def test(self):
expected = util.matrix_to_dataframe(
[['2019-11-27', 13.88, 0.0005159071471232402],
['2019-11-28', 13.63, 0.000507181628455422]])
input_example = util.matrix_to_dataframe([['2019-11-27', 13.88],
['2019-11-28', 13.63]])
result = logic.calculate_cdi_rate_for_time_series(input_example)
pd.testing.assert_frame_equal(expected, result)
def setUp(self):
if os.path.exists(processed_cdi_prices):
os.remove(processed_cdi_prices)
expected = [
['2019-11-27', 5, 0.0001936305065440],
['2019-11-28', 4, 0.0001556498627913],
['2019-11-29', 3, 0.0001173037138344],
['2019-12-02', 2, 0.0000785849419846],
['2019-12-03', 1, 0.0000394862194537]
]
self.expected = util.matrix_to_dataframe(expected)
def test_for_valid_file(self):
expected = util.matrix_to_dataframe([
['2019-11-27', 5],
['2019-11-28', 4],
['2019-11-29', 3],
['2019-12-02', 2],
['2019-12-03', 1]
])
result = data.load_raw_cdi_prices(raw_cdi_prices)
pd.testing.assert_frame_equal(expected, result)
def test_for_last_days(self):
expected = util.matrix_to_dataframe([
['2020-12-09', 9, 90],
])
start = util.str_to_datetime('2020-12-09')
end = util.str_to_datetime('2020-12-10')
result = logic.filter_by_date_interval(self.input_example, start, end)
result = result.reset_index(drop=True)
pd.testing.assert_frame_equal(expected, result)
def setUp(self):
input_example = [
['2020-12-01', 13.88, 0.00051591],
['2020-12-02', 13.88, 0.00051591],
['2020-12-03', 13.88, 0.00051591],
['2020-12-04', 13.88, 0.00051591],
['2020-12-05', 13.88, 0.00051591],
['2020-12-06', 13.88, 0.00051591],
['2020-12-07', 13.88, 0.00051591],
['2020-12-08', 13.88, 0.00051591],
['2020-12-09', 13.88, 0.00051591],
]
self.input_example = util.matrix_to_dataframe(input_example)
def setUp(self):
input_example = [
['2020-12-01', 1, 10],
['2020-12-02', 2, 20],
['2020-12-03', 3, 30],
['2020-12-04', 4, 40],
['2020-12-05', 5, 50],
['2020-12-06', 6, 60],
['2020-12-07', 7, 70],
['2020-12-08', 8, 80],
['2020-12-09', 9, 90],
]
self.input_example = util.matrix_to_dataframe(input_example)
def test_save_and_load_file(self):
expected = util.matrix_to_dataframe([
['2019-11-27', 5, 0.0001936305065440],
['2019-11-28', 4, 0.0001556498627913],
['2019-11-29', 3, 0.0001173037138344],
['2019-12-02', 2, 0.0000785849419846],
['2019-12-03', 1, 0.0000394862194537]
])
data.save_processed_cdi_prices_file(expected, processed_cdi_prices)
result = data.load_processed_cdi_prices_file(processed_cdi_prices)
pd.testing.assert_frame_equal(expected, result)
def test_for_valid_interval(self):
expected = util.matrix_to_dataframe([
['2020-12-04', 4, 40],
['2020-12-05', 5, 50],
['2020-12-06', 6, 60],
])
start = util.str_to_datetime('2020-12-04')
end = util.str_to_datetime('2020-12-07')
result = logic.filter_by_date_interval(self.input_example, start, end)
result = result.reset_index(drop=True)
pd.testing.assert_frame_equal(expected, result)
def test_if_accumulated_values_are_correct(self):
expected = util.matrix_to_dataframe([
['2020-12-01', 1.0005339668500000],
['2020-12-02', 1.0010682188206000],
['2020-12-03', 1.0016027560640400],
['2020-12-04', 1.0021375787326500],
['2020-12-05', 1.0026726869788300],
['2020-12-06', 1.0032080809550800],
['2020-12-07', 1.0037437608139600],
['2020-12-08', 1.0042797267081300],
['2020-12-09', 1.0048159787903200],
], ['date', 'accumulated'])
cdb = 103.5
result = logic.calculate_accumulated_cdi_rate(self.input_example, cdb)
pd.testing.assert_frame_equal(expected, result)