lib.py 42.7 KB
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#!/usr/bin/env python

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import re, sys, argparse, random
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#import numpy as np  # Imported only when calling nnls()
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from ConfigParser import RawConfigParser, MissingSectionHeaderError
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from StringIO import StringIO
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# Patterns that match entire sequences.
PAT_SEQ_RAW = re.compile("^[ACGT]*$")
PAT_SEQ_TSSV = re.compile("^(?:[ACGT]+\(\d+\))*$")
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PAT_SEQ_ALLELENAME = re.compile(  # First line: n_ACT[m] or alias.
    "^(?:(?:(?:CE)?\d+(?:\.\d+)?_(?:[ACGT]+\[\d+\])+)|((?!_).+?))"
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    "(?:_[-+]\d+(?:\.1)?(?P<a>(?:(?<=\.1)-)|(?<!\.1)[ACGT]+)>"  # _+3A>
        "(?!(?P=a))(?:[ACTG]+|-))*$")  # Portion of variants after '>'.

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# Patterns that match blocks of TSSV-style sequences and allele names.
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PAT_TSSV_BLOCK = re.compile("([ACGT]+)\((\d+)\)")
PAT_ALLELENAME_BLOCK = re.compile("([ACGT]+)\[(\d+)\]")
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PAT_ALIAS = re.compile("^(?!_).+$")
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# Pattern that matches a single prefix/suffix variant.
PAT_VARIANT = re.compile(
    "^([-+]\d+)(?:\.1)?"  # Position number
    "(?P<a>(?:(?<=\.1)-)|(?<!\.1)[ACGT]+)>"  # From part
    "(?!(?P=a))([ACTG]+|-)$")  # To part

# Patterns that match (parts of) an STR definition.
PAT_STR_DEF = re.compile(
    "^(?:[ACGT]+\s+\d+\s+\d+(?:\s+[ACGT]+\s+\d+\s+\d+)*)?$")
PAT_STR_DEF_BLOCK = re.compile("([ACGT]+)\s+(\d+)\s+(\d+)")

# Pattern to split a comma-, semicolon-, or space-separated list.
PAT_SPLIT = re.compile("[,; ]+")

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# Default regular expression to capture sample tags in file names.
# This is the default of the -e command line option.
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DEF_TAG_EXPR = "^(.*?)(?:\.[^.]+)?$"
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# Default formatting template to write sample tags.
# This is the default of the -f command line option.
DEF_TAG_FORMAT = "\\1"

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def call_variants(template, sequence, reverse_indices=False, cache=True,
                  debug=False):
    """
    Perform a global alignment of sequence to template and return a
    list of variants detected.  All variants are given as substitutions
    in the form posX>Y, where the first base in the template is pos=1.
    Set reverse_indices to True to count from right to left instead.
    Insertions and deletions are pos.1->Y and posX>-, respectively.

    By default, the results of this function are cached.  Set cache to
    False to suppress caching the result and reduce memory usage.

    Setting debug to True will cause the alignment matrices to be
    printed to sys.stdout.  Be aware that they can be quite large.
    """
    # Saving the results in a cache to avoid repeating alignments.
    try:
        return call_variants.cache[template, sequence, reverse_indices]
    except KeyError:
        pass

    row_offset = len(template) + 1
    matrix_match = [0] * row_offset * (len(sequence)+1)
    matrix_gap1 = [-sys.maxint-1] * row_offset * (len(sequence)+1)
    matrix_gap2 = [-sys.maxint-1] * row_offset * (len(sequence)+1)

    MATCH_SCORE = 1
    MISMATCH_SCORE = -1
    GAP_OPEN_SCORE = -10
    GAP_EXTEND_SCORE = -1

    for i in range(len(matrix_match)):
        x = i % row_offset
        y = i / row_offset

        # Initialisation of first row and column.
        if x == 0 or y == 0:
            if x != 0:
                # Top row.
                matrix_gap1[i] = GAP_OPEN_SCORE + GAP_EXTEND_SCORE * (x - 1)
                matrix_match[i] = matrix_gap1[i]
            elif y != 0:
                # Left column.
                matrix_gap2[i] = GAP_OPEN_SCORE + GAP_EXTEND_SCORE * (y - 1)
                matrix_match[i] = matrix_gap2[i]
            continue

        matrix_gap1[i] = max(
            matrix_match[i-1] + GAP_OPEN_SCORE,
            matrix_gap1[i-1] + GAP_EXTEND_SCORE)
        matrix_gap2[i] = max(
            matrix_match[i-row_offset] + GAP_OPEN_SCORE,
            matrix_gap2[i-row_offset] + GAP_EXTEND_SCORE)

        if template[x-1] == sequence[y-1]:
            match = MATCH_SCORE
        else:
            match = MISMATCH_SCORE

        matrix_match[i] = max(
            matrix_match[i-1-row_offset] + match,
            matrix_gap1[i],
            matrix_gap2[i])

    if debug:
        print("GAP1")
        for i in range(0, len(matrix_gap1), row_offset):
            print(("%5i" * row_offset) % tuple(matrix_gap1[i:i+row_offset]))
        print("GAP2")
        for i in range(0, len(matrix_gap2), row_offset):
            print(("%5i" * row_offset) % tuple(matrix_gap2[i:i+row_offset]))
        print("Match")
        for i in range(0, len(matrix_match), row_offset):
            print(("%5i" * row_offset) % tuple(matrix_match[i:i+row_offset]))


