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This will give us the ability to specify different config options for different dataroots. the key of the dataroot dictionary is no longer the same as the dataroot_url. Previously key==dataroot_url, and now those are separated. Added an "is_multi_dataset" function to simplify logic where it branched on single vs multi. Simplified the rest.py interface by no longer passing in the user annotations object, since that can be retrieved from the dataset.
157 lines
6.4 KiB
Python
157 lines
6.4 KiB
Python
import json
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from os import path, listdir
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import unittest
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import server.test.decode_fbs as decode_fbs
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import shutil
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import numpy as np
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import pandas as pd
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from server.common.rest import schema_get_helper, annotations_put_fbs_helper
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from server.test import data_with_tmp_annotations, make_fbs
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from server.data_common.matrix_loader import MatrixDataType
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class WritableAnnotationTest(unittest.TestCase):
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def setUp(self):
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self.data, self.tmp_dir, self.annotations = data_with_tmp_annotations(MatrixDataType.H5AD)
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self.data.dataset_config.user_annotations = self.annotations
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def tearDown(self):
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shutil.rmtree(self.tmp_dir)
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def annotation_put_fbs(self, fbs):
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annotations_put_fbs_helper(self.data, fbs)
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res = json.dumps({"status": "OK"})
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return res
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def test_error_checks(self):
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# verify that the expected errors are generated
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n_rows = self.data.get_shape()[0]
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fbs_bad = make_fbs({"louvain": pd.Series(["undefined"] * n_rows, dtype="category")})
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# ensure we catch attempt to overwrite non-writable data
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with self.assertRaises(KeyError):
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self.annotation_put_fbs(fbs_bad)
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def test_write_to_file(self):
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# verify the file is written as expected
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n_rows = self.data.get_shape()[0]
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fbs = make_fbs(
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{
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"cat_A": pd.Series(["label_A"] * n_rows, dtype="category"),
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"cat_B": pd.Series(["label_B"] * n_rows, dtype="category"),
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}
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)
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res = self.annotation_put_fbs(fbs)
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self.assertEqual(res, json.dumps({"status": "OK"}))
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self.assertTrue(path.exists(self.annotations.output_file))
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df = pd.read_csv(self.annotations.output_file, index_col=0, header=0, comment="#")
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self.assertEqual(df.shape, (n_rows, 2))
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self.assertEqual(set(df.columns), {"cat_A", "cat_B"})
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self.assertTrue(self.data.original_obs_index.equals(df.index))
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self.assertTrue(np.all(df["cat_A"] == ["label_A"] * n_rows))
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self.assertTrue(np.all(df["cat_B"] == ["label_B"] * n_rows))
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# verify complete overwrite on second attempt, AND rotation occurs
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fbs = make_fbs(
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{
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"cat_A": pd.Series(["label_A1"] * n_rows, dtype="category"),
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"cat_C": pd.Series(["label_C"] * n_rows, dtype="category"),
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}
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)
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res = self.annotation_put_fbs(fbs)
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self.assertEqual(res, json.dumps({"status": "OK"}))
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self.assertTrue(path.exists(self.annotations.output_file))
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df = pd.read_csv(self.annotations.output_file, index_col=0, header=0, comment="#")
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self.assertEqual(set(df.columns), {"cat_A", "cat_C"})
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self.assertTrue(np.all(df["cat_A"] == ["label_A1"] * n_rows))
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self.assertTrue(np.all(df["cat_C"] == ["label_C"] * n_rows))
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# rotation
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name, ext = path.splitext(self.annotations.output_file)
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backup_dir = f"{name}-backups"
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self.assertTrue(path.isdir(backup_dir))
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found_files = listdir(backup_dir)
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self.assertEqual(len(found_files), 1)
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def test_file_rotation_to_max_9(self):
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# verify we stop rotation at 9
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n_rows = self.data.get_shape()[0]
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fbs = make_fbs(
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{
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"cat_A": pd.Series(["label_A"] * n_rows, dtype="category"),
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"cat_B": pd.Series(["label_B"] * n_rows, dtype="category"),
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}
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)
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for i in range(0, 11):
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res = self.annotation_put_fbs(fbs)
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self.assertEqual(res, json.dumps({"status": "OK"}))
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name, ext = path.splitext(self.annotations.output_file)
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backup_dir = f"{name}-backups"
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self.assertTrue(path.isdir(backup_dir))
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found_files = listdir(backup_dir)
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self.assertTrue(len(found_files) <= 9)
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def test_put_get_roundtrip(self):
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# verify that OBS PUTs (annotation_put_fbs) are accessible via
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# GET (annotation_to_fbs_matrix)
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n_rows = self.data.get_shape()[0]
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fbs = make_fbs(
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{
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"cat_A": pd.Series(["label_A"] * n_rows, dtype="category"),
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"cat_B": pd.Series(["label_B"] * n_rows, dtype="category"),
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}
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)
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# put
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res = self.annotation_put_fbs(fbs)
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self.assertEqual(res, json.dumps({"status": "OK"}))
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# get
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labels = self.annotations.read_labels(None)
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fbsAll = self.data.annotation_to_fbs_matrix("obs", None, labels)
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schema = schema_get_helper(self.data)
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annotations = decode_fbs.decode_matrix_FBS(fbsAll)
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obs_index_col_name = schema["annotations"]["obs"]["index"]
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self.assertEqual(annotations["n_rows"], n_rows)
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self.assertEqual(annotations["n_cols"], 7)
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self.assertIsNone(annotations["row_idx"])
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self.assertEqual(
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annotations["col_idx"],
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[obs_index_col_name, "n_genes", "percent_mito", "n_counts", "louvain", "cat_A", "cat_B"],
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)
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col_idx = annotations["col_idx"]
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self.assertEqual(annotations["columns"][col_idx.index("cat_A")], ["label_A"] * n_rows)
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self.assertEqual(annotations["columns"][col_idx.index("cat_B")], ["label_B"] * n_rows)
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# verify the schema was updated
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all_col_schema = {c["name"]: c for c in schema["annotations"]["obs"]["columns"]}
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self.assertEqual(
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all_col_schema["cat_A"],
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{"name": "cat_A", "type": "categorical", "categories": ["label_A"], "writable": True},
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)
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self.assertEqual(
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all_col_schema["cat_B"],
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{"name": "cat_B", "type": "categorical", "categories": ["label_B"], "writable": True},
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)
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def test_config(self):
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features = self.data.get_features(self.annotations)
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# test each for singular presence and accuracy of available flag
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def check_feature(method, path, available):
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feature = list(
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filter(lambda f: f.method == method and f.path == path and f.available == available, features)
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)
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self.assertIsNotNone(feature)
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self.assertEqual(len(feature), 1)
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check_feature("POST", "/cluster/", False)
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check_feature("POST", "/diffexp/", self.data.dataset_config.diffexp__enable)
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check_feature("GET", "/layout/obs", True)
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check_feature("PUT", "/layout/obs", self.data.dataset_config.embeddings__enable_reembedding)
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check_feature("PUT", "/annotations/obs", True)
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