Linear code constructors that do not preserve the structural information¶
This file contains a variety of constructions which builds the generator matrix
of special (or random) linear codes and wraps them in a
sage.coding.linear_code.LinearCode object. These constructions are
therefore not rich objects such as
sage.coding.grs_code.GeneralizedReedSolomonCode.
All codes available here can be accessed through the codes object:
sage: codes.random_linear_code(GF(2), 5, 2)
[5, 2]  linear code over GF(2)
>>> from sage.all import *
>>> codes.random_linear_code(GF(Integer(2)), Integer(5), Integer(2))
[5, 2]  linear code over GF(2)
REFERENCES:
AUTHORS:
- David Joyner (2007-05): initial version 
- David Joyner (2008-02): added cyclic codes, Hamming codes 
- David Joyner (2008-03): added BCH code, LinearCodeFromCheckmatrix, ReedSolomonCode, WalshCode, DuadicCodeEvenPair, DuadicCodeOddPair, QR codes (even and odd) 
- David Joyner (2008-09) fix for bug in BCHCode reported by F. Voloch 
- David Joyner (2008-10) small docstring changes to WalshCode and walsh_matrix 
- sage.coding.code_constructions.DuadicCodeEvenPair(F, S1, S2)[source]¶
- Construct the “even pair” of duadic codes associated to the “splitting” (see the docstring for - _is_a_splittingfor the definition) S1, S2 of n.- Warning - Maybe the splitting should be associated to a sum of q-cyclotomic cosets mod n, where q is a prime. - EXAMPLES: - sage: from sage.coding.code_constructions import _is_a_splitting sage: n = 11; q = 3 sage: C = Zmod(n).cyclotomic_cosets(q); C [[0], [1, 3, 4, 5, 9], [2, 6, 7, 8, 10]] sage: S1 = C[1] sage: S2 = C[2] sage: _is_a_splitting(S1,S2,11) True sage: codes.DuadicCodeEvenPair(GF(q),S1,S2) ([11, 5] Cyclic Code over GF(3), [11, 5] Cyclic Code over GF(3)) - >>> from sage.all import * >>> from sage.coding.code_constructions import _is_a_splitting >>> n = Integer(11); q = Integer(3) >>> C = Zmod(n).cyclotomic_cosets(q); C [[0], [1, 3, 4, 5, 9], [2, 6, 7, 8, 10]] >>> S1 = C[Integer(1)] >>> S2 = C[Integer(2)] >>> _is_a_splitting(S1,S2,Integer(11)) True >>> codes.DuadicCodeEvenPair(GF(q),S1,S2) ([11, 5] Cyclic Code over GF(3), [11, 5] Cyclic Code over GF(3)) 
- sage.coding.code_constructions.DuadicCodeOddPair(F, S1, S2)[source]¶
- Construct the “odd pair” of duadic codes associated to the “splitting” S1, S2 of n. - Warning - Maybe the splitting should be associated to a sum of q-cyclotomic cosets mod n, where q is a prime. - EXAMPLES: - sage: from sage.coding.code_constructions import _is_a_splitting sage: n = 11; q = 3 sage: C = Zmod(n).cyclotomic_cosets(q); C [[0], [1, 3, 4, 5, 9], [2, 6, 7, 8, 10]] sage: S1 = C[1] sage: S2 = C[2] sage: _is_a_splitting(S1,S2,11) True sage: codes.DuadicCodeOddPair(GF(q),S1,S2) ([11, 6] Cyclic Code over GF(3), [11, 6] Cyclic Code over GF(3)) - >>> from sage.all import * >>> from sage.coding.code_constructions import _is_a_splitting >>> n = Integer(11); q = Integer(3) >>> C = Zmod(n).cyclotomic_cosets(q); C [[0], [1, 3, 4, 5, 9], [2, 6, 7, 8, 10]] >>> S1 = C[Integer(1)] >>> S2 = C[Integer(2)] >>> _is_a_splitting(S1,S2,Integer(11)) True >>> codes.DuadicCodeOddPair(GF(q),S1,S2) ([11, 6] Cyclic Code over GF(3), [11, 6] Cyclic Code over GF(3)) - This is consistent with Theorem 6.1.3 in [HP2003]. 