    # Backtracking.
    variants = []
    variant_template = 0
    variant_sequence = 0
    i = len(matrix_match) - 1
    while i >= 0:
        x = i % row_offset
        y = i / row_offset

        if matrix_gap1[i] == matrix_match[i]:
            # Go horizontally.  Deletion.
            variant_template += 1
            i -= 1
            continue

        if matrix_gap2[i] == matrix_match[i]:
            # Go vertically.  Insertion.
            variant_sequence += 1
            i -= row_offset
            continue

        # Only backtracking diagonally if a gap is out of the question.
        # Go diagonally.  Either match or mismatch.
        if i == 0 or template[x - 1] == sequence[y - 1]:
            # Match.  Flush variants.
            if variant_template or variant_sequence:
                if variant_template == 0:
                    # Insertions: "-131.1->C" instead of "-130->C".
                    variants.append("%+i.1->%s" % (
                        x - int(reverse_indices) * row_offset,
                        sequence[y:y+variant_sequence]))
                else:
                    variants.append("%+i%s>%s" % (
                        (x + 1) - int(reverse_indices) * row_offset,
                        template[x:x+variant_template],
                        sequence[y:y+variant_sequence] or "-"))
                variant_template = 0
                variant_sequence = 0
        else:
            # Start/extend mismatch.
            variant_template += 1
            variant_sequence += 1
        i -= 1 + row_offset

    # If reverse_indices=False, we need to reverse the output instead.
    if not reverse_indices:
        variants.reverse()

    # Store the result in the cache.
    if cache:
        call_variants.cache[template, sequence, reverse_indices] = variants
    return variants
#call_variants
call_variants.cache = {}


def mutate_sequence(sequence, variants):
    """Apply the given variants to the given sequence."""
    if not sequence and len(variants) > 1:
        raise ValueError("With an empty sequence, only a single variant is "
                         "possible: an insertion '+0.1->x' or '-1.1->x'.")
    sequence = list(sequence)
    for variant in variants:
        vm = PAT_VARIANT.match(variant)
        if vm is None:
            raise ValueError("Unrecognised variant '%s'" % variant)
        pos = int(vm.group(1))
        old = vm.group(2)
        new = vm.group(3)
        if old == "-":
            old = ""
        if new == "-":
            new = ""
        if pos < 0:
            pos += len(sequence) + 1
        if pos == 0 and len(sequence) == 0:
            # Insertion into empty sequence.
            return new
        if old != "".join(sequence[pos-1:pos+len(old)-1]):
            raise ValueError("Incorrect original sequence in variant '%s'; "
                             "should be '%s'!" % (variant,
                               "".join(sequence[pos-1:pos+len(old)-1]) or "-"))
        sequence[pos-1:pos+len(old)-1] = [""] * len(old)
        if pos:
            sequence[pos-1] += new
        else:
            # Insertion at the beginning of the sequence
            sequence[0] = new + sequence[0]
    return "".join(sequence)
#mutate_sequence


def parse_library(handle):
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    if handle == sys.stdin:
        # Can't seek on pipes, so read it into a buffer first.
        handle = StringIO(sys.stdin.read())
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    try:
        return parse_library_ini(handle)
    except MissingSectionHeaderError:
        # Not an ini file.
        pass
    handle.seek(0)
    return parse_library_tsv(handle)
#parse_library


def parse_library_tsv(handle):
    """
    Parse a TSSV library file (tab-separated values format).

    The provided file should contain at least four columns: marker name,
    left flanking sequence, right flanking sequence, and STR definition.

    Return a nested dict with top-level keys "flanks" and "regex".
    """
    library = {
      "flanks": {},
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      "regex": {},
      "regex_middle": {}
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    }
    for line in handle:
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        line = [x.strip() for x in line.rstrip("\r\n").split("\t")]
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        if line == [""]:
            continue
        if len(line) < 4:
            raise ValueError(
                "Invalid library file: encountered line with %i columns, "
                "need at least 4" % len(line))
        marker = line[0]
        if PAT_SEQ_RAW.match(line[1]) is None:
            raise ValueError("Flanking sequence '%s' of marker %s is invalid" %
                             (line[1], marker))
        if PAT_SEQ_RAW.match(line[2]) is None:
            raise ValueError("Flanking sequence '%s' of marker %s is invalid" %
                             (line[2], marker))
        if PAT_STR_DEF.match(line[3]) is None:
            raise ValueError("STR definition '%s' of marker %s is invalid" %
                             (line[3], marker))
        library["flanks"][marker] = line[1:3]
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        library["regex_middle"][marker] = re.compile("".join(
            "(%s){%s,%s}" % x for x in PAT_STR_DEF_BLOCK.findall(line[3])))
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        library["regex"][marker] = re.compile(
            "".join(["^", library["regex_middle"][marker].pattern, "$"]))
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    return library
#parse_library_tsv


