def direct_sum_decompose(U_basis, V_basis, w):
    '''
    Input:
        - U_basis: a list of Vecs forming a basis for a vector space U
        - V_basis: a list of Vecs forming a basis for a vector space V
        - w: a Vec in the direct sum of U and V
    Output:
        - a pair (u, v) such that u + v = w, u is in U, v is in V
    Example:

        >>> D = {0,1,2,3,4,5}
        >>> U_basis = [Vec(D,{0: 2, 1: 1, 2: 0, 3: 0, 4: 6, 5: 0}), Vec(D,{0: 11, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0}), Vec(D,{0: 3, 1: 1.5, 2: 0, 3: 0, 4: 7.5, 5: 0})]
        >>> V_basis = [Vec(D,{0: 0, 1: 0, 2: 7, 3: 0, 4: 0, 5: 1}), Vec(D,{0: 0, 1: 0, 2: 15, 3: 0, 4: 0, 5: 2})]
        >>> w = Vec(D,{0: 2, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0})
        >>> (u, v) = direct_sum_decompose(U_basis, V_basis, w)
        >>> (u + v - w).is_almost_zero()
        True
        >>> U_matrix = coldict2mat(U_basis)
        >>> V_matrix = coldict2mat(V_basis)
        >>> (u - U_matrix*solve(U_matrix, u)).is_almost_zero()
        True
        >>> (v - V_matrix*solve(V_matrix, v)).is_almost_zero()
        True
        >>> ww = Vec(D,{0: 2, 1: 5, 2: 51, 4: 1, 5: 7})
        >>> (u, v) = direct_sum_decompose(U_basis, V_basis, ww)
        >>> (u + v - ww).is_almost_zero()
        True
        >>> (u - U_matrix*solve(U_matrix, u)).is_almost_zero()
        True
        >>> (v - V_matrix*solve(V_matrix, v)).is_almost_zero()
        True
        >>> U_basis == [Vec(D,{0: 2, 1: 1, 2: 0, 3: 0, 4: 6, 5: 0}), Vec(D,{0: 11, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0}), Vec(D,{0: 3, 1: 1.5, 2: 0, 3: 0, 4: 7.5, 5: 0})]
        True
        >>> V_basis == [Vec(D,{0: 0, 1: 0, 2: 7, 3: 0, 4: 0, 5: 1}), Vec(D,{0: 0, 1: 0, 2: 15, 3: 0, 4: 0, 5: 2})]
        True
        >>> w == Vec(D,{0: 2, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0})
        True
    '''
    u = rep2vec(vec2rep(U_basis, w), U_basis)
    v = rep2vec(vec2rep(V_basis, w), V_basis)
    return (u,v)
示例#2
0
def direct_sum_decompose(U_basis, V_basis, w):
    '''
    Input:
        - U_basis: a list of Vecs forming a basis for a vector space U
        - V_basis: a list of Vecs forming a basis for a vector space V
        - w: a Vec in the direct sum of U and V
    Output:
        - a pair (u, v) such that u + v = w, u is in U, v is in V
    Example:

