Running ‘testthat.R’ [60s/60s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(psycho)
  > 
  > test_check("psycho")
  Failed with error:  'there is no package called 'GPArotation''
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 1).
  Rejecting initial value:
    Log probability evaluates to log(0), i.e. negative infinity.
    Stan can't start sampling from this initial value.
  Rejecting initial value:
    Log probability evaluates to log(0), i.e. negative infinity.
    Stan can't start sampling from this initial value.
  
  Gradient evaluation took 0.000175 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.75 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:   1 / 1000 [  0%]  (Warmup)
  Iteration: 100 / 1000 [ 10%]  (Warmup)
  Iteration: 200 / 1000 [ 20%]  (Warmup)
  Iteration: 300 / 1000 [ 30%]  (Warmup)
  Iteration: 400 / 1000 [ 40%]  (Warmup)
  Iteration: 500 / 1000 [ 50%]  (Warmup)
  Iteration: 501 / 1000 [ 50%]  (Sampling)
  Iteration: 600 / 1000 [ 60%]  (Sampling)
  Iteration: 700 / 1000 [ 70%]  (Sampling)
  Iteration: 800 / 1000 [ 80%]  (Sampling)
  Iteration: 900 / 1000 [ 90%]  (Sampling)
  Iteration: 1000 / 1000 [100%]  (Sampling)
  
   Elapsed Time: 0.34989 seconds (Warm-up)
                 0.261425 seconds (Sampling)
                 0.611315 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 0.0001 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:   1 / 1000 [  0%]  (Warmup)
  Iteration: 100 / 1000 [ 10%]  (Warmup)
  Iteration: 200 / 1000 [ 20%]  (Warmup)
  Iteration: 300 / 1000 [ 30%]  (Warmup)
  Iteration: 400 / 1000 [ 40%]  (Warmup)
  Iteration: 500 / 1000 [ 50%]  (Warmup)
  Iteration: 501 / 1000 [ 50%]  (Sampling)
  Iteration: 600 / 1000 [ 60%]  (Sampling)
  Iteration: 700 / 1000 [ 70%]  (Sampling)
  Iteration: 800 / 1000 [ 80%]  (Sampling)
  Iteration: 900 / 1000 [ 90%]  (Sampling)
  Iteration: 1000 / 1000 [100%]  (Sampling)
  
   Elapsed Time: 2.14321 seconds (Warm-up)
                 1.63318 seconds (Sampling)
                 3.77639 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 4.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.43 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:   1 / 1000 [  0%]  (Warmup)
  Iteration: 100 / 1000 [ 10%]  (Warmup)
  Iteration: 200 / 1000 [ 20%]  (Warmup)
  Iteration: 300 / 1000 [ 30%]  (Warmup)
  Iteration: 400 / 1000 [ 40%]  (Warmup)
  Iteration: 500 / 1000 [ 50%]  (Warmup)
  Iteration: 501 / 1000 [ 50%]  (Sampling)
  Iteration: 600 / 1000 [ 60%]  (Sampling)
  Iteration: 700 / 1000 [ 70%]  (Sampling)
  Iteration: 800 / 1000 [ 80%]  (Sampling)
  Iteration: 900 / 1000 [ 90%]  (Sampling)
  Iteration: 1000 / 1000 [100%]  (Sampling)
  
   Elapsed Time: 0.034693 seconds (Warm-up)
                 0.03505 seconds (Sampling)
                 0.069743 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 4.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.48 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:   1 / 1000 [  0%]  (Warmup)
  Iteration: 100 / 1000 [ 10%]  (Warmup)
  Iteration: 200 / 1000 [ 20%]  (Warmup)
  Iteration: 300 / 1000 [ 30%]  (Warmup)
  Iteration: 400 / 1000 [ 40%]  (Warmup)
  Iteration: 500 / 1000 [ 50%]  (Warmup)
  Iteration: 501 / 1000 [ 50%]  (Sampling)
  Iteration: 600 / 1000 [ 60%]  (Sampling)
  Iteration: 700 / 1000 [ 70%]  (Sampling)
  Iteration: 800 / 1000 [ 80%]  (Sampling)
  Iteration: 900 / 1000 [ 90%]  (Sampling)
  Iteration: 1000 / 1000 [100%]  (Sampling)
  
   Elapsed Time: 0.062355 seconds (Warm-up)
                 0.061377 seconds (Sampling)
                 0.123732 seconds (Total)
  
  ------------------------------------------------------------
  EXPERIMENTAL ALGORITHM:
    This procedure has not been thoroughly tested and may be unstable
    or buggy. The interface is subject to change.
  ------------------------------------------------------------
  
  
  
  Gradient evaluation took 4.4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.44 seconds.
  Adjust your expectations accordingly!
  
