Gets or sets an image's mask.

    The output image retains the metadata and footprint of the input image.
    Pixels where the mask changes from zero to another value will be filled with
    zeros, or the values closest to zero within the range of the pixel type.

    Note: the version that sets a mask will be deprecated. To set a mask from an
    image on previously unmasked pixels, use Image.updateMask. To unmask
    previously masked pixels, use Image.unmask.

    Args:
      mask: The mask image. If specified, the input image is copied to the
        output but given the mask by the values of this image. If this is a
        single band, it is used for all bands in the input image. If not
        specified, returns an image created from the mask of the input image,
        scaled to the range [0:1] (invalid = 0, valid = 1.0).

    Returns:
      An ee.Image.


Calculates the Cholesky decomposition of a matrix.

    The Cholesky decomposition is a decomposition into the form L * L' where L
    is a lower triangular matrix. The input must be a symmetric
    positive-definite matrix. Returns an image with 1 band named 'L'.

    Returns:
      An ee.Image.


Computes the determinant of the matrix.


Returns an image where each pixel is a 2D identity matrix of size.

    Args:
      size: The length of each axis.


Calculates the LU matrix decomposition.

    Calculates the LU matrix decomposition such that Pxinput=LxU, where L is
    lower triangular (with unit diagonal terms), U is upper triangular and P is
    a partial pivot permutation matrix.

    The input matrix must be square. Returns an image with bands named 'L', 'U'
    and 'P'.

    Returns:
      An ee.Image.


Returns the matrix multiplication with image2.

    Returns the matrix multiplication A * B for each matched pair of bands in
    image1 and image2. If either image1 or image2 has only 1 band, then it is
    used against all the bands in the other image. If the images have the same
    number of bands, but not the same names, they're used pairwise in the
    natural order. The output bands are named for the longer of the two inputs,
    or if they're equal in length, in image1's order. The type of the output
    pixels is the union of the input types.

    Args:
      image2: The image from which the right operand bands are taken.


Computes the Moore-Penrose pseudoinverse of the matrix.


Calculates the QR-decomposition of a matrix.

    Calculates the QR-decomposition of a matrix into two matrices Q and R such
    that input = QR, where Q is orthogonal, and R is upper triangular.

    Returns an image with bands named 'Q' and 'R'.

    Returns:
      An ee.Image.


Calculates the Singular Value Decomposition.

    Calculates the Singular Value Decomposition of the input matrix into UxSxV',
    such that U and V are orthogonal and S is diagonal.

    Returns:
      An image with bands named 'U', 'S' and 'V'.


Returns the solution for x in the matrix equation A * x = B.

    Solves for x in the matrix equation A * x = B, finding a least-squares
    solution if A is overdetermined for each matched pair of bands in image1 and
    image2. If either image1 or image2 has only 1 band, then it is used against
    all the bands in the other image. If the images have the same number of
    bands, but not the same names, they're used pairwise in the natural order.
    The output bands are named for the longer of the two inputs, or if they're
    equal in length, in image1's order. The type of the output pixels is the
    union of the input types.

    Args:
      image2: The image from which the right operand bands are taken.

    Returns:
      An ee.Image.


Returns the maximum of the image or image2.

    Selects the maximum of the first and second values for each matched pair of
    bands in image1 and image2. If either image1 or image2 has only 1 band, then
    it is used against all the bands in the other image. If the images have the
    same number of bands, but not the same names, they're used pairwise in the
    natural order. The output bands are named for the longer of the two inputs,
    or if they're equal in length, in image1's order. The type of the output
    pixels is the union of the input types.

    Args:
      image2: The image from which the right operand bands are taken.

    Returns:
      An ee.Image.


Returns the discrete medial axis of the input image.

    Computes the discrete medial axis of the zero valued pixels of the first
    band of the input. Outputs 4 bands:

    * medial - the medial axis points, scaled by the distance.
    * coverage - the number of points supporting each medial axis point.
    * xlabel - the horizontal distance to the power point for each pixel.
    * ylabel - the vertical distance to the power point for each pixel.

    Args:
      neighborhood: Neighborhood size in pixels.
      units: The units of the neighborhood, currently only 'pixels' are
        supported.

    Returns:
      An ee.Image.


Generates a constant image of type double from a metadata property.

    Args:
      property: The property from which to take the value.
      name: The name for the output band. If unspecified, it will be the same as
        the property name.

    Returns:
      An ee.Image.


Returns the minimum of the image or image2.

    Selects the minimum of the first and second values for each matched pair of
    bands in image1 and image2. If either image1 or image2 has only 1 band, then
    it is used against all the bands in the other image. If the images have the
    same number of bands, but not the same names, they're used pairwise in the
    natural order. The output bands are named for the longer of the two inputs,
    or if they're equal in length, in image1's order. The type of the output
    pixels is the union of the input types.

    Args:
      image2: The image from which the right operand bands are taken.


Returns the remainder of the image divided by the second (modulus).

    Calculates the remainder of the first value divided by the second for each
    matched pair of bands in image1 and image2. If either image1 or image2 has
    only 1 band, then it is used against all the bands in the other image. If
    the images have the same number of bands, but not the same names, they're
    used pairwise in the natural order. The output bands are named for the
    longer of the two inputs, or if they're equal in length, in image1's order.
    The type of the output pixels is the union of the input types.

    Args:
      image2: The image from which the right operand bands are taken.


Returns the image multiplied by image2.

    Multiplies the first value by the second for each matched pair of bands in
    image1 and image2. If either image1 or image2 has only 1 band, then it is
    used against all the bands in the other image. If the images have the same
    number of bands, but not the same names, they're used pairwise in the
    natural order. The output bands are named for the longer of the two inputs,
    or if they're equal in length, in image1's order. The type of the output
    pixels is the union of the input types.

    Args:
      image2: The image from which the right operand bands are taken.


Turns the neighborhood of each pixel in a scalar image into a 2D array.

    Axes 0 and 1 of the output array correspond to Y and X axes of the image,
    respectively. The output image will have as many bands as the input; each
    output band has the same mask as the corresponding input band. The footprint
    and metadata of the input image are preserved.

    Args:
      kernel: The kernel specifying the shape of the neighborhood. Only fixed,
        square and rectangle kernels are supported. Weights are ignored; only
        the shape of the kernel is used.
      defaultValue: The value to use in the output arrays to replace the invalid
        (masked) pixels of the input. If the band type is integral, the
        fractional part of this value is discarded; in all cases, the value is
        clamped to the value range of the band.

    Returns:
      An ee.Image.


Turns the neighborhood of a pixel into a set of bands.

    The neighborhood is specified using a Kernel and only non-zero-weight
    kernel values are used. The weights of the kernel is otherwise ignored.

    Each input band produces x * y output bands. Each output band is named
    'input_x_y' where x and y indicate the pixel's location in the kernel. For
    example, a 3x3 kernel operating on a 2-band image produces 18 output bands.

    Args:
      kernel: The kernel specifying the neighborhood. Zero-weight values are
        ignored.

    Returns:
      An ee.Image.


Returns 1 if the pixel in the image is not equal to the pixel in image2.

    Returns 1 if and only if the first value is not equal to the second for each
    matched pair of bands in image1 and image2. If either image1 or image2 has
    only 1 band, then it is used against all the bands in the other image. If
    the images have the same number of bands, but not the same names, they're
    used pairwise in the natural order. The output bands are named for the
    longer of the two inputs, or if they're equal in length, in image1's order.
    The type of the output pixels is boolean.

    Args:
      image2: The image from which the right operand bands are taken.


Returns 1 if the pixel in either image is non-zero, and 0 otherwise.

    Returns 1 if and only if either input value is non-zero for each matched
    pair of bands in image1 and image2. If either image1 or image2 has only 1
    band, then it is used against all the bands in the other image. If the
    images have the same number of bands, but not the same names, they're used
    pairwise in the natural order. The output bands are named for the longer of
    the two inputs, or if they're equal in length, in image1's order. The type
    of the output pixels is boolean.

    Args:
      image2: The image from which the right operand bands are taken.


Returns an image with the geometries of a collection painted onto it.

    Paints the geometries of a collection onto an image, using the given 'color'
    value to replace each band's values where any geometry covers the image (or,
    if a line width is specified, where the perimeters do).

    This algorithm is most suitable for converting categorical data from feature
    properties to pixels in an image; if you wish to visualize a collection,
    consider using FeatureCollection.style instead, which supports RGB colors
    whereas this algorithm is strictly 'monochrome' (using single numeric
    values).

    Args:
      featureCollection: The collection painted onto the image.
      color: The pixel value to paint into every band of the input image, either
        as a number which will be used for all features, or the name of a
        numeric property to take from each feature in the collection.
      width: Line width, either as a number which will be the line width for all
        geometries, or the name of a numeric property to take from each feature
        in the collection. If unspecified, the geometries will be filled instead
        of outlined.


Returns an image with the value of each pixel in square meters.

    Returns an image in which the value of each pixel is the area of that pixel
    in square meters.

    The returned image has a single band called "area."


Returns the x and y coordinates of each pixel in the given projection.

    Creates a two-band image containing the x and y coordinates of each pixel in
    the given projection.

    Args:
      projection: The projection in which to provide pixels.


Returns an image with two bands named 'longitude' and 'latitude'.

    The result at each pixel is in degrees.


Compute a polynomial at each pixel using the given coefficients.

    Args:
      coefficients: The polynomial coefficients in increasing order of degree
        starting with the constant term.

    Returns:
      An ee.Image.


Returns an Image with image to the power of image2.

    Raises the first value to the power of the second for each matched pair of
    bands in image1 and image2. If either image1 or image2 has only 1 band, then
    it is used against all the bands in the other image. If the images have the
    same number of bands, but not the same names, they're used pairwise in the
    natural order. The output bands are named for the longer of the two inputs,
    or if they're equal in length, in image1's order. The type of the output
    pixels is float.

