"""Window utilities and related functions.

A window is an instance of Window

    Window(column_offset, row_offset, width, height)

or a 2D N-D array indexer in the form of a tuple.

    ((row_start, row_stop), (col_start, col_stop))

The latter can be evaluated within the context of a given height and
width and a boolean flag specifying whether the evaluation is boundless
or not. If boundless=True, negative index values do not mean index from
the end of the array dimension as they do in the boundless=False case.

The newer float precision read-write window capabilities of Rasterio
require instances of Window to be used.
"""

from __future__ import division
import collections
import functools
import math
import warnings

import attr
from affine import Affine
import numpy as np

from rasterio.errors import WindowError
from rasterio.transform import rowcol, guard_transform


PIXEL_PRECISION = 6


class WindowMethodsMixin(object):
    """Mixin providing methods for window-related calculations.
    These methods are wrappers for the functionality in
    `rasterio.windows` module.

    A subclass with this mixin MUST provide the following
    properties: `transform`, `height` and `width`
    """

    def window(self, left, bottom, right, top, precision=None):
        """Get the window corresponding to the bounding coordinates.

        The resulting window is not cropped to the row and column
        limits of the dataset.

        Parameters
        ----------
        left: float
            Left (west) bounding coordinate
        bottom: float
            Bottom (south) bounding coordinate
        right: float
            Right (east) bounding coordinate
        top: float
            Top (north) bounding coordinate
        precision: int, optional
            Number of decimal points of precision when computing inverse
            transform.

        Returns
        -------
        window: Window
        """
        transform = guard_transform(self.transform)

        return from_bounds(
            left, bottom, right, top, transform=transform,
            height=self.height, width=self.width, precision=precision)

    def window_transform(self, window):
        """Get the affine transform for a dataset window.

        Parameters
        ----------
        window: rasterio.windows.Window
            Dataset window

        Returns
        -------
        transform: Affine
            The affine transform matrix for the given window
        """

        gtransform = guard_transform(self.transform)
        return transform(window, gtransform)

    def window_bounds(self, window):
        """Get the bounds of a window

        Parameters
        ----------
        window: rasterio.windows.Window
            Dataset window

        Returns
        -------
        bounds : tuple
            x_min, y_min, x_max, y_max for the given window
        """

        transform = guard_transform(self.transform)
        return bounds(window, transform)


def iter_args(function):
    """Decorator to allow function to take either *args or
    a single iterable which gets expanded to *args.
    """
    @functools.wraps(function)
    def wrapper(*args, **kwargs):
        if len(args) == 1 and isinstance(args[0], collections.Iterable):
            return function(*args[0])
        else:
            return function(*args)
    return wrapper


def toranges(window):
    """Normalize Windows to range tuples"""
    if isinstance(window, Window):
        return window.toranges()
    else:
        return window


def get_data_window(arr, nodata=None):
    """Window covering the input array's valid data pixels.

    Parameters
    ----------
    arr: numpy ndarray, <= 3 dimensions
    nodata: number
        If None, will either return a full window if arr is not a masked
        array, or will use the mask to determine non-nodata pixels.
        If provided, it must be a number within the valid range of the
        dtype of the input array.

    Returns
    -------
    Window
    """

    num_dims = len(arr.shape)
    if num_dims > 3:
        raise WindowError(
            "get_data_window input array must have no more than "
            "3 dimensions")

    if nodata is None:
        if not hasattr(arr, 'mask'):
            return Window.from_slices((0, arr.shape[-2]), (0, arr.shape[-1]))
    else:
        arr = np.ma.masked_array(arr, arr == nodata)

    if num_dims == 2:
        data_rows, data_cols = np.where(np.equal(arr.mask, False))
    else:
        data_rows, data_cols = np.where(
            np.any(np.equal(np.rollaxis(arr.mask, 0, 3), False), axis=2))

    if data_rows.size:
        row_range = (data_rows.min(), data_rows.max() + 1)
    else:
        row_range = (0, 0)

    if data_cols.size:
        col_range = (data_cols.min(), data_cols.max() + 1)
    else:
        col_range = (0, 0)

    return Window.from_slices(row_range, col_range)


@iter_args
def union(*windows):
    """
    Union windows and return the outermost extent they cover.

    Parameters
    ----------
    windows: sequence
        One or more Windows.

