def calculate(self,funcs):
## always count the data
funcs = [{'function':len,'name':'count'}] + funcs
## check the function definition dictionary for common problems
check_function_dictionary(funcs)
## convert the time vector for faster referencing
time_conv = [[getattr(time,grp) for grp in self.time_grouping]
for time in self.sub.timevec]
## the shared list
all_attrs = Manager().list()
if self.procs > 1:
processes = [Process(target=self.f_calculate,
args=(all_attrs,
self.sub,
groups,
funcs,
time_conv,
self.time_grouping,
self.grouping))
for groups in self.groups]
self.run_parallel(processes)
else:
self.f_calculate(all_attrs,self.sub,self.groups[0],funcs,time_conv,self.time_grouping,self.grouping)
return(all_attrs)
def calculate(self,funcs):
## always count the data
base_funcs = [{'function':len,'name':'count_agg','raw':False}]
## check if there are raw calculation functions
if any([f['raw'] for f in funcs]):
has_raw = True
if self.sub.value_set == {}:
raise(ValueError('Raw aggregate statistics requested with no "value_set_coll"!!'))
else:
has_raw = False
## need to count the raw data values if raw value are present
if has_raw:
base_funcs.append({'function':len,'name':'count_raw','raw':True})
## append the rest of the functions
funcs = base_funcs + funcs
## check the function definition dictionary for common problems
check_function_dictionary(funcs)
## convert the time vector for faster referencing
time_conv = [[getattr(time,grp) for grp in self.time_grouping]
for time in self.sub.timevec]
## the shared list
all_attrs = Manager().list()
if self.procs > 1:
processes = [Process(target=self.f_calculate,
args=(all_attrs,
self.sub,
groups,
funcs,
time_conv,
self.time_grouping,
self.grouping,
has_raw))
for groups in self.groups]
pmanager = ProcessManager(processes,self.procs)
pmanager.run()
else:
self.f_calculate(all_attrs,
self.sub,
self.groups[0],
funcs,
time_conv,
self.time_grouping,
self.grouping,
has_raw)
self.stats = merge_dict_list(list(all_attrs))
def calculate(self, funcs):
## always count the data
base_funcs = [{'function': len, 'name': 'count_agg', 'raw': False}]
## check if there are raw calculation functions
if any([f['raw'] for f in funcs]):
has_raw = True
if self.sub.value_set == {}:
raise (ValueError(
'Raw aggregate statistics requested with no "value_set_coll"!!'
))
else:
has_raw = False
## need to count the raw data values if raw value are present
if has_raw:
base_funcs.append({
'function': len,
'name': 'count_raw',
'raw': True
})
## append the rest of the functions
funcs = base_funcs + funcs
## check the function definition dictionary for common problems
check_function_dictionary(funcs)
## convert the time vector for faster referencing
time_conv = [[getattr(time, grp) for grp in self.time_grouping]
for time in self.sub.timevec]
## the shared list
all_attrs = Manager().list()
if self.procs > 1:
processes = [
Process(target=self.f_calculate,
args=(all_attrs, self.sub, groups, funcs, time_conv,
self.time_grouping, self.grouping, has_raw))
for groups in self.groups
]
pmanager = ProcessManager(processes, self.procs)
pmanager.run()
else:
self.f_calculate(all_attrs, self.sub, self.groups[0], funcs,
time_conv, self.time_grouping, self.grouping,
has_raw)
self.stats = merge_dict_list(list(all_attrs))
def calculate(self, funcs):
## always count the data
funcs = [{'function': len, 'name': 'count'}] + funcs
## check the function definition dictionary for common problems
check_function_dictionary(funcs)
## convert the time vector for faster referencing
time_conv = [[getattr(time, grp) for grp in self.time_grouping]
for time in self.sub.timevec]
## the shared list
all_attrs = Manager().list()
if self.procs > 1:
processes = [
Process(target=self.f_calculate,
args=(all_attrs, self.sub, groups, funcs, time_conv,
self.time_grouping, self.grouping))
for groups in self.groups
]
self.run_parallel(processes)
else:
self.f_calculate(all_attrs, self.sub, self.groups[0], funcs,
time_conv, self.time_grouping, self.grouping)
return (all_attrs)
def _get_(self):
stat = OcgStatFunction()
function_list = stat.get_function_list(self.url_arg[0].split(' '))
check_function_dictionary(function_list)
return(function_list)
def _get_(self):
stat = OcgStatFunction()
function_list = stat.get_function_list(self.url_arg[0].split(' '))
check_function_dictionary(function_list)
return (function_list)