def test_nnet_detector_returns_expected_results(path_to_nnet_config, path_to_output_reference): np.random.seed(0) yass.set_config(path_to_nnet_config) (standarized_path, standarized_params, channel_index, whiten_filter) = preprocess.run() scores, clear, collision = detect.run(standarized_path, standarized_params, channel_index, whiten_filter) path_to_scores = path.join(path_to_output_reference, 'detect_nnet_scores.npy') path_to_clear = path.join(path_to_output_reference, 'detect_nnet_clear.npy') path_to_collision = path.join(path_to_output_reference, 'detect_nnet_collision.npy') ReferenceTesting.assert_array_almost_equal(scores, path_to_scores, decimal=4) ReferenceTesting.assert_array_equal(clear, path_to_clear) ReferenceTesting.assert_array_equal(collision, path_to_collision) clean_tmp()
def handle_notification(r, user): if not user.can_do("notify", r.builder): log.alert("user %s is not allowed to notify:%s" % (user.login, r.builder)) q = B_Queue(path.req_queue_file) q.lock(0) q.read() not_fin = filter(lambda (r): not r.is_done(), q.requests) r.apply_to(q) for r in not_fin: if r.is_done(): util.clean_tmp(path.srpms_dir + '/' + r.id) now = time.time() def leave_it(r): # for ,,done'' set timeout to 4d if r.is_done() and r.time + 4 * 24 * 60 * 60 < now: return False # and for not ,,done'' set it to 20d if r.time + 20 * 24 * 60 * 60 < now: util.clean_tmp(path.srpms_dir + '/' + r.id) return False return True q.requests = filter(leave_it, q.requests) q.write() q.dump(path.queue_stats_file) q.dump_html(path.queue_html_stats_file) q.write_signed(path.req_queue_signed_file) q.unlock()
def test_can_detect_with_nnet(path_to_nnet_config): yass.set_config(path_to_nnet_config) standarized_path, standarized_params, whiten_filter = preprocess.run() scores, clear, collision = detect.run(standarized_path, standarized_params, whiten_filter) clean_tmp()
def test_example_works_pip_and_dict(path_to_config_sample): with open(path_to_config_sample) as f: cfg = yaml.load(f) pipeline.run(cfg) clean_tmp()
def test_templates_returns_expected_results(path_to_threshold_config, path_to_data_folder): np.random.seed(0) yass.set_config(path_to_threshold_config) (standarized_path, standarized_params, channel_index, whiten_filter) = preprocess.run() (score, spike_index_clear, spike_index_all) = detect.run(standarized_path, standarized_params, channel_index, whiten_filter) spike_train_clear, tmp_loc, vbParam = cluster.run(score, spike_index_clear) (templates_, spike_train, groups, idx_good_templates) = templates.run(spike_train_clear, tmp_loc) path_to_templates = path.join(path_to_data_folder, 'output_reference', 'templates.npy') ReferenceTesting.assert_array_equal(templates_, path_to_templates) clean_tmp()
def test_can_detect_with_threshold(path_to_threshold_config): yass.set_config(path_to_threshold_config) (standarized_path, standarized_params, channel_index, whiten_filter) = preprocess.run() scores, clear, collision = detect.run(standarized_path, standarized_params, channel_index, whiten_filter) clean_tmp()
def clean_dir(path, max): curtime = time.time() for i in os.listdir(path): if curtime - os.path.getmtime(path + '/' + i) > max: if os.path.isdir(path + '/' + i): util.clean_tmp(path + '/' + i) else: os.unlink(path + '/' + i)
def clean_dir(path, max): curtime=time.time() for i in os.listdir(path): if curtime - os.path.getmtime(path+'/'+i) > max: if os.path.isdir(path+'/'+i): util.clean_tmp(path+'/'+i) else: os.unlink(path+'/'+i)
def test_decovnolution(path_to_config): yass.set_config('tests/config_nnet.yaml') clear_scores, spike_index_clear, spike_index_collision = preprocess.run() (spike_train_clear, templates, spike_index_collision) = process.run(clear_scores, spike_index_clear, spike_index_collision) deconvolute.run(spike_train_clear, templates, spike_index_collision) clean_tmp()