    Returns
    -------
    Window
    """
    stacked = np.dstack([toranges(w) for w in windows])
    return Window.from_slices(
        (stacked[0, 0].min(), stacked[0, 1].max()),
        (stacked[1, 0].min(), stacked[1, 1]. max()))


@iter_args
def intersection(*windows):
    """Innermost extent of window intersections.

    Will raise WindowError if windows do not intersect.

    Parameters
    ----------
    windows: sequence
        One or more Windows.

    Returns
    -------
    Window
    """
    if not intersect(windows):
        raise WindowError("windows do not intersect")

    stacked = np.dstack([toranges(w) for w in windows])
    return Window.from_slices(
        (stacked[0, 0].max(), stacked[0, 1].min()),
        (stacked[1, 0].max(), stacked[1, 1]. min()))


@iter_args
def intersect(*windows):
    """Test if all given windows intersect.

    Parameters
    ----------
    windows: sequence
        One or more Windows.

    Returns
    -------
    bool
        True if all windows intersect.
    """
    from itertools import combinations

    def intersects(range1, range2):
        return not (
            range1[0] >= range2[1] or range1[1] <= range2[0])

    windows = np.array([toranges(w) for w in windows])

    for i in (0, 1):
        for c in combinations(windows[:, i], 2):
            if not intersects(*c):
                return False

    return True


def from_bounds(left, bottom, right, top, transform=None,
                height=None, width=None, precision=None):
    """Get the window corresponding to the bounding coordinates.

    Parameters
    ----------
    left, bottom, right, top: float
        Left (west), bottom (south), right (east), and top (north)
        bounding coordinates.
    transform: Affine
        Affine transform matrix.
    height, width: int
        Number of rows and columns of the window.
    precision: int, optional
        Number of decimal points of precision when computing inverse
        transform.

    Returns
    -------
    Window
        A new Window
    """
    row_start, col_start = rowcol(
        transform, left, top, op=float, precision=precision)

    row_stop, col_stop = rowcol(
        transform, right, bottom, op=float, precision=precision)

    return Window.from_slices(
        (row_start, row_stop), (col_start, col_stop), height=height,
        width=width, boundless=True)


def transform(window, transform):
    """Construct an affine transform matrix relative to a window.

    Parameters
    ----------
    window: Window
        The input window.
    transform: Affine
        an affine transform matrix.

    Returns
    -------
    Affine
        The affine transform matrix for the given window
    """
    window = evaluate(window, height=0, width=0)

    x, y = transform * (window.col_off or 0.0, window.row_off or 0.0)
    return Affine.translation(
        x - transform.c, y - transform.f) * transform


def bounds(window, transform, height=0, width=0):
    """Get the spatial bounds of a window.

    Parameters
    ----------
    window: Window
        The input window.
    transform: Affine
        an affine transform matrix.

    Returns
    -------
    left, bottom, right, top: float
        A tuple of spatial coordinate bounding values.
    """
    window = evaluate(window, height=height, width=width)

    row_min = window.row_off
    row_max = row_min + window.height
    col_min = window.col_off
    col_max = col_min + window.width

    left, bottom = transform * (col_min, row_max)
    right, top = transform * (col_max, row_min)
    return left, bottom, right, top


def crop(window, height, width):
    """Crops a window to given height and width.

    Parameters
    ----------
    window : Window.
        The input window.
    height, width : int
        The number of rows and cols in the cropped window.

    Returns
    -------
    Window
        A new Window object.
    """
    window = evaluate(window, height=height, width=width)

    row_start = min(max(window.row_off, 0), height)
    col_start = min(max(window.col_off, 0), width)
    row_stop = max(0, min(window.row_off + window.height, height))
    col_stop = max(0, min(window.col_off + window.width, width))

    return Window(col_start, row_start, col_stop - col_start,
                  row_stop - row_start)


def evaluate(window, height, width, boundless=False):
    """Evaluates a window tuple that may contain relative index values.

    The height and width of the array the window targets is the context
    for evaluation.

    Parameters
    ----------
    window: Window or tuple of (rows, cols).
        The input window.
    height, width: int
        The number of rows or columns in the array that the window
        targets.

    Returns
    -------
    Window
        A new Window object with absolute index values.
    """
    if isinstance(window, Window):
        return window
    else:
        rows, cols = window
        return Window.from_slices(rows=rows, cols=cols, height=height,
                                  width=width, boundless=boundless)


def shape(window, height=-1, width=-1):
    """The shape of a window.

    height and width arguments are optional if there are no negative
    values in the window.

