mirror of https://github.com/saitohirga/WSJT-X.git
Add 'code b' - a better (128,90) code. Code b has irregular column weights - 80% weight 3 and 20% weight 4.
This commit is contained in:
Steve Franke
parent
1aeaa1715b
commit
6846964170
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@ -5,18 +5,18 @@ subroutine bpdecode128_90(llr,apmask,maxiterations,decoded,cw,nharderror,iter)
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integer, parameter:: N=128, K=90, M=N-K
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integer*1 codeword(N),cw(N),apmask(N)
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integer*1 decoded(K)
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integer Nm(11,M)
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integer Mn(3,N) ! 3 checks per bit
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integer Nm(12,M)
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integer Mn(4,N)
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integer synd(M)
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real tov(3,N)
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real toc(11,M)
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real tanhtoc(11,M)
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real tov(4,N)
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real toc(12,M)
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real tanhtoc(12,M)
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real zn(N)
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real llr(N)
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real Tmn
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integer nrw(M),ncw
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integer nrw(M),ncw(N)
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include "ldpc_128_90_reordered_parity.f90"
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include "ldpc_128_90_b_reordered_parity.f90"
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decoded=0
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toc=0
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@ -36,7 +36,7 @@ do iter=0,maxiterations
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! Update bit log likelihood ratios (tov=0 in iteration 0).
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do i=1,N
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if( apmask(i) .ne. 1 ) then
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zn(i)=llr(i)+sum(tov(1:ncw,i))
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zn(i)=llr(i)+sum(tov(1:ncw(i),i))
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else
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zn(i)=llr(i)
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endif
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@ -84,7 +84,7 @@ do iter=0,maxiterations
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do i=1,nrw(j)
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ibj=Nm(i,j)
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toc(i,j)=zn(ibj)
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do kk=1,ncw ! subtract off what the bit had received from the check
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do kk=1,4 ! subtract off what the bit had received from the check
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if( Mn(kk,ibj) .eq. j ) then
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toc(i,j)=toc(i,j)-tov(kk,ibj)
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endif
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@ -94,11 +94,11 @@ do iter=0,maxiterations
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! send messages from check nodes to variable nodes
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do i=1,M
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tanhtoc(1:11,i)=tanh(-toc(1:11,i)/2)
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tanhtoc(1:12,i)=tanh(-toc(1:12,i)/2)
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enddo
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do j=1,N
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do i=1,ncw
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do i=1,ncw(j)
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ichk=Mn(i,j) ! Mn(:,j) are the checks that include bit j
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Tmn=product(tanhtoc(1:nrw(ichk),ichk),mask=Nm(1:nrw(ichk),ichk).ne.j)
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call platanh(-Tmn,y)
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@ -10,7 +10,7 @@ integer*1 codeword(N)
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integer*1 gen(M,K)
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integer*1 message(K)
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integer*1 pchecks(M)
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include "ldpc_128_90_generator.f90"
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include "ldpc_128_90_b_generator.f90"
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logical first
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data first/.true./
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save first,gen
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@ -0,0 +1,41 @@
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character*23 g(38)
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data g/ &
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"c555076254d8161b5cf0d3c", &
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"de721b14e8339ab48de8e54", &
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"e72d0efb6ca44934a896ca0", &
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"631b7cc783a5e626c360598", &
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"7050206b9b2e40439d17d94", &
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"2f31c22ab472282d65cde44", &
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"822baa20e8bcd6487d34268", &
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"f9a85b9d103459b8ac34830", &
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"60335e63618f9e59e031a5c", &
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"b106c464771df41ab75884c", &
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"3936fcebf87320d200e6b1c", &
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"00135e63218f1c59c031e5c", &
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"554abf55a1605425b8e8248", &
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"2211850e5b32c02e42c85ec", &
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"853e66d64fdf2f5cf4237a8", &
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"90592d932a0c8e8190e6c50", &
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"d0cdf8954d48457b6a43df0", &
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"83714b5735b5bcd718887f0", &
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"3146c024731df43a3750844", &
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"a231a50e5232c0ae40c8dac", &
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"8f5f0d73fab5d0d57bb9c48", &
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"5650a8094847925466e560c", &
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"5842d5c55ff32151f36ca3c", &
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"0f571d7bfab4d0c57bfbcc8", &
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"bb68edb9987ea6a4f56a214", &
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"9d7cb35b100c0e8d07cff80", &
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"6774a36c46e8d7b518780b0", &