    Args:
      image2: The image from which the right operand bands are taken.


Returns the default projection of an Image.

    Throws an error if the bands of the image don't all have the same
    projection.


Returns an image with a random number at each pixel location.

    When using the 'uniform' distribution, outputs are in the range of [0, 1).
    Using the 'normal' distribution, the outputs have mu=0, sigma=1, but no
    explicit limits.

    Args:
      seed: Seed for the random number generator.
      distribution: The distribution type of random numbers to produce. One of
        'uniform' or 'normal'.


Returns a random visualization image.

    Creates a visualization image by assigning a random color to each unique
    value of the pixels of the first band.

    The first three bands of the output image will contain 8-bit R, G and B
    values, followed by all bands of the input image.


Applies a reducer to all of the bands of an image.

    The reducer must have a single input and will be called at each pixel to
    reduce the stack of band values.

    The output image will have one band for each reducer output.

    Args:
      reducer: The reducer to apply to the given image.

    Returns:
      An ee.Image.


Applies a reducer to all of the pixels inside of each 'object'.

    Pixels are considered to belong to an object if they are connected (8-way)
    and have the same value in the 'label' band. The label band is only used to
    identify the connectedness; the rest are provided as inputs to the reducer.

    Args:
      reducer: The reducer to apply to pixels within the connected component.
      labelBand: The name of the band to use to detect connectedness. If
        unspecified, the first band is used.
      maxSize: Size of the neighborhood to consider when aggregating values. Any
        objects larger than maxSize in either the horizontal or vertical
        dimension will be masked, since portions of the object might be outside
        of the neighborhood.

    Returns:
      An ee.Image.


Returns an ee.Image with the reducer applied as determined by the kernel.

    Applies the given reducer to the neighborhood around each pixel, as
    determined by the given kernel. If the reducer has a single input, it
    will be applied separately to each band of the collection; otherwise it
    must have the same number of inputs as the input image has bands.

    The reducer output names determine the names of the output bands: reducers
    with multiple inputs will use the output names directly, while reducers with
    a single input will prefix the output name with the input band name (e.g.,
    '10_mean', '20_mean').
    Reducers with weighted inputs can have the input weight based on the input
    mask, the kernel value, or the smaller of those two.

    Args:
      reducer: The reducer to apply to pixels within the neighborhood.
      kernel: The kernel defining the neighborhood.
      inputWeight: One of 'mask', 'kernel', or 'min'.
      skipMasked: Mask output pixels if the corresponding input pixel is masked.
      optimization: Optimization strategy. Options are 'boxcar' and 'window'.
        The 'boxcar' method is a fast method for computing count, sum or mean.
        It requires a homogeneous kernel, a single-input reducer and either
        MASK, KERNEL or no weighting. The 'window' method uses a running window,
        and has the same requirements as 'boxcar', but can use any single input
        reducer. Both methods require considerable additional memory.


Apply a reducer to all the pixels in a specific region.

    Either the reducer must have the same number of inputs as the input image
    has bands, or it must have a single input and will be repeated for each
    band.

    Args:
      reducer: The reducer to apply.
      geometry: The region over which to reduce data. Defaults to the footprint
        of the image's first band.
      scale: A nominal scale in meters of the projection to work in.
      crs: The projection to work in. If unspecified, the projection of the
        image's first band is used. If specified in addition to scale, rescaled
        to the specified scale.
      crsTransform: The list of CRS transform values. This is a row-major
        ordering of the 3x2 transform matrix. This option is mutually exclusive
        with 'scale', and replaces any transform already set on the projection.
      bestEffort: If the polygon would contain too many pixels at the given
        scale, compute and use a larger scale which would allow the operation to
        succeed.
      maxPixels: The maximum number of pixels to reduce.
      tileScale: A scaling factor between 0.1 and 16 used to adjust aggregation
        tile size; setting a larger tileScale (e.g., 2 or 4) uses smaller tiles
        and may enable computations that run out of memory with the default.

    Returns:
      An ee.Dictionary of the reducer's outputs.


Apply a reducer over the area of each feature in the given collection.

    The reducer must have the same number of inputs as the input image has
    bands.

    Args:
      collection: The features to reduce over.
      reducer: The reducer to apply.
      scale: A nominal scale in meters of the projection to work in.
      crs: The projection to work in. If unspecified, the projection of the
        image's first band is used. If specified in addition to scale, rescaled
        to the specified scale.
      crsTransform: The list of CRS transform values. This is a row-major
        ordering of the 3x2 transform matrix. This option is mutually exclusive
        with 'scale', and will replace any transform already set on the
        projection.
      tileScale: A scaling factor used to reduce aggregation tile size; using a
        larger tileScale (e.g., 2 or 4) may enable computations that run out of
        memory with the default.
      maxPixelsPerRegion: The maximum number of pixels to reduce per region.

    Returns:
      Returns the input ee.FeatureCollection, each augmented with the
      corresponding reducer outputs.


Returns an ee.Image with the reducer applied to combine all input pixels.

    Enables reprojection using the given reducer to combine all input pixels
    corresponding to each output pixel. If the reducer has a single input, it
    will be applied separately to each band of the collection; otherwise it must
    have the same number of inputs as the input image has bands.

    The reducer output names determine the names of the output bands: reducers
    with multiple inputs will use the output names directly, reducers with a
    single input and single output will preserve the input band names, and
    reducers with a single input and multiple outputs will prefix the output
    name with the input band name (e.g., '10_mean', '10_stdDev', '20_mean',
    '20_stdDev').

    Reducer input weights will be the product of the  input mask and the
    fraction of the output pixel covered by the input pixel.

    Args:
      reducer: The reducer to apply to be used for combining pixels.
      bestEffort: If using the input at its default resolution would require too
        many pixels, start with already-reduced input pixels from a pyramid
        level that allows the operation to succeed.
      maxPixels: The maximum number of input pixels to combine for each output
        pixel. Setting this too large will cause out-of-memory problems.


Convert an image to a feature collection by reducing homogeneous regions.

    Given an image containing a band of labeled segments and zero or more
    additional bands, runs a reducer over the pixels in each segment producing a
    feature per segment.

    Either the reducer must have one fewer inputs than the image has bands, or
    it must have a single input and will be repeated for each band.

    Args:
      reducer: The reducer to apply. Its inputs will be taken from the image's
        bands after dropping the first band. Defaults to Reducer.countEvery()
      geometry: The region over which to reduce data. Defaults to the footprint
        of the image's first band.
      scale: A nominal scale in meters of the projection to work in.
      geometryType: How to choose the geometry of each generated feature; one of
        'polygon' (a polygon enclosing the pixels in the segment), 'bb' (a
        rectangle bounding the pixels), or 'centroid' (the centroid of the
        pixels).
      eightConnected: If true, diagonally-connected pixels are considered
        adjacent; otherwise only pixels that share an edge are.
      labelProperty: If non-null, the value of the first band will be saved as
        the specified property of each feature.
      crs: The projection to work in. If unspecified, the projection of the
        image's first band is used. If specified in addition to scale, rescaled
        to the specified scale.
      crsTransform: The list of CRS transform values. This is a row-major
        ordering of the 3x2 transform matrix. This option is mutually exclusive
        with 'scale', and replaces any transform already set on the projection.
      bestEffort: If the polygon would contain too many pixels at the given
        scale, compute and use a larger scale which would allow the operation to
        succeed.
      maxPixels: The maximum number of pixels to reduce.
      tileScale: A scaling factor used to reduce aggregation tile size; using a
        larger tileScale (e.g., 2 or 4) may enable computations that run out of
        memory with the default.
      geometryInNativeProjection: Create geometries in the pixel projection,
        rather than WGS84.

    Returns:
      An ee.FeatureCollection.


Renames the bands of an image.

    Renames the bands of an image by applying a regular expression replacement
    to the current band names. Any bands not matched by the regex will be copied
    over without renaming.

    Args:
      regex: A regular expression to match in each band name.
      replacement: The text with which to replace each match. Supports $n syntax
        for captured values.
      all: If true, all matches in a given string will be replaced. Otherwise,
        only the first match in each string will be replaced.

    Returns:
      An ee.Image.


Registers an image to a reference image.

    Registers an image to a reference image while allowing local, rubber sheet
    deformations. Displacements are computed in the CRS of the reference image,
    at a scale dictated by the lowest resolution of the following three
    projections: input image projection, reference image projection, and
    requested projection. The displacements then applied to the input image to
    register it with the reference.

    Args:
      referenceImage: The image to register to.
      maxOffset: The maximum offset allowed when attempting to align the input
        images, in meters. Using a smaller value can reduce computation time
        significantly, but it must still be large enough to cover the greatest
        displacement within the entire image region.
      patchWidth: Patch size for detecting image offsets, in meters. This should
        be set large enough to capture texture, as well as large enough that
        ignorable objects are small within the patch. Default is null. Patch
        size will be determined automatically if notprovided.
      stiffness: Enforces a stiffness constraint on the solution. Valid values
        are in the range [0,10]. The stiffness is used for outlier rejection
        when determining displacements at adjacent grid points. Higher values
        move the solution towards a rigid transformation. Lower values allow
        more distortion or warping of the image during registration.

    Returns:
      An ee.Image.


Returns an image with the values of a band remapped.

    Maps from input values to output values, represented by two parallel lists.
    Any input values not included in the input list are either set to
    defaultValue if it is given or masked if it isn't. Note that inputs
    containing floating point values might sometimes fail to match due to
    floating point precision errors.

    Args:
      from: The source values (numbers or ee.Array). All values in this list
        will be mapped to the corresponding value in 'to'.
      to: The destination values (numbers or ee.Array). These are used to
        replace the corresponding values in 'from'. Must have the same number of
        values as 'from'.
      defaultValue: The default value to replace values that weren't matched by
        a value in 'from'. If not specified, unmatched values are masked out.
      bandName: The name of the band to remap. If not specified, the first band
        in the image is used.


