codonPython/tests/tolerance_test.py at 9c96115f2fb15c382c753ee987493b71e70018e8 · NHSDigital/codonPython · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
from codonpython.tolerance import check_tolerance
import numpy as np
import pandas as pd
import pandas.testing as pdt
import pytest

testdata = [
    pd.Series([1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242]),
    pd.Series([1, 2, 3, 4, 5, 5.5, 6, 6.5, 7]),
]


@pytest.mark.parametrize(
    "t, y, to_exclude, poly_features, alpha, parse_dates, expected",
    [
        (
            *testdata,
            2,
            [1, 2],
            0.05,
            False,
            pd.DataFrame(
                {
                    "t": [1241, 1242, 1241, 1242],
                    "yhat_u": [
                        8.11380197739608,
                        9.051653693670929,
                        7.127135023632205,
                        7.735627110021585,
                    ],
                    "yobs": [6.5, 7.0, 6.5, 7.0],
                    "yhat": [
                        7.214285714285714,
                        8.071428571428573,
                        6.500000000000002,
                        6.821428571428574,
                    ],
                    "yhat_l": [
                        6.31476945117535,
                        7.091203449186216,
                        5.872864976367799,
                        5.907230032835563,
                    ],
                    "polynomial": [1, 1, 2, 2],
                }
            ),
        ),
        (
            *testdata,
            2,
            [3],
            0.05,
            False,
            pd.DataFrame(
                {
                    "t": [1241, 1242],
                    "yhat_u": [6.753927165005773, 7.214574732953706],
                    "yobs": [6.5, 7.0],
                    "yhat": [6.0000000000000036, 5.571428571428576],
                    "yhat_l": [5.2460728349942345, 3.928282409903445],
                    "polynomial": [3, 3],
                }
            ),
        ),
        (
            pd.Series(
                [  # Check dates
                    "2012-05-16",
                    "2012-05-17",
                    "2012-05-18",
                    "2012-05-19",
                    "2012-05-20",
                    "2012-05-21",
                    "2012-05-22",
                    "2012-05-23",
                    "2012-05-24",
                ]
            ),
            pd.Series([1, 2, 3, 4, 5, 5.5, 6, 6.5, 7]),
            2,
            [3],
            0.05,
            True,
            pd.DataFrame(
                {
                    "t": ["2012-05-23", "2012-05-24"],
                    "yhat_u": [6.753927165005773, 7.214574732953706],
                    "yobs": [6.5, 7.0],
                    "yhat": [6.0000000000000036, 5.571428571428576],
                    "yhat_l": [5.2460728349942345, 3.928282409903445],
                    "polynomial": [3, 3],
                }
            ),
        ),
    ],
)
def test_tolerance_checking_BAU(
    t, y, to_exclude, poly_features, alpha, parse_dates, expected
):
    obtained = check_tolerance(
        t,
        y,
        to_exclude=to_exclude,
        poly_features=poly_features,
        alpha=alpha,
        parse_dates=parse_dates,
    )
    pdt.assert_frame_equal(expected, obtained)


@pytest.mark.parametrize(
    "t, y, to_exclude, poly_features, alpha",
    [
        (*testdata, 2, "flamingo", 0.05),  # This should be a list
        (*testdata, 2, [2], "flamingo"),  # Needs to be int
        (*testdata, 2, [2], 42),  # Needs to be between 0 and 1
        (*testdata, "flamingo", [2], 0.05),  # Needs to be int
    ],
)
def test_ValueErrors(t, y, to_exclude, poly_features, alpha):
    with pytest.raises(ValueError):
        check_tolerance(
            t, y, to_exclude=to_exclude, poly_features=poly_features, alpha=alpha
        )


@pytest.mark.parametrize(
    "t, y, to_exclude, poly_features, alpha",
    [
        (*testdata, 2, [42], 0.05),  # Elements in the list should be between 0 and 4
        (
            *testdata,
            42,  # Can't have to_exclude making your sample size smaller than 4
            [2],
            0.05,
        ),
        (
            pd.Series(
                [1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, np.nan]
            ),  # Missing t value
            pd.Series([1, 2, 3, 4, 5, 5.5, 6, 6.5, 7]),
            2,
            [2],
            0.05,
        ),
        (
            pd.Series([1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242]),
            pd.Series([1, 2, 3, 4, 5, 5.5, 6, 6.5, np.nan]),  # Missing y value
            2,
            [2],
            0.05,
        ),
    ],
)
def test_AssertionErrors(t, y, to_exclude, poly_features, alpha):
    with pytest.raises(AssertionError):
        check_tolerance(
            t, y, to_exclude=to_exclude, poly_features=poly_features, alpha=alpha
        )