def test_tz_aggregation(self):
w = self.widget
data = Timeseries.from_file('airpassengers')[:20]
self.send_signal(w.Inputs.time_series, data)
w.controls.autocommit.click()
output = self.get_output(w.Outputs.time_series)
self.assertEqual(output[0][0], "1949-01-01")
def test_time_var_removed(self):
ts_with_tv = Timeseries.from_file('airpassengers')
# select columns without time variable
ts_without_tv = Timeseries.from_data_table(
ts_with_tv[:, ts_with_tv.domain.class_var])
self.assertTrue(ts_with_tv.time_variable)
# make sure the Timeseries without time variable in domain has
# time_variable set to None
self.assertIsNone(ts_without_tv.time_variable)
def test_tz_aggregation(self):
""" Aggregation should consider timezone """
w = self.widget
data = Timeseries.from_file('airpassengers')[:20]
self.send_signal(w.Inputs.time_series, data)
# select the first item
self.select_item(w, 0)
output = self.get_output(w.Outputs.time_series)
self.assertEqual(output[0][0], "1949-01-01")
def test_no_datetime(self):
""" Raise error if no data with TimeVariable """
w = self.widget
time_series = Timeseries.from_file("airpassengers")
table = Table.from_file('iris')
self.send_signal(w.Inputs.time_series, time_series)
self.assertFalse(w.Error.no_time_variable.is_shown())
self.send_signal(w.Inputs.time_series, table)
self.assertTrue(w.Error.no_time_variable.is_shown())
self.send_signal(w.Inputs.time_series, time_series)
self.assertFalse(w.Error.no_time_variable.is_shown())
def test_no_time_series(self):
"""
Clean variables list view when no data.
GH-46
"""
w = self.widget
time_series = Timeseries.from_file("airpassengers")
self.send_signal(w.Inputs.time_series, time_series)
self.send_signal(w.Inputs.time_series, None)
self.send_signal(w.Inputs.forecast, time_series, 1)
w.configs[0].view.selectAll()
w.configs[0].selection_changed()
def test_no_instances(self):
"""
At least two instances are required.
GH-45
"""
def assert_error_shown(data, is_shown):
self.send_signal(self.widget.Inputs.time_series, data)
self.assertEqual(self.widget.Error.no_instances.is_shown(),
is_shown)
ts = Timeseries.from_file("airpassengers")
self.assertFalse(self.widget.Error.no_instances.is_shown())
for data, is_shown in ((ts[:1], True), (ts, False), (ts[:0], True),
(None, False)):
assert_error_shown(data, is_shown)
def test_new_data(self):
"""
Widget crashes when it gets new data with different domain.
GH-50
"""
w = self.widget
time_series1 = Timeseries.from_file("airpassengers")
url = "http://file.biolab.si/datasets/cyber-security-breaches.tab"
time_series2 = Timeseries.from_url(url)
self.send_signal(w.Inputs.time_series, time_series1)
self.select_item(w, 0)
output1 = self.get_output(w.Outputs.time_series)
self.send_signal(w.Inputs.time_series, time_series2)
self.select_item(w, 0)
output2 = self.get_output(w.Outputs.time_series)
self.assertNotEqual(output1, output2)
def test_negative_values(self):
"""
Multiplicative seasonality does not work if there are negative
values.
