from io import StringIO import numpy as np import pandas as pd import pytest from bioframe.core import construction from bioframe.core.construction import from_any def test_add_ucsc_name_column(): df = pd.DataFrame( {"chrom": [f"chr{i}" for i in range(3)], "start": [1, 2, 3], "end": [4, 5, 6]} ) pd.testing.assert_series_equal( construction.add_ucsc_name_column(df)["name"], pd.Series( data=["chr0:1-4", "chr1:2-5", "chr2:3-6"], index=[0, 1, 2], name="name" ), ) def test_any(): ### tests copied from old parse_regions # main functionality: convert to dataframe and create name df = pd.DataFrame( {"chrom": [f"chr{i}" for i in range(3)], "start": [1, 2, 3], "end": [4, 5, 6]} ) parsed = from_any(df) assert "name" not in parsed.columns assert parsed.iloc[0]["chrom"] == "chr0" # re-create dataframe from UCSC name alone df2 = pd.DataFrame( { "regions": construction.add_ucsc_name_column(parsed, name_col="regions")[ "regions" ].values } ) assert ( (from_any(df2, name_col="regions")[["chrom", "start", "end"]] == parsed) .all() .all() ) # re-parsing results yields the same assert (from_any(parsed) == parsed).all().all() # extra columns don't get overwritten df["name"] = "test-value" assert (from_any(df)["name"] == df["name"]).all() # None or False will be parsed assert from_any([("chr1", None, 5)], fill_null={"chr1": 10})["start"].values[0] == 0 # pull end from chromsizes p2 = from_any([("chr1", 5, None)], fill_null={"chr1": 40}) assert list(p2.values[0]) == ["chr1", 5, 40] # We could keep things as None if chromsizes were not proviced p3 = from_any(["chr1", "chr2"], fill_null=False) assert list(p3.values[0]) == ["chr1", None, None] # parse the strange name p8 = from_any(["chr1:1,000,000-4M"]) assert list(p8.values[0]) == ["chr1", 1000000, 4000000] p9 = from_any(["chr1"]) assert list(p9.values[0]) == ["chr1", None, None] with pytest.raises(ValueError): from_any([("ch1", 1, 2, "chr1:1-2", "puppies")]) # puppies are not allowed with pytest.raises(ValueError): from_any([("chr1", 5, None)], fill_null={"chr2": 40}) # input tuple of tuples p2 = from_any((("chr1", 5, 10), ("chrX", 10, 20))) assert list(p2.values[0]) == ["chr1", 5, 10] # input tuple of lists p2 = from_any((["chr1", 5, 10], ["chrX", 10, 20])) assert list(p2.values[0]) == ["chr1", 5, 10] # input tuple of ucsc strings p2 = from_any(("chr1:5-10",)) assert list(p2.values[0]) == ["chr1", 5, 10] # input single tuple p2 = from_any(("chr1", 5, 10)) assert list(p2.values[0]) == ["chr1", 5, 10] def test_sanitize_bedframe(): df1 = pd.DataFrame( [ ["chr1", 10, 20], ["chr1", 10, 20], ["chr1", 15, np.nan], ["chr1", pd.NA, 25], ], columns=["chrom", "start", "end"], ) # drop rows with null values sanitized_df1 = pd.DataFrame( [["chr1", 10, 20], ["chr1", 10, 20]], columns=["chrom", "start", "end"] ) sanitized_df1 = sanitized_df1.astype( {"chrom": str, "start": pd.Int64Dtype(), "end": pd.Int64Dtype()} ) pd.testing.assert_frame_equal( sanitized_df1, construction.sanitize_bedframe(df1, drop_null=True) ) # keep rows with null, but recast sanitized_df1 = pd.DataFrame( [ ["chr1", 10, 20], ["chr1", 10, 