  
  Begin eta adaptation.
  Iteration:   1 / 250 [  0%]  (Adaptation)
  Iteration:  50 / 250 [ 20%]  (Adaptation)
  Iteration: 100 / 250 [ 40%]  (Adaptation)
  Iteration: 150 / 250 [ 60%]  (Adaptation)
  Iteration: 200 / 250 [ 80%]  (Adaptation)
  Success! Found best value [eta = 1] earlier than expected.
  
  Begin stochastic gradient ascent.
    iter       ELBO   delta_ELBO_mean   delta_ELBO_med   notes 
     100     -4e+02             1.000            1.000
     200     -2e+02             1.011            1.021
     300     -2e+02             0.682            1.000
     400     -2e+02             0.511            1.000
     500     -2e+02             0.409            0.024
     600     -2e+02             0.341            0.024
     700     -2e+02             0.293            0.002   MEDIAN ELBO CONVERGED
  
  Drawing a sample of size 1000 from the approximate posterior... 
  COMPLETED.
  ------------------------------------------------------------
  EXPERIMENTAL ALGORITHM:
    This procedure has not been thoroughly tested and may be unstable
    or buggy. The interface is subject to change.
  ------------------------------------------------------------
  
  
  
  Gradient evaluation took 5.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.53 seconds.
  Adjust your expectations accordingly!
  
  
  Begin eta adaptation.
  Iteration:   1 / 250 [  0%]  (Adaptation)
  Iteration:  50 / 250 [ 20%]  (Adaptation)
  Iteration: 100 / 250 [ 40%]  (Adaptation)
  Iteration: 150 / 250 [ 60%]  (Adaptation)
  Iteration: 200 / 250 [ 80%]  (Adaptation)
  Success! Found best value [eta = 1] earlier than expected.
  
  Begin stochastic gradient ascent.
    iter       ELBO   delta_ELBO_mean   delta_ELBO_med   notes 
     100     -9e+04             1.000            1.000
     200     -6e+02            79.074          157.147
     300     -5e+02            52.759            1.000
     400     -2e+02            39.982            1.651
     500     -2e+02            31.989            1.000
     600     -2e+02            26.660            1.000
     700     -2e+02            22.854            0.130
     800     -2e+02            19.999            0.130
     900     -2e+02            17.778            0.018
    1000     -2e+02            16.000            0.018
    1100     -2e+02            15.902            0.016   MAY BE DIVERGING... INSPECT ELBO
    1200     -2e+02             0.188            0.014
    1300     -2e+02             0.176            0.014
    1400     -2e+02             0.011            0.014
    1500     -2e+02             0.010            0.013   MEAN ELBO CONVERGED
  
  Drawing a sample of size 1000 from the approximate posterior... 
  COMPLETED.
  Initial log joint probability = -100816
  Optimization terminated normally: 
    Convergence detected: relative gradient magnitude is below tolerance
  The Crawford-Howell (1998) t-test suggests no dissociation between test X and test Y (t(5) = 2.10, p = 0.09<b0>). The patient's score on test X is not significantly altered compared to its score on test Y.
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 0.000196 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.96 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.695949 seconds (Warm-up)
                 0.758674 seconds (Sampling)
                 1.45462 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 0.000143 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.43 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.70552 seconds (Warm-up)
                 0.691302 seconds (Sampling)
                 1.39682 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 9.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.95 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.654731 seconds (Warm-up)
                 0.619775 seconds (Sampling)
                 1.27451 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 6.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.65 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.649614 seconds (Warm-up)
                 0.537403 seconds (Sampling)
                 1.18702 seconds (Total)
  
  ── 1. Error: If it works. (@test-get_contrasts.stanreg.R#10)  ──────────────────
  number of items to replace is not a multiple of replacement length
  1: psycho::get_contrasts(fit, "Salary") at testthat/test-get_contrasts.stanreg.R:10
  2: get_contrasts.stanreg(fit, "Salary")
  3: fit %>% emmeans::emmeans(formula) %>% coda::as.mcmc() %>% as.matrix() %>% coda::as.mcmc() %>% 
         as.data.frame()
  4: withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
  5: eval(quote(`_fseq`(`_lhs`)), env, env)
  6: eval(quote(`_fseq`(`_lhs`)), env, env)
  7: `_fseq`(`_lhs`)
  8: freduce(value, `_function_list`)
  9: function_list[[i]](value)
  10: as.matrix(.)
  11: as.matrix.mcmc(.)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 1).
  
