| # 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() | |