fixup: Format Python code with Black

src/cgr_gwas_qc/parsers/illumina/adpc.py

@@ -58,14 +58,7 @@ def validate(self):
     def __iter__(self):
         """This allows tuple unpacking"""
         return iter(
-            (
-                self.x_raw,
-                self.y_raw,
-                self.x_norm,
-                self.y_norm,
-                self.genotype_score,
-                self.genotype,
-            )
+            (self.x_raw, self.y_raw, self.x_norm, self.y_norm, self.genotype_score, self.genotype,)
         )
 
     def __str__(self):

src/cgr_gwas_qc/scripts/legacy_compare.py

@@ -161,11 +161,7 @@ def compare_config(config: Config, legacy_dir: Path, ignored_config: bool):
             config.software_params.contam_population,
             "B Allele Frequency Population (contamination check)",
         ),
-        (
-            legacy_config["strand"].lower(),
-            config.software_params.strand,
-            "Strand",
-        ),
+        (legacy_config["strand"].lower(), config.software_params.strand, "Strand",),
         (
             legacy_config["pi_hat_threshold"],
             config.software_params.pi_hat_threshold,
@@ -222,8 +218,7 @@ def _file_comparison(cmp):
         typer.secho(f"{cmp.message} did not match ({cmp.legacy} vs {cmp.current}).", fg=RED)
     except NotImplementedError:
         typer.secho(
-            f"Cannot currently compare {cmp.message}",
-            fg=YELLOW,
+            f"Cannot currently compare {cmp.message}", fg=YELLOW,
         )
 
 
@@ -449,22 +444,8 @@ def compare_contamination(legacy_dir: Path, mix_atol: float, llk_atol: float, ll
 def _parse_snpweights(filename):
     return (
         pd.read_csv(filename, dtype={"ID": str}, low_memory=False)
-        .rename(
-            {
-                "ID": "Sample_ID",
-                "AFR": "Pct_AFR",
-                "ASN": "Pct_ASN",
-                "EUR": "Pct_EUR",
-            },
-            axis=1,
-        )
-        .replace(
-            {
-                "EUR": "European",
-                "AFR": "African",
-                "ASN": "East Asian",
-            }
-        )
+        .rename({"ID": "Sample_ID", "AFR": "Pct_AFR", "ASN": "Pct_ASN", "EUR": "Pct_EUR",}, axis=1,)
+        .replace({"EUR": "European", "AFR": "African", "ASN": "East Asian",})
         .set_index("Sample_ID")
         .sort_index()
     )

src/cgr_gwas_qc/testing/comparison.py

@@ -30,11 +30,7 @@ def sorted_file_equal(file1: PathLike, file2: PathLike) -> bool:
 
 
 def file_rows_almost_equal(
-    file1: PathLike,
-    file2: PathLike,
-    fuzzy_col: int,
-    sep: str = "\t",
-    header: bool = False,
+    file1: PathLike, file2: PathLike, fuzzy_col: int, sep: str = "\t", header: bool = False,
 ) -> bool:
     """Compares two files row by row and makes sure they are almost equal"""
     results = []
@@ -122,10 +118,7 @@ def assert_legacy_dev_sample_qc_equal(legacy_file: PathLike, dev_file: PathLike)
     )
     assert_series_equal(legacy["Call_Rate_2"], dev["Call_Rate_2"])
     assert_series_equal(
-        legacy["Low Call Rate"],
-        dev["is_call_rate_filtered"],
-        check_dtype=False,
-        check_names=False,
+        legacy["Low Call Rate"], dev["is_call_rate_filtered"], check_dtype=False, check_names=False,
     )
 
     # --------------------

src/cgr_gwas_qc/workflow/scripts/bim_filter_vcf.py

@@ -20,10 +20,7 @@ def main(
     ),
     vcf_file: Path = typer.Argument(..., help="The 1KG VCF file.", exists=True, readable=True),
     snp_removal_list: Path = typer.Argument(
-        ...,
-        help="Text file to save the list of makers to remove.",
-        file_okay=True,
-        writable=True,
+        ..., help="Text file to save the list of makers to remove.", file_okay=True, writable=True,
     ),
     output_bim: Optional[Path] = typer.Argument(
         None,

src/cgr_gwas_qc/workflow/scripts/sample_concordance.py

@@ -102,11 +102,7 @@ def read(filename: PathLike):
 
