def _apply_metaparams(cls, list_configs, dico_meta):
""" Deal with genearting random runs, names of the simulation
METAPARAMETERS: RANDOM RUNS
---------------------------
'_RDM_RUNS': default = 1 type = 'int':
Number of random runs for each config
'_RDM_FIXSEED': default = False type = 'bool'
If True all the configurations for the same random run will have
the same random seed (new key, value added in config '_RDM_SEED' != None)
To keep track of which configurations map to the same initial configuration
(i.e. without taking care of rdm runs) a flag 'ID_DET' is added
METAPARAMETERS: OUTPUT
----------------------
'_OUT_PREFIX': ('res_','str'),
'_OUT_FOLDER': (None, 'str'),
'_OUT_COUNTER': (None, 'int'),
'_OUT_NAME': (None, 'list'),
'_OUT_STORE_CONFIG': (True, 'bool'),
METAPARAMETERS: MISC
------------------------
'_MP_FLAG':(False, 'bool')}
"""
dico_meta_filled = cls._parse_metaparams(dico_meta)
#Management of the random runs
nb_rdm_run = dico_meta_filled['_RDM_RUNS']
fix_seed = dico_meta_filled['_RDM_FIXSEED']
runs = range(nb_rdm_run)
if(fix_seed):
seeds = RandomGenerator.RandomGenerator.gen_seed(nb = nb_rdm_run)
if(nb_rdm_run == 1): seeds = [seeds]
else:
seeds = [None for _ in runs]
random_bits = [{'_RDM_RUN':n, '_RDM_SEED': seeds[n]} for n in runs]
for conf in list_configs:
conf['_ID_DET'] = RandomGenerator.RandomGenerator.gen_seed()
list_configs = ut.cartesianProduct(list_configs, random_bits, ut.add_dico)
#Management of the output
name_res_list = []
for conf in list_configs:
name_res_tmp, dico_meta_filled = cls._gen_name_res(conf, dico_meta_filled)
conf['_RES_NAME'] = name_res_tmp
assert (name_res_tmp not in name_res_list), "Duplicated name: {0}".format(name_res_tmp)
name_res_list.append(name_res_tmp)
conf['_OUT_FOLDER'] = dico_meta_filled['_OUT_FOLDER']
conf['_OUT_STORE_CONFIG'] = dico_meta_filled['_OUT_STORE_CONFIG']
conf['_MP_FLAG'] = dico_meta_filled['_MP_FLAG']
return list_configs
def parse_meta_config(cls, input_file = 'inputfile.txt', update_rules = False, debug = False):
""" Parsing an input file containing a meta-config into a list of configs.
It relies on generating the cartesian product of the elements
Example (txt file containing a meta config)
-------
###
_CONTEXT {'_T':5}
key1 Val1 Val2
key2 Val3
###
--> [{key1: eval(Val1), key2: eval(Val3)}, {key1: eval(Val2), key2: eval(Val3)}]
Syntax of the meta-config file:
---------------------------------
Keys starting with a _ and in self.METAPARAMS_INFO.keys() are metaparameters
of the parser. o.w. they will be keys of the final config dico.
If the first line key = _CONTEXT the Val associated should be of the form
{'_contextvar1':val,'_contextvar2':val1} i.e. a dico with keys starting with a '_'
Arguments
---------
input_file: str
path of the meta-config file
update_rules :
When building the configs should the first value seen (e.g. Val1) be used
as a reference. Only works if Vals are <dic>. If True exampel's output becomes:
[{key1: eval(Val1), key2: eval(Val3)}, {key1: eval(Val2).update(eval(Val2)), key2: eval(Val3)}]
debug : bool
debug mode
Output
------
list_configs_processing_meta_configs: <list<dic>>
"""
if(debug): pdb.set_trace()
use_context = False
with open(input_file, 'r') as csvfile:
reader = csv.reader(csvfile, delimiter = ' ')
list_values = list([])
list_keys = list([])
nbline = 0
dico_METAPARAMS = {}
for line in reader:
nbline += 1
if(line in cls.EMPTY_LINE) or (line[0] in cls.LEX_NA): pass
elif(line[0] == '_CONTEXT'):
context = literal_eval(line[1])
if(ut.is_dico(context) and np.product([c[0] == '_' for c in context])):
use_context = True
elif(line[0] in cls.METAPARAMS_NAME):
assert(len(line) == 2), 'batch input file: 1 arg expected in l.' + str(nbline)+ ' (' +str(line[0]) + ')'
dico_METAPARAMS[line[0]] = literal_eval(line[1])
else:
assert (len(line)>=2), 'batch input file: not enough args in l.' + str(nbline)
list_keys.append(line[0])
if(use_context):
line_with_context = [cls._apply_context(line[i], context) for i in range(1,len(line))]
ev_tmp = [eval(lwc) for lwc in line_with_context]
else:
ev_tmp = [literal_eval(line[i]) for i in range(1,len(line))]
if(update_rules):
ref_value = copy.copy(ev_tmp[0])
ev_tmp_new = []
for ev_i in ev_tmp:
in_progress = ut.merge_dico(ref_value, ev_i, update_type = 0, copy = True)
ev_tmp_new.append(copy.copy(in_progress))
ev_tmp = ev_tmp_new
list_values = ut.cartesianProduct(list_values, ev_tmp, ut.appendList)
list_configs = [ut.lists2dico(list_keys, l) for l in list_values]
list_configs = cls._apply_metaparams(list_configs, dico_METAPARAMS)
list_configs = [cls._processing_meta_configs(c) for c in list_configs]
return list_configs
