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tests.py
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tests.py
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import unittest
from datetime import timedelta, datetime, timezone
from random import randint, random
from pandas import DataFrame, date_range#, Index
from numpy import nan
from compost import Dataset, ShortDatasetError, SubMinuteTimestepError
from compost import SavingCalculation, DailyAverageModel
class TestDatasetCreation(unittest.TestCase):
"""tests for error states in constructor"""
def setUp(self):
index = date_range('1/1/2015', periods=365)
self.df = DataFrame(list(range(len(index))), index=index, columns=['value'])
def test_sub_minute(self):
self.assertRaises(SubMinuteTimestepError, Dataset, self.df, 30, cumulative=False)
def test_sub_minute_edge(self):
self.assertRaises(SubMinuteTimestepError, Dataset, self.df, 59, cumulative=False)
def test_sub_minute_negative(self):
self.assertRaises(SubMinuteTimestepError, Dataset, self.df, -4, cumulative=False)
def test_sub_minute_one_and_a_bit(self):
self.assertRaises(SubMinuteTimestepError, Dataset, self.df, 64, cumulative=False)
def test_minute_ok(self):
try:
Dataset(self.df, 60, cumulative=False)
except SubMinuteTimestepError:
self.fail("Dataset(df, 60) raised SubMinuteTimestepError!")
class TestPerfectData(unittest.TestCase):
"""what happens with nice data"""
def setUp(self):
index = date_range('1/1/2015', periods=365)
self.df = DataFrame(list(range(len(index))), index=index, columns=['value'])
self.dataset = Dataset(self.df, 60*60*24, cumulative=False)
def test_validates(self):
self.assertTrue(self.dataset.validate())
def test_partial_validates(self):
"""cut the data up and it still works"""
d = Dataset(self.df.head(100), 60*60*24, cumulative=False)
self.assertTrue(d.validate())
def test_short_raises(self):
"""single value datasets raise an error"""
d = Dataset(self.df.head(1), 60*60*24, cumulative=False)
self.assertRaises(ShortDatasetError, d.validate)
def test_interpolate_skipped(self):
d2 = self.dataset.interpolate()
self.assertEqual(self.dataset, d2)
class InterpolatedDataTests(object):
"""common tests for data that needs work"""
def test_validation_fails(self):
self.assertFalse(self.dataset.validate())
def test_interpolate_validates(self):
d1 = self.dataset.interpolate()
self.assertTrue(d1.validate())
def test_interpolate_maintains_total(self):
d1 = self.dataset.interpolate()
self.assertEqual(self.dataset.total(), d1.total())
class TestLowResData(InterpolatedDataTests, unittest.TestCase):
"""what happens with e.g. weekly data"""
def setUp(self):
index = date_range('1/1/2015', periods=5, freq="7D")
df = DataFrame(list(range(len(index))), index=index, columns=['value'])
self.dataset = Dataset(df, 60*60*24, cumulative=False)
super(TestLowResData, self).setUp()
class TestCumulativeLowResData(InterpolatedDataTests, unittest.TestCase):
"""what happens with e.g. weekly cumulative data"""
def setUp(self):
index = date_range('1/1/2015', periods=5, freq="7D")
df = DataFrame(list(range(len(index))), index=index, columns=['value'])
self.dataset = Dataset(df, 60*60*24, cumulative=True)
super(TestCumulativeLowResData, self).setUp()
class TestMissingLowResData(InterpolatedDataTests, unittest.TestCase):
"""what happens when weekly data has missing values?"""
def setUp(self):
index = date_range('1/1/2015', periods=52, freq="7D")
df = DataFrame(list(range(len(index))), index=index, columns=['value'])[index.month != 5]
self.dataset = Dataset(df, 60*60*24, cumulative=False)
super(TestMissingLowResData, self).setUp()
class TestMissingCumulativeLowResData(InterpolatedDataTests, unittest.TestCase):
"""what happens when cumulative weekly data has missing values?"""
def setUp(self):
index = date_range('1/1/2015', periods=52, freq="7D")
df = DataFrame(list(range(len(index))), index=index, columns=['value'])[index.month != 5]
self.dataset = Dataset(df, 60*60*24, cumulative=True)
super(TestMissingCumulativeLowResData, self).setUp()
class TestHighResData(InterpolatedDataTests, unittest.TestCase):
"""what happens with e.g. 15-minutely data"""
def setUp(self):
index = date_range('1/1/2015', periods=4*24*365, freq="15Min")
df = DataFrame(list(range(len(index))), index=index, columns=['value'])
self.dataset = Dataset(df, 60*60*24, cumulative=False)
super(TestHighResData, self).setUp()
class TestCumulativeHighResData(InterpolatedDataTests, unittest.TestCase):
"""what happens with e.g. 15-minutely cumulative data"""
def setUp(self):
index = date_range('1/1/2015', periods=4*24*365, freq="15Min")
df = DataFrame(list(range(len(index))), index=index, columns=['value'])
self.dataset = Dataset(df, 60*60*24, cumulative=True)
super(TestCumulativeHighResData, self).setUp()
class TestMissingHighResData(InterpolatedDataTests, unittest.TestCase):
"""what happens when 15-minutely data has missing values?"""
