# 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.

"""Information about the IUPAC alphabets."""


protein_letters = "ACDEFGHIKLMNPQRSTVWY"
extended_protein_letters = "ACDEFGHIKLMNPQRSTVWYBXZJUO"
#   B = "Asx";  aspartic acid or asparagine (D or N)
#   X = "Xxx";  unknown or 'other' amino acid
#   Z = "Glx";  glutamic acid or glutamine (E or Q)
#   http://www.chem.qmul.ac.uk/iupac/AminoAcid/A2021.html#AA212
#
#   J = "Xle";  leucine or isoleucine (L or I, used in NMR)
#   Mentioned in http://www.chem.qmul.ac.uk/iubmb/newsletter/1999/item3.html
#   Also the International Nucleotide Sequence Database Collaboration (INSDC)
#   (i.e. GenBank, EMBL, DDBJ) adopted this in 2006
#   http://www.ddbj.nig.ac.jp/insdc/icm2006-e.html
#
#   Xle (J); Leucine or Isoleucine
#   The residue abbreviations, Xle (the three-letter abbreviation) and J
#   (the one-letter abbreviation) are reserved for the case that cannot
#   experimentally distinguish leucine from isoleucine.
#
#   U = "Sec";  selenocysteine
#   http://www.chem.qmul.ac.uk/iubmb/newsletter/1999/item3.html
#
#   O = "Pyl";  pyrrolysine
#   http://www.chem.qmul.ac.uk/iubmb/newsletter/2009.html#item35

protein_letters_1to3 = {
    'A': 'Ala', 'C': 'Cys', 'D': 'Asp',
    'E': 'Glu', 'F': 'Phe', 'G': 'Gly', 'H': 'His',
    'I': 'Ile', 'K': 'Lys', 'L': 'Leu', 'M': 'Met',
    'N': 'Asn', 'P': 'Pro', 'Q': 'Gln', 'R': 'Arg',
    'S': 'Ser', 'T': 'Thr', 'V': 'Val', 'W': 'Trp',
    'Y': 'Tyr',
}
protein_letters_1to3_extended = dict(list(protein_letters_1to3.items()) + list({
    'B': 'Asx', 'X': 'Xaa', 'Z': 'Glx', 'J': 'Xle',
    'U': 'Sel', 'O': 'Pyl',
}.items()))

protein_letters_3to1 = dict((x[1], x[0]) for x in
                            protein_letters_1to3.items())
protein_letters_3to1_extended = dict((x[1], x[0]) for x in
                                     protein_letters_1to3_extended.items())

ambiguous_dna_letters = "GATCRYWSMKHBVDN"
unambiguous_dna_letters = "GATC"
ambiguous_rna_letters = "GAUCRYWSMKHBVDN"
unambiguous_rna_letters = "GAUC"

#   B == 5-bromouridine
#   D == 5,6-dihydrouridine
#   S == thiouridine
#   W == wyosine
extended_dna_letters = "GATCBDSW"

# are there extended forms?
# extended_rna_letters = "GAUCBDSW"

ambiguous_dna_values = {
    "A": "A",
    "C": "C",
    "G": "G",
    "T": "T",
    "M": "AC",
    "R": "AG",
    "W": "AT",
    "S": "CG",
    "Y": "CT",
    "K": "GT",
    "V": "ACG",
    "H": "ACT",
    "D": "AGT",
    "B": "CGT",
    "X": "GATC",
    "N": "GATC",
    }
ambiguous_rna_values = {
    "A": "A",
    "C": "C",
    "G": "G",
    "U": "U",
    "M": "AC",
    "R": "AG",
    "W": "AU",
    "S": "CG",
    "Y": "CU",
    "K": "GU",
    "V": "ACG",
    "H": "ACU",
    "D": "AGU",
    "B": "CGU",
    "X": "GAUC",
    "N": "GAUC",
    }

ambiguous_dna_complement = {
    "A": "T",
    "C": "G",
    "G": "C",
    "T": "A",
    "M": "K",
    "R": "Y",
    "W": "W",
    "S": "S",
    "Y": "R",
    "K": "M",
    "V": "B",
    "H": "D",
    "D": "H",
    "B": "V",
    "X": "X",
    "N": "N",
    }