 @app.command()
 def main(
-    sample_sheet_csv: Path,
-    plink_file: Path,
-    graf_file: Path,
-    king_file: Path,
-    outfile: Path,
+    sample_sheet_csv: Path, plink_file: Path, graf_file: Path, king_file: Path, outfile: Path,
 ):
     ss = sample_sheet.read(sample_sheet_csv)
     concordance = (
@@ -249,8 +245,7 @@ def _graf(filename: PathLike):
         .set_index(["ID1", "ID2"])
         .reindex(["HGMR", "AGMR", "relationship"], axis=1)
         .rename(
-            {"HGMR": "GRAF_HGMR", "AGMR": "GRAF_AGMR", "relationship": "GRAF_relationship"},
-            axis=1,
+            {"HGMR": "GRAF_HGMR", "AGMR": "GRAF_AGMR", "relationship": "GRAF_relationship"}, axis=1,
         )
     )
 

src/cgr_gwas_qc/workflow/scripts/sample_concordance_new.py

@@ -104,11 +104,7 @@ def read(filename: PathLike):
 
 @app.command()
 def main(
-    sample_sheet_csv: Path,
-    plink_file: Path,
-    graf_file: Path,
-    king_file: Path,
-    outfile: Path,
+    sample_sheet_csv: Path, plink_file: Path, graf_file: Path, king_file: Path, outfile: Path,
 ):
     ss = sample_sheet.read(sample_sheet_csv)
     concordance = (
@@ -273,8 +269,7 @@ def _graf(filename: PathLike):
         .set_index(["ID1", "ID2"])
         .reindex(["HGMR", "AGMR", "relationship"], axis=1)
         .rename(
-            {"HGMR": "GRAF_HGMR", "AGMR": "GRAF_AGMR", "relationship": "GRAF_relationship"},
-            axis=1,
+            {"HGMR": "GRAF_HGMR", "AGMR": "GRAF_AGMR", "relationship": "GRAF_relationship"}, axis=1,
         )
     )
 

src/cgr_gwas_qc/workflow/scripts/sample_qc_table.py

@@ -190,9 +190,7 @@ def main(
         intensity,
     )
     add_qc_columns(
-        sample_qc,
-        remove_contam,
-        remove_rep_discordant,
+        sample_qc, remove_contam, remove_rep_discordant,
     )
     save(sample_qc, outfile)
 
@@ -398,8 +396,7 @@ def _read_contam(file_name: Optional[Path], Sample_IDs: pd.Index) -> pd.DataFram
 
     if file_name is None:
         return pd.DataFrame(
-            index=Sample_IDs,
-            columns=["Contamination_Rate", "is_contaminated"],
+            index=Sample_IDs, columns=["Contamination_Rate", "is_contaminated"],
         ).astype({"Contamination_Rate": "float", "is_contaminated": "boolean"})
 
     return (
@@ -442,16 +439,12 @@ def _read_intensity(file_name: Optional[Path], Sample_IDs: pd.Index) -> pd.Serie
 
 
 def add_qc_columns(
-    sample_qc: pd.DataFrame,
-    remove_contam: bool,
-    remove_rep_discordant: bool,
+    sample_qc: pd.DataFrame, remove_contam: bool, remove_rep_discordant: bool,
 ) -> pd.DataFrame:
     add_call_rate_flags(sample_qc)
     _add_identifiler(sample_qc)
     _add_analytic_exclusion(
-        sample_qc,
-        remove_contam,
-        remove_rep_discordant,
+        sample_qc, remove_contam, remove_rep_discordant,
     )
     _add_subject_representative(sample_qc)
     _add_subject_dropped_from_study(sample_qc)
@@ -497,9 +490,7 @@ def reason_string(row: pd.Series) -> str:
 
 
 def _add_analytic_exclusion(
-    sample_qc: pd.DataFrame,
-    remove_contam: bool,
-    remove_rep_discordant: bool,
+    sample_qc: pd.DataFrame, remove_contam: bool, remove_rep_discordant: bool,
 ) -> pd.DataFrame:
     """Adds a flag to remove samples based on provided conditions.
 