Rename the bands of an image.

    Can be called with either a list of strings or any number of strings.

    Args:
      names: An array of strings specifying the new names for the bands. Must
        exactly match the number of bands in the image.
      *args: Band names as varargs.

    Returns:
      An image with the renamed bands.


Force an image to be computed in a given projection and resolution.

    Args:
      crs: The CRS to project the image to.
      crsTransform: The list of CRS transform values. This is a row-major
        ordering of the 3x2 transform matrix. This option is mutually exclusive
        with the scale option, and replaces any transform already on the
        projection.
      scale: If scale is specified, then the projection is scaled by dividing
        the specified scale value by the nominal size of a meter in the
        specified projection. If scale is not specified, then the scale of the
        given projection will be used.

    Returns:
      An ee.Image.


Returns an image that uses bilinear or bicubic interpolation.

    An algorithm that returns an image identical to its argument, but which uses
    bilinear or bicubic interpolation (rather than the default nearest-neighbor)
    to compute pixels in projections other than its native projection or other
    levels of the same image pyramid.

    This relies on the input image's default projection being meaningful, and so
    cannot be used on composites, for example. (Instead, you should resample the
    images that are used to create the composite.)

    Args:
      mode: The interpolation mode to use. One of 'bilinear' or 'bicubic'.

    Returns:
      An ee.Image.


Transforms the image from the RGB color space to the HSV color space.

    Expects a 3 band image in the range [0, 1], and produces three bands: hue,
    saturation and value with values in the range [0, 1].

    Returns:
      An ee.Image.


Returns an image with the pixels right shifted by image2.

    Calculates the signed right shift of v1 by v2 bits for each matched pair of
    bands in image1 and image2. If either image1 or image2 has only 1 band, then
    it is used against all the bands in the other image. If the images have the
    same number of bands, but not the same names, they're used pairwise in the
    natural order. The output bands are named for the longer of the two inputs,
    or if they're equal in length, in image1's order. The type of the output
    pixels is the union of the input types.

    Args:
      image2: The image from which the right operand bands are taken.

    Returns:
      An ee.Image.


Calculated the Reverse Squared Euclidean Distance (RSED).

    Computes the 2D maximal height surface created by placing an inverted
    parabola over each non-zero pixel of the input image, where the pixel's
    value is the height of the parabola. Viewed as a binary image
    (zero/not-zero) this is equivalent to buffering each non-zero input pixel by
    the square root of its value, in pixels.

    Args:
      neighborhood: Neighborhood size in pixels.
      units: The units of the neighborhood, currently only 'pixels' are
        supported.

    Returns:
      An ee.Image.


Returns an ee.FeatureCollection of samples from an ee.Image.

    Samples the pixels of an image, returning them as a FeatureCollection. Each
    feature will have 1 property per band in the input image. Note that the
    default behavior is to drop features that intersect masked pixels, which
    result in null-valued properties (see dropNulls argument).

    Args:
      region: The region to sample from. If unspecified, uses the image's whole
        footprint.
      scale: A nominal scale in meters of the projection to sample in.
      projection: The projection in which to sample. If unspecified, the
        projection of the image's first band is used. If specified in addition
        to scale, rescaled to the specified scale.
      factor: A subsampling factor, within (0, 1]. If specified, 'numPixels'
        must not be specified. Defaults to no subsampling.
      numPixels: The approximate number of pixels to sample. If specified,
        'factor' must not be specified.
      seed: A randomization seed to use for subsampling.
      dropNulls: Post filter the result to drop features that have null-valued
        properties.
      tileScale: A scaling factor used to reduce aggregation tile size; using a
        larger tileScale (e.g., 2 or 4) may enable computations that run out of
        memory with the default.
      geometries: If true, adds the center of the sampled pixel as the geometry
        property of the output feature. Otherwise, geometries will be omitted
        (saving memory).


Returns pixels from an image into a ND array per band.

    The arrays are returned in a feature retaining the same properties as the
    image and a geometry the same as that used to sample the image (or the image
    footprint if unspecified). Each band is sampled in its input projection, and
    if no geometry is specified, sampled using its footprint. For scalar bands,
    the output array is 2D. For array bands the output array is (2+N)D where N
    is the number of dimensions in the original band. If sampling array bands,
    all arrays must have the same number of elements. If a band's sampled region
    is entirely masked and a default array value is specified, the default array
    value is used in-lieu of sampling the image.

    Args:
      region: The region whose projected bounding box is used to sample the
        image. Defaults to the footprint in each band.
      properties: The properties to copy over from the sampled image. Defaults
        to all non-system properties.
      defaultValue: A default value used when a sampled pixel is masked or
        outside a band's footprint.
      defaultArrayValue: A default value used when a sampled array pixel is
        masked or outside a band's footprint.


Returns an ee.FeatureCollection of samples from an ee.Image.

    Converts each pixel of an image (at a given scale) that intersects one or
    more regions to a Feature, returning them as a FeatureCollection. Each
    output feature will have one property per band of the input image, as well
    as any specified properties copied from the input feature.

    Note that geometries will be snapped to pixel centers.

    Args:
      collection: The regions to sample over.
      properties: The list of properties to copy from each input feature.
        Defaults to all non-system properties.
      scale: A nominal scale in meters of the projection to sample in. If
        unspecified, the scale of the image's first band is used.
      projection: The projection in which to sample. If unspecified, the
        projection of the image's first band is used. If specified in addition
        to scale, rescaled to the specified scale.
      tileScale: A scaling factor used to reduce aggregation tile size; using a
        larger tileScale (e.g., 2 or 4) may enable computations that run out of
        memory with the default.
      geometries: If true, the results will include a point geometry per sampled
        pixel. Otherwise, geometries will be omitted (saving memory).


Selects bands from an image.

    Can be called in one of two ways:
      - Passed any number of non-list arguments. All of these will be
        interpreted as band selectors. These can be band names, regexes, or
        numeric indices. For example:
        selected = image.select('a', 'b', 3, 'd');
      - Passed two lists. The first will be used as band selectors and the
        second as new names for the selected bands. The number of new names
        must match the number of selected bands. For example:
        selected = image.select(['a', 4], ['newA', 'newB']);

    Args:
      selectors: An array of names, regexes or numeric indices specifying the
        bands to select.
      names: An array of strings specifying the new names for the selected
        bands.
      *args: Selector elements as varargs.

    Returns:
      An image with the selected bands.


Updates an image's mask based on the image itself.

    Updates an image's mask at all positions where the existing mask is not zero
    using the value of the image as the new mask value.

    The output image retains the metadata and footprint of the input image.

    Returns:
      An ee.Image.


Computes the signum function (sign) of the input.

    The return value is 0 if the input is 0, 1 if the input is greater than 0,
    -1 if the input is less than 0.

    Returns:
      An ee.Image.


Styles a raster input with the provided OGC SLD styling.

    Points of note:

    * OGC SLD 1.0 and OGC SE 1.1 are supported.
    * The XML document passed in can be complete, or just the
      SldRasterSymbolizer element and down.
    * Exactly one SldRasterSymbolizer is required.
    * Bands may be selected by their proper Earth Engine names or using numeric
      identifiers ("1", "2", ...). Proper Earth Engine names are tried first.
    * The Histogram and Normalize contrast stretch mechanisms are supported.
    * The type="values", type="intervals" and type="ramp" attributes for
      ColorMap element in SLD 1.0 (GeoServer extensions) are supported.
    * Opacity is only taken into account when it is 0.0 (transparent).
      Non-zero opacity values are treated as completely opaque.
    * The OverlapBehavior definition is currently ignored.
    * The ShadedRelief mechanism is not currently supported.
    * The ImageOutline mechanism is not currently supported.
    * The Geometry element is ignored.

    The output image will have histogram_bandname metadata if histogram
    equalization or normalization is requested.

    Args:
      sldXml: The OGC SLD 1.0 or 1.1 document (or fragment).

    Returns:
      An ee.Image.


Selects a contiguous group of bands from an image by position.

    Args:
      start: Where to start the selection. Negative numbers select from the end,
        counting backwards.
      end: Where to end the selection. If omitted, selects all bands from the
        start position to the end.

    Returns:
      An ee.Image.


Returns the spectral/spatial dilation of an image.

    Computes the spectral/spatial dilation of an image by computing the spectral
    distance of each pixel under a structuring kernel from the centroid of all
    pixels under the kernel and taking the most distant result.

    See 'Spatial/spectral endmember extraction by multidimensional morphological
    operations.' IEEE transactions on geoscience and remote sensing 40.9 (2002):
    2025-2041.

    Args:
      metric: The spectral distance metric to use. One of 'sam' (spectral angle
        mapper), 'sid' (spectral information divergence), 'sed' (squared
        Euclidean distance), or 'emd' (earth movers distance).
      kernel: Connectedness kernel. Defaults to a square of radius 1 (8-way
        connected).
      useCentroid: If true, distances are computed from the mean of all pixels
        under the kernel instead of the kernel's center pixel.


Computes the per-pixel spectral distance between two images.

    If the images are array based then only the first band of each image is
    used; otherwise all bands are involved in the distance computation. The two
    images are therefore expected  to contain the same number of bands or have
    the same 1-dimensional array length.

    Args:
      image2: The second image.
      metric: The spectral distance metric to use. One of 'sam' (spectral angle
        mapper), 'sid' (spectral information divergence), 'sed' (squared
        Euclidean distance), or 'emd' (earth movers distance).

    Returns:
      An ee.Image.


Returns the spectral/spatial erosion of an image.

    Computes the spectral/spatial erosion of an image by computing the spectral
    distance of each pixel under a structuring kernel from the centroid of all
    pixels under the kernel and taking the closest result.

