#C7.txt, Feb. 8, 2024 Help:=proc(): print(` NN(C,v), DecodeT(q,n,C) , GLC1(q,M,d) , GLC(q,n,d), SAah(q,n,M)`):end: #Feb. 5, 2024, C6.txt#C5.txt, Feb. 1, 2024 Help6:=proc(): print(`LtoC(q,M), MinW(q,M), SFde(q,M) `):end: Help5:=proc(): print(`Nei(q,c), SP(q,c,t), GRC(q,n,d), GRCgs(q,n,d) , MinD(C), CV(S,n)`): print(`BDtoC(BD,n)`): end: #Old code #Jan. 29, 2024 C4.txt Help4:=proc(): print(`Fqn(q,n), HD(u,v), RV(q,n) , RC(q,n,d,K), SPB(q,n,t), BDfano(), BDex212() `):end: #Alphabet {0,1,...q-1}, Fqn(q,n): {0,1,...,q-1}^n Fqn:=proc(q,n) local S,a,v: option remember: if n=0 then RETURN({[]}): fi: S:=Fqn(q,n-1): {seq(seq([op(v),a],a=0..q-1), v in S)}: end: #Def. (n,M,d) q-ary code is a subset of Fqn(q,n) with M elements with #minimal Hamming Distance d between any two members #It can detect up to d-1 errors # #If d=2*t+1 correct t errors. # # #HD(u,v): The Hamming distance between two words (of the same length) HD:=proc(u,v) local i,co: co:=0: for i from 1 to nops(u) do if u[i]<>v[i] then co:=co+1: fi: od: co: end: #SPB(q,n,d): The best you can hope for (as far as the size of C) for q-ary (n,2*t+1) code SPB:=proc(q,n,t) local i: trunc(q^n/add(binomial(n,i)*(q-1)^i,i=0..t)): end: #RV(q,n): A random word of length n in {0,1,..,q-1} RV:=proc(q,n) local ra,i: ra:=rand(0..q-1): [seq( ra(), i=1..n)]: end: #RC(q,n,d,K): inputs q,n,d, and K and keeps picking K+1 (thanks to Nuray) random vectors #whenver the new vector is not distance <=d-1 from all the previous one RC:=proc(q,n,d,K) local C,v,i,c: C:={RV(q,n)}: for i from 1 to K do v:=RV(q,n): if min(seq(HD(v,c), c in C))>=d then C:=C union {v}: fi: od: C: end: BDfano:=proc(): {{1,2,4},{2,3,5},{3,4,6},{4,5,7},{5,6,1},{6,7,2},{7,1,3}}: end: BDex212:=proc(): {{1,3,4,5,9}, {2,4,5,6,10}, {3,5,6,7,11}, {1,4,6,7,8}, {2,5,7,8,9}, {3,6,8,9,10}, {4,7,9,10,11}, {1,5,8,10,11}, {1,2,6,9,11}, {1,2,3,7,10}, {2,3,4,8,11} } end: #end of old code #Nei(q,c): all the neighbors of the vector c in Fqn(q,n) Nei:=proc(q,c) local n,i,a: n:=nops(c): {seq(seq([op(1..i-1,c),a,op(i+1..n,c)], a=0..q-1) , i=1..n)}: end: #SP(q,c,t): the set of all vectors in Fqn(q,n) whose distance is <=t from c SP:=proc(q,c,t) local S,s,i: S:={c}: for i from 1 to t do S:=S union {seq(op(Nei(q,s)),s in S)}: od: S: end: GRC:=proc(q,n,d) local S,A,v: A:=Fqn(q,n): S:={}: while A<>{} do: v:=A[1]: S:=S union {v}: A:=A minus SP(q,v,d-1): od: S: end: #GRCgs(q,n,d): George Spahn's version GRCgs:=proc(q,n,d) local S,A,v: print(`Warning: use at your own risk`): A:=Fqn(q,n): S:={}: while A<>{} do: v:=A[rand(1..nops(A))()]: S:=S union {v}: A:=A minus SP(q,v,d-1): od: S: end: #MinD(C): The minimal (Hamming) distance of the code C MinD:=proc(C) local i,j: min( seq(seq(HD(C[i],C[j]),j=i+1..nops(C)), i=1..nops(C))): end: #CV(S,n): the characteristic vector of the subset S of {1,...,n} CV:=proc(S,n) local v,i: v:=[]: for i from 1 to n do if member(i,S) then v:=[op(v),1]: else v:=[op(v),0]: fi: od: v: end: BDtoC:=proc(BD,n) local s, C: C:={seq(CV(s,n),s in BD)}: C:=C union subs({0=1,1=0},C): C union {[0$n],[1$n]}: end: ##end of old stuff #LtoC(q,M): inputs a list of basis vectors for our linear code over GF(q) #outputs all the codewords (the actual subset of GF(q)^n with q^k elements LtoC:=proc(q,M) local n,k,C,c,i,M1: option remember: k:=nops(M): n:=nops(M[1]): if k=1 then RETURN({seq(i*M[1] mod q,i=0..q-1) }): fi: M1:=M[1..k-1]: C:=LtoC(q,M1): {seq(seq(c+i*M[k] mod q,i=0..q-1),c in C)}: end: #MinW(q,M): The minimal weight of the Linear code generated by M over GF(q) MinW:=proc(q,M) local n,C,c: n:=nops(M[1]): C:=LtoC(q,M): min( seq(HD(c,[0$n]), c in C minus {[0$n]} )): end: ####end of old code #start new code for C7.txt #NN(C,v), inputs a code C (subset of Fqn(q,n) where n:=nops(v)) finds #the set of members of C closest to v NN:=proc(C,v) local i,rec,cha: cha:={C[1]}: rec:=HD(v,C[1]): for i from 2 to nops(C) do if HD(v,C[i])FAIL do M:=M1: M1:=GLC1(q,M,d): od: M: end: #SA(q,n,M): inputs a basis M of a linear [n,nops(M),d] code outputs Slepian's Standard Array #as a matrix of vectors containing all the vectors in GF(q)^n (alas Fqn(q,n)) such that #the first row is an ordering of the members of the actual code (LtoC(q,M)) with #[0$n] the first entry and the first columns are the coset reprenatives SA:=proc(q,n,M) local SL,C,A: C:=LtoC(q,M): C:=C minus {[0$n]}: SL:=[[0$n],op(C)]: A:=Fqn(q,n) minus {op(SL[1])}: #write a function minW(A) that finds a vector of smallest weight among A #choose it as the next coset represntatice a1 #the next row is a1+SL[1]: #keep updating A until you run out of vectors in Fq(q,n) end: ###start code by Daniel Elwell # PART 4: SF() PROCEDURE: # ----------------------- # gets a row from a matrix GetRow:=proc(M,r) local v,i,n: v:=[]; n:=nops(M[1]); for i from 1 to n do: v:=[op(v),M[r,i]]; od; return v; end; # sets a row in a matrix SetRow:=proc(M,r,v) local i,M1: M1:=copy(M); for i from 1 to nops(v) do: M1[r,i]:=v[i]; od; return M1; end; # gets a column from a matrix GetCol:=proc(M,c) local v,i,n: v:=[]; n:=nops(M); for i from 1 to n do: v:=[op(v),M[i,c]]; od; return v; end; # sets a column in a matrix SetCol:=proc(M,c,v) local i,M1: M1:=copy(M); for i from 1 to nops(v) do: M1[i,c]:=v[i]; od; return M1; end; # returns matrix M in standard form SFde:=proc(q,M) local k,n,i,j,S,rj,cj,ri: k:=nops(M); n:=nops(M[1]); S:=copy(M); for i from 1 to k do: # algorithm is iterated from 1 to k # if S_ii = 0, then we need to perform a swap: if S[i,i] = 0 then for j from i+1 to k while S[j,i] = 0 do od; # look for available row if j<=k then # swap rows rj:=GetRow(S,j); S:=SetRow(S,j, GetRow(S,i)); S:=SetRow(S,i,rj); else # look to swap columns for j from i+1 to n while S[i,j] = 0 do od; # look for available col # swap cols cj:=GetCol(S,j); S:=SetCol(S,j, GetCol(S,i)); S:=SetCol(S,i,cj); fi; fi; # scale row to have leading entry 1 ri:=GetRow(S,i); ri:=(ri*(ri[i]&^(-1) mod q)) mod q; S:=SetRow(S,i,ri); for j from 1 to k do: if j <> i then rj:=GetRow(S,j); rj:=(rj - (rj[i] * ri mod q)) mod q; S:=SetRow(S,j,rj); fi; od; od; return S; end; ###end code by Daniel Elwell #start code from Aurora Hiveley # finds a vector of smallest weight among A (collection of given vectors) minW := proc(A) local n,v,w,minw,minv: n:= nops(A[1]): minw := HD(A[1],[0$n]): minv := A[1]: # initialize min weight vectors for v in A do w:= HD(v,[0$n]): if w < minw then minw := w : minv := v : fi: od: minv; end: #SAah(q,n,M): inputs a basis M of a linear [n,nops(M),d] code outputs Slepian's Standard Array #as a matrix of vectors containing all the vectors in GF(q)^n (alas Fqn(q,n)) such that #the first row is an ordering of the members of the actual code (LtoC(q,M)) with #[0$n] the first entry and the first columns are the coset reprenatives SAah:=proc(q,n,M) local SL,C,A,a,r1,r,j: # copied from class C:=LtoC(q,M): C:=C minus {[0$n]}: # added r1 := [[0$n],op(C)]: SL := [r1]: A:=Fqn(q,n) minus {op(r1)}: # changed from class while A<>{} do # find coset representative of min weight a := minW(A) : # build next row r := []: for j from 1 to nops(r1) do r := [op(r), a + r1[j] mod q]: od: # add new row to array SL := [op(SL), r]; # print(SL); # update available vectors A := A minus {op(SL[-1])}: od: SL; end: #end code from Aurora Hiveley