src/cgr_gwas_qc/workflow/scripts/subject_qc_table.py

@@ -78,9 +78,7 @@ def read(filename: PathLike) -> pd.DataFrame:
 
 @app.command()
 def main(
-    sample_qc_csv: Path,
-    sample_concordance_csv: Path,
-    outfile: Path,
+    sample_qc_csv: Path, sample_concordance_csv: Path, outfile: Path,
 ):
     (
         sample_qc_table.read(sample_qc_csv)

src/cgr_gwas_qc/workflow/scripts/update_snps_to_1kg_rsID.py

@@ -42,10 +42,7 @@ def main(
         writable=True,
     ),
     id_map_out: Path = typer.Argument(
-        ...,
-        help="CSV mapping array ids to thousand genome ids.",
-        file_okay=True,
-        writable=True,
+        ..., help="CSV mapping array ids to thousand genome ids.", file_okay=True, writable=True,
     ),
 ):
     """Compares a plink BIM file with a VCF and updates IDs to match VCF.

tests/workflow/modules/test_eigensoft.py

@@ -90,10 +90,8 @@ def test_eigensoft_smartpca(tmp_path, conda_envs):
 
     # THEN: the files exists
     file_hashes_equal(
-        data_cache / "legacy_outputs/pca/EUR_subjects.smartpca.par",
-        tmp_path / "samples.pca.par",
+        data_cache / "legacy_outputs/pca/EUR_subjects.smartpca.par", tmp_path / "samples.pca.par",
     )
     file_hashes_equal(
-        data_cache / "legacy_outputs/pca/EUR_subjects.eigenvec",
-        tmp_path / "samples.eigenvec",
+        data_cache / "legacy_outputs/pca/EUR_subjects.eigenvec", tmp_path / "samples.eigenvec",
     )

tests/workflow/sub_workflows/test_entry_points.py

@@ -176,16 +176,13 @@ def gtc_grouped_entry(pytestconfig, tmp_path_factory, conda_envs):
 def test_gtc_grouped_entry(gtc_entry, gtc_grouped_entry):
     # The merged samples files should exist.
     assert file_hashes_equal(
-        gtc_entry / "sample_level/samples.bed",
-        gtc_grouped_entry / "sample_level/samples.bed",
+        gtc_entry / "sample_level/samples.bed", gtc_grouped_entry / "sample_level/samples.bed",
     )
     assert file_hashes_equal(
-        gtc_entry / "sample_level/samples.bim",
-        gtc_grouped_entry / "sample_level/samples.bim",
+        gtc_entry / "sample_level/samples.bim", gtc_grouped_entry / "sample_level/samples.bim",
     )
     assert file_hashes_equal(
-        gtc_entry / "sample_level/samples.fam",
-        gtc_grouped_entry / "sample_level/samples.fam",
+        gtc_entry / "sample_level/samples.fam", gtc_grouped_entry / "sample_level/samples.fam",
     )
 
 

tests/workflow/sub_workflows/test_sample_qc.py

@@ -339,8 +339,7 @@ def sample_qc_workflow(pytestconfig, tmp_path_factory, conda_envs):
 @pytest.mark.workflow
 def test_sample_qc_compare_hashes(real_data_cache, sample_qc_workflow, filename):
     assert comparison.file_hashes_equal(
-        real_data_cache / "dev_outputs" / filename,
-        sample_qc_workflow / filename,
+        real_data_cache / "dev_outputs" / filename, sample_qc_workflow / filename,
     )
 
 

tests/workflow/sub_workflows/test_subject_qc.py

@@ -300,6 +300,5 @@ def subject_qc_workflow(pytestconfig, tmp_path_factory, conda_envs):
 @pytest.mark.workflow
 def test_subject_qc_file_hashes(real_data_cache, subject_qc_workflow, filename):
     assert comparison.file_hashes_equal(
-        real_data_cache / "dev_outputs" / filename,
-        subject_qc_workflow / filename,
+        real_data_cache / "dev_outputs" / filename, subject_qc_workflow / filename,
     )