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authorAlexander Kabui2021-04-12 16:53:48 +0300
committerAlexander Kabui2021-04-12 16:53:48 +0300
commit35f5ac0335f44923184ffe0f0a3380a9cf1859ef (patch)
tree8f1fcb15ace3574eb19bd0eafdc5b5bb0822ed09 /tests/integration
parent8ce82f5b6cccc015c38a728864c63c026fe6a3a0 (diff)
parent31ac939f58bf7b6d353ced995ca395376203b25f (diff)
downloadgenenetwork3-35f5ac0335f44923184ffe0f0a3380a9cf1859ef.tar.gz
fix merge conflict
Diffstat (limited to 'tests/integration')
-rw-r--r--tests/integration/test_correlation.py23
1 files changed, 17 insertions, 6 deletions
diff --git a/tests/integration/test_correlation.py b/tests/integration/test_correlation.py
index bc3f542..e67f58d 100644
--- a/tests/integration/test_correlation.py
+++ b/tests/integration/test_correlation.py
@@ -62,13 +62,17 @@ class CorrelationIntegrationTest(TestCase):
self.assertEqual(response.get_json(), api_response)
@mock.patch("gn3.api.correlation.compute_all_lit_correlation")
- def test_lit_correlation(self, mock_compute_corr):
+ @mock.patch("gn3.api.correlation.database_connector")
+ def test_lit_correlation(self, database_connector, mock_compute_corr):
"""Test api/correlation/lit_corr/{species}/{gene_id}"""
mock_compute_corr.return_value = []
- post_data = [{"gene_id": 8, "lit_corr": 1}, {
- "gene_id": 12, "lit_corr": 0.3}]
+ database_connector.return_value = (mock.Mock(), mock.Mock())
+
+ post_data = {"1426678_at": "68031",
+ "1426679_at": "68036",
+ "1426680_at": "74777"}
response = self.app.post(
"/api/correlation/lit_corr/mouse/16", json=post_data, follow_redirects=True)
@@ -81,13 +85,20 @@ class CorrelationIntegrationTest(TestCase):
"""Test api/correlation/tissue_corr/{corr_method}"""
mock_tissue_corr.return_value = {}
+ target_trait_symbol_dict = {
+ "1418702_a_at": "Bxdc1", "1412_at": "Bxdc2"}
+ symbol_tissue_dict = {
+ "bxdc1": [12, 21.1, 11.4, 16.7], "bxdc2": [12, 20.1, 12.4, 1.1]}
+
primary_dict = {"trait_id": "1449593_at", "tissue_values": [1, 2, 3]}
- target_tissue_dict_list = [
- {"trait_id": "1449593_at", "tissue_values": [1, 2, 3]}]
+ target_tissue_data = {
+ "trait_symbol_dict": target_trait_symbol_dict,
+ "symbol_tissue_vals_dict": symbol_tissue_dict
+ }
tissue_corr_input_data = {"primary_tissue": primary_dict,
- "target_tissues": target_tissue_dict_list}
+ "target_tissues_dict": target_tissue_data}
response = self.app.post("/api/correlation/tissue_corr/spearman",
json=tissue_corr_input_data, follow_redirects=True)