        >>> D = {0,1,2,3,4,5}
        >>> U_basis = [Vec(D,{0: 2, 1: 1, 2: 0, 3: 0, 4: 6, 5: 0}), Vec(D,{0: 11, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0}), Vec(D,{0: 3, 1: 1.5, 2: 0, 3: 0, 4: 7.5, 5: 0})]
        >>> V_basis = [Vec(D,{0: 0, 1: 0, 2: 7, 3: 0, 4: 0, 5: 1}), Vec(D,{0: 0, 1: 0, 2: 15, 3: 0, 4: 0, 5: 2})]
        >>> w = Vec(D,{0: 2, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0})
        >>> (u, v) = direct_sum_decompose(U_basis, V_basis, w)
        >>> (u + v - w).is_almost_zero()
        True
        >>> U_matrix = coldict2mat(U_basis)
        >>> V_matrix = coldict2mat(V_basis)
        >>> (u - U_matrix*solve(U_matrix, u)).is_almost_zero()
        True
        >>> (v - V_matrix*solve(V_matrix, v)).is_almost_zero()
        True
        >>> ww = Vec(D,{0: 2, 1: 5, 2: 51, 4: 1, 5: 7})
        >>> (u, v) = direct_sum_decompose(U_basis, V_basis, ww)
        >>> (u + v - ww).is_almost_zero()
        True
        >>> (u - U_matrix*solve(U_matrix, u)).is_almost_zero()
        True
        >>> (v - V_matrix*solve(V_matrix, v)).is_almost_zero()
        True
        >>> U_basis == [Vec(D,{0: 2, 1: 1, 2: 0, 3: 0, 4: 6, 5: 0}), Vec(D,{0: 11, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0}), Vec(D,{0: 3, 1: 1.5, 2: 0, 3: 0, 4: 7.5, 5: 0})]
        True
        >>> V_basis == [Vec(D,{0: 0, 1: 0, 2: 7, 3: 0, 4: 0, 5: 1}), Vec(D,{0: 0, 1: 0, 2: 15, 3: 0, 4: 0, 5: 2})]
        True
        >>> w == Vec(D,{0: 2, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0})
        True
    '''
    u = rep2vec(vec2rep(U_basis, w), U_basis)
    v = rep2vec(vec2rep(V_basis, w), V_basis)
    return (u, v)
def direct_sum_decompose(U_basis, V_basis, w):
    '''
    Input:
        - U_basis: a list of Vecs forming a basis for a vector space U
        - V_basis: a list of Vecs forming a basis for a vector space V
        - w: a Vec in the direct sum of U and V
    Output:
        - a pair (u, v) such that u + v = w, u is in U, v is in V
    Example:

        >>> D = {0,1,2,3,4,5}
        >>> U_basis = [Vec(D,{0: 2, 1: 1, 2: 0, 3: 0, 4: 6, 5: 0}), Vec(D,{0: 11, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0}), Vec(D,{0: 3, 1: 1.5, 2: 0, 3: 0, 4: 7.5, 5: 0})]
        >>> V_basis = [Vec(D,{0: 0, 1: 0, 2: 7, 3: 0, 4: 0, 5: 1}), Vec(D,{0: 0, 1: 0, 2: 15, 3: 0, 4: 0, 5: 2})]
        >>> w = Vec(D,{0: 2, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0})
        >>> (u, v) = direct_sum_decompose(U_basis, V_basis, w)
        >>> (u + v - w).is_almost_zero()
        True
        >>> U_matrix = coldict2mat(U_basis)
        >>> V_matrix = coldict2mat(V_basis)
        >>> (u - U_matrix*solve(U_matrix, u)).is_almost_zero()
        True
        >>> (v - V_matrix*solve(V_matrix, v)).is_almost_zero()
        True
        >>> ww = Vec(D,{0: 2, 1: 5, 2: 51, 4: 1, 5: 7})
        >>> (u, v) = direct_sum_decompose(U_basis, V_basis, ww)
        >>> (u + v - ww).is_almost_zero()
        True
        >>> (u - U_matrix*solve(U_matrix, u)).is_almost_zero()
        True
        >>> (v - V_matrix*solve(V_matrix, v)).is_almost_zero()
        True
        >>> U_basis == [Vec(D,{0: 2, 1: 1, 2: 0, 3: 0, 4: 6, 5: 0}), Vec(D,{0: 11, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0}), Vec(D,{0: 3, 1: 1.5, 2: 0, 3: 0, 4: 7.5, 5: 0})]
        True
        >>> V_basis == [Vec(D,{0: 0, 1: 0, 2: 7, 3: 0, 4: 0, 5: 1}), Vec(D,{0: 0, 1: 0, 2: 15, 3: 0, 4: 0, 5: 2})]
        True
        >>> w == Vec(D,{0: 2, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0})
        True
    '''
    U_V_basis = list(U_basis)
    U_V_basis.extend(V_basis)
    w_coordinates = vec2rep(U_V_basis, w)
    w_u_coord = list()
    w_v_coord = list()
    for n in range(len(U_V_basis)):
        if n < len(U_basis):
            w_u_coord.append(w_coordinates[n])
        else:
            w_v_coord.append(w_coordinates[n])