def setUp(self):
index = date_range('1/1/2015', periods=4*24*365, freq="15Min")
df = DataFrame(list(range(len(index))), index=index, columns=['value'])[index.day != 5]
self.dataset = Dataset(df, 60*60*24, cumulative=False)
super(TestMissingHighResData, self).setUp()
class TestMissingCumulativeHighResData(InterpolatedDataTests, unittest.TestCase):
"""what happens when cumulative 15-minutely data has missing values?"""
def setUp(self):
index = date_range('1/1/2015', periods=4*24*365, freq="15Min")
df = DataFrame(list(range(len(index))), index=index, columns=['value'])[index.day != 5]
self.dataset = Dataset(df, 60*60*24, cumulative=True)
super(TestMissingCumulativeHighResData, self).setUp()
# class TestHighResWithMissingData(unittest.TestCase):
# """what happens when 15-minutely data has missing values?"""
#
# def setUp(self):
# index = date_range('1/1/2015', periods=4*24*365, freq="15Min")
# self.df = DataFrame(list(range(len(index))), index=index, columns=['value'])[index.day >= 3]
# self.dataset1 = Dataset(self.df, 60*60*24)
# self.dataset2 = Dataset(self.df, 60*60*24, cumulative=True)
# def test_validation_fails(self):
# self.assertFalse(self.dataset1.validate())
#
# def test_interpolate_validates(self):
# d1 = self.dataset1.interpolate()
# d2 = self.dataset2.interpolate()
# self.assertTrue(d1.validate())
# self.assertTrue(d2.validate())
#
# def test_interpolate_maintains_total(self):
# # print(self.dataset1.measurements.head(5))
# d1 = self.dataset1.interpolate()
# # print(d1.measurements.head(5))
# d2 = self.dataset2.interpolate()
# self.assertEqual(self.dataset1.measurements.value.sum(), d1.measurements.value.sum())
# self.assertEqual(self.dataset2.measurements.diff().value.sum(), d2.measurements.diff().value.sum())
# class TestDatasetValidation(unittest.TestCase):
#
# def setUp(self):
# index = date_range('1/1/2015', periods=365)
# self.df = DataFrame(list(range(365)), index=index, columns=['value'])
#
# def test_missing(self):
# d = Dataset(self.df[self.df.index.day != 1], 60*60*24)
# self.assertFalse(d.validate())
#
# def test_bad_resolution(self):
# d = Dataset(self.df[self.df.index.day != 1], 60*60*12)
# self.assertFalse(d.validate())
#
#
# class TestDatasetInterpolation(unittest.TestCase):
#
# def setUp(self):
# index = date_range('1/1/2015', periods=366)
# self.df = DataFrame(list(range(366)), index=index, columns=['value'])
#
#
# def test_low_resolution(self):
# d1 = Dataset(self.df, 60*60*12)
# d2 = d1.interpolate()
# self.assertTrue(d2.validate())
#
# def test_high_resolution(self):
# d1 = Dataset(self.df, 60*60*48)
# d2 = d1.interpolate()
# self.assertTrue(d2.validate())
#
# def test_high_resolution_cumulative(self):
# d1 = Dataset(self.df, 60*60*48, cumulative=True)
# d2 = d1.interpolate()
# self.assertTrue(d2.validate())
#
# def test_missing_data(self):
# df = self.df[self.df.index.day != 5] #cut out some data
# d1 = Dataset(df, 60*60*48)
# d2 = d1.interpolate()
# self.assertTrue(d2.validate())
#
# def test_randomised_index(self):
# index = Index([i + timedelta(seconds=randint(-100,100)) for i in self.df.index])
# self.df.index = index
# d1 = Dataset(self.df, 60*60*48)
# d2 = d1.normalise()
# self.assertTrue(d2.validate())
#
class TestSavingCalculation(unittest.TestCase):
def setUp(self):
index = date_range('1/1/2015', periods=4*24*365, freq="15Min")
self.df = DataFrame([random() for i in range(len(index))], index=index, columns=['value'])[index.day != 5]
def test_something(self):
class DateRange(object):
def __init__(self, start, end):
self.start_date = start.replace(tzinfo=timezone.utc)
self.end_date = end.replace(tzinfo=timezone.utc)
baseline = DateRange(datetime(2015,1,1), datetime(2015,4,30))
competition = DateRange(datetime(2015,5,1), datetime(2015,8,31))
sc = SavingCalculation(self.df, DailyAverageModel, competition, baseline, cumulative=False)
savings = sc.savings()
if __name__ == "__main__":
from pandas import __version__
print(f"pandas v{__version__}")
unittest.main()