r"""
Reed-Muller code

Given integers `m, r` and a finite field `F`,
the corresponding Reed-Muller Code is the set:

.. MATH::

    \{ (f(\alpha_i)\mid \alpha_i \in F^m)  \mid  f \in F[x_1,x_2,\ldots,x_m], \deg f \leq r \}

This file contains the following elements:

    - :class:`QAryReedMullerCode`, the class for Reed-Muller codes over non-binary field of size q and `r<q`
    - :class:`BinaryReedMullerCode`, the class for Reed-Muller codes over binary field and `r<=m`
    - :class:`ReedMullerVectorEncoder`, an encoder with a vectorial message space (for both the two code classes)
    - :class:`ReedMullerPolynomialEncoder`, an encoder with a polynomial message space (for both the code classes)
"""
#*****************************************************************************
#       Copyright (C) 2016 Parthasarathi Panda <parthasarathipanda314@gmail.com>
#
# This program 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 2 of the License, or
# (at your option) any later version.
#                  http://www.gnu.org/licenses/
#*****************************************************************************
from six.moves import range

from operator import mul
from sage.matrix.constructor import matrix
from sage.functions.other import binomial
from sage.calculus.var import var
from sage.misc.functional import symbolic_sum
from sage.coding.linear_code import AbstractLinearCode, LinearCodeSyndromeDecoder
from sage.coding.encoder import Encoder
from sage.combinat.subset import Subsets
from sage.combinat.tuple import Tuples
from sage.categories.finite_fields import FiniteFields
from sage.rings.finite_rings.finite_field_constructor import GF
from sage.rings.integer import Integer
from sage.modules.free_module_element import vector
from sage.rings.polynomial.polynomial_ring_constructor import PolynomialRing
from sage.interfaces.gap import gfq_gap_to_sage
from sage.interfaces.all import gap
from sage.misc.cachefunc import cached_method
from functools import reduce


def _binomial_sum(n, k):
    r"""
    Returns the sum of all binomials `\binom{n}{i}`,
    with `i` ranging from `0` to `k` and including `k`.

    INPUT:

    - ``n, k`` - integers

    EXAMPLES::

        sage: from sage.coding.reed_muller_code import _binomial_sum
        sage: _binomial_sum(4, 2)
        11
    """
    s = 1
    nCi = 1
    for i in range(k):
        nCi = ((n - i) * nCi) // (i + 1)
        s = nCi + s
    return s


def _multivariate_polynomial_interpolation(evaluation, order, polynomial_ring):
    r"""
    Returns `f \in \GF(q)[X_1,...,X_m]` such that `f(\mathbf a) = v[i(\mathbf a)]`
    for all `\mathbf a \in \GF(q^m)`, where `v \in GF(q){qm}` is a given
    vector of evaluations, and `i(a)` is a specific ordering of `GF(q^m)` (see below for details)

    The ordering `i(a)` is the one used by Sage when listing the elements
    of a Finite Field with a call to the method ``list``.

    In case the polynomial `f` does not exist, this method returns an arbitrary polynomial.

    INPUT:

    - ``evaluation`` -- A vector or a list of evaluation of the polynomial at all the points.

    - ``num_of_var`` -- The number of variables used in the polynomial to interpolate

    - ``order`` -- The degree of the polynomial to interpolate

    - ``polynomial_ring`` -- The Polynomial Ring the polynomial in question is from

    EXAMPLES::

        sage: from sage.coding.reed_muller_code import _multivariate_polynomial_interpolation
        sage: F = GF(3)
        sage: R.<x,y> = F[]
        sage: v = vector(F, [1, 2, 0, 0, 2, 1, 1, 1, 1])
        sage: _multivariate_polynomial_interpolation(v, 2, R)
        x*y + y^2 + x + y + 1