- sage.coding.code_constructions.ExtendedQuadraticResidueCode(n, F)[source]¶
- The extended quadratic residue code (or XQR code) is obtained from a QR code by adding a check bit to the last coordinate. (These codes have very remarkable properties such as large automorphism groups and duality properties - see [HP2003], Section 6.6.3-6.6.4.) - INPUT: - n– an odd prime
- F– a finite prime field whose order must be a quadratic residue modulo \(n\)
 - OUTPUT: an extended quadratic residue code - EXAMPLES: - sage: C1 = codes.QuadraticResidueCode(7, GF(2)) sage: C2 = C1.extended_code() sage: C3 = codes.ExtendedQuadraticResidueCode(7, GF(2)); C3 Extension of [7, 4] Cyclic Code over GF(2) sage: C2 == C3 True sage: C = codes.ExtendedQuadraticResidueCode(17, GF(2)) sage: C Extension of [17, 9] Cyclic Code over GF(2) sage: C3 = codes.QuadraticResidueCodeOddPair(7, GF(2))[0] sage: C3x = C3.extended_code() sage: C4 = codes.ExtendedQuadraticResidueCode(7, GF(2)) sage: C3x == C4 True - >>> from sage.all import * >>> C1 = codes.QuadraticResidueCode(Integer(7), GF(Integer(2))) >>> C2 = C1.extended_code() >>> C3 = codes.ExtendedQuadraticResidueCode(Integer(7), GF(Integer(2))); C3 Extension of [7, 4] Cyclic Code over GF(2) >>> C2 == C3 True >>> C = codes.ExtendedQuadraticResidueCode(Integer(17), GF(Integer(2))) >>> C Extension of [17, 9] Cyclic Code over GF(2) >>> C3 = codes.QuadraticResidueCodeOddPair(Integer(7), GF(Integer(2)))[Integer(0)] >>> C3x = C3.extended_code() >>> C4 = codes.ExtendedQuadraticResidueCode(Integer(7), GF(Integer(2))) >>> C3x == C4 True - AUTHORS: - David Joyner (07-2006) 
 
- sage.coding.code_constructions.QuadraticResidueCode(n, F)[source]¶
- A quadratic residue code (or QR code) is a cyclic code whose generator polynomial is the product of the polynomials \(x-\alpha^i\) (\(\alpha\) is a primitive \(n\)-th root of unity; \(i\) ranges over the set of quadratic residues modulo \(n\)). - See - QuadraticResidueCodeEvenPairand- QuadraticResidueCodeOddPairfor a more general construction.- INPUT: - n– an odd prime
- F– a finite prime field whose order must be a quadratic residue modulo \(n\)
 - OUTPUT: a quadratic residue code - EXAMPLES: - sage: C = codes.QuadraticResidueCode(7, GF(2)) sage: C [7, 4] Cyclic Code over GF(2) sage: C = codes.QuadraticResidueCode(17, GF(2)) sage: C [17, 9] Cyclic Code over GF(2) sage: C1 = codes.QuadraticResidueCodeOddPair(7, GF(2))[0] sage: C2 = codes.QuadraticResidueCode(7, GF(2)) sage: C1 == C2 True sage: C1 = codes.QuadraticResidueCodeOddPair(17, GF(2))[0] sage: C2 = codes.QuadraticResidueCode(17, GF(2)) sage: C1 == C2 True - >>> from sage.all import * >>> C = codes.QuadraticResidueCode(Integer(7), GF(Integer(2))) >>> C [7, 4] Cyclic Code over GF(2) >>> C = codes.QuadraticResidueCode(Integer(17), GF(Integer(2))) >>> C [17, 9] Cyclic Code over GF(2) >>> C1 = codes.QuadraticResidueCodeOddPair(Integer(7), GF(Integer(2)))[Integer(0)] >>> C2 = codes.QuadraticResidueCode(Integer(7), GF(Integer(2))) >>> C1 == C2 True >>> C1 = codes.QuadraticResidueCodeOddPair(Integer(17), GF(Integer(2)))[Integer(0)] >>> C2 = codes.QuadraticResidueCode(Integer(17), GF(Integer(2))) >>> C1 == C2 True - AUTHORS: - David Joyner (11-2005) 
 
- sage.coding.code_constructions.QuadraticResidueCodeEvenPair(n, F)[source]¶
- Quadratic residue codes of a given odd prime length and base ring either don’t exist at all or occur as 4-tuples - a pair of “odd-like” codes and a pair of “even-like” codes. If \(n > 2\) is prime then (Theorem 6.6.2 in [HP2003]) a QR code exists over \(\GF{q}\) iff q is a quadratic residue mod \(n\). - They are constructed as “even-like” duadic codes associated the splitting \((Q,N)\) mod \(n\), where \(Q\) is the set of nonzero quadratic residues and \(N\) is the non-residues. - EXAMPLES: - sage: codes.QuadraticResidueCodeEvenPair(17, GF(13)) # known bug (#25896) ([17, 8] Cyclic Code over GF(13), [17, 8] Cyclic Code over GF(13)) sage: codes.QuadraticResidueCodeEvenPair(17, GF(2)) ([17, 8] Cyclic Code over GF(2), [17, 8] Cyclic Code over GF(2)) sage: codes.QuadraticResidueCodeEvenPair(13, GF(9,"z")) # known bug (#25896) ([13, 6] Cyclic Code over GF(9), [13, 6] Cyclic Code over GF(9)) sage: C1,C2 = codes.QuadraticResidueCodeEvenPair(7, GF(2)) sage: C1.is_self_orthogonal() True sage: C2.is_self_orthogonal() True sage: C3 = codes.QuadraticResidueCodeOddPair(17, GF(2))[0] sage: C4 = codes.QuadraticResidueCodeEvenPair(17, GF(2))[1] sage: C3.systematic_generator_matrix() == C4.dual_code().systematic_generator_matrix() True - >>> from sage.all import * >>> codes.QuadraticResidueCodeEvenPair(Integer(17), GF(Integer(13))) # known bug (#25896) ([17, 8] Cyclic Code over GF(13), [17, 8] Cyclic Code over GF(13)) >>> codes.QuadraticResidueCodeEvenPair(Integer(17), GF(Integer(2))) ([17, 8] Cyclic Code over GF(2), [17, 8] Cyclic Code over GF(2)) >>> codes.QuadraticResidueCodeEvenPair(Integer(13), GF(Integer(9),"z")) # known bug (#25896) ([13, 6] Cyclic Code over GF(9), [13, 6] Cyclic Code over GF(9)) >>> C1,C2 = codes.QuadraticResidueCodeEvenPair(Integer(7), GF(Integer(2))) >>> C1.is_self_orthogonal() True >>> C2.is_self_orthogonal() True >>> C3 = codes.QuadraticResidueCodeOddPair(Integer(17), GF(Integer(2)))[Integer(0)] >>> C4 = codes.QuadraticResidueCodeEvenPair(Integer(17), GF(Integer(2)))[Integer(1)] >>> C3.systematic_generator_matrix() == C4.dual_code().systematic_generator_matrix() True - This is consistent with Theorem 6.6.9 and Exercise 365 in [HP2003]. 