    See 'Spatial/spectral endmember extraction by multidimensional morphological
    operations.' IEEE transactions on geoscience and remote sensing 40.9 (2002):
    2025-2041.

    Args:
      metric: The spectral distance metric to use. One of 'sam' (spectral angle
        mapper), 'sid' (spectral information divergence), 'sed' (squared
        Euclidean distance), or 'emd' (earth movers distance).
      kernel: Connectedness kernel. Defaults to a square of radius 1 (8-way
        connected).
      useCentroid: If true, distances are computed from the mean of all pixels
        under the kernel instead of the kernel's center pixel.


Returns the spectral gradient of an image.

    Computes the spectral gradient over all bands of an image (or the first band
    if the image is Array typed) by computing the per-pixel difference between
    the spectral erosion and dilation with a given structuring kernel and
    distance metric. See: Plaza, Antonio, et al. 'Spatial/spectral endmember
    extraction by multidimensional morphological operations.' IEEE transactions
    on geoscience and remote sensing 40.9 (2002): 2025-2041.

    Args:
      metric: The spectral distance metric to use. One of 'sam' (spectral angle
        mapper), 'sid' (spectral information divergence), 'sed' (squared
        Euclidean distance), or 'emd' (earth movers distance).
      kernel: Connectedness kernel. Defaults to a square of radius 1 (8-way
        connected).
      useCentroid: If true, distances are computed from the mean of all pixels
        under the kernel instead of the kernel's center pixel.


Extracts a stratified random sample of points from an image.

    Extracts the specified number of samples for each distinct value discovered
    within the 'classBand'. Returns a FeatureCollection of 1 Feature per
    extracted point, with each feature having 1 property per band in the input
    image. If there are less than the specified number of samples available for
    a given class value, then all of the points for that class will be included.
    Requires that the classBand contain integer values.

    Args:
      numPoints: The default number of points to sample in each class. Can be
        overridden for specific classes using the 'classValues' and
        'classPoints' properties.
      classBand: The name of the band containing the classes to use for
        stratification. If unspecified, the first band of the input image is
        used.
      region: The region to sample from. If unspecified, the input image's whole
        footprint is used.
      scale: A nominal scale in meters of the projection to sample in. Defaults
        to the scale of the first band of the input image.
      projection: The projection in which to sample. If unspecified, the
        projection of the input image's first band is used. If specified in
        addition to scale, rescaled to the specified scale.
      seed: A randomization seed to use for subsampling.
      classValues: A list of class values for which to override the numPoints
        parameter. Must be the same size as classPoints or null.
      classPoints: A list of the per-class maximum number of pixels to sample
        for each class in  the classValues list. Must be the same size as
        classValues or null.
      dropNulls: Skip pixels in which any band is masked.
      tileScale: A scaling factor used to reduce aggregation tile size; using a
        larger tileScale (e.g., 2 or 4) may enable computations that run out of
        memory with the default.
      geometries: If true, the results will include a geometry per sampled
        pixel. Otherwise, geometries will be omitted (saving memory).

    Returns:
      An ee.FeatureCollection.


Returns image2 subtracted from this image.

    Subtracts the second value from the first for each matched pair of bands in
    image1 and image2. If either image1 or image2 has only 1 band, then it is
    used against all the bands in the other image. If the images have the same
    number of bands, but not the same names, they're used pairwise in the
    natural order. The output bands are named for the longer of the two inputs,
    or if they're equal in length, in image1's order. The type of the output
    pixels is the union of the input types.

    Args:
      image2: The image from which the right operand bands are taken.


Concatenates pixels from each band into a single array per pixel.

    The result will be masked if any input bands are masked.

    Args:
      axis: Axis to concatenate along; must be at least 0 and at most the
        dimension of the inputs. If the axis equals the dimension of the inputs,
        the result will have 1 more dimension than the inputs.

    Returns:
      An ee.Image.


Translate the input image.

    Args:
      x: The amount to translate the image in the x direction.
      y: The amount to translate the image in the y direction.
      units: The units for x and y; 'meters' or 'pixels'.
      proj: The projection in which to translate the image; defaults to the
        projection of the first band.

    Returns:
      An ee.Image.


Returns an ee.Image with input values [low, high] scaled to [0, 1].

    Scales the input so that the range of input values [low, high] becomes [0,
    1]. Values outside the range are NOT clamped. This algorithm always produces
    floating point pixels.

    Args:
      low: The value mapped to 0.
      high: The value mapped to 1.

    Returns:
      An ee.Image.


Returns an ee.Image with mask and value of the value image.

    Replaces mask and value of the input image with the mask and value of
    another image at all positions where the input mask is zero. The output
    image retains the metadata of the input image. By default, the output image
    also retains the footprint of the input, but setting sameFootprint to false
    allows to extend the footprint.

    Args:
      value: New value and mask for the masked pixels of the input image. If not
        specified, defaults to constant zero image which is valid everywhere.
      sameFootprint: If true (or unspecified), the output retains the footprint
        of the input image. If false, the footprint of the output is the union
        of the input footprint with the footprint of the value image.

    Returns:
      An ee.Image.


Returns an ee.Image with endmembers unmixing each pixel.

    Unmix each pixel with the given endmembers, by computing the pseudo-inverse
    and multiplying it through each pixel. Returns an image of doubles with the
    same number of bands as endmembers.

    Args:
      endmembers: The endmembers to unmix with.
      sumToOne: Constrain the outputs to sum to one.
      nonNegative: Constrain the outputs to be non-negative.

    Returns:
      An ee.Image.


Returns an ee.Image with mask of the mask image.

    Updates an image's mask at all positions where the existing mask is not
    zero. The output image retains the metadata and footprint of the input
    image.

    Args:
      mask: New mask for the image, as a floating-point value in the range [0,
        1] (invalid = 0, valid = 1). If this image has a single band, it is used
        for all bands in the input image; otherwise, must have the same number
        of bands as the input image.

    Returns:
      An ee.Image.


Produces an RGB or grayscale visualization of an image.

    Each of the gain, bias, min, max, and gamma arguments can take either a
    single value, which will be applied to all bands, or a list of values the
    same length as bands.

    Args:
      bands: A list of the bands to visualize. If empty, the first 3 are used.
      gain: The visualization gain(s) to use.
      bias: The visualization bias(es) to use.
      min: The value(s) to map to RGB8 value 0.
      max: The value(s) to map to RGB8 value 255.
      gamma: The gamma correction factor(s) to use.
      opacity: The opacity scaling factor to use.
      palette: The color palette to use. List of CSS color identifiers or
        hexadecimal color strings (e.g., ['red', '00FF00', 'blueviolet']).
      forceRgbOutput: Whether to produce RGB output even for single-band inputs.

    Returns:
      An ee.Image.


Performs conditional replacement of values.

    For each pixel in each band of 'input', if the corresponding pixel in 'test'
    is nonzero, output the corresponding pixel in value, otherwise output the
    input pixel.

    If at a given pixel, either test or value is masked, the input value is
    used. If the input is masked, nothing is done.

    The output bands have the same names as the input bands. The output type of
    each band is the larger of the input and value types. The output image
    retains the metadata and footprint of the input image.

    Args:
      test: The test image. The pixels of this image determines which of the
        input pixels is returned. If this is a single band, it is used for all
        bands in the input image. This may not be an array image.
      value: The output value to use where test is not zero. If this is a single
        band, it is used for all bands in the input image.

    Returns:
      An ee.Image.


Returns an ee.Model from a description of an AI Platform prediction model.

    DEPRECATED: Cloud AI Platform is deprecated migrate to Vertex AI:
    https://developers.google.com/earth-engine/guides/ee-vertex-migrate

    (See https://cloud.google.com/ml-engine/).

    Args:
      projectName: The Google Cloud project that owns the model. Deprecated: use
        "projectId" instead.
      projectId: The ID of the Google Cloud project that owns the model.
      modelName: The name of the model.
      version: The model version. Defaults to the AI Platform default model
        version.
      region: The model deployment region. Defaults to "us-central1".
      inputProperties: Properties passed with each prediction instance. Image
        predictions are tiled, so these properties will be replicated into each
        image tile instance. Defaults to no properties.
      inputTypeOverride: Types to which model inputs will be coerced if
        specified. Both Image bands and Image/Feature properties are valid.
      inputShapes: The fixed shape of input array bands. For each array band not
        specified, the fixed array shape will be automatically deduced from a
        non-masked pixel.
      proj: The input projection at which to sample all bands. Defaults to the
        default projection of an image's first band.
      fixInputProj: If true, pixels will be sampled in a fixed projection
        specified by 'proj'. The output projection is used otherwise. Defaults
        to false.
      inputTileSize: Rectangular dimensions of pixel tiles passed in to
        prediction instances. Required for image predictions.
      inputOverlapSize: Amount of adjacent-tile overlap in X/Y along each edge
        of pixel tiles passed in to prediction instances. Defaults to [0, 0].
      outputTileSize: Rectangular dimensions of pixel tiles returned from AI
        Platform. Defaults to the value in 'inputTileSize'.
      outputBands: A map from output band names to a dictionary of output band
        info. Valid band info fields are 'type' and 'dimensions'. 'type' should
        be a ee.PixelType describing the output band, and 'dimensions' is an
        optional integer with the number of dimensions in that band e.g.,
        "outputBands: {'p': {'type': ee.PixelType.int8(), 'dimensions': 1}}".
        Required for image predictions.
      outputProperties: A map from output property names to a dictionary of
        output property info. Valid property info fields are 'type' and
        'dimensions'. 'type' should be a ee.PixelType describing the output
        property, and 'dimensions' is an optional integer with the number of
        dimensions for that property if it is an array e.g., "outputBands: {'p':
        {'type': ee.PixelType.int8(), 'dimensions': 1}}". Required for
        predictions from FeatureCollections.
      outputMultiplier: An approximation to the increase in data volume for the
        model outputs over the model inputs. If specified this must be >= 1.
        This is only needed if the model produces more data than it consumes,
        e.g., a model that takes 5 bands and produces 10 outputs per pixel.

