"""
Copyright 2022, the CVXPY authors.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""

# The implementation of partial_transpose is due to @duguyipiao.

from typing import Optional, Tuple

import numpy as np
import scipy.sparse as sp

from cvxpy.atoms.atom import Atom


def _term(expr, i: int, j: int, dims: Tuple[int], axis: Optional[int] = 0):
    """Helper function for partial transpose.

    Parameters
    ----------
    expr : :class:`~cvxpy.expressions.expression.Expression`
        The 2D expression to take the partial transpose of.
    i : int
        Term in the partial transpose sum.
    j : int
        Term in the partial transpose sum.
    dims : tuple of ints.
        A tuple of integers encoding the dimensions of each subsystem.
    axis : int
        The index of the subsystem to be transposed
        from the tensor product that defines expr.
    """
    # (I ⊗ |i><j| ⊗ I) x (I ⊗ |i><j| ⊗ I) for all (i,j)'s
    # in the system we want to transpose.
    # This function returns the (i,j)-th term in the sum, namely
    # (I ⊗ |i><j| ⊗ I) x (I ⊗ |i><j| ⊗ I).
    a = sp.coo_matrix(([1.0], ([0], [0])))
    for (i_axis, dim) in enumerate(dims):
        if i_axis == axis:
            v = sp.coo_matrix(([1], ([i], [j])), shape=(dim, dim))
            a = sp.kron(a, v)
        else:
            eye_mat = sp.eye(dim)
            a = sp.kron(a, eye_mat)
    return a @ expr @ a


def partial_transpose(expr, dims: Tuple[int], axis: Optional[int] = 0):
    """
    Assumes :math:`\\texttt{expr} = X_1 \\otimes ... \\otimes X_n` is a 2D Kronecker
    product composed of :math:`n = \\texttt{len(dims)}` implicit subsystems.
    Letting :math:`k = \\texttt{axis}`, the returned expression is a
    *partial transpose* of :math:`\\texttt{expr}`, with the transpose applied to its
    :math:`k^{\\text{th}}` implicit subsystem:

    .. math::
        X_1 \\otimes ... \\otimes X_k^T \\otimes ... \\otimes X_n.

    Parameters
    ----------
    expr : :class:`~cvxpy.expressions.expression.Expression`
        The 2D expression to take the partial transpose of.
    dims : tuple of ints.
        A tuple of integers encoding the dimensions of each subsystem.
    axis : int
        The index of the subsystem to be transposed
        from the tensor product that defines expr.
    """
    expr = Atom.cast_to_const(expr)
    if expr.ndim < 2 or expr.shape[0] != expr.shape[1]:
        raise ValueError("Only supports square matrices.")
    if axis < 0 or axis >= len(dims):
        raise ValueError(
            f"Invalid axis argument, should be between 0 and {len(dims)}, got {axis}."
        )
    if expr.shape[0] != np.prod(dims):
        raise ValueError("Dimension of system doesn't correspond to dimension of subsystems.")
    return sum([
        _term(expr, i, j, dims, axis) for i in range(dims[axis]) for j in range(dims[axis])
    ])