- sage.coding.code_constructions.QuadraticResidueCodeOddPair(n, F)[source]¶
- Quadratic residue codes of a given odd prime length and base ring either don’t exist at all or occur as 4-tuples - a pair of “odd-like” codes and a pair of “even-like” codes. If n 2 is prime then (Theorem 6.6.2 in [HP2003]) a QR code exists over \(\GF{q} iff `q\) is a quadratic residue mod \(n\). - They are constructed as “odd-like” duadic codes associated the splitting \((Q,N)\) mod \(n\), where \(Q\) is the set of nonzero quadratic residues and \(N\) is the non-residues. - EXAMPLES: - sage: codes.QuadraticResidueCodeOddPair(17, GF(13)) # known bug (#25896) ([17, 9] Cyclic Code over GF(13), [17, 9] Cyclic Code over GF(13)) sage: codes.QuadraticResidueCodeOddPair(17, GF(2)) ([17, 9] Cyclic Code over GF(2), [17, 9] Cyclic Code over GF(2)) sage: codes.QuadraticResidueCodeOddPair(13, GF(9,"z")) # known bug (#25896) ([13, 7] Cyclic Code over GF(9), [13, 7] Cyclic Code over GF(9)) sage: C1 = codes.QuadraticResidueCodeOddPair(17, GF(2))[1] sage: C1x = C1.extended_code() sage: C2 = codes.QuadraticResidueCodeOddPair(17, GF(2))[0] sage: C2x = C2.extended_code() sage: C2x.spectrum(); C1x.spectrum() [1, 0, 0, 0, 0, 0, 102, 0, 153, 0, 153, 0, 102, 0, 0, 0, 0, 0, 1] [1, 0, 0, 0, 0, 0, 102, 0, 153, 0, 153, 0, 102, 0, 0, 0, 0, 0, 1] sage: C3 = codes.QuadraticResidueCodeOddPair(7, GF(2))[0] sage: C3x = C3.extended_code() sage: C3x.spectrum() [1, 0, 0, 0, 14, 0, 0, 0, 1] - >>> from sage.all import * >>> codes.QuadraticResidueCodeOddPair(Integer(17), GF(Integer(13))) # known bug (#25896) ([17, 9] Cyclic Code over GF(13), [17, 9] Cyclic Code over GF(13)) >>> codes.QuadraticResidueCodeOddPair(Integer(17), GF(Integer(2))) ([17, 9] Cyclic Code over GF(2), [17, 9] Cyclic Code over GF(2)) >>> codes.QuadraticResidueCodeOddPair(Integer(13), GF(Integer(9),"z")) # known bug (#25896) ([13, 7] Cyclic Code over GF(9), [13, 7] Cyclic Code over GF(9)) >>> C1 = codes.QuadraticResidueCodeOddPair(Integer(17), GF(Integer(2)))[Integer(1)] >>> C1x = C1.extended_code() >>> C2 = codes.QuadraticResidueCodeOddPair(Integer(17), GF(Integer(2)))[Integer(0)] >>> C2x = C2.extended_code() >>> C2x.spectrum(); C1x.spectrum() [1, 0, 0, 0, 0, 0, 102, 0, 153, 0, 153, 0, 102, 0, 0, 0, 0, 0, 1] [1, 0, 0, 0, 0, 0, 102, 0, 153, 0, 153, 0, 102, 0, 0, 0, 0, 0, 1] >>> C3 = codes.QuadraticResidueCodeOddPair(Integer(7), GF(Integer(2)))[Integer(0)] >>> C3x = C3.extended_code() >>> C3x.spectrum() [1, 0, 0, 0, 14, 0, 0, 0, 1] - This is consistent with Theorem 6.6.14 in [HP2003]. 
