def get_all_dataset(self, idmodel):
con = lite.connect(self.name)
with con:
con.row_factory = lite.Row
cur = con.cursor()
cur.execute("SELECT * FROM dataset where idmodel=:idmodel", {'idmodel': idmodel})
rows = cur.fetchall()
dataset = Dataset.from_db_rows(rows, self.setup)
return dataset
def get_benchmarking_data(self, idmodel, it=-1):
"""
Returns a Dataset instance with the data used for learning up to iteration it
"""
con = lite.connect(self.name)
cues = []
obs = []
nobs = defaultdict(int)
with con:
con.row_factory = lite.Row
cur = con.cursor()
if it < 0:
cur.execute("SELECT * FROM benchmark_data WHERE idmodel=:idmodel", {'idmodel': idmodel})
else:
cur.execute("SELECT * FROM benchmark_data WHERE idmodel=:idmodel AND it<=:it", {'idmodel': idmodel, 'it': it})
rows = cur.fetchall()
dataset = Dataset.from_db_rows(rows, self.setup)
return dataset
def get_random_dataset(self, idmodel, nexp, max_stimuli=0, max_inhibitors=0):
rows = self.get_population_rows(idmodel, max_stimuli, max_inhibitors)
exps = random.sample(rows, nexp)
dataset = Dataset.from_db_rows(exps, self.setup)
return dataset
