/dports/biology/p5-Bio-Graphics/Bio-Graphics-2.40/scripts/ |
H A D | coverage_to_topoview.pl | 70 close COV; 126 my $offset = tell(COV); 137 $offset = tell(COV); 155 $offset = tell(COV); 160 $offset = tell(COV); 175 $offset = tell(COV); 196 print COV join("\t",$start,$signal), "\n"; 208 print COV "# offsets for $key\n"; 209 my $offset = tell(COV); 215 print COV $str . "\n"; [all …]
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/dports/math/cmlib/cmlib-3.0_8/src/cluster/ |
H A D | remove.f | 1 SUBROUTINE REMOVE(DMCOV, N, COV, I, S) argument 40 DIMENSION COV(DMCOV,*), S(*) 43 IF (COV(I,I).LT.TH.OR.S(I).EQ.0.) RETURN 48 * COV(J,K)=COV(J,K)-COV(I,J)*COV(I,K)/COV(I,I)
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H A D | two.f | 1 SUBROUTINE TWO(MM, M, N, A, CLAB, RLAB, TITLE, DMCOV, COV, argument 104 DIMENSION COV(DMCOV,*),AVE(*),A(MM,*) 128 COV(J,K)=0. 130 50 COV(J,K)=COV(J,K)+(A(I,J)-AVE(J))*(A(I,K)-AVE(K)) 131 COV(J,K)=COV(J,K)/M 132 60 COV(K,J)=COV(J,K)
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H A D | wcov.f | 1 SUBROUTINE WCOV(MM, M, N, A, CLAB, RLAB, TITLE, NC, DMCOV, COV, argument 93 DIMENSION A(MM,*), COV(DMCOV,*), NC(*), WORK(*) 101 10 COV(I,J)=0. 130 70 COV(J,JJ)=COV(J,JJ)+(A(I,J)-WORK(J))*(A(I,JJ) 140 IF(Q.GT.0.) COV(J,JJ)=COV(J,JJ)/Q 141 100 COV(JJ,J)=COV(J,JJ)
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H A D | first.f | 1 SUBROUTINE FIRST(DMCOV, N, COV, X, Y) argument 46 DIMENSION COV(DMCOV,*), X(*), Y(*) 51 IF(COV(I,I).LE.TH) THEN 53 COV(I,J) = 0. 54 10 COV(J,I) = 0. 56 IF (X(I).NE.0.) X(I)=SQRT(COV(I,I)) 70 60 IF (X(J).NE.0.) Y(I)=Y(I)+COV(I,J)*X(J)
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H A D | find.f | 1 SUBROUTINE FIND(DMCOV, N, COV, Y, X, XY) argument 44 DIMENSION COV(DMCOV,*), X(*), Y(*), XY(*) 52 20 CALL FIRST(DMCOV,N,COV,X,XY) 69 40 XX=XX+X(I)*COV(I,J) 70 XX=XX*XX/(SS*SS*COV(J,J)) 86 CALL REMOVE(DMCOV,N,COV,IMIN,X)
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H A D | sparse.f | 1 SUBROUTINE SPARSE(MM, M, N, A, CLAB, RLAB, TITLE, KK, DMCOV, COV, argument 107 DIMENSION COV(DMCOV,*), WORK1(DMWRK1,*), WORK2(DMWRK2,*), A(MM,*) 114 CALL TWO(MM,M,N,A,CLAB,RLAB,TITLE,DMCOV,COV,CWORK(1),CTITLE, 121 CALL OUT(DMCOV,N,N,COV,CWORK(1),CWORK(1),CTITLE,OUNIT) 124 10 SS=SS+COV(J,J) 129 20 WORK2(I,J)=COV(I,J) 130 CALL FIND(DMCOV,N,COV,WORK1(1,KR),WORK2(1,N+1),WORK2(1,N+2)) 136 30 COV(I,J)=WORK2(I,J)-WORK1(I,KR)*WORK1(J,KR)
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/dports/math/gsl/gsl-2.7/doc/examples/ |
H A D | fitting2.c | 57 #define COV(i,j) (gsl_matrix_get(cov,(i),(j))) in main() macro 65 COV(0,0), COV(0,1), COV(0,2)); in main() 67 COV(1,0), COV(1,1), COV(1,2)); in main() 69 COV(2,0), COV(2,1), COV(2,2)); in main()
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/dports/science/dakota/dakota-6.13.0-release-public.src-UI/packages/external/acro/packages/utilib/src/libs/ |
H A D | cov.c | 17 int covariance(double **X, int m, int n, double **COV); 19 int covariance(double **X, int m, int n, double **COV) in covariance() argument 24 temp_vec = COV[0]; in covariance() 42 COV[k][l] = 0.0; in covariance() 44 COV[k][l] += X[j][k]*X[j][l]; in covariance() 45 COV[k][l] /= ((double) (m-1)); in covariance() 46 COV[l][k] = COV[k][l]; in covariance()