- sage.coding.code_constructions.ToricCode(P, F)[source]¶
- Let \(P\) denote a list of lattice points in \(\ZZ^d\) and let \(T\) denote the set of all points in \((F^x)^d\) (ordered in some fixed way). Put \(n=|T|\) and let \(k\) denote the dimension of the vector space of functions \(V = \mathrm{Span}\{x^e \ |\ e \in P\}\). The associated toric code \(C\) is the evaluation code which is the image of the evaluation map \[\operatorname{eval}_T : V \rightarrow F^n,\]- where \(x^e\) is the multi-index notation (\(x=(x_1,...,x_d)\), \(e=(e_1,...,e_d)\), and \(x^e = x_1^{e_1}...x_d^{e_d}\)), where \(\operatorname{eval}_T (f(x)) = (f(t_1),...,f(t_n))\), and where \(T=\{t_1,...,t_n\}\). This function returns the toric codes discussed in [Joy2004]. - INPUT: - P– all the integer lattice points in a polytope defining the toric variety
- F– a finite field
 - OUTPUT: toric code with length \(n\), dimension \(k\) over field \(F\) - EXAMPLES: - sage: C = codes.ToricCode([[0,0],[1,0],[2,0],[0,1],[1,1]], GF(7)) sage: C [36, 5] linear code over GF(7) sage: C.minimum_distance() # needs sage.groups 24 sage: C.minimum_distance(algorithm='guava') # optional - gap_package_guava ...24 sage: C = codes.ToricCode([[-2,-2],[-1,-2],[-1,-1],[-1,0], ....: [0,-1],[0,0],[0,1],[1,-1],[1,0]], GF(5)) sage: C [16, 9] linear code over GF(5) sage: C.minimum_distance() # needs sage.groups 6 sage: C.minimum_distance(algorithm='guava') # optional - gap_package_guava 6 sage: C = codes.ToricCode([[0,0],[1,1],[1,2],[1,3],[1,4],[2,1], ....: [2,2],[2,3],[3,1],[3,2],[4,1]], GF(8,"a")) sage: C [49, 11] linear code over GF(8) - >>> from sage.all import * >>> C = codes.ToricCode([[Integer(0),Integer(0)],[Integer(1),Integer(0)],[Integer(2),Integer(0)],[Integer(0),Integer(1)],[Integer(1),Integer(1)]], GF(Integer(7))) >>> C [36, 5] linear code over GF(7) >>> C.minimum_distance() # needs sage.groups 24 >>> C.minimum_distance(algorithm='guava') # optional - gap_package_guava ...24 >>> C = codes.ToricCode([[-Integer(2),-Integer(2)],[-Integer(1),-Integer(2)],[-Integer(1),-Integer(1)],[-Integer(1),Integer(0)], ... [Integer(0),-Integer(1)],[Integer(0),Integer(0)],[Integer(0),Integer(1)],[Integer(1),-Integer(1)],[Integer(1),Integer(0)]], GF(Integer(5))) >>> C [16, 9] linear code over GF(5) >>> C.minimum_distance() # needs sage.groups 6 >>> C.minimum_distance(algorithm='guava') # optional - gap_package_guava 6 >>> C = codes.ToricCode([[Integer(0),Integer(0)],[Integer(1),Integer(1)],[Integer(1),Integer(2)],[Integer(1),Integer(3)],[Integer(1),Integer(4)],[Integer(2),Integer(1)], ... [Integer(2),Integer(2)],[Integer(2),Integer(3)],[Integer(3),Integer(1)],[Integer(3),Integer(2)],[Integer(4),Integer(1)]], GF(Integer(8),"a")) >>> C [49, 11] linear code over GF(8) - This is in fact a [49,11,28] code over \(\GF{8}\). If you type next - C.minimum_distance()and wait overnight (!), you should get 28.- AUTHOR: - David Joyner (07-2006) 
 
- sage.coding.code_constructions.WalshCode(m)[source]¶
