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e4b9a7b | 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 | # Copyright 2020 MONAI Consortium
# 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.
import csv
import os
import tempfile
import unittest
import numpy as np
import torch
from monai.data import CSVSaver
class TestCSVSaver(unittest.TestCase):
def test_saved_content(self):
with tempfile.TemporaryDirectory() as tempdir:
saver = CSVSaver(output_dir=tempdir, filename="predictions.csv")
meta_data = {"filename_or_obj": ["testfile" + str(i) for i in range(8)]}
saver.save_batch(torch.zeros(8), meta_data)
saver.finalize()
filepath = os.path.join(tempdir, "predictions.csv")
self.assertTrue(os.path.exists(filepath))
with open(filepath, "r") as f:
reader = csv.reader(f)
i = 0
for row in reader:
self.assertEqual(row[0], "testfile" + str(i))
self.assertEqual(np.array(row[1:]).astype(np.float32), 0.0)
i += 1
self.assertEqual(i, 8)
if __name__ == "__main__":
unittest.main()
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