#!/usr/bin/env python
# -*- coding: UTF-8 -*-

"""
Utility to run Automated Human Readable Description (AHRD) pipeline.

<https://github.com/groupschoof/AHRD>
"""
import os.path as op
import sys
import re

from os import symlink

from ..apps.base import ActionDispatcher, OptionParser, logger, mkdir, glob
from ..formats.base import must_open


# --- Compiled RegExps ----
# Cellular locations
loc_pat = re.compile(r",\s*(chloroplastic|cytoplasmic|mitochondrial).*?\s$", re.I)
# Any word that matches e.g. Os02g0234800
osg_pat = re.compile(r"\bOs\d{2}g\d{7}.*?\s", re.I)
# (fragment)
frag_pat = re.compile(r"\(fragment[s]?\)", re.I)
# Trailing protein numeric copy (e.g. Myb 1)
trail_pat = re.compile(r"(?<!type)\s\d+\s*$", re.I)
# UPF
upf_pat = re.compile(r"^UPF.*$")
# Remove 'DDB_G\d+' ID
ddb_pat = re.compile(r"\s+DDB_G\d+", re.I)

# Any AHRD that matches e.g. "AT5G54690-like protein"
atg_pat = re.compile(r"\bAT[1-5M]G\d{5}-like protein", re.I)

# remove 'arabidopsis thaliana'
atg_id_pat = re.compile(r"[_]*AT\dG\d+[/]*", re.I)
athila_pat1 = re.compile(r"Belongs to|^Encodes|^Expression|^highly", re.I)
athila_pat2 = re.compile(r"^Arabidopsis thaliana ", re.I)
athila_pat3 = re.compile(r"^Arabidopsis ", re.I)
athila_pat4 = re.compile(r"BEST Arabidopsis thaliana protein match is: ", re.I)

# &apos;? => '
apos_pat = re.compile(r"&apos;?")

# &gt => none
gt_pat = re.compile(r"&gt")

# -like to -like protein
like_pat = re.compile(r"[-]like$", re.I)

# 'repeat$' to 'repeat protein'
repeat_pat = re.compile(r"repeat$", re.I)

# re used by the following 3 cases
Protein_pat = re.compile(r"Protein\s+", re.I)

# 'binding$' to 'binding protein'
binding_pat = re.compile(r"binding$", re.I)

# 'domain$' to 'domain-containing protein'
domain_pat = re.compile(r"domain$", re.I)

# 'related$' to '-like protein'
related_pat = re.compile(r"[,\s+]*[\s+|-]*related$", re.I)

# '[0-9]+ homolog' to '-like protein'
homolog_pat1 = re.compile(r"(?<!type)\s+\d+\s+homolog.*$", re.I)

# 'Protein\s+(.*)\s+homolog' to '$1-like protein'
homolog_pat2 = re.compile(r"^Protein([\s\S]+)\s+homolog.*", re.I)

# 'homolog protein' to '-like protein'
homolog_pat3 = re.compile(r"\s+homolog\s+protein.*", re.I)
# 'homolog \S+' to '-like protein'
homolog_pat4 = re.compile(r"\s+homolog\s+\d+$", re.I)
# 'homologue$' to '-like protein'
homolog_pat5 = re.compile(r"\s+homologue[\s\S]+$", re.I)
# 'homolog$' to '-like protein'
homolog_pat6 = re.compile(r"\s+homolog$", re.I)

# 'Agenet domain-containing protein / bromo-adjacent homology (BAH) domain-containing protein'
# to 'Agenet and bromo-adjacent homology (BAH) domain-containing protein'
agenet_pat = re.compile(r"Agenet domain-containing protein / ", re.I)

# plural to singular
plural_pat = re.compile(r"[deinr]s$", re.I)

# 'like_TBP' or 'likeTBP' to 'like TBP'
tbp_pat = re.compile(r"like[_]*TBP", re.I)

# 'protein protein' to 'protein'
prot_pat = re.compile(r"protein protein", re.I)

# 'Candidate|Hypothetical|Novel|Predicted|Possible' to 'Putative'
put_pat = re.compile(
    r"Candidate|Hypothetical|Novel|Predicted|Possible|Probable|Uncharacterized", re.I
)