- Return the binary Walsh code of length \(2^m\). - The matrix of codewords correspond to a Hadamard matrix. This is a (constant rate) binary linear \([2^m,m,2^{m-1}]\) code. - EXAMPLES: - sage: C = codes.WalshCode(4); C [16, 4] linear code over GF(2) sage: C = codes.WalshCode(3); C [8, 3] linear code over GF(2) sage: C.spectrum() [1, 0, 0, 0, 7, 0, 0, 0, 0] sage: C.minimum_distance() # needs sage.libs.gap 4 sage: C.minimum_distance(algorithm='gap') # check d=2^(m-1) # needs sage.libs.gap 4 - >>> from sage.all import * >>> C = codes.WalshCode(Integer(4)); C [16, 4] linear code over GF(2) >>> C = codes.WalshCode(Integer(3)); C [8, 3] linear code over GF(2) >>> C.spectrum() [1, 0, 0, 0, 7, 0, 0, 0, 0] >>> C.minimum_distance() # needs sage.libs.gap 4 >>> C.minimum_distance(algorithm='gap') # check d=2^(m-1) # needs sage.libs.gap 4 - REFERENCES: 
- sage.coding.code_constructions.from_parity_check_matrix(H)[source]¶
- Return the linear code that has - Has a parity check matrix.- If - Hhas dimensions \(h \times n\) then the linear code will have dimension \(n-h\) and length \(n\).- EXAMPLES: - sage: C = codes.HammingCode(GF(2), 3); C [7, 4] Hamming Code over GF(2) sage: H = C.parity_check_matrix(); H [1 0 1 0 1 0 1] [0 1 1 0 0 1 1] [0 0 0 1 1 1 1] sage: C2 = codes.from_parity_check_matrix(H); C2 [7, 4] linear code over GF(2) sage: C2.systematic_generator_matrix() == C.systematic_generator_matrix() True - >>> from sage.all import * >>> C = codes.HammingCode(GF(Integer(2)), Integer(3)); C [7, 4] Hamming Code over GF(2) >>> H = C.parity_check_matrix(); H [1 0 1 0 1 0 1] [0 1 1 0 0 1 1] [0 0 0 1 1 1 1] >>> C2 = codes.from_parity_check_matrix(H); C2 [7, 4] linear code over GF(2) >>> C2.systematic_generator_matrix() == C.systematic_generator_matrix() True 
- sage.coding.code_constructions.permutation_action(g, v)[source]¶
- Return permutation of rows \(g * v\). - Works on lists, matrices, sequences and vectors (by permuting coordinates). The code requires switching from \(i\) to \(i+1\) (and back again) since the - SymmetricGroupis, by convention, the symmetric group on the “letters” \(1\), \(2\), …, \(n\) (not \(0\), \(1\), …, \(n-1\)).- EXAMPLES: - sage: # needs sage.groups sage: V = VectorSpace(GF(3),5) sage: v = V([0,1,2,0,1]) sage: G = SymmetricGroup(5) sage: g = G([(1,2,3)]) sage: permutation_action(g,v) (1, 2, 0, 0, 1) sage: g = G([()]) sage: permutation_action(g,v) (0, 1, 2, 0, 1) sage: g = G([(1,2,3,4,5)]) sage: permutation_action(g,v) (1, 2, 0, 1, 0) sage: L = Sequence([1,2,3,4,5]) sage: permutation_action(g,L) [2, 3, 4, 5, 1] sage: MS = MatrixSpace(GF(3),3,7) sage: A = MS([[1,0,0,0,1,1,0],[0,1,0,1,0,1,0],[0,0,0,0,0,0,1]]) sage: S5 = SymmetricGroup(5) sage: g = S5([(1,2,3)]) sage: A [1 0 0 0 1 1 0] [0 1 0 1 0 1 0] [0 0 0 0 0 0 1] sage: permutation_action(g,A) [0 1 0 1 0 1 0] [0 0 0 0 0 0 1] [1 0 0 0 1 1 0] - >>> from sage.all import * >>> # needs sage.groups >>> V = VectorSpace(GF(Integer(3)),Integer(5)) >>> v = V([Integer(0),Integer(1),Integer(2),Integer(0),Integer(1)]) >>> G = SymmetricGroup(Integer(5)) >>> g = G([(Integer(1),Integer(2),Integer(3))]) >>> permutation_action(g,v) (1, 2, 0, 0, 1) >>> g = G([()]) >>> permutation_action(g,v) (0, 1, 2, 0, 1) >>> g = G([(Integer(1),Integer(2),Integer(3),Integer(4),Integer(5))]) >>> permutation_action(g,v) (1, 