def parse_library_ini(handle):
    library = {
      "flanks": {},
      "prefix": {},
      "suffix": {},
      "regex": {},
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      "regex_middle": {},
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      "length_adjust": {},
      "block_length": {},
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      "aliases": {}
    }
    markers = set()

    ini = RawConfigParser()
    ini.optionxform = str
    ini.readfp(handle)
    for section in ini.sections():
        for marker in ini.options(section):
            value = ini.get(section, marker)
            if section == "flanks":
                values = PAT_SPLIT.split(value)
                if len(values) != 2:
                    raise ValueError(
                        "For marker %s, %i flanking sequences were given,"
                        "need exactly 2" % (marker, len(values)))
                for value in values:
                    if PAT_SEQ_RAW.match(value) is None:
                        raise ValueError(
                            "Flanking sequence '%s' of marker %s is invalid" %
                            (value, marker))
                library["flanks"][marker] = values
                markers.add(marker)
            elif section == "prefix":
                values = PAT_SPLIT.split(value)
                for value in values:
                    if PAT_SEQ_RAW.match(value) is None:
                        raise ValueError(
                            "Prefix sequence '%s' of marker %s is invalid" %
                            (value, marker))
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                library["prefix"][marker] = values
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                markers.add(marker)
            elif section == "suffix":
                values = PAT_SPLIT.split(value)
                for value in values:
                    if PAT_SEQ_RAW.match(value) is None:
                        raise ValueError(
                            "Suffix sequence '%s' of marker %s is invalid" %
                            (value, marker))
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                library["suffix"][marker] = values
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                markers.add(marker)
            elif section == "length_adjust":
                try:
                    value = int(value)
                except:
                    raise ValueError(
                        "Length adjustment '%s' of marker %s is not a valid "
                        "integer" % (value, marker))
                library["length_adjust"][marker] = value
                markers.add(marker)
            elif section == "block_length":
                try:
                    value = int(value)
                except:
                    raise ValueError(
                        "Block length '%s' of marker %s is not a valid integer"
                        % (value, marker))
                library["block_length"][marker] = value
                markers.add(marker)
            elif section == "aliases":
                values = PAT_SPLIT.split(value)
                if len(values) != 3:
                    raise ValueError("Alias %s does not have 3 values, but %i"
                                     % (marker, len(values)))
                if PAT_SEQ_RAW.match(values[1]) is None:
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                    raise ValueError(
                        "Alias sequence '%s' of alias %s is invalid" %
                        (values[1], marker))
                if PAT_ALIAS.match(values[2]) is None:
                    raise ValueError(
                        "Allele name '%s' of alias %s is invalid" %
                        (values[2], marker))
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                library["aliases"][marker] = {
                    "marker": values[0],
                    "sequence": values[1],
                    "name": values[2]
                }
                markers.add(marker)
            elif section == "repeat":
                if PAT_STR_DEF.match(value) is None:
                    raise ValueError(
                        "STR definition '%s' of marker %s is invalid" %
                        (value, marker))
                library["regex"][marker] = value
                markers.add(marker)

    # Compile regular expressions.
    # NOTE: The libconvert tool expects "(seq){num,num}" blocks ONLY!
    # TODO: Should a single prefix/suffix be required (i.e., seq{1,1})?
    #       Then also update libconvert when converting to TSSV format.
    for marker in markers:
        parts = []
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        partsm = []
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        if marker in library["prefix"]:
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            parts += ("(%s){0,1}" % x for x in library["prefix"][marker])
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        if marker in library["aliases"]:
            parts.append("(%s){0,1}" % library["aliases"][marker]["sequence"])
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            partsm.append("(%s){0,1}" % library["aliases"][marker]["sequence"])
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        elif marker in library["regex"]:
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            partsm = ("(%s){%s,%s}" % x for x in
                      PAT_STR_DEF_BLOCK.findall(library["regex"][marker]))
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            parts += partsm
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        if marker in library["suffix"]:
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            parts += ("(%s){0,1}" % x for x in library["suffix"][marker])
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        if parts:
            library["regex"][marker] = re.compile(
                "".join(["^"] + parts + ["$"]))
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        if partsm:
            library["regex_middle"][marker] = re.compile("".join(partsm))
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    return library
#parse_library_ini
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def load_profiles(profilefile, library=None):
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    if profilefile == sys.stdin:
        # Can't seek on pipes, so read it into a buffer first.
        profilefile = StringIO(sys.stdin.read())
    headline = profilefile.readline().rstrip("\r\n").split("\t")
    profilefile.seek(0)
    try:
        get_column_ids(headline, "marker", "allele", "sequence", "fmean",
            "rmean")
    except ValueError:
        try:
            int(headline[1])
        except:
            raise ValueError(
                "Invalid background noise profiles file: unable to determine "
                "file format!")
        return load_profiles_crosstab(profilefile, library)
    return load_profiles_columnar(profilefile, library)
#load_profiles


def load_profiles_columnar(profilefile, library=None):
    column_names = profilefile.readline().rstrip("\r\n").split("\t")
    colid_marker, colid_allele, colid_sequence, colid_fmean, colid_rmean = \
        get_column_ids(column_names, "marker", "allele", "sequence", "fmean",
            "rmean")