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/dports/math/R-cran-acepack/acepack/src/ |
H A D | rlsmo.f | 67 COV=0. 77 COV=COV+WIN*(XIN-XBAR)*(YIN-YBAR)*(SUMW+WIN)/SUMW 90 COV=COV-WIN*(XOUT-XBAR)*(YOUT-YBAR)*SUMW/(SUMW-WIN) 109 COV=COV+WIN*(XIN-XBAR)*(YIN-YBAR)*(SUMW+WIN)/SUMW 116 SCRAT(1)=COV/VAR 171 COV=COV+WIN*(XIN-XBAR)*(YIN-YBAR)*(SUMW+WIN)/SUMW 183 COV=COV+WIN*(XIN-XBAR)*(YIN-YBAR)*(SUMW+WIN)/SUMW 192 COV=COV-WIN*(XOUT-XBAR)*(YOUT-YBAR)*SUMW/(SUMW-WIN) 204 COV=COV-WIN*(XOUT-XBAR)*(YOUT-YBAR)*SUMW/(SUMW-WIN) 216 COV=COV-WIN*(XOUT-XBAR)*(YOUT-YBAR)*SUMW/(SUMW-WIN) [all …]
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/dports/science/dakota/dakota-6.13.0-release-public.src-UI/packages/pecos/src/ |
H A D | LognormalRandomVariable.hpp | 322 Real COV = coefficient_of_variation(), COV_rv; in correlation_warping_factor() local 327 return 1.019 + (0.014 + 0.249*COV)*COV + 0.01*corr*corr; break; in correlation_warping_factor() 330 + ( 0.019 + 0.303*COV - 0.437*corr)*COV; break; in correlation_warping_factor() 333 + ( 0.014 + 0.233*COV - 0.197*corr)*COV; break; in correlation_warping_factor() 339 std::sqrt(bmth::log1p(COV*COV)*bmth::log1p(COV_rv*COV_rv)); break; in correlation_warping_factor() 343 + (0.004 + 0.223*COV - 0.104*corr)*COV in correlation_warping_factor() 348 + (-0.019 + 0.288*COV - 0.441*corr)*COV in correlation_warping_factor() 353 + (0.011 + 0.22*COV + 0.005*corr)*COV in correlation_warping_factor() 479 Real COV = std_dev/mean, zeta = std::sqrt(bmth::log1p(COV*COV)); in error_factor_from_std_deviation() local 496 Real COV = std_dev/mean; in zeta_sq_from_moments() local [all …]
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H A D | FrechetRandomVariable.hpp | 254 Real COV = coefficient_of_variation(), COV_rv; in correlation_warping_factor() local 260 Real COV2 = COV*COV, COV_rv2 = COV_rv*COV_rv, corr2 = corr*corr; in correlation_warping_factor() 261 return 1.086 + 0.054*corr + 0.104*(COV + COV_rv) - 0.055*corr2 in correlation_warping_factor() 262 + 0.662*(COV2 + COV_rv2) - 0.57*corr*(COV + COV_rv) + 0.203*COV*COV_rv in correlation_warping_factor() 263 - 0.02*corr2*corr - 0.218*(COV2*COV+COV_rv2*COV_rv) in correlation_warping_factor() 264 - 0.371*corr*(COV2 + COV_rv2) + 0.257*corr2*(COV + COV_rv) in correlation_warping_factor() 265 + 0.141*COV*COV_rv*(COV + COV_rv); break; in correlation_warping_factor() 270 + (-0.259 + 0.435*COV_rv + 0.034*COV - 0.481*corr)*COV_rv in correlation_warping_factor() 271 + ( 0.241 + 0.372*COV + 0.005*corr)*COV; break; in correlation_warping_factor()
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H A D | NormalRandomVariable.hpp | 271 Real COV; in correlation_warping_factor() local 287 COV = rv.coefficient_of_variation(); in correlation_warping_factor() 288 return COV/std::sqrt(bmth::log1p(COV*COV)); break; // Exact in correlation_warping_factor() 290 COV = rv.coefficient_of_variation(); in correlation_warping_factor() 291 return 1.001 + (-0.007 + 0.118*COV)*COV; break; // Max Error 0.0% in correlation_warping_factor() 293 COV = rv.coefficient_of_variation(); in correlation_warping_factor() 294 return 1.03 + ( 0.238 + 0.364*COV)*COV; break; // Max Error 0.1% in correlation_warping_factor() 296 COV = rv.coefficient_of_variation(); in correlation_warping_factor() 297 return 1.031 + (-0.195 + 0.328*COV)*COV; break; // Max Error 0.1% in correlation_warping_factor()
