def run_on_random(num_ts=5, n_points=70, prompt=False):
n_plots_long = 5
n_plots_wide = 1
i = 0
#timescale = (5, 'day')
timescale = None
params = {'beta_step': 1000,
'beta_d1': 0.0,
'beta_d2': 1.0
}
for seed in xrange(num_ts):
print 'seed: %s' % seed
t, y = make_random_ts(n_points, seed=seed)
model = ZaggyModel(t, y, timescale=timescale, params=params)
model.fit()
if doplot:
if i % (n_plots_long*n_plots_wide) == 0:
plt.clf()
n_plot = (i % (n_plots_long*n_plots_wide)) + 1
plt.subplot(n_plots_long, n_plots_wide, n_plot)
plt.plot(t, y)
plt.plot(t, model.solution['model'])
if prompt:
ans = raw_input('ok?:')
if ans == 'q':
return
i += 1
def make_simple_plot(params=None):
mock = get_mock_with_dates()
plot_mock(mock)
timescale = (1.0, 'month')
model = ZaggyModel(mock['dates'], mock['y'], timescale=timescale,
params=params)
model.fit()
plot_model(model)
plt.legend()
return model
def test_zaggy_predict_on_fitted_points(self):
self.model = ZaggyModel(self.dates, self.y)
self.model.fit()
results = self.model.predict(self.dates)
assert isinstance(results, ndarray)
for expected, result in zip(self.model.solution['model'], results):
self.assertEquals(expected, result)
def test_zaggy_predict_is_zero_on_dates_before_first_data_point(self):
self.model = ZaggyModel(self.dates, self.y)
self.model.fit()
old_dates = date_range(2013, 1, 2014, 12)
results = self.model.predict(old_dates)
for expected, result in zip(self.model.solution['model'], results):
self.assertEquals(result, 0.0)
def make_extrapolatad_plot(params=None):
mock = get_mock_with_dates()
plot_mock(mock)
timescale = (1.0, 'month')
model = ZaggyModel(mock['dates'], mock['y'], timescale=timescale,
params=params)
model.fit()
plot_model(model)
dates = date_range(2022, 1, 2024, 12)
results = model.predict(dates)
plt.plot(dates, results, color='orange', alpha=0.7, marker='d',
label='predictions')
dates = date_range(2014, 1, 2016, 1)
results = model.predict(dates)
plt.plot(dates, results, color='orange', alpha=0.7, marker='s',
label='predictions (earlier)')
plt.legend(loc='upper left')
return model
def test_zaggy_model_fit_runs(self):
self.model = ZaggyModel(self.dates, self.y)
self.assertIsNone(self.model.solution)
self.model.fit()
self.assertIsNotNone(self.model.solution)
self.assertIsNotNone(self.model.slope)
self.assertIsNotNone(self.model.offset)
self.assertIsNotNone(self.model.seasonal)
self.assertIsNotNone(self.model.interpolate)
self.assertIsNotNone(self.model.extrapolate_without_seasonal)
self.assertIsNotNone(self.model.seasonality_function)
self.assertIsNotNone(self.model.date_to_seasonal_component)
self.assertIsNotNone(self.model.compression_dict)
class TestZaggyModel(TestCase):
def setUp(self):
mock = make_mock()
self.y = mock['y']
num = len(self.y)
self.dates = date_range(2015, 1, 2029, 12)[0: num]
def test_zaggy_model_runs(self):
self.model = ZaggyModel(self.dates, self.y)
assert True
def test_zaggy_model_fit_runs(self):
self.model = ZaggyModel(self.dates, self.y)
self.assertIsNone(self.model.solution)
self.model.fit()
self.assertIsNotNone(self.model.solution)
self.assertIsNotNone(self.model.slope)
self.assertIsNotNone(self.model.offset)
self.assertIsNotNone(self.model.seasonal)
self.assertIsNotNone(self.model.interpolate)
self.assertIsNotNone(self.model.extrapolate_without_seasonal)
self.assertIsNotNone(self.model.seasonality_function)
self.assertIsNotNone(self.model.date_to_seasonal_component)
self.assertIsNotNone(self.model.compression_dict)
def test_zaggy_predict_on_fitted_points(self):
self.model = ZaggyModel(self.dates, self.y)
self.model.fit()
results = self.model.predict(self.dates)
assert isinstance(results, ndarray)
for expected, result in zip(self.model.solution['model'], results):
self.assertEquals(expected, result)
def test_zaggy_predict_is_zero_on_dates_before_first_data_point(self):
self.model = ZaggyModel(self.dates, self.y)
self.model.fit()
old_dates = date_range(2013, 1, 2014, 12)
results = self.model.predict(old_dates)
for expected, result in zip(self.model.solution['model'], results):
self.assertEquals(result, 0.0)
def test_zaggy_model_runs(self):
self.model = ZaggyModel(self.dates, self.y)
assert True