2, 0, 1, 0) >>> L = Sequence([Integer(1),Integer(2),Integer(3),Integer(4),Integer(5)]) >>> permutation_action(g,L) [2, 3, 4, 5, 1] >>> MS = MatrixSpace(GF(Integer(3)),Integer(3),Integer(7)) >>> A = MS([[Integer(1),Integer(0),Integer(0),Integer(0),Integer(1),Integer(1),Integer(0)],[Integer(0),Integer(1),Integer(0),Integer(1),Integer(0),Integer(1),Integer(0)],[Integer(0),Integer(0),Integer(0),Integer(0),Integer(0),Integer(0),Integer(1)]]) >>> S5 = SymmetricGroup(Integer(5)) >>> g = S5([(Integer(1),Integer(2),Integer(3))]) >>> A [1 0 0 0 1 1 0] [0 1 0 1 0 1 0] [0 0 0 0 0 0 1] >>> permutation_action(g,A) [0 1 0 1 0 1 0] [0 0 0 0 0 0 1] [1 0 0 0 1 1 0] - It also works on lists and is a “left action”: - sage: # needs sage.groups sage: v = [0,1,2,0,1] sage: G = SymmetricGroup(5) sage: g = G([(1,2,3)]) sage: gv = permutation_action(g,v); gv [1, 2, 0, 0, 1] sage: permutation_action(g,v) == g(v) True sage: h = G([(3,4)]) sage: gv = permutation_action(g,v) sage: hgv = permutation_action(h,gv) sage: hgv == permutation_action(h*g,v) True - >>> from sage.all import * >>> # needs sage.groups >>> v = [Integer(0),Integer(1),Integer(2),Integer(0),Integer(1)] >>> G = SymmetricGroup(Integer(5)) >>> g = G([(Integer(1),Integer(2),Integer(3))]) >>> gv = permutation_action(g,v); gv [1, 2, 0, 0, 1] >>> permutation_action(g,v) == g(v) True >>> h = G([(Integer(3),Integer(4))]) >>> gv = permutation_action(g,v) >>> hgv = permutation_action(h,gv) >>> hgv == permutation_action(h*g,v) True - AUTHORS: - David Joyner, licensed under the GPL v2 or greater. 
 
- sage.coding.code_constructions.random_linear_code(F, length, dimension)[source]¶
- Generate a random linear code of length - length, dimension- dimensionand over the field- F.- This function is Las Vegas probabilistic: always correct, usually fast. Random matrices over the - Fare drawn until one with full rank is hit.- If - Fis infinite, the distribution of the elements in the random generator matrix will be random according to the distribution of- F.random_element().- EXAMPLES: - sage: C = codes.random_linear_code(GF(2), 10, 3) sage: C [10, 3] linear code over GF(2) sage: C.generator_matrix().rank() 3 - >>> from sage.all import * >>> C = codes.random_linear_code(GF(Integer(2)), Integer(10), Integer(3)) >>> C [10, 3] linear code over GF(2) >>> C.generator_matrix().rank() 3 
- sage.coding.code_constructions.walsh_matrix(m0)[source]¶
- This is the generator matrix of a Walsh code. The matrix of codewords correspond to a Hadamard matrix. - EXAMPLES: - sage: walsh_matrix(2) [0 0 1 1] [0 1 0 1] sage: walsh_matrix(3) [0 0 0 0 1 1 1 1] [0 0 1 1 0 0 1 1] [0 1 0 1 0 1 0 1] sage: C = LinearCode(walsh_matrix(4)); C [16, 4] linear code over GF(2) sage: C.spectrum() [1, 0, 0, 0, 0, 0, 0, 0, 15, 0, 0, 0, 0, 0, 0, 0, 0] - >>> from sage.all import * >>> walsh_matrix(Integer(2)) [0 0 1 1] [0 1 0 1] >>> walsh_matrix(Integer(3)) [0 0 0 0 1 1 1 1] [0 0 1 1 0 0 1 1] [0 1 0 1 0 1 0 1] >>> C = LinearCode(walsh_matrix(Integer(4))); C [16, 4] linear code over GF(2) >>> C.spectrum() [1, 0, 0, 0, 0, 0, 0, 0, 15, 0, 0, 0, 0, 0, 0, 0, 0] - This last code has minimum distance 8. - REFERENCES: