From 8aa507d2892183402e9b4fb41bd3f879e0ded6b9 Mon Sep 17 00:00:00 2001
From: xyg123 <xiangyuge123@hotmail.co.uk>
Date: Tue, 12 Mar 2024 12:32:55 +0000
Subject: [PATCH] fix: removed unused coloc tests

---
 .../method/test_colocalisation_method.py      | 134 ------------------
 1 file changed, 134 deletions(-)

diff --git a/tests/gentropy/method/test_colocalisation_method.py b/tests/gentropy/method/test_colocalisation_method.py
index f28ddf120..1f52244be 100644
--- a/tests/gentropy/method/test_colocalisation_method.py
+++ b/tests/gentropy/method/test_colocalisation_method.py
@@ -54,140 +54,6 @@ def test_single_snp_coloc(
         assert difference.filter(f.abs(f.col(col)) > threshold).count() == 0
 
 
-def test_single_snp_coloc(
-    spark: SparkSession,
-    threshold: float = 1e-5,
-) -> None:
-    """Test edge case of coloc where only one causal SNP is present in the StudyLocusOverlap."""
-    test_overlap_df = spark.createDataFrame(
-        [
-            {
-                "leftStudyLocusId": 1,
-                "rightStudyLocusId": 2,
-                "chromosome": "1",
-                "tagVariantId": "snp",
-                "left_logBF": 10.3,
-                "right_logBF": 10.5,
-            }
-        ]
-    )
-    test_overlap = StudyLocusOverlap(
-        test_overlap_df.select(
-            "leftStudyLocusId",
-            "rightStudyLocusId",
-            "chromosome",
-            "tagVariantId",
-            f.struct(f.col("left_logBF"), f.col("right_logBF")).alias("statistics"),
-        ),
-        StudyLocusOverlap.get_schema(),
-    )
-    test_result = Coloc.colocalise(test_overlap)
-
-    expected = spark.createDataFrame(
-        [
-            {
-                "h0": 9.254841951638903e-5,
-                "h1": 2.7517068829182966e-4,
-                "h2": 3.3609423764447284e-4,
-                "h3": 9.254841952564387e-13,
-                "h4": 0.9992961866536217,
-            }
-        ]
-    )
-    difference = test_result.df.select("h0", "h1", "h2", "h3", "h4").subtract(expected)
-    for col in difference.columns:
-        assert difference.filter(f.abs(f.col(col)) > threshold).count() == 0
-
-
-def test_single_snp_coloc_one_negative(
-    spark: SparkSession,
-    threshold: float = 1e-5,
-) -> None:
-    """Test edge case of coloc where only one causal SNP is present (On one side!) in the StudyLocusOverlap."""
-    test_overlap_df = spark.createDataFrame(
-        [
-            {
-                "leftStudyLocusId": 1,
-                "rightStudyLocusId": 2,
-                "chromosome": "1",
-                "tagVariantId": "snp",
-                "left_logBF": 18.3,
-                "right_logBF": 0.01,
-            }
-        ]
-    )
-    test_overlap = StudyLocusOverlap(
-        test_overlap_df.select(
-            "leftStudyLocusId",
-            "rightStudyLocusId",
-            "chromosome",
-            "tagVariantId",
-            f.struct(f.col("left_logBF"), f.col("right_logBF")).alias("statistics"),
-        ),
-        StudyLocusOverlap.get_schema(),
-    )
-    test_result = Coloc.colocalise(test_overlap)
-    test_result.df.show(1, False)
-    expected = spark.createDataFrame(
-        [
-            {
-                "h0": 1.0246538505087709e-4,
-                "h1": 0.9081680002273896,
-                "h2": 1.0349517929098209e-8,
-                "h3": 1.0246538506112363e-12,
-                "h4": 0.09172952403701702,
-            }
-        ]
-    )
-    difference = test_result.df.select("h0", "h1", "h2", "h3", "h4").subtract(expected)
-    for col in difference.columns:
-        assert difference.filter(f.abs(f.col(col)) > threshold).count() == 0
-
-
-def test_single_snp_coloc_both_negative(
-    spark: SparkSession,
-    threshold: float = 1e-5,
-) -> None:
-    """Test edge case of coloc where only one non-causal SNP overlaps in the StudyLocusOverlap."""
-    test_overlap_df = spark.createDataFrame(
-        [
-            {
-                "leftStudyLocusId": 1,
-                "rightStudyLocusId": 2,
-                "chromosome": "1",
-                "tagVariantId": "snp",
-                "left_logBF": 0.03,
-                "right_logBF": 0.01,
-            }
-        ]
-    )
-    test_overlap = StudyLocusOverlap(
-        test_overlap_df.select(
-            "leftStudyLocusId",
-            "rightStudyLocusId",
-            "chromosome",
-            "tagVariantId",
-            f.struct(f.col("left_logBF"), f.col("right_logBF")).alias("statistics"),
-        ),
-        StudyLocusOverlap.get_schema(),
-    )
-    test_result = Coloc.colocalise(test_overlap)
-    expected = spark.createDataFrame(
-        [
-            {
-                "h0": 0.9997855774090624,
-                "h1": 1.0302335812225042e-4,
-                "h2": 1.0098335895103664e-4,
-                "h3": 9.9978557750904e-9,
-                "h4": 1.0405876008495098e-5,
-            }
-        ]
-    )
-    difference = test_result.df.select("h0", "h1", "h2", "h3", "h4").subtract(expected)
-    for col in difference.columns:
-        assert difference.filter(f.abs(f.col(col)) > threshold).count() == 0
-
-
 def test_ecaviar(mock_study_locus_overlap: StudyLocusOverlap) -> None:
     """Test eCAVIAR."""
     assert isinstance(ECaviar.colocalise(mock_study_locus_overlap), Colocalisation)