''' Utilities for dealing with sam files. '''

import re
import subprocess
import os
import shutil
import heapq
import contextlib
import copy
import functools

from collections import Counter, defaultdict
from pathlib import Path

import pysam
import numpy as np

from . import utilities
from . import fastq
from . import fasta
from . import mapping_tools
from . import interval

BAM_CMATCH = 0     # M
BAM_CINS = 1       # I
BAM_CDEL = 2       # D
BAM_CREF_SKIP = 3  # N
BAM_CSOFT_CLIP = 4 # S
BAM_CHARD_CLIP = 5 # H
BAM_CPAD = 6       # P
BAM_CEQUAL = 7     # =
BAM_CDIFF = 8      # X

op_to_char = {
    BAM_CMATCH:     'M',
    BAM_CINS:       'I',
    BAM_CDEL:       'D',
    BAM_CREF_SKIP:  'N',
    BAM_CSOFT_CLIP: 'S',
    BAM_CHARD_CLIP: 'H',
    BAM_CPAD:       'P',
    BAM_CEQUAL:     '=',
    BAM_CDIFF:      'X',
}
# Want to be able to lookup with int or char keys, so make every relevant char
# return itself.
for v in list(op_to_char.values()):
    op_to_char[v] = v

read_consuming_ops = {
    BAM_CMATCH,
    BAM_CINS,
    BAM_CSOFT_CLIP,
    BAM_CEQUAL,
    BAM_CDIFF,
}

ref_consuming_ops = {
    BAM_CMATCH,
    BAM_CDEL,
    BAM_CEQUAL,
    BAM_CDIFF,
    BAM_CREF_SKIP,
}

def get_strand(mapping):
    if mapping.is_reverse:
        strand = '-'
    else:
        strand = '+'
    return strand

opposite_strand = {
    '+': '-',
    '-': '+',
}

def get_opposite_strand(mapping):
    return opposite_strand[get_strand(mapping)]

def get_original_seq(mapping):
    if mapping.is_reverse:
        original_seq = utilities.reverse_complement(mapping.query_sequence)
    else:
        original_seq = mapping.query_sequence
    return original_seq

def get_original_qual(mapping):
    if mapping.is_reverse:
        original_qual = mapping.query_qualities[::-1]
    else:
        original_qual = mapping.query_qualities
    return original_qual

def unmapped_aligned_read(qname):
    aligned_read = pysam.AlignedRead()
    aligned_read.qname = qname
    aligned_read.flag = 0x4
    aligned_read.rname = -1
    aligned_read.pos = -1
    aligned_read.mapq = 0
    aligned_read.cigar = None
    aligned_read.rnext = -1
    aligned_read.pnext = -1
    aligned_read.tlen = 0
    aligned_read.seq = '*'
    aligned_read.qual = '*'
    return aligned_read

def splice_in_name(line, new_name):
    return '\t'.join([new_name] + line.split('\t')[1:])

cigar_block = re.compile(r'(\d+)([MIDNSHP=X])')

def cigar_string_to_blocks(cigar_string):
    ''' Decomposes a CIGAR string into a list of its operations. '''
    return [(int(l), k) for l, k in cigar_block.findall(cigar_string)]

def total_reference_nucs(cigar):
    return sum(length for op, length in cigar if op in ref_consuming_ops)

def total_reference_nucs_except_splicing(cigar):
    return sum(length for op, length in cigar if op in ref_consuming_ops and op != BAM_CREF_SKIP)

def total_read_nucs(cigar):
    return sum(length for op, length in cigar if op in read_consuming_ops)

def contains_indel(read):
    kinds = [k for k, l in read.cigar]
    return (BAM_CINS in kinds or BAM_CDEL in kinds)

def indel_distance_from_edge(cigar):
    indel_indices = [i for i, (k, l) in enumerate(cigar) if k == BAM_CINS or k == BAM_CDEL]
    first_indel_index = min(indel_indices)
    ref_nucs_before = total_reference_nucs(cigar[:first_indel_index])
    last_indel_index = max(indel_indices)
    ref_nucs_after = total_reference_nucs(cigar[last_indel_index + 1:])
    return min(ref_nucs_before, ref_nucs_after)

def contains_splicing(read):
    return any(k == BAM_CREF_SKIP for k, l in read.cigar)

def contains_soft_clipping(parsed_line):
    cigar_blocks = cigar_string_to_blocks(parsed_line['CIGAR'])
    kinds = [k for k, l in cigar_blocks]
    return ('S' in kinds)

def contains_soft_clipping_pysam(read):
    kinds = [k for k, l in read.cigar]
    return (BAM_CSOFT_CLIP in kinds)

def get_soft_clipped_block(alignment, edge):
    strand = get_strand(alignment)

    if (edge == 5 and strand == '+') or (edge == 3 and strand == '-'):
        op, length = alignment.cigar[0]
        if op == BAM_CSOFT_CLIP:
            sl = slice(None, length)
        else:
            sl = slice(0)
    elif (edge == 5 and strand == '-') or (edge == 3 and strand == '+'):
        op, length = alignment.cigar[-1]
        if op == BAM_CSOFT_CLIP:
            sl = slice(-length, None)
        else:
            sl = slice(0)

    seq = alignment.seq[sl]
    qual = alignment.query_qualities[sl]

    return seq, qual

def get_max_soft_clipped_length(alignment):
    max_soft_clipped = 0
    for edge in [5, 3]:
        seq, qual = get_soft_clipped_block(alignment, edge)
        max_soft_clipped = max(max_soft_clipped, len(seq))
    return max_soft_clipped

def cigar_blocks_to_string(cigar_blocks):
    ''' Builds a CIGAR string out of a corresponding list of operations. '''
    string = [f'{length}{op_to_char[op]}' for op, length in cigar_blocks]
    return ''.join(string)

def aligned_pairs_to_cigar(aligned_pairs, guide=None):
    op_sequence = []
    for read, ref in aligned_pairs:
        if read == None or read == '-':
            op_sequence.append(BAM_CDEL)
        elif read == 's':
            op_sequence.append(BAM_CREF_SKIP)
        elif ref == None or ref == '-':
            op_sequence.append(BAM_CINS)
        elif ref == 'S':
            op_sequence.append(BAM_CSOFT_CLIP)
        else:
            op_sequence.append(BAM_CMATCH)

    cigar = [(op, len(times)) for op, times in utilities.group_by(op_sequence)]

    if guide:
        guide_cigar, from_side = guide

        if from_side == 'right':
            cigar = cigar[::-1]
            guide_cigar = guide_cigar[::-1]

        for i in range(min(len(cigar), len(guide_cigar))):
            op, length = cigar[i]
            guide_op, guide_length = guide_cigar[i]
            cigar[i] = (guide_op, length)
        
        if from_side == 'right':
            cigar = cigar[::-1]
            guide_cigar = guide_cigar[::-1]

    return cigar

def cigar_to_aligned_pairs(cigar, start):
    aligned_pairs = []

    ref_pos = start
    read_pos = 0
    for op, length in cigar:
        if op == BAM_CMATCH or op == BAM_CEQUAL or op == BAM_CDIFF:
            for i in range(length):
                aligned_pairs.append((read_pos, ref_pos))

                ref_pos += 1
                read_pos += 1

        elif op == BAM_CDEL:
            # Deletion results in gap in read
            for i in range(length):
                aligned_pairs.append((None, ref_pos))
                
                ref_pos += 1
        
        elif op == BAM_CREF_SKIP:
            # Skip results in gap in read
            for i in range(length):
                aligned_pairs.append(('s', ref_pos))
                
                ref_pos += 1

        elif op == BAM_CINS:
            # Insertion results in gap in ref
            for i in range(length):
                aligned_pairs.append((read_pos, None))

