import os
import fnmatch
import re
import numpy as np  # Thinly-wrapped numpy
from ..obs import Obs
from . import utils


def read_sfcf(path, prefix, name, quarks='.*', corr_type='bi', noffset=0, wf=0, wf2=0, version="1.0c", cfg_separator="n", **kwargs):
    """Read sfcf c format from given folder structure.

    Parameters
    ----------
    path : str
        Path to the sfcf files.
    prefix : str
        Prefix of the sfcf files.
    name : str
        Name of the correlation function to read.
    quarks : str
        Label of the quarks used in the sfcf input file. e.g. "quark quark"
        for version 0.0 this does NOT need to be given with the typical " - "
        that is present in the output file,
        this is done automatically for this version
    corr_type : str
        Type of correlation function to read. Can be
        - 'bi' for boundary-inner
        - 'bb' for boundary-boundary
        - 'bib' for boundary-inner-boundary
    noffset : int
        Offset of the source (only relevant when wavefunctions are used)
    wf : int
        ID of wave function
    wf2 : int
        ID of the second wavefunction
        (only relevant for boundary-to-boundary correlation functions)
    im : bool
        if True, read imaginary instead of real part
        of the correlation function.
    names : list
        Alternative labeling for replicas/ensembles.
        Has to have the appropriate length
    ens_name : str
        replaces the name of the ensemble
    version: str
        version of SFCF, with which the measurement was done.
        if the compact output option (-c) was specified,
        append a "c" to the version (e.g. "1.0c")
        if the append output option (-a) was specified,
        append an "a" to the version
    cfg_separator : str
        String that separates the ensemble identifier from the configuration number (default 'n').
    replica: list
        list of replica to be read, default is all
    files: list
        list of files to be read per replica, default is all.
        for non-compact output format, hand the folders to be read here.
    check_configs: list[list[int]]
        list of list of supposed configs, eg. [range(1,1000)]
        for one replicum with 1000 configs

    Returns
    -------
    result: list[Obs]
        list of Observables with length T, observable per timeslice.
        bb-type correlators have length 1.
    """
    if kwargs.get('im'):
        im = 1
        part = 'imaginary'
    else:
        im = 0
        part = 'real'
    if "replica" in kwargs:
        reps = kwargs.get("replica")
    if corr_type == 'bb':
        b2b = True
        single = True
    elif corr_type == 'bib':
        b2b = True
        single = False
    else:
        b2b = False
        single = False
    compact = True
    appended = False
    known_versions = ["0.0", "1.0", "2.0", "1.0c", "2.0c", "1.0a", "2.0a"]

    if version not in known_versions:
        raise Exception("This version is not known!")
    if (version[-1] == "c"):
        appended = False
        compact = True
        version = version[:-1]
    elif (version[-1] == "a"):
        appended = True
        compact = False
        version = version[:-1]
    else:
        compact = False
        appended = False
    read = 0
    T = 0
    start = 0
    ls = []
    if "replica" in kwargs:
        ls = reps
    else:
        for (dirpath, dirnames, filenames) in os.walk(path):
            if not appended:
                ls.extend(dirnames)
            else:
                ls.extend(filenames)
            break
        if not ls:
            raise Exception('Error, directory not found')
        # Exclude folders with different names
        for exc in ls:
            if not fnmatch.fnmatch(exc, prefix + '*'):
                ls = list(set(ls) - set([exc]))

    if not appended:
        if len(ls) > 1:
            # New version, to cope with ids, etc.
            ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0]))
        replica = len(ls)
    else:
        replica = len([file.split(".")[-1] for file in ls]) // len(set([file.split(".")[-1] for file in ls]))
    print('Read', part, 'part of', name, 'from', prefix[:-1],
          ',', replica, 'replica')
    if 'names' in kwargs:
        new_names = kwargs.get('names')
        if len(new_names) != len(set(new_names)):
            raise Exception("names are not unique!")
        if len(new_names) != replica:
            raise Exception('Names does not have the required length', replica)
    else:
        new_names = []
        if not appended:
            for entry in ls:
                try:
                    idx = entry.index('r')
                except Exception:
                    raise Exception("Automatic recognition of replicum failed, please enter the key word 'names'.")

