import os
import glob
import warnings
from itertools import chain

import astropy.units as u
from astropy.units import Quantity
from astropy.table import Table
from astropy.io import fits
from astropy.nddata import StdDevUncertainty, VarianceUncertainty, InverseVariance
from astropy.time import Time
from astropy.wcs import WCS
from gwcs.wcstools import grid_from_bounding_box

from ...spectra import Spectrum1D, SpectrumList
from ..registers import data_loader
from ..parsing_utils import read_fileobj_or_hdulist

__all__ = ["jwst_x1d_single_loader", "jwst_x1d_multi_loader", "jwst_x1d_miri_mrs_loader"]


def identify_jwst_miri_mrs(origin, *args, **kwargs):
    """
    Check whether the given set of files is a JWST MIRI MRS spectral data product.
    """
    input = args[2]

    # if string, it can be either a directory or a glob pattern (this last
    # one not implemented yet due to astropy choking when passed an invalid
    # file path string).
    if isinstance(input, str):
        if os.path.isdir(input):
            return True

        if len(glob.glob(input)) > 0:
            return True

    # or it can be either a list of file names, or a list of file objects
    elif isinstance(input, (list, tuple)) and len(input) > 0:
        return True

    return False


def _identify_spec1d_fits(origin, extname, *args, **kwargs):
    """ Generic spec 1d identifier function """
    is_jwst = _identify_jwst_fits(*args)
    with read_fileobj_or_hdulist(*args, memmap=False, **kwargs) as hdulist:
        return (is_jwst and extname in hdulist and (extname, 2) not in hdulist)


def _identify_spec1d_multi_fits(origin, extname, *args, **kwargs):
    """
    Check whether the given file is a JWST c1d/x1d spectral data product with many slits.
    """
    is_jwst = _identify_jwst_fits(*args)
    with read_fileobj_or_hdulist(*args, memmap=False, **kwargs) as hdulist:
        return is_jwst and (extname, 2) in hdulist


def identify_jwst_c1d_fits(origin, *args, **kwargs):
    """
    Check whether the given file is a JWST c1d spectral data product.
    """
    return _identify_spec1d_fits(origin, 'COMBINE1D', *args, **kwargs)


def identify_jwst_c1d_multi_fits(origin, *args, **kwargs):
    """
    Check whether the given file is a JWST c1d spectral data product with many slits.
    """
    return _identify_spec1d_multi_fits(origin, 'COMBINE1D', *args, **kwargs)


def identify_jwst_x1d_fits(origin, *args, **kwargs):
    """
    Check whether the given file is a JWST x1d spectral data product.
    """
    return _identify_spec1d_fits(origin, 'EXTRACT1D', *args, **kwargs)


def identify_jwst_x1d_multi_fits(origin, *args, **kwargs):
    """
    Check whether the given file is a JWST x1d spectral data product with many slits.
    """
    return _identify_spec1d_multi_fits(origin, 'EXTRACT1D', *args, **kwargs)


def identify_jwst_s2d_fits(origin, *args, **kwargs):
    """
    Check whether the given file is a JWST s2d spectral data product.
    """
    is_jwst = _identify_jwst_fits(*args)
    with read_fileobj_or_hdulist(*args, memmap=False, **kwargs) as hdulist:
        return (is_jwst and "SCI" in hdulist and ("SCI", 2) not in hdulist
                and "EXTRACT1D" not in hdulist and len(hdulist["SCI"].data.shape) == 2)


def identify_jwst_s2d_multi_fits(origin, *args, **kwargs):
    """
    Check whether the given file is a JWST s2d spectral data product with many slits.
    """
    is_jwst = _identify_jwst_fits(*args)
    with read_fileobj_or_hdulist(*args, memmap=False, **kwargs) as hdulist:
        return (is_jwst and ("SCI", 2) in hdulist and "EXTRACT1D" not in hdulist
                and len(hdulist["SCI"].data.shape) == 2)


def identify_jwst_s3d_fits(origin, *args, **kwargs):
    """
    Check whether the given file is a JWST s3d spectral data product.
    """
    is_jwst = _identify_jwst_fits(*args)
    with read_fileobj_or_hdulist(*args, memmap=False, **kwargs) as hdulist:
        return (is_jwst and "SCI" in hdulist and "EXTRACT1D" not in hdulist
                and len(hdulist["SCI"].data.shape) == 3)


def _identify_jwst_fits(*args):
    """
    Check whether the given file is a JWST data product.
    """
    try:
        with read_fileobj_or_hdulist(*args, memmap=False) as hdulist:
            return "ASDF" in hdulist and hdulist[0].header.get("TELESCOP") == "JWST"
    # This probably means we didn't have a FITS file
    except Exception:
        return False