                read_pos += 1
        
        elif BAM_CSOFT_CLIP:
            # Soft-clipping results in gap in ref
            for i in range(length):
                aligned_pairs.append((read_pos, 'S'))

                read_pos += 1

        else:
            raise ValueError('Unsupported op', cigar)

    return aligned_pairs

def cigar_to_aligned_pairs_backwards(cigar, end, read_length):
    aligned_pairs = []

    ref_pos = end
    read_pos = read_length - 1
    for op, length in cigar[::-1]:
        if op == BAM_CMATCH or op == BAM_CEQUAL or op == BAM_CDIFF:
            for i in range(length):
                aligned_pairs.append((read_pos, ref_pos))

                ref_pos -= 1
                read_pos -= 1

        elif op == BAM_CDEL or op == BAM_CREF_SKIP:
            # Deletion results in gap in read
            for i in range(length):
                aligned_pairs.append((None, ref_pos))
                
                ref_pos -= 1

        elif op == BAM_CINS:
            # Insertion results in gap in ref
            for i in range(length):
                aligned_pairs.append((read_pos, None))

                read_pos -= 1
        
        elif op == BAM_CSOFT_CLIP:
            # Soft-clipping results in gap in ref
            for i in range(length):
                aligned_pairs.append((read_pos, 'S'))

                read_pos -= 1

        else:
            raise ValueError('Unsupported op', cigar)

    return aligned_pairs

def truncate_cigar_blocks_up_to(cigar_blocks, truncated_length):
    ''' Given pysam-style cigar_blocks, truncates the blocks to explain
        truncated_length read bases.
    '''
    bases_so_far = 0
    truncated_blocks = []

    for operation, length in cigar_blocks:
        # If the next block wouldn't consume anything, we want to include it.
        if bases_so_far == truncated_length and operation in read_consuming_ops:
            break

        if operation in read_consuming_ops:
            length_to_use = min(truncated_length - bases_so_far, length)
            bases_so_far += length_to_use
        else:
            length_to_use = length

        truncated_blocks.append((operation, length_to_use))

        # If we didn't use the whole block, need to break because the next loop
        # will try to use the next block if it is non-consuming.
        if length_to_use < length:
            break

    return truncated_blocks

def truncate_cigar_blocks_from_beginning(cigar_blocks, truncated_length):
    ''' Removes cigar operations from the beginning of cigar_blocks so that
    truncated_length total read bases remain accounted for.
    '''
    flipped_truncated_blocks = truncate_cigar_blocks_up_to(cigar_blocks[::-1],
                                                           truncated_length,
                                                          )
    truncated_blocks = flipped_truncated_blocks[::-1]
    return truncated_blocks

def collapse_cigar_blocks(cigar_blocks):
    collapsed = []
    for kind, blocks in utilities.group_by(cigar_blocks, lambda t: t[0]):
        collapsed.append((kind, sum(t[1] for t in blocks)))
    return collapsed

def aligned_pairs_to_MD_string(aligned_pairs):
    ''' Produce an MD string from an alignment. '''
    # Mark all blocks of matching with numbers, all deletion bases with '^*0', and all mismatch bases.
    MD_list = []
    current_match_length = 0
    for ref_char, read_char in aligned_pairs:
        if ref_char == read_char:
            current_match_length += 1
        elif ref_char != '-':
            if current_match_length > 0:
                MD_list.append(current_match_length)
                current_match_length = 0

            if read_char == '-':
                MD_list.append(0)
            else:
                MD_list.append(ref_char)
    
    if current_match_length > 0:
        MD_list.append(current_match_length)

    # Remove all zeros that aren't a deletion followed by a mismatch
    reduced_MD_list = []
    for i in range(len(MD_list)):
        if isinstance(MD_list[i], int):
            if MD_list[i] > 0:
                reduced_MD_list.append(MD_list[i])
            elif 0 < i < len(MD_list) - 1:
                if isinstance(MD_list[i - 1], str) and isinstance(MD_list[i + 1], str) and MD_list[i - 1][0] == '^' and MD_list[i + 1][0] != '^':
                    reduced_MD_list.append(MD_list[i])
        else:
            reduced_MD_list.append(MD_list[i])
    
    # Collapse all deletions.
    collapsed_MD_list = [reduced_MD_list[0]]
    for i in range(1, len(reduced_MD_list)):
        if isinstance(collapsed_MD_list[-1], str) and collapsed_MD_list[-1][0] == '^' and \
           isinstance(reduced_MD_list[i], str) and reduced_MD_list[i][0] == '^':
            
            collapsed_MD_list[-1] += reduced_MD_list[i][1]
        else:
            collapsed_MD_list.append(reduced_MD_list[i])

    # The standard calls for a number to start and to end, zero if necessary.
    if isinstance(collapsed_MD_list[0], str):
        collapsed_MD_list.insert(0, 0)
    if isinstance(collapsed_MD_list[-1], str):
        collapsed_MD_list.append(0)
    
    MD_string = ''.join(map(str, collapsed_MD_list))
    return MD_string

md_number = re.compile(r'[0-9]+')
md_text = re.compile(r'[A-Z]+')

def md_string_to_ops_string(md_string):
    ''' Converts an MD string into a list of operations for supplying reference
        characters, either '=' if equal to the read, or any other char if equal
        to that char.
    '''
    # In the presence of a CIGAR string, the '^' character seems extraneous.
    # 94 is unicode ^.
    md_string = md_string.translate({94: None})
    
    match_lengths = [int(s) for s in re.findall(md_number, md_string)]
    text_blocks = re.findall(md_text, md_string)
    
    # The standard calls for a number to start and end, zero if necessary,
    # so after removing the initial number, there must be the same number of 
    # match_lengths and text_blocks.
    if len(text_blocks) != len(match_lengths) - 1:
        raise ValueError(md_string)
    
    ops_string = '='*match_lengths[0]
    for text_block, match_length in zip(text_blocks, match_lengths[1:]):
        ops_string += text_block
        ops_string += '='*match_length
    
    return ops_string

md_item_pattern = re.compile(r'[0-9]+|[TCAGN^]+')

def int_if_possible(string):
    try:
        int_value = int(string)
        return int_value
    except ValueError:
        return string

def md_string_to_items(md_string):
    items = [int_if_possible(item) for item in md_item_pattern.findall(md_string)]
    return items

def md_items_to_md_string(items):
    string = ''.join(str(item) for item in items)
    return string

def reverse_md_items(items):
    reversed_items = []
    for item in items[::-1]:
        if isinstance(item, int):
            reversed_items.append(item)
        else:
            if item.startswith('^'):
                reversed_items.append('^' + item[:0:-1])
            else:
                reversed_items.append(item[::-1])
    return reversed_items

def truncate_md_items(md_items, truncated_length):
    if truncated_length == 0:
        truncated_items = [0]
    else:
        bases_so_far = 0
        truncated_items = []

        for item in md_items:
            if bases_so_far == truncated_length:
                break

            if isinstance(item, int):
                length_to_use = min(truncated_length - bases_so_far, item)
                bases_so_far += length_to_use
                truncated_items.append(length_to_use)
            else:
                if item.startswith('^'):
                    truncated_item = ['^']
                    item = item[1:]
                else:
                    truncated_item = []

                for c in item:
                    if c == '^':
                        raise ValueError
                    
                    if bases_so_far == truncated_length:
                        break

                    truncated_item.append(c)
                    bases_so_far += 1

                truncated_items.append(''.join(truncated_item))

