#!/usr/bin/env python
# Created: Wed May 29 08:07:18 2002
# thomas@cbs.dtu.dk, Cecilia.Alsmark@ebc.uu.se
# Copyright 2001 by Thomas Sicheritz-Ponten and Cecilia Alsmark.
# Revisions copyright 2014 by Markus Piotrowski.
# Revisions copyright 2014-2016 by Peter Cock.
# All rights reserved.
# This code is part of the Biopython distribution and governed by its
# license.  Please see the LICENSE file that should have been included
# as part of this package.

"""Miscellaneous functions for dealing with sequences."""

from __future__ import print_function

import re
from math import pi, sin, cos

from Bio.Seq import Seq, MutableSeq
from Bio import Alphabet
from Bio.Data import IUPACData


######################################
# DNA
######################
# {{{


def GC(seq):
    """Calculates G+C content, returns the percentage (float between 0 and 100).

    Copes mixed case sequences, and with the ambiguous nucleotide S (G or C)
    when counting the G and C content.  The percentage is calculated against
    the full length, e.g.:

    >>> from Bio.SeqUtils import GC
    >>> GC("ACTGN")
    40.0

    Note that this will return zero for an empty sequence.
    """
    gc = sum(seq.count(x) for x in ['G', 'C', 'g', 'c', 'S', 's'])
    try:
        return gc * 100.0 / len(seq)
    except ZeroDivisionError:
        return 0.0


def GC123(seq):
    """Calculates total G+C content plus first, second and third positions.

    Returns a tuple of four floats (percentages between 0 and 100) for the
    entire sequence, and the three codon positions.  e.g.

    >>> from Bio.SeqUtils import GC123
    >>> GC123("ACTGTN")
    (40.0, 50.0, 50.0, 0.0)

    Copes with mixed case sequences, but does NOT deal with ambiguous
    nucleotides.
    """
    d = {}
    for nt in ['A', 'T', 'G', 'C']:
        d[nt] = [0, 0, 0]

    for i in range(0, len(seq), 3):
        codon = seq[i:i + 3]
        if len(codon) < 3:
            codon += '  '
        for pos in range(0, 3):
            for nt in ['A', 'T', 'G', 'C']:
                if codon[pos] == nt or codon[pos] == nt.lower():
                    d[nt][pos] += 1
    gc = {}
    gcall = 0
    nall = 0
    for i in range(0, 3):
        try:
            n = d['G'][i] + d['C'][i] + d['T'][i] + d['A'][i]
            gc[i] = (d['G'][i] + d['C'][i]) * 100.0 / n
        except Exception:  # TODO - ValueError?
            gc[i] = 0

        gcall = gcall + d['G'][i] + d['C'][i]
        nall = nall + n

    gcall = 100.0 * gcall / nall
    return gcall, gc[0], gc[1], gc[2]


def GC_skew(seq, window=100):
    """Calculates GC skew (G-C)/(G+C) for multiple windows along the sequence.

    Returns a list of ratios (floats), controlled by the length of the sequence
    and the size of the window.

    Does NOT look at any ambiguous nucleotides.
    """
    # 8/19/03: Iddo: added lowercase
    values = []
    for i in range(0, len(seq), window):
        s = seq[i: i + window]
        g = s.count('G') + s.count('g')
        c = s.count('C') + s.count('c')
        skew = (g - c) / float(g + c)
        values.append(skew)
    return values


def xGC_skew(seq, window=1000, zoom=100,
                         r=300, px=100, py=100):
    """Calculates and plots normal and accumulated GC skew (GRAPHICS !!!)."""
    try:
        import Tkinter as tkinter  # Python 2
    except ImportError:
        import tkinter  # Python 3

    yscroll = tkinter.Scrollbar(orient=tkinter.VERTICAL)
    xscroll = tkinter.Scrollbar(orient=tkinter.HORIZONTAL)
    canvas = tkinter.Canvas(yscrollcommand=yscroll.set,
                            xscrollcommand=xscroll.set, background='white')
    win = canvas.winfo_toplevel()
    win.geometry('700x700')

    yscroll.config(command=canvas.yview)
    xscroll.config(command=canvas.xview)
    yscroll.pack(side=tkinter.RIGHT, fill=tkinter.Y)
    xscroll.pack(side=tkinter.BOTTOM, fill=tkinter.X)
    canvas.pack(fill=tkinter.BOTH, side=tkinter.LEFT, expand=1)
    canvas.update()