  Gradient evaluation took 5.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.53 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.139009 seconds (Warm-up)
                 0.15002 seconds (Sampling)
                 0.289029 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 2).
  
  Gradient evaluation took 4.4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.44 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.140456 seconds (Warm-up)
                 0.167522 seconds (Sampling)
                 0.307978 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 3).
  
  Gradient evaluation took 3.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.32 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.136296 seconds (Warm-up)
                 0.135706 seconds (Sampling)
                 0.272002 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 4).
  
  Gradient evaluation took 2.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.28 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.130546 seconds (Warm-up)
                 0.130512 seconds (Sampling)
                 0.261058 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 4.4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.44 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.11053 seconds (Warm-up)
                 0.09566 seconds (Sampling)
                 0.20619 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 2.4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.24 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.115109 seconds (Warm-up)
                 0.109423 seconds (Sampling)
                 0.224532 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.2 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.114184 seconds (Warm-up)
                 0.109687 seconds (Sampling)
                 0.223871 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 4.1e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.41 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.128611 seconds (Warm-up)
                 0.105908 seconds (Sampling)
                 0.234519 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 7.1e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.71 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.309422 seconds (Warm-up)
                 0.29503 seconds (Sampling)
                 0.604452 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 3.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.38 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.32923 seconds (Warm-up)
                 0.321172 seconds (Sampling)
                 0.650402 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 4.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.45 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.239804 seconds (Warm-up)
                 0.214089 seconds (Sampling)
                 0.453893 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 6.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.65 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.275708 seconds (Warm-up)
                 0.286725 seconds (Sampling)
                 0.562433 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 0.000129 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.29 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.709462 seconds (Warm-up)
                 0.682941 seconds (Sampling)
                 1.3924 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 9.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.92 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.76142 seconds (Warm-up)
                 1.04279 seconds (Sampling)
                 1.80421 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 0.000125 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.25 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.952822 seconds (Warm-up)
                 0.949248 seconds (Sampling)
                 1.90207 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 9e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.9 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.796199 seconds (Warm-up)
                 0.840207 seconds (Sampling)
                 1.63641 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 5.7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.57 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
           three stages of adaptation as currently configured.
           Reducing each adaptation stage to 15%/75%/10% of
           the given number of warmup iterations:
             init_buffer = 7
             adapt_window = 38
             term_buffer = 5
  
  Iteration:  1 / 100 [  1%]  (Warmup)
  Iteration: 10 / 100 [ 10%]  (Warmup)
  Iteration: 20 / 100 [ 20%]  (Warmup)
  Iteration: 30 / 100 [ 30%]  (Warmup)
  Iteration: 40 / 100 [ 40%]  (Warmup)
  Iteration: 50 / 100 [ 50%]  (Warmup)
  Iteration: 51 / 100 [ 51%]  (Sampling)
  Iteration: 60 / 100 [ 60%]  (Sampling)
  Iteration: 70 / 100 [ 70%]  (Sampling)
  Iteration: 80 / 100 [ 80%]  (Sampling)
  Iteration: 90 / 100 [ 90%]  (Sampling)
  Iteration: 100 / 100 [100%]  (Sampling)
  
   Elapsed Time: 0.010495 seconds (Warm-up)
                 0.011909 seconds (Sampling)
                 0.022404 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 4.6e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.46 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
           three stages of adaptation as currently configured.
           Reducing each adaptation stage to 15%/75%/10% of
           the given number of warmup iterations:
             init_buffer = 7
             adapt_window = 38
             term_buffer = 5
  
  Iteration:  1 / 100 [  1%]  (Warmup)
  Iteration: 10 / 100 [ 10%]  (Warmup)
  Iteration: 20 / 100 [ 20%]  (Warmup)
  Iteration: 30 / 100 [ 30%]  (Warmup)
  Iteration: 40 / 100 [ 40%]  (Warmup)
  Iteration: 50 / 100 [ 50%]  (Warmup)
  Iteration: 51 / 100 [ 51%]  (Sampling)
  Iteration: 60 / 100 [ 60%]  (Sampling)
  Iteration: 70 / 100 [ 70%]  (Sampling)
  Iteration: 80 / 100 [ 80%]  (Sampling)
  Iteration: 90 / 100 [ 90%]  (Sampling)
  Iteration: 100 / 100 [100%]  (Sampling)
  
