/dports/deskutils/calibre/calibre-src-5.34.0/recipes/ |
H A D | daily_mirror.recipe | 78 cov2 = str(cov) 79 cov2 = 'http://www.politicshome.com' + cov2[9:-142] 80 # cov2 now contains url of the page containing pic 81 soup = self.index_to_soup(cov2) 84 cov2 = re.findall( 86 cov2 = str(cov2) 87 cov2 = cov2[2:len(cov2) - 2] 88 # cov2 now is pic url, now go back to original function 92 br.open_novisit(cov2) 93 cover_url = cov2
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H A D | birmingham_post.recipe | 33 cov2 = str(cov['src']) 34 print('88888888 ', cov2, ' 888888888888') 36 # cover_url=cov2 41 br.open_novisit(cov2) 42 cover_url = cov2
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/dports/biology/seqan-apps/seqan-seqan-v2.4.0/tests/journaled_string_tree/ |
H A D | test_delta_map.h | 76 TCoverage cov2; in createMock() local 77 _getCoverage(cov2, 10, 5); in createMock() 103 TCoverage cov2; in SEQAN_DEFINE_TEST() local 104 _getCoverage(cov2, 10, 5); in SEQAN_DEFINE_TEST() 142 TCoverage cov2; in SEQAN_DEFINE_TEST() local 143 _getCoverage(cov2, 10, 5); in SEQAN_DEFINE_TEST() 175 TCoverage cov2; in SEQAN_DEFINE_TEST() local 176 _getCoverage(cov2, 10, 5); in SEQAN_DEFINE_TEST() 200 TCoverage cov2; in SEQAN_DEFINE_TEST() local 201 _getCoverage(cov2, 10, 5); in SEQAN_DEFINE_TEST() [all …]
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/dports/lang/ruby26/ruby-2.6.9/tool/ |
H A D | test-coverage.rb | 9 cov2 = res2[path] 10 if cov2 13 add_count(cov2[:lines], i, count1) 16 if cov2[:branches][base_key] 18 add_count(cov2[:branches][base_key], target_key, count1) 21 cov2[:branches][base_key] = targets1 25 add_count(cov2[:methods], key, count1)
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/dports/science/R-cran-cmprsk/cmprsk/R/ |
H A D | cmprsk.R | 39 if(!missing(cov2)) 49 if (!missing(cov2)) { 50 cov2 <- as.matrix(cov2) 51 nc2 <- ncol(cov2) 52 d <- cbind(d,cov2) 89 cov2 <- 0 289 function(object,cov1,cov2,...) { argument 304 cov2 <- as.matrix(cov2) 312 c(cov2*object$coef[(np-length(cov2)+1):np]))*object$bfitj) 315 cov2 <- as.matrix(cov2) [all …]
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/dports/science/R-cran-cmprsk/cmprsk/tests/ |
H A D | test.R | 34 cov2 <- cbind(cv[,1],cv[,1]) globalVar 36 print(ww <- crr(ss,cc,cv,cov2,tf=tf,cengroup=cv[,3])) 44 print(ww <- crr(ssd,ccd,cbind(cv[,1:2],cv3),cov2,tf=tf,cengroup=cv3)) 45 print(ww <- crr(ssd,ccd,cbind(cv[,1:2],cv3),cov2,tf=tf)) 50 print(ww <- crr(ss,cc,cv,cov2,tf=tf,cengroup=cv[,3],subset=d2$X==1)) 51 print(ww <- crr(ss,cc,cv,cov2,tf=tf,cengroup=cv[,3],failcode=2)) 52 print(ww <- crr(ss,cc,cv,cov2,tf=tf,cengroup=cv[,3],cencode=2)) 54 print(ww <- crr(ss,cc,cov2=cv[,1],tf=function(x) x))
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/dports/science/dakota/dakota-6.13.0-release-public.src-UI/packages/external/muq2/modules/SamplingAlgorithms/test/ |
H A D | MarkovChainTests.cpp | 155 Eigen::MatrixXd cov2 = collection.Covariance(); in TEST_F() local 157 EXPECT_NEAR(trueCov(0,0), cov2(0,0), 50.0/sqrt(double(numSamps))); in TEST_F() 158 EXPECT_NEAR(trueCov(0,1), cov2(0,1), 100.0/sqrt(double(numSamps))); in TEST_F() 159 EXPECT_NEAR(trueCov(1,0), cov2(1,0), 100.0/sqrt(double(numSamps))); in TEST_F() 160 EXPECT_NEAR(trueCov(1,1), cov2(1,1), 150.0/sqrt(double(numSamps))); in TEST_F() 162 EXPECT_NEAR(sampCov(0,0), cov2(0,0), 1e-13); in TEST_F() 163 EXPECT_NEAR(sampCov(0,1), cov2(0,1), 1e-13); in TEST_F() 164 EXPECT_NEAR(sampCov(1,0), cov2(1,0), 1e-13); in TEST_F() 165 EXPECT_NEAR(sampCov(1,1), cov2(1,1), 1e-13); in TEST_F()
