Mercurial > repos > galaxy-australia > alphafold2

comparison docker/alphafold/run_alphafold_test.py @ 1:6c92e000d684 draft

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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
author galaxy-australia
date Tue, 01 Mar 2022 02:53:05 +0000
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0:7ae9d78b06f5 1:6c92e000d684
1 # Copyright 2021 DeepMind Technologies Limited
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 """Tests for run_alphafold."""
16
17 import os
18
19 from absl.testing import absltest
20 from absl.testing import parameterized
21 import run_alphafold
22 import mock
23 import numpy as np
24 # Internal import (7716).
25
26
27 class RunAlphafoldTest(parameterized.TestCase):
28
29 @parameterized.named_parameters(
30 ('relax', True),
31 ('no_relax', False),
32 )
33 def test_end_to_end(self, do_relax):
34
35 data_pipeline_mock = mock.Mock()
36 model_runner_mock = mock.Mock()
37 amber_relaxer_mock = mock.Mock()
38
39 data_pipeline_mock.process.return_value = {}
40 model_runner_mock.process_features.return_value = {
41 'aatype': np.zeros((12, 10), dtype=np.int32),
42 'residue_index': np.tile(np.arange(10, dtype=np.int32)[None], (12, 1)),
43 }
44 model_runner_mock.predict.return_value = {
45 'structure_module': {
46 'final_atom_positions': np.zeros((10, 37, 3)),
47 'final_atom_mask': np.ones((10, 37)),
48 },
49 'predicted_lddt': {
50 'logits': np.ones((10, 50)),
51 },
52 'plddt': np.ones(10) * 42,
53 'ranking_confidence': 90,
54 'ptm': np.array(0.),
55 'aligned_confidence_probs': np.zeros((10, 10, 50)),
56 'predicted_aligned_error': np.zeros((10, 10)),
57 'max_predicted_aligned_error': np.array(0.),
58 }
59 model_runner_mock.multimer_mode = False
60 amber_relaxer_mock.process.return_value = ('RELAXED', None, None)
61
62 fasta_path = os.path.join(absltest.get_default_test_tmpdir(),
63 'target.fasta')
64 with open(fasta_path, 'wt') as f:
65 f.write('>A\nAAAAAAAAAAAAA')
66 fasta_name = 'test'
67
68 out_dir = absltest.get_default_test_tmpdir()
69
70 run_alphafold.predict_structure(
71 fasta_path=fasta_path,
72 fasta_name=fasta_name,
73 output_dir_base=out_dir,
74 data_pipeline=data_pipeline_mock,
75 model_runners={'model1': model_runner_mock},
76 amber_relaxer=amber_relaxer_mock if do_relax else None,
77 benchmark=False,
78 random_seed=0)
79
80 base_output_files = os.listdir(out_dir)
81 self.assertIn('target.fasta', base_output_files)
82 self.assertIn('test', base_output_files)
83
84 target_output_files = os.listdir(os.path.join(out_dir, 'test'))
85 expected_files = [
86 'features.pkl', 'msas', 'ranked_0.pdb', 'ranking_debug.json',
87 'result_model1.pkl', 'timings.json', 'unrelaxed_model1.pdb',
88 ]
89 if do_relax:
90 expected_files.append('relaxed_model1.pdb')
91 self.assertCountEqual(expected_files, target_output_files)
92
93 # Check that pLDDT is set in the B-factor column.
94 with open(os.path.join(out_dir, 'test', 'unrelaxed_model1.pdb')) as f:
95 for line in f:
96 if line.startswith('ATOM'):
97 self.assertEqual(line[61:66], '42.00')
98
99
100 if __name__ == '__main__':
101 absltest.main()