    Returns:
      An ee.Model.


Returns an ee.Model from a description of a Vertex AI model endpoint.

    See https://cloud.google.com/vertex-ai.

    Warning: This method is in public preview and may undergo breaking changes.

    Args:
      endpoint: The endpoint name for predictions.
      inputProperties: Properties passed with each prediction instance. Image
        predictions are tiled, so these properties will be replicated into each
        image tile instance. Defaults to no properties.
      inputTypeOverride: Types to which model inputs will be coerced if
        specified. Both Image bands and Image/Feature properties are valid.
      inputShapes: The fixed shape of input array bands. For each array band not
        specified, the fixed array shape will be automatically deduced from a
        non-masked pixel.
      proj: The input projection at which to sample all bands. Defaults to the
        default projection of an image's first band.
      fixInputProj: If true, pixels will be sampled in a fixed projection
        specified by 'proj'. The output projection is used otherwise. Defaults
        to false.
      inputTileSize: Rectangular dimensions of pixel tiles passed in to
        prediction instances. Required for image predictions.
      inputOverlapSize: Amount of adjacent-tile overlap in X/Y along each edge
        of pixel tiles passed in to prediction instances. Defaults to [0, 0].
      outputTileSize: Rectangular dimensions of pixel tiles returned from AI
        Platform. Defaults to the value in 'inputTileSize'.
      outputBands: A map from output band names to a dictionary of output band
        info. Valid band info fields are 'type' and 'dimensions'. 'type' should
        be a ee.PixelType describing the output band, and 'dimensions' is an
        optional integer with the number of dimensions in that band e.g.,
        "outputBands: {'p': {'type': ee.PixelType.int8(), 'dimensions': 1}}".
        Required for image predictions.
      outputProperties: A map from output property names to a dictionary of
        output property info. Valid property info fields are 'type' and
        'dimensions'. 'type' should be a ee.PixelType describing the output
        property, and 'dimensions' is an optional integer with the number of
        dimensions for that property if it is an array e.g., "outputBands: {'p':
        {'type': ee.PixelType.int8(), 'dimensions': 1}}". Required for
        predictions from FeatureCollections.
      outputMultiplier: An approximation to the increase in data volume for the
        model outputs over the model inputs. If specified this must be >= 1.
        This is only needed if the model produces more data than it consumes,
        e.g., a model that takes 5 bands and produces 10 outputs per pixel.
      maxPayloadBytes: The prediction payload size limit in bytes. Defaults to
        1.5MB (1500000 bytes.)
      payloadFormat: The payload format of entries in prediction requests and
        responses. One of: ['SERIALIZED_TF_TENSORS, 'RAW_JSON', 'ND_ARRAYS',
        'GRPC_TF_TENSORS', 'GRPC_SERIALIZED_TF_TENSORS', 'GRPC_TF_EXAMPLES'].
        Defaults to 'SERIALIZED_TF_TENSORS'.

    Returns:
      An ee.Model.


Returns an image with predictions from pixel tiles of an image.

    The predictions are merged as bands with the input image.

    The model will receive 0s in place of masked pixels. The masks of predicted
    output bands are the minimum of the masks of the inputs.

    Args:
      image: The input image.


Returns a feature collection with predictions for each feature.

    Predicted properties are merged with the properties of the input feature.

    Args:
      collection: The input collection.


Returns true if the given Date or DateRange is within this DateRange.

    Args:
      other: The Date or DateRange to check if it is inside the DateRange.

    Returns:
      A Boolean ComputedObject.


Returns a DateRange that contains all the timespan of this and other.

    Args:
      other: The other DateRange to include in the intersection.

    Raises:
      EEException if the result is an empty DateRange.

    Returns:
      An ee.DateRange.


Returns true if the other DateRange has at least one time in common.

    Args:
      other: The other DateRange to check against.

    Returns:
      A Boolean ComputedObject.


Returns a DateRange that contains all points in this and other.

    Args:
      other: The DateRange to union with.

    Returns:
      An ee.DateRange.


Call a named API function with positional and keyword arguments.

    Args:
      name: The name of the API function to call.
      *args: Positional arguments to pass to the function.
      **kwargs: Keyword arguments to pass to the function.

    Returns:
      An object representing the called function. If the signature specifies
      a recognized return type, the returned value will be cast to that type.


Call a named API function with a dictionary of named arguments.

    Args:
      name: The name of the API function to call.
      named_args: A dictionary of arguments to the function.

    Returns:
      An object representing the called function. If the signature specifies
      a recognized return type, the returned value will be cast to that type.


Returns the functions that have not been bound using importApi() yet.


Looks up an API function by name.

    Args:
      name: The name of the function to get.

    Returns:
      The requested ApiFunction.


Looks up an API function by name.

    Args:
      name: The name of the function to get.

    Returns:
      The requested ApiFunction or None if not found.


Initializes the list of signatures from the Earth Engine front-end.


Adds all API functions that begin with a given prefix to a target class.

    Args:
      target: The class to add to.
      prefix: The prefix to search for in the signatures.
      type_name: The name of the object's type. Functions whose first argument
        matches this type are bound as instance methods, and those whose first
        argument doesn't match are bound as static methods.
      prepend: An optional string to prepend to the names of the added
        functions.


Removes all methods added by importApi() from a target class.

    Args:
      target: The class to remove from.


Makes an HTTP request using httplib2 semantics.


Builds a callable that wraps an API request.

  Args:
    headers_supplier: If not None, this will be called for each request and the
      resulting dict incorporated into that request's HTTP headers.
    response_inspector: If not None, this will be called with an
      httplib2.Response containing the HTTP response and body content.
      The call happens no matter what the HTTP response status was.

  Returns:
    Something that can be called in place of the http.HttpRequest constructor
    to build an HttpRequest.


Builds an HttpRequest, adding headers and response inspection.


Builds an Earth Engine Cloud API resource.

  Args:
    api_base_url: The base URL of the cloud endpoints.
    session: The Requests session to issue all requests in. This manages
      shared resources, such as connection pools.
    api_key: An API key that's enabled for use with the Earth Engine Cloud API.
    credentials: OAuth2 credentials to use when authenticating to the API.
    timeout: How long a timeout to set on requests, in seconds.
    num_retries: The number of times to retry discovery with randomized
      exponential backoff, in case of intermittent/connection issues.
    headers_supplier: A callable that will return a set of headers to be applied
      to a request. Will be called once for each request.
    response_inspector: A callable that will be invoked with the raw
      httplib2.Response responses.
    http_transport: An optional custom http_transport to use.
    raw: Whether or not to return raw bytes when making method requests.

  Returns:
    A resource object to use to call the Cloud API.


Builds an Earth Engine Cloud API resource from a description of the API.

  This version is intended for use in tests.

  Args:
    discovery_document: The description of the API.
    http_transport: An HTTP transport object to use for the call.
    headers_supplier: A callable that will return a set of headers to be applied
      to a request. Will be called once for each request.
    response_inspector: A callable that will be invoked with the raw
      httplib2.Response responses.
    raw: Whether to return raw bytes when making method requests.

  Returns:
    A resource object to use to call the Cloud API.


Applies a set of conversion rules to a dict.

  Args:
    to_convert: A dictionary of key/value pairs to convert.
    conversions: A dictionary giving the mapping from key names in "to_convert"
      to how those keys and their values will be handled. Key/value pairs in
      "to_convert" will be modified in a way that depends on how the key
      appears in "conversions". If "to_convert" contains a key/value mapping
      of "k"->"v", then:
      - If "conversions" contains "k"->"X" then the result will contain
        "X"->"v".
      - If "conversions" contains "k"->None then the result will not contain an
        entry for "k".
      - If "conversions" contains "k"->("X", f) then the result will contain
        "X"->f("v")
      - If "conversions" does not contain an entry for "k" then the result
        will not contain an entry for "k" unless retain_keys is true;
        if key_warnings is True then a warning will be printed.
      - If two or more distinct input keys are converted to the same output key,
        one of the resulting values will appear in the result, the others
        will be dropped, and a warning will be printed.
    defaults: Values to insert in the result if the result of conversion does
      not contain these keys.
    key_warnings: Whether to print warnings for input keys that are not mapped
      to anything in the output.
    retain_keys: Whether or not to retain the state of dict.  If false, any keys
      that don't show up in the conversions dict will be dropped from result.

  Returns:
    The "to_convert" dict with keys renamed, values converted, and defaults
    added.


Converts a value using a set of value mappings.

  Args:
    value: The value to convert.
    conversions: A dict giving the desired output for each of a set of possible
      input values.
    default: The value to return if the input value is not one of the ones
      listed in "conversions".

  Returns:
    The converted value.


Converts a time value to a google.protobuf.Timestamp's string form.

  Args:
    time_msec: A time in msec since the Unix epoch.

  Returns:
    A string formatted like '2003-09-07T19:30:12.345Z', which is the expected
    form of google.protobuf.Timestamp values.


Converts a google.protobuf.Timestamp's string form to a time in msec.

  Args:
    timestamp: A string formatted like '2003-09-07T19:30:12.345Z', which is the
      expected form of google.protobuf.Timestamp values.

  Returns:
    A time in msec since the Unix epoch.


Converts a lng/lat bounding box to a GeoJSON string.


Converts a getList params dict to something usable with listAssets.


Converts a listAssets result to something getList can return.


Converts a listImages params dict to something usable with listAssets.


Converts a listImages result to something getList can return.


Converts an EarthEngineAsset to the format returned by getList.


Converts an Image to the format returned by getList.


Converts an EarthEngineAsset.Type to the format returned by getList.


Converts a createAsset asset type to an EarthEngineAsset.Type.


