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1# Copyright 2021 Huawei Technologies Co., Ltd
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7# http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14# ============================================================================
15# """test_roc"""
16
17import numpy as np
18import pytest
19from mindspore import Tensor
20from mindspore.nn.metrics import ROC
21
22
23def test_roc():
24    """test_roc_binary"""
25    x = Tensor(np.array([[3, 0, 1], [1, 3, 0], [1, 0, 2]]))
26    y = Tensor(np.array([[0, 2, 1], [1, 2, 1], [0, 0, 1]]))
27    metric = ROC(pos_label=1)
28    metric.clear()
29    metric.update(x, y)
30    fpr, tpr, thresholds = metric.eval()
31
32    assert np.equal(fpr, np.array([0, 0.4, 0.4, 0.6, 1])).all()
33    assert np.equal(tpr, np.array([0, 0, 0.25, 0.75, 1])).all()
34    assert np.equal(thresholds, np.array([4, 3, 2, 1, 0])).all()
35
36
37def test_roc2():
38    """test_roc_multiclass"""
39    x = Tensor(np.array([[0.28, 0.55, 0.15, 0.05], [0.10, 0.20, 0.05, 0.05], [0.20, 0.05, 0.15, 0.05],
40                         [0.05, 0.05, 0.05, 0.75]]))
41    y = Tensor(np.array([0, 1, 2, 3]))
42    metric = ROC(class_num=4)
43    metric.clear()
44    metric.update(x, y)
45    fpr, tpr, thresholds = metric.eval()
46    list1 = [np.array([0., 0., 0.33333333, 0.66666667, 1.]), np.array([0., 0.33333333, 0.33333333, 1.]),
47             np.array([0., 0.33333333, 1.]), np.array([0., 0., 1.])]
48    list2 = [np.array([0., 1., 1., 1., 1.]), np.array([0., 0., 1., 1.]),
49             np.array([0., 1., 1.]), np.array([0., 1., 1.])]
50    list3 = [np.array([1.28, 0.28, 0.2, 0.1, 0.05]), np.array([1.55, 0.55, 0.2, 0.05]),
51             np.array([1.15, 0.15, 0.05]), np.array([1.75, 0.75, 0.05])]
52
53    assert fpr[0].shape == list1[0].shape
54    assert np.equal(tpr[1], list2[1]).all()
55    assert np.equal(thresholds[2], list3[2]).all()
56
57
58def test_roc_update1():
59    x = Tensor(np.array([[0.2, 0.5, 0.7], [0.3, 0.1, 0.2], [0.9, 0.6, 0.5]]))
60    metric = ROC()
61    metric.clear()
62
63    with pytest.raises(ValueError):
64        metric.update(x)
65
66
67def test_roc_update2():
68    x = Tensor(np.array([[0.2, 0.5, 0.7], [0.3, 0.1, 0.2], [0.9, 0.6, 0.5]]))
69    y = Tensor(np.array([1, 0]))
70    metric = ROC()
71    metric.clear()
72
73    with pytest.raises(ValueError):
74        metric.update(x, y)
75
76
77def test_roc_init1():
78    with pytest.raises(TypeError):
79        ROC(pos_label=1.2)
80
81
82def test_roc_init2():
83    with pytest.raises(TypeError):
84        ROC(class_num="class_num")
85
86
87def test_roc_runtime():
88    metric = ROC()
89    metric.clear()
90
91    with pytest.raises(RuntimeError):
92        metric.eval()
93