        # Ensure that it starts and ends with a number
        if not isinstance(truncated_items[0], int):
            truncated_items = [0] + truncated_items
        if not isinstance(truncated_items[-1], int):
            truncated_items = truncated_items + [0]

    return truncated_items

def combine_md_strings(first_string, second_string):
    if first_string == '':
        return second_string
    if second_string == '':
        return first_string

    first_items = md_string_to_items(first_string)
    second_items = md_string_to_items(second_string)
    before = first_items[:-1]
    after = second_items[1:]

    if isinstance(first_items[-1], int):
        if isinstance(second_items[0], int):
            interface = [first_items[-1] + second_items[0]]
        else:
            interface = [first_items[-1], second_items[0]]
    else:
        if isinstance(second_items[0], int):
            interface = [first_items[-1], second_items[0]]
        else:
            if first_items[-1].startswith('^'):
                if second_items[0].startswith('^'):
                    interface = [first_items[-1] + second_items[0][1:]]
                else:
                    interface = [first_items[-1], 0, second_items[0]]
            else:
                if second_items[0].startswith('^'):
                    interface = [first_items[-1], 0, second_items[0]]
                else:
                    interface = [first_items[-1] + second_items[0]]

    combined_items = before + interface + after

    combined_string = md_items_to_md_string(combined_items)
    
    return combined_string

def truncate_md_string_up_to(md_string, truncated_length):
    ''' Truncates from the end of md_string so that the result only consumes
    truncated_length ref characters.
    '''
    md_items = md_string_to_items(md_string)
    truncated_items = truncate_md_items(md_items, truncated_length)
    return md_items_to_md_string(truncated_items)

def truncate_md_string_from_beginning(md_string, truncated_length):
    ''' Truncates from the beginning of md_string so that the result only
    consumes truncated_length ref characters.
    '''
    md_items = md_string_to_items(md_string)
    reversed_items = reverse_md_items(md_items)
    reversed_truncated_items = truncate_md_items(reversed_items, truncated_length)
    truncated_items = reverse_md_items(reversed_truncated_items)
    return md_items_to_md_string(truncated_items)
    
def produce_alignment(mapping):
    ''' Returns a list of (ref_char, read_char, qual_char, ref_pos, read_pos)
        tuples.
    '''
    read_seq = mapping.seq
    if read_seq == None:
        read_seq = ''
    
    read_quals = mapping.query_qualities
    if read_quals == None:
        read_quals = []
    
    MD_string = dict(mapping.tags)['MD']
    
    ref_ops = iter(md_string_to_ops_string(MD_string))
    
    columns = []

    ref_pos = mapping.pos
    read_pos = 0
    for op, length in mapping.cigar:
        if op == BAM_CMATCH or op == BAM_CEQUAL or op == BAM_CDIFF:
            for i in range(length):
                read_char = read_seq[read_pos]
                
                ref_op = next(ref_ops)
                if ref_op == '=':
                    ref_char = read_char
                else:
                    ref_char = ref_op
                
                qual = read_quals[read_pos]
                
                column = (ref_char, read_char, qual, ref_pos, read_pos)
                columns.append(column)

                ref_pos += 1
                read_pos += 1

        elif op == BAM_CDEL:
            # Deletion results in gap in read
            for i in range(length):
                read_char = '-'
                ref_char = next(ref_ops)
                qual = 0 
                
                column = (ref_char, read_char, qual, ref_pos, read_pos)
                columns.append(column)
                
                ref_pos += 1

        elif op == BAM_CINS:
            # Insertion results in gap in ref
            for i in range(length):
                read_char = read_seq[read_pos]
                ref_char = '-'
                qual = read_quals[read_pos]
                column = (ref_char, read_char, qual, ref_pos, read_pos)
                columns.append(column)

                read_pos += 1

        elif op == BAM_CREF_SKIP:
            ref_pos += length

        elif op == BAM_CSOFT_CLIP:
            read_pos += length
    
    return columns

def ref_dict_from_mapping(mapping):
    ''' Build a dictionary mapping reference positions to base identities from
    the cigar and MD tag of a mapping.
    '''
    alignment = produce_alignment(mapping)
    ref_dict = {}
    for ref_char, _, _, ref_position, _ in alignment:
        if ref_char == '-':
            continue

        if ref_position in ref_dict:
            # A ref_position shouldn't appear more than once
            raise ValueError(mapping)

        ref_dict[ref_position] = ref_char

    return ref_dict

def merge_ref_dicts(first_dict, second_dict):
    ''' Merge dictionaries mapping reference positions to base identities. '''
    merged_dict = {}
    merged_dict.update(first_dict)
    for position, base in second_dict.items():
        if position in merged_dict:
            if merged_dict[position] != base:
                # contradiction
                raise ValueError(first_dict, second_dict)
        else:
            merged_dict[position] = base

    return merged_dict

def sort_bam(input_file_name, output_file_name, by_name=False, additional_threads=0):
    output_file_name = Path(output_file_name)

    samtools_command = ['samtools', 'sort']
    if by_name:
        samtools_command.append('-n')

    # For unambiguously marking temp files from this function.
    tail = 'SORT_TEMP'

    # Clean up any temporary files left behind by previous attempts to sort.
    # A little confused by escaping slashes here.
    pattern = f'{output_file_name.name}\\.{tail}\\.\\d\\d\\d\\d\\.bam'
    for fn in output_file_name.parent.iterdir():
        if re.match(pattern, fn.name):
            fn.unlink()

    samtools_command.extend(['-@', str(additional_threads),
                             '-T', str(output_file_name) + f'.{tail}',
                             '-o', str(output_file_name),
                             str(input_file_name),
                            ])

    try:
        subprocess.run(samtools_command, check=True, stderr=subprocess.PIPE)
    except subprocess.CalledProcessError as e:
        print(e.stderr)
        raise

    if not by_name:
        pysam.index(str(output_file_name))

def merge_sorted_bam_files(input_file_names, merged_file_name, by_name=False, make_index=True):
    # To avoid running into max open file limits, split into groups of 500.
    if len(input_file_names) > 500:
        chunks = utilities.list_chunks(input_file_names, 500)
        merged_chunk_fns = []
        for i, chunk in enumerate(chunks):
            merged_chunk_fn = f'{merged_file_name}.intermediate_chunk.{i:04d}'
            merged_chunk_fns.append(merged_chunk_fn)
            merge_sorted_bam_files(chunk, merged_chunk_fn, by_name=by_name, make_index=False)

        merge_sorted_bam_files(merged_chunk_fns, merged_file_name, by_name=by_name)

        for merged_chunk_fn in merged_chunk_fns:
            os.remove(merged_chunk_fn)

    else:
        input_file_names = [str(fn) for fn in input_file_names]
        merged_file_name = str(merged_file_name)

        if len(input_file_names) == 1:
            shutil.copy(input_file_names[0], merged_file_name)
        else:
            merge_command = ['samtools', 'merge', '-f']

            if by_name:
                merge_command.append('-n')

            merge_command.extend([merged_file_name] + input_file_names)

            try:
                subprocess.run(merge_command, check=True, stderr=subprocess.PIPE)
            except subprocess.CalledProcessError as e:
                print(e.stderr)
                raise
        
        if make_index and not by_name:
            try:
                pysam.index(merged_file_name)
            except pysam.utils.SamtoolsError:
                # Need to sort the merged file because at least one input file was missing a target.
                temp_sorted_name = merged_file_name + '.temp_sorted'
                sort_bam(merged_file_name, temp_sorted_name)
                os.rename(temp_sorted_name, merged_file_name)
                os.rename(temp_sorted_name + '.bai', merged_file_name + '.bai')

def bam_to_sam(bam_file_name, sam_file_name):
    view_command = ['samtools', 'view', '-h', '-o', sam_file_name, bam_file_name]
    subprocess.check_call(view_command)