   Elapsed Time: 0.008485 seconds (Warm-up)
                 0.011054 seconds (Sampling)
                 0.019539 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 3.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.38 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
           three stages of adaptation as currently configured.
           Reducing each adaptation stage to 15%/75%/10% of
           the given number of warmup iterations:
             init_buffer = 7
             adapt_window = 38
             term_buffer = 5
  
  Iteration:  1 / 100 [  1%]  (Warmup)
  Iteration: 10 / 100 [ 10%]  (Warmup)
  Iteration: 20 / 100 [ 20%]  (Warmup)
  Iteration: 30 / 100 [ 30%]  (Warmup)
  Iteration: 40 / 100 [ 40%]  (Warmup)
  Iteration: 50 / 100 [ 50%]  (Warmup)
  Iteration: 51 / 100 [ 51%]  (Sampling)
  Iteration: 60 / 100 [ 60%]  (Sampling)
  Iteration: 70 / 100 [ 70%]  (Sampling)
  Iteration: 80 / 100 [ 80%]  (Sampling)
  Iteration: 90 / 100 [ 90%]  (Sampling)
  Iteration: 100 / 100 [100%]  (Sampling)
  
   Elapsed Time: 0.008809 seconds (Warm-up)
                 0.008417 seconds (Sampling)
                 0.017226 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 2.4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.24 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
           three stages of adaptation as currently configured.
           Reducing each adaptation stage to 15%/75%/10% of
           the given number of warmup iterations:
             init_buffer = 7
             adapt_window = 38
             term_buffer = 5
  
  Iteration:  1 / 100 [  1%]  (Warmup)
  Iteration: 10 / 100 [ 10%]  (Warmup)
  Iteration: 20 / 100 [ 20%]  (Warmup)
  Iteration: 30 / 100 [ 30%]  (Warmup)
  Iteration: 40 / 100 [ 40%]  (Warmup)
  Iteration: 50 / 100 [ 50%]  (Warmup)
  Iteration: 51 / 100 [ 51%]  (Sampling)
  Iteration: 60 / 100 [ 60%]  (Sampling)
  Iteration: 70 / 100 [ 70%]  (Sampling)
  Iteration: 80 / 100 [ 80%]  (Sampling)
  Iteration: 90 / 100 [ 90%]  (Sampling)
  Iteration: 100 / 100 [100%]  (Sampling)
  
   Elapsed Time: 0.006363 seconds (Warm-up)
                 0.007971 seconds (Sampling)
                 0.014334 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 6.9e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.69 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
           three stages of adaptation as currently configured.
           Reducing each adaptation stage to 15%/75%/10% of
           the given number of warmup iterations:
             init_buffer = 7
             adapt_window = 38
             term_buffer = 5
  
  Iteration:  1 / 100 [  1%]  (Warmup)
  Iteration: 10 / 100 [ 10%]  (Warmup)
  Iteration: 20 / 100 [ 20%]  (Warmup)
  Iteration: 30 / 100 [ 30%]  (Warmup)
  Iteration: 40 / 100 [ 40%]  (Warmup)
  Iteration: 50 / 100 [ 50%]  (Warmup)
  Iteration: 51 / 100 [ 51%]  (Sampling)
  Iteration: 60 / 100 [ 60%]  (Sampling)
  Iteration: 70 / 100 [ 70%]  (Sampling)
  Iteration: 80 / 100 [ 80%]  (Sampling)
  Iteration: 90 / 100 [ 90%]  (Sampling)
  Iteration: 100 / 100 [100%]  (Sampling)
  
   Elapsed Time: 0.150948 seconds (Warm-up)
                 0.180009 seconds (Sampling)
                 0.330957 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 5.6e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.56 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
           three stages of adaptation as currently configured.
           Reducing each adaptation stage to 15%/75%/10% of
           the given number of warmup iterations:
             init_buffer = 7
             adapt_window = 38
             term_buffer = 5
  
  Iteration:  1 / 100 [  1%]  (Warmup)
  Iteration: 10 / 100 [ 10%]  (Warmup)
  Iteration: 20 / 100 [ 20%]  (Warmup)
  Iteration: 30 / 100 [ 30%]  (Warmup)
  Iteration: 40 / 100 [ 40%]  (Warmup)
  Iteration: 50 / 100 [ 50%]  (Warmup)
  Iteration: 51 / 100 [ 51%]  (Sampling)
  Iteration: 60 / 100 [ 60%]  (Sampling)
  Iteration: 70 / 100 [ 70%]  (Sampling)
  Iteration: 80 / 100 [ 80%]  (Sampling)
  Iteration: 90 / 100 [ 90%]  (Sampling)
  Iteration: 100 / 100 [100%]  (Sampling)
  
