def test_interpolateEmptyTS(self):
'''
Checks that an Error is raised if try to interpolate based on an empty ArrayTimeSeries
'''
ts = ArrayTimeSeries([], [])
with self.assertRaises(AssertionError):
ts.interpolate([1])
def test_interpolateNumeric(self):
'''
Checks that an Error is raised if the time sequence input for interpolation contains non numeric elements
'''
test_times = [1, 2, 3, 4, 5]
test_values = [1, 2, 3, 4, 5]
ts = ArrayTimeSeries(test_times, test_values)
with self.assertRaises(AssertionError):
ts.interpolate(list('abcd'))
def test_interpolateBoundaryCondition(self):
'''
Verify if a new time point is smaller than the first time point in the existing time series, the interpolate function outputs the first value; likewise for larger time points.
'''
test_times = [1, 3]
test_values = [3, 9]
ts = ArrayTimeSeries(test_times, test_values)
self.assertEqual(ts.interpolate([3, 5]), [9, 9])
def test_interpolateInBound(self):
'''
Test the interpolate function for a new time input within the boundary of the existing time sequence
'''
test_times = [1, 2]
test_values = [3, 6]
ts = ArrayTimeSeries(test_times, test_values)
self.assertEqual(ts.interpolate([1.5]), [4.5])
def test_interpolateEmptyInput(self):
'''
Checks that an Error is raised if try to interpolate based on an empty ArrayTimeSeries
'''
ts = ArrayTimeSeries([1], [2])
self.assertEqual(ts.interpolate([]), [])