    If there does not exist
    """
    def _interpolate(evaluation, num_of_var, order):
        if num_of_var == 0 or order == 0:
            return evaluation[0]
        base_field = polynomial_ring.base_ring()
        q = base_field.cardinality()
        n_by_q = q**(num_of_var - 1)
        d = min(order + 1, q)
        multipoint_evaluation_list = []
        uni_poly_ring = PolynomialRing(base_field, 'x')
        base_field_zero = base_field.zero()
        for k in range(n_by_q):
            iterator = iter(base_field)
            points = []
            for i in range(d):
                xcoordinate = next(iterator)
                points.append((xcoordinate, evaluation[k + i * n_by_q]))
            polyVector = uni_poly_ring.lagrange_polynomial(
                points).coefficients(sparse=False)
            if len(polyVector) < d:
                # adding zeros to represet a (d-1) degree polynomial
                polyVector += [base_field_zero] * (d - len(polyVector))
            multipoint_evaluation_list.append(polyVector)
        poly = polynomial_ring.zero()
        z = 1
        x = polynomial_ring.gen(num_of_var - 1)
        for k in range(d):  # computing the polynomial
            poly = poly + z * _interpolate([multipoint_evaluation_list[i][k]
                                            for i in range(n_by_q)], num_of_var - 1, order - k)
            z *= x
        return poly
    return _interpolate(evaluation, polynomial_ring.ngens(), order)


def ReedMullerCode(base_field, order, num_of_var):
    r"""
    Returns a Reed-Muller code.

    A Reed-Muller Code of order `r` and number of variables `m` over a finite field `F` is the set:

    .. MATH::

        \{ (f(\alpha_i)\mid \alpha_i \in F^m)  \mid  f \in F[x_1,x_2,\ldots,x_m], \deg f \leq r \}

    INPUT:

    - ``base_field`` -- The finite field `F` over which the code is built.

    - ``order`` -- The order of the Reed-Muller Code, which is the maximum
                   degree of the polynomial to be used in the code.

    - ``num_of_var`` -- The number of variables used in polynomial.

    .. WARNING::

        For now, this implementation only supports Reed-Muller codes whose order is less than q.
        Binary Reed-Muller codes must have their order less than or
        equal to their number of variables.

    EXAMPLES:

    We build a Reed-Muller code::

        sage: F = GF(3)
        sage: C = codes.ReedMullerCode(F, 2, 2)
        sage: C
        Reed-Muller Code of order 2 and 2 variables over Finite Field of size 3

    We ask for its parameters::

        sage: C.length()
        9
        sage: C.dimension()
        6
        sage: C.minimum_distance()
        3

    If one provides a finite field of size 2, a Binary Reed-Muller code is built::

        sage: F = GF(2)
        sage: C = codes.ReedMullerCode(F, 2, 2)
        sage: C
        Binary Reed-Muller Code of order 2 and number of variables 2
    """
    if not(base_field in FiniteFields):
        raise ValueError("The parameter `base_field` must be a finite field")
    q = base_field.cardinality()
    if q == 2:
        return BinaryReedMullerCode(order, num_of_var)
    else:
        return QAryReedMullerCode(base_field, order, num_of_var)


class QAryReedMullerCode(AbstractLinearCode):
    r"""
    Representation of a q-ary Reed-Muller code.

    For details on the definition of Reed-Muller codes, refer to
    :meth:`ReedMullerCode`.

    .. NOTE::

        It is better to use the aforementioned method rather than calling
        this class directly, as :meth:`ReedMullerCode` creates either
        a binary or a q-ary Reed-Muller code according to the arguments it receives.

    INPUT:

    - ``base_field`` -- A finite field, which is the base field of the code.

    - ``order`` -- The order of the Reed-Muller Code, i.e., the maximum degree of the polynomial to be used in the code.

    - ``num_of_var`` -- The number of variables used in polynomial.

    .. WARNING::

        For now, this implementation only supports Reed-Muller codes whose order is less than q.

    EXAMPLES::

        sage: from sage.coding.reed_muller_code import QAryReedMullerCode
        sage: F = GF(3)
        sage: C = QAryReedMullerCode(F, 2, 2)
        sage: C
        Reed-Muller Code of order 2 and 2 variables over Finite Field of size 3
    """

    _registered_encoders = {}
    _registered_decoders = {}

    def __init__(self, base_field, order, num_of_var):
        r"""
        TESTS:

        Note that the order given cannot be greater than (q-1). An error is raised if that happens::

            sage: from sage.coding.reed_muller_code import QAryReedMullerCode
            sage: C = QAryReedMullerCode(GF(3), 4, 4)
            Traceback (most recent call last):
            ...
            ValueError: The order must be less than 3

        The order and the number of variable must be integers::

            sage: C = QAryReedMullerCode(GF(3),1.1,4)
            Traceback (most recent call last):
            ...
            ValueError: The order of the code must be an integer

