def test_eA1c_mmol_equal_mg(self):
self.simple_df[GLUCOSE] = len(self.simple_df) * [100]
simple_df_mmol = self.simple_df.copy()
simple_df_mmol[GLUCOSE] = simple_df_mmol[GLUCOSE] / 18.02
index_mg = indices.GVeA1c(df=self.simple_df,
calc_config=self.mock_5_mg_config)
index_mmol = indices.GVeA1c(df=simple_df_mmol,
calc_config=self.mock_5_mmol_config)
self.assertAlmostEqual(
index_mg.calculate(),
index_mmol.calculate(),
msg="\neA1c based on mg: {}. eA1c based on mmol: {}\n".format(
index_mg.calculate(), index_mmol.calculate()))
def test_mage_join_extremas_minimas_first(self):
index = indices.GVmage(df=self.simple_df,
calc_config=self.mock_5_mg_config)
minimas = [1, 3, 5]
maximas = [2, 4, 6]
self.assertListEqual(list1=[1, 2, 3, 4, 5, 6],
list2=index._join_extremas(minimas, maximas))
def test_mage_moving_average_window_not_int(self):
index = indices.GVmage(df=self.simple_df,
calc_config=self.mock_5_mg_config)
arr = pd.Series([1, 3, 4, 6, 7])
window_size = "test"
with self.assertRaises(ValueError):
index._moving_average(arr, window_size)
def test_mage_moving_average_arr_not_series(self):
index = indices.GVmage(df=self.simple_df,
calc_config=self.mock_5_mg_config)
arr = [1, 3, 4, 6, 7]
window_size = 2
with self.assertRaises(ValueError):
index._moving_average(arr, window_size)
def test_mage_moving_average_simple_array(self):
index = indices.GVmage(df=self.simple_df,
calc_config=self.mock_5_mg_config)
arr = pd.Series([1, 3, 4, 6, 7])
window_size = 2
self.assertTrue(
np.array_equal(index._moving_average(arr, window_size),
np.array([2, 3.5, 5, 6.5])))
def test_mage_join_extremas_util_maximas_first(self):
index = indices.GVmage(df=self.simple_df,
calc_config=self.mock_5_mg_config)
minimas = [2, 4, 6]
maximas = [1, 3, 5]
joined = [1]
minimas_turn = True
index._join_extremas_util(joined, minimas, maximas, 0, 1, minimas_turn)
self.assertListEqual(list1=[1, 2, 3, 4, 5, 6], list2=joined)
def test_mage_join_extremas_util_different_lengths_arrays(self):
index = indices.GVmage(df=self.simple_df,
calc_config=self.mock_5_mg_config)
minimas = [1, 3, 5]
maximas = [2, 4, 6, 7]
joined = [1]
minimas_turn = False
index._join_extremas_util(joined, minimas, maximas, 1, 0, minimas_turn)
self.assertListEqual(list1=[1, 2, 3, 4, 5, 6], list2=joined)
def test_mean_hypo_event_duration_no_hypo(self):
self.simple_df = pd.DataFrame({
DT:
pd.date_range(start="27-07-2020 12:00", periods=8, freq="5min"),
GLUCOSE: [10, 10, 10, 0, 0, 10, 10, 10]
})
index = indices.GVmean_hypo_event_duration(
df=self.simple_df, calc_config=self.mock_5_mg_config)
self.assertEqual(first=index.calculate(threshold=9,
records_duration=15),
second=0)
def test_conga_all_values_the_same(self):
# Variance should obviously be 0 for a measurement
# made up of all the same values
dates = pd.date_range("12:00 2020/09/11", periods=500, freq="5min")
values = np.repeat(100, repeats=500)
test_df = pd.DataFrame({GLUCOSE: values}, index=dates)
index = indices.GVcongaX(df=test_df, calc_config=self.mock_5_mg_config)
self.assertEqual(
0,
index.calculate(2),
msg="Returned: {}. Expected 0".format(index.calculate(2)),
)
def test_mage_join_extremas_minimas_doubled(self):
index = indices.GVmage(df=self.simple_df,
calc_config=self.mock_5_mg_config)
minimas = [1, 3, 5]
maximas = [2, 6]
self.assertListEqual(
list1=[1, 2, 3, 6],
list2=index._join_extremas(minimas, maximas),
msg="_join_extremas returned: {}, expected: {}".format(
index._join_extremas(minimas, maximas),
[1, 2, 3, 6],
))
def test_mage_runtime_error(self):
# integration test in fact
self.simple_df = pd.DataFrame({
DT:
pd.date_range(start="27-07-2020 12:00", periods=50, freq="5min"),
GLUCOSE:
50 * [100]
})
index = indices.GVmage(df=self.simple_df,
calc_config=self.mock_5_mg_config)
with self.assertRaises(RuntimeError):
index.calculate()
def test_mage_basic_df(self):
# integration test in fact
self.simple_df = pd.DataFrame({
DT:
pd.date_range(start="27-07-2020 12:00", periods=50, freq="5min"),
GLUCOSE:
50 * [100]
})
self.simple_df.iloc[10, 1] = 50
self.simple_df.iloc[20, 1] = 50
self.simple_df.iloc[30, 1] = 300
self.simple_df.iloc[40, 1] = 200
index = indices.GVmage(df=self.simple_df,
calc_config=self.mock_5_mg_config)
self.assertEqual(first=index.calculate(), second=0)
def test_modd_simple_examples(self):
same_values = pd.DataFrame({
DT:
pd.date_range(start="10/11/2020 12:00",
periods=3 * 256,
freq="5min"),
GLUCOSE:
3 * 256 * [100],
})
index = indices.GVmodd(df=same_values,
calc_config=self.mock_5_mg_config)
self.assertEqual(
index.calculate(),
0,
msg="Expected 0 for the array of all equal values. Returned: {}\n".