    Parameters
    ----------
    window: Window
        The input window.
    height, width : int, optional
        The number of rows or columns in the array that the window
        targets.

    Returns
    -------
    num_rows, num_cols
        The number of rows and columns of the window.
    """
    evaluated = evaluate(window, height, width)
    return evaluated.height, evaluated.width


def window_index(window, height=0, width=0):
    """Construct a pair of slice objects for ndarray indexing

    Starting indexes are rounded down, Stopping indexes are rounded up.

    Parameters
    ----------
    window: Window
        The input window.

    Returns
    -------
    row_slice, col_slice: slice
        A pair of slices in row, column order
    """
    window = evaluate(window, height=height, width=width)

    (row_start, row_stop), (col_start, col_stop) = window.toranges()
    return (
        slice(int(math.floor(row_start)), int(math.ceil(row_stop))),
        slice(int(math.floor(col_start)), int(math.ceil(col_stop))))


def round_window_to_full_blocks(window, block_shapes, height=0, width=0):
    """Round window to include full expanse of intersecting tiles.

    Parameters
    ----------
    window: Window
        The input window.

    block_shapes : tuple of block shapes
        The input raster's block shape. All bands must have the same
        block/stripe structure

    Returns
    -------
    Window
    """
    if len(set(block_shapes)) != 1:  # pragma: no cover
        raise WindowError(
            "All bands must have the same block/stripe structure")

    window = evaluate(window, height=height, width=width)

    height_shape = block_shapes[0][0]
    width_shape = block_shapes[0][1]

    (row_start, row_stop), (col_start, col_stop) = window.toranges()

    row_min = int(row_start // height_shape) * height_shape
    row_max = int(row_stop // height_shape) * height_shape + \
        (height_shape if row_stop % height_shape != 0 else 0)

    col_min = int(col_start // width_shape) * width_shape
    col_max = int(col_stop // width_shape) * width_shape + \
        (width_shape if col_stop % width_shape != 0 else 0)

    return Window(col_min, row_min, col_max - col_min, row_max - row_min)


def validate_length_value(instance, attribute, value):
    if value and value < 0:
        raise ValueError("Number of columns or rows must be non-negative")


@attr.s(slots=True)
class Window(object):
    """Windows are rectangular subsets of rasters.

    This class abstracts the 2-tuples mentioned in the module docstring
    and adds methods and new constructors.

    Attributes
    ----------
    col_off, row_off: float
        The offset for the window.
    width, height: float
        Lengths of the window.

    Previously the lengths were called 'num_cols' and 'num_rows' but
    this is a bit confusing in the new float precision world and the
    attributes have been changed. The originals are deprecated.
    """
    col_off = attr.ib()
    row_off = attr.ib()
    width = attr.ib(validator=validate_length_value)
    height = attr.ib(validator=validate_length_value)

    def __repr__(self):
        """Return a nicely formatted representation string"""
        return (
            "Window(col_off={self.col_off}, row_off={self.row_off}, "
            "width={self.width}, height={self.height})").format(
                self=self)

    def flatten(self):
        """A flattened form of the window.

        Returns
        -------
        col_off, row_off, width, height: float
            Window offsets and lengths.
        """
        return (self.col_off, self.row_off, self.width, self.height)

    def todict(self):
        """A mapping of attribute names and values.

        Returns
        -------
        dict
        """
        return collections.OrderedDict(
            col_off=self.col_off, row_off=self.row_off, width=self.width,
            height=self.height)

    def toranges(self):
        """Makes an equivalent pair of range tuples"""
        return (
            (self.row_off, self.row_off + self.height),
            (self.col_off, self.col_off + self.width))

    def toslices(self):
        """Slice objects for use as an ndarray indexer.

        Returns
        -------
        row_slice, col_slice: slice
            A pair of slices in row, column order
        """
        return tuple(slice(*rng) for rng in self.toranges())

    @classmethod
    def from_slices(cls, rows, cols, height=-1, width=-1, boundless=False):
        """Construct a Window from row and column slices or tuples / lists of
        start and stop indexes. Converts the rows and cols to offsets, height,
        and width.