        The base_field parameter must be a finite field::

            sage: C = QAryReedMullerCode(QQ,1,4)
            Traceback (most recent call last):
            ...
            ValueError: the input `base_field` must be a FiniteField
        """
        # input sanitization
        if not(base_field in FiniteFields):
            raise ValueError("the input `base_field` must be a FiniteField")
        if not(isinstance(order, (Integer, int))):
            raise ValueError("The order of the code must be an integer")
        if not(isinstance(num_of_var, (Integer, int))):
            raise ValueError("The number of variables must be an integer")
        q = base_field.cardinality()
        if (order >= q):
            raise ValueError("The order must be less than %s" % q)

        super(QAryReedMullerCode,self).__init__(base_field, q**num_of_var, "EvaluationVector", "Syndrome")
        self._order = order
        self._num_of_var = num_of_var
        self._dimension = binomial(num_of_var + order, order)

    def order(self):
        r"""
        Returns the order of ``self``.

        Order is the maximum degree of the polynomial used in the Reed-Muller code.

        EXAMPLES::

            sage: from sage.coding.reed_muller_code import QAryReedMullerCode
            sage: F = GF(59)
            sage: C = QAryReedMullerCode(F, 2, 4)
            sage: C.order()
            2
        """
        return self._order

    def number_of_variables(self):
        r"""
        Returns the number of variables of the polynomial ring used in ``self``.

        EXAMPLES::

            sage: from sage.coding.reed_muller_code import QAryReedMullerCode
            sage: F = GF(59)
            sage: C = QAryReedMullerCode(F, 2, 4)
            sage: C.number_of_variables()
            4
        """
        return self._num_of_var

    def minimum_distance(self):
        r"""
        Returns the minimum distance between two words in ``self``.

        The minimum distance of a q-ary Reed-Muller code with order `d` and number of variables `m` is `(q-d)q^{m-1}`

        EXAMPLES::

            sage: from sage.coding.reed_muller_code import QAryReedMullerCode
            sage: F = GF(5)
            sage: C = QAryReedMullerCode(F, 2, 4)
            sage: C.minimum_distance()
            375
        """
        d = self.order()
        q = self.base_field().cardinality()
        n = self.length()
        return ((q - d) * n) // q

    def _repr_(self):
        r"""
        Returns a string representation of ``self``.

        EXAMPLES::

            sage: from sage.coding.reed_muller_code import QAryReedMullerCode
            sage: F = GF(59)
            sage: C = QAryReedMullerCode(F, 2, 4)
            sage: C
            Reed-Muller Code of order 2 and 4 variables over Finite Field of size 59
        """
        return "Reed-Muller Code of order %s and %s variables over %s" % (
            self.order(), self.number_of_variables(), self.base_field())

    def _latex_(self):
        r"""
        Returns a latex representation of ``self``.

        EXAMPLES::

            sage: from sage.coding.reed_muller_code import QAryReedMullerCode
            sage: F = GF(59)
            sage: C = QAryReedMullerCode(F, 2, 4)
            sage: latex(C)
            \textnormal{Reed-Muller Code of order} 2 \textnormal{and }4 \textnormal{variables over} \Bold{F}_{59}
        """
        return "\\textnormal{Reed-Muller Code of order} %s \\textnormal{and }%s \\textnormal{variables over} %s"\
            % (self.order(), self.number_of_variables(), self.base_field()._latex_())

    def __eq__(self, other):
        r"""
        Tests equality between Reed-Muller Code objects.

        EXAMPLES::

            sage: from sage.coding.reed_muller_code import QAryReedMullerCode
            sage: F = GF(59)
            sage: C1 = QAryReedMullerCode(F, 2, 4)
            sage: C2 = QAryReedMullerCode(GF(59), 2, 4)
            sage: C1.__eq__(C2)
            True
        """
        # I am not comparing the base field directly because of possible change
        # in variables
        return isinstance(other, QAryReedMullerCode) \
            and self.base_field() == other.base_field() \
            and self.order() == other.order() \
            and self.number_of_variables() == other.number_of_variables()


class BinaryReedMullerCode(AbstractLinearCode):
    r"""
    Representation of a binary Reed-Muller code.

    For details on the definition of Reed-Muller codes, refer to
    :meth:`ReedMullerCode`.

    .. NOTE::

        It is better to use the aforementioned method rather than calling
        this class directly, as :meth:`ReedMullerCode` creates either
        a binary or a q-ary Reed-Muller code according to the arguments it receives.


