35 lines
1.2 KiB
Python
35 lines
1.2 KiB
Python
# Copyright 2021 Huawei Technologies Co., Ltd
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
# ============================================================================
|
|
# """test_auc"""
|
|
|
|
import math
|
|
import numpy as np
|
|
from mindspore import Tensor
|
|
from mindspore.nn.metrics import ROC, auc
|
|
|
|
|
|
def test_auc():
|
|
"""test_auc"""
|
|
x = Tensor(np.array([[3, 0, 1], [1, 3, 0], [1, 0, 2]]))
|
|
y = Tensor(np.array([[0, 2, 1], [1, 2, 1], [0, 0, 1]]))
|
|
metric = ROC(pos_label=1)
|
|
metric.clear()
|
|
metric.update(x, y)
|
|
fpr, tpr, thre = metric.eval()
|
|
output = auc(fpr, tpr)
|
|
|
|
assert math.isclose(output, 0.45, abs_tol=0.001)
|
|
assert np.equal(thre, np.array([4, 3, 2, 1, 0])).all()
|