
type = est.name
name = est.name
elif has_type:
type = est.type
name = est.type
else:
self.error('estimator '+estname+' has no type or name')
#end if
cname = self.condense_name(name)
ctype = self.condense_name(type)
if ctype=='density' and not has_name:
name = 'any'
#end if
if ctype in analyzer_quantities:
analyzer_quants[name] = self.condense_name(type)
#end if
#end for
not_scalars = set(analyzer_quants.keys())
self.scalars_hdf = analyzers.scalars_hdf(not_scalars,nindent=self.subindent())
analyzer_quantities = analyzer_quantities & request.quantities
for name,type in analyzer_quants.iteritems():
if type in analyzer_quantities:
if type in analyzers:
qqa = analyzers[type](name,nindent=self.subindent())
qqa.init_sub_analyzers()
self[name] = qqa
else:
ignored_quantities.add(name)
#end if
#end if
#end for
self.info.ignored_quantities = ignored_quantities
#end if
if 'dmc' in data_sources:
filepath = os.path.join(source_path,files.dmc)
self.dmc = analyzers.dmc_dat(filepath,nindent=self.subindent())
#end if
if 'traces' in data_sources and 'traces' in files:
self.traces = analyzers.traces(source_path,files.traces,nindent=self.subindent())
#end if
self.unset_global_info()
return
#end def init_sub_analyzers
def load_data_local(self):
source_path = QAanalyzer.run_info.source_path
data_sources = self.info.data_sources
files = self.info.files
if 'stat' in data_sources:
filepath = os.path.join(source_path,files.stat)
hr = HDFreader(filepath)
if not hr._success:
self.warn(' hdf file seems to be corrupted, skipping contents:\n '+filepath)
#end if
hdf = hr.obj
self.data = QAHDFdata()
self.data.transfer_from(hdf)
#end if
remove = []
for name,value in self.iteritems():
if isinstance(value,HDFAnalyzer):
value.load_data_local(self.data)
value.info.data_loaded = True
if value.info.should_remove:
remove.append(name)
#end if
#end if
#end for
for name in remove:
del self[name]
#end for
#end def load_data_local
def set_global_info(self):
QAanalyzer.method_info = self.info
#end def set_global_info
def unset_global_info(self):
QAanalyzer.method_info = None
#end def unset_global_info
def check_traces(self,pad=None):
verbose = pad!=None
method = self.info.method
series = self.info.series
if verbose:
desc = 'method {0} series {1}'.format(method,series)
#end if
if 'traces' in self:
check = {None:True,False:False,True:True}
if verbose:
self.log(pad+'Checking traces in '+desc)
#end if
scalars = None
scalars_hdf = None
dmc = None
if 'scalars' in self and 'data' in self.scalars:
scalars = self.scalars.data
#end if
if 'scalars_hdf' in self and 'data' in self.scalars_hdf:
scalars_hdf = self.scalars_hdf.data
#end if
if 'dmc' in self and 'data' in self.dmc:
dmc = self.dmc.data
#end if
checks = Checks('traces')
checks.exclude(None)
traces = self.traces
checks.psums = traces.check_particle_sums()
if method=='dmc':
checks.dmc = traces.check_dmc(dmc)
else:
svalid,shvalid = traces.check_scalars(scalars,scalars_hdf)
checks.scalars = svalid
checks.scalars_hdf = shvalid
#end if
valid = checks.valid()
if verbose:
checks.write(pad+' ')
#end if
return valid
else:
if verbose:
self.log(pad+'No traces in '+desc)
#end if
return None