def get_length_counts(bam_file_name, only_primary=True, only_unique=False):
    bam_file = pysam.AlignmentFile(bam_file_name)
    if only_unique:
        qlen_counts = Counter(ar.qlen for ar in bam_file if ar.mapping_quality == 50)
    elif only_primary:
        qlen_counts = Counter(ar.qlen for ar in bam_file if not ar.is_unmapped and not ar.is_secondary)
    else:
        qlen_counts = Counter(ar.qlen for ar in bam_file)
    
    return qlen_counts

def get_tlen_counts(bam_file_name, only_primary=True, only_unique=False):
    bam_file = pysam.AlignmentFile(bam_file_name)
    if only_unique:
        tlen_counts = Counter(ar.tlen for ar in bam_file if ar.mapping_quality == 50)
    elif only_primary:
        tlen_counts = Counter(ar.tlen for ar in bam_file if not ar.is_unmapped and not ar.is_secondary)
    else:
        tlen_counts = Counter(ar.tlen for ar in bam_file)
    
    return tlen_counts

def get_mapq_counts(bam_file_name):
    bam_file = pysam.AlignmentFile(bam_file_name)
    mapq_counts = Counter(ar.mapq for ar in bam_file)
    return mapq_counts

def mapping_to_Read(mapping):
    seq = mapping.get_forward_sequence()
    qual = fastq.encode_sanger(mapping.get_forward_qualities())

    read = fastq.Read(mapping.query_name, seq, qual)
    return read

def sam_to_fastq(sam_file_name):
    sam_file = pysam.AlignmentFile(str(sam_file_name))
    for mapping in sam_file:
        yield mapping_to_Read(mapping)

bam_to_fastq = sam_to_fastq

class AlignmentSorter:
    ''' Context manager that handles writing AlignedSegments into a samtools
    sort process.
    '''
    temp_prefix_tail = 'ALIGNMENTSORTER_TEMP'

    def __init__(self, output_file_name, header, by_name=False):
        self.header = header
        self.output_file_name = Path(output_file_name)
        self.by_name = by_name
        self.fifo = mapping_tools.TemporaryFifo(name='unsorted_fifo.bam')

    def remove_temporary_files(self):
        ''' Find any temporary files that might have been left behind by a
        previous call with the same output_file_name.
        '''
        # A little confused by escaping slashes here.
        pattern = f'{self.output_file_name.name}\\.{AlignmentSorter.temp_prefix_tail}\\.\\d\\d\\d\\d\\.bam'
        for fn in self.output_file_name.parent.iterdir():
            if re.match(pattern, fn.name):
                fn.unlink()

    def __enter__(self):
        self.fifo.__enter__()

        self.remove_temporary_files()

        sort_command = ['samtools', 'sort']
        if self.by_name:
            sort_command.append('-n')

        self.dev_null = open(os.devnull, 'w')
        sort_command.extend(['-T', f'{self.output_file_name}.{AlignmentSorter.temp_prefix_tail}',
                             '-o', f'{self.output_file_name}',
                             self.fifo.file_name,
                            ])
        self.sort_process = subprocess.Popen(sort_command,
                                             stderr=subprocess.PIPE,
                                            )

        self.sam_file = pysam.AlignmentFile(self.fifo.file_name, 'wbu', header=self.header)

        return self

    def __exit__(self, exception_type, exception_value, exception_traceback):
        self.sam_file.close()
        _, err_output = self.sort_process.communicate()
        self.dev_null.close()
        self.fifo.__exit__(exception_type, exception_value, exception_traceback)
        
        self.remove_temporary_files()

        if self.sort_process.returncode:
            raise RuntimeError(err_output)

        if not self.by_name:
            pysam.index(str(self.output_file_name))

    def write(self, alignment):
        self.sam_file.write(alignment)

class multiple_AlignmentSorters(contextlib.ExitStack):
    def __init__(self, header=None, by_name=False):
        super().__init__()
        self.sorters = {}
        self.header = header
        self.by_name = by_name
            
    def __enter__(self):
        super().__enter__()
        for name in self.sorters:
            self.enter_context(self.sorters[name])

        return self
            
    def __getitem__(self, key):
        return self.sorters[key]

    def __setitem__(self, name, fn_and_possibly_header):
        if isinstance(fn_and_possibly_header, tuple):
            fn, header = fn_and_possibly_header
        else:
            fn = fn_and_possibly_header
            header = self.header

        self.sorters[name] = AlignmentSorter(fn, header, self.by_name)

class AlignedSegmentByName(object):
    def __init__(self, aligned_segment):
        self.aligned_segment = aligned_segment
        
    def __lt__(self, other):
        return self.aligned_segment.query_name < other.aligned_segment.query_name

def merge_by_name(*mapping_iterators):
    ''' Merges iterators over mappings that are sorted by name.
    '''
    wrapped_iterators = [(AlignedSegmentByName(m) for m in mappings) for mappings in mapping_iterators]
    merged_wrapped = heapq.merge(*wrapped_iterators)
    last_qname = None
    for al_by_name in merged_wrapped:
        qname = al_by_name.aligned_segment.query_name
        if last_qname is not None and qname < last_qname:
            print(last_qname, qname)
            raise ValueError('Attempted to merge unsorted mapping iterators')

        last_qname = qname
        yield al_by_name.aligned_segment

def aligned_pairs_exclude_soft_clipping(mapping):
    cigar = mapping.cigartuples
    aligned_pairs = mapping.aligned_pairs
    
    first_op, first_length = cigar[0]

    if first_op == BAM_CSOFT_CLIP:
        aligned_pairs = aligned_pairs[first_length:]

    if len(cigar) > 1:
        last_op, last_length = cigar[-1]
        if last_op == BAM_CSOFT_CLIP and last_length != 0:
            aligned_pairs = aligned_pairs[:-last_length]

    return aligned_pairs

def parse_idxstats(bam_fn):
    lines = pysam.idxstats(str(bam_fn)).splitlines()
    fields = [line.split('\t') for line in lines]
    parsed = {rname: int(count) for rname, _, count, _ in fields}
    return parsed

def get_num_alignments(bam_fn):
    return sum(parse_idxstats(bam_fn).values())

def collapse_soft_clip_blocks(cigar_blocks):
    ''' If there are multiple consecutive soft clip blocks on either end,
    collapse them into a single block.
    '''
    first_non_cigar_index = 0
    while cigar_blocks[first_non_cigar_index][0] == BAM_CSOFT_CLIP:
        first_non_cigar_index += 1

    if first_non_cigar_index > 0:
        total_length = sum(length for kind, length in cigar_blocks[:first_non_cigar_index])
        if total_length > 0:
            to_add = [(BAM_CSOFT_CLIP, total_length)]
        else:
            to_add = []
        cigar_blocks = to_add + cigar_blocks[first_non_cigar_index:]
    
    last_non_cigar_index = len(cigar_blocks) - 1
    while cigar_blocks[last_non_cigar_index][0] == BAM_CSOFT_CLIP:
        last_non_cigar_index -= 1

    if last_non_cigar_index < len(cigar_blocks) - 1:
        total_length = sum(length for kind, length in cigar_blocks[last_non_cigar_index + 1:])
        if total_length > 0:
            to_add = [(BAM_CSOFT_CLIP, total_length)]
        else:
            to_add = []
        cigar_blocks = cigar_blocks[:last_non_cigar_index + 1] + to_add

    return cigar_blocks

def crop_al_to_query_int(alignment, start, end):
    ''' Replace any parts of alignment that involve query bases not in the
    interval [start, end] with soft clipping.
    query coords are given relative to the original read (and are therefore
    transformed if alignment is reversed.)
    '''
    alignment = copy.deepcopy(alignment)