        In general, indexes are defined relative to the upper left corner of
        the dataset: rows=(0, 10), cols=(0, 4) defines a window that is 4
        columns wide and 10 rows high starting from the upper left.

        Start indexes may be `None` and will default to 0.
        Stop indexes may be `None` and will default to width or height, which
        must be provided in this case.

        Negative start indexes are evaluated relative to the lower right of the
        dataset: rows=(-2, None), cols=(-2, None) defines a window that is 2
        rows high and 2 columns wide starting from the bottom right.

        Parameters
        ----------
        rows, cols: slice, tuple, or list
            Slices or 2 element tuples/lists containing start, stop indexes.
        height, width: float
            A shape to resolve relative values against. Only used when a start
            or stop index is negative or a stop index is None.
        boundless: bool, optional
            Whether the inputs are bounded (default) or not.

        Returns
        -------
        Window
        """

        # Normalize to slices
        if isinstance(rows, (tuple, list)):
            if len(rows) != 2:
                raise WindowError("rows must have a start and stop index")
            rows = slice(*rows)

        elif not isinstance(rows, slice):
            raise WindowError("rows must be a slice, tuple, or list")

        if isinstance(cols, (tuple, list)):
            if len(cols) != 2:
                raise WindowError("cols must have a start and stop index")
            cols = slice(*cols)

        elif not isinstance(cols, slice):
            raise WindowError("cols must be a slice, tuple, or list")

        # Height and width are required if stop indices are implicit
        if rows.stop is None and height < 0:
            raise WindowError("height is required if row stop index is None")

        if cols.stop is None and width < 0:
            raise WindowError("width is required if col stop index is None")

        # Convert implicit indices to offsets, height, and width
        row_off = 0.0 if rows.start is None else rows.start
        row_stop = height if rows.stop is None else rows.stop

        col_off = 0.0 if cols.start is None else cols.start
        col_stop = width if cols.stop is None else cols.stop

        if not boundless:
            if (row_off < 0 or row_stop < 0):
                if height < 0:
                    raise WindowError("height is required when providing "
                                      "negative indexes")

                if row_off < 0:
                    row_off += height

                if row_stop < 0:
                    row_stop += height

            if (col_off < 0 or col_stop < 0):
                if width < 0:
                    raise WindowError("width is required when providing "
                                      "negative indexes")

                if col_off < 0:
                    col_off += width

                if col_stop < 0:
                    col_stop += width

        num_cols = max(col_stop - col_off, 0.0)
        num_rows = max(row_stop - row_off, 0.0)

        return cls(col_off=col_off, row_off=row_off, width=num_cols,
                   height=num_rows)

    def round_lengths(self, op='floor', pixel_precision=None):
        """Return a copy with width and height rounded.

        Lengths are rounded to the nearest whole number. The offsets
        are not changed.

        Parameters
        ----------
        op: str
            'ceil' or 'floor'
        pixel_precision: int, optional (default: None)
            Number of places of rounding precision.

        Returns
        -------
        Window
        """
        operator = getattr(math, op, None)
        if not operator:
            raise WindowError("operator must be 'ceil' or 'floor'")
        else:
            return Window(
                self.col_off, self.row_off,
                operator(round(self.width, pixel_precision) if
                         pixel_precision is not None else self.width),
                operator(round(self.height, pixel_precision) if
                         pixel_precision is not None else self.height))

    round_shape = round_lengths

    def round_offsets(self, op='floor', pixel_precision=None):
        """Return a copy with column and row offsets rounded.

        Offsets are rounded to the nearest whole number. The lengths
        are not changed.

        Parameters
        ----------
        op : str
            'ceil' or 'floor'
        pixel_precision : int, optional (default: None)
            Number of places of rounding precision.

        Returns
        -------
        Window
        """
        operator = getattr(math, op, None)
        if not operator:
            raise WindowError("operator must be 'ceil' or 'floor'")
        else:
            return Window(
                operator(round(self.col_off, pixel_precision) if
                         pixel_precision is not None else self.col_off),
                operator(round(self.row_off, pixel_precision) if
                         pixel_precision is not None else self.row_off),
                self.width, self.height)

    def crop(self, height, width):
        """Return a copy cropped to height and width"""
        return crop(self, height, width)

    def intersection(self, other):
        """Return the intersection of this window and another

        Parameters
        ----------

        other: Window
            Another window

        Returns
        -------
        Window
        """
        return intersection([self, other])