# 'dimerisation' to 'dimerization'
dimer_pat = re.compile(r"dimerisation", re.I)

# '\s+LENGTH=\d+' to ''
length_pat = re.compile(r"\s+LENGTH=\d+", re.I)

# disallowed words
disallow = ("genome", "annotation", "project")
disallow_pat = re.compile("|".join(str(x) for x in disallow))

# disallowed organism names
organism = ("thaliana", "rickettsia", "rice", "yeast")
organism_pat = re.compile("|".join("^.*{0}".format(str(x)) for x in organism))

# consolidate glycosidic links
glycosidic_link_pat = re.compile(r"\d+,\d+")

# Kevin Silverstein suggested names (exclude list)
spada = ("LCR", "RALF", "SCR")
spada_pat = re.compile("|".join("^{0}$".format(str(x)) for x in spada))

# names with all capital letters (maybe followed by numbers)
sym_pat = re.compile(r"^[A-Z]+[A-Z0-9\-]*$")
lc_sym_pat = re.compile(r"^[A-z][a-z]+[0-9]+$")
eol_sym_pat = re.compile(r"\([A-Z]+[A-Z0-9\-]*\)$")

# sulfer -> sulfur
# sulph -> sulf
sulfer_pat = re.compile(r"sulfer")
sulph_pat = re.compile(r"sulph")

# monoxy to monooxy
monoxy_pat = re.compile(r"monoxy")

# proteine to protein
proteine_pat = re.compile(r"proteine")

# signalling to signaling
signalling_pat = re.compile(r"signalling")

# aluminium to aluminum
aluminium_pat = re.compile(r"aluminium", re.I)

# haem to heme
# haemo to hemo
haem_pat = re.compile(r"\bhaem\b", re.I)
haemo_pat = re.compile(r"haemo", re.I)

# assessory -> accessory
assessory_pat = re.compile(r"assessory")

# british to american spelling conversion
# -ise -> -ize
# -ised -> -ized
# -isation -> -ization
# -bre -> -ber
ise_pat = re.compile(r"\b([A-z]+)ise([d]?)\b")
isation_pat = re.compile(r"\b([A-z]+)isation\b")
bre_pat = re.compile(r"\b([A-z]+)bre\b")

# /with \S+ and \S+/ pattern
# /, and \S+/ pattern
# identify names with two domains
with_and_pat = re.compile(r"[with|,]\s*\S+and\S+")

Template = """
proteins_fasta: {2}
token_score_bit_score_weight: {4}
token_score_database_score_weight: {5}
token_score_overlap_score_weight: {6}
description_score_relative_description_frequency_weight: 0.6
output: {3}
blast_dbs:
  swissprot:
    weight: 100
    file: ./swissprot/{1}.swissprot.tab
    database: ./dbs/swissprot.fasta
    blacklist: {0}/blacklist_descline.txt
    filter: {0}/filter_descline_sprot.txt
    token_blacklist: {0}/blacklist_token.txt
    description_score_bit_score_weight: 0.2

  tair:
    weight: 50
    file: ./tair/{1}.tair.tab
    database: ./dbs/tair.fasta
    blacklist: {0}/blacklist_descline.txt
    filter: {0}/filter_descline_tair.txt
    fasta_header_regex: "^>(?<accession>[aA][tT][0-9mMcC][gG]\\\\d+(\\\\.\\\\d+)?)\\\\s+\\\\|[^\\\\|]+\\\\|\\\\s+(?<description>[^\\\\|]+)(\\\\s*\\\\|.*)?$"
    short_accession_regex: "^(?<shortAccession>.+)$"
    token_blacklist: {0}/blacklist_token.txt
    description_score_bit_score_weight: 0.4

  trembl:
    weight: 10
    file: ./trembl/{1}.trembl.tab
    database: ./dbs/trembl.fasta
    blacklist: {0}/blacklist_descline.txt
    filter: {0}/filter_descline_trembl.txt
    token_blacklist: {0}/blacklist_token.txt
    description_score_bit_score_weight: 0.4
{7}
"""

iprscanTemplate = """
interpro_database: ./interpro.xml
interpro_result: {0}
"""

