def create_pindex_test(table_name,
T,
T_var,
k,
k_var,
direct_var,
index_name=None,
agg_interval=1.,
col_to_row_ratio=10,
time_column='row_id'):
interface = SqlImplementation(driver="postgresql",
host="localhost",
database="querytime_test",
user="******",
password="******")
time_series_table = [table_name, 'ts', time_column]
T0 = 1000
gamma = 0.5
TSPD = TSPI(T=T,
T_var=T,
rank=k,
rank_var=k_var,
agg_interval=agg_interval,
col_to_row_ratio=col_to_row_ratio,
index_name=index_name,
gamma=gamma,
interface=interface,
time_series_table=time_series_table,
direct_var=direct_var)
TSPD.create_index()
print(TSPD.ts_model._denoiseTS()[-10:], TSPD.ts_model.TimeSeriesIndex)
def ts_table_tests(init_points=10**4,
update_points=[1000, 100, 5000, 10000],
T=1000,
direct_var=True,
index_name='ts_basic_ts_pindex'):
interface = SqlImplementation(driver="postgresql",
host="localhost",
database="querytime_test",
user="******",
password="******")
df = pd.DataFrame(data={'ts': np.arange(init_points).astype('float')})
timestamps = pd.date_range('2012-10-01 00:00:00',
periods=init_points + 1,
freq='5s')
end = timestamps[-1]
df.index = timestamps[:-1]
interface.create_table('ts_basic_ts',
df,
'timestamp',
index_label='timestamp')
time_series_table = ['ts_basic_ts', 'ts', 'timestamp']
T0 = 1000
gamma = 0.5
k = 2
k_var = 1
TSPD = TSPI(_dir='C:/Program Files/PostgreSQL/10/data/',
agg_interval=5,
T=T,
T_var=T,
rank=k,
rank_var=k_var,
col_to_row_ratio=10,
index_name=index_name,
gamma=gamma,
interface=interface,
time_series_table=time_series_table,
direct_var=direct_var)
TSPD.create_index()
interface = SqlImplementation(driver="postgresql",
host="localhost",
database="querytime_test",
user="******",
password="******")
for points in update_points:
df = pd.DataFrame(
data={
'ts': np.arange(init_points, points +
init_points).astype('float')
})
timestamps = pd.date_range(end, periods=points + 1, freq='5s')
end = timestamps[-1]
df.index = timestamps[:-1]
interface.bulk_insert('ts_basic_ts', df, index_label='timestamp')
init_points += points
print('successfully updated %s points' % points)
gamma = 0.5
k = 2
no_ts = 3
# get_prediction_range('tspdb.pindex_mixturets2', 'mixturets2', 'ts_0', interface, 20000,20020)
# get_prediction('tspdb.pindex_mixturets2', 'mixturets2', 'ts_0', interface, 100000+1)
N = 10**6
data = np.zeros([N, no_ts])
for i in range(no_ts):
# data[:,i] = (i+1)*np.arange(N)+np.random.normal(0,0.1,N)
data[:, i] = i
TSPD = TSPI(T=T,
rank=k,
interface=SqlImplementation(driver="postgresql",
host="localhost",
database="querytime_test",
user="******",
password="******"),
value_column=['ts_1', 'ts_7', 'ts_9'],
time_series_table_name=time_series_table[0],
time_column=time_series_table[2])
TSPD.update_model(data)
TSPD.write_model(1)
TSPD2 = load_pindex(interface, 'tspdb.pindex_mixturets_var')
TSPD2 = load_pindex2(interface, 'tspdb.pindex_mixturets_var')
N2 = 10**2
data = np.zeros([N, no_ts])
for i in range(no_ts):
data[:, i] = (i + 1) * np.arange(N, N + N2) + np.random.normal(0, 0.1, N)