   Elapsed Time: 0.136625 seconds (Warm-up)
                 0.301463 seconds (Sampling)
                 0.438088 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 4.6e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.46 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
           three stages of adaptation as currently configured.
           Reducing each adaptation stage to 15%/75%/10% of
           the given number of warmup iterations:
             init_buffer = 7
             adapt_window = 38
             term_buffer = 5
  
  Iteration:  1 / 100 [  1%]  (Warmup)
  Iteration: 10 / 100 [ 10%]  (Warmup)
  Iteration: 20 / 100 [ 20%]  (Warmup)
  Iteration: 30 / 100 [ 30%]  (Warmup)
  Iteration: 40 / 100 [ 40%]  (Warmup)
  Iteration: 50 / 100 [ 50%]  (Warmup)
  Iteration: 51 / 100 [ 51%]  (Sampling)
  Iteration: 60 / 100 [ 60%]  (Sampling)
  Iteration: 70 / 100 [ 70%]  (Sampling)
  Iteration: 80 / 100 [ 80%]  (Sampling)
  Iteration: 90 / 100 [ 90%]  (Sampling)
  Iteration: 100 / 100 [100%]  (Sampling)
  
   Elapsed Time: 0.314044 seconds (Warm-up)
                 0.332838 seconds (Sampling)
                 0.646882 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 3.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.32 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
           three stages of adaptation as currently configured.
           Reducing each adaptation stage to 15%/75%/10% of
           the given number of warmup iterations:
             init_buffer = 7
             adapt_window = 38
             term_buffer = 5
  
  Iteration:  1 / 100 [  1%]  (Warmup)
  Iteration: 10 / 100 [ 10%]  (Warmup)
  Iteration: 20 / 100 [ 20%]  (Warmup)
  Iteration: 30 / 100 [ 30%]  (Warmup)
  Iteration: 40 / 100 [ 40%]  (Warmup)
  Iteration: 50 / 100 [ 50%]  (Warmup)
  Iteration: 51 / 100 [ 51%]  (Sampling)
  Iteration: 60 / 100 [ 60%]  (Sampling)
  Iteration: 70 / 100 [ 70%]  (Sampling)
  Iteration: 80 / 100 [ 80%]  (Sampling)
  Iteration: 90 / 100 [ 90%]  (Sampling)
  Iteration: 100 / 100 [100%]  (Sampling)
  
   Elapsed Time: 0.435375 seconds (Warm-up)
                 0.454678 seconds (Sampling)
                 0.890053 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.7 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.2146 seconds (Warm-up)
                 0.197113 seconds (Sampling)
                 0.411713 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 3.7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.37 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.210516 seconds (Warm-up)
                 0.203678 seconds (Sampling)
                 0.414194 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 3.1e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.31 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.160073 seconds (Warm-up)
                 0.130802 seconds (Sampling)
                 0.290875 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 3.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.35 seconds.
  Adjust your expectations accordingly!
  
  
  Iteration:    1 / 2000 [  0%]  (Warmup)
  Iteration:  200 / 2000 [ 10%]  (Warmup)
  Iteration:  400 / 2000 [ 20%]  (Warmup)
  Iteration:  600 / 2000 [ 30%]  (Warmup)
  Iteration:  800 / 2000 [ 40%]  (Warmup)
  Iteration: 1000 / 2000 [ 50%]  (Warmup)
  Iteration: 1001 / 2000 [ 50%]  (Sampling)
  Iteration: 1200 / 2000 [ 60%]  (Sampling)
  Iteration: 1400 / 2000 [ 70%]  (Sampling)
  Iteration: 1600 / 2000 [ 80%]  (Sampling)
  Iteration: 1800 / 2000 [ 90%]  (Sampling)
  Iteration: 2000 / 2000 [100%]  (Sampling)
  
   Elapsed Time: 0.222545 seconds (Warm-up)
                 0.20496 seconds (Sampling)
                 0.427505 seconds (Total)
  
  .0%
  .33%
  .67%
  .100%
  1
  ══ testthat results  ═══════════════════════════════════════════════════════════
  OK: 138 SKIPPED: 0 FAILED: 1
  1. Error: If it works. (@test-get_contrasts.stanreg.R#10) 
  
  Error: testthat unit tests failed
  Execution halted