    X0, Y0 = r + px, r + py
    x1, x2, y1, y2 = X0 - r, X0 + r, Y0 - r, Y0 + r

    ty = Y0
    canvas.create_text(X0, ty, text='%s...%s (%d nt)' % (seq[:7], seq[-7:], len(seq)))
    ty += 20
    canvas.create_text(X0, ty, text='GC %3.2f%%' % (GC(seq)))
    ty += 20
    canvas.create_text(X0, ty, text='GC Skew', fill='blue')
    ty += 20
    canvas.create_text(X0, ty, text='Accumulated GC Skew', fill='magenta')
    ty += 20
    canvas.create_oval(x1, y1, x2, y2)

    acc = 0
    start = 0
    for gc in GC_skew(seq, window):
        r1 = r
        acc += gc
        # GC skew
        alpha = pi - (2 * pi * start) / len(seq)
        r2 = r1 - gc * zoom
        x1 = X0 + r1 * sin(alpha)
        y1 = Y0 + r1 * cos(alpha)
        x2 = X0 + r2 * sin(alpha)
        y2 = Y0 + r2 * cos(alpha)
        canvas.create_line(x1, y1, x2, y2, fill='blue')
        # accumulated GC skew
        r1 = r - 50
        r2 = r1 - acc
        x1 = X0 + r1 * sin(alpha)
        y1 = Y0 + r1 * cos(alpha)
        x2 = X0 + r2 * sin(alpha)
        y2 = Y0 + r2 * cos(alpha)
        canvas.create_line(x1, y1, x2, y2, fill='magenta')

        canvas.update()
        start += window

    canvas.configure(scrollregion=canvas.bbox(tkinter.ALL))


def nt_search(seq, subseq):
    """Search for a DNA subseq in sequence.

    use ambiguous values (like N = A or T or C or G, R = A or G etc.)
    searches only on forward strand
    """
    pattern = ''
    for nt in subseq:
        value = IUPACData.ambiguous_dna_values[nt]
        if len(value) == 1:
            pattern += value
        else:
            pattern += '[%s]' % value

    pos = -1
    result = [pattern]
    l = len(seq)
    while True:
        pos += 1
        s = seq[pos:]
        m = re.search(pattern, s)
        if not m:
            break
        pos += int(m.start(0))
        result.append(pos)
    return result

# }}}

######################################
# Protein
######################
# {{{


def seq3(seq, custom_map=None, undef_code='Xaa'):
    """Turn a one letter code protein sequence into one with three letter codes.

    The single required input argument 'seq' should be a protein sequence using
    single letter codes, either as a python string or as a Seq or MutableSeq
    object.

    This function returns the amino acid sequence as a string using the three
    letter amino acid codes. Output follows the IUPAC standard (including
    ambiguous characters B for "Asx", J for "Xle" and X for "Xaa", and also U
    for "Sel" and O for "Pyl") plus "Ter" for a terminator given as an asterisk.
    Any unknown character (including possible gap characters), is changed into
    'Xaa' by default.

    e.g.

    >>> from Bio.SeqUtils import seq3
    >>> seq3("MAIVMGRWKGAR*")
    'MetAlaIleValMetGlyArgTrpLysGlyAlaArgTer'

    You can set a custom translation of the codon termination code using the
    dictionary "custom_map" argument (which defaults to {'*': 'Ter'}), e.g.