                if 'ens_name' in kwargs:
                    new_names.append(kwargs.get('ens_name') + '|' + entry[idx:])
                else:
                    new_names.append(entry[:idx] + '|' + entry[idx:])
        else:

            for exc in ls:
                if not fnmatch.fnmatch(exc, prefix + '*.' + name):
                    ls = list(set(ls) - set([exc]))
            ls.sort(key=lambda x: int(re.findall(r'\d+', x)[-1]))
            for entry in ls:
                myentry = entry[:-len(name) - 1]
                try:
                    idx = myentry.index('r')
                except Exception:
                    raise Exception("Automatic recognition of replicum failed, please enter the key word 'names'.")

                if 'ens_name' in kwargs:
                    new_names.append(kwargs.get('ens_name') + '|' + myentry[idx:])
                else:
                    new_names.append(myentry[:idx] + '|' + myentry[idx:])
    idl = []
    if not appended:
        for i, item in enumerate(ls):
            sub_ls = []
            if "files" in kwargs:
                sub_ls = kwargs.get("files")
                sub_ls.sort(key=lambda x: int(re.findall(r'\d+', x)[-1]))
            else:
                for (dirpath, dirnames, filenames) in os.walk(path + '/' + item):
                    if compact:
                        sub_ls.extend(filenames)
                    else:
                        sub_ls.extend(dirnames)
                    break
                if compact:
                    for exc in sub_ls:
                        if not fnmatch.fnmatch(exc, prefix + '*'):
                            sub_ls = list(set(sub_ls) - set([exc]))
                    sub_ls.sort(key=lambda x: int(re.findall(r'\d+', x)[-1]))
                else:
                    for exc in sub_ls:
                        if not fnmatch.fnmatch(exc, 'cfg*'):
                            sub_ls = list(set(sub_ls) - set([exc]))
                    sub_ls.sort(key=lambda x: int(x[3:]))
            rep_idl = []
            no_cfg = len(sub_ls)
            for cfg in sub_ls:
                try:
                    if compact:
                        rep_idl.append(int(cfg.split(cfg_separator)[-1]))
                    else:
                        rep_idl.append(int(cfg[3:]))
                except Exception:
                    raise Exception("Couldn't parse idl from directroy, problem with file " + cfg)
            rep_idl.sort()
            # maybe there is a better way to print the idls
            print(item, ':', no_cfg, ' configurations')
            idl.append(rep_idl)
            # here we have found all the files we need to look into.
            if i == 0:
                # here, we want to find the place within the file,
                # where the correlator we need is stored.
                # to do so, the pattern needed is put together
                # from the input values
                if version == "0.0":
                    pattern = "# " + name + " : offset " + str(noffset) + ", wf " + str(wf)
                    # if b2b, a second wf is needed
                    if b2b:
                        pattern += ", wf_2 " + str(wf2)
                    qs = quarks.split(" ")
                    pattern += " : " + qs[0] + " - " + qs[1]
                    file = open(path + '/' + item + '/' + sub_ls[0] + '/' + name, "r")
                    for k, line in enumerate(file):
                        if read == 1 and not line.strip() and k > start + 1:
                            break
                        if read == 1 and k >= start:
                            T += 1
                        if pattern in line:
                            read = 1
                            start = k + 1
                    print(str(T) + " entries found.")
                    file.close()
                else:
                    pattern = 'name      ' + name + '\nquarks    ' + quarks + '\noffset    ' + str(noffset) + '\nwf        ' + str(wf)
                    if b2b:
                        pattern += '\nwf_2      ' + str(wf2)
                    # and the file is parsed through to find the pattern
                    if compact:
                        file = open(path + '/' + item + '/' + sub_ls[0], "r")
                    else:
                        # for non-compactified versions of the files
                        file = open(path + '/' + item + '/' + sub_ls[0] + '/' + name, "r")

                    content = file.read()
                    match = re.search(pattern, content)
                    if match:
                        start_read = content.count('\n', 0, match.start()) + 5 + b2b
                        end_match = re.search(r'\n\s*\n', content[match.start():])
                        T = content[match.start():].count('\n', 0, end_match.start()) - 4 - b2b
                        assert T > 0
                        print(T, 'entries, starting to read in line', start_read)
                        file.close()
                    else:
                        file.close()
                        raise Exception('Correlator with pattern\n' + pattern + '\nnot found.')