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"b07ca6f22cc3db62ca73fac", &
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"d6610575c99c82edcddd028", &
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"e64c7bb5d67de03d1fb0824", &
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"e9bb04fe35bb65a16e856ec", &
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"6c5c41bc591174e3b81e950", &
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"49b480238e0623d1dd61e08", &
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"c48ae6d581d94c8c2b4a8a0", &
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"a16ace594ec778f95e5020c", &
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"ef2cd3309b2a4e8e9a98614", &
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"06008a62f368d236fbf2998", &
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"015fe1f7dd017a9f67be59c"/
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@ -0,0 +1,184 @@
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data Mn/ &
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10, 25, 37, 0, &
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1, 19, 20, 0, &
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20, 27, 29, 0, &
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3, 22, 36, 0, &
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4, 26, 30, 0, &
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5, 15, 28, 0, &
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6, 21, 23, 0, &
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7, 16, 32, 0, &
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9, 31, 38, 0, &
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10, 13, 18, 0, &
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11, 20, 37, 0, &
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12, 24, 33, 0, &
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14, 25, 33, 0, &
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15, 17, 32, 0, &
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1, 9, 14, 0, &
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2, 16, 17, 0, &
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3, 5, 18, 0, &
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4, 23, 38, 0, &
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6, 24, 37, 0, &
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7, 25, 35, 0, &
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8, 29, 33, 0, &
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10, 30, 36, 0, &
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11, 27, 28, 0, &
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12, 22, 32, 0, &
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13, 17, 21, 0, &
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10, 19, 31, 0, &
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18, 26, 34, 0, &
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1, 5, 30, 0, &
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2, 19, 25, 0, &
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3, 9, 21, 0, &
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4, 8, 11, 0, &
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6, 35, 38, 0, &
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7, 13, 29, 0, &
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12, 20, 26, 0, &
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14, 24, 27, 0, &
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15, 23, 34, 0, &
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16, 31, 37, 0, &
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10, 22, 28, 0, &
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28, 34, 36, 0, &
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1, 37, 38, 0, &
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2, 5, 13, 0, &
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3, 7, 14, 0, &
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4, 16, 19, 0, &
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6, 18, 29, 0, &
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8, 17, 23, 0, &
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9, 33, 36, 0, &
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11, 12, 35, 0, &
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15, 25, 27, 0, &
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20, 30, 32, 0, &
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21, 24, 26, 0, &
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22, 31, 33, 0, &
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1, 3, 17, 0, &
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2, 8, 36, 0, &
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4, 14, 34, 0, &
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5, 20, 24, 0, &
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6, 12, 30, 0, &
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7, 19, 37, 0, &
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9, 22, 23, 0, &
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10, 27, 35, 0, &
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11, 25, 38, 0, &
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13, 28, 31, 0, &
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11, 15, 29, 0, &
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16, 18, 21, 0, &
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26, 27, 32, 0, &
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1, 4, 10, 0, &
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2, 9, 29, 32, &
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3, 6, 20, 33, &
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5, 21, 31, 34, &
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7, 8, 15, 30, &
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12, 13, 14, 16, &
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17, 22, 26, 37, &
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15, 18, 36, 38, &
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19, 22, 24, 35, &
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12, 23, 25, 28, &
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1, 13, 32, 33, &
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2, 11, 14, 18, &
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3, 10, 26, 38, &
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4, 24, 31, 32, &
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5, 6, 17, 25, &
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7, 9, 24, 28, &
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8, 9, 34, 37, &
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16, 20, 23, 35, &
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19, 21, 27, 30, &
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16, 26, 29, 36, &
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1, 22, 25, 29, &
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2, 3, 15, 37, &
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4, 12, 21, 36, &
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5, 8, 14, 19, &
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6, 7, 10, 34, &
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11, 17, 19, 33, &
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1, 12, 31, 0, &
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2, 4, 33, 0, &
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3, 16, 30, 0, &
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1, 2, 24, 0, &
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5, 23, 27, 0, &
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6, 28, 32, 0, &
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7, 17, 36, 0, &
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8, 22, 38, 0, &
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9, 18, 20, 0, &
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10, 21, 29, 0, &
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11, 13, 34, 0, &
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4, 20, 22, 0, &
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7, 11, 21, 0, &
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14, 35, 37, 0, &
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15, 19, 26, 0, &
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3, 28, 29, 0, &
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9, 13, 35, 0, &
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14, 17, 30, 0, &
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10, 15, 33, 0, &
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5, 12, 37, 0, &
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18, 25, 32, 0, &
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8, 16, 27, 0, &
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19, 34, 38, 0, &
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24, 25, 36, 0, &
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2, 28, 35, 0, &
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19, 23, 36, 0, &
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3, 12, 34, 0, &
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9, 15, 16, 0, &
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4, 5, 7, 0, &
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1, 8, 21, 0, &
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6, 13, 22, 0, &
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11, 24, 30, 0, &
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8, 26, 35, 0, &
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6, 26, 31, 0, &
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14, 32, 38, 0, &
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18, 23, 33, 0, &
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2, 27, 34, 0, &
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17, 29, 31, 0/
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data Nm/ &
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2, 15, 28, 40, 52, 65, 75, 85, 91, 94, 120, 0, &
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16, 29, 41, 53, 66, 76, 86, 92, 94, 115, 127, 0, &
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4, 17, 30, 42, 52, 67, 77, 86, 93, 106, 117, 0, &
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5, 18, 31, 43, 54, 65, 78, 87, 92, 102, 119, 0, &
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6, 17, 28, 41, 55, 68, 79, 88, 95, 110, 119, 0, &
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7, 19, 32, 44, 56, 67, 79, 89, 96, 121, 124, 0, &
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8, 20, 33, 42, 57, 69, 80, 89, 97, 103, 119, 0, &
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21, 31, 45, 53, 69, 81, 88, 98, 112, 120, 123, 0, &
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9, 15, 30, 46, 58, 66, 80, 81, 99, 107, 118, 0, &
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1, 10, 22, 26, 38, 59, 65, 77, 89, 100, 109, 0, &
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11, 23, 31, 47, 60, 62, 76, 90, 101, 103, 122, 0, &
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12, 24, 34, 47, 56, 70, 74, 87, 91, 110, 117, 0, &
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10, 25, 33, 41, 61, 70, 75, 101, 107, 121, 0, 0, &
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13, 15, 35, 42, 54, 70, 76, 88, 104, 108, 125, 0, &
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6, 14, 36, 48, 62, 69, 72, 86, 105, 109, 118, 0, &
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8, 16, 37, 43, 63, 70, 82, 84, 93, 112, 118, 0, &
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14, 16, 25, 45, 52, 71, 79, 90, 97, 108, 128, 0, &
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10, 17, 27, 44, 63, 72, 76, 99, 111, 126, 0, 0, &
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2, 26, 29, 43, 57, 73, 83, 88, 90, 105, 113, 116, &
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2, 3, 11, 34, 49, 55, 67, 82, 99, 102, 0, 0, &
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7, 25, 30, 50, 63, 68, 83, 87, 100, 103, 120, 0, &
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4, 24, 38, 51, 58, 71, 73, 85, 98, 102, 121, 0, &
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7, 18, 36, 45, 58, 74, 82, 95, 116, 126, 0, 0, &
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12, 19, 35, 50, 55, 73, 78, 80, 94, 114, 122, 0, &
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1, 13, 20, 29, 48, 60, 74, 79, 85, 111, 114, 0, &
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5, 27, 34, 50, 64, 71, 77, 84, 105, 123, 124, 0, &
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3, 23, 35, 48, 59, 64, 83, 95, 112, 127, 0, 0, &
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6, 23, 38, 39, 61, 74, 80, 96, 106, 115, 0, 0, &
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3, 21, 33, 44, 62, 66, 84, 85, 100, 106, 128, 0, &
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5, 22, 28, 49, 56, 69, 83, 93, 108, 122, 0, 0, &
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9, 26, 37, 51, 61, 68, 78, 91, 124, 128, 0, 0, &
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8, 14, 24, 49, 64, 66, 75, 78, 96, 111, 125, 0, &
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12, 13, 21, 46, 51, 67, 75, 90, 92, 109, 126, 0, &
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27, 36, 39, 54, 68, 81, 89, 101, 113, 117, 127, 0, &
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20, 32, 47, 59, 73, 82, 104, 107, 115, 123, 0, 0, &
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4, 22, 39, 46, 53, 72, 84, 87, 97, 114, 116, 0, &
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1, 11, 19, 37, 40, 57, 71, 81, 86, 104, 110, 0, &
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9, 18, 32, 40, 60, 72, 77, 98, 113, 125, 0, 0/
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data nrw/ &
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11,11,11,11,11,11,11,11,11,11,11,11,10,11,11,11, &
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11,10,12,10,11,11,10,11,11,11,10,10,11,10,10,11, &
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11,11,10,11,11,10/
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data ncw/ &
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3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3, &
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3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3, &
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3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3, &
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3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3, &
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3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4, &
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4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3, &
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3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3, &
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3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3/
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