# Necessary for the script to know the location of `interpro.xml` and `interpro.dtd`
iprscan_datadir = "/usr/local/devel/ANNOTATION/iprscan/iprscan_v4.7/data"


def main():

    actions = (
        ("batch", "batch run AHRD"),
        ("merge", "merge AHRD run results"),
        ("fix", "fix AHRD names"),
    )
    p = ActionDispatcher(actions)
    p.dispatch(globals())


Unknown = "Unknown protein"
Hypothetical = "hypothetical protein"


def read_interpro(ipr):
    store = {}
    fp = open(ipr)
    # Aco000343.1     0d98a55eb3399a408e06252a2e24efcf        2083    Pfam
    # PF00476 DNA polymerase family A 1685    2075    1.70E-55        T
    # 10-10-2014      IPR001098       "DNA-directed DNA polymerase, family A,
    # palm domain"    GO:0003677|GO:0003887|GO:0006260        KEGG:
    # 00230+2.7.7.7|KEGG: 00240+2.7.7.7
    for row in fp:
        (
            accession,
            md5,
            seqlen,
            analysis,
            signature,
            signature_description,
            start,
            stop,
            score,
            status,
            date,
            interpro,
            interpro_description,
            GO,
            pathway,
        ) = row.split("\t")
        accession = accession.split(".")[0]
        interpro_description = interpro_description.replace('"', "")
        pathway = pathway.strip()
        if accession not in ipr:
            store[accession] = (interpro, interpro_description, GO, pathway)
    return store


def fix_text(s, ignore_sym_pat=False):

    if not ignore_sym_pat:
        # Fix descriptions like D7TDB1 (
        s = re.sub(r"([A-Z0-9]){6} \(", "", s)
        s = s.split(";")[0]

    # Fix parantheses containing names
    s = s.strip("[]")
    s = s.replace("(-)", "[-]")
    s = s.replace("(+)", "[+]")
    s = s.replace("(Uncharacterized protein)", "")
    if not ignore_sym_pat:
        s = s.strip("()")

    # fix minor typos, seen in `autonaming` output
    # change 'protei ' to 'protein '
    # change 'hypthetical' to 'hypothetical'
    # fix string starting with 'ytochrome'
    if "protei " in s:
        s = s.replace("protei ", "protein ")
    if "hypthetical" in s:
        s = s.replace("hypthetical", "hypothetical")
    if s.startswith("ytochrome"):
        s = s.replace("ytochrome", "cytochrome")

    # before trimming off at the first ";", check if name has glycosidic
    # linkage information (e.g 1,3 or 1,4). If so, also check if multiple
    # linkages are separated by ";". If so, replace ";" by "-"
    m = re.findall(glycosidic_link_pat, s)
    if m and ";" in s:
        s = re.sub(r";\s*", "-", s)

    # remove underscore from description
    s = re.sub("_", " ", s)

    # Cellular locations
    # Any word that matches e.g. AT5G54690
    # Any word that matches e.g. Os02g0234800
    # (fragment)
    # UPF
    # Remove 'DDB_G\d+' ID
    # '_At[0-9]+g[0-9]+' to ''
    for pat in (loc_pat, osg_pat, frag_pat, upf_pat, ddb_pat):
        # below is a hack since word boundaries don't work on /
        s = s.strip() + " "
        s = re.sub(pat, "", s)

    # &apos;? => '
    s = re.sub(apos_pat, "'", s)
    # &gt => none
    s = re.sub(gt_pat, "", s)
    # reduce runs such as -- '''
    s = re.sub(r"[-]+", "-", s)
    s = re.sub(r"[']+", "'", s)

    s = s.strip()

    # -like to -like protein
    s = re.sub(like_pat, "-like protein", s)

    # 'repeat$' to 'repeat protein'
    if re.search(repeat_pat, s):
        s += "-containing protein"

    # 'binding$' to 'binding protein'
    if re.search(binding_pat, s):
        s += " protein"
        if re.match(Protein_pat, s):
            s = re.sub(Protein_pat, "", s)