    u = rep2vec(list2vec(w_u_coord), U_basis)
    v = rep2vec(list2vec(w_v_coord), V_basis)
    return (u, v)
def morph(S, B):
    """
    Input:
        - S: a list of distinct Vecs
        - B: a list of linearly independent Vecs all in Span S
    Output: a list of pairs of vectors to inject and eject (see problem description)
    Example:
        >>> # This is how our morph works.  Yours may yield different results.
        >>> # Note: Make a copy of S to modify instead of modifying S itself.
        >>> from vecutil import list2vec
        >>> from vec import Vec
        >>> S = [list2vec(v) for v in [[1,0,0],[0,1,0],[0,0,1]]]
        >>> B = [list2vec(v) for v in [[1,1,0],[0,1,1],[1,0,1]]]
        >>> D = {0, 1, 2}
        >>> morph(S, B) == [(Vec(D,{0: 1, 1: 1, 2: 0}), Vec(D,{0: 1, 1: 0, 2: 0})), (Vec(D,{0: 0, 1: 1, 2: 1}), Vec(D,{0: 0, 1: 1, 2: 0})), (Vec(D,{0: 1, 1: 0, 2: 1}), Vec(D,{0: 0, 1: 0, 2: 1}))]
        True
        >>> S == [list2vec(v) for v in [[1,0,0],[0,1,0],[0,0,1]]]
        True
        >>> B == [list2vec(v) for v in [[1,1,0],[0,1,1],[1,0,1]]]
        True
        >>> from GF2 import one
        >>> D = {0, 1, 2, 3, 4, 5, 6, 7}
        >>> S = [Vec(D,{1: one, 2: one, 3: one, 4: one}), Vec(D,{1: one, 3: one}), Vec(D,{0: one, 1: one, 3: one, 5: one, 6: one}), Vec(D,{3: one, 4: one}), Vec(D,{3: one, 5: one, 6: one})]
        >>> B = [Vec(D,{2: one, 4: one}), Vec(D,{0: one, 1: one, 2: one, 3: one, 4: one, 5: one, 6: one}), Vec(D,{0: one, 1: one, 2: one, 5: one, 6: one})]
        >>> sol = morph(S, B)
        >>> sol == [(B[0],S[0]), (B[1],S[2]), (B[2],S[3])] or sol == [(B[0],S[1]), (B[1],S[2]), (B[2],S[3])]
        True
        >>> # Should work the same regardless of order of S
        >>> from random import random
        >>> sol = morph(sorted(S, key=lambda x:random()), B)
        >>> sol == [(B[0],S[0]), (B[1],S[2]), (B[2],S[3])] or sol == [(B[0],S[1]), (B[1],S[2]), (B[2],S[3])]
        True
    """
    tmp_S = S[:]
    tmp_B = B[:]
    A = []
    res = []
    for i in range(len(tmp_B)):
        z = tmp_B[i]
        idxes = vec2rep(tmp_S, z)
        idxes = [idxes[k] for k in idxes.D]

        for i in range(len(idxes)):
            if idxes[i] != 0 and tmp_S[i] not in A:
                w = tmp_S[i]
                break

