# Path: bioframe/core/stringops.py
# def parse_region(reg, chromsizes=None):
#     """
#     Coerce a genomic region string or sequence into a triple (chrom, start, end).
# 
#     Genomic regions are represented as half-open intervals (0-based starts,
#     1-based ends) along the length coordinate of a contig/scaffold/chromosome.
#     Start must be >= 0, and end coordinate must be >= start.
# 
#     Parameters
#     ----------
#     reg : str or tuple
#         UCSC-style genomic region string, or
#         Triple (chrom, start, end), where ``start`` or ``end`` may be ``None``.
#         Quadriple (chrom, start, end, name) (name is ignored).
#     chromsizes : mapping, optional
#         Lookup table of scaffold lengths to check against ``chrom`` and the
#         ``end`` coordinate. Required if ``end`` is not supplied.
# 
#     Returns
#     -------
#     triple : (str, int, int)
#         A well-formed genomic region triple (str, int, int)
# 
#     """
#     if isinstance(reg, str):
#         chrom, start, end = parse_region_string(reg)
#     else:
#         if len(reg) not in [3, 4]:
#             raise ValueError("length of a region should be 3 or 4")
#         chrom, start, end = reg[:3]
#         start = int(start) if start is not None else start
#         end = int(end) if end is not None else end
# 
#     try:
#         clen = chromsizes[chrom] if chromsizes is not None else None
#     except KeyError:
#         raise ValueError("Unknown sequence label: {}".format(chrom))
# 
#     start = 0 if start is None else start
#     if end is None:
#         end = clen  # if clen is None, end is None too!
# 
#     if (end is not None) and (end < start):
#         raise ValueError("End cannot be less than start")
# 
#     if start < 0 or (clen is not None and end > clen):
#         raise ValueError("Genomic region out of bounds: [{}, {})".format(start, end))
# 
#     return chrom, start, end
# 
# Path: bioframe/core/arrops.py
# def argnatsort(array):
#     array = np.asarray(array)
#     if not len(array):
#         return np.array([], dtype=int)
#     cols = tuple(zip(*(natsort_key(x) for x in array)))
#     return np.lexsort(cols[::-1])  # numpy's lexsort is ass-backwards
# 
# Path: bioframe/io/schemas.py
# SCHEMAS = {
#     "bed": BED_FIELDS,
#     "bed3": BED_FIELDS[:3],
#     "bed4": BED_FIELDS[:4],
#     "bedGraph": BEDGRAPH_FIELDS,
#     "bed5": BED_FIELDS[:5],
#     "bed6": BED_FIELDS,
#     "bed9": BED12_FIELDS[:9],
#     "bed12": BED12_FIELDS,
#     "bedpe": BEDPE_FIELDS,
#     "gff": GFF_FIELDS,
#     "gtf": GFF_FIELDS,
#     "bedRnaElements": BEDRNAELEMENTS_FIELDS,
#     "narrowPeak": NARROWPEAK_FIELDS,
#     "broadPeak": BROADPEAK_FIELDS,
#     "gappedPeak": GAPPEDPEAK_FIELDS,
#     "centromeres": CENTROMERES_FIELDS,
#     "cytoband": CYTOBAND_FIELDS,
#     "sam": BAM_FIELDS,
#     "vcf": VCF_FIELDS,
#     "jaspar": JASPAR_FIELDS,
#     "gap": GAP_FIELDS,
#     "UCSCmRNA": UCSC_MRNA_FIELDS,
#     "pgsnp": PGSNP_FIELDS,
# }
# 
# BAM_FIELDS = [
#     "QNAME",
#     "FLAG",
#     "RNAME",
#     "POS",
#     "MAPQ",
#     "CIGAR",
#     "RNEXT",
#     "PNEXT",
#     "TLEN",
#     "SEQ",
#     "QUAL",
#     "TAGs",
# ]


from collections import OrderedDict
from contextlib import closing
from ..core.stringops import parse_region
from ..core.arrops import argnatsort
from .schemas import SCHEMAS, BAM_FIELDS
import subprocess
import tempfile
import json
import io
import numpy as np
import pandas as pd
    import bbi
    import pyBigWig
    import pysam
    import pypairix
    import cytoolz as toolz
    import pysam
            import pysam
            import pyfaidx

    Notes
    -----
    Mention name patterns

    See also
    --------
    * UCSC assembly terminology: <http://genome.ucsc.edu/FAQ/FAQdownloads.html#download9>
    * NCBI assembly terminology: <https://www.ncbi.nlm.nih.gov/grc/help/definitions>

    """
    if isinstance(filepath_or, str) and filepath_or.endswith(".gz"):
        kwargs.setdefault("compression", "gzip")

    chromtable = pd.read_csv(
        filepath_or,
        sep="\t",
        usecols=[0, 1],
        names=["name", "length"],
        dtype={"name": str},
        **kwargs
    )

    if filter_chroms:
        parts = []
        for pattern in chrom_patterns:
            if not len(pattern):
                continue
            part = chromtable[chromtable["name"].str.contains(pattern)]
            if natsort:

# Path: bioframe/core/stringops.py
# def parse_region(reg, chromsizes=None):
#     """
#     Coerce a genomic region string or sequence into a triple (chrom, start, end).
# 
#     Genomic regions are represented as half-open intervals (0-based starts,
#     1-based ends) along the length coordinate of a contig/scaffold/chromosome.
#     Start must be >= 0, and end coordinate must be >= start.
# 
#     Parameters
#     ----------
#     reg : str or tuple
#         UCSC-style genomic region string, or
#         Triple (chrom, start, end), where ``start`` or ``end`` may be ``None``.
#         Quadriple (chrom, start, end, name) (name is ignored).
#     chromsizes : mapping, optional
#         Lookup table of scaffold lengths to check against ``chrom`` and the
#         ``end`` coordinate. Required if ``end`` is not supplied.
# 
#     Returns
#     -------
#     triple : (str, int, int)
#         A well-formed genomic region triple (str, int, int)
# 
#     """
#     if isinstance(reg, str):
#         chrom, start, end = parse_region_string(reg)
#     else:
#         if len(reg) not in [3, 4]:
#             raise ValueError("length of a region should be 3 or 4")
#         chrom, start, end = reg[:3]
#         start = int(start) if start is not None else start
#         end = int(end) if end is not None else end
# 
#     try:
#         clen = chromsizes[chrom] if chromsizes is not None else None
#     except KeyError:
#         raise ValueError("Unknown sequence label: {}".format(chrom))
# 
#     start = 0 if start is None else start
#     if end is None:
#         end = clen  # if clen is None, end is None too!
# 
#     if (end is not None) and (end < start):
#         raise ValueError("End cannot be less than start")
# 
#     if start < 0 or (clen is not None and end > clen):
#         raise ValueError("Genomic region out of bounds: [{}, {})".format(start, end))
# 
#     return chrom, start, end
# 
# Path: bioframe/core/arrops.py
# def argnatsort(array):
#     array = np.asarray(array)
#     if not len(array):
#         return np.array([], dtype=int)
#     cols = tuple(zip(*(natsort_key(x) for x in array)))
#     return np.lexsort(cols[::-1])  # numpy's lexsort is ass-backwards
# 
# Path: bioframe/io/schemas.py
# SCHEMAS = {
#     "bed": BED_FIELDS,
#     "bed3": BED_FIELDS[:3],
#     "bed4": BED_FIELDS[:4],
#     "bedGraph": BEDGRAPH_FIELDS,
#     "bed5": BED_FIELDS[:5],
#     "bed6": BED_FIELDS,
#     "bed9": BED12_FIELDS[:9],
#     "bed12": BED12_FIELDS,
#     "bedpe": BEDPE_FIELDS,
#     "gff": GFF_FIELDS,
#     "gtf": GFF_FIELDS,
#     "bedRnaElements": BEDRNAELEMENTS_FIELDS,
#     "narrowPeak": NARROWPEAK_FIELDS,
#     "broadPeak": BROADPEAK_FIELDS,
#     "gappedPeak": GAPPEDPEAK_FIELDS,
#     "centromeres": CENTROMERES_FIELDS,
#     "cytoband": CYTOBAND_FIELDS,
#     "sam": BAM_FIELDS,
#     "vcf": VCF_FIELDS,
#     "jaspar": JASPAR_FIELDS,
#     "gap": GAP_FIELDS,
#     "UCSCmRNA": UCSC_MRNA_FIELDS,
#     "pgsnp": PGSNP_FIELDS,
# }
# 
# BAM_FIELDS = [
#     "QNAME",
#     "FLAG",
#     "RNAME",
#     "POS",
#     "MAPQ",
#     "CIGAR",
#     "RNEXT",
#     "PNEXT",
#     "TLEN",
#     "SEQ",
#     "QUAL",
#     "TAGs",
# ]


# Path: bioframe/io/fileops.py
from collections import OrderedDict
from contextlib import closing
from ..core.stringops import parse_region
from ..core.arrops import argnatsort
from .schemas import SCHEMAS, BAM_FIELDS
import subprocess
import tempfile
import json
import io
import numpy as np
import pandas as pd
    import bbi
    import pyBigWig
    import pysam
    import pypairix
    import cytoolz as toolz
    import pysam
            import pysam
            import pyfaidx


    Notes
    -----
    Mention name patterns

    See also
    --------
    * UCSC assembly terminology: <http://genome.ucsc.edu/FAQ/FAQdownloads.html#download9>
    * NCBI assembly terminology: <https://www.ncbi.nlm.nih.gov/grc/help/definitions>

    """
    if isinstance(filepath_or, str) and filepath_or.endswith(".gz"):
        kwargs.setdefault("compression", "gzip")

    chromtable = pd.read_csv(
        filepath_or,
        sep="\t",
        usecols=[0, 1],
        names=["name", "length"],
        dtype={"name": str},
        **kwargs
    )

    if filter_chroms:
        parts = []
        for pattern in chrom_patterns:
            if not len(pattern):
                continue
            part = chromtable[chromtable["name"].str.contains(pattern)]
            if natsort:

                part = part.iloc[argnatsort(part["name"])]