"""An implementation of qubits and gates acting on them.

Todo:

* Update docstrings.
* Update tests.
* Implement apply using decompose.
* Implement represent using decompose or something smarter. For this to
  work we first have to implement represent for SWAP.
* Decide if we want upper index to be inclusive in the constructor.
* Fix the printing of Rk gates in plotting.
"""

from sympy import Expr, Matrix, exp, I, pi, Integer, Symbol
from sympy.functions import sqrt

from sympy.physics.quantum.qapply import qapply
from sympy.physics.quantum.qexpr import QuantumError, QExpr
from sympy.matrices import eye
from sympy.physics.quantum.tensorproduct import matrix_tensor_product

from sympy.physics.quantum.gate import (
    Gate, HadamardGate, SwapGate, OneQubitGate, CGate, PhaseGate, TGate, ZGate
)

__all__ = [
    'QFT',
    'IQFT',
    'RkGate',
    'Rk'
]

#-----------------------------------------------------------------------------
# Fourier stuff
#-----------------------------------------------------------------------------


class RkGate(OneQubitGate):
    """This is the R_k gate of the QTF."""
    gate_name = 'Rk'
    gate_name_latex = 'R'

    def __new__(cls, *args):
        if len(args) != 2:
            raise QuantumError(
                'Rk gates only take two arguments, got: %r' % args
            )
        # For small k, Rk gates simplify to other gates, using these
        # substitutions give us familiar results for the QFT for small numbers
        # of qubits.
        target = args[0]
        k = args[1]
        if k == 1:
            return ZGate(target)
        elif k == 2:
            return PhaseGate(target)
        elif k == 3:
            return TGate(target)
        args = cls._eval_args(args)
        inst = Expr.__new__(cls, *args)
        inst.hilbert_space = cls._eval_hilbert_space(args)
        return inst

    @classmethod
    def _eval_args(cls, args):
        # Fall back to this, because Gate._eval_args assumes that args is
        # all targets and can't contain duplicates.
        return QExpr._eval_args(args)

    @property
    def k(self):
        return self.label[1]

    @property
    def targets(self):
        return self.label[:1]

    @property
    def gate_name_plot(self):
        return r'$%s_%s$' % (self.gate_name_latex, str(self.k))

    def get_target_matrix(self, format='sympy'):
        if format == 'sympy':
            return Matrix([[1, 0], [0, exp(Integer(2)*pi*I/(Integer(2)**self.k))]])
        raise NotImplementedError(
            'Invalid format for the R_k gate: %r' % format)


Rk = RkGate


class Fourier(Gate):
    """Superclass of Quantum Fourier and Inverse Quantum Fourier Gates."""

    @classmethod
    def _eval_args(self, args):
        if len(args) != 2:
            raise QuantumError(
                'QFT/IQFT only takes two arguments, got: %r' % args
            )
        if args[0] >= args[1]:
            raise QuantumError("Start must be smaller than finish")
        return Gate._eval_args(args)

    def _represent_default_basis(self, **options):
        return self._represent_ZGate(None, **options)

    def _represent_ZGate(self, basis, **options):
        """
            Represents the (I)QFT In the Z Basis
        """
        nqubits = options.get('nqubits', 0)
        if nqubits == 0:
            raise QuantumError(
                'The number of qubits must be given as nqubits.')
        if nqubits < self.min_qubits:
            raise QuantumError(
                'The number of qubits %r is too small for the gate.' % nqubits
            )
        size = self.size
        omega = self.omega

        #Make a matrix that has the basic Fourier Transform Matrix
        arrayFT = [[omega**(
            i*j % size)/sqrt(size) for i in range(size)] for j in range(size)]
        matrixFT = Matrix(arrayFT)

        #Embed the FT Matrix in a higher space, if necessary
        if self.label[0] != 0:
            matrixFT = matrix_tensor_product(eye(2**self.label[0]), matrixFT)
        if self.min_qubits < nqubits:
            matrixFT = matrix_tensor_product(
                matrixFT, eye(2**(nqubits - self.min_qubits)))

        return matrixFT

    @property
    def targets(self):
        return range(self.label[0], self.label[1])

    @property
    def min_qubits(self):
        return self.label[1]

    @property
    def size(self):
        """Size is the size of the QFT matrix"""
        return 2**(self.label[1] - self.label[0])

    @property
    def omega(self):
        return Symbol('omega')


class QFT(Fourier):
    """The forward quantum Fourier transform."""

    gate_name = 'QFT'
    gate_name_latex = 'QFT'

    def decompose(self):
        """Decomposes QFT into elementary gates."""
        start = self.label[0]
        finish = self.label[1]
        circuit = 1
        for level in reversed(range(start, finish)):
            circuit = HadamardGate(level)*circuit
            for i in range(level - start):
                circuit = CGate(level - i - 1, RkGate(level, i + 2))*circuit
        for i in range((finish - start)//2):
            circuit = SwapGate(i + start, finish - i - 1)*circuit
        return circuit

    def _apply_operator_Qubit(self, qubits, **options):
        return qapply(self.decompose()*qubits)

    def _eval_inverse(self):
        return IQFT(*self.args)

    @property
    def omega(self):
        return exp(2*pi*I/self.size)


class IQFT(Fourier):
    """The inverse quantum Fourier transform."""

    gate_name = 'IQFT'
    gate_name_latex = '{QFT^{-1}}'

    def decompose(self):
        """Decomposes IQFT into elementary gates."""
        start = self.args[0]
        finish = self.args[1]
        circuit = 1
        for i in range((finish - start)//2):
            circuit = SwapGate(i + start, finish - i - 1)*circuit
        for level in range(start, finish):
            for i in reversed(range(level - start)):
                circuit = CGate(level - i - 1, RkGate(level, -i - 2))*circuit
            circuit = HadamardGate(level)*circuit
        return circuit

    def _eval_inverse(self):
        return QFT(*self.args)

    @property
    def omega(self):
        return exp(-2*pi*I/self.size)