ambiguous_rna_complement = {
    "A": "U",
    "C": "G",
    "G": "C",
    "U": "A",
    "M": "K",
    "R": "Y",
    "W": "W",
    "S": "S",
    "Y": "R",
    "K": "M",
    "V": "B",
    "H": "D",
    "D": "H",
    "B": "V",
    "X": "X",
    "N": "N",
    }


def _make_ranges(mydict):
    d = {}
    for key, value in mydict.items():
        d[key] = (value, value)
    return d

# Mass data taken from PubChem


# Average masses of monophosphate deoxy nucleotides
unambiguous_dna_weights = {
    "A": 331.2218,
    "C": 307.1971,
    "G": 347.2212,
    "T": 322.2085
    }

# Monoisotopic masses of monophospate deoxy nucleotides
monoisotopic_unambiguous_dna_weights = {
    "A": 331.06817,
    "C": 307.056936,
    "G": 347.063084,
    "T": 322.056602
    }

unambiguous_dna_weight_ranges = _make_ranges(unambiguous_dna_weights)

unambiguous_rna_weights = {
    "A": 347.2212,
    "C": 323.1965,
    "G": 363.2206,
    "U": 324.1813
}

monoisotopic_unambiguous_rna_weights = {
    "A": 347.063084,
    "C": 323.051851,
    "G": 363.057999,
    "U": 324.035867
}

unambiguous_rna_weight_ranges = _make_ranges(unambiguous_rna_weights)


def _make_ambiguous_ranges(mydict, weight_table):
    range_d = {}
    avg_d = {}
    for letter, values in mydict.items():
        # Following line is a quick hack to skip undefined weights for U and O
        if len(values) == 1 and values[0] not in weight_table:
            continue

        weights = [weight_table.get(x) for x in values]
        range_d[letter] = (min(weights), max(weights))
        total_w = 0.0
        for w in weights:
            total_w = total_w + w
        avg_d[letter] = total_w / len(weights)
    return range_d, avg_d


ambiguous_dna_weight_ranges, avg_ambiguous_dna_weights = \
               _make_ambiguous_ranges(ambiguous_dna_values,
                                      unambiguous_dna_weights)

ambiguous_rna_weight_ranges, avg_ambiguous_rna_weights = \
               _make_ambiguous_ranges(ambiguous_rna_values,
                                      unambiguous_rna_weights)

protein_weights = {
    "A": 89.0932,
    "C": 121.1582,
    "D": 133.1027,
    "E": 147.1293,
    "F": 165.1891,
    "G": 75.0666,
    "H": 155.1546,
    "I": 131.1729,
    "K": 146.1876,
    "L": 131.1729,
    "M": 149.2113,
    "N": 132.1179,
    "O": 255.3134,
    "P": 115.1305,
    "Q": 146.1445,
    "R": 174.201,
    "S": 105.0926,
    "T": 119.1192,
    "U": 168.0532,
    "V": 117.1463,
    "W": 204.2252,
    "Y": 181.1885
    }

monoisotopic_protein_weights = {
    "A": 89.047678,
    "C": 121.019749,
    "D": 133.037508,
    "E": 147.053158,
    "F": 165.078979,
    "G": 75.032028,
    "H": 155.069477,
    "I": 131.094629,
    "K": 146.105528,
    "L": 131.094629,
    "M": 149.051049,
    "N": 132.053492,
    "O": 255.158292,
    "P": 115.063329,
    "Q": 146.069142,
    "R": 174.111676,
    "S": 105.042593,
    "T": 119.058243,
    "U": 168.964203,
    "V": 117.078979,
    "W": 204.089878,
    "Y": 181.073893,
    }