    if alignment is None or alignment.is_unmapped:
        return alignment
    
    if end < start:
        # query interval is empty
        return None
    else:
        overlap = interval.Interval(start, end) & interval.get_covered(alignment)
        if len(overlap) == 0:
            return None

    if alignment.is_reverse:
        start, end = alignment.query_length - 1 - end, alignment.query_length - 1 - start

    aligned_pairs = cigar_to_aligned_pairs(alignment.cigar, alignment.reference_start)

    start_i = 0
    read, ref = aligned_pairs[start_i]
    while read is None or read == 's' or read < start:
        start_i += 1
        read, ref = aligned_pairs[start_i]
        
    end_i = len(aligned_pairs) - 1
    read, ref = aligned_pairs[end_i]
    while read is None or read == 's' or read > end:
        end_i -= 1
        read, ref = aligned_pairs[end_i]

    if alignment.has_tag('MD'):
        MD = alignment.get_tag('MD')

        total_ref_nucs = total_reference_nucs_except_splicing(alignment.cigar)
        removed_from_start = total_reference_nucs_except_splicing(aligned_pairs_to_cigar(aligned_pairs[:start_i]))
        removed_from_end = total_reference_nucs_except_splicing(aligned_pairs_to_cigar(aligned_pairs[end_i + 1:]))

        MD = truncate_md_string_up_to(MD, total_ref_nucs - removed_from_end)
        MD = truncate_md_string_from_beginning(MD, total_ref_nucs - removed_from_end - removed_from_start)

        alignment.set_tag('MD', MD)

    restricted_pairs = aligned_pairs[start_i:end_i + 1]
    cigar = aligned_pairs_to_cigar(restricted_pairs) 

    before_soft = start
    if before_soft > 0:
        cigar = [(BAM_CSOFT_CLIP, before_soft)] + cigar

    after_soft = alignment.query_length - end - 1
    if after_soft > 0:
        cigar = cigar + [(BAM_CSOFT_CLIP, after_soft)]

    cigar = collapse_soft_clip_blocks(cigar)

    restricted_rs = [r for q, r in restricted_pairs if r != None and r != 'S']
    if not restricted_rs:
        alignment.is_unmapped = True
        alignment.cigar = []
    else:
        alignment.reference_start = min(restricted_rs)
        alignment.cigar = cigar

    return alignment

def crop_al_to_ref_int(alignment, start, end):
    ''' Returns a copy of alignment in which any query bases that align
    outside the interval [start, end] are soft-clipped. If no bases are left,
    sets alignment.is_unmapped to true.
    '''
    if alignment is None:
        return None

    original_alignment = alignment
    alignment = copy.deepcopy(alignment)

    if alignment.reference_start > end or alignment.reference_end - 1 < start:
        # alignment doesn't overlap the ref interval at all
        return None

    if alignment.reference_start >= start and alignment.reference_end - 1 <= end:
        # alignment is entirely contained in the ref_interval
        return alignment

    query_length = alignment.query_length
    aligned_pairs = cigar_to_aligned_pairs(alignment.cigar, alignment.reference_start)

    start_i = 0
    while (
        aligned_pairs[start_i][1] == 'S' or
        aligned_pairs[start_i][0] is None or
        aligned_pairs[start_i][1] is None or
        aligned_pairs[start_i][1] < start
    ):
        start_i += 1
        
    end_i = len(aligned_pairs) - 1
    while (
        aligned_pairs[end_i][1] == 'S' or
        aligned_pairs[end_i][0] is None or
        aligned_pairs[end_i][1] is None or
        aligned_pairs[end_i][1] > end
    ):
        end_i -= 1

    remaining = aligned_pairs[start_i:end_i + 1]
    if remaining:
        cigar = aligned_pairs_to_cigar(remaining)
        before_soft = remaining[0][0]
        if before_soft > 0:
            cigar = [(BAM_CSOFT_CLIP, before_soft)] + cigar

        after_soft = query_length - remaining[-1][0] - 1
        if after_soft > 0:
            cigar = cigar + [(BAM_CSOFT_CLIP, after_soft)]

        alignment.cigar = cigar

        alignment.reference_start = aligned_pairs[start_i][1]
    else:
        alignment.is_unmapped = True
        alignment.cigar = []

    if alignment.has_tag('MD'):
        MD = alignment.get_tag('MD')

        total_ref_nucs = total_reference_nucs_except_splicing(original_alignment.cigar)
        removed_from_start = total_reference_nucs_except_splicing(aligned_pairs_to_cigar(aligned_pairs[:start_i]))
        removed_from_end = total_reference_nucs_except_splicing(aligned_pairs_to_cigar(aligned_pairs[end_i + 1:]))

        MD = truncate_md_string_up_to(MD, total_ref_nucs - removed_from_end)
        MD = truncate_md_string_from_beginning(MD, total_ref_nucs - removed_from_end - removed_from_start)

        alignment.set_tag('MD', MD)
    
    return alignment

def crop_al_to_feature(al, feature):
    cropped_al = crop_al_to_ref_int(al, feature.start, feature.end)
    return cropped_al

def query_interval_overlapping_feature(al, feature):
    cropped_al = crop_al_to_feature(al, feature)
    return interval.get_covered(cropped_al)

def disallow_query_positions_from_other(alignment, other):
    start, end = query_interval(alignment)
    other_start, other_end = query_interval(other)
    if other_start <= end or other_end >= start:
        if other_start > start and other_end < end:
            raise ValueError
        elif other_start <= start:
            alignment = crop_al_to_query_int(alignment, other_end + 1, alignment.query_length - 1)
        elif other_end >= end:
            alignment = crop_al_to_query_int(alignment, 0, other_start - 1)

    return alignment

def query_interval(alignment):
    start = alignment.query_alignment_start
    end = alignment.query_alignment_end - 1

    if alignment.is_reverse:
        start, end = true_query_position(end, alignment), true_query_position(start, alignment)

    return start, end

def ref_interval(alignment):
    return alignment.reference_start, alignment.reference_end - 1

def merge_multiple_adjacent_alignments(als, ref_seqs, max_deletion_length=np.inf):
    merger = functools.partial(merge_adjacent_alignments, ref_seqs=ref_seqs, max_deletion_length=max_deletion_length)
    als = sorted(als, key=query_interval)
    return functools.reduce(merger, als)

def merge_any_adjacent_pairs(als, ref_seqs, max_deletion_length=np.inf, max_insertion_length=0):
    if len(als) == 0:
        return als
    else:
        als = sorted(als, key=query_interval)

        all_merged_als = []

        als_by_ref_name = defaultdict(list)
        for al in als:
            als_by_ref_name[al.reference_name].append(al)

        for ref_name, als in als_by_ref_name.items():
            merged_als = [als[0]]

            while len(als) > 0:
                left_al = merged_als.pop()
                right_al = als.pop(0)
                
                merged = merge_adjacent_alignments(left_al, right_al, ref_seqs, max_deletion_length=max_deletion_length, max_insertion_length=max_insertion_length)
                if merged is not None:
                    merged_als.append(merged)
                else:
                    merged_als.extend([left_al, right_al])
        
            all_merged_als.extend(merged_als)

        return all_merged_als

def merge_adjacent_alignments(first, second, ref_seqs, max_deletion_length=np.inf, max_insertion_length=0):
    ''' If first and second are alignments to the same reference name and strand
    that are adjacent or partially overlap on the query, or are consistent with being
    separated by an insertion up to length max_insertion_length, returns a single merged
    alignment with an appropriately sized insertion or deletion that minimizes edit distance,
    otherwise return None.
    '''
    if first is None or second is None:
        return None

    if first == second:
        return first

    if first.reference_name != second.reference_name:
        return None
    else:
        ref_seq = ref_seqs[first.reference_name]

    if get_strand(first) != get_strand(second):
        return None

    left_query, right_query = sorted([first, second], key=query_interval)
    left_covered = interval.get_covered(left_query)
    right_covered = interval.get_covered(right_query)