    profiles = {}
    for line in profilefile:
        line = line.rstrip("\r\n").split("\t")
        if line == [""]:
            continue
        marker = line[colid_marker]
        if marker not in profiles:
            profiles[marker] = {
                "m": set(),  # To be replaced by its length below.
                "n": set(),  # To be replaced by its length below.
                "seqs": [],
                "forward": {},  # To be replaced by a list below.
                "reverse": {}  # To be replaced by a list below.
                }
        allele = ensure_sequence_format(line[colid_allele], "raw",
            library=library, marker=marker)
        sequence = ensure_sequence_format(line[colid_sequence], "raw",
            library=library, marker=marker)
        if (allele, sequence) in profiles[marker]["forward"]:
            raise ValueError(
                "Invalid background noise profiles file: encountered "
                "multiple values for marker '%s' allele '%s' sequence '%s'" %
                (marker, allele, sequence))
        profiles[marker]["forward"][allele,sequence] = float(line[colid_fmean])
        profiles[marker]["reverse"][allele,sequence] = float(line[colid_rmean])
        profiles[marker]["m"].update((allele, sequence))
        profiles[marker]["n"].add(allele)

    # Check completeness and reorder true alleles.
    for marker in profiles:
        profiles[marker]["seqs"] = list(profiles[marker]["n"]) + \
            list(profiles[marker]["m"]-profiles[marker]["n"])
        profiles[marker]["n"] = len(profiles[marker]["n"])
        profiles[marker]["m"] = len(profiles[marker]["m"])
        newprofiles = {"forward": [], "reverse": []}
        for i in range(profiles[marker]["n"]):
            allele = profiles[marker]["seqs"][i]
            for direction in newprofiles:
                newprofiles[direction].append([0] * profiles[marker]["m"])
            for j in range(profiles[marker]["m"]):
                sequence = profiles[marker]["seqs"][j]
                if (allele, sequence) in profiles[marker]["forward"]:
                    for direction in newprofiles:
                        newprofiles[direction][i][j] = \
                            profiles[marker][direction][allele, sequence]
        profiles[marker]["forward"] = newprofiles["forward"]
        profiles[marker]["reverse"] = newprofiles["reverse"]

    return profiles
#load_profiles_columnar


def load_profiles_crosstab(profilefile, library=None):
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    profiles = {}

    # Read the profile file without assuming it is sorted.
    for line in profilefile:
        line = line.rstrip("\r\n").split("\t")
        if line == [""]:
            continue
        if len(line) < 3:
            raise ValueError(
                "Invalid background noise profiles file: encountered line "
                "with %i columns, need at least 3" % len(line))
        marker = line[0]
        try:
            num = int(line[1])
        except ValueError:
            raise ValueError(
                "Invalid background noise profiles file: encountered "
                "non-number '%s' in the second column" % line[1])
        values = line[2:]
        if marker not in profiles:
            profiles[marker] = {
                "m": len(values),
                "n": abs(num),
                "seqs": [],
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                "forward": {},  # To be replaced by a list below.
                "reverse": {}  # To be replaced by a list below.
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                }
        elif len(values) != profiles[marker]["m"]:
            raise ValueError(
                "Invalid background noise profiles file: profiles of "
                "marker '%s'% have inconsistent lengths" % marker)
        profiles[marker]["n"] = max(abs(num), profiles[marker]["n"])
        if num == 0:
            if profiles[marker]["seqs"]:
                raise ValueError(
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                    "Invalid background noise profiles file: encountered "
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                    "multiple header lines for marker '%s'" % marker)
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            values = [ensure_sequence_format(seq, "raw", library=library,
                        marker=marker) for seq in values]
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            profiles[marker]["seqs"] = values
        else:
            direction = "forward" if num > 0 else "reverse"
            if abs(num) in profiles[marker][direction]:
                raise ValueError(
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                    "Invalid background noise profiles file: encountered "
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                    "multiple %s profiles for marker '%s' allele %i" %
                    (direction, marker, abs(num)))
            values = map(float, values)
            profiles[marker][direction][abs(num)] = values

    # Check completeness and reorder true alleles.
    for marker in profiles:
        newprofiles = {"forward": [], "reverse": []}
        if not profiles[marker]["seqs"]:
            raise ValueError(
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                "Invalid background noise profiles file: missing header line "
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                "for marker '%s'" % marker)
        for i in range(1, profiles[marker]["n"] + 1):
            for direction in newprofiles:
                if i not in profiles[marker][direction]:
                    raise ValueError(
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                        "Invalid background noise profiles file: missing %s "
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                        "profile for marker '%s' allele %i" %
                        (direction, marker, i))
                newprofiles[direction].append(profiles[marker][direction][i])
        profiles[marker]["forward"] = newprofiles["forward"]
        profiles[marker]["reverse"] = newprofiles["reverse"]

    return profiles
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#load_profiles_crosstab
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def regex_longest_match(pattern, subject):
    """Return the longest match of the pattern in the subject string."""
    return reduce(lambda x, y:
        y if x is None or x.end()-x.start() < y.end()-y.start() else x,
        pattern.finditer(subject), None)
#regex_longest_match