extended_protein_values = {
    "A": "A",
    "B": "ND",
    "C": "C",
    "D": "D",
    "E": "E",
    "F": "F",
    "G": "G",
    "H": "H",
    "I": "I",
    "J": "IL",
    "K": "K",
    "L": "L",
    "M": "M",
    "N": "N",
    "O": "O",
    "P": "P",
    "Q": "Q",
    "R": "R",
    "S": "S",
    "T": "T",
    "U": "U",
    "V": "V",
    "W": "W",
    "X": "ACDEFGHIKLMNPQRSTVWY",
    # TODO - Include U and O in the possible values of X?
    # This could alter the extended_protein_weight_ranges ...
    # by MP: Won't do this, because they are so rare.
    "Y": "Y",
    "Z": "QE",
}

protein_weight_ranges = _make_ranges(protein_weights)

extended_protein_weight_ranges, avg_extended_protein_weights = \
               _make_ambiguous_ranges(extended_protein_values,
                                      protein_weights)


# For Center of Mass Calculation.
# Taken from http://www.chem.qmul.ac.uk/iupac/AtWt/ & PyMol
atom_weights = {
    'H': 1.00794,
    'D': 2.01410,
    'He': 4.002602,
    'Li': 6.941,
    'Be': 9.012182,
    'B': 10.811,
    'C': 12.0107,
    'N': 14.0067,
    'O': 15.9994,
    'F': 18.9984032,
    'Ne': 20.1797,
    'Na': 22.989770,
    'Mg': 24.3050,
    'Al': 26.981538,
    'Si': 28.0855,
    'P': 30.973761,
    'S': 32.065,
    'Cl': 35.453,
    'Ar': 39.948,
    'K': 39.0983,
    'Ca': 40.078,
    'Sc': 44.955910,
    'Ti': 47.867,
    'V': 50.9415,
    'Cr': 51.9961,
    'Mn': 54.938049,
    'Fe': 55.845,
    'Co': 58.933200,
    'Ni': 58.6934,
    'Cu': 63.546,
    'Zn': 65.39,
    'Ga': 69.723,
    'Ge': 72.64,
    'As': 74.92160,
    'Se': 78.96,
    'Br': 79.904,
    'Kr': 83.80,
    'Rb': 85.4678,
    'Sr': 87.62,
    'Y': 88.90585,
    'Zr': 91.224,
    'Nb': 92.90638,
    'Mo': 95.94,
    'Tc': 98.0,
    'Ru': 101.07,
    'Rh': 102.90550,
    'Pd': 106.42,
    'Ag': 107.8682,
    'Cd': 112.411,
    'In': 114.818,
    'Sn': 118.710,
    'Sb': 121.760,
    'Te': 127.60,
    'I': 126.90447,
    'Xe': 131.293,
    'Cs': 132.90545,
    'Ba': 137.327,
    'La': 138.9055,
    'Ce': 140.116,
    'Pr': 140.90765,
    'Nd': 144.24,
    'Pm': 145.0,
    'Sm': 150.36,
    'Eu': 151.964,
    'Gd': 157.25,
    'Tb': 158.92534,
    'Dy': 162.50,
    'Ho': 164.93032,
    'Er': 167.259,
    'Tm': 168.93421,
    'Yb': 173.04,
    'Lu': 174.967,
    'Hf': 178.49,
    'Ta': 180.9479,
    'W': 183.84,
    'Re': 186.207,
    'Os': 190.23,
    'Ir': 192.217,
    'Pt': 195.078,
    'Au': 196.96655,
    'Hg': 200.59,
    'Tl': 204.3833,
    'Pb': 207.2,
    'Bi': 208.98038,
    'Po': 208.98,
    'At': 209.99,
    'Rn': 222.02,
    'Fr': 223.02,
    'Ra': 226.03,
    'Ac': 227.03,
    'Th': 232.0381,
    'Pa': 231.03588,
    'U': 238.02891,
    'Np': 237.05,
    'Pu': 244.06,
    'Am': 243.06,
    'Cm': 247.07,
    'Bk': 247.07,
    'Cf': 251.08,
    'Es': 252.08,
    'Fm': 257.10,
    'Md': 258.10,
    'No': 259.10,
    'Lr': 262.11,
    'Rf': 261.11,
    'Db': 262.11,
    'Sg': 266.12,
    'Bh': 264.12,
    'Hs': 269.13,
    'Mt': 268.14,
}