        tmp_S.remove(w)
        tmp_S.append(z)
        A.append(z)
        res.append((z, w))
    return res
示例#5
0
def morph(S, B):
    '''
    Input:
        - S: a list of distinct Vecs
        - B: a list of linearly independent Vecs all in Span S
    Output: a list of pairs of vectors to inject and eject (see problem description)
    Example:
        >>> # This is how our morph works.  Yours may yield different results.
        >>> # Note: Make a copy of S to modify instead of modifying S itself.
        >>> from vecutil import list2vec
        >>> from vec import Vec
        >>> S = [list2vec(v) for v in [[1,0,0],[0,1,0],[0,0,1]]]
        >>> B = [list2vec(v) for v in [[1,1,0],[0,1,1],[1,0,1]]]
        >>> D = {0, 1, 2}
        >>> morph(S, B) == [(Vec(D,{0: 1, 1: 1, 2: 0}), Vec(D,{0: 1, 1: 0, 2: 0})), (Vec(D,{0: 0, 1: 1, 2: 1}), Vec(D,{0: 0, 1: 1, 2: 0})), (Vec(D,{0: 1, 1: 0, 2: 1}), Vec(D,{0: 0, 1: 0, 2: 1}))]
        True
        >>> S == [list2vec(v) for v in [[1,0,0],[0,1,0],[0,0,1]]]
        True
        >>> B == [list2vec(v) for v in [[1,1,0],[0,1,1],[1,0,1]]]
        True
        >>> from GF2 import one
        >>> D = {0, 1, 2, 3, 4, 5, 6, 7}
        >>> S = [Vec(D,{1: one, 2: one, 3: one, 4: one}), Vec(D,{1: one, 3: one}), Vec(D,{0: one, 1: one, 3: one, 5: one, 6: one}), Vec(D,{3: one, 4: one}), Vec(D,{3: one, 5: one, 6: one})]
        >>> B = [Vec(D,{2: one, 4: one}), Vec(D,{0: one, 1: one, 2: one, 3: one, 4: one, 5: one, 6: one}), Vec(D,{0: one, 1: one, 2: one, 5: one, 6: one})]
        >>> sol = morph(S, B)
        >>> sol == [(B[0],S[0]), (B[1],S[2]), (B[2],S[3])] or sol == [(B[0],S[1]), (B[1],S[2]), (B[2],S[3])]
        True
        >>> # Should work the same regardless of order of S
        >>> from random import random
        >>> sol = morph(sorted(S, key=lambda x:random()), B)
        >>> sol == [(B[0],S[0]), (B[1],S[2]), (B[2],S[3])] or sol == [(B[0],S[1]), (B[1],S[2]), (B[2],S[3])]
        True
    '''
    tmp_S = S[:]
    tmp_B = B[:]
    A = [] 
    res = []
    for i in range(len(tmp_B)):
        z = tmp_B[i]
        idxes = vec2rep(tmp_S, z)
        idxes = [idxes[k] for k in idxes.D] 
        
        for i in range(len(idxes)):
            if idxes[i] != 0 and tmp_S[i] not in A:
                w = tmp_S[i]
                break
              
        tmp_S.remove(w)
        tmp_S.append(z)
        A.append(z)
        res.append((z, w))
    return res
示例#6
0
def direct_sum_decompose(U_basis, V_basis, w):
    '''
    Input:
        - U_basis: a list of Vecs forming a basis for a vector space U
        - V_basis: a list of Vecs forming a basis for a vector space V
        - w: a Vec in the direct sum of U and V
    Output:
        - a pair (u, v) such that u + v = w, u is in U, v is in V
    Example:

        >>> D = {0,1,2,3,4,5}
        >>> U_basis = [Vec(D,{0: 2, 1: 1, 2: 0, 3: 0, 4: 6, 5: 0}), Vec(D,{0: 11, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0}), Vec(D,{0: 3, 1: 1.5, 2: 0, 3: 0, 4: 7.5, 5: 0})]
        >>> V_basis = [Vec(D,{0: 0, 1: 0, 2: 7, 3: 0, 4: 0, 5: 1}), Vec(D,{0: 0, 1: 0, 2: 15, 3: 0, 4: 0, 5: 2})]
        >>> w = Vec(D,{0: 2, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0})
        >>> (u, v) = direct_sum_decompose(U_basis, V_basis, w)
        >>> (u + v - w).is_almost_zero()
        True
        >>> U_matrix = coldict2mat(U_basis)
        >>> V_matrix = coldict2mat(V_basis)
        >>> (u - U_matrix*solve(U_matrix, u)).is_almost_zero()
        True
        >>> (v - V_matrix*solve(V_matrix, v)).is_almost_zero()
        True
        >>> ww = Vec(D,{0: 2, 1: 5, 2: 51, 4: 1, 5: 7})
        >>> (u, v) = direct_sum_decompose(U_basis, V_basis, ww)
        >>> (u + v - ww).is_almost_zero()
        True
        >>> (u - U_matrix*solve(U_matrix, u)).is_almost_zero()
        True
        >>> (v - V_matrix*solve(V_matrix, v)).is_almost_zero()
        True
        >>> U_basis == [Vec(D,{0: 2, 1: 1, 2: 0, 3: 0, 4: 6, 5: 0}), Vec(D,{0: 11, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0}), Vec(D,{0: 3, 1: 1.5, 2: 0, 3: 0, 4: 7.5, 5: 0})]
        True
        >>> V_basis == [Vec(D,{0: 0, 1: 0, 2: 7, 3: 0, 4: 0, 5: 1}), Vec(D,{0: 0, 1: 0, 2: 15, 3: 0, 4: 0, 5: 2})]
        True
        >>> w == Vec(D,{0: 2, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0})
        True
    '''
    direct_sum_basis = U_basis + V_basis
    x = vec2rep(direct_sum_basis, w)  # len(x) = len(direct_sum_basis)
    u = Vec(U_basis[0].D, {})
    v = Vec(V_basis[0].D, {})