                # we found where the correlator
                # that is to be read is in the files
                # after preparing the datastructure
                # the correlators get parsed into...
                deltas = []
                for j in range(T):
                    deltas.append([])

            for t in range(T):
                deltas[t].append(np.zeros(no_cfg))
            if compact:
                for cfg in range(no_cfg):
                    with open(path + '/' + item + '/' + sub_ls[cfg]) as fp:
                        lines = fp.readlines()
                        # check, if the correlator is in fact
                        # printed completely
                        if (start_read + T > len(lines)):
                            raise Exception("EOF before end of correlator data! Maybe " + path + '/' + item + '/' + sub_ls[cfg] + " is corrupted?")
                        # and start to read the correlator.
                        # the range here is chosen like this,
                        # since this allows for implementing
                        # a security check for every read correlator later...
                        for k in range(start_read - 6, start_read + T):
                            if k == start_read - 5 - b2b:
                                if lines[k].strip() != 'name      ' + name:
                                    raise Exception('Wrong format', sub_ls[cfg])
                            if (k >= start_read and k < start_read + T):
                                floats = list(map(float, lines[k].split()))
                                deltas[k - start_read][i][cfg] = floats[-2:][im]
            else:
                for cnfg, subitem in enumerate(sub_ls):
                    with open(path + '/' + item + '/' + subitem + '/' + name) as fp:
                        # since the non-compatified files
                        # are typically not so long,
                        # we can iterate over the whole file.
                        # here one can also implement the chekc from above.
                        for k, line in enumerate(fp):
                            if (k >= start_read and k < start_read + T):
                                floats = list(map(float, line.split()))
                                if version == "0.0":
                                    deltas[k - start][i][cnfg] = floats[im - single]
                                else:
                                    deltas[k - start_read][i][cnfg] = floats[1 + im - single]

    else:
        if "files" in kwargs:
            ls = kwargs.get("files")
        else:
            for exc in ls:
                if not fnmatch.fnmatch(exc, prefix + '*.' + name):
                    ls = list(set(ls) - set([exc]))
                ls.sort(key=lambda x: int(re.findall(r'\d+', x)[-1]))
        pattern = 'name      ' + name + '\nquarks    ' + quarks + '\noffset    ' + str(noffset) + '\nwf        ' + str(wf)
        if b2b:
            pattern += '\nwf_2      ' + str(wf2)
        for rep, file in enumerate(ls):
            rep_idl = []
            with open(path + '/' + file, 'r') as fp:
                content = fp.readlines()
                data_starts = []
                for linenumber, line in enumerate(content):
                    if "[run]" in line:
                        data_starts.append(linenumber)
                if len(set([data_starts[i] - data_starts[i - 1] for i in range(1, len(data_starts))])) > 1:
                    raise Exception("Irregularities in file structure found, not all runs have the same output length")
                chunk = content[:data_starts[1]]
                for linenumber, line in enumerate(chunk):
                    if line.startswith("gauge_name"):
                        gauge_line = linenumber
                    elif line.startswith("[correlator]"):
                        corr_line = linenumber
                        found_pat = ""
                        for li in chunk[corr_line + 1: corr_line + 6 + b2b]:
                            found_pat += li
                        if re.search(pattern, found_pat):
                            start_read = corr_line + 7 + b2b
                            break
                endline = corr_line + 6 + b2b
                while not chunk[endline] == "\n":
                    endline += 1
                T = endline - start_read
                if rep == 0:
                    deltas = []
                    for t in range(T):
                        deltas.append([])
                for t in range(T):
                    deltas[t].append(np.zeros(len(data_starts)))
                # all other chunks should follow the same structure
                for cnfg in range(len(data_starts)):
                    start = data_starts[cnfg]
                    stop = start + data_starts[1]
                    chunk = content[start:stop]
                    try:
                        rep_idl.append(int(chunk[gauge_line].split(cfg_separator)[-1]))
                    except Exception:
                        raise Exception("Couldn't parse idl from directory, problem with chunk around line ", gauge_line)

                    found_pat = ""
                    for li in chunk[corr_line + 1:corr_line + 6 + b2b]:
                        found_pat += li
                    if re.search(pattern, found_pat):
                        for t, line in enumerate(chunk[start_read:start_read + T]):
                            floats = list(map(float, line.split()))
                            deltas[t][rep][cnfg] = floats[im + 1 - single]
            idl.append(rep_idl)

    if "check_configs" in kwargs:
        print("Checking for missing configs...")
        che = kwargs.get("check_configs")
        if not (len(che) == len(idl)):
            raise Exception("check_configs has to be the same length as replica!")
        for r in range(len(idl)):
            print("checking " + new_names[r])
            utils.check_idl(idl[r], che[r])
        print("Done")
    result = []
    for t in range(T):
        result.append(Obs(deltas[t], new_names, idl=idl))
    return result