    >>> seq3("MAIVMGRWKGAR*", custom_map={"*": "***"})
    'MetAlaIleValMetGlyArgTrpLysGlyAlaArg***'

    You can also set a custom translation for non-amino acid characters, such
    as '-', using the "undef_code" argument, e.g.

    >>> seq3("MAIVMGRWKGA--R*", undef_code='---')
    'MetAlaIleValMetGlyArgTrpLysGlyAla------ArgTer'

    If not given, "undef_code" defaults to "Xaa", e.g.

    >>> seq3("MAIVMGRWKGA--R*")
    'MetAlaIleValMetGlyArgTrpLysGlyAlaXaaXaaArgTer'

    This function was inspired by BioPerl's seq3.
    """
    if custom_map is None:
        custom_map = {'*': 'Ter'}
    # not doing .update() on IUPACData dict with custom_map dict
    # to preserve its initial state (may be imported in other modules)
    threecode = dict(list(IUPACData.protein_letters_1to3_extended.items()) +
                     list(custom_map.items()))
    # We use a default of 'Xaa' for undefined letters
    # Note this will map '-' to 'Xaa' which may be undesirable!
    return ''.join(threecode.get(aa, undef_code) for aa in seq)


def seq1(seq, custom_map=None, undef_code='X'):
    """Turns a three-letter code protein sequence into one with single letter codes.

    The single required input argument 'seq' should be a protein sequence
    using three-letter codes, either as a python string or as a Seq or
    MutableSeq object.

    This function returns the amino acid sequence as a string using the one
    letter amino acid codes. Output follows the IUPAC standard (including
    ambiguous characters "B" for "Asx", "J" for "Xle", "X" for "Xaa", "U" for
    "Sel", and "O" for "Pyl") plus "*" for a terminator given the "Ter" code.
    Any unknown character (including possible gap characters), is changed
    into '-' by default.

    e.g.

    >>> from Bio.SeqUtils import seq3
    >>> seq1("MetAlaIleValMetGlyArgTrpLysGlyAlaArgTer")
    'MAIVMGRWKGAR*'

    The input is case insensitive, e.g.

    >>> from Bio.SeqUtils import seq3
    >>> seq1("METalaIlEValMetGLYArgtRplysGlyAlaARGTer")
    'MAIVMGRWKGAR*'

    You can set a custom translation of the codon termination code using the
    dictionary "custom_map" argument (defaulting to {'Ter': '*'}), e.g.

    >>> seq1("MetAlaIleValMetGlyArgTrpLysGlyAlaArg***", custom_map={"***": "*"})
    'MAIVMGRWKGAR*'

    You can also set a custom translation for non-amino acid characters, such
    as '-', using the "undef_code" argument, e.g.

    >>> seq1("MetAlaIleValMetGlyArgTrpLysGlyAla------ArgTer", undef_code='?')
    'MAIVMGRWKGA??R*'

    If not given, "undef_code" defaults to "X", e.g.

    >>> seq1("MetAlaIleValMetGlyArgTrpLysGlyAla------ArgTer")
    'MAIVMGRWKGAXXR*'

    """
    if custom_map is None:
        custom_map = {'Ter': '*'}
    # reverse map of threecode
    # upper() on all keys to enable caps-insensitive input seq handling
    onecode = dict((k.upper(), v) for k, v in
                   IUPACData.protein_letters_3to1_extended.items())
    # add the given termination codon code and custom maps
    onecode.update((k.upper(), v) for (k, v) in custom_map.items())
    seqlist = [seq[3 * i:3 * (i + 1)] for i in range(len(seq) // 3)]
    return ''.join(onecode.get(aa.upper(), undef_code) for aa in seqlist)


# }}}

######################################
# Mixed ???
######################
# {{{


def molecular_weight(seq, seq_type=None, double_stranded=False, circular=False,
                     monoisotopic=False):
    """Calculates the molecular weight of a DNA, RNA or protein sequence.

    Only unambiguous letters are allowed. Nucleotide sequences are assumed to
    have a 5' phosphate.