    for i in range(len(U_basis)):
        u = u + x[i] * U_basis[i]
    for j in range(len(V_basis)):
        v = v + x[len(U_basis) + j] * V_basis[j]

    return (u, v)
def direct_sum_decompose(U_basis, V_basis, w):
    '''
    Input:
        - U_basis: a list of Vecs forming a basis for a vector space U
        - V_basis: a list of Vecs forming a basis for a vector space V
        - w: a Vec in the direct sum of U and V
    Output:
        - a pair (u, v) such that u + v = w, u is in U, v is in V
    Example:

        >>> D = {0,1,2,3,4,5}
        >>> U_basis = [Vec(D,{0: 2, 1: 1, 2: 0, 3: 0, 4: 6, 5: 0}), Vec(D,{0: 11, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0}), Vec(D,{0: 3, 1: 1.5, 2: 0, 3: 0, 4: 7.5, 5: 0})]
        >>> V_basis = [Vec(D,{0: 0, 1: 0, 2: 7, 3: 0, 4: 0, 5: 1}), Vec(D,{0: 0, 1: 0, 2: 15, 3: 0, 4: 0, 5: 2})]
        >>> w = Vec(D,{0: 2, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0})
        >>> (u, v) = direct_sum_decompose(U_basis, V_basis, w)
        >>> (u + v - w).is_almost_zero()
        True
        >>> U_matrix = coldict2mat(U_basis)
        >>> V_matrix = coldict2mat(V_basis)
        >>> (u - U_matrix*solve(U_matrix, u)).is_almost_zero()
        True
        >>> (v - V_matrix*solve(V_matrix, v)).is_almost_zero()
        True
        >>> ww = Vec(D,{0: 2, 1: 5, 2: 51, 4: 1, 5: 7})
        >>> (u, v) = direct_sum_decompose(U_basis, V_basis, ww)
        >>> (u + v - ww).is_almost_zero()
        True
        >>> (u - U_matrix*solve(U_matrix, u)).is_almost_zero()
        True
        >>> (v - V_matrix*solve(V_matrix, v)).is_almost_zero()
        True
        >>> U_basis == [Vec(D,{0: 2, 1: 1, 2: 0, 3: 0, 4: 6, 5: 0}), Vec(D,{0: 11, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0}), Vec(D,{0: 3, 1: 1.5, 2: 0, 3: 0, 4: 7.5, 5: 0})]
        True
        >>> V_basis == [Vec(D,{0: 0, 1: 0, 2: 7, 3: 0, 4: 0, 5: 1}), Vec(D,{0: 0, 1: 0, 2: 15, 3: 0, 4: 0, 5: 2})]
        True
        >>> w == Vec(D,{0: 2, 1: 5, 2: 0, 3: 0, 4: 1, 5: 0})
        True
    '''
    direct_sum_basis = U_basis+V_basis
    x = vec2rep(direct_sum_basis, w) # len(x) = len(direct_sum_basis)
    u = Vec(U_basis[0].D, {}); v = Vec(V_basis[0].D, {})
    
    for i in range(len(U_basis)):
        u = u+x[i]*U_basis[i]
    for j in range(len(V_basis)):
        v = v+x[len(U_basis)+j]*V_basis[j]
    
    return (u, v)
示例#8
0
def exchange(S, A, z):
    u = vec2rep(S, z)
    for i, v in enumerate(S):
        coef = u[i]
        if v not in A and coef != 0:
            return v