    INPUT:

    - ``order`` -- The order of the Reed-Muller Code, i.e., the maximum degree of the polynomial to be used in the code.

    - ``num_of_var`` -- The number of variables used in the polynomial.

    EXAMPLES:

    A binary Reed-Muller code can be constructed by simply giving the order of the code and the number of variables::

        sage: C = codes.BinaryReedMullerCode(2, 4)
        sage: C
        Binary Reed-Muller Code of order 2 and number of variables 4
    """

    _registered_encoders = {}
    _registered_decoders = {}

    def __init__(self, order, num_of_var):
        r"""
        TESTS:

        If the order given is greater than the number of variables an error is raised::

            sage: C = codes.BinaryReedMullerCode(5, 4)
            Traceback (most recent call last):
            ...
            ValueError: The order must be less than or equal to 4

        The order and the number of variable must be integers::

            sage: C = codes.BinaryReedMullerCode(1.1,4)
            Traceback (most recent call last):
            ...
            ValueError: The order of the code must be an integer
        """
        # input sanitization
        if not(isinstance(order, (Integer, int))):
            raise ValueError("The order of the code must be an integer")
        if not(isinstance(num_of_var, (Integer, int))):
            raise ValueError("The number of variables must be an integer")
        if (num_of_var < order):
            raise ValueError(
                "The order must be less than or equal to %s" %
                num_of_var)

        super(BinaryReedMullerCode, self).__init__(GF(2), 2**num_of_var,
            "EvaluationVector", "Syndrome")
        self._order = order
        self._num_of_var = num_of_var
        self._dimension = _binomial_sum(num_of_var, order)

    def order(self):
        r"""
        Returns the order of ``self``. Order is the maximum degree of the polynomial used in the Reed-Muller code.

        EXAMPLES::

            sage: C = codes.BinaryReedMullerCode(2, 4)
            sage: C.order()
            2
        """
        return self._order

    def number_of_variables(self):
        r"""
        Returns the number of variables of the polynomial ring used in ``self``.

        EXAMPLES::

            sage: C = codes.BinaryReedMullerCode(2, 4)
            sage: C.number_of_variables()
            4
        """
        return self._num_of_var

    def minimum_distance(self):
        r"""
        Returns the minimum distance of ``self``.
        The minimum distance of a binary Reed-Muller code of order $d$ and number of variables $m$ is $q^{m-d}$

        EXAMPLES::

            sage: C = codes.BinaryReedMullerCode(2, 4)
            sage: C.minimum_distance()
            4
        """
        return 2**(self.number_of_variables() - self.order())

    def _repr_(self):
        r"""
        Returns a string representation of ``self``.

        EXAMPLES::

            sage: C = codes.BinaryReedMullerCode(2, 4)
            sage: C
            Binary Reed-Muller Code of order 2 and number of variables 4
        """
        return "Binary Reed-Muller Code of order %s and number of variables %s" % (
            self.order(), self.number_of_variables())

    def _latex_(self):
        r"""
        Returns a latex representation of ``self``.

        EXAMPLES::

            sage: C = codes.BinaryReedMullerCode(2, 4)
            sage: latex(C)
            \textnormal{Binary Reed-Muller Code of order} 2 \textnormal{and number of variables} 4
        """
        return "\\textnormal{Binary Reed-Muller Code of order} %s \\textnormal{and number of variables} %s" % (
            self.order(), self.number_of_variables())

    def __eq__(self, other):
        r"""
        Tests equality between Reed-Muller Code objects.

        EXAMPLES::

            sage: C1 = codes.BinaryReedMullerCode(2, 4)
            sage: C2 = codes.BinaryReedMullerCode(2, 4)
            sage: C1.__eq__(C2)
            True
        """
        return isinstance(other, BinaryReedMullerCode) \
            and self.order() == other.order() \
            and self.number_of_variables() == other.number_of_variables()


class ReedMullerVectorEncoder(Encoder):
    r"""
    Encoder for Reed-Muller codes which encodes vectors into codewords.

    Consider a Reed-Muller code of order `r`, number of variables `m`, length `n`,
    dimension `k` over some finite field `F`.
    Let those variables be `(x_1, x_2, \dots, x_m)`.
    We order the monomials by lowest power on lowest index variables. If we have three monomials
    `x_1 \times x_2`, `x_1 \times x_2^2` and `x_1^2 \times x_2`, the ordering is:
    `x_1 \times x_2 < x_1 \times x_2^2 < x_1^2 \times x_2`

    Let now `(v_1,v_2,\ldots,v_k)` be a vector of `F`, which corresponds to the polynomial
    `f = \Sigma^{k}_{i=1} v_i \times x_i`.

