from dataclasses import dataclass
import math

feps = 2.0**-23.0
tiniest = 2.0**-1022.0
check = object()  # secret "key" to pass to wrap_untrustworthy to extract feval_count
final = object()  # secret "key" to pass to wrap_untrustworthy to extract results

color_factory = lambda color: lambda s: print(f"\033[{color}m{s}\033[m")
m1 = color_factory(1)
m30 = color_factory(30)
m31 = color_factory(31)
m32 = color_factory(32)
m33 = color_factory(33)
m34 = color_factory(34)
m35 = color_factory(35)
m36 = color_factory(36)
m37 = color_factory(37)
m90 = color_factory(90)
m91 = color_factory(91)
m92 = color_factory(92)
m93 = color_factory(93)
m94 = color_factory(94)
m95 = color_factory(95)
m96 = color_factory(96)
m97 = color_factory(97)


class ExhaustedTrialsError(Exception):
    pass


def scalar_softplus(x):
    if x >= 33.276435657655455:
        return float(x)
    elif x <= -745.13330078125:
        return 0.0
    else:
        return math.log1p(math.exp(x))


def phi(d):
    # phi(1) = golden ratio
    # phi(2) = plastic constant
    # phi(3) = the positive real root of x**4-x-1
    x = 2.0
    for i in range(30 if d == 1 else max(10, 28 - d)):
        x = pow(1 + x, 1 / (d + 1))
    return x


def wrap_untrustworthy(
    objective, n_trials, *, raising=False, bounding=None, softplus=False, eps=0.0
):
    # also handles bounding now, so it may be used for other purposes as well. whoops.
    feval_count = 0
    best_so_far = None

    def _objective(x):
        nonlocal feval_count, best_so_far
        if x is check:
            return feval_count
        if x is final:
            assert best_so_far is not None
            fopt, xopt = best_so_far
            return fopt, xopt, feval_count
        if raising and feval_count >= n_trials:
            raise ExhaustedTrialsError()
        if bounding is not None:
            x = do_bounding(x, bounding)
        fx = objective(x)
        feval_count += 1
        if n_trials is None or feval_count <= n_trials:
            if best_so_far is None or fx < best_so_far[0]:
                best_so_far = (fx, x.copy())
        return scalar_softplus(fx) + eps if softplus else fx

    return _objective


@dataclass
class KeyData:
    key: str
    d: int
    n: int
    opt: str
    obj: str
    run: int


def decode_key(key, _filtering=False):
    # example key:
    # COWrap_d03_n130_freelunch_qpso_ps16_cube_go_amgm_on_cube
    k, _, run = key.partition("[")
    run, _, _ = run.partition("]")
    k = k.removeprefix("COWrap_")
    d, _, k = k.partition("_")
    n, _, k = k.partition("_")
    opt, _, k = k.partition("_cube_")
    obj, _, k = k.partition("_on_cube")
    if not obj:
        if opt.endswith("_on_cube"):
            return  # fcmaes_biteopt was missing the _cube in its name for a while
    if _filtering and obj in ("go_stochastic", "go_xinsheyang01"):
        return  # these are random
    assert not k, k
    d = int(d.removeprefix("d"), 10)
    n = int(n.removeprefix("n"), 10)
    run = int(run, 10)
    return KeyData(key=key, d=d, n=n, opt=opt, obj=obj, run=run)


class AcquireForWriting:
    """
    A context manager that allows for very crude file-locking-like
    functionality when the FileLock module is missing.
    """

    def __init__(self, filepath, usingfilelock=None):
        from pathlib import Path

        self.filepath = Path(filepath)
        if usingfilelock is None:
            try:
                from filelock import FileLock
            except ModuleNotFoundError:
                self._locking = False
                self.lock = None
            else:
                self._locking = True
                self.lock = FileLock(self._altpath)
        elif usingfilelock:
            from filelock import FileLock

            self._locking = True
            self.lock = FileLock(self._altpath)
        else:
            self._locking = False
            self.lock = None

