formatting

Author: jkmckenna

src/smftools/__init__.py

@@ -1,4 +1,5 @@
 """smftools"""
+
 from __future__ import annotations
 
 import logging
@@ -13,8 +14,17 @@
 __version__ = version(package_name)
 
 if TYPE_CHECKING:
-    from smftools import cli, config, datasets, hmm, informatics, machine_learning, plotting
-    from smftools import preprocessing, tools
+    from smftools import (
+        cli,
+        config,
+        datasets,
+        hmm,
+        informatics,
+        machine_learning,
+        plotting,
+        preprocessing,
+        tools,
+    )
 
 _LAZY_MODULES = {
     "cli": "smftools.cli",

src/smftools/cli/load_adata.py

@@ -4,6 +4,8 @@
 from pathlib import Path
 from typing import Iterable, Union
 
+import numpy as np
+
 from smftools.logging_utils import get_logger
 
 from .helpers import AdataPaths
@@ -107,9 +109,6 @@ def load_adata_core(cfg, paths: AdataPaths, config_path: str | None = None):
     cfg : ExperimentConfig
         (Same object, possibly with some fields updated, e.g. fasta path.)
     """
-    from pathlib import Path
-
-    import numpy as np
 
     from ..informatics.bam_functions import (
         align_and_sort_BAM,

src/smftools/hmm/call_hmm_peaks.py

@@ -1,7 +1,6 @@
 from __future__ import annotations
 
 # FILE: smftools/hmm/call_hmm_peaks.py
-
 from pathlib import Path
 from typing import Any, Dict, Optional, Sequence, Union
 

src/smftools/hmm/hmm_readwrite.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+
 def load_hmm(model_path, device="cpu"):
     """
     Reads in a pretrained HMM.

src/smftools/informatics/bam_functions.py

@@ -3,14 +3,14 @@
 import glob
 import os
 import re
+import shutil
 import subprocess
 import time
 from collections import Counter, defaultdict, deque
 from concurrent.futures import ThreadPoolExecutor, as_completed
 from itertools import zip_longest
 from pathlib import Path
-import shutil
-from typing import Any, Dict, Iterable, List, Optional, Tuple, Union, TYPE_CHECKING
+from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Tuple, Union
 
 import numpy as np
 from tqdm import tqdm
@@ -173,9 +173,7 @@ def _index_bam_with_pysam(bam_path: Union[str, Path], threads: Optional[int] = N
         pysam_mod.index(bam_path)
 
 
-def _bam_to_fastq_with_samtools(
-    bam_path: Union[str, Path], fastq_path: Union[str, Path]
-) -> None:
+def _bam_to_fastq_with_samtools(bam_path: Union[str, Path], fastq_path: Union[str, Path]) -> None:
     """Convert BAM to FASTQ using samtools."""
     if not shutil.which("samtools"):
         raise RuntimeError("samtools is required but not available in PATH.")

src/smftools/informatics/bed_functions.py

@@ -8,7 +8,6 @@
 from pathlib import Path
 from typing import TYPE_CHECKING
 
-import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
 
@@ -58,13 +57,17 @@ def _require_pysam() -> "pysam_types":
     return require("pysam", extra="pysam", purpose="FASTA indexing")
 
 
-def _resolve_backend(backend: str | None, *, tool: str, python_available: bool, cli_name: str) -> str:
+def _resolve_backend(
+    backend: str | None, *, tool: str, python_available: bool, cli_name: str
+) -> str:
     choice = (backend or "auto").strip().lower()
     if choice not in {"auto", "python", "cli"}:
         raise ValueError(f"{tool}_backend must be one of: auto, python, cli")
     if choice == "python":
         if not python_available:
-            raise RuntimeError(f"{tool}_backend=python requires the Python package to be installed.")
+            raise RuntimeError(
+                f"{tool}_backend=python requires the Python package to be installed."
+            )
         return "python"
     if choice == "cli":
         if not shutil.which(cli_name):
@@ -143,7 +146,10 @@ def _bed_to_bigwig(
 
     # 1) Compute coverage → bedGraph
     bedtools_choice = _resolve_backend(
-        bedtools_backend, tool="bedtools", python_available=pybedtools is not None, cli_name="bedtools"
+        bedtools_backend,
+        tool="bedtools",
+        python_available=pybedtools is not None,
+        cli_name="bedtools",
     )
     if bedtools_choice == "python":
         logger.debug(f"[pybedtools] generating coverage bedgraph from {bed}")
@@ -172,7 +178,10 @@ def _bed_to_bigwig(
 
     # 2) Convert bedGraph → BigWig via pyBigWig
     bigwig_choice = _resolve_backend(
-        bigwig_backend, tool="bigwig", python_available=pyBigWig is not None, cli_name="bedGraphToBigWig"
+        bigwig_backend,
+        tool="bigwig",
+        python_available=pyBigWig is not None,
+        cli_name="bedGraphToBigWig",
     )
     if bigwig_choice == "python":
         logger.debug(f"[pyBigWig] converting bedgraph → bigwig: {bigwig}")
@@ -245,6 +254,8 @@ def _plot_bed_histograms(
     coordinate_mode : {"one_based","zero_based"}
         One-based, inclusive (your file) vs BED-standard zero-based, half-open.
     """
+    plt = require("matplotlib.pyplot", extra="plotting", purpose="plotting BED histograms")
+
     os.makedirs(plotting_directory, exist_ok=True)
 
     bed_basename = os.path.basename(bed_file).rsplit(".bed", 1)[0]

src/smftools/informatics/binarize_converted_base_identities.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+
 def binarize_converted_base_identities(
     base_identities,
     strand,

src/smftools/plotting/position_stats.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+
 def plot_volcano_relative_risk(
     results_dict,
     save_path=None,

src/smftools/preprocessing/binary_layers_to_ohe.py

@@ -1,7 +1,6 @@
 from __future__ import annotations
 
 ## binary_layers_to_ohe
-
 from smftools.logging_utils import get_logger
 
 logger = get_logger(__name__)

src/smftools/preprocessing/calculate_pairwise_hamming_distances.py

@@ -2,6 +2,7 @@
 
 ## calculate_pairwise_hamming_distances
 
+
 ## Conversion SMF Specific
 def calculate_pairwise_hamming_distances(arrays):
     """