def leave_it(r): # for ,,done'' set timeout to 4d if r.is_done() and r.time + 4 * 24 * 60 * 60 < now: return False # and for not ,,done'' set it to 20d if r.time + 20 * 24 * 60 * 60 < now: util.clean_tmp(path.srpms_dir + '/' + r.id) return False return True
def test_threshold_pipeline_returns_expected_results(path_to_threshold_config, path_to_data_folder): spike_train = pipeline.run(path_to_threshold_config, clean=True) path_to_reference = path.join(path_to_data_folder, 'output_reference', 'threshold_spike_train.npy') ReferenceTesting.assert_array_equal(spike_train, path_to_reference) clean_tmp()
def test_cluster(path_to_threshold_config): yass.set_config(path_to_threshold_config) (standarized_path, standarized_params, whiten_filter) = preprocess.run() (score, spike_index_clear, spike_index_all) = detect.run(standarized_path, standarized_params, whiten_filter) cluster.run(score, spike_index_clear) clean_tmp()
def test_decovnolution(path_to_threshold_config): yass.set_config('tests/config_nnet.yaml') (standarized_path, standarized_params, whiten_filter) = preprocess.run() (score, spike_index_clear, spike_index_all) = detect.run(standarized_path, standarized_params, whiten_filter) spike_train_clear, tmp_loc, vbParam = cluster.run(score, spike_index_clear) (templates_, spike_train, groups, idx_good_templates) = templates.run(spike_train_clear, tmp_loc) deconvolute.run(spike_index_all, templates_) clean_tmp()
def test_templates(path_to_threshold_config): yass.set_config(path_to_threshold_config) (standarized_path, standarized_params, channel_index, whiten_filter) = preprocess.run() (score, spike_index_clear, spike_index_all) = detect.run(standarized_path, standarized_params, channel_index, whiten_filter) spike_train_clear, tmp_loc, vbParam = cluster.run( score, spike_index_clear) templates.run(spike_train_clear, tmp_loc) clean_tmp()
def test_preprocess_returns_expected_results(path_to_threshold_config, path_to_output_reference): yass.set_config(path_to_threshold_config) standarized_path, standarized_params, whiten_filter = preprocess.run() # load standarized data standarized = np.fromfile(standarized_path, dtype=standarized_params['dtype']) path_to_standarized = path.join(path_to_output_reference, 'preprocess_standarized.npy') path_to_whiten_filter = path.join(path_to_output_reference, 'preprocess_whiten_filter.npy') ReferenceTesting.assert_array_almost_equal(standarized, path_to_standarized) ReferenceTesting.assert_array_almost_equal(whiten_filter, path_to_whiten_filter) clean_tmp()
def test_cluster_returns_expected_results(path_to_threshold_config, path_to_data_folder): np.random.seed(0) yass.set_config(path_to_threshold_config) (standarized_path, standarized_params, whiten_filter) = preprocess.run() (score, spike_index_clear, spike_index_all) = detect.run(standarized_path, standarized_params, whiten_filter) spike_train, tmp_loc, vbParam = cluster.run(score, spike_index_clear) path_to_spike_train = path.join(path_to_data_folder, 'output_reference', 'cluster_spike_train.npy') path_to_tmp_loc = path.join(path_to_data_folder, 'output_reference', 'cluster_tmp_loc.npy') ReferenceTesting.assert_array_equal(spike_train, path_to_spike_train) ReferenceTesting.assert_array_equal(tmp_loc, path_to_tmp_loc) clean_tmp()
def teardown_function(function): reset_config() clean_tmp()
def test_example_works_default_pipeline(path_to_config_sample): pipeline.run(path_to_config_sample) clean_tmp()
def teardown_function(function): clean_tmp()
def test_example_works(path_to_config_sample, path_to_output): cli._run_pipeline(path_to_config_sample, path_to_output) clean_tmp()
def test_can_preprocess_with_nnet(path_to_nn_config): yass.set_config(path_to_nn_config) clear_scores, spike_index_clear, spike_index_collision = preprocess.run() clean_tmp()
def tmp_folder(): make_tmp() yield os.path.join(PATH_TO_TESTS, 'data/tmp/') clean_tmp()