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H A D | SampleCollectionTests.cpp | 181 Eigen::MatrixXd cov2 = collection.Covariance(); in TEST_F() local 183 EXPECT_NEAR(trueCov(0,0), cov2(0,0), 5.0/sqrt(double(numSamps))); in TEST_F() 184 EXPECT_NEAR(trueCov(0,1), cov2(0,1), 10.0/sqrt(double(numSamps))); in TEST_F() 185 EXPECT_NEAR(trueCov(1,0), cov2(1,0), 10.0/sqrt(double(numSamps))); in TEST_F() 186 EXPECT_NEAR(trueCov(1,1), cov2(1,1), 50.0/sqrt(double(numSamps))); in TEST_F() 188 EXPECT_NEAR(sampCov(0,0), cov2(0,0), 1e-13); in TEST_F() 189 EXPECT_NEAR(sampCov(0,1), cov2(0,1), 1e-13); in TEST_F() 190 EXPECT_NEAR(sampCov(1,0), cov2(1,0), 1e-13); in TEST_F() 191 EXPECT_NEAR(sampCov(1,1), cov2(1,1), 1e-13); in TEST_F()
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/dports/science/R-cran-cmprsk/cmprsk/man/ |
H A D | predict.crr.Rd | 10 \method{predict}{crr}(object, cov1, cov2, \dots) 16 \item{cov1, cov2}{ 17 each row of cov1 and cov2 is a set of covariate values where the 18 subdistribution should be estimated. The columns of cov1 and cov2 must 30 and cov2, at each failure time (the value that the estimate jumps to at
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/dports/devel/boost-docs/boost_1_72_0/libs/accumulators/test/ |
H A D | tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., covariate1 = cov2); in test_stat() 62 acc2( 50., covariate1 = cov2); in test_stat() 68 acc3( 50., covariate1 = cov2); in test_stat() 74 acc4( 50., covariate1 = cov2); in test_stat()
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H A D | weighted_tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., weight = 0.9, covariate1 = cov2); in test_stat() 62 acc2( 50., weight = 0.9, covariate1 = cov2); in test_stat() 68 acc3( 50., weight = 0.9, covariate1 = cov2); in test_stat() 74 acc4( 50., weight = 0.9, covariate1 = cov2); in test_stat()
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/dports/databases/percona57-pam-for-mysql/boost_1_59_0/libs/accumulators/test/ |
H A D | tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., covariate1 = cov2); in test_stat() 62 acc2( 50., covariate1 = cov2); in test_stat() 68 acc3( 50., covariate1 = cov2); in test_stat() 74 acc4( 50., covariate1 = cov2); in test_stat()
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H A D | weighted_tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., weight = 0.9, covariate1 = cov2); in test_stat() 62 acc2( 50., weight = 0.9, covariate1 = cov2); in test_stat() 68 acc3( 50., weight = 0.9, covariate1 = cov2); in test_stat() 74 acc4( 50., weight = 0.9, covariate1 = cov2); in test_stat()
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/dports/databases/xtrabackup/boost_1_59_0/libs/accumulators/test/ |
H A D | tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., covariate1 = cov2); in test_stat() 62 acc2( 50., covariate1 = cov2); in test_stat() 68 acc3( 50., covariate1 = cov2); in test_stat() 74 acc4( 50., covariate1 = cov2); in test_stat()
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H A D | weighted_tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., weight = 0.9, covariate1 = cov2); in test_stat() 62 acc2( 50., weight = 0.9, covariate1 = cov2); in test_stat() 68 acc3( 50., weight = 0.9, covariate1 = cov2); in test_stat() 74 acc4( 50., weight = 0.9, covariate1 = cov2); in test_stat()
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/dports/databases/percona57-server/boost_1_59_0/libs/accumulators/test/ |
H A D | tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., covariate1 = cov2); in test_stat() 62 acc2( 50., covariate1 = cov2); in test_stat() 68 acc3( 50., covariate1 = cov2); in test_stat() 74 acc4( 50., covariate1 = cov2); in test_stat()