    # 'domain$' to 'domain-containing protein'
    if re.search(domain_pat, s):
        s += "-containing protein"
        if re.search(r"-domain", s):
            s = re.sub(r"-domain", " domain", s)
        if re.match(Protein_pat, s):
            s = re.sub(Protein_pat, "", s)

    # 'related$' to '-like protein'
    if re.search(related_pat, s):
        s = re.sub(related_pat, "-like protein", s)
        if re.match(Protein_pat, s) and not re.match(r"Protein kinase", s):
            s = re.sub(Protein_pat, "", s)

    # '[0-9]+ homolog' to '-like protein'
    if re.search(homolog_pat1, s):
        s = re.sub(homolog_pat1, "-like protein", s)
        if re.match(Protein_pat, s):
            s = re.sub(Protein_pat, "", s)

    # 'Protein\s+(.*)\s+homolog' to '$1-like protein'
    match = re.search(homolog_pat2, s)
    if match and not re.match(r"Protein kinase", s):
        ret = match.group(1)
        s = re.sub(homolog_pat2, ret + "-like protein", s)
        s = re.sub(r"^\s+", "", s)
        s = s.capitalize()

    # 'homolog protein' to '-like protein'
    # 'homologue$' to '-like protein'
    # 'homolog$' to '-like protein'
    for pat in (homolog_pat3, homolog_pat5, homolog_pat6):
        if re.search(pat, s):
            s = re.sub(pat, "-like protein", s)

    # 'Agenet domain-containing protein / bromo-adjacent homology (BAH) domain-containing protein'
    # to 'Agenet and bromo-adjacent homology (BAH) domain-containing protein'
    if re.search(agenet_pat, s):
        s = re.sub(agenet_pat, "Agenet and ", s)

    # plural to singular
    if re.search(plural_pat, s):
        if (s.find("biogenesis") == -1 and s.find("Topors") == -1) or (
            not re.search(with_and_pat, s)
        ):
            s = re.sub(r"s$", "", s)

    # 'like_TBP' or 'likeTBP' to 'like TBP'
    if re.search(tbp_pat, s):
        s = re.sub(tbp_pat, "like TBP", s)

    # 'protein protein' to 'protein'
    if re.search(prot_pat, s):
        s = re.sub(prot_pat, "protein", s)

    # 'dimerisation' to 'dimerization'
    if re.search(dimer_pat, s):
        s = re.sub(dimer_pat, "dimerization", s)

    # Any AHRD that matches e.g. "AT5G54690-like protein"
    # Any AHRD that contains the words '^Belongs|^Encoded|^Expression|^highly'
    for pat in (atg_pat, athila_pat1):
        if re.search(pat, s):
            s = Unknown

    # remove 'arabidopsis[ thaliana]' and/or embedded Atg IDs
    for pat in (atg_id_pat, athila_pat2, athila_pat3, athila_pat4):
        # below is a hack since word boundaries don't work on /
        s = s.strip() + " "
        s = re.sub(pat, "", s)

    # remove "\s+LENGTH=\d+" from TAIR deflines
    if re.search(length_pat, s):
        s = re.sub(length_pat, "", s)

    # if name has a dot followed by a space (". ") in it and contains multiple
    # parts separated by a comma, strip name starting from first occurrence of ","
    if re.search(r"\. ", s):
        if re.search(r",", s):
            s = s.split(",")[0]

    # if name contains any of the disallowed words,
    # remove word occurrence from name
    # if name contains references to any other organism, trim name upto
    # that occurrence
    for pat in (disallow_pat, organism_pat):
        if re.search(pat, s):
            s = re.sub(pat, "", s)

    s = s.strip()

    if not ignore_sym_pat:
        # 'homolog \d+' to '-like protein'
        if re.search(homolog_pat4, s):
            s = re.sub(homolog_pat4, "", s)

        # Trailing protein numeric copy (e.g. Myb 1)
        if re.search(trail_pat, s):
            s = re.sub(trail_pat, "", s)

        # if name is entirely a gene symbol-like (all capital letters, maybe followed by numbers)
        # add a "-like protein" at the end
        if (re.search(sym_pat, s) or re.search(lc_sym_pat, s)) and not re.search(
            spada_pat, s
        ):
            s = s + "-like protein"

