"""Enumerations."""

from enum import Enum, IntEnum

class TransformDirection(IntEnum):
    """Coordinate transform direction
    
    Forward transform direction defined as image pixel (row, col) to 
    geographic/projected (x, y) coordinates. Reverse transform direction defined as
    geographic/projected (x, y) to image pixel (row, col) coordinates.

    Notes
    -----
    The convention for transform direction for RPC based coordinate transform is
    typically the opposite of what is previously described. For consistency
    all coordinate transforms methods use the same convention.
    """
    forward = 1
    reverse = 0

class TransformMethod(Enum):
    affine = 'transform'
    gcps = 'gcps'
    rpcs = 'rpcs'

class ColorInterp(IntEnum):
    """Raster band color interpretation."""
    undefined = 0
    gray = 1
    grey = 1
    palette = 2
    red = 3
    green = 4
    blue = 5
    alpha = 6
    hue = 7
    saturation = 8
    lightness = 9
    cyan = 10
    magenta = 11
    yellow = 12
    black = 13
    Y = 14
    Cb = 15
    Cr = 16


class Resampling(IntEnum):
    """Available warp resampling algorithms.
    
    Attributes
    ----------
    nearest
        Nearest neighbor resampling (default, fastest algorithm, worst interpolation quality).
    bilinear
        Bilinear resampling.
    cubic
        Cubic resampling.
    cubic_spline
        Cubic spline resampling.
    lanczos
        Lanczos windowed sinc resampling.
    average
        Average resampling, computes the weighted average of all non-NODATA contributing pixels.
    mode
        Mode resampling, selects the value which appears most often of all the sampled points.
    gauss
        Gaussian resampling, Note: not available to the functions in rio.warp.
    max
        Maximum resampling, selects the maximum value from all non-NODATA contributing pixels. (GDAL >= 2.0)
    min
        Minimum resampling, selects the minimum value from all non-NODATA contributing pixels. (GDAL >= 2.0)
    med
        Median resampling, selects the median value of all non-NODATA contributing pixels. (GDAL >= 2.0)
    q1
        Q1, first quartile resampling, selects the first quartile value of all non-NODATA contributing pixels. (GDAL >= 2.0)
    q3
        Q3, third quartile resampling, selects the third quartile value of all non-NODATA contributing pixels. (GDAL >= 2.0)
    sum
        Sum, compute the weighted sum of all non-NODATA contributing pixels. (GDAL >= 3.1)
    rms
        RMS, root mean square / quadratic mean of all non-NODATA contributing pixels. (GDAL >= 3.3)
    
    Notes
    ----------
    The first 8, 'nearest', 'bilinear', 'cubic', 'cubic_spline',
    'lanczos', 'average', 'mode', and 'gauss', are available for making
    dataset overviews.

    'max', 'min', 'med', 'q1', 'q3' are only supported in GDAL >= 2.0.0.

    'nearest', 'bilinear', 'cubic', 'cubic_spline', 'lanczos',
    'average', 'mode' are always available (GDAL >= 1.10).

    'sum' is only supported in GDAL >= 3.1.

    'rms' is only supported in GDAL >= 3.3.

    Note: 'gauss' is not available to the functions in rio.warp.
    """
    nearest = 0
    bilinear = 1
    cubic = 2
    cubic_spline = 3
    lanczos = 4
    average = 5
    mode = 6
    gauss = 7
    max = 8
    min = 9
    med = 10
    q1 = 11
    q3 = 12
    sum = 13
    rms = 14


class _OverviewResampling(IntEnum):
    """Available Overview resampling algorithms.

    The first 8, 'nearest', 'bilinear', 'cubic', 'cubic_spline',
    'lanczos', 'average', 'mode', and 'gauss', are available for making
    dataset overviews.

    'nearest', 'bilinear', 'cubic', 'cubic_spline', 'lanczos',
    'average', 'mode' are always available (GDAL >= 1.10).

    'rms' is only supported in GDAL >= 3.3.

    """
    nearest = 0
    bilinear = 1
    cubic = 2
    cubic_spline = 3
    lanczos = 4
    average = 5
    mode = 6
    gauss = 7
    rms = 14


class Compression(Enum):
    """Available compression algorithms."""
    jpeg = 'JPEG'
    lzw = 'LZW'
    packbits = 'PACKBITS'
    deflate = 'DEFLATE'
    ccittrle = 'CCITTRLE'
    ccittfax3 = 'CCITTFAX3'
    ccittfax4 = 'CCITTFAX4'
    lzma = 'LZMA'
    none = 'NONE'
    zstd = 'ZSTD'
    lerc = 'LERC'
    lerc_deflate = 'LERC_DEFLATE'
    lerc_zstd = 'LERC_ZSTD'
    webp = 'WEBP'
    jpeg2000 = 'JPEG2000'


class Interleaving(Enum):
    pixel = 'PIXEL'
    line = 'LINE'
    band = 'BAND'


class MaskFlags(IntEnum):
    all_valid = 1
    per_dataset = 2
    alpha = 4
    nodata = 8


class PhotometricInterp(Enum):
    black = 'MINISBLACK'
    white = 'MINISWHITE'
    rgb = 'RGB'
    cmyk = 'CMYK'
    ycbcr = 'YCbCr'
    cielab = 'CIELAB'
    icclab = 'ICCLAB'
    itulab = 'ITULAB'


class MergeAlg(Enum):
    """Available rasterization algorithms"""
    replace = 'REPLACE'
    add = 'ADD'


class WktVersion(Enum):
    """
     .. versionadded:: 1.3.0

    Supported CRS WKT string versions
    """

    #: WKT Version 2 from 2015
    WKT2_2015 = "WKT2_2015"
    #: Alias for latest WKT Version 2
    WKT2 = "WKT2"
    #: WKT Version 2 from 2019
    WKT2_2019 = "WKT2_2018"
    #: WKT Version 1 GDAL Style
    WKT1_GDAL = "WKT1_GDAL"
    #: Alias for WKT Version 1 GDAL Style
    WKT1 = "WKT1"
    #: WKT Version 1 ESRI Style
    WKT1_ESRI = "WKT1_ESRI"


    @classmethod
    def _missing_(cls, value):
        if value == "WKT2_2019":
            # WKT2_2019 alias added in GDAL 3.2, use WKT2_2018 for compatibility
            return WktVersion.WKT2_2019
        raise ValueError(f"Invalid value for WktVersion: {value}")