def plot_gaussian_dates():
"""
Used to demonstrate that the Gaussian date generator is indeed a Gaussian.
This function will display a histogram - it should look bell-shaped!
"""
# generate test data
mean = datetime.datetime(2010, 12, 1, 0, 0)
sigma_in_days = 100
dates = gaussian_date_generator(mean, sigma_in_days)
dates_in_seconds = [(dates.next() - datetime.datetime.utcfromtimestamp(0)).total_seconds()
for _ in range(1000)]
plot_points(dates_in_seconds, 100)
def test_gaussian_date_generator(self):
""" Confirm that the generated dates are distributed according
to a Gaussian. We doe this assertion 10 times.
"""
expected_mean = datetime(2014, 6, 1)
expected_sigma_in_days = 100
gg = gaussian_date_generator(expected_mean, expected_sigma_in_days)
for _ in range(10):
distribution = [next(gg) for _ in range(100000)]
seconds = [convert_datetime_to_seconds(d) for d in distribution]
actual_mean = self.mean(seconds)
diff = actual_mean - convert_datetime_to_seconds(expected_mean)
diff_in_days = seconds_to_days(diff)
one_day = 1
# assert stuff
self.assertLessEqual(diff_in_days, one_day)
actual_sigma = self.standard_deviation(seconds)
diff = abs(actual_sigma - days_to_seconds(expected_sigma_in_days))
self.assertLessEqual(diff, days_to_seconds(1))