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def detect_sequence_format(seq):
    """Return format of seq.  One of 'raw', 'tssv', or 'allelename'."""
    if not seq:
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        raise ValueError("Empty sequence")
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    if PAT_SEQ_RAW.match(seq):
        return 'raw'
    if PAT_SEQ_TSSV.match(seq):
        return 'tssv'
    if PAT_SEQ_ALLELENAME.match(seq):
        return 'allelename'
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    raise ValueError("Unrecognised sequence format")
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#detect_sequence_format


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def convert_sequence_tssv_raw(seq):
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    return "".join(block[0] * int(block[1])
                   for block in PAT_TSSV_BLOCK.findall(seq))
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#convert_sequence_tssv_raw


def convert_sequence_raw_tssv(seq, library, marker, return_alias=False):
    # Try to match this marker's pattern, or any of its aliases.
    match = None
    if "aliases" in library:
        for alias in library["aliases"]:
            if (library["aliases"][alias]["marker"] == marker and
                    alias in library["regex"]):
                match = library["regex"][alias].match(seq)
                if match is not None:
                    marker = alias
                    break
    if match is None and marker in library["regex"]:
        match = library["regex"][marker].match(seq)
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    if match is not None:
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        parts = ((match.group(i), match.end(i))
                 for i in range(1, match.lastindex+1) if match.group(i))
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    # Use heuristics if the sequence does not match the pattern.
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    else:
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        # Find explictily provided prefix and/or suffix if present.
        pre_suf = ["", ""]
        if "prefix" in library and marker in library["prefix"]:
            for prefix in library["prefix"][marker]:
                if seq.startswith(prefix):
                    pre_suf[0] = prefix
                    seq = seq[len(prefix):]
                    break
        if "suffix" in library and marker in library["suffix"]:
            for suffix in library["suffix"][marker]:
                if seq.endswith(suffix):
                    pre_suf[1] = suffix
                    seq = seq[:-len(suffix)]
                    break

        # Find longest match of middle pattern.
        middle = [(seq, len(pre_suf[0])+len(seq))]
        if marker in library["regex_middle"]:
            match = regex_longest_match(library["regex_middle"][marker], seq)
            if match is not None and match.end()-match.start():
                # TODO: If I did not have a prefix yet, but the
                # canonical prefix ends with the first few blocks that
                # we obtained in the match, move these blocks into the
                # prefix.  Also do this with the suffix.
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                middle = ((match.group(i), match.end(i)+len(pre_suf[0]))
                    for i in range(1, match.lastindex+1) if match.group(i))
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                pre_suf[0] += seq[:match.start()]
                pre_suf[1] = seq[match.end():] + pre_suf[1]
                seq = match.group()

        # Now construct parts.
        parts = []
        if pre_suf[0]:
            parts.append((pre_suf[0], len(pre_suf[0])))
        parts += middle
        if pre_suf[1]:
            parts.append((pre_suf[1], sum(map(len,pre_suf))+len(seq)))

    seq = reduce(
        lambda a, b: (a[0] + "%s(%i)" % (b[0], (b[1]-a[1])/len(b[0])), b[1]),
        reduce(
            lambda x, y: x[:-1] + [y] if x[-1][0] == y[0] else x + [y],
            parts,
            [("", 0)]))[0]
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    return (seq, marker) if return_alias else seq
#convert_sequence_raw_tssv


def convert_sequence_allelename_tssv(seq, library, marker):
    # Check whether there is an alias for this sequence.
    if "aliases" in library:
        for alias in library["aliases"]:
            if library["aliases"][alias]["marker"] == marker and (
                    seq == library["aliases"][alias]["name"] or
                    seq.startswith(library["aliases"][alias]["name"] + "_")):
                marker = alias
                seq = "".join([
                    "0_",
                    library["aliases"][alias]["sequence"] + "[1]",
                    seq[len(library["aliases"][alias]["name"]):]])
                break

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    # It should NOT be an alias now.
    match = PAT_SEQ_ALLELENAME.match(seq)
    if match is None or match.group(1) is not None:
        raise ValueError("Invalid allele name '%s' encountered!" % seq)

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    allele = seq.split("_")

    # Get and mutate prefix and suffix.
    if "prefix" in library and marker in library["prefix"]:
        prefix = library["prefix"][marker][0]
    else:
        prefix = ""
    if "suffix" in library and marker in library["suffix"]:
        suffix = library["suffix"][marker][0]
    else:
        suffix = ""
    variants = [[], []]
    for variant in allele[2:]:
        if variant[0] == "-":
            if not prefix:
                raise ValueError("Encountered prefix variant '%s', but marker "
                                 "'%s' has no prefix!" % (variant, marker))
            variants[0].append(variant)
        elif variant[0] == "+":
            if not suffix:
                raise ValueError("Encountered suffix variant '%s', but marker "
                                 "'%s' has no suffix!" % (variant, marker))
            variants[1].append(variant)
        else:
            raise ValueError("Unrecognised variant '%s'" % variant)
    if variants[0]:
        prefix = mutate_sequence(prefix, variants[0])
    if variants[1]:
        suffix = mutate_sequence(suffix, variants[1])

    blocks = []
    if prefix:
        blocks.append((prefix, 1))
    for block in PAT_ALLELENAME_BLOCK.findall(allele[1]):
        blocks.append((block[0], int(block[1])))
    if suffix:
        blocks.append((suffix, 1))
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    return "".join("%s(%i)" % block for block in blocks)
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#convert_sequence_allelename_tssv


def convert_sequence_raw_allelename(seq, library, marker):
    # We actually convert raw->allelename via TSSV format.
    seq, alias = convert_sequence_raw_tssv(seq, library, marker, True)
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    blocks = PAT_TSSV_BLOCK.findall(seq)

