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authorBonfaceKilz2020-09-28 13:38:23 +0300
committerGitHub2020-09-28 13:38:23 +0300
commit131bfa7bf63ec7d92f5734bddcd46c50f00f85ea (patch)
treef11a3373654016bd333c77ef4bff6d0dc26eff7d /wqflask/tests
parent3ec4eb6b831eaa5adcf32a9fca8a60ea229cc1c4 (diff)
parent312835014d8d243c72f3520bb116eb3c36cd6b85 (diff)
downloadgenenetwork2-131bfa7bf63ec7d92f5734bddcd46c50f00f85ea.tar.gz
Merge pull request #446 from BonfaceKilz/Bug/Fix-casting-error
Bug/fix casting error
Diffstat (limited to 'wqflask/tests')
-rw-r--r--wqflask/tests/base/test_trait.py134
1 files changed, 134 insertions, 0 deletions
diff --git a/wqflask/tests/base/test_trait.py b/wqflask/tests/base/test_trait.py
index 960f2c81..1a3820f2 100644
--- a/wqflask/tests/base/test_trait.py
+++ b/wqflask/tests/base/test_trait.py
@@ -99,3 +99,137 @@ class TestRetrieveTraitInfo(unittest.TestCase):
"ファイルを画面毎に見て行くには、次のコマンドを使います。".decode('utf-8'))
self.assertEqual(test_trait.authors,
"Jane Doe かいと".decode('utf-8'))
+
+ @mock.patch('base.trait.requests.get')
+ @mock.patch('base.trait.g')
+ @mock.patch('base.trait.get_resource_id')
+ def test_retrieve_trait_info_with_non_empty_lrs(self,
+ resource_id_mock,
+ g_mock,
+ requests_mock):
+ """Test """
+ resource_id_mock.return_value = 1
+ g_mock.db.execute.return_value.fetchone = mock.Mock()
+ g_mock.db.execute.return_value.fetchone.side_effect = [
+ [1, 2, 3, 4], # trait_info = g.db.execute(query).fetchone()
+ [1, 2.37, 3, 4, 5], # trait_qtl = g.db.execute(query).fetchone()
+ [2.7333, 2.1204] # trait_info = g.db.execute(query).fetchone()
+ ]
+ requests_mock.return_value = None
+
+ mock_dataset = mock.MagicMock()
+ type(mock_dataset).display_fields = mock.PropertyMock(
+ return_value=["a", "b", "c", "d"])
+ type(mock_dataset).type = "ProbeSet"
+ type(mock_dataset).name = "RandomName"
+
+ mock_trait = MockTrait(
+ dataset=mock_dataset,
+ pre_publication_description="test_string"
+ )
+ trait_attrs = {
+ "description": "some description",
+ "probe_target_description": "some description",
+ "cellid": False,
+ "chr": 2.733,
+ "mb": 2.1204
+ }
+
+ for key, val in list(trait_attrs.items()):
+ setattr(mock_trait, key, val)
+ test_trait = retrieve_trait_info(trait=mock_trait,
+ dataset=mock_dataset,
+ get_qtl_info=True)
+ self.assertEqual(test_trait.LRS_score_repr,
+ "2.4")
+
+ @mock.patch('base.trait.requests.get')
+ @mock.patch('base.trait.g')
+ @mock.patch('base.trait.get_resource_id')
+ def test_retrieve_trait_info_with_empty_lrs_field(self,
+ resource_id_mock,
+ g_mock,
+ requests_mock):
+ """Test retrieve trait info with empty lrs field"""
+ resource_id_mock.return_value = 1
+ g_mock.db.execute.return_value.fetchone = mock.Mock()
+ g_mock.db.execute.return_value.fetchone.side_effect = [
+ [1, 2, 3, 4], # trait_info = g.db.execute(query).fetchone()
+ [1, None, 3, 4, 5], # trait_qtl = g.db.execute(query).fetchone()
+ [2, 3] # trait_info = g.db.execute(query).fetchone()
+ ]
+ requests_mock.return_value = None
+
+ mock_dataset = mock.MagicMock()
+ type(mock_dataset).display_fields = mock.PropertyMock(
+ return_value=["a", "b", "c", "d"])
+ type(mock_dataset).type = "ProbeSet"
+ type(mock_dataset).name = "RandomName"
+
+ mock_trait = MockTrait(
+ dataset=mock_dataset,
+ pre_publication_description="test_string"
+ )
+ trait_attrs = {
+ "description": "some description",
+ "probe_target_description": "some description",
+ "cellid": False,
+ "chr": 2.733,
+ "mb": 2.1204
+ }
+
+ for key, val in list(trait_attrs.items()):
+ setattr(mock_trait, key, val)
+ test_trait = retrieve_trait_info(trait=mock_trait,
+ dataset=mock_dataset,
+ get_qtl_info=True)
+ self.assertEqual(test_trait.LRS_score_repr,
+ "N/A")
+ self.assertEqual(test_trait.LRS_location_repr,
+ "Chr2: 3.000000")
+
+ @mock.patch('base.trait.requests.get')
+ @mock.patch('base.trait.g')
+ @mock.patch('base.trait.get_resource_id')
+ def test_retrieve_trait_info_with_empty_chr_field(self,
+ resource_id_mock,
+ g_mock,
+ requests_mock):
+ """Test retrieve trait info with empty chr field"""
+ resource_id_mock.return_value = 1
+ g_mock.db.execute.return_value.fetchone = mock.Mock()
+ g_mock.db.execute.return_value.fetchone.side_effect = [
+ [1, 2, 3, 4], # trait_info = g.db.execute(query).fetchone()
+ [1, 2, 3, 4, 5], # trait_qtl = g.db.execute(query).fetchone()
+ [None, 3] # trait_info = g.db.execute(query).fetchone()
+ ]
+
+ requests_mock.return_value = None
+
+ mock_dataset = mock.MagicMock()
+ type(mock_dataset).display_fields = mock.PropertyMock(
+ return_value=["a", "b", "c", "d"])
+ type(mock_dataset).type = "ProbeSet"
+ type(mock_dataset).name = "RandomName"
+
+ mock_trait = MockTrait(
+ dataset=mock_dataset,
+ pre_publication_description="test_string"
+ )
+ trait_attrs = {
+ "description": "some description",
+ "probe_target_description": "some description",
+ "cellid": False,
+ "chr": 2.733,
+ "mb": 2.1204
+ }
+
+ for key, val in list(trait_attrs.items()):
+ setattr(mock_trait, key, val)
+ test_trait = retrieve_trait_info(trait=mock_trait,
+ dataset=mock_dataset,
+ get_qtl_info=True)
+ self.assertEqual(test_trait.LRS_score_repr,
+ "N/A")
+ self.assertEqual(test_trait.LRS_location_repr,
+ "N/A")