        # if gene symbol in parantheses at EOL, remove symbol
        if re.search(eol_sym_pat, s):
            s = re.sub(eol_sym_pat, "", s)

        # if name terminates at a symbol([^A-Za-z0-9_]), trim it off
        if re.search(r"\W+$", s) and not re.search(r"\)$", s):
            s = re.sub(r"\W+$", "", s)

        if "uncharacterized" in s:
            s = "uncharacterized protein"

    # change sulfer to sulfur
    if re.search(sulfer_pat, s):
        s = re.sub(sulfer_pat, "sulfur", s)

    # change sulph to sulf
    if re.search(sulph_pat, s):
        s = re.sub(sulph_pat, "sulf", s)

    # change monoxy to monooxy
    if re.search(monoxy_pat, s):
        s = re.sub(monoxy_pat, "monooxy", s)

    # change proteine to protein
    if re.search(proteine_pat, s):
        s = re.sub(proteine_pat, "protein", s)

    # change signalling to signaling
    if re.search(signalling_pat, s):
        s = re.sub(signalling_pat, "signaling", s)

    # change aluminium to aluminum
    if re.search(aluminium_pat, s):
        s = re.sub(aluminium_pat, "aluminum", s)

    # change haem to heme
    if re.search(haem_pat, s):
        s = re.sub(haem_pat, "heme", s)

    # chage haemo to hemo
    if re.search(haemo_pat, s):
        s = re.sub(haemo_pat, "hemo", s)

    # change assessory to accessory
    if re.search(assessory_pat, s):
        s = re.sub(assessory_pat, "accessory", s)

    # change -ise/-ised/-isation to -ize/-ized/-ization
    match = re.search(ise_pat, s)
    if match:
        ret = match.group(1)
        if match.group(2):
            suff = match.group(2)
            s = re.sub(ise_pat, "{0}ize{1}".format(ret, suff), s)
        else:
            s = re.sub(ise_pat, "{0}ize".format(ret), s)

    match = re.search(isation_pat, s)
    if match:
        ret = match.group(1)
        s = re.sub(isation_pat, "{0}ization".format(ret), s)

    # change -bre to -ber
    match = re.search(bre_pat, s)
    if match:
        ret = match.group(1)
        s = re.sub(bre_pat, "{0}ber".format(ret), s)

    if not s.startswith(Hypothetical):
        # 'Candidate|Hypothetical|Novel|Predicted|Possible|Probable|Uncharacterized' to 'Putative'
        if s.startswith("Uncharacterized") and any(
            pat in s for pat in ("UCP", "UPF", "protein")
        ):
            pass
        else:
            if re.search(put_pat, s):
                s = re.sub(put_pat, "Putative", s)

    sl = s.lower()

    # Any mention of `clone` or `contig` is not informative
    if "clone" in sl or "contig" in sl:
        s = Unknown

    # All that's left is `protein` is not informative
    if sl in ("protein", "protein, putative", ""):
        s = Unknown

    if Unknown.lower() in sl:
        s = Unknown

    if "FUNCTIONS IN".lower() in sl and "unknown" in sl:
        s = Unknown

    if "LOCATED IN".lower() in sl:
        s = Unknown

    s = re.sub(r"[,]*\s+putative$", "", s)

    if s == Unknown or s.strip() == "protein":
        s = Hypothetical

    # Compact all spaces
    s = " ".join(s.split())

    assert s.strip()

    return s


def fix(args):
    """
    %prog fix ahrd.csv > ahrd.fixed.csv

    Fix ugly names from Uniprot.
    """
    p = OptionParser(fix.__doc__)
    p.add_argument(
        "--ignore_sym_pat",
        default=False,
        action="store_true",
        help="Do not fix names matching symbol patterns i.e."
        + " names beginning or ending with gene symbols or a series of numbers."
        + " e.g. `ARM repeat superfamily protein`, `beta-hexosaminidase 3`,"
        + " `CYCLIN A3;4`, `WALL ASSOCIATED KINASE (WAK)-LIKE 10`",
    )
    p.set_outfile()
    opts, args = p.parse_args(args)

    if len(args) < 1:
        sys.exit(not p.print_help())