@data_loader(
    "JWST c1d", identifier=identify_jwst_c1d_fits, dtype=Spectrum1D,
    extensions=['fits'], priority=10,
)
def jwst_c1d_single_loader(file_obj, **kwargs):
    """
    Loader for JWST c1d 1-D spectral data in FITS format

    Parameters
    ----------
    filename : str
        The path to the FITS file

    Returns
    -------
    Spectrum1D
        The spectrum contained in the file.
    """
    spectrum_list = _jwst_spec1d_loader(file_obj, extname='COMBINE1D', **kwargs)
    if len(spectrum_list) == 1:
        return spectrum_list[0]
    else:
        raise RuntimeError(f"Input data has {len(spectrum_list)} spectra. "
                           "Use SpectrumList.read() instead.")


@data_loader(
    "JWST c1d multi", identifier=identify_jwst_c1d_multi_fits,
    dtype=SpectrumList, extensions=['fits'], priority=10,
)
def jwst_c1d_multi_loader(file_obj, **kwargs):
    """
    Loader for JWST x1d 1-D spectral data in FITS format

    Parameters
    ----------
    file_obj: str, file-like, or HDUList
          FITS file name, object (provided from name by Astropy I/O Registry),
          or HDUList (as resulting from astropy.io.fits.open()).

    Returns
    -------
    SpectrumList
        A list of the spectra that are contained in the file.
    """
    return _jwst_spec1d_loader(file_obj, extname='COMBINE1D', **kwargs)


@data_loader(
    "JWST x1d", identifier=identify_jwst_x1d_fits, dtype=Spectrum1D,
    extensions=['fits'], priority=10
)
def jwst_x1d_single_loader(file_obj, **kwargs):
    """
    Loader for JWST x1d 1-D spectral data in FITS format

    Parameters
    ----------
    filename : str
        The path to the FITS file

    Returns
    -------
    Spectrum1D
        The spectrum contained in the file.
    """
    spectrum_list = _jwst_spec1d_loader(file_obj, extname='EXTRACT1D', **kwargs)
    if len(spectrum_list) == 1:
        return spectrum_list[0]
    else:
        raise RuntimeError(f"Input data has {len(spectrum_list)} spectra. "
                           "Use SpectrumList.read() instead.")


@data_loader(
    "JWST x1d multi", identifier=identify_jwst_x1d_multi_fits,
    dtype=SpectrumList, extensions=['fits'], priority=10,
)
def jwst_x1d_multi_loader(file_obj, **kwargs):
    """
    Loader for JWST x1d 1-D spectral data in FITS format

    Parameters
    ----------
    file_obj: str, file-like, or HDUList
          FITS file name, object (provided from name by Astropy I/O Registry),
          or HDUList (as resulting from astropy.io.fits.open()).

    Returns
    -------
    SpectrumList
        A list of the spectra that are contained in the file.
    """
    return _jwst_spec1d_loader(file_obj, extname='EXTRACT1D', **kwargs)


@data_loader(
    "JWST x1d MIRI MRS", identifier=identify_jwst_miri_mrs, dtype=SpectrumList,
    extensions=['*'], priority=10,
)
def jwst_x1d_miri_mrs_loader(input, missing="raise", **kwargs):
    """
    Loader for JWST x1d MIRI MRS spectral data in FITS format.

    A single data set consists of a bunch of _x1d files corresponding to
    a variety of wavelength bands. This reader reads them one by one and packs
    the result into a SpectrumList instance.

    Parameters
    ----------
    input : list of str or file-like
        List of FITS file names, or objects (provided from name by
        Astropy I/O Registry). Alternatively, a directory path on
        which glob.glob runs with pattern an implicit pattern "_x1d.fits",
        or a directory path with a glob pattern already set.
    missing : {'warn', 'silent'}
        Allows the user to continue loading if one file is missing by setting
        the value to "warn" or "silent". In the first case a warning will be issued
        to the user, in the latter the file will silently be skipped. Any other
        value will result in a FileNotFoundError if any files in the list are missing.

