def test_grouped_filter(self):
f = Filter().lt('LapCount',
1).group(Filter().gt('Coolant',
212).or_().gt('RPM', 9000))
expected_output = 'datapoint.LapCount < 1 AND (datapoint.Coolant > 212 OR datapoint.RPM > 9000)'
filter_text = str(f).strip()
self.assertSequenceEqual(filter_text, expected_output)
def test_chained_filter(self):
f = Filter().lt('LapCount', 1).gt('Coolant', 212).or_().eq('RPM', 9001)
expected_output = 'datapoint.LapCount < 1 AND datapoint.Coolant > 212 OR datapoint.RPM = 9001'
filter_text = str(f).strip()
self.assertSequenceEqual(filter_text, expected_output)
def test_not_equal_filter(self):
f = Filter().neq('LapCount', 1)
expected_output = 'datapoint.LapCount != 1'
filter_text = str(f).strip()
self.assertSequenceEqual(filter_text, expected_output)
def test_basic_filter(self):
f = Filter().lt('LapCount', 1)
expected_output = 'datapoint.LapCount < 1'
filter_text = str(f).strip()
self.assertSequenceEqual(filter_text, expected_output)
def test_dataset_record_oriented(self):
f = Filter().lt('LapCount', 1)
dataset = self.ds.query(channels=['Coolant', 'RPM', 'MAP'],
data_filter=f)
records = dataset.fetch_records(100)
self.assertEqual(len(records), 100)
def test_dataset_val_count(self):
f = Filter().lt('LapCount', 1)
dataset = self.ds.query(channels=['Coolant', 'RPM', 'MAP'],
data_filter=f)
samples = dataset.fetch_columns(100)
for k in samples.keys():
self.assertEqual(len(samples[k]), 100)
def test_dataset_columns(self):
f = Filter().lt('LapCount', 1)
dataset = self.ds.query(channels=['Coolant', 'RPM', 'MAP'],
data_filter=f)
expected_channels = ['Coolant', 'RPM', 'MAP']
dset_channels = dataset.channels
#Sort both lists to ensure that they'll compare properly
expected_channels.sort()
dset_channels.sort()
self.assertListEqual(expected_channels, dset_channels)
def test_get_all_laptimes(self):
f = Filter().gt('LapCount', 0)
dataset = self.ds.query(sessions=[1],
channels=['LapCount', 'LapTime'],
data_filter=f,
distinct_records=True)
laptimes = {}
records = dataset.fetch_records()
for r in records:
laptimes[int(r[1])] = r[2]
self.assertEqual(laptimes[1], 3.437)
self.assertEqual(laptimes[2], 2.257)
self.assertEqual(laptimes[3], 2.227)
self.assertEqual(laptimes[4], 2.313)
self.assertEqual(laptimes[5], 2.227)
self.assertEqual(laptimes[6], 2.227)
self.assertEqual(laptimes[7], 2.423)
self.assertEqual(laptimes[8], 2.31)
self.assertEqual(laptimes[9], 2.223)
self.assertEqual(laptimes[10], 2.233)
self.assertEqual(laptimes[11], 2.247)
self.assertEqual(laptimes[12], 2.24)
self.assertEqual(laptimes[13], 2.25)
self.assertEqual(laptimes[14], 2.237)
self.assertEqual(laptimes[15], 2.243)
self.assertEqual(laptimes[16], 2.29)
self.assertEqual(laptimes[17], 2.387)
self.assertEqual(laptimes[18], 2.297)
self.assertEqual(laptimes[19], 2.383)
self.assertEqual(laptimes[20], 2.177)
self.assertEqual(laptimes[21], 2.207)
self.assertEqual(laptimes[22], 2.18)
self.assertEqual(laptimes[23], 2.17)
self.assertEqual(laptimes[24], 2.22)
self.assertEqual(laptimes[25], 2.217)
self.assertEqual(laptimes[26], 2.223)
self.assertEqual(laptimes[27], 2.173)
self.assertEqual(laptimes[28], 2.19)
self.assertEqual(laptimes[29], 2.33)
self.assertEqual(laptimes[30], 2.227)
self.assertEqual(laptimes[31], 2.257)
self.assertEqual(laptimes[32], 2.183)
self.assertEqual(laptimes[33], 2.163)
self.assertEqual(laptimes[34], 2.23)
self.assertEqual(laptimes[35], 2.23)
self.assertEqual(laptimes[36], 2.54)
self.assertEqual(laptimes[37], 3.383)
def test_distinct_queries(self):
"""
This is a really basic test to ensure that we always obey the distinct keyword
Distinct should filter out duplicate results, leading to a much smaller dataset
"""
f = Filter().gt('LapCount', 0)
dataset = self.ds.query(sessions=[1],
channels=['LapCount', 'LapTime'],
data_filter=f)
records = dataset.fetch_records()
self.assertEqual(len(records), 24667)
dataset = self.ds.query(sessions=[1],
channels=['LapCount', 'LapTime'],
data_filter=f,
distinct_records=True)
records = dataset.fetch_records()
self.assertEqual(len(records), 37)