    # Find prefix and suffix.
    prefix = suffix = this_prefix = this_suffix = ""
    remaining_blocks = len(blocks)
    if "prefix" in library and marker in library["prefix"]:
        prefix = library["prefix"][marker][0]
        remaining_blocks -= 1
    if "suffix" in library and marker in library["suffix"]:
        suffix = library["suffix"][marker][0]
        remaining_blocks -= 1
    if remaining_blocks > 0 and prefix and blocks[0][1] == "1":
        this_prefix = blocks[0][0]
        blocks = blocks[1:]
    if remaining_blocks > 0 and suffix and blocks[-1][1] == "1":
        this_suffix = blocks[-1][0]
        blocks = blocks[:-1]
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    # Generate prefix/suffix variants.
    length = 0
    variants = []
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    if prefix != this_prefix:
        variants += call_variants(prefix, this_prefix, True)
        length += len(this_prefix) - len(prefix)
    if suffix != this_suffix:
        variants += call_variants(suffix, this_suffix, False)
        length += len(this_suffix) - len(suffix)
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    # We are ready to return the allele name of aliases.
    if alias != marker:
        return "_".join([library["aliases"][marker]["name"]] + variants)

    # Compute CE allele number for the other alleles.
    # TODO: perhaps produce a more intelligent name if there is exactly
    #       one alias with the same length
    blocknames = []
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    blocksize = library.get("block_length", {}).get(marker, 4)
    length -= library.get("length_adjust", {}).get(marker, 0)
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    for block in blocks:
        blocknames.append("%s[%s]" % (block[0], block[1]))
        length += len(block[0]) * int(block[1])

    allelename = "CE" + str(length / blocksize)
    if length % blocksize:
        allelename += "." + str(length % blocksize)
    return "_".join([allelename, "".join(blocknames)] + variants)
#convert_sequence_raw_allelename


def ensure_sequence_format(seq, to_format, from_format=None, library=None,
                           marker=None):
    """Convert seq to 'raw', 'tssv', or 'allelename' format."""
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    known_formats = ("raw", "tssv", "allelename")
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    if to_format not in known_formats:
        raise ValueError("Unknown format '%s', choose from %s" %
                         (to_format, known_formats))
    if from_format is None:
        from_format = detect_sequence_format(seq) if seq else "raw"
    elif from_format not in known_formats:
        raise ValueError("Unknown format '%s', choose from %s" %
                         (from_format, known_formats))

    # No conversion needed?
    if to_format == from_format:
        return seq

    # From TSSV to raw sequence is easy.
    # We'll need a library and marker name for anything else.
    if (library is None or marker is None) and (from_format != "tssv" or
            to_format != "raw"):
        raise ValueError("Sequence needs to be converted from %s to %s, this "
                          "conversion requires a library file" %
                          (from_format, to_format))

    # Perform conversions.
    if from_format == "allelename":
        seq = convert_sequence_allelename_tssv(seq, library, marker)
    if to_format == "tssv":
        if from_format == "raw":
            return convert_sequence_raw_tssv(seq, library, marker)
        return seq
    if from_format != "raw":
        seq = convert_sequence_tssv_raw(seq)
    if to_format == "raw":
        return seq
    return convert_sequence_raw_allelename(seq, library, marker)
#ensure_sequence_format


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def reverse_complement(sequence):
    """Return the reverse complement of the given DNA sequence."""
    c = {"A": "T", "T": "A", "U": "A", "G": "C", "C": "G", "R": "Y", "Y": "R",
         "K": "M", "M": "K", "B": "V", "V": "B", "D": "H", "H": "D",
         "a": "t", "t": "a", "u": "a", "g": "c", "c": "g", "r": "y", "y": "r",
         "k": "m", "m": "k", "b": "v", "v": "b", "d": "h", "h": "d"}
    return "".join(c[x] if x in c else x for x in sequence[::-1])
#reverse_complement


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def nnls(A, C, B=None, max_iter=200, min_change=0.0001, debug=False):
    """
    Solve for B in A * B = C in the least squares sense, s.t. B >= 0.

    Hint: call nnls(B.T, C.T).T to solve for A.

    Algorithm has converged if the sum of squared error has decreased
    by less than a factor of min_change in one iteration.  If debug is
    True, print the sum of squared error to sys.stdout after each
    iteration.