    Returns
    -------
    SpectrumList
        A list of the spectra that are contained in all the files.
    """

    # If input is a list, go read each file. If directory, glob-expand
    # list of file names.
    if not isinstance(input, (list, tuple)):
        if os.path.isdir(input):
            file_list = glob.glob(os.path.join(input, "*_x1d.fits"), recursive=True)
        else:
            file_list = glob.glob(input, recursive=True)
    else:
        file_list = input

    spectra = []
    for file_obj in file_list:
        try:
            sp = _jwst_spec1d_loader(file_obj, **kwargs)
        except FileNotFoundError as e:
            if missing.lower() == "warn":
                warnings.warn(f'Failed to load {file_obj}: {repr(e)}')
                continue
            elif missing.lower() == "silent":
                continue
            else:
                raise FileNotFoundError(f"Failed to load {file_obj}: {repr(e)}. "
                                        "To suppress this error, set argument missing='warn'")

        spectra.append(sp)

    # the call to `chain.from_iterable` allows us to handle multiple HDUs
    # stored within multiple FITS files, all unpacked into one `SpectrumList`
    return SpectrumList(chain.from_iterable(spectra))


def _jwst_spec1d_loader(file_obj, extname='EXTRACT1D', **kwargs):
    """Implementation of loader for JWST x1d 1-D spectral data in FITS format

    Parameters
    ----------
    file_obj: str, file-like, or HDUList
          FITS file name, object (provided from name by Astropy I/O Registry),
          or HDUList (as resulting from astropy.io.fits.open()).
    extname: str
        The name of the science extension. Either "COMBINE1D" or "EXTRACT1D".  By default "EXTRACT1D".

    Returns
    -------
    SpectrumList
        A list of the spectra that are contained in the file.
    """

    if extname not in ['COMBINE1D', 'EXTRACT1D']:
        raise ValueError('Incorrect extname given for 1d spectral data.')

    spectra = []

    with read_fileobj_or_hdulist(file_obj, memmap=False, **kwargs) as hdulist:

        primary_header = hdulist["PRIMARY"].header

        for hdu in hdulist:
            # Read only the BinaryTableHDUs named COMBINE1D/EXTRACT1D and SCI
            if hdu.name != extname:
                continue

            # Correct some known bad unit strings before reading the table
            bad_units = {"(MJy/sr)^2": "MJy2 sr-2"}
            for c in hdu.columns:
                if c.unit in bad_units:
                    c.unit = bad_units[c.unit]

            data = Table.read(hdu)

            wavelength = Quantity(data["WAVELENGTH"])

            # Determine if FLUX or SURF_BRIGHT column should be returned
            # based on whether it is point or extended source.
            #
            # SRCTYPE used to be in primary header, but was moved around. As
            # per most recent pipeline definition, it should be in the
            # EXTRACT1D extension.
            #
            # SRCTYPE should either be POINT or EXTENDED.  In some cases, it is UNKNOWN
            # or missing.  If that's the case, default to using POINT as the SRCTYPE.
            # Error out only when SRCTYPE is a bad value.
            srctype = None
            if "srctype" in hdu.header:
                srctype = hdu.header.get("srctype", None)

            # checking if SRCTPYE is missing or UNKNOWN
            if not srctype or srctype == 'UNKNOWN':
                warnings.warn('SRCTYPE is missing or UNKNOWN in JWST x1d loader. '
                              'Defaulting to srctype="POINT".')
                srctype = 'POINT'

            if srctype == "POINT":
                flux = Quantity(data["FLUX"])
                if 'ERROR' in data.colnames:
                    uncertainty = StdDevUncertainty(data["ERROR"])
                elif 'FLUX_ERROR' in data.colnames:
                    uncertainty = StdDevUncertainty(data["FLUX_ERROR"])
                else:
                    uncertainty = None
            elif srctype == "EXTENDED":
                flux = Quantity(data["SURF_BRIGHT"])
                uncertainty = StdDevUncertainty(data["SB_ERROR"])
            else:
                raise RuntimeError(f"Keyword SRCTYPE is {srctype}.  It should "
                                   "be 'POINT' or 'EXTENDED'. Can't decide between `flux` and "
                                   "`surf_bright` columns.")

            # Merge primary and slit headers and dump into meta
            slit_header = hdu.header
            header = primary_header.copy()
            header.extend(slit_header, strip=True, update=True)
            meta = {'header': header}

            spec = Spectrum1D(flux=flux, spectral_axis=wavelength,
                              uncertainty=uncertainty, meta=meta)
            spectra.append(spec)

    return SpectrumList(spectra)


@data_loader(
    "JWST s2d", identifier=identify_jwst_s2d_fits, dtype=Spectrum1D,
    extensions=['fits'], priority=10,
)
def jwst_s2d_single_loader(filename, **kwargs):
    """
    Loader for JWST s2d 2D rectified spectral data in FITS format.