        - seq: String or Biopython sequence object.
        - seq_type: The default (None) is to take the alphabet from the seq argument,
          or assume DNA if the seq argument is a string. Override this with
          a string 'DNA', 'RNA', or 'protein'.
        - double_stranded: Calculate the mass for the double stranded molecule?
        - circular: Is the molecule circular (has no ends)?
        - monoisotopic: Use the monoisotopic mass tables?

    Note that for backwards compatibility, if the seq argument is a string,
    or Seq object with a generic alphabet, and no seq_type is specified
    (i.e. left as None), then DNA is assumed.

    >>> print("%0.2f" % molecular_weight("AGC"))
    949.61
    >>> print("%0.2f" % molecular_weight(Seq("AGC")))
    949.61

    However, it is better to be explicit - for example with strings:

    >>> print("%0.2f" % molecular_weight("AGC", "DNA"))
    949.61
    >>> print("%0.2f" % molecular_weight("AGC", "RNA"))
    997.61
    >>> print("%0.2f" % molecular_weight("AGC", "protein"))
    249.29

    Or, with the sequence alphabet:

    >>> from Bio.Seq import Seq
    >>> from Bio.Alphabet import generic_dna, generic_rna, generic_protein
    >>> print("%0.2f" % molecular_weight(Seq("AGC", generic_dna)))
    949.61
    >>> print("%0.2f" % molecular_weight(Seq("AGC", generic_rna)))
    997.61
    >>> print("%0.2f" % molecular_weight(Seq("AGC", generic_protein)))
    249.29

    Also note that contradictory sequence alphabets and seq_type will also
    give an exception:

    >>> from Bio.Seq import Seq
    >>> from Bio.Alphabet import generic_dna
    >>> print("%0.2f" % molecular_weight(Seq("AGC", generic_dna), "RNA"))
    Traceback (most recent call last):
      ...
    ValueError: seq_type='RNA' contradicts DNA from seq alphabet

    """
    # Rewritten by Markus Piotrowski, 2014

    # Find the alphabet type
    tmp_type = ''
    if isinstance(seq, (Seq, MutableSeq)):
        base_alphabet = Alphabet._get_base_alphabet(seq.alphabet)
        if isinstance(base_alphabet, Alphabet.DNAAlphabet):
            tmp_type = 'DNA'
        elif isinstance(base_alphabet, Alphabet.RNAAlphabet):
            tmp_type = 'RNA'
        elif isinstance(base_alphabet, Alphabet.ProteinAlphabet):
            tmp_type = 'protein'
        elif isinstance(base_alphabet, Alphabet.ThreeLetterProtein):
            tmp_type = 'protein'
            # Convert to one-letter sequence. Have to use a string for seq1
            seq = Seq(seq1(str(seq)), alphabet=Alphabet.ProteinAlphabet())
        elif not isinstance(base_alphabet, Alphabet.Alphabet):
            raise TypeError("%s is not a valid alphabet for mass calculations"
                             % base_alphabet)
        else:
            tmp_type = "DNA"  # backward compatibity
        if seq_type and tmp_type and tmp_type != seq_type:
            raise ValueError("seq_type=%r contradicts %s from seq alphabet"
                             % (seq_type, tmp_type))
        seq_type = tmp_type
    elif isinstance(seq, str):
        if seq_type is None:
            seq_type = "DNA"  # backward compatibity
    else:
        raise TypeError("Expected a string or Seq object, not seq=%r" % seq)

    seq = ''.join(str(seq).split()).upper()  # Do the minimum formatting

    if seq_type == 'DNA':
        if monoisotopic:
            weight_table = IUPACData.monoisotopic_unambiguous_dna_weights
        else:
            weight_table = IUPACData.unambiguous_dna_weights
    elif seq_type == 'RNA':
        if monoisotopic:
            weight_table = IUPACData.monoisotopic_unambiguous_rna_weights
        else:
            weight_table = IUPACData.unambiguous_rna_weights
    elif seq_type == 'protein':
        if monoisotopic:
            weight_table = IUPACData.monoisotopic_protein_weights
        else:
            weight_table = IUPACData.protein_weights
    else:
        raise ValueError("Allowed seq_types are DNA, RNA or protein, not %r"
                         % seq_type)