20], [pd.NA, pd.NA, pd.NA], [pd.NA, pd.NA, pd.NA], ], columns=["chrom", "start", "end"], ) sanitized_df1 = sanitized_df1.astype( {"chrom": object, "start": pd.Int64Dtype(), "end": pd.Int64Dtype()} ) pd.testing.assert_frame_equal( sanitized_df1.fillna(-1), construction.sanitize_bedframe(df1).fillna(-1) ) # flip intervals as well as drop NA df1 = pd.DataFrame( [ ["chr1", 20, 10], ["chr1", pd.NA, 25], ], columns=["chrom", "start", "end"], ) sanitized_df1 = pd.DataFrame([["chr1", 10, 20]], columns=["chrom", "start", "end"]) sanitized_df1 = sanitized_df1.astype( {"chrom": str, "start": pd.Int64Dtype(), "end": pd.Int64Dtype()} ) pd.testing.assert_frame_equal( sanitized_df1, construction.sanitize_bedframe( df1, start_exceed_end_action="fLiP", drop_null=True ), ) # flip intervals as well as drop NA df1 = pd.DataFrame( [ ["chr1", 20, 10], ["chr1", pd.NA, 25], ], columns=["chrom", "start", "end"], ) sanitized_df1 = pd.DataFrame([["chr1", 10, 20]], columns=["chrom", "start", "end"]) sanitized_df1 = sanitized_df1.astype( {"chrom": str, "start": pd.Int64Dtype(), "end": pd.Int64Dtype()} ) assert construction.sanitize_bedframe( df1, start_exceed_end_action="drop", drop_null=True ).empty def test_make_viewframe(): # test dict input view_df = pd.DataFrame( [ ["chrTESTX", 0, 10, "chrTESTX:0-10"], ["chrTESTX_p", 0, 12, "chrTESTX_p:0-12"], ], columns=["chrom", "start", "end", "name"], ) pd.testing.assert_frame_equal( view_df.copy(), construction.make_viewframe( {"chrTESTX": 10, "chrTESTX_p": 12}, name_style="ucsc" ), ) # test list input region_list = [("chrTESTX", 0, 10), ("chrTESTX_p", 0, 12)] pd.testing.assert_frame_equal( view_df.copy(), construction.make_viewframe(region_list, name_style="ucsc"), ) # test pd.Series input chromsizes = pd.Series(data=[5, 8], index=["chrTESTXq", "chrTEST_2p"]) d = """ chrom start end name 0 chrTESTXq 0 5 chrTESTXq 1 chrTEST_2p 0 8 chrTEST_2p""" view_df = pd.read_csv(StringIO(d), sep=r"\s+") pd.testing.assert_frame_equal( view_df.copy(), construction.make_viewframe(chromsizes, name_style=None) ) d = """ chrom start end name 0 chrTESTXq 0 5 chrTESTXq:0-5 1 chrTEST_2p 0 8 chrTEST_2p:0-8""" view_df = pd.read_csv(StringIO(d), sep=r"\s+") pd.testing.assert_frame_equal( view_df.copy(), construction.make_viewframe(chromsizes, name_style="UCSC"), ) # test pd.DataFrame input pd.testing.assert_frame_equal(view_df.copy(), construction.make_viewframe(view_df)) # if you provide unique names, this is accepted unchanged by make_viewframe view_df = pd.DataFrame( [["chrTESTX", 0, 10, "chrTEST_1"], ["chrTESTY", 0, 12, "chrTEST_2"]], columns=["chrom", "start", "end", "name"], ) region_list = [("chrTESTX", 0, 10, "chrTEST_1"), ("chrTESTY", 0, 12, "chrTEST_2")] pd.testing.assert_frame_equal( view_df.copy(), construction.make_viewframe(region_list) ) pd.testing.assert_frame_equal(view_df.copy(), construction.make_viewframe(view_df)) pd.testing.assert_frame_equal( view_df.copy(), construction.make_viewframe( view_df, check_bounds={"chrTESTX": 11, "chrTESTY": 13} ), ) with pytest.raises(ValueError): construction.make_viewframe( view_df, check_bounds={"chrTESTX": 9, "chrTESTY": 13} )