    Let `(\beta_1, \beta_2, \ldots, \beta_q)` be the elements of `F` ordered as they are
    returned by Sage when calling ``F.list()``.

    The aforementioned polynomial `f` is encoded as:

    `(f(\alpha_{11},\alpha_{12},\ldots,\alpha_{1m}),f(\alpha_{21},\alpha_{22},\ldots,
    \alpha_{2m}),\ldots,f(\alpha_{q^m1},\alpha_{q^m2},\ldots,\alpha_{q^mm}`, with
    `\alpha_{ij}=\beta_{i \ mod \ q^j} \forall (i,j)`

    INPUT:

    - ``code`` -- The associated code of this encoder.

    EXAMPLES::

        sage: C1=codes.ReedMullerCode(GF(2), 2, 4)
        sage: E1=codes.encoders.ReedMullerVectorEncoder(C1)
        sage: E1
        Evaluation vector-style encoder for Binary Reed-Muller Code of order 2 and number of variables 4
        sage: C2=codes.ReedMullerCode(GF(3), 2, 2)
        sage: E2=codes.encoders.ReedMullerVectorEncoder(C2)
        sage: E2
        Evaluation vector-style encoder for Reed-Muller Code of order 2 and 2 variables over Finite Field of size 3

    Actually, we can construct the encoder from ``C`` directly::

        sage: C=codes.ReedMullerCode(GF(2), 2, 4)
        sage: E = C.encoder("EvaluationVector")
        sage: E
        Evaluation vector-style encoder for Binary Reed-Muller Code of order 2 and number of variables 4
    """

    def __init__(self, code):
        r"""
        TESTS:

        If ``code`` is not a Reed-Muller code, an error is raised::

            sage: C  = codes.random_linear_code(GF(11), 10, 4)
            sage: codes.encoders.ReedMullerVectorEncoder(C)
            Traceback (most recent call last):
            ...
            ValueError: the code has to be a Reed-Muller code
        """
        if not (
            isinstance(
                code,
                QAryReedMullerCode) or isinstance(
                code,
                BinaryReedMullerCode)):
            raise ValueError("the code has to be a Reed-Muller code")
        super(ReedMullerVectorEncoder, self).__init__(code)

    def _repr_(self):
        r"""
        Returns a string representation of ``self``.

        EXAMPLES::

            sage: F = GF(11)
            sage: C = codes.ReedMullerCode(F, 2, 4)
            sage: E=codes.encoders.ReedMullerVectorEncoder(C)
            sage: E
            Evaluation vector-style encoder for Reed-Muller Code of order 2 and 4 variables over Finite Field of size 11
        """
        return "Evaluation vector-style encoder for %s" % self.code()

    def _latex_(self):
        r"""
        Returns a string representation of ``self``.

        EXAMPLES::

            sage: F = GF(11)
            sage: C = codes.ReedMullerCode(F, 2, 4)
            sage: E=codes.encoders.ReedMullerVectorEncoder(C)
            sage: latex(E)
            \textnormal{Evaluation vector-style encoder for }\textnormal{Reed-Muller Code of order} 2 \textnormal{and }4 \textnormal{variables over} \Bold{F}_{11}
        """
        return "\\textnormal{Evaluation vector-style encoder for }%s" % self.code()._latex_()

    def __eq__(self, other):
        r"""
        Tests equality between ReedMullerVectorEncoder objects.

        EXAMPLES::

            sage: F = GF(11)
            sage: C = codes.ReedMullerCode(F, 2, 4)
            sage: D1 = codes.encoders.ReedMullerVectorEncoder(C)
            sage: D2 = codes.encoders.ReedMullerVectorEncoder(C)
            sage: D1.__eq__(D2)
            True
            sage: D1 is D2
            False
        """
        return (isinstance(other, ReedMullerVectorEncoder)
                ) and self.code() == other.code()

    @cached_method
    def generator_matrix(self):
        r"""
        Returns a generator matrix of ``self``

