Running ‘testthat.R’ [25s/34s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > # This file is part of the standard setup for testthat.
  > # It is recommended that you do not modify it.
  > #
  > # Where should you do additional test configuration?
  > # Learn more about the roles of various files in:
  > # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
  > # * https://testthat.r-lib.org/articles/special-files.html
  > 
  > library(testthat)
  > library(ccar3)
  > 
  > test_check("ccar3")
  
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   Permutation  20  out of  50  123456789
   Permutation  21  out of  50  123456789
   Permutation  22  out of  50  123456789
   Permutation  23  out of  50  123456789
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   Permutation  50  out of  50  123456789
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0479 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0479 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0714 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0714 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0714 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0479 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0374 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0479 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 1 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029 
  
  Estimating optimal shrinkage intensity lambda.var (variance vector): 0.8132 
  
  Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1408 
  
  Saving _problems/test-cca_group_rrr-79.R
  [1] "Done ADMM"
  [1] "Done CVXR"
  [1] "We have:"
  [1] 100   1   5
  [1] "--------------------------------------"
  [1] "Generating data ..."
  [1] "Number of non zeros is: 5"
  [1] "Data generated."
  [1] "--------------------------------------"
  eps = 1e-04  maxiter = 500 
  
  iter: 50  r: 8.41e-15  s: 0.0386
  iter: 100  r: 8.12e-15  s: 0.0131
  iter: 150  r: 8.55e-15  s: 0.00634
  iter: 200  r: 8.43e-15  s: 0.00357
  iter: 250  r: 8.62e-15  s: 0.00221
  iter: 300  r: 8.77e-15  s: 0.00145
  iter: 350  r: 8.94e-15  s: 0.000977
  iter: 400  r: 8.72e-15  s: 0.000672
  iter: 450  r: 8.5e-15  s: 0.000466
  iter: 500  r: 9.08e-15  s: 0.000324
  ADMM did not converge (hit maxiter).
  [1] "We have:"
  [1] 100   1   5
  [1] "--------------------------------------"
  [1] "Generating data ..."
  [1] "Number of non zeros is: 5"
  [1] "Data generated."
  [1] "--------------------------------------"
  eps = 1e-04  maxiter = 500 
  
  ADMM converged.
  [1] "We have:"
  [1] 100   1   5
  [1] "--------------------------------------"
  [1] "Generating data ..."
  [1] "Number of non zeros is: 5"
  [1] "Data generated."
  [1] "--------------------------------------"
  
  Starting lambda 1/7: 0.5
   lambda 1/7 = 0.5
  Finished lambda 1/7 in 0.0s
  Starting lambda 2/7: 0.1
   lambda 2/7 = 0.1
  Finished lambda 2/7 in 0.0s
  Starting lambda 3/7: 0.075
   lambda 3/7 = 0.075
  Finished lambda 3/7 in 0.0s
  Starting lambda 4/7: 0.05
   lambda 4/7 = 0.05
  Finished lambda 4/7 in 0.0s
  Starting lambda 5/7: 0.01
   lambda 5/7 = 0.01
  Finished lambda 5/7 in 0.0s
  Starting lambda 6/7: 0.001
   lambda 6/7 = 0.001
  Finished lambda 6/7 in 0.0s
  Starting lambda 7/7: 0.0001
   lambda 7/7 = 0.0001
  Finished lambda 7/7 in 0.0s
  Starting lambda 1/7: 0.5
   lambda 1/7 = 0.5
  Finished lambda 1/7 in 0.0s
  Starting lambda 2/7: 0.1
   lambda 2/7 = 0.1
  Finished lambda 2/7 in 0.0s
  Starting lambda 3/7: 0.075
   lambda 3/7 = 0.075
  Finished lambda 3/7 in 0.0s
  Starting lambda 4/7: 0.05
   lambda 4/7 = 0.05
  Finished lambda 4/7 in 0.0s
  Starting lambda 5/7: 0.01
   lambda 5/7 = 0.01
  Finished lambda 5/7 in 0.0s
  Starting lambda 6/7: 0.001
   lambda 6/7 = 0.001
  Finished lambda 6/7 in 0.0s
  Starting lambda 7/7: 0.0001
   lambda 7/7 = 0.0001
  Finished lambda 7/7 in 0.0s
  Starting lambda 1/7: 0.5
   lambda 1/7 = 0.5
  Finished lambda 1/7 in 0.0s
  Starting lambda 2/7: 0.1
   lambda 2/7 = 0.1
  Finished lambda 2/7 in 0.0s
  Starting lambda 3/7: 0.075
   lambda 3/7 = 0.075
  Finished lambda 3/7 in 0.0s
  Starting lambda 4/7: 0.05
   lambda 4/7 = 0.05
  Finished lambda 4/7 in 0.0s
  Starting lambda 5/7: 0.01
   lambda 5/7 = 0.01
  Finished lambda 5/7 in 0.0s
  Starting lambda 6/7: 0.001
   lambda 6/7 = 0.001
  Finished lambda 6/7 in 0.0s
  Starting lambda 7/7: 0.0001
   lambda 7/7 = 0.0001
  Finished lambda 7/7 in 0.0s
  Starting lambda 1/7: 0.5
   lambda 1/7 = 0.5
  Finished lambda 1/7 in 0.0s
  Starting lambda 2/7: 0.1
   lambda 2/7 = 0.1
  Finished lambda 2/7 in 0.0s
  Starting lambda 3/7: 0.075
   lambda 3/7 = 0.075
  Finished lambda 3/7 in 0.0s
  Starting lambda 4/7: 0.05
   lambda 4/7 = 0.05
  Finished lambda 4/7 in 0.0s
  Starting lambda 5/7: 0.01
   lambda 5/7 = 0.01
  Finished lambda 5/7 in 0.0s
  Starting lambda 6/7: 0.001
   lambda 6/7 = 0.001
  Finished lambda 6/7 in 0.0s
  Starting lambda 7/7: 0.0001
   lambda 7/7 = 0.0001
  Finished lambda 7/7 in 0.0s
  Starting lambda 1/7: 0.5
   lambda 1/7 = 0.5
  Finished lambda 1/7 in 0.0s
  Starting lambda 2/7: 0.1
   lambda 2/7 = 0.1
  Finished lambda 2/7 in 0.0s
  Starting lambda 3/7: 0.075
   lambda 3/7 = 0.075
  Finished lambda 3/7 in 0.0s
  Starting lambda 4/7: 0.05
   lambda 4/7 = 0.05
  Finished lambda 4/7 in 0.0s
  Starting lambda 5/7: 0.01
   lambda 5/7 = 0.01
  Finished lambda 5/7 in 0.0s
  Starting lambda 6/7: 0.001
   lambda 6/7 = 0.001
  Finished lambda 6/7 in 0.0s
  Starting lambda 7/7: 0.0001
   lambda 7/7 = 0.0001
  Finished lambda 7/7 in 0.0s
  Refitting at selected lambda with ADMM logs...
  