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H A D | GammaRandomVariable.hpp | 343 Real COV = coefficient_of_variation(), COV_rv; in correlation_warping_factor() local 349 + (-0.007 + 0.131*COV - 0.132*corr)*COV; break; in correlation_warping_factor() 354 return 1.002 + 0.022*corr - 0.012*(COV + COV_rv) + 0.001*corr*corr in correlation_warping_factor() 355 + 0.125*(COV*COV + COV_rv*COV_rv) - 0.077*corr*(COV + COV_rv) in correlation_warping_factor() 356 + 0.014*COV*COV_rv; break; in correlation_warping_factor() 360 + (-0.03 + 0.174*COV - 0.313*corr)*COV in correlation_warping_factor() 361 + (0.225 + 0.379*COV_rv + 0.075*COV - 0.182*corr)*COV_rv; break; in correlation_warping_factor() 365 + (-0.007 + 0.121*COV - 0.006*corr + 0.003*COV_rv)*COV in correlation_warping_factor()
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H A D | ExponentialRandomVariable.hpp | 292 Real COV; in correlation_warping_factor() local 303 COV = rv.coefficient_of_variation(); in correlation_warping_factor() 305 + (-0.008 + 0.173*COV - 0.296*corr)*COV; break; // Max Error 0.9% in correlation_warping_factor() 307 COV = rv.coefficient_of_variation(); in correlation_warping_factor() 309 + ( 0.361 + 0.455*COV - 0.728*corr)*COV; break; // Max Error 4.5% in correlation_warping_factor() 311 COV = rv.coefficient_of_variation(); in correlation_warping_factor() 313 + (-0.271 + 0.459*COV - 0.467*corr)*COV; break; // Max Error 0.4% in correlation_warping_factor()
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/dports/math/R-cran-mvtnorm/mvtnorm/src/ |
H A D | mvt.f | 164 COV(2) = COV(2)/R 284 COV(IJ) = CORREL(II) 287 COV(IJ) = 1 346 COV(II+I) = CVDIAG 355 COV(IL+I) = COV(IL+I)/CVDIAG 358 COV(IL+J) = COV(IL+J) - COV(IL+I)*COV(IJ+I) 378 COV(II) = COV(II)/CVDIAG 386 COV(IL+I) = 0 404 COV(II+L) = COV(II+L)/COV(II+J) 411 CALL MVSSWP( COV(IJ-K+M), COV(IJ+M) ) [all …]
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/dports/math/octave-forge-nan/nan-3.6.1/inst/ |
H A D | cov.m | 2 % COV covariance matrix 14 % However, COV is faster than CORRCOEF and might be good enough in some cases. 16 % C = COV(X [,Mode]); 18 % C = COV(X,Y [,Mode]); 25 % a) use COV([X(:),Y(:)]) if you want the traditional Matlab result. 26 % b) use C = COV([X,Y]), C = C(1:size(X,2),size(X,2)+1:size(C,2)); if you want to be compatib… 73 fprintf(2,'Error COV: invalid number of arguments\n'); 77 % COV in Matlab is differently defined than COV in Octave. 79 …fprintf(2,'Warning NaN/COV: This kind of use of COV is discouraged because it produces different r… 80 … fprintf(2,' (a) the traditional Matlab result can be obtained with: C = COV([X(:),Y(:)]).\n'); [all …]
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H A D | decovm.m | 1 function [mu,sd,COV,xc,M,R2]=decovm(XCN,NN) 3 % standard deviation, the (pure) Covariance (COV), 6 % [mu,sd,COV,xc,N,R2]=decovm(ECM[,NN]) 53 COV = XCN(2:c,2:c) - mu'*mu; variable 54 sd = sqrt(diag(COV))'; 56 xc = COV./(sd'*sd); 64 COV=(XCN(2:N,2:N)/XCN(1,1)-XCN(2:N,1)*XCN(1,2:N)/XCN(1,1)^2); 65 sd=sqrt(diag(COV)); 66 xc=COV./(sd*sd');