Converts an internal asset ID to a Cloud API asset name.

  If asset_id already matches the format 'projects/*/assets/**', it is returned
  as-is.

  Args:
    asset_id: The asset ID to convert.

  Returns:
    An asset name string in the format 'projects/*/assets/**'.


Splits an asset name into the parent and ID parts.

  Args:
    asset_name: The asset ID to split, in the form 'projects/*/assets/**'.

  Returns:
    The parent ('projects/*') and ID ('**') parts of the name.


Converts params to an ImageManifest for ingestion.


Converts params to a TableManifest for ingestion.


Converts a tileset to a one platform representation of a tileset.


Converts the sources to one platform representation of sources.


Converts a ListAlgorithmsResult to the internal format.

  The internal code expects a dict mapping each algorithm's name to a dict
  containing:
  - description: string
  - returns: string
  - arguments: list of dicts, each containing
    - name: argument name
    - type: argument type
    - description: argument description (optional)
    - optional: bool (optional)
    - default: default value (optional)
  - hidden: bool (optional)
  - preview: bool (optional)
  - deprecated: string containing deprecation reason (optional)

  Args:
    algorithms: A ListAlgorithmResult.

  Returns:
    A version of that algorithms list that can be interpreted by
    apifunction.initialize().


Converts an Algorithm to the internal format.


Converts a legacy file format string to an ImageFileFormat enum value.

  Args:
    format_str: A string describing an image file format that was passed to
      one of the functions in ee.data that takes image file formats.

  Returns:
    A best guess at the corresponding ImageFileFormat enum name.


Converts a legacy file format string to a TableFileFormat enum value.

  Args:
    format_str: A string describing a table file format that was passed to
      one of the functions in ee.data that takes table file formats.

  Returns:
    A best guess at the corresponding TableFileFormat enum name.


Converts a band list, possibly as CSV, to a real list of bands.

  Args:
    bands: A list of strings containing band names, or a string containing
      a comma-separated list of band names, or None.

  Returns:
    A list of band names.


Extracts a VisualizationOptions from a param dict.

  Args:
    params: See ee.data.getMapId() for the description of the keys and values
      that might appear here.

  Returns:
    A VisualizationOptions proto, in dict form.


Converts a string containing CSV numbers to a list.


Converts an Operation to a legacy Task.


Converts a state string from an Operation to the Task equivalent.


Converts an IAM Policy proto to the legacy ACL format.


Converts the legacy ACL format to an IAM Policy proto.


Converts an input value to GridDimensions.

  Args:
    dimensions: May specify a single number to indicate a square shape,
      or a tuple of two dimensions to indicate (width,height).

  Returns:
    A GridDimensions as a dict.


Converts an operation to a task.


Returns True if the given state is an active one.


Returns True if the given state indicates a completed task.


Starts the task. No-op for started tasks.


Fetches the current status of the task.

    Returns:
      A dictionary describing the current status of the task as it appears on
      the EE server. Includes the following fields:
      - state: One of the values in Task.State.
      - creation_timestamp_ms: The Unix timestamp of when the task was created.
      - update_timestamp_ms: The Unix timestamp of when the task last changed.
      - output_url: URL of the output. Appears only if state is COMPLETED.
      - error_message: Failure reason. Appears only if state is FAILED.
      May also include other fields.


Returns the tasks submitted to EE by the current user.

    These include all currently running tasks as well as recently canceled or
    failed tasks.

    Returns:
      A list of Tasks.


Creates a task to export an EE Image to an EE Asset.

      Args:
        image: The image to be exported.
        description: Human-readable name of the task.
        assetId: The destination asset ID.
        pyramidingPolicy: The pyramiding policy to apply to each band in the
            image, a dictionary keyed by band name. Values must be
            one of: "mean", "sample", "min", "max", or "mode".
            Defaults to "mean". A special key, ".default", may be used to
            change the default for all bands.
        dimensions: The dimensions of the exported image. Takes either a
            single positive integer as the maximum dimension or "WIDTHxHEIGHT"
            where WIDTH and HEIGHT are each positive integers.
        region: The lon,lat coordinates for a LinearRing or Polygon
            specifying the region to export. Can be specified as a nested
            lists of numbers or a serialized string. Defaults to the image's
            region.
        scale: The resolution in meters per pixel. Defaults to the
            native resolution of the image asset unless a crsTransform
            is specified.
        crs: The coordinate reference system of the exported image's
            projection. Defaults to the image's default projection.
        crsTransform: A comma-separated string of 6 numbers describing
            the affine transform of the coordinate reference system of the
            exported image's projection, in the order: xScale, xShearing,
            xTranslation, yShearing, yScale and yTranslation. Defaults to
            the image's native CRS transform.
        maxPixels: The maximum allowed number of pixels in the exported
            image. The task will fail if the exported region covers more
            pixels in the specified projection. Defaults to 100,000,000.
        priority: The priority of the task within the project. Higher priority
          tasks are scheduled sooner. Must be an integer between 0 and 9999.
          Defaults to 100.
        **kwargs: Holds other keyword arguments that may have been deprecated
            such as 'crs_transform'.

      Returns:
        An unstarted Task that exports the image as an Earth Engine asset.


Creates a task to export an EE Image to Google Cloud Storage.

      Args:
        image: The image to be exported.
        description: Human-readable name of the task.
        bucket: The name of a Cloud Storage bucket for the export.
        fileNamePrefix: Cloud Storage object name prefix for the export.
          Defaults to the name of the task.
        dimensions: The dimensions of the exported image. Takes either a single
          positive integer as the maximum dimension or "WIDTHxHEIGHT" where
          WIDTH and HEIGHT are each positive integers.
        region: The lon,lat coordinates for a LinearRing or Polygon specifying
          the region to export. Can be specified as a nested lists of numbers or
          a serialized string. Defaults to the image's region.
        scale: The resolution in meters per pixel. Defaults to the native
          resolution of the image asset unless a crsTransform is specified.
        crs: The coordinate reference system of the exported image's projection.
          Defaults to the image's default projection.
        crsTransform: A comma-separated string of 6 numbers describing the
          affine transform of the coordinate reference system of the exported
          image's projection, in the order: xScale, xShearing, xTranslation,
          yShearing, yScale and yTranslation. Defaults to the image's native CRS
          transform.
        maxPixels: The maximum allowed number of pixels in the exported image.
          The task will fail if the exported region covers more pixels in the
          specified projection. Defaults to 100,000,000.
        shardSize: Size in pixels of the tiles in which this image will be
          computed. Defaults to 256.
        fileDimensions: The dimensions in pixels of each image file, if the
          image is too large to fit in a single file. May specify a single
          number to indicate a square shape, or a tuple of two dimensions to
          indicate (width,height). Note that the image will still be clipped to
          the overall image dimensions. Must be a multiple of shardSize.
        skipEmptyTiles: If true, skip writing empty (i.e. fully-masked) image
          tiles. Defaults to false. Only supported on GeoTIFF exports.
        fileFormat: The string file format to which the image is exported.
          Currently only 'GeoTIFF' and 'TFRecord' are supported, defaults to
          'GeoTIFF'.
        formatOptions: A dictionary of string keys to format-specific options.
          For 'GeoTIFF': 'cloudOptimized' (bool), 'noData' (float).
        priority: The priority of the task within the project. Higher priority
          tasks are scheduled sooner. Must be an integer between 0 and 9999.
          Defaults to 100.
        **kwargs: Holds other keyword arguments that may have been deprecated
          such as 'crs_transform'.

      Returns:
        An unstarted Task that exports the image to Google Cloud Storage.


Creates a task to export an EE Image to Drive.

      Args:
        image: The image to be exported.
        description: Human-readable name of the task.
        folder: The name of a unique folder in your Drive account to export
          into. Defaults to the root of the drive.
        fileNamePrefix: The Google Drive filename for the export. Defaults to
          the name of the task.
        dimensions: The dimensions of the exported image. Takes either a single
          positive integer as the maximum dimension or "WIDTHxHEIGHT" where
          WIDTH and HEIGHT are each positive integers.
        region: The lon,lat coordinates for a LinearRing or Polygon specifying
          the region to export. Can be specified as a nested lists of numbers or
          a serialized string. Defaults to the image's region.
        scale: The resolution in meters per pixel. Defaults to the native
          resolution of the image asset unless a crsTransform is specified.
        crs: The coordinate reference system of the exported image's projection.
          Defaults to the image's default projection.
        crsTransform: A comma-separated string of 6 numbers describing the
          affine transform of the coordinate reference system of the exported
          image's projection, in the order: xScale, xShearing, xTranslation,
          yShearing, yScale and yTranslation. Defaults to the image's native CRS
          transform.
        maxPixels: The maximum allowed number of pixels in the exported image.
          The task will fail if the exported region covers more pixels in the
          specified projection. Defaults to 100,000,000.
        shardSize: Size in pixels of the tiles in which this image will be
          computed. Defaults to 256.
        fileDimensions: The dimensions in pixels of each image file, if the
          image is too large to fit in a single file. May specify a single
          number to indicate a square shape, or a tuple of two dimensions to
          indicate (width,height). Note that the image will still be clipped to
          the overall image dimensions. Must be a multiple of shardSize.
        skipEmptyTiles: If true, skip writing empty (i.e. fully-masked) image
          tiles. Defaults to false. Only supported on GeoTIFF exports.
        fileFormat: The string file format to which the image is exported.
          Currently only 'GeoTIFF' and 'TFRecord' are supported, defaults to
          'GeoTIFF'.
        formatOptions: A dictionary of string keys to format-specific options.
          For 'GeoTIFF': 'cloudOptimized' (bool), 'noData' (float).
        priority: The priority of the task within the project. Higher priority
          tasks are scheduled sooner. Must be an integer between 0 and 9999.
          Defaults to 100.
        **kwargs: Holds other keyword arguments that may have been deprecated
          such as 'crs_transform', 'driveFolder', and 'driveFileNamePrefix'.

