#
# Copyright (C) 2016-2019 by Nathan Lovato, Daniel Oakey, Razvan Radulescu, and contributors
#
# This file is part of Power Sequencer.
#
# Power Sequencer is free software: you can redistribute it and/or modify it under the terms of the
# GNU General Public License as published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any later version.
#
# Power Sequencer is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY;
# without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License along with Power Sequencer. If
# not, see <https://www.gnu.org/licenses/>.
#
import numpy as np
import warnings


def segment_axis(a, length, overlap=0, axis=None, end="cut", endvalue=0):
    """Generate a new array that chops the given array along the given axis
    into overlapping frames.

    example:
    >>> segment_axis(arange(10), 4, 2)
    array([[0, 1, 2, 3],
           [2, 3, 4, 5],
           [4, 5, 6, 7],
           [6, 7, 8, 9]])

    arguments:
    a       The array to segment
    length  The length of each frame
    overlap The number of array elements by which the frames should overlap
    axis    The axis to operate on; if None, act on the flattened array
    end     What to do with the last frame, if the array is not evenly
            divisible into pieces. Options are:

            'cut'   Simply discard the extra values
            'wrap'  Copy values from the beginning of the array
            'pad'   Pad with a constant value

    endvalue    The value to use for end='pad'

    The array is not copied unless necessary (either because it is unevenly
    strided and being flattened or because end is set to 'pad' or 'wrap').
    """

    if axis is None:
        a = np.ravel(a)  # may copy
        axis = 0

    l = a.shape[axis]

    if overlap >= length:
        raise ValueError("frames cannot overlap by more than 100%")
    if overlap < 0 or length <= 0:
        raise ValueError("overlap must be nonnegative and length must " "be positive")

    if l < length or (l - length) % (length - overlap):
        if l > length:
            roundup = length + (1 + (l - length) // (length - overlap)) * (length - overlap)
            rounddown = length + ((l - length) // (length - overlap)) * (length - overlap)
        else:
            roundup = length
            rounddown = 0
        assert rounddown < l < roundup
        assert roundup == rounddown + (length - overlap) or (roundup == length and rounddown == 0)
        a = a.swapaxes(-1, axis)

        if end == "cut":
            a = a[..., :rounddown]
        elif end in ["pad", "wrap"]:  # copying will be necessary
            s = list(a.shape)
            s[-1] = roundup
            b = np.empty(s, dtype=a.dtype)
            b[..., :l] = a
            if end == "pad":
                b[..., l:] = endvalue
            elif end == "wrap":
                b[..., l:] = a[..., : roundup - l]
            a = b

        a = a.swapaxes(-1, axis)

    l = a.shape[axis]
    if l == 0:
        raise ValueError(
            "Not enough data points to segment array in 'cut' mode; " "try 'pad' or 'wrap'"
        )
    assert l >= length
    assert (l - length) % (length - overlap) == 0
    n = 1 + (l - length) // (length - overlap)
    s = a.strides[axis]
    newshape = a.shape[:axis] + (n, length) + a.shape[axis + 1 :]
    newstrides = a.strides[:axis] + ((length - overlap) * s, s) + a.strides[axis + 1 :]

    try:
        return np.ndarray.__new__(
            np.ndarray, strides=newstrides, shape=newshape, buffer=a, dtype=a.dtype
        )
    except TypeError:
        warnings.warn("Problem with ndarray creation forces copy.")
        a = a.copy()
        # Shape doesn't change but strides does
        newstrides = a.strides[:axis] + ((length - overlap) * s, s) + a.strides[axis + 1 :]
        return np.ndarray.__new__(
            np.ndarray, strides=newstrides, shape=newshape, buffer=a, dtype=a.dtype
        )