GH-35
"""
w = self.widget
table = Timeseries.from_file("iris")
table.X[1, 1] = -1
w.decomposition = 1
w.autocommit = True
self.assertFalse(w.Error.seasonal_decompose_fail.is_shown())
self.send_signal(w.Inputs.time_series, table)
self.widget.view.selectAll()
self.assertTrue(w.Error.seasonal_decompose_fail.is_shown())
self.send_signal(w.Inputs.time_series, None)
self.assertFalse(w.Error.seasonal_decompose_fail.is_shown())
def setUp(self):
data = Timeseries.from_file('airpassengers')
data.Y[:2] = np.nan
data.Y[10:15] = np.nan
data.Y[-2:] = np.nan
self.data = data
times.append(key_time)
subset = data[list(indices)]
xs, ys, ms = [], [], []
for attr, func in self.model:
values = Table.from_table(
Domain([], [], [attr], source=data.domain), subset).metas
out = (xs if attr in data.domain.attributes else
ys if attr in data.domain.class_vars else ms)
out.append(func(values))
X.append(xs)
Y.append(ys)
M.append(ms)
ts = Timeseries(Domain([data.time_variable] + attrs, cvars, metas),
np.column_stack((times, np.row_stack(X))), np.array(Y),
np.array(np.row_stack(M), dtype=object))
self.Outputs.time_series.send(ts)
if __name__ == "__main__":
from AnyQt.QtWidgets import QApplication
a = QApplication([])
ow = OWAggregate()
ow.set_data(Timeseries.from_file('airpassengers'))
ow.show()
a.exec()
def commit(self):
self.Outputs.selected_features.send(self.selected_attributes or None)
def on_select(self):
selected_rows = self.causality_view.selectionModel().selectedRows()
row_indices = [i.row() for i in selected_rows]
row_indices = self.model.mapToSourceRows(row_indices)
attributes = [
self.model[i][j]
for i in row_indices
for j in [COLUMNS.index("Series 1"), COLUMNS.index("Series 2")]
]
# remove duplicated attributes - I know I could use set for this but
# I want to keep the order of attributes - keeping first appearance
# of an attribute and remove the rest
attributes = list(dict.fromkeys(attributes))
self.selected_attributes = [self.data.domain[a] for a in attributes]
self.commit()
def header_click(self, _):
# Store the header states
sort_order = self.model.sortOrder()
sort_column = self.model.sortColumn()
self.sorting = (sort_column, sort_order)
if __name__ == "__main__":
data = Timeseries.from_file("AMZN")
WidgetPreview(OWGrangerCausality).run(data)
def setUp(self):
self.widget: OWGrangerCausality = self.create_widget(OWGrangerCausality)
dataset_dir = os.path.join(os.path.dirname(__file__), "datasets")
self.amzn = Timeseries.from_file(os.path.join(dataset_dir, "AMZN.tab"))[:, :-3]
def test_multiple_on_same_dt(self):
# GH-115
data = Timeseries.from_file(
os.path.join(self.dataset_dir, 'multipleonsamedt.csv'))
self.widget.set_data(data)
self.assertTrue(self.widget.Outputs.subset)
def test_numeric_timedelta(self):
# GH-110
data = Timeseries.from_file(
os.path.join(self.dataset_dir, 'numericdt.csv'))
self.widget.set_data(data)
self.assertTrue(self.widget.Outputs.subset)
def setUp(self):
self.widget = self.create_widget(OWLineChart) # type: OWLineChart
self.airpassengers = Timeseries.from_file("airpassengers")
dataset_dir = os.path.join(os.path.dirname(__file__), "datasets")
self.amzn = Timeseries.from_file(os.path.join(dataset_dir, "AMZN.tab"))
def setUp(self):
self.widget = self.create_widget(OWSpiralogram) # type: OWSpiralogram
self.passengers = Timeseries.from_file("airpassengers")
self.philadelphia = Timeseries.from_url(
'http://datasets.orange.biolab.si/core/philadelphia-crime.csv.xz')
def test_no_timedelta_ts(self):
# GH-126
data = Timeseries.from_file(
os.path.join(self.dataset_dir, 'notddt.csv'))
self.widget.set_data(data)
self.assertTrue(self.widget.Outputs.subset)
def test_unsorted_ts(self):
data = Timeseries.from_file(
os.path.join(self.dataset_dir, 'unsortedts.csv'))
self.widget.set_data(data)
self.assertTrue(self.widget.Outputs.subset)
def test_year_timedelta(self):
data = Timeseries.from_file(
os.path.join(self.dataset_dir, 'yeardt.csv'))
self.widget.set_data(data)
self.assertTrue(self.widget.Outputs.subset)
def test_month_timedelta(self):
data = Timeseries.from_file('airpassengers')
self.widget.set_data(data)
self.assertTrue(self.widget.Outputs.subset)
import unittest
import numpy as np
from orangecontrib.timeseries import Timeseries, periodogram, periodogram_nonequispaced
data = Timeseries.from_file('airpassengers')
class TestPeriodogram(unittest.TestCase):
def test_periodogram(self):
periods, pgram = periodogram(data.Y)
self.assertEqual(max(pgram), 1)
self.assertEqual(np.round(periods[pgram == 1]), 6)
def test_periodogram_nonequispaced(self):
periods, pgram = periodogram_nonequispaced(data.X.ravel(), data.Y, detrend='diff')
self.assertEqual(max(pgram), 1)
def setUp(self):
self.widget = self.create_widget(OWAggregate) # type: OWAggregate
self.time_series = Timeseries.from_file("airpassengers")