    # Ensure that the alignments point towards each other.
    strand = get_strand(first)
    if strand == '+':
        left_cropped = crop_al_to_query_int(left_query, 0, right_covered.start - 1)
        if left_cropped is None or left_cropped.is_unmapped:
            # left alignment doesn't cover any query not covered by right
            return None

    elif strand == '-':
        right_cropped = crop_al_to_query_int(right_query, left_covered.end + 1, np.inf)
        if right_cropped is None or right_cropped.is_unmapped:
           # right alignment doesn't cover any query not covered by left
           return None

    query_gap = right_covered.start - left_covered.end - 1

    if query_gap >= 0:
        # If intervals are disjoint, no cropping is necessary.
        left_cropped, right_cropped = left_query, right_query

    else:
        overlap = left_covered & right_covered
        left_ceds = cumulative_edit_distances(left_query, overlap, False, ref_seq=ref_seq)
        right_ceds = cumulative_edit_distances(right_query, overlap, True, ref_seq=ref_seq)

        switch_after_edits = {
            overlap.start - 1 : right_ceds[overlap.start],
            overlap.end: left_ceds[overlap.end],
        }

        for q in range(overlap.start, overlap.end):
            switch_after_edits[q] = left_ceds[q] + right_ceds[q + 1]

        min_edits = min(switch_after_edits.values())
        best_switch_points = [s for s, d in switch_after_edits.items() if d == min_edits]
        switch_after = best_switch_points[0]

        left_cropped = crop_al_to_query_int(left_query, 0, switch_after)
        right_cropped = crop_al_to_query_int(right_query, switch_after + 1, right_query.query_length)

    if left_cropped is None or left_cropped.is_unmapped or right_cropped is None or right_cropped.is_unmapped:
        # this may not be appropriate in all circumstances
        return None

    if strand == '+':
        first_al, second_al = left_cropped, right_cropped
    elif strand == '-':
        first_al, second_al = right_cropped, left_cropped

    possible_insertion = (first_al.reference_end - 1) + max(query_gap, 0) >= second_al.reference_start

    possible_deletion = query_gap <= 0

    if possible_insertion:
        # Crop first_al so that no ref position is represented twice.
        first_al = crop_al_to_ref_int(first_al, first_al.reference_start, second_al.reference_start - 1)

        # If cropping eliminates first_al, not a valid insertion.
        if first_al is None:
            return None

        left_covered, right_covered = sorted(map(interval.get_covered, [first_al, second_al]))
        insertion_length = (right_covered.start - 1) - left_covered.end

        if insertion_length > max_insertion_length:
            return None
        elif insertion_length > 0:
            # TODO: Does MD tag need to be modified here?
            indel_cigar = [(BAM_CINS, insertion_length)]
        else:
            indel_cigar = []

    elif possible_deletion:
        # Possible deletion
        deletion_length = second_al.reference_start - first_al.reference_end

        if deletion_length > max_deletion_length:
            return None
        elif deletion_length > 0:
            indel_cigar = [(BAM_CDEL, deletion_length)]
        else:
            indel_cigar = []

    else:
        return None

    left_ref, right_ref = sorted([first_al, second_al], key=ref_interval)

    merged = copy.deepcopy(left_ref)
    merged.cigar = left_ref.cigar[:-1] + indel_cigar + right_ref.cigar[1:]

    return merged

def cumulative_edit_distances(mapping, query_interval, from_end, ref_seq=None):
    ''' Returns a dictionary of how many cumulatives edits are involved
    in mapping from the beginning (or end, if from_end is True) of query_interval
    to each query position in query_interval.
    '''
    tuples = aligned_tuples(mapping, ref_seq=ref_seq)
    
    if get_strand(mapping) == '-':    
        tuples = tuples[::-1]
        
    beginning = [i for i, (q, read, r, ref, qual) in enumerate(tuples) if q == query_interval.start][0]
    end = [i for i, (q, read, r, ref, qual) in enumerate(tuples) if q == query_interval.end][-1]
    
    relevant = tuples[beginning:end + 1]
    if from_end:
        relevant = relevant[::-1]

    c_e_ds = {}

    total = 0

    for q, read_b, r, ref_b, qual in relevant:
        if read_b != ref_b:
            total += 1
        
        if q is not None:
            c_e_ds[q] = total
            
    return c_e_ds

def are_overlapping(first_al, second_al):
    return interval.get_covered(first_al) & interval.get_covered(second_al)

def find_best_query_switch_after(left_al, right_al, left_ref_seq, right_ref_seq, tie_break):
    ''' If left_al and right_al overlap on the query, find the query position such that switching from
    left_al to right_al after that position minimizes the total number of edits.
    '''
    left_covered = interval.get_covered(left_al)
    right_covered = interval.get_covered(right_al)
    overlap = left_covered & right_covered

    if left_al is None and right_al is None:
        raise ValueError

    elif left_al is None:
        gap_interval = interval.Interval(0, right_covered.start - 1)

    elif right_al is None:
        gap_interval = interval.Interval(left_covered.end + 1, len(left_al.seq) - 1)

    else:
        gap_interval = interval.Interval(left_covered.end + 1, right_covered.start - 1)

    if overlap:
        left_ceds = cumulative_edit_distances(left_al, overlap, False, ref_seq=left_ref_seq)
        right_ceds = cumulative_edit_distances(right_al, overlap, True, ref_seq=right_ref_seq)

        switch_after_edits = {
            overlap.start - 1: right_ceds[overlap.start],
            overlap.end: left_ceds[overlap.end],
        }

        # 22.08.17: I understand this less well than I thought I did.
        # It's not clear what the behavior should be for entirely contained als,
        # but probably should be that switch_after entirely outside should be
        # included, and if this code is included, this doesn't happen. 
        # # If left_al doesn't covers the query base before overlap.start,
        # # overlap.start - 1 needs to pay a penalty of 1. 
        # if left_covered.start > overlap.start - 1:
        #     switch_after_edits[overlap.start - 1] += 1

        # 22.08.15: does equivalent logic need to be added to overlap.end?

        for q in range(overlap.start, overlap.end):
            switch_after_edits[q] = left_ceds[q] + right_ceds[q + 1]

        min_edits = min(switch_after_edits.values())
        best_switch_points = [s for s, d in switch_after_edits.items() if d == min_edits]
        switch_after = tie_break(best_switch_points)

    else:
        min_edits = 0
        switch_after = left_covered.end
        switch_after_edits = {}
        left_ceds = None
        right_ceds = None
        best_switch_points = [switch_after]

    if gap_interval.is_empty:
        gap_length = 0
        gap_interval = None
    else:
        gap_length = len(gap_interval)
    
    results = {
        'switch_after': switch_after,
        'best_switch_points': sorted(best_switch_points),
        'min_edits': min_edits,
        'gap_interval': gap_interval,
        'gap_length': gap_length,
    }

    return results

def true_query_position(p, alignment):
    if alignment.is_reverse:
        p = alignment.query_length - 1 - p
    return p

def closest_query_position(r, alignment, which_side='either'):
    ''' Return query position paired with r (or with the closest to r) '''
    r_to_q = {r: true_query_position(q, alignment)
              for q, r in alignment.aligned_pairs
              if r is not None and q is not None
             }
    if r in r_to_q:
        q = r_to_q[r]
    else:
        if which_side == 'either':
            rs = r_to_q
        elif which_side == 'before':
            rs = (other_r for other_r in r_to_q if other_r < r)
        elif which_side == 'after':
            rs = (other_r for other_r in r_to_q if other_r > r)