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H A D | weighted_tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., weight = 0.9, covariate1 = cov2); in test_stat() 62 acc2( 50., weight = 0.9, covariate1 = cov2); in test_stat() 68 acc3( 50., weight = 0.9, covariate1 = cov2); in test_stat() 74 acc4( 50., weight = 0.9, covariate1 = cov2); in test_stat()
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/dports/databases/percona57-client/boost_1_59_0/libs/accumulators/test/ |
H A D | tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., covariate1 = cov2); in test_stat() 62 acc2( 50., covariate1 = cov2); in test_stat() 68 acc3( 50., covariate1 = cov2); in test_stat() 74 acc4( 50., covariate1 = cov2); in test_stat()
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H A D | weighted_tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., weight = 0.9, covariate1 = cov2); in test_stat() 62 acc2( 50., weight = 0.9, covariate1 = cov2); in test_stat() 68 acc3( 50., weight = 0.9, covariate1 = cov2); in test_stat() 74 acc4( 50., weight = 0.9, covariate1 = cov2); in test_stat()
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/dports/devel/boost-libs/boost_1_72_0/libs/accumulators/test/ |
H A D | tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., covariate1 = cov2); in test_stat() 62 acc2( 50., covariate1 = cov2); in test_stat() 68 acc3( 50., covariate1 = cov2); in test_stat() 74 acc4( 50., covariate1 = cov2); in test_stat()
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H A D | weighted_tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., weight = 0.9, covariate1 = cov2); in test_stat() 62 acc2( 50., weight = 0.9, covariate1 = cov2); in test_stat() 68 acc3( 50., weight = 0.9, covariate1 = cov2); in test_stat() 74 acc4( 50., weight = 0.9, covariate1 = cov2); in test_stat()
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/dports/devel/boost-python-libs/boost_1_72_0/libs/accumulators/test/ |
H A D | tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., covariate1 = cov2); in test_stat() 62 acc2( 50., covariate1 = cov2); in test_stat() 68 acc3( 50., covariate1 = cov2); in test_stat() 74 acc4( 50., covariate1 = cov2); in test_stat()
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H A D | weighted_tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., weight = 0.9, covariate1 = cov2); in test_stat() 62 acc2( 50., weight = 0.9, covariate1 = cov2); in test_stat() 68 acc3( 50., weight = 0.9, covariate1 = cov2); in test_stat() 74 acc4( 50., weight = 0.9, covariate1 = cov2); in test_stat()
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/dports/databases/mysqlwsrep57-server/boost_1_59_0/libs/accumulators/test/ |
H A D | tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., covariate1 = cov2); in test_stat() 62 acc2( 50., covariate1 = cov2); in test_stat() 68 acc3( 50., covariate1 = cov2); in test_stat() 74 acc4( 50., covariate1 = cov2); in test_stat()
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/dports/devel/hyperscan/boost_1_75_0/libs/accumulators/test/ |
H A D | tail_variate_means.cpp | 43 variate_set_type cov1, cov2, cov3, cov4, cov5; in test_stat() local 50 cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type)); in test_stat() 56 acc1( 50., covariate1 = cov2); in test_stat() 62 acc2( 50., covariate1 = cov2); in test_stat() 68 acc3( 50., covariate1 = cov2); in test_stat() 74 acc4( 50., covariate1 = cov2); in test_stat()
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