def setUp(self):
self.df = select_mungedata(2, 1, '2013-1-1', '2015-1-1')
self.xtest = select_features('2015-1-1', '2015-1-10')
self.actuals = select_mungedata_simple(2, 1, '2015-1-1', '2015-1-10')
self.daily_avg = self.df.waittime.resample('D', how='mean')
model = RandomForestRegressor(n_jobs=-1,
n_estimators=2,
random_state=1)
self.im = IncrementalModel(self.df, model, categoricals=['event'])
self.im.predict(self.xtest)
def setUp(self):
self.df = select_mungedata(2, 1, '2013-1-1', '2015-1-1')
self.xtest = select_features('2015-1-1', '2015-1-10')
self.actuals = select_mungedata_simple(2, 1, '2015-1-1', '2015-1-10')
self.daily_avg = self.df.waittime.resample('D', how='mean')
model = RandomForestRegressor(n_jobs=-1, n_estimators=2,
random_state=1)
self.im = IncrementalModel(self.df, model, categoricals=['event'])
self.im.predict(self.xtest)
class TestIncrementalModel(unittest.TestCase):
def setUp(self):
self.df = select_mungedata(2, 1, '2013-1-1', '2015-1-1')
self.xtest = select_features('2015-1-1', '2015-1-10')
self.actuals = select_mungedata_simple(2, 1, '2015-1-1', '2015-1-10')
self.daily_avg = self.df.waittime.resample('D', how='mean')
model = RandomForestRegressor(n_jobs=-1,
n_estimators=2,
random_state=1)
self.im = IncrementalModel(self.df, model, categoricals=['event'])
self.im.predict(self.xtest)
def test_deltas(self):
df = self.im.deltas(self.df.waittime)
self.assertAlmostEqual(
df.loc['2014-2-20 15:30'].avg_delta_2,
self.daily_avg.loc['2014-2-19'] - self.daily_avg.loc['2014-2-5'])
def test_baseline(self):
baseline = self.im.baseline()
self.assertEqual(len(baseline), len(self.im.y_predict))
self.assertEqual(baseline.loc['2015-1-2 21:30'],
baseline.loc['2015-1-9 21:30'])
def test_set_actual(self):
actual = select_mungedata_simple(2, 1, '2015-1-1', '2015-1-10')
self.im.set_actual(actual.waittime)
self.assertEqual(actual.ix[24].waittime, self.im.actual.ix[24])
def test_run_Incremental(self):
model = RandomForestRegressor(n_jobs=-1,
n_estimators=2,
random_state=1)
im = run_Incremental(model, 2, 1, '2013-1-1', '2015-1-1', '2015-1-1',
'2015-1-10')
self.assertEqual(im.score(), self.im.score(self.actuals.waittime))
class TestIncrementalModel(unittest.TestCase):
def setUp(self):
self.df = select_mungedata(2, 1, '2013-1-1', '2015-1-1')
self.xtest = select_features('2015-1-1', '2015-1-10')
self.actuals = select_mungedata_simple(2, 1, '2015-1-1', '2015-1-10')
self.daily_avg = self.df.waittime.resample('D', how='mean')
model = RandomForestRegressor(n_jobs=-1, n_estimators=2,
random_state=1)
self.im = IncrementalModel(self.df, model, categoricals=['event'])
self.im.predict(self.xtest)
def test_deltas(self):
df = self.im.deltas(self.df.waittime)
self.assertAlmostEqual(df.loc['2014-2-20 15:30'].avg_delta_2,
self.daily_avg.loc['2014-2-19'] -
self.daily_avg.loc['2014-2-5'])
def test_baseline(self):
baseline = self.im.baseline()
self.assertEqual(len(baseline), len(self.im.y_predict))
self.assertEqual(baseline.loc['2015-1-2 21:30'],
baseline.loc['2015-1-9 21:30'])
def test_set_actual(self):
actual = select_mungedata_simple(2, 1, '2015-1-1', '2015-1-10')
self.im.set_actual(actual.waittime)
self.assertEqual(actual.ix[24].waittime, self.im.actual.ix[24])
def test_run_Incremental(self):
model = RandomForestRegressor(n_jobs=-1, n_estimators=2,
random_state=1)
im = run_Incremental(model, 2, 1, '2013-1-1', '2015-1-1',
'2015-1-1', '2015-1-10')
self.assertEqual(im.score(), self.im.score(self.actuals.waittime))