        closest_r = min(rs, key=lambda other_r: abs(other_r - r))
        q = r_to_q[closest_r]

    return q

def query_position_to_ref_position(alignment):
    return {true_query_position(q, alignment): r
            for q, r in alignment.aligned_pairs
            if r is not None and q is not None
           }

def closest_ref_position(q, alignment, which_side='either'):
    ''' Return ref position paired with q (or with the closest to q) '''
    q_to_r = query_position_to_ref_position(alignment)

    if q in q_to_r:
        r = q_to_r[q]
    else:
        if which_side == 'either':
            qs = q_to_r
        elif which_side == 'before':
            qs = [other_q for other_q in q_to_r if other_q < q]
        elif which_side == 'after':
            qs = [other_q for other_q in q_to_r if other_q > q]
        elif which_side == 'exact':
            qs = []
        else:
            raise ValueError(which_side)

        if len(qs) == 0:
            r = None
        else:
            closest_q = min(qs, key=lambda other_q: abs(other_q - q))
            r = q_to_r[closest_q]

    return r

def max_block_length(alignment, block_types):
    if alignment is None or alignment.is_unmapped:
        return 0
    else:
        block_lengths = [l for k, l in alignment.cigar if k in block_types]
        if len(block_lengths) == 0:
            return 0
        else:
            return max(block_lengths)

def total_indel_lengths(alignment):
    if alignment.is_unmapped:
        return 0
    else:
        return sum(l for k, l in alignment.cigar if k == BAM_CDEL or k == BAM_CINS)

def get_ref_pos_to_block(alignment):
    ref_pos_to_block = {}
    ref_pos = alignment.reference_start
    for kind, length in alignment.cigar:
        if kind in ref_consuming_ops:
            starts_at = ref_pos

            for r in range(ref_pos, ref_pos + length):
                ref_pos_to_block[r] = (kind, length, starts_at)

            ref_pos += length

    return ref_pos_to_block

def split_at_first_large_insertion(alignment, min_length, exempt_if_overlaps=None):
    q = 0

    # If the alignment is reversed, alignment.cigar is reversed relative to
    # true query positions.
    cigar = alignment.cigar
    if alignment.is_reverse:
        cigar = cigar[::-1]

    # Using cigar blocks, march from beginning of the read to the (possible)
    # insertion point to determine the query interval to crop to.
    for kind, length in cigar:
        if kind == BAM_CINS and length >= min_length:
            before = crop_al_to_query_int(alignment, 0, q - 1)
            after = crop_al_to_query_int(alignment, q + length, alignment.query_length)
            
            if get_strand(alignment) == '+':
                inserted_at = after.reference_start - 0.5
            else:
                inserted_at = before.reference_start - 0.5

            if exempt_if_overlaps is None or inserted_at not in exempt_if_overlaps:
                return [before, after]

        if kind in read_consuming_ops:
            q += length

    return [alignment]

def split_at_large_insertions(alignment, min_length, exempt_if_overlaps=None):
    ''' O(n^2) behavior can be bad for pacbio alignments. '''
    all_split = []
    
    to_split = [alignment]

    while len(to_split) > 0:
        candidate = to_split.pop()
        split = split_at_first_large_insertion(candidate, min_length, exempt_if_overlaps=exempt_if_overlaps)
        if len(split) > 1:
            to_split.extend(split)
        else:
            all_split.extend(split)

    return all_split

def split_at_deletions(alignment, min_length, exempt_if_overlaps=None):
    ''' Split at deletions at least min_length that don't overlap exempt_if_overlaps. '''

    ref_start = alignment.reference_start
    query_bases_before = 0
    query_bases_after = alignment.query_length
    
    tuples = []

    split_at = []
    
    for i, (kind, length) in enumerate(alignment.cigar):
        if kind == BAM_CDEL:
            del_interval = interval.Interval(ref_start, ref_start + length - 1)

            if exempt_if_overlaps is None:
                overlaps = False
            else:
                overlaps = len(del_interval & exempt_if_overlaps) > 0

            if length >= min_length and not overlaps:
                if i != 0 and i != len(alignment.cigar) - 1:
                    split_at.append(i)
        
        if kind in read_consuming_ops:
            read_consumed = length
        else:
            read_consumed = 0
            
        if kind in ref_consuming_ops:
            ref_consumed = length
        else:
            ref_consumed = 0
            
        query_bases_after -= read_consumed
        tuples.append((query_bases_before, query_bases_after, ref_start))
        
        query_bases_before += read_consumed
        ref_start += ref_consumed
        
    split_alignments = []

    if len(split_at) == 0:
        split_alignments = [alignment]
    else:
        split_at = [-1] + split_at + [len(alignment.cigar)]
    
        for i in range(len(split_at) - 1):
            query_bases_before, _, ref_start = tuples[split_at[i] + 1]
            if split_at[i + 1] == len(alignment.cigar):
                query_bases_after = 0
            else:
                _, query_bases_after, _ = tuples[split_at[i + 1]]

            new_cigar = alignment.cigar[split_at[i] + 1:split_at[i + 1]]

            if query_bases_before > 0:
                new_cigar = [(BAM_CSOFT_CLIP, query_bases_before)] + new_cigar

            if query_bases_after > 0:
                new_cigar = new_cigar + [(BAM_CSOFT_CLIP, query_bases_after)]

            split_al = copy.deepcopy(alignment)
            split_al.cigar = new_cigar
            split_al.reference_start = ref_start
            
            split_alignments.append(split_al)

    split_alignments = [soft_clip_terminal_insertions(al) for al in split_alignments]

    return split_alignments

def soft_clip_terminal_insertions(al):
    ''' If al starts or ends with insertions, convert the relevant bases into soft-clipping. '''
    initial_cigar = al.cigar
    clip_lengths = {}
    
    if initial_cigar[0][0] == BAM_CSOFT_CLIP:
        clip_lengths['beginning'] = initial_cigar[0][1]
    else:
        clip_lengths['beginning'] = 0
    
    if len(initial_cigar) > 1 and initial_cigar[-1][0] == BAM_CSOFT_CLIP:
        clip_lengths['end'] = initial_cigar[-1][1]
    else:
        clip_lengths['end'] = 0
        
    non_soft_clipped_blocks = [(kind, length) for kind, length in al.cigar if kind != BAM_CSOFT_CLIP]
    
    if len(non_soft_clipped_blocks) == 0:
        return al
    
    had_terminal_insertion = False
    
    first_kind, first_length = non_soft_clipped_blocks[0]

    if first_kind == BAM_CINS:
        had_terminal_insertion = True
        clip_lengths['beginning'] += first_length

        non_soft_clipped_blocks = non_soft_clipped_blocks[1:]
        
    if len(non_soft_clipped_blocks) > 0:
        last_kind, last_length = non_soft_clipped_blocks[-1]
        
        if last_kind == BAM_CINS:
            had_terminal_insertion = True
            clip_lengths['end'] += last_length

            non_soft_clipped_blocks = non_soft_clipped_blocks[:-1]
    
    if had_terminal_insertion:
        new_cigar = non_soft_clipped_blocks

        if clip_lengths['beginning'] > 0:
            new_cigar = [(BAM_CSOFT_CLIP, clip_lengths['beginning'])] + new_cigar

        if clip_lengths['end'] > 0:
            new_cigar = new_cigar + [(BAM_CSOFT_CLIP, clip_lengths['end'])]

        new_al = copy.deepcopy(al)
        new_al.cigar = new_cigar
    else:
        new_al = al
    
