Running ‘testthat.R’ [52s/81s]
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 4.9e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.49 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.27669 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 9.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.92 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 1.44193 seconds (Warm-up)
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                 2.63556 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 4.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.42 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.0354 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.4 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.035678 seconds (Warm-up)
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                 0.071149 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 6.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.65 seconds.
  Adjust your expectations accordingly!
  
  
  Begin eta adaptation.
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  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 5.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.58 seconds.
  Adjust your expectations accordingly!
  
  
  Begin eta adaptation.
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  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 0.000152 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.52 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.533058 seconds (Warm-up)
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                 1.10446 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.7 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.530599 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 7.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.72 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.54521 seconds (Warm-up)
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                 1.10741 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 7.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.72 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.501872 seconds (Warm-up)
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  ── 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 4.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.42 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.089769 seconds (Warm-up)
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                 0.188663 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 2).
  
  Gradient evaluation took 1.9e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.19 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.089538 seconds (Warm-up)
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                 0.195304 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' 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!
  
  
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   Elapsed Time: 0.086586 seconds (Warm-up)
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                 0.17186 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 4).
  
  Gradient evaluation took 2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.2 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.082613 seconds (Warm-up)
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  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!
  
  
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   Elapsed Time: 0.064782 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 1.9e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.19 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.062979 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 1.6e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.16 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.059589 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 1.7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.17 seconds.
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   Elapsed Time: 0.072553 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 7.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.73 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.202297 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 2.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.28 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.210668 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 2.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.28 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.207095 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 2.7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.27 seconds.
  Adjust your expectations accordingly!
  
  
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 0.00011 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.1 seconds.
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 9.5e-05 seconds
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 6e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.6 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
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           Reducing each adaptation stage to 15%/75%/10% of
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 2.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.23 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
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  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
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  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
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 7.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.75 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
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  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
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 3.4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.34 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:
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  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
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             term_buffer = 5
  
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 6.7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.67 seconds.
  Adjust your expectations accordingly!
  
  
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 2.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.28 seconds.
  Adjust your expectations accordingly!
  
  
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 2.7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.27 seconds.
  Adjust your expectations accordingly!
  
  
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 2.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.28 seconds.
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  .0%
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  .100%
  1
  ══ testthat results  ═══════════════════════════════════════════════════════════
  OK: 136 SKIPPED: 0 FAILED: 1
  1. Error: If it works. (@test-get_contrasts.stanreg.R#10) 
  
  Error: testthat unit tests failed
  Execution halted