      Returns:
        An unstarted Task that exports the image to Drive.


Creates a task to export an Image as a pyramid of map tiles.

      Exports a rectangular pyramid of map tiles for use with web map
      viewers. The map tiles will be accompanied by a reference
      index.html file that displays them using the Google Maps API,
      and an earth.html file for opening the map on Google Earth.

      Args:
        image: The image to export as tiles.
        description: Human-readable name of the task.
        bucket: The destination bucket to write to.
        fileFormat: The map tiles' file format, one of 'auto', 'png',
            or 'jpeg'. Defaults to 'auto', which means that opaque tiles
            will be encoded as 'jpg' and tiles with transparency will be
            encoded as 'png'.
        path: The string used as the output's path. A trailing '/'
            is optional. Defaults to the task's description.
        writePublicTiles: Whether to write public tiles instead of using the
            bucket's default object ACL. Defaults to True and requires the
            invoker to be an OWNER of bucket.
        maxZoom: The maximum zoom level of the map tiles to export.
        scale: The max image resolution in meters per pixel, as an alternative
            to 'maxZoom'. The scale will be converted to the most appropriate
            maximum zoom level at the equator.
        minZoom: The optional minimum zoom level of the map tiles to export.
        region: The lon,lat coordinates for a LinearRing or Polygon
            specifying the region to export. Can be specified as a nested
            lists of numbers or a serialized string. Map tiles will be
            produced in the rectangular region containing this geometry.
            Defaults to the image's region.
        skipEmptyTiles: If true, skip writing empty (i.e. fully-transparent)
            map tiles. Defaults to false.
        mapsApiKey: Used in index.html to initialize the Google Maps API. This
            removes the "development purposes only" message from the map.
        bucketCorsUris: A list of domains that are allowed to retrieve the
            exported tiles from JavaScript. Setting the tiles to public is not
            enough to allow them to be accessible by a web page, so you must
            explicitly give domains access to the bucket. This is known as
            Cross-Origin-Resource-Sharing, or CORS. You can allow all domains to
            have access using "*", but this is generally discouraged. See
            https://cloud.google.com/storage/docs/cross-origin for more details.
        priority: The priority of the task within the project. Higher priority
          tasks are scheduled sooner. Must be an integer between 0 and 9999.
          Defaults to 100.
        **kwargs: Holds other keyword arguments that may have been deprecated
            such as 'crs_transform'.

      Returns:
        An unstarted Task that exports the image to Google Cloud Storage.


Creates a task to export a FeatureCollection to Google Cloud Storage.

      Args:
        collection: The feature collection to be exported.
        description: Human-readable name of the task.
        bucket: The name of a Cloud Storage bucket for the export.
        fileNamePrefix: Cloud Storage object name prefix for the export.
            Defaults to the name of the task.
        fileFormat: The output format: "CSV" (default), "GeoJSON", "KML", "KMZ",
            "SHP", or "TFRecord".
        selectors: The list of properties to include in the output, as a list
            of strings or a comma-separated string. By default, all properties
            are included.
        maxVertices:
            Max number of uncut vertices per geometry; geometries with more
            vertices will be cut into pieces smaller than this size.
        priority: The priority of the task within the project. Higher priority
          tasks are scheduled sooner. Must be an integer between 0 and 9999.
          Defaults to 100.
        **kwargs: Holds other keyword arguments that may have been deprecated
            such as 'outputBucket'.

      Returns:
        An unstarted Task that exports the table to Google Cloud Storage.


Creates a task to export a FeatureCollection to Drive.

      Args:
        collection: The feature collection to be exported.
        description: Human-readable name of the task.
        folder: The name of a unique folder in your Drive account to
            export into. Defaults to the root of the drive.
        fileNamePrefix: The Google Drive filename for the export.
            Defaults to the name of the task.
        fileFormat: The output format: "CSV" (default), "GeoJSON", "KML",
            "KMZ", "SHP", or "TFRecord".
        selectors: The list of properties to include in the output, as a list
            of strings or a comma-separated string. By default, all properties
            are included.
        maxVertices:
            Max number of uncut vertices per geometry; geometries with more
            vertices will be cut into pieces smaller than this size.
        priority: The priority of the task within the project. Higher priority
          tasks are scheduled sooner. Must be an integer between 0 and 9999.
          Defaults to 100.
        **kwargs: Holds other keyword arguments that may have been deprecated
            such as 'driveFolder' and 'driveFileNamePrefix'.

      Returns:
        An unstarted Task that exports the table.


Creates a task to export a FeatureCollection to an EE table asset.

      Args:
        collection: The feature collection to be exported.
        description: Human-readable name of the task.
        assetId: The destination asset ID.
        maxVertices:
            Max number of uncut vertices per geometry; geometries with more
            vertices will be cut into pieces smaller than this size.
        priority: The priority of the task within the project. Higher priority
          tasks are scheduled sooner. Must be an integer between 0 and 9999.
          Defaults to 100.
        **kwargs: Holds other keyword arguments that may have been deprecated.

      Returns:
        An unstarted Task that exports the table.


Creates a task to export a FeatureCollection to a FeatureView.

      Args:
        collection: The feature collection to be exported.
        description: Human-readable name of the task.
        assetId: The destination asset ID.
        ingestionTimeParameters: The FeatureView ingestion time parameters.
        priority: The priority of the task within the project. Higher priority
          tasks are scheduled sooner. Must be an integer between 0 and 9999.
          Defaults to 100.
        **kwargs: Holds other keyword arguments that may have been deprecated.

      Returns:
        An unstarted Task that exports the table.


Creates a task to export a FeatureCollection to a BigQuery table.

      This feature is in Preview, and the API and behavior may change
      significantly.

      Args:
        collection: The feature collection to be exported.
        description: Human-readable name of the task.
        table: The fully-qualifed BigQuery destination table with
          "project_id.dataset_id.table_id" format.
        overwrite: Whether the existing table should be
          overwritten by the results of this export.
          The `overwrite` and `append` parameters cannot be `true`
          simultaneously. The export fails if the table already exists and both
          `overwrite` and `append` are `false`.
        append: Whether table data should be appended if the table already
          exists and has a compatible schema.
        selectors: The list of properties to include in the output, as a list of
          strings or a comma-separated string. By default, all properties are
          included.
        maxVertices: Max number of uncut vertices per geometry; geometries with
          more vertices will be cut into pieces smaller than this size.
        priority: The priority of the task within the project. Higher priority
          tasks are scheduled sooner. Must be an integer between 0 and 9999.
          Defaults to 100.
        **kwargs: Holds other keyword arguments that may have been deprecated.

      Returns:
        An unstarted Task that exports the table.


Creates a task to export an ImageCollection video to Cloud Storage.

      Args:
        collection: The image collection to be exported. The collection must
            only contain RGB images.
        description: Human-readable name of the task.
        bucket: The name of a Cloud Storage bucket for the export.
        fileNamePrefix: Cloud Storage object name prefix for the export.
            Defaults to the task's description.
        framesPerSecond: A number between .1 and 120 describing the
            framerate of the exported video.
        dimensions: The dimensions of the exported video. Takes either a
            single positive integer as the maximum dimension or "WIDTHxHEIGHT"
            where WIDTH and HEIGHT are each positive integers.
        region: The lon,lat coordinates for a LinearRing or Polygon
            specifying the region to export. Can be specified as a nested
            lists of numbers or a serialized string. Defaults to the first
            image's region.
        scale: The resolution in meters per pixel.
        crs: The coordinate reference system of the exported video's
            projection. Defaults to SR-ORG:6627.
        crsTransform: A comma-separated string of 6 numbers describing
            the affine transform of the coordinate reference system of the
            exported video's projection, in the order: xScale, xShearing,
            xTranslation, yShearing, yScale and yTranslation. Defaults to
            the image collection's native CRS transform.
        maxPixels: The maximum number of pixels per frame.
            Defaults to 1e8 pixels per frame. By setting this explicitly,
            you may raise or lower the limit.
        maxFrames: The maximum number of frames to export.
            Defaults to 1000 frames. By setting this explicitly, you may
            raise or lower the limit.
        priority: The priority of the task within the project. Higher priority
          tasks are scheduled sooner. Must be an integer between 0 and 9999.
          Defaults to 100.
        **kwargs: Holds other keyword arguments that may have been deprecated
            such as 'crs_transform'.

      Returns:
        An unstarted Task that exports the image collection
        to Google Cloud Storage.


Creates a task to export an ImageCollection as a video to Drive.

      Args:
        collection: The image collection to be exported. The collection must
            only contain RGB images.
        description: Human-readable name of the task.
        folder: The name of a unique folder in your Drive account to
            export into. Defaults to the root of the drive.
        fileNamePrefix: The Google Drive filename for the export.
            Defaults to the name of the task.
        framesPerSecond: A number between .1 and 120 describing the
            framerate of the exported video.
        dimensions: The dimensions of the exported video. Takes either a
            single positive integer as the maximum dimension or "WIDTHxHEIGHT"
            where WIDTH and HEIGHT are each positive integers.
        region: The lon,lat coordinates for a LinearRing or Polygon
            specifying the region to export. Can be specified as a nested
            lists of numbers or a serialized string. Defaults to the first
            image's region.
        scale: The resolution in meters per pixel.
        crs: The coordinate reference system of the exported video's
            projection. Defaults to SR-ORG:6627.
        crsTransform: A comma-separated string of 6 numbers describing
            the affine transform of the coordinate reference system of the
            exported video's projection, in the order: xScale, xShearing,
            xTranslation, yShearing, yScale and yTranslation. Defaults to
            the image collection's native CRS transform.
        maxPixels: The maximum number of pixels per frame.
            Defaults to 1e8 pixels per frame. By setting this explicitly,
            you may raise or lower the limit.
        maxFrames: The maximum number of frames to export.
            Defaults to 1000 frames. By setting this explicitly, you may
            raise or lower the limit.
        priority: The priority of the task within the project. Higher priority
          tasks are scheduled sooner. Must be an integer between 0 and 9999.
          Defaults to 100.
        **kwargs: Holds other keyword arguments that may have been deprecated
            such as 'crs_transform'.