    (csvfile,) = args
    fp = open(csvfile)
    fw = must_open(opts.outfile, "w")
    for row in fp:
        if row[0] == "#":
            continue
        if row.strip() == "":
            continue
        atoms = row.rstrip("\r\n").split("\t")
        name, hit, ahrd_code, desc = (
            atoms[:4] if len(atoms) > 2 else (atoms[0], None, None, atoms[-1])
        )

        newdesc = fix_text(desc, ignore_sym_pat=opts.ignore_sym_pat)
        if hit and hit.strip() != "" and newdesc == Hypothetical:
            newdesc = "conserved " + newdesc
        print("\t".join(atoms[:4] + [newdesc] + atoms[4:]), file=fw)


def merge(args):
    """
    %prog merge output/*.csv > ahrd.csv

    Merge AHRD results, remove redundant headers, empty lines, etc. If there are
    multiple lines containing the same ID (first column). Then whatever comes
    the first will get retained.
    """
    p = OptionParser(merge.__doc__)
    opts, args = p.parse_args(args)

    if len(args) < 1:
        sys.exit(not p.print_help())

    csvfiles = args
    cf = csvfiles[0]
    fp = open(cf)
    for row in fp:
        if row.startswith("Protein"):
            break
    header = row.rstrip()
    print(header)

    seen = set()
    for cf in csvfiles:
        fp = open(cf)
        for row in fp:
            if row[0] == "#":
                continue
            if row.strip() == "":
                continue
            if row.strip() == header:
                continue

            atoms = row.rstrip().split("\t")
            id = atoms[0]
            if id in seen:
                logger.error("ID `%s` ignored.", id)
                continue

            seen.add(id)
            print(row.strip())


def batch(args):
    """
    %prog batch splits output

    The arguments are two folders.
    Input FASTA sequences are in splits/.
    Output csv files are in output/.

    Must have folders swissprot/, tair/, trembl/ that contains the respective
    BLAST output. Once finished, you can run, for example:

    $ parallel java -Xmx2g -jar ~/code/AHRD/dist/ahrd.jar {} ::: output/*.yml
    """
    p = OptionParser(batch.__doc__)

    ahrd_weights = {"blastp": [0.5, 0.3, 0.2], "blastx": [0.6, 0.4, 0.0]}
    blast_progs = tuple(ahrd_weights.keys())

    p.add_argument(
        "--path",
        default="~/code/AHRD/",
        help="Path where AHRD is installed",
    )
    p.add_argument(
        "--blastprog",
        default="blastp",
        choices=blast_progs,
        help="Specify the blast program being run. Based on this option,"
        + " the AHRD parameters (score_weights) will be modified",
    )
    p.add_argument(
        "--iprscan",
        default=None,
        help="Specify path to InterProScan results file if available."
        + " If specified, the yml conf file will be modified"
        + " appropriately",
    )

    opts, args = p.parse_args(args)

    if len(args) != 2:
        sys.exit(not p.print_help())

    splits, output = args
    mkdir(output)

    bit_score, db_score, ovl_score = ahrd_weights[opts.blastprog]

    for f in glob("{0}/*.fa*".format(splits)):
        fb = op.basename(f).rsplit(".", 1)[0]
        fw = open(op.join(output, fb + ".yml"), "w")

        path = op.expanduser(opts.path)
        dir = op.join(path, "test/resources")
        outfile = op.join(output, fb + ".csv")
        interpro = iprscanTemplate.format(opts.iprscan) if opts.iprscan else ""

        print(
            Template.format(
                dir, fb, f, outfile, bit_score, db_score, ovl_score, interpro
            ),
            file=fw,
        )

    if opts.iprscan:
        if not op.lexists("interpro.xml"):
            symlink(op.join(iprscan_datadir, "interpro.xml"), "interpro.xml")

        if not op.lexists("interpro.dtd"):
            symlink(op.join(iprscan_datadir, "interpro.dtd"), "interpro.dtd")


if __name__ == "__main__":
    main()