    Parameters
    ----------
    filename : str
        The path to the FITS file

    Returns
    -------
    Spectrum1D
        The spectrum contained in the file.
    """
    spectrum_list = _jwst_s2d_loader(filename, **kwargs)
    if len(spectrum_list) == 1:
        return spectrum_list[0]
    elif len(spectrum_list) > 1:
        raise RuntimeError(f"Input data has {len(spectrum_list)} spectra. "
                           "Use SpectrumList.read() instead.")
    else:
        raise RuntimeError(f"Input data has {len(spectrum_list)} spectra.")


@data_loader(
    "JWST s2d multi", identifier=identify_jwst_s2d_multi_fits,
    dtype=SpectrumList, extensions=['fits'], priority=10,
)
def jwst_s2d_multi_loader(filename, **kwargs):
    """
    Loader for JWST s2d 2D rectified spectral data in FITS format.

    Parameters
    ----------
    filename : str
        The path to the FITS file

    Returns
    -------
    SpectrumList
        The spectra contained in the file.
    """
    return _jwst_s2d_loader(filename, **kwargs)


def _jwst_s2d_loader(filename, **kwargs):
    """
    Loader for JWST s2d 2D rectified spectral data in FITS format.

    Parameters
    ----------
    filename : str
        The path to the FITS file

    Returns
    -------
    SpectrumList
        The spectra contained in the file.
    """
    from stdatamodels import asdf_in_fits

    spectra = []
    slits = None

    # Get a list of GWCS objects from the slits
    with asdf_in_fits.open(filename) as af:
        # Slits can be listed under "slits", "products" or "exposures"
        if "products" in af.tree:
            slits = "products"
        elif "exposures" in af.tree:
            slits = "exposures"
        elif "slits" in af.tree:
            slits = "slits"
        else:
            # No slits.  Case for s3d cubes
            wcslist = [af.tree["meta"]["wcs"]]

        # Create list of the GWCS objects, one for each slit
        if slits is not None:
            wcslist = [slit["meta"]["wcs"] for slit in af.tree[slits]]

    with fits.open(filename, memmap=False) as hdulist:

        primary_header = hdulist["PRIMARY"].header

        hdulist_sci = [hdu for hdu in hdulist if hdu.name == "SCI"]

        for hdu, wcs in zip(hdulist_sci, wcslist):
            # Get flux
            try:
                flux_unit = u.Unit(hdu.header["BUNIT"])
            except (ValueError, KeyError):
                flux_unit = None

            # The dispersion axis is 1 or 2.  1=x, 2=y.
            dispaxis = hdu.header.get("DISPAXIS")
            if dispaxis is None:
                dispaxis = hdulist["PRIMARY"].header.get("DISPAXIS")

            # Get the wavelength array from the GWCS object which returns a
            # tuple of (RA, Dec, lambda)
            grid = grid_from_bounding_box(wcs.bounding_box)
            _, _, lam = wcs(*grid)
            _, _, lam_unit = wcs.output_frame.unit

            # Make sure the dispersion axis is the same for every spatial axis
            # for s2d data
            if dispaxis == 1:
                flux_array = hdu.data
                wavelength_array = lam[0]
                # Make sure all rows are the same
                if not (lam == wavelength_array).all():
                    raise RuntimeError("This 2D or 3D spectrum is not rectified "
                                       "and cannot be loaded into a Spectrum1D object.")
            elif dispaxis == 2:
                flux_array = hdu.data.T
                wavelength_array = lam[:, 0]
                # Make sure all columns are the same
                if not (lam.T == lam[None, :, 0]).all():
                    raise RuntimeError("This 2D or 3D spectrum is not rectified "
                                       "and cannot be loaded into a Spectrum1D object.")
            else:
                raise RuntimeError("This 2D spectrum has an unknown dispaxis "
                                   "and cannot be loaded into a Spectrum1D object.")

            flux = Quantity(flux_array, unit=flux_unit)
            wavelength = Quantity(wavelength_array, unit=lam_unit)

            # Merge primary and slit headers and dump into meta
            slit_header = hdu.header
            header = primary_header.copy()
            header.extend(slit_header, strip=True, update=True)
            meta = {'header': header}

            spec = Spectrum1D(flux=flux, spectral_axis=wavelength, meta=meta)
            spectra.append(spec)

    return SpectrumList(spectra)


@data_loader(
    "JWST s3d", identifier=identify_jwst_s3d_fits, dtype=Spectrum1D,
    extensions=['fits'], priority=10,
)
def jwst_s3d_single_loader(filename, **kwargs):
    """
    Loader for JWST s3d 3D rectified spectral data in FITS format.