    return new_al

def remove_terminal_deletions(al):
    al = copy.deepcopy(al)
    
    last_block_type, last_block_length = al.cigar[-1]
    if last_block_type == BAM_CDEL:
        al.cigar = al.cigar[:-1]
        if al.is_reverse:
            al.reference_start = al.reference_start + last_block_length
            
    first_block_type, first_block_length = al.cigar[0]
    if first_block_type == BAM_CDEL:
        al.cigar = al.cigar[1:]
        if not al.is_reverse:
            al.reference_start = al.reference_start + first_block_length
    
    return al

def grouped_by_name(als):
    if isinstance(als, (str, Path)):
        saved_verbosity = pysam.set_verbosity(0)
        als = pysam.AlignmentFile(als)
        pysam.set_verbosity(saved_verbosity)

    grouped = utilities.group_by(als, lambda al: al.query_name)

    return grouped

def header_from_STAR_index(index):
    index = Path(index)
    names = (index / 'chrName.txt').read_text().splitlines()
    lengths = [int(l) for l in (index / 'chrLength.txt').read_text().splitlines()]
    header = pysam.AlignmentHeader.from_references(names, lengths)
    return header

def header_from_fasta(fasta_fn):
    fai = fasta.load_fai(fasta_fn).sort_index()

    names = [str(name) for name, row in fai.iterrows()]
    lengths = [row['LENGTH'] for name, row in fai.iterrows()]

    header = pysam.AlignmentHeader.from_references(names, lengths)

    return header

def overlaps_feature(alignment, feature, require_same_strand=True):
    if alignment is None or alignment.is_unmapped:
        return False

    same_reference = alignment.reference_name == feature.seqname
    num_overlapping_bases = feature_overlap_length(alignment, feature)

    if require_same_strand:
        same_strand = (get_strand(alignment) == feature.strand)
    else:
        same_strand = True

    return same_reference and same_strand and (num_overlapping_bases > 0) 

def feature_overlap_length(alignment, feature):
    if alignment is None:
        overlap = 0
    else:
        overlap = alignment.get_overlap(feature.start, feature.end + 1)

    return overlap

def reference_edges(alignment):
    ''' Returns a dictionary of 
    {
        5: reference position mapped to by the left-most query nt in alignment,
        3: reference position mapped to by the right-most query nt in alignment,
    }

    TODO: For consistency with other conventions, these keys should probably
    be 'left' and 'right' instead of 5 and 3.
    '''

    if alignment is None or alignment.is_unmapped:
        return {5: None, 3: None}

    strand = get_strand(alignment)

    if strand == '+':
        edges = {
            5: alignment.reference_start,
            3: alignment.reference_end - 1,
        }
    elif strand == '-':
        edges = {
            5: alignment.reference_end - 1,
            3: alignment.reference_start,
        }

    return edges

def reference_interval(alignment):
    return interval.Interval(alignment.reference_start, alignment.reference_end - 1)

def aligned_tuples(alignment, ref_seq=None):
    tuples = []

    if ref_seq is None:
        aligned_pairs = alignment.get_aligned_pairs(with_seq=True)

        # Remove soft-clipping
        min_i = min(i for i, (q, _, ref_b) in enumerate(aligned_pairs) if ref_b is not None)
        max_i = max(i for i, (q, _, ref_b) in enumerate(aligned_pairs) if ref_b is not None)
        aligned_pairs = aligned_pairs[min_i:max_i + 1]

        for read_i, ref_i, ref_b in aligned_pairs:
            if read_i is None:
                true_read_i = None
                read_b = '-'
                qual = -1
            else:
                true_read_i = true_query_position(read_i, alignment)
                read_b = alignment.query_sequence[read_i].upper()
                qual = alignment.query_qualities[read_i]
            
            if ref_i is not None and ref_b is None:
                # don't include spliced reference positions. (Is this an appropriate check for this situation?)
                continue

            if ref_i is None:
                ref_b = '-'
            else:
                ref_b = ref_b.upper()

            tuples.append((true_read_i, read_b, ref_i, ref_b, qual))

    else:
        aligned_pairs = aligned_pairs_exclude_soft_clipping(alignment)
        
        for read_i, ref_i in aligned_pairs:
            if read_i is None:
                read_b = '-'
                true_read_i = None
                qual = -1
            else:
                true_read_i = true_query_position(read_i, alignment)
                read_b = alignment.query_sequence[read_i].upper()
                qual = alignment.query_qualities[read_i]
                
            if ref_i is None:
                ref_b = '-'
            else:
                ref_b = ref_seq[ref_i].upper()
                
            tuples.append((true_read_i, read_b, ref_i, ref_b, qual))

    return tuples

def total_edit_distance(alignment, ref_seq=None):
    return edit_distance_in_query_interval(alignment, ref_seq=ref_seq)

def edit_distance_in_query_interval(alignment, query_interval=None, ref_seq=None, only_Q30=False):
    if query_interval is None:
        query_interval = interval.Interval(0, np.inf)

    if query_interval.is_empty or alignment is None or alignment.is_unmapped:
        return 0

    distance = 0

    start = query_interval.start
    end = query_interval.end

    tuples = aligned_tuples(alignment, ref_seq)
    if alignment.is_reverse:
        tuples = tuples[::-1]

    first_i = min(i for i, (q, _, _, _, _) in enumerate(tuples) if q is not None and q >= start)
    last_i = max(i for i, (q, _, _, _, _) in enumerate(tuples) if q is not None and q <= end)
    
    for q, q_base, r, r_base, qual in tuples[first_i:last_i + 1]:
        if q_base != r_base:
            if qual >= 30 or not only_Q30:
                distance += 1

    return distance

def get_header(bam_fn):
    saved_verbosity = pysam.set_verbosity(0)
    with pysam.AlignmentFile(bam_fn) as bam_file:
        header = bam_file.header
    pysam.set_verbosity(saved_verbosity)
    return header

def flip_alignment(alignment):
    # Changing the is_reverse flag is functionally equivalent to the read having been
    # reverse complemented before alignment.
    flipped_alignment = copy.deepcopy(alignment)
    flipped_alignment.is_reverse = not alignment.is_reverse
    return flipped_alignment

def fingerprint(al):
    if al is None:
        return None
    else:
        return tuple(al.cigar), al.reference_start, al.reference_name, al.is_reverse

def make_nonredundant(alignments):
    ''' Two alignments of the same read are redundant if they pair the same read bases with the same
    reference bases. Given alignments of the same read, return alignments in which only one representative
    of each equivalent class of redundancy is retained.
    ''' 
    
    nonredundant = {fingerprint(al): al for al in alignments if al is not None}
    
    return list(nonredundant.values())

def make_noncontained(alignments, max_length=np.inf, alignments_contained_in=None):
    ''' Alignment A is contained in alignment B if
    the query interval covered by A is a subset of the query interval covered by B.
    Does not remove als longer than max_length.
    ''' 
    query_intervals = [interval.get_covered(al) for al in alignments]

    if alignments_contained_in is None:
        alignments_contained_in = alignments
        query_intervals_contained_in = query_intervals
    else:
        query_intervals_contained_in = [interval.get_covered(al) for al in alignments_contained_in]

    to_remove = set()
    for first_i in range(len(alignments)):
        for second_i in range(len(alignments_contained_in)):

            if alignments[first_i] == alignments_contained_in[second_i]:
                continue

            if query_intervals[first_i] in query_intervals_contained_in[second_i]:
                if query_intervals[first_i].total_length <= max_length:
                    to_remove.add(first_i)
    
    noncontained = [al for i, al in enumerate(alignments) if i not in to_remove and al is not None]
    
    return noncontained