    @property
    def _altpath(self):
        suffix = ".lock" if self._locking else "~"
        return self.filepath.with_suffix(self.filepath.suffix + suffix)

    def __enter__(self):
        if self._locking:
            self.lock.__enter__()
        else:
            from time import sleep

            for _ in range(3):
                if self._altpath.exists():
                    sleep(1)
            assert not self._altpath.exists(), f"file is locked: {self.filepath}"
            if not self._locking:
                self._altpath.write_bytes(b"")
        return self.filepath if self._locking else self._altpath

    def __exit__(self, *exc):
        if self._locking:
            self.lock.__exit__(*exc)
        elif exc == (None, None, None):
            assert self._altpath.exists(), f"file went missing: {self.filepath}"
            try:
                data = self._altpath.read_bytes()
                if data:
                    self.filepath.write_bytes(data)
            finally:
                self._altpath.unlink()
            # from shutil import move
            # move(self._altpath, self.filepath)  # assumes os.rename overwrites files


def perform_another_experimental_scoring_method(results):
    new_results = {}
    all_opt_names = set()
    for obj_name, obj_res in results.items():
        all_res = {}
        for fopt, opt_name in obj_res:
            all_res.setdefault(fopt, []).append(opt_name)
            all_opt_names.add(opt_name)
        new_results[obj_name] = dict(sorted(all_res.items()))

    limited_by_floating_point_precision = 53

    best_ranks_and_counts = {}
    for outer_rank in range(1, limited_by_floating_point_precision + 1):
        for obj_name, all_res in new_results.items():
            for fopt, opt_names in all_res.items():
                dirty = False
                for opt_name in set(opt_names):
                    if opt_name in best_ranks_and_counts:
                        rank, count = best_ranks_and_counts[opt_name]
                        if rank == outer_rank:
                            best_ranks_and_counts[opt_name] = (rank, count + 1)
                            dirty = True
                    else:
                        best_ranks_and_counts[opt_name] = (outer_rank, 1)
                        dirty = True
                if dirty:
                    break

    scores = {k: 0.0 for k in all_opt_names}
    for opt_name, (rank, count) in best_ranks_and_counts.items():
        points = 2**(1 - rank)
        count = min(count, limited_by_floating_point_precision)
        scores[opt_name] = score = sum(points / 2**i for i in range(count))

    return scores


def needs_rerun(key, value):
    n_dim = len(value["xopt"])
    ng = []

    if value["duration"] > -1683000000.0:
        if n_dim == 3:
            ng += "go_ackley01 go_alpine01 go_deflectedcorrugatedspring go_exponential go_griewank go_infinity go_mishra11 go_multimodal go_pinter go_qing go_rastrigin go_salomon go_schwefel01 go_schwefel20 go_schwefel21 go_schwefel22 go_sineenvelope go_sodp go_trigonometric02 go_wavy go_weierstrass go_xinsheyang01 go_xinsheyang02 go_xinsheyang03 go_yaoliu04 go_yaoliu09 go_zerosum".split()
            ng += "go_amgm go_brown go_cigar go_deb01 go_deb03 go_deceptive go_needleeye go_penalty01 go_schwefel04 go_schwefel26 go_sphere go_stretchedv go_styblinskitang go_zacharov".split()
        if n_dim == 4:
            ng += "go_ackley01 go_alpine01 go_cigar go_exponential go_griewank go_infinity go_pinter go_qing go_schwefel01 go_schwefel02 go_schwefel20 go_schwefel21 go_schwefel22 go_sineenvelope go_sphere go_step2 go_step go_stretchedv go_trigonometric02 go_weierstrass go_whitley go_xinsheyang01 go_xinsheyang02 go_yaoliu04 go_yaoliu09 go_zerosum".split()
            ng += "go_amgm go_brown go_colville go_deb03 go_penalty01 go_penalty02 go_powell go_rosenbrock go_schwefel04 go_shekel05 go_shekel07 go_shekel10 go_shubert03 go_shubert04 go_styblinskitang go_vincent".split()

    kd = decode_key(key)
    assert kd is not None, key
    if kd.obj in ng:
        # print("filtered", key, file=__import__("sys").stderr)
        return True

    return False


def merge_summaries(all_summaries):
    # i only needed to write this because i effed up my filenames at one point. oh well.
    if len(all_summaries) == 0:
        return {}
    elif len(all_summaries) == 1:
        return {k: v for k, v in all_summaries[0].items() if not needs_rerun(k, v)}
    new_summaries = {}
    for s in all_summaries:
        for key, value in s.items():
            if needs_rerun(key, value):
                continue
            k, _, run = key.partition("[")
            run, _, _ = run.partition("]")
            for i in range(1, 100):
                new_key = f"{k}[{i}]"
                if new_key in new_summaries:
                    if new_summaries[new_key] == value:  # this works 'cause it's POD
                        break  # already exists (probably; duration is fucked)
                    continue
                new_summaries[new_key] = value
                break
    return new_summaries


try:
    import numpy
except ModuleNotFoundError:
    pass
else:
    from utils_np import *