  Starting lambda 1/1: 0.05
   lambda 1/1 = 0.05
     iter 1  r=0.938376  s=0.402581
     iter 2  r=0.386388  s=0.351783
     iter 3  r=0.174349  s=0.213626
     iter 4  r=0.0894817  s=0.118771
     iter 5  r=0.0499279  s=0.0651281
     iter 6  r=0.0292555  s=0.0362484
     iter 7  r=0.017375  s=0.0211264
     iter 8  r=0.0105751  s=0.0128797
     iter 9  r=0.00652473  s=0.0081953
     iter 10  r=0.00407171  s=0.00544353
     iter 11  r=0.00257974  s=0.00371766
     iter 12  r=0.00165766  s=0.0025963
     iter 13  r=0.00107901  s=0.00184187
  Finished lambda 1/1 in 0.0s
  Final ADMM refit completed.
  [1] "We have:"
  [1] 100   1   5
  [1] "--------------------------------------"
  [1] "Generating data ..."
  [1] "Number of non zeros is: 5"
  [1] "Data generated."
  [1] "--------------------------------------"
  
  Refitting at selected lambda with ADMM logs...
  
  Starting lambda 1/1: 0.05
   lambda 1/1 = 0.05
     iter 1  r=0.938376  s=0.402581
     iter 2  r=0.386388  s=0.351783
     iter 3  r=0.174349  s=0.213626
     iter 4  r=0.0894817  s=0.118771
     iter 5  r=0.0499279  s=0.0651281
     iter 6  r=0.0292555  s=0.0362484
     iter 7  r=0.017375  s=0.0211264
     iter 8  r=0.0105751  s=0.0128797
     iter 9  r=0.00652473  s=0.0081953
     iter 10  r=0.00407171  s=0.00544353
     iter 11  r=0.00257974  s=0.00371766
     iter 12  r=0.00165766  s=0.0025963
     iter 13  r=0.00107901  s=0.00184187
  Finished lambda 1/1 in 0.0s
  Final ADMM refit completed.
  [ FAIL 1 | WARN 1 | SKIP 0 | PASS 154 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-cca_group_rrr.R:76:3'): cca_group computes the same solutions across solvers ──
  Error in `Rmosek::mosek(prob, opts)`: Unknown exported object to be built. Please use 'Rmosek::mosek_attachbuilder' to complete the installation of Rmosek.
  Backtrace:
       ▆
    1. └─ccar3::cca_group_rrr(...) at test-cca_group_rrr.R:76:3
    2.   └─ccar3:::solve_group_rrr_cvxr(X, tilde_Y, groups, lambda, thresh_0 = thresh_0)
    3.     └─CVXR (local) cvxr_psolve(prob)
    4.       └─CVXR::solve_via_data(...)
    5.         ├─S7::S7_dispatch()
    6.         └─CVXR (local) `method(solve_via_data, CVXR::SolvingChain)`(...)
    7.           └─CVXR::solve_via_data(...)
    8.             ├─S7::S7_dispatch()
    9.             └─CVXR (local) `method(solve_via_data, CVXR::Mosek_Solver)`(...)
   10.               └─Rmosek::mosek(prob, opts)
  
  [ FAIL 1 | WARN 1 | SKIP 0 | PASS 154 ]
  Error:
  ! Test failures.
  Execution halted