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