def as_vector_old(self):
'''
turn this record to a vector that can be fed into a prediction model
'''
# assert self.tag == MetricsTag.ENC, 'metrics un-encoded, unable to vectorize'
assert self.tag == 'enc', 'metrics un-encoded, unable to vectorize'
conf = LumosConf()
inst_id = conf.get_inst_id(self.inst_type)
scale_id = conf.get_scale_id(self.scale)
X = np.array([inst_id, scale_id, self.ts[0], self.ts[1]])
X = np.concatenate((X, self.metrics), axis=0)
Y = self.jct
return X, Y
def as_vector(self):
'''
turn this record to a vector that can be fed into a prediction model
'''
# assert self.tag == MetricsTag.ENC, 'metrics un-encoded, unable to vectorize'
assert self.tag == 'enc', 'metrics un-encoded, unable to vectorize'
conf = LumosConf()
inst_id = conf.get_inst_id(self.inst_type)
d_info = conf.get_inst_detailed_conf(self.inst_type)
n_fam, n_cpu, n_mem = d_info['family'], d_info['cpu'], d_info['memory']
scale_id = conf.get_scale_id(self.scale)
X = np.array(
[inst_id, n_fam, n_cpu, n_mem, scale_id, self.ts[0], self.ts[1]])
X = np.concatenate((X, self.metrics), axis=0)
Y = self.jct
return X, Y