    This code was partially adopted from nimfa.methods.factorization.bd.
    """
    import numpy as np
    if B is None:
        B = np.matrix(np.zeros([A.shape[1], C.shape[1]]))
    E = A.T * A
    F = A.T * C
    prev_score = cur_score = sys.float_info.max
    for i in range(max_iter):
        for n in range(B.shape[0]):
            nn = list(range(n)) + list(range(n + 1, B.shape[0]))
            tmp = (F[n, :] - E[n, nn] * B[nn, :]) / E[n, n]
            tmp[np.isnan(tmp)] = 0
            tmp[tmp < 0] = 0
            B[n, :] = tmp
        prev_score = cur_score
        cur_score = np.square(C - A * B).sum()
        score_change = (prev_score-cur_score)/prev_score

        if debug:
            if i:
                print("%4i %15.6f %15.6f %6.2f" % (i, cur_score,
                    prev_score-cur_score, 100*score_change))
            else:
                print("%4i %15.6f" % (i, cur_score))

        if not cur_score or score_change < min_change:
            # We have converged.
            break

    return B
#nnls


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def adjust_stats(value, stats=None):
    """
    Adjust the given stats in place with the given observed value and
    return the adjusted stats as well.  If no stats dict is given,
    create a new stats dict with the following initial values:
    {"n": 1, "min": value, "max": value, "mean": value, "m2": 0.0,
     "variance": 0.0}
    """
    value += 0.0
    if not stats:
        return {"n": 1, "min": value, "max": value, "mean": value, "m2": 0.0,
                "variance": 0.0}
    stats["n"] += 1
    delta = value - stats["mean"]
    stats["mean"] += delta / stats["n"]
    stats["m2"] += delta * (value - stats["mean"])
    try:
        stats["variance"] = stats["m2"] / (stats["n"] - 1)
        stats["min"] = min(stats["min"], value)
        stats["max"] = max(stats["max"], value)
    except ZeroDivisionError:
        stats["variance"] = 0
        stats["min"] = value
        stats["max"] = value
    return stats
#adjust_stats


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def read_sample_data_file(infile, data, annotation_column=None, seqformat=None,
                          library=None, default_marker=None):
    """Add data from infile to data dict as [marker, allele]=reads."""
    # Get column numbers.
    column_names = infile.readline().rstrip("\r\n").split("\t")
    colid_allele, colid_forward, colid_reverse = \
        get_column_ids(column_names, "allele", "forward", "reverse")

    # Get marker name column if it exists.
    try:
        colid_name = get_column_ids(column_names, "name")
    except:
        colid_name = None

    # Also try to get annotation column if we have one.
    if annotation_column is not None:
        try:
            colid_annotation = get_column_ids(column_names, annotation_column)
        except:
            annotation_column = None

    found_alleles = []
    for line in infile:
        line = line.rstrip("\r\n").split("\t")
        marker = line[colid_name] if colid_name is not None else default_marker
        allele = line[colid_allele] if seqformat is None \
            else ensure_sequence_format(line[colid_allele], seqformat, library)
        if (annotation_column is not None and
                line[colid_annotation].startswith("ALLELE")):
            found_alleles.append(marker, allele)
        data[marker, allele] = map(int,
            (line[colid_forward], line[colid_reverse]))

    return found_alleles
#read_sample_data_file


def reduce_read_counts(data, limit_reads):
    sum_reads = 0
    for markerallele in data:
        sum_reads += sum(data[markerallele])
    if sum_reads <= limit_reads:
        return

    remove = sorted(random.sample(xrange(sum_reads), sum_reads - limit_reads))
    i = 0
    seen = 0
    while i < len(remove) and seen > remove[i]:
        # Skip the reads filtered out above.
        i += 1
    for markerallele in data:
        for direction in (0, 1):
            seen += data[markerallele][direction]
            while i < len(remove) and seen > remove[i]:
                data[markerallele][direction] -= 1
                i += 1
#reduce_read_counts


def get_sample_data(tags_to_files, callback, allelelist=None,
                    annotation_column=None, seqformat=None, library=None,
                    marker=None, homozygotes=False, limit_reads=sys.maxint,
                    drop_samples=0):
    if drop_samples:
        sample_tags = tags_to_files.keys()
        for tag in random.sample(xrange(len(sample_tags)),
                                 int(len(sample_tags) * drop_samples)):
            del tags_to_files[sample_tags[tag]]

    for tag in tags_to_files:
        data = {}
        alleles = set()
        for infile in tags_to_files[tag]:
            alleles.update(read_sample_data_file(infile, data,
                annotation_column, seqformat, library, marker))
        if limit_reads < sys.maxint:
            reduce_read_counts(data, limit_reads)
        if allelelist is not None:
            if tag not in allelelist:
                allelelist[tag] = {}
            for markerx, allele in alleles:
                if markerx not in allelelist[tag]:
                    allelelist[tag][markerx] = set()
                allelelist[tag][markerx].add(allele)
            if marker:
                if marker in allelelist[tag]:
                    allelelist[tag] = {marker: allelelist[tag][marker]}
                else:
                    allelelist[tag] = {}
            if homozygotes:
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                for markerx in allelelist[tag].keys():
                    if len(allelelist[tag][markerx]) > 1:
                        del allelelist[tag][markerx]
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        callback(tag, data)
#get_sample_data