        EXAMPLES::

            sage: F = GF(3)
            sage: C = codes.ReedMullerCode(F, 2, 2)
            sage: E = codes.encoders.ReedMullerVectorEncoder(C)
            sage: E.generator_matrix()
            [1 1 1 1 1 1 1 1 1]
            [0 1 2 0 1 2 0 1 2]
            [0 0 0 1 1 1 2 2 2]
            [0 1 1 0 1 1 0 1 1]
            [0 0 0 0 1 2 0 2 1]
            [0 0 0 1 1 1 1 1 1]
        """
        C = self.code()
        base_field = C.base_field()
        order = C.order()
        num_of_var = C.number_of_variables()
        q = base_field.cardinality()
        dimension = C.dimension()
        points = base_field**num_of_var
        matrix_list = []
        max_individual_degree = min(order, (q - 1))
        for degree in range(order + 1):
            exponents = Subsets(list(range(num_of_var)) * max_individual_degree,
                                degree, submultiset=True)
            matrix_list += [[reduce(mul, [x[i] for i in exponent], 1)
                             for x in points] for exponent in exponents]
        M = matrix(base_field, matrix_list)
        M.set_immutable()
        return M

    def points(self):
        r"""
        Returns the points of $F^m$, where $F$ is base field and $m$ is the number of variables, in order of which polynomials are evaluated on.

        EXAMPLES::

            sage: F = GF(3)
            sage: Fx.<x0,x1> = F[]
            sage: C = codes.ReedMullerCode(F, 2, 2)
            sage: E = C.encoder("EvaluationVector")
            sage: E.points()
            [(0, 0), (1, 0), (2, 0), (0, 1), (1, 1), (2, 1), (0, 2), (1, 2), (2, 2)]
        """
        code = self.code()
        return ((code.base_field())**code.number_of_variables()).list()


class ReedMullerPolynomialEncoder(Encoder):
    r"""
    Encoder for Reed-Muller codes which encodes appropiate multivariate polynomials into codewords.

    Consider a Reed-Muller code of order `r`, number of variables `m`, length `n`,
    dimension `k` over some finite field `F`.
    Let those variables be `(x_1, x_2, \dots, x_m)`.
    We order the monomials by lowest power on lowest index variables. If we have three monomials
    `x_1 \times x_2`, `x_1 \times x_2^2` and `x_1^2 \times x_2`, the ordering is:
    `x_1 \times x_2 < x_1 \times x_2^2 < x_1^2 \times x_2`

    Let now `f` be a polynomial of the multivariate polynomial ring `F[x_1, \dots, x_m]`.

    Let `(\beta_1, \beta_2, \ldots, \beta_q)` be the elements of `F` ordered as they are
    returned by Sage when calling ``F.list()``.

    The aforementioned polynomial `f` is encoded as:

    `(f(\alpha_{11},\alpha_{12},\ldots,\alpha_{1m}),f(\alpha_{21},\alpha_{22},\ldots,
    \alpha_{2m}),\ldots,f(\alpha_{q^m1},\alpha_{q^m2},\ldots,\alpha_{q^mm}`, with
    `\alpha_{ij}=\beta_{i \ mod \ q^j} \forall (i,j)`


    INPUT:

    - ``code`` -- The associated code of this encoder.

    -``polynomial_ring`` -- (default:``None``) The polynomial ring from which the message is chosen.
                            If this is set to ``None``, a polynomial ring in `x` will be built
                            from the code parameters.

    EXAMPLES::

        sage: C1=codes.ReedMullerCode(GF(2), 2, 4)
        sage: E1=codes.encoders.ReedMullerPolynomialEncoder(C1)
        sage: E1
        Evaluation polynomial-style encoder for Binary Reed-Muller Code of order 2 and number of variables 4
        sage: C2=codes.ReedMullerCode(GF(3), 2, 2)
        sage: E2=codes.encoders.ReedMullerPolynomialEncoder(C2)
        sage: E2
        Evaluation polynomial-style encoder for Reed-Muller Code of order 2 and 2 variables over Finite Field of size 3

    We can also pass a predefined polynomial ring::

        sage: R=PolynomialRing(GF(3), 2, 'y')
        sage: C=codes.ReedMullerCode(GF(3), 2, 2)
        sage: E=codes.encoders.ReedMullerPolynomialEncoder(C, R)
        sage: E
        Evaluation polynomial-style encoder for Reed-Muller Code of order 2 and 2 variables over Finite Field of size 3

    Actually, we can construct the encoder from ``C`` directly::

        sage: E = C1.encoder("EvaluationPolynomial")
        sage: E
        Evaluation polynomial-style encoder for Binary Reed-Muller Code of order 2 and number of variables 4
    """

    def __init__(self, code, polynomial_ring=None):
        r"""
        TESTS:

        If ``code`` is not a Reed-Muller code, an error is raised::

            sage: C  = codes.random_linear_code(GF(11), 10, 4)
            sage: codes.encoders.ReedMullerPolynomialEncoder(C)
            Traceback (most recent call last):
            ...
            ValueError: the code has to be a Reed-Muller code

        If the polynomial ring passed is not according to the requirement (over a different field or different number of variables) then an error is raised::

            sage: F=GF(59)
            sage: R.<x,y,z,w>=F[]
            sage: C=codes.ReedMullerCode(F, 2, 3)
            sage: E=codes.encoders.ReedMullerPolynomialEncoder(C, R)
            Traceback (most recent call last):
            ...
            ValueError: The Polynomial ring should be on Finite Field of size 59 and should have 3 variables
        """
        if not (
            isinstance(code, QAryReedMullerCode)
                or isinstance(code, BinaryReedMullerCode)):
            raise ValueError("the code has to be a Reed-Muller code")
        super(ReedMullerPolynomialEncoder, self).__init__(code)
        if polynomial_ring is None:
            self._polynomial_ring = PolynomialRing(code.base_field(),
                    code.number_of_variables(), 'x')
        else:
            if (polynomial_ring.base_ring() == code.base_field()) and (
                    len(polynomial_ring.variable_names()) == code.number_of_variables()):
                self._polynomial_ring = polynomial_ring
            else:
                raise ValueError(
                    "The Polynomial ring should be on %s and should have %s variables" %
                    (code.base_field(), code.number_of_variables()))

    def _repr_(self):
        r"""
        Returns a string representation of ``self``.

        EXAMPLES::

            sage: F = GF(59)
            sage: C = codes.ReedMullerCode(F, 2, 4)
            sage: E=codes.encoders.ReedMullerPolynomialEncoder(C)
            sage: E
            Evaluation polynomial-style encoder for Reed-Muller Code of order 2 and 4 variables over Finite Field of size 59
        """
        return "Evaluation polynomial-style encoder for %s" % self.code()

    def _latex_(self):
        r"""
        Returns a string representation of ``self``.

        EXAMPLES::

            sage: F = GF(59)
            sage: C = codes.ReedMullerCode(F, 2, 4)
            sage: E=codes.encoders.ReedMullerPolynomialEncoder(C)
            sage: latex(E)
            \textnormal{Evaluation polynomial-style encoder for }\textnormal{Reed-Muller Code of order} 2 \textnormal{and }4 \textnormal{variables over} \Bold{F}_{59}
        """
        return "\\textnormal{Evaluation polynomial-style encoder for }%s" % self.code()._latex_()

    def __eq__(self, other):
        r"""
        Tests equality between ReedMullerVectorEncoder objects.

        EXAMPLES::

            sage: F = GF(11)
            sage: C = codes.ReedMullerCode(F, 2, 4)
            sage: D1 = codes.encoders.ReedMullerPolynomialEncoder(C)
            sage: D2 = codes.encoders.ReedMullerPolynomialEncoder(C)
            sage: D1.__eq__(D2)
            True
            sage: D1 is D2
            False
        """
        return isinstance(other, ReedMullerPolynomialEncoder) \
               and self.code() == other.code()

    def encode(self, p):
        r"""
        Transforms the polynomial ``p`` into a codeword of :meth:`code`.

        INPUT:

        - ``p`` -- A polynomial from the message space of ``self`` of degree
          less than ``self.code().order()``.

        OUTPUT:

        - A codeword in associated code of ``self``

        EXAMPLES::

            sage: F = GF(3)
            sage: Fx.<x0,x1> = F[]
            sage: C = codes.ReedMullerCode(F, 2, 2)
            sage: E = C.encoder("EvaluationPolynomial")
            sage: p = x0*x1 + x1^2 + x0 + x1 + 1
            sage: c = E.encode(p); c
            (1, 2, 0, 0, 2, 1, 1, 1, 1)
            sage: c in C
            True

        If a polynomial with good monomial degree but wrong monomial
        degree is given,an error is raised::

            sage: p = x0^2*x1
            sage: E.encode(p)
            Traceback (most recent call last):
            ...
            ValueError: The polynomial to encode must have degree at most 2