    if monoisotopic:
        water = 18.010565
    else:
        water = 18.0153

    try:
        weight = sum(weight_table[x] for x in seq) - (len(seq) - 1) * water
        if circular:
            weight -= water
    except KeyError as e:
        raise ValueError('%s is not a valid unambiguous letter for %s'
                         % (e, seq_type))
    except:
        raise

    if seq_type in ('DNA', 'RNA') and double_stranded:
        seq = str(Seq(seq).complement())
        weight += sum(weight_table[x] for x in seq) - (len(seq) - 1) * water
        if circular:
            weight -= water
    elif seq_type == 'protein' and double_stranded:
        raise ValueError('double-stranded proteins await their discovery')

    return weight


def six_frame_translations(seq, genetic_code=1):
    """Formatted string showing the 6 frame translations and GC content.

    nice looking 6 frame translation with GC content - code from xbbtools
    similar to DNA Striders six-frame translation

    >>> from Bio.SeqUtils import six_frame_translations
    >>> print(six_frame_translations("AUGGCCAUUGUAAUGGGCCGCUGA"))
    GC_Frame: a:5 t:0 g:8 c:5 
    Sequence: auggccauug ... gggccgcuga, 24 nt, 54.17 %GC
    <BLANKLINE>
    <BLANKLINE>
    1/1
      G  H  C  N  G  P  L
     W  P  L  *  W  A  A
    M  A  I  V  M  G  R  *
    auggccauuguaaugggccgcuga   54 %
    uaccgguaacauuacccggcgacu
    A  M  T  I  P  R  Q 
     H  G  N  Y  H  A  A  S
      P  W  Q  L  P  G  S
    <BLANKLINE>
    <BLANKLINE>

    """  # noqa for pep8 W291 trailing whitespace
    from Bio.Seq import reverse_complement, translate
    anti = reverse_complement(seq)
    comp = anti[::-1]
    length = len(seq)
    frames = {}
    for i in range(0, 3):
        fragment_length = 3 * ((length - i) // 3)
        frames[i + 1] = translate(seq[i:i + fragment_length], genetic_code)
        frames[-(i + 1)] = translate(anti[i:i + fragment_length], genetic_code)[::-1]

    # create header
    if length > 20:
        short = '%s ... %s' % (seq[:10], seq[-10:])
    else:
        short = seq
    header = 'GC_Frame: '
    for nt in ['a', 't', 'g', 'c']:
        header += '%s:%d ' % (nt, seq.count(nt.upper()))

    header += '\nSequence: %s, %d nt, %0.2f %%GC\n\n\n' % (short.lower(), length, GC(seq))
    res = header

    for i in range(0, length, 60):
        subseq = seq[i:i + 60]
        csubseq = comp[i:i + 60]
        p = i // 3
        res += '%d/%d\n' % (i + 1, i / 3 + 1)
        res += '  ' + '  '.join(frames[3][p:p + 20]) + '\n'
        res += ' ' + '  '.join(frames[2][p:p + 20]) + '\n'
        res += '  '.join(frames[1][p:p + 20]) + '\n'
        # seq
        res += subseq.lower() + '%5d %%\n' % int(GC(subseq))
        res += csubseq.lower() + '\n'
        # - frames
        res += '  '.join(frames[-2][p:p + 20]) + ' \n'
        res += ' ' + '  '.join(frames[-1][p:p + 20]) + '\n'
        res += '  ' + '  '.join(frames[-3][p:p + 20]) + '\n\n'
    return res

# }}}


if __name__ == "__main__":
    from Bio._utils import run_doctest
    run_doctest()