      Returns:
        An unstarted Task that exports the image collection to Drive.


Creates a task to export an ee.Classifier as an Earth Engine asset.

      Only supported for ee.Classifier.smileRandomForest,
      ee.Classifier.smileCart, ee.Classifier.DecisionTree and
      ee.Classifier.DecisionTreeEnsemble.

      Args:
        classifier: The classifier to be exported.
        description: Human-readable name of the task.
        assetId: The destination asset ID.
        overwrite: If an existing asset can be overwritten by this export.
        priority: The priority of the task within the project. Higher priority
          tasks are scheduled sooner. Must be an integer between 0 and 9999.
          Defaults to 100.
        **kwargs: Holds other keyword arguments.

      Returns:
        An unstarted Task that exports the image as an Earth Engine Asset.


Performs all preparation steps for an image export.

  Args:
    image: The Image to be exported.
    config: All the user-specified export parameters. May be modified.
    export_destination: One of the Task.ExportDestination values.

  Returns:
    A config dict containing all information required for the export.


Performs all preparation steps for a map export.

  Args:
    image: The Image to be exported.
    config: All the user-specified export parameters. May be modified.

  Returns:
    A config dict containing all information required for the export.


Performs all preparation steps for a table export.

  Args:
    collection: The FeatureCollection to be exported.
    config: All the user-specified export parameters. May be modified.
    export_destination: One of the Task.ExportDestination values.

  Returns:
    A config dict containing all information required for the export.


Performs all preparation steps for a video export.

  Args:
    collection: The ImageCollection to be exported as a video.
    config: All the user-specified export parameters. May be modified.
    export_destination: One of the Task.ExportDestination values.

  Returns:
    A config dict containing all information required for the export.


Builds an ImageFileExportOptions from values in a config dict.

  Args:
    config: All the user-specified export parameters. Will be modified in-place
      by removing parameters used in the ImageFileExportOptions.
    export_destination: One of the Task.ExportDestination values.

  Returns:
    An ImageFileExportOptions containing information extracted from config.


Builds a TableFileExportOptions from values in a config dict.

  Args:
    config: All the user-specified export parameters. Will be modified in-place
      by removing parameters used in the TableFileExportOptions.
    export_destination: One of the Task.ExportDestination values.

  Returns:
    A TableFileExportOptions containing information extracted from config.


Builds a VideoOptions from values in a config dict.

  Args:
    config: All the user-specified export parameters. Will be modified in-place
      by removing parameters used in the VideoOptions.

  Returns:
    A VideoOptions containing information extracted from config.


Builds a VideoFileExportOptions from values in a config dict.

  Args:
    config: All the user-specified export parameters. Will be modified in-place
      by removing parameters used in the VideoFileExportOptions.
    export_destination: One of the Task.ExportDestination values.

  Returns:
    A VideoFileExportOptions containing information extracted from config.


Performs all preparation steps for a classifier export.

  Args:
    classifier: The Classifier to be exported.
    config: All the user-specified export parameters. May be modified.
    export_destination: One of the Task.ExportDestination values.

  Returns:
    A config dict containing all information required for the export.


Builds a DriveDestination from values in a config dict.

  Args:
    config: All the user-specified export parameters. Will be modified in-place
      by removing parameters used in the DriveDestination.

  Returns:
    A DriveDestination containing information extracted from config.


Builds a CloudStorageDestination from values in a config dict.

  Args:
    config: All the user-specified export parameters. Will be modified in-place
      by removing parameters used in the CloudStorageDestination.

  Returns:
    A CloudStorageDestination containing information extracted from
    config.


Builds a BigqueryDestination from values in a config dict.

  Args:
    config: All the user-specified export parameters. Will be modified in-place
      by removing parameters used in the BigqueryDestination.

  Returns:
    A BigqueryDestination containing information extracted from
    config.


Builds a TileOptions from values in a config dict.

  Args:
    config: All the user-specified export parameters. Will be modified in-place
      by removing parameters used in the TileOptions.

  Returns:
    A TileOptions containing information extracted from config.


Builds an EarthEngineDestination from values in a config dict.

  Args:
    config: All the user-specified export parameters. Will be modified in-place
      by removing parameters used in the EarthEngineDestination.

  Returns:
    An EarthEngineDestination containing information extracted from
    config.


Builds a FeatureViewDestination from values in a config dict.

  Args:
    config: All the user-specified export parameters. Will be modified in-place
      by removing parameters used in the FeatureViewDestination.

  Returns:
    A FeatureViewDestination containing information extracted from config.


Returns a RankByOneThingRule dict created from the rank-by-one-thing rule.

  Args:
    rule_str: The rule string. The string is expected in the format:
      `rule_type rule_direction`. Valid rule types include `.minZoomLevel`,
      `.geometryType`, or an arbitrary string to represent attribute rules.
      Valid rule directions include `ASC` or `DESC`.

  Returns:
    A RankByOneThingRule object containing information extracted from rule_str.


Returns a RankingRule dict created from the rank-by-one-thing rules.

  Args:
    rules: A string representing comma separated rank-by-one-thing rules, or a
      list of rank-by-one-thing rule strings.

  Returns:
    A RankingRule object containing information extracted from rules.


Returns a ThinningOptions dict created from the config.

  Args:
    config: The user-specified ingestion parameters. Will be modified in-place
      by removing parameters used in the ThinningOptions.

  Returns:
    A ThinningOptions object containing information extracted from config.


Returns a RankingOptions dict created from the config.

  Args:
    config: The user-specified export parameters. Will be modified in-place
      by removing parameters used in the RankingOptions.

  Returns:
    A RankingOptions object containing information extracted from config.


Builds a FeatureViewIngestionTimeParameters from values in a params dict.

  Args:
    input_params: All the user-specified ingestions time parameters. Will be
      modified in-place to remove fields in FeatureViewIngestionTimeParameters.

  Returns:
    A FeatureViewIngestionTimeParameters containing information extracted from
    config.


Creates an export task.

  Args:
    config: Custom config fields for the task.
    task_type: The type of the task to create. One of Task.Type.

  Returns:
    An unstarted export Task.


Creates a parameter dict by copying all non-None locals.

  This is generally invoked as the first part of call processing, via
  something like
    _capture_parameters(locals(), ['image'])
  so that all call parameters can be pulled into a single dict.

  Args:
    all_locals: The dict of local variables.
    parameters_to_exclude: An iterable giving names of parameters that should
      be excluded from the result.

  Returns:
    A dict containing all the non-None values in all_locals, except for
    those listed in parameters_to_exclude.


Canonicalizes a set of parameter names.

  For legacy and other reasons, there are multiple ways to specify some export
  parameters. This function applies canonicalization rules to simplify further
  processing. It validates that the canonicalization introduces no collisions.

  Note that config is changed in place and not returned.

  The parameter name mappings performed here are:
    crsTransform -> crs_transform
    bucket -> outputBucket
    fileNamePrefix, path -> outputPrefix or driveFileNamePrefix depending
      on whether the destination is GCS or Drive. "description" is used as
      the default value of outputPrefix or driveFileNamePrefix if nothing else
      provided a value.
    folder -> driveFolder
    If "fileFormat" is "GeoTIFF": tiffX -> formatOptions { x }
    If "fileFormat" is "TfRecord": tfrecordX -> formatOptions { x }

  The "region" parameter's value, if present, is processed with
  _canonicalize_region.

  The "selectors" parameter's value, if present and a string, is converted
  to a list by splitting at commas.

  Args:
    config: The configuration dictionary to be converted.
    destination: The type of destination targeted by the export.


Renames config[a] to config[b].


Converts a region parameter to a form appropriate for export.


Returns the names of the inputs used by this Clusterer.

    Or None if this Clusterer has not had any training data added yet.


Returns a trained Clusterer.

    Trains the Clusterer on a collection of features using the specified
    numeric properties of each feature as training data. The geometry of the
    features is ignored.

    Args:
      features: The collection to train on.
      inputProperties: The list of property names to include as training data.
        Each feature must have all these properties, and their values must be
        numeric. This argument is optional if the input collection contains a
        'band_order' property (as produced by Image.sample).
      subsampling: An optional subsampling factor, within (0, 1].
      subsamplingSeed: A randomization seed to use for subsampling.


Returns a weka Cascade K-Means Clusterer.

    Cascade simple k-means, selects the best k according to the
    Calinski-Harabasz criterion. For more information see:
    Calinski, T. and J. Harabasz. 1974. A dendrite method for cluster analysis,
    Commun. Stat. 3: 1-27.

    Args:
      minClusters: Min number of clusters.
      maxClusters: Max number of clusters.
      restarts: Number of restarts.
      manual: Manually select the number of clusters.
      init: Set whether to initialize using the probabilistic farthest first
        like method of the k-means++ algorithm (rather than the standard random
        selection of initial cluster centers).
      distanceFunction: Distance function to use. Options are: Euclidean and
        Manhattan.
      maxIterations: Maximum number of iterations for k-means.


Returns a weka Cobweb Clusterer.

    Implementation of the Cobweb clustering algorithm. For more information see:
    D. Fisher (1987). Knowledge acquisition via incremental conceptual
    clustering. Machine Learning. 2(2):139-172. and J. H. Gennari, P. Langley,
    D. Fisher (1990). Models of incremental concept formation. Artificial
    Intelligence. 40:11-61.

    Args:
      acuity: Acuity (minimum standard deviation).
      cutoff: Cutoff (minimum category utility).
      seed: Random number seed.