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def get_column_ids(column_names, *names):
    """Find all names in column_names and return their indices."""
    result = []
    for name in names:
        try:
            result.append(column_names.index(name))
        except ValueError:
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            raise ValueError("Column not found in input file: %s" % name)
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    if len(result) == 1:
        return result[0]
    return tuple(result)
#get_column_ids


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def parse_allelelist(allelelist, convert=None, library=None):
    """Read allele list from open file handle."""
    column_names = allelelist.readline().rstrip("\r\n").split("\t")
    colid_sample, colid_marker, colid_allele = get_column_ids(column_names,
        "sample", "marker", "allele")
    alleles = {}
    for line in allelelist:
        line = line.rstrip("\r\n").split("\t")
        sample = line[colid_sample]
        marker = line[colid_marker]
        allele = line[colid_allele]
        if convert is not None:
            allele = ensure_sequence_format(allele, convert, library=library,
                                            marker=marker)
        if sample not in alleles:
            alleles[sample] = {}
        if marker not in alleles[sample]:
            alleles[sample][marker] = set()
        alleles[sample][marker].add(allele)
    return alleles
#parse_allelelist


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def pos_int_arg(value):
    """Convert str to int, raise ArgumentTypeError if not positive."""
    if not value.isdigit() or not int(value):
        raise argparse.ArgumentTypeError(
            "invalid positive int value: '%s'" % value)
    return int(value)
#pos_int_arg


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def add_allele_detection_args(parser):
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    group = parser.add_argument_group("allele detection options")
    group.add_argument('-a', '--allelelist', metavar="ALLELEFILE",
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        type=argparse.FileType('r'),
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        help="file containing a list of the true alleles of each sample "
             "(e.g., obtained from allelefinder)")
    group.add_argument('-c', '--annotation-column', metavar="COLNAME",
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        help="name of a column in the sample files, which contains a value "
             "beginning with 'ALLELE' for the true alleles of the sample")
#add_allele_detection_args


def add_sample_files_args(parser):
    """Add arguments for opening sample files to the given parser."""
    parser.add_argument('filelist', nargs='*', metavar="FILE",
        default=[sys.stdin], type=argparse.FileType('r'),
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        help="the sample data file(s) to process (default: read from stdin)")
    group = parser.add_argument_group("sample tag parsing options")
    group.add_argument('-e', '--tag-expr', metavar="REGEX", type=re.compile,
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        default=DEF_TAG_EXPR,
        help="regular expression that captures (using one or more capturing "
             "groups) the sample tags from the file names; by default, the "
             "entire file name except for its extension (if any) is captured")
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    group.add_argument('-f', '--tag-format', metavar="EXPR",
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        default=DEF_TAG_FORMAT,
        help="format of the sample tags produced; a capturing group reference "
             "like '\\n' refers to the n-th capturing group in the regular "
             "expression specified with -e/--tag-expr (the default of '\\1' "
             "simply uses the first capturing group); with a single sample, "
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             "you can enter the sample tag here explicitly")
#add_sample_files_args


def add_output_args(parser, report=True):
    group = parser.add_argument_group("output destination options")
    group.add_argument('-o', '--output', metavar="FILE",
        type=argparse.FileType('w'),
        default=sys.stdout,
        help="file to write output to (default: write to stdout)")
    if report:
        group.add_argument('-r', '--report', metavar="FILE",
            type=argparse.FileType('w'),
            default=sys.stderr,
            help="file to write a report to (default: write to stderr)")
#add_output_args


def add_sequence_format_args(parser, default_format=None, force=False):
    group = parser.add_argument_group("sequence format options")
    if force:
        group.set_defaults(sequence_format=default_format)
    else:
        group.add_argument('-F', '--sequence-format', metavar="FORMAT",
            choices=("raw", "tssv", "allelename"),
            default=default_format,
            help="convert sequences to the specified format: one of "
                 "%(choices)s (default: " + (
                 "no conversion" if default_format is None else default_format)
                 + ")")
    group.add_argument('-l', '--library', metavar="LIBRARY",
        type=argparse.FileType('r'),
        help="library file for sequence format conversion")
#add_sequence_format_args


def add_random_subsampling_args(parser):
    group = parser.add_argument_group("random subsampling options (advanced)")
    group.add_argument('-R', '--limit-reads', metavar="N", type=pos_int_arg,
        default=sys.maxint,
        help="simulate lower sequencing depth by randomly dropping reads down "
             "to this maximum total number of reads for each sample")
    group.add_argument('-x', '--drop-samples', metavar="N", type=float,
        default=0, help="randomly drop this fraction of input samples")
#add_random_subsampling_args
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def get_tag(filename, tag_expr, tag_format):
    """Return formatted sample tag from filename using regex."""
    try:
        return tag_expr.search(filename).expand(tag_format)
    except:
        return filename
#get_tag


def map_tags_to_files(filelist, tag_expr, tag_format):
    tags_to_files = {}
    for infile in filelist:
        tag = get_tag(infile.name, tag_expr, tag_format)
        if tag not in tags_to_files:
            tags_to_files[tag] = [infile]
        else:
            tags_to_files[tag].append(infile)
    return tags_to_files
#map_tags_to_files


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def print_db(text, debug):
    """Print text if debug is True."""
    if debug:
        print(text)
#print_db