    Parameters
    ----------
    filename : str
        The path to the FITS file

    Returns
    -------
    Spectrum1D
        The spectrum contained in the file.
    """
    spectrum_list = _jwst_s3d_loader(filename, **kwargs)
    if len(spectrum_list) == 1:
        return spectrum_list[0]
    elif len(spectrum_list) > 1:
        raise RuntimeError(f"Input data has {len(spectrum_list)} spectra. "
                           "Use SpectrumList.read() instead.")
    else:
        raise RuntimeError(f"Input data has {len(spectrum_list)} spectra.")


def _jwst_s3d_loader(filename, **kwargs):
    """
    Loader for JWST s3d 3D rectified spectral data in FITS format.

    Parameters
    ----------
    filename : str
        The path to the FITS file

    Returns
    -------
    SpectrumList
        The spectra contained in the file.
    """
    from stdatamodels import asdf_in_fits

    spectra = []

    # Get a list of GWCS objects from the slits
    with asdf_in_fits.open(filename) as af:
        wcslist = [af.tree["meta"]["wcs"]]

    with fits.open(filename, memmap=False) as hdulist:

        primary_header = hdulist["PRIMARY"].header

        hdulist_sci = [hdu for hdu in hdulist if hdu.name == "SCI"]

        for hdu, wcs in zip(hdulist_sci, wcslist):
            # Get flux
            try:
                flux_unit = u.Unit(hdu.header["BUNIT"])
            except (ValueError, KeyError):
                flux_unit = None

            # The spectral axis is first.  We need it last
            flux_array = hdu.data.T
            flux = Quantity(flux_array, unit=flux_unit)

            # Get the wavelength array from the GWCS object which returns a
            # tuple of (RA, Dec, lambda).
            # Since the spatial and spectral axes are orthogonal in s3d data,
            # it is much faster to compute a slice down the spectral axis.
            grid = grid_from_bounding_box(wcs.bounding_box)[:, :, 0, 0]
            _, _, wavelength_array = wcs(*grid)
            _, _, wavelength_unit = wcs.output_frame.unit

            wavelength = Quantity(wavelength_array, unit=wavelength_unit)

            # The GWCS is currently broken for some IFUs, here we work around that
            wcs = None
            if wavelength.shape[0] != flux.shape[-1]:
                # Need MJD-OBS for this workaround
                if 'MJD-OBS' not in hdu.header:
                    for key in ('MJD-BEG', 'DATE-OBS'):  # Possible alternatives
                        if key in hdu.header:
                            if key.startswith('MJD'):
                                hdu.header['MJD-OBS'] = hdu.header[key]
                                break
                            else:
                                t = Time(hdu.header[key])
                                hdu.header['MJD-OBS'] = t.mjd
                                break
                wcs = WCS(hdu.header)
                # Swap to match the flux transpose
                wcs = wcs.swapaxes(-1, 0)

            # Merge primary and slit headers and dump into meta
            slit_header = hdu.header
            header = primary_header.copy()
            header.extend(slit_header, strip=True, update=True)
            meta = {'header': header}

            # get uncertainty information
            ext_name = primary_header.get("ERREXT", "ERR")
            err_type = hdulist[ext_name].header.get("ERRTYPE", 'ERR')
            err_unit = hdulist[ext_name].header.get("BUNIT", None)
            err_array = hdulist[ext_name].data.T

            # ERRTYPE can be one of "ERR", "IERR", "VAR", "IVAR"
            # but mostly ERR for JWST cubes
            # see https://jwst-pipeline.readthedocs.io/en/latest/jwst/data_products/science_products.html#s3d
            if err_type == "ERR":
                err = StdDevUncertainty(err_array, unit=err_unit)
            elif err_type == 'VAR':
                err = VarianceUncertainty(err_array, unit=err_unit)
            elif err_type == 'IVAR':
                err = InverseVariance(err_array, unit=err_unit)
            elif err_type == 'IERR':
                warnings.warn("Inverse error is not yet a supported astropy.nddata "
                              "uncertainty. Setting err to None.")
                err = None

            # get mask information
            mask_name = primary_header.get("MASKEXT", "DQ")
            mask = hdulist[mask_name].data.T

            if wcs is not None:
                spec = Spectrum1D(flux=flux, wcs=wcs, meta=meta, uncertainty=err, mask=mask)
            else:
                spec = Spectrum1D(flux=flux, spectral_axis=wavelength, meta=meta,
                                  uncertainty=err, mask=mask)
            spectra.append(spec)

    return SpectrumList(spectra)