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/dports/science/py-scipy/scipy-1.7.1/scipy/stats/ |
H A D | mvndst.f | 236 SAVE A, B, INFI, COV 354 COV(IJ) = CORREL(II) 357 COV(IJ) = 1 409 COV(II+I) = CVDIAG 418 COV(IL+I) = COV(IL+I)/CVDIAG 421 COV(IL+J) = COV(IL+J) - COV(IL+I)*COV(IJ+I) 439 COV(II) = COV(II)/CVDIAG 446 COV(IL+I) = 0 463 COV(II+L) = COV(II+L)/COV(II+J) 470 CALL DKSWAP( COV(IJ-K+M), COV(IJ+M) ) [all …]
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/dports/security/snuffleupagus/snuffleupagus-0.7.0/ |
H A D | Makefile | 36 rm -Rf src/COV.html 39 lcov --base-directory ./src --directory ./src -c -o ./src/COV.info --rc lcov_branch_coverage=1 40 …lcov --remove src/COV.info '/usr/*' --remove src/COV.info '*tweetnacl.c' -o src/COV.info --rc lcov… 41 genhtml --show-details -o src/COV.html ./src/COV.info --branch-coverage
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/dports/devel/llvm-devel/llvm-project-f05c95f10fc1d8171071735af8ad3a9e87633120/compiler-rt/test/fuzzer/ |
H A D | OutOfProcessFuzzTarget.cpp | 51 static std::string *Run, *IN, *COV; variable 54 unlink(COV->c_str()); in TearDown() 60 COV = new std::string("lf-oop-cov-" + std::to_string(getpid())); in Initialize() 66 Run = new std::string("SANCOV_OUT=" + *COV + " " + TargetEnv + " " + *IN); in Initialize() 81 if (FILE *f = fopen(COV->c_str(), "r")) { in LLVMFuzzerTestOneInput()
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/dports/biology/biosig/biosig-2.3.3/biosig4matlab/t490_EvaluationCriteria/ |
H A D | qcmahal.m | 11 % [Q,D,R,COV]=qcmahal(XC); 16 % COV gives the suggested class definition 49 n=NC; %size(COV); 54 for k=1:NC(1),%size(COV,1); 55 %[M,SD1,XC01,xc01,N1] = decovm(squeeze(COV(k,:,:))); 77 w{k,l} = squeeze(COV(k,2:n(2),1)-COV(l,2:n(2),1)) / (XC{k} + XC{l}); 78 w{k,l} = [-sum(COV([k,l],2:n(2),1),1)*w{k,l}; w{k,l}]; 91 %tmpCOV = COV; 99 if any(q>Q), COV = tmp1; end; % if actual value is not optimal, keep reduced matrix
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/dports/biology/biosig/biosig-2.3.3/biosig4matlab/t400_Classification/ |
H A D | decovm.m | 1 function [mu,sd,COV,xc,M,R2]=decovm(XCN,NN) 3 % standard deviation, the (pure) Covariance (COV), 6 % [mu,sd,COV,xc,N,R2]=decovm(ECM[,NN]) 53 COV = XCN(2:c,2:c) - mu'*mu; variable 54 sd = sqrt(diag(COV))'; 56 xc = COV./(sd'*sd); 64 COV=(XCN(2:N,2:N)/XCN(1,1)-XCN(2:N,1)*XCN(1,2:N)/XCN(1,1)^2); 65 sd=sqrt(diag(COV)); 66 xc=COV./(sd*sd');
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/dports/math/cado-nfs/cado-nfs-f4284e2391121b2bfb97bc4880b6273c7250dc2f/dev_docs/ |
H A D | README.coverage.md | 15 if [ "$COV" ] ; then 26 COV=1 make cmake 27 COV=1 make -j8 28 COV=1 ./cado-nfs.py 90377629292003121684002147101760858109247336549001090677693 29 eval $(COV=1 make show)
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/dports/math/cmlib/cmlib-3.0_8/src/nl2sn/ |
H A D | nl2it.f | 127 INTEGER COV, G1, GI, I, IV1, JTOL1, K, L, LH, 363 COV = L 365 COV = IABS(IV(FDH)) 372 CALL LINVRT(P, V(COV), V(COV)) 373 CALL LTSQAR(P, V(COV), V(COV)) 375 L = COV + LH - 1 376 DO 260 I = COV, L 378 IV(COVMAT) = COV
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