def dcc_scenarios(parameter_ids, experiment_ids, backtest_ids):
parameters = dataframe2json(db.load_dcc_parameters_by_id(parameter_ids))
experiments = dataframe2json(db.load_experiments(experiment_ids))
backtests = dataframe2json(db.load_backtests(backtest_ids))
scenarios = list()
for p, e, b in itertools.product(parameters, experiments, backtests):
p = copy.deepcopy(p)
e = copy.deepcopy(e)
b = copy.deepcopy(b)
metadata = {'parameters_id': int(p['id']),
'experiment_id': int(e['id']),
'backtest_id': int(b['id'])}
p.pop('id', None)
e.pop('id', None)
b.pop('id', None)
e['start_date'] = str(e['start_date'])
e['end_date'] = str(e['end_date'])
# Numpy.int64 is not JSON serializable for some reason.
b['trailing_periods'] = int(b['trailing_periods'])
b['update_periods'] = int(b['update_periods'])
scenario = {'metadata': metadata,
'portfolio': p,
'returns': e,
'backtest': b}
scenarios.append(json.dumps(scenario))
return scenarios
df
.apply(lambda row: {c: v for c,v in zip(df.columns, row)}, axis=1)
.tolist())
# %%
dcc_params = db.load_dcc_parameters([0.0001, 0.01], [0.01, 0.1],
[0.0, 1.0], [1.0, 10.0])
dcc_params = dataframe2json(dcc_params)
mv_params = db.load_mv_parameters([0.001, 1.0])
mv_params = dataframe2json(mv_params)
experiment_ids = list(range(3, 23))
experiments = db.load_experiments(experiment_ids)
experiments = dataframe2json(experiments)
backtest = {'update_periods': 12,
'trailing_periods': 120}
# %%
def dcc_scenarios(parameter_ids, experiment_ids, backtest_ids):
parameters = dataframe2json(db.load_dcc_parameters_by_id(parameter_ids))
experiments = dataframe2json(db.load_experiments(experiment_ids))
backtests = dataframe2json(db.load_backtests(backtest_ids))
scenarios = list()
for p, e, b in itertools.product(parameters, experiments, backtests):
p = copy.deepcopy(p)
e = copy.deepcopy(e)