format(index.calculate()))
def test_set_calc_config_not_calcconfig(self):
with self.assertRaises(ValueError):
indices.GVIndex(df=self.simple_df, calc_config="wrong_class")
def test_call_df_not_pandas(self):
with self.assertRaises(ValueError):
test_ind = indices.GVIndex(df=self.simple_df,
calc_config=self.mock_5_mg_config)
indices.GVIndex.__call__(test_ind, df="test")
def test_set_df_not_pandas(self):
with self.assertRaises(ValueError):
indices.GVIndex(df="test", calc_config=self.mock_5_mg_config)
def test_calculate_not_implemented(self):
with self.assertRaises(NotImplementedError):
indices.GVIndex(df=self.simple_df,
calc_config=self.mock_5_mg_config).calculate()
def test_hbgi(self):
index = indices.GVhbgi(df=self.simple_df,
calc_config=self.mock_5_mg_config)
self.assertAlmostEqual(first=0, second=index.calculate())
def test_lbgi(self):
index = indices.GVlbgi(df=self.simple_df,
calc_config=self.mock_5_mg_config)
self.assertAlmostEqual(first=567.362808824868,
second=index.calculate())
def test_mean_hypo_event_duration_records_duration(self):
index = indices.GVmean_hypo_event_duration(
df=self.simple_df, calc_config=self.mock_5_mg_config)
with self.assertRaises(ValueError):
index.calculate(threshold=0, records_duration="wrong_type")
def test_time_in_hypo_value_error(self):
index = indices.GVtime_in_hypo(df=self.simple_df,
calc_config=self.mock_5_mg_config)
with self.assertRaises(ValueError):
index.calculate(threshold="test")
def test_time_in_hypo(self):
index = indices.GVtime_in_hypo(df=self.simple_df,
calc_config=self.mock_5_mg_config)
self.assertEqual(first=index.calculate(threshold=3), second=10)
def test_hypo_events_count_threshold_duration_not_int(self):
index = indices.GVhypo_events_count(df=self.simple_df,
calc_config=self.mock_5_mg_config)
with self.assertRaises(ValueError):
index.calculate(threshold=0, threshold_duration="test")
def test_call_self_calculate_on_call(self):
with self.assertRaises(NotImplementedError):
base_index = indices.GVIndex(calc_config=self.mock_5_mg_config)
base_index(self.simple_df)
def test_eA1c_simple_df(self):
self.simple_df[GLUCOSE] = len(self.simple_df) * [100]
index = indices.GVeA1c(df=self.simple_df,
calc_config=self.mock_5_mg_config)
self.assertAlmostEqual(first=index.calculate(),
second=5.09752973287909)
def test_grade_hyper_mmol(self):
self.simple_df[GLUCOSE] = len(self.simple_df) * [15]
index = indices.GVgrade_hyper(df=self.simple_df,
calc_config=self.mock_5_mmol_config)
self.assertAlmostEqual(first=index.calculate(), second=1)
def test_auc_simple_df_no_stand(self):
# test on a df with all 1s
self.simple_df[GLUCOSE] = len(self.simple_df) * [1]
index = indices.GVauc(df=self.simple_df,
calc_config=self.mock_5_mg_config)
self.assertEqual(index.calculate(standardize=False), 20)
def test_time_in_range_value_error2(self):
index = indices.GVtime_in_range(df=self.simple_df,
calc_config=self.mock_5_mg_config)
with self.assertRaises(ValueError):
index.calculate(lower_bound="test", upper_bound=1)
def test_hypo_events_count_simple_df(self):
self.simple_df[GLUCOSE] = [1, 1, 3, 2, 2]
index = indices.GVhypo_events_count(df=self.simple_df,
calc_config=self.mock_5_mg_config)
self.assertEqual(index.calculate(threshold=3, threshold_duration=10),
2)
def test_time_in_range_accept_floats(self):
index = indices.GVtime_in_range(df=self.simple_df,
calc_config=self.mock_5_mg_config)
self.assertEqual(index.calculate(lower_bound=1.0, upper_bound=5.0),
0.6)