        If ``p`` is not an element of the proper polynomial ring, an error is raised::

            sage: Qy.<y1,y2> = QQ[]
            sage: p = y1^2 + 1
            sage: E.encode(p)
            Traceback (most recent call last):
            ...
            ValueError: The value to encode must be in Multivariate Polynomial Ring in x0, x1 over Finite Field of size 3
        """
        M = self.message_space()
        if p not in M:
            raise ValueError("The value to encode must be in %s" % M)
        C = self.code()
        if p.degree() > C.order():
            raise ValueError("The polynomial to encode must have degree at most %s"
                             % C.order())
        base_fieldTuple = Tuples(C.base_field().list(), C.number_of_variables())
        return vector(C.base_ring(), [p(x) for x in base_fieldTuple])

    def unencode_nocheck(self, c):
        r"""
        Returns the message corresponding to the codeword ``c``.

        Use this method with caution: it does not check if ``c``
        belongs to the code, and if this is not the case, the output is
        unspecified. Instead, use :meth:`unencode`.

        INPUT:

        - ``c`` -- A codeword of :meth:`code`.

        OUTPUT:

        - An polynomial of degree less than ``self.code().order()``.

        EXAMPLES::

            sage: F = GF(3)
            sage: C = codes.ReedMullerCode(F, 2, 2)
            sage: E = C.encoder("EvaluationPolynomial")
            sage: c = vector(F, (1, 2, 0, 0, 2, 1, 1, 1, 1))
            sage: c in C
            True
            sage: p = E.unencode_nocheck(c); p
            x0*x1 + x1^2 + x0 + x1 + 1
            sage: E.encode(p) == c
            True

        Note that no error is thrown if ``c`` is not a codeword, and that the
        result is undefined::

            sage: c = vector(F, (1, 2, 0, 0, 2, 1, 0, 1, 1))
            sage: c in C
            False
            sage: p = E.unencode_nocheck(c); p
            -x0*x1 - x1^2 + x0 + 1
            sage: E.encode(p) == c
            False

        """
        return _multivariate_polynomial_interpolation(
            c,
            self.code().order(),
            self.polynomial_ring())

    def message_space(self):
        r"""
        Returns the message space of ``self``

        EXAMPLES::

            sage: F = GF(11)
            sage: C = codes.ReedMullerCode(F, 2, 4)
            sage: E = C.encoder("EvaluationPolynomial")
            sage: E.message_space()
            Multivariate Polynomial Ring in x0, x1, x2, x3 over Finite Field of size 11
        """
        return self._polynomial_ring

    def polynomial_ring(self):
        r"""
        Returns the polynomial ring associated with ``self``

        EXAMPLES::

            sage: F = GF(11)
            sage: C = codes.ReedMullerCode(F, 2, 4)
            sage: E = C.encoder("EvaluationPolynomial")
            sage: E.polynomial_ring()
            Multivariate Polynomial Ring in x0, x1, x2, x3 over Finite Field of size 11
        """
        return self._polynomial_ring

    def points(self):
        r"""
        Returns the evaluation points in the appropriate order as used by ``self`` when
        encoding a message.

        EXAMPLES::

            sage: F = GF(3)
            sage: Fx.<x0,x1> = F[]
            sage: C = codes.ReedMullerCode(F, 2, 2)
            sage: E = C.encoder("EvaluationPolynomial")
            sage: E.points()
            [(0, 0), (1, 0), (2, 0), (0, 1), (1, 1), (2, 1), (0, 2), (1, 2), (2, 2)]
        """
        code = self.code()
        return ((code.base_field())**code.number_of_variables()).list()


####################### registration ###############################

QAryReedMullerCode._registered_encoders["EvaluationVector"] = ReedMullerVectorEncoder
QAryReedMullerCode._registered_encoders["EvaluationPolynomial"] = ReedMullerPolynomialEncoder

QAryReedMullerCode._registered_decoders["Syndrome"] = LinearCodeSyndromeDecoder

BinaryReedMullerCode._registered_encoders["EvaluationVector"] = ReedMullerVectorEncoder
BinaryReedMullerCode._registered_encoders["EvaluationPolynomial"] = ReedMullerPolynomialEncoder

BinaryReedMullerCode._registered_decoders["Syndrome"] = LinearCodeSyndromeDecoder
