def test_artificial_data(self):
dt1 = datetime.datetime(2019, 8, 1)
dt2 = datetime.datetime(2019, 9, 1)
data = artificial_data(dt1, dt2, minutes=24 * 60)
self.assertEqual(data.shape, (27, 2))
data = artificial_data(dt1, dt2, minutes=60)
self.assertEqual(data.shape, (297, 2))
self.assertEqual(data.shape[0] * 1. / 27, data.shape[0] // 27)
def test_clusters2(self):
dt1 = datetime.datetime(2018, 8, 1)
dt2 = datetime.datetime(2019, 8, 15)
data = artificial_data(dt1, dt2, minutes=15)
data['y2'] = data['y'] + 1.
names = numpy.empty(data.shape[0], dtype=str)
names[:] = 'A'
for i in range(1, 20):
names[i::20] = 'BCDEFGHIJKLMNOPQRSTUVWXYZ'[i]
clusters, dists = find_ts_group_pattern(data['time'].values,
data[['y',
'y2']].values, names)
self.assertEqual(clusters.shape[0], dists.shape[0])
self.assertEqual(8, dists.shape[1])
def test_agg_data(self):
dt1 = datetime.datetime(2019, 8, 1)
dt2 = datetime.datetime(2019, 8, 8)
data = artificial_data(dt1, dt2, minutes=15)
data['y'] = 1
agg = aggregate_timeseries(data, per='week')
self.assertEqual(agg.shape, (132, 2))
self.assertEqual(agg['y'].min(), 2)
self.assertEqual(agg['y'].max(), 2)
dt1 = datetime.datetime(2019, 8, 1)
dt2 = datetime.datetime(2019, 8, 15)
data = artificial_data(dt1, dt2, minutes=15)
data['y'] = 1
agg = aggregate_timeseries(data, per='week')
self.assertEqual(agg.shape, (132, 2))
self.assertEqual(agg['y'].min(), 4)
self.assertEqual(agg['y'].max(), 4)
agg = aggregate_timeseries(data, per='month')
self.assertEqual(agg.shape, (264, 2))
self.assertEqual(agg['y'].min(), 2)
self.assertEqual(agg['y'].max(), 2)
def test_plot_data(self):
import matplotlib.pyplot as plt # pylint: disable=C0415
dt1 = datetime.datetime(2019, 8, 1)
dt2 = datetime.datetime(2019, 8, 15)
data = artificial_data(dt1, dt2, minutes=15)
agg = aggregate_timeseries(data, per='week')
ax = plot_week_timeseries(agg['weektime'],
agg['y'],
label="y",
value2=agg['y'] / 2,
label2="y/2",
normalise=False)
self.assertNotEmpty(ax)
if __name__ == "__main__":
plt.show()
plt.clf()
def test_plot_data(self):
try:
import matplotlib.pyplot as plt # pylint: disable=C0415
except Exception as e:
if 'generated new fontManager' in str(e):
warnings.warn(e)
return
raise e
dt1 = datetime.datetime(2019, 8, 1)
dt2 = datetime.datetime(2019, 8, 15)
data = artificial_data(dt1, dt2, minutes=15)
agg = aggregate_timeseries(data, per='week')
ax = plot_week_timeseries(agg['weektime'],
agg['y'],
label="y",
value2=agg['y'] / 2,
label2="y/2",
normalise=False)
self.assertNotEmpty(ax)
if __name__ == "__main__":
plt.show()
plt.clf()