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Type 'q()' to quit R. > # 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/tests.html > # * https://testthat.r-lib.org/reference/test_package.html#special-files > > library(testthat) > library(bennu) > > test_check("bennu") Loading required package: StanHeaders rstan version 2.32.7 (Stan version 2.32.2) For execution on a local, multicore CPU with excess RAM we recommend calling options(mc.cores = parallel::detectCores()). To avoid recompilation of unchanged Stan programs, we recommend calling rstan_options(auto_write = TRUE) For within-chain threading using `reduce_sum()` or `map_rect()` Stan functions, change `threads_per_chain` option: rstan_options(threads_per_chain = 1) Do not specify '-march=native' in 'LOCAL_CPPFLAGS' or a Makevars file starting worker pid=175884 on localhost:11675 at 19:45:29.011 starting worker pid=56776 on localhost:11675 at 19:45:29.270 SAMPLING FOR MODEL 'distribution_covariate_model' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000187 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1.87 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: WARNING: There aren't enough warmup iterations to fit the Chain 1: three stages of adaptation as currently configured. Chain 1: Reducing each adaptation stage to 15%/75%/10% of Chain 1: the given number of warmup iterations: Chain 1: init_buffer = 15 Chain 1: adapt_window = 75 Chain 1: term_buffer = 10 Chain 1: Chain 1: Iteration: 1 / 200 [ 0%] (Warmup) Chain 1: Iteration: 20 / 200 [ 10%] (Warmup) Chain 1: Iteration: 40 / 200 [ 20%] (Warmup) SAMPLING FOR MODEL 'distribution_covariate_model' NOW (CHAIN 2). Chain 2: Chain 2: Gradient evaluation took 6.6e-05 seconds Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.66 seconds. Chain 2: Adjust your expectations accordingly! Chain 2: Chain 2: Chain 2: WARNING: There aren't enough warmup iterations to fit the Chain 2: three stages of adaptation as currently configured. Chain 2: Reducing each adaptation stage to 15%/75%/10% of Chain 2: the given number of warmup iterations: Chain 2: init_buffer = 15 Chain 2: adapt_window = 75 Chain 2: term_buffer = 10 Chain 2: Chain 2: Iteration: 1 / 200 [ 0%] (Warmup) Chain 1: Iteration: 60 / 200 [ 30%] (Warmup) Chain 2: Iteration: 20 / 200 [ 10%] (Warmup) Chain 2: Iteration: 40 / 200 [ 20%] (Warmup) Chain 1: Iteration: 80 / 200 [ 40%] (Warmup) Chain 1: Iteration: 100 / 200 [ 50%] (Warmup) Chain 1: Iteration: 101 / 200 [ 50%] (Sampling) Chain 2: Iteration: 60 / 200 [ 30%] (Warmup) Chain 1: Iteration: 120 / 200 [ 60%] (Sampling) Chain 1: Iteration: 140 / 200 [ 70%] (Sampling) Chain 2: Iteration: 80 / 200 [ 40%] (Warmup) Chain 1: Iteration: 160 / 200 [ 80%] (Sampling) Chain 1: Iteration: 180 / 200 [ 90%] (Sampling) Chain 2: Iteration: 100 / 200 [ 50%] (Warmup) Chain 1: Iteration: 200 / 200 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 0.543 seconds (Warm-up) Chain 1: 0.444 seconds (Sampling) Chain 1: 0.987 seconds (Total) Chain 1: Chain 2: Iteration: 101 / 200 [ 50%] (Sampling) Chain 2: Iteration: 120 / 200 [ 60%] (Sampling) Chain 2: Iteration: 140 / 200 [ 70%] (Sampling) Chain 2: Iteration: 160 / 200 [ 80%] (Sampling) Chain 2: Iteration: 180 / 200 [ 90%] (Sampling) Chain 2: Iteration: 200 / 200 [100%] (Sampling) Chain 2: Chain 2: Elapsed Time: 0.737 seconds (Warm-up) Chain 2: 0.907 seconds (Sampling) Chain 2: 1.644 seconds (Total) Chain 2: starting worker pid=114480 on localhost:11675 at 19:45:35.831 starting worker pid=73072 on localhost:11675 at 19:45:36.111 SAMPLING FOR MODEL 'distribution_covariate_model' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 8.7e-05 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.87 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: WARNING: There aren't enough warmup iterations to fit the Chain 1: three stages of adaptation as currently configured. Chain 1: Reducing each adaptation stage to 15%/75%/10% of Chain 1: the given number of warmup iterations: Chain 1: init_buffer = 15 Chain 1: adapt_window = 75 Chain 1: term_buffer = 10 Chain 1: Chain 1: Iteration: 1 / 200 [ 0%] (Warmup) Chain 1: Iteration: 20 / 200 [ 10%] (Warmup) Chain 1: Iteration: 40 / 200 [ 20%] (Warmup) Chain 1: Iteration: 60 / 200 [ 30%] (Warmup) Chain 1: Iteration: 80 / 200 [ 40%] (Warmup) Chain 1: Iteration: 100 / 200 [ 50%] (Warmup) Chain 1: Iteration: 101 / 200 [ 50%] (Sampling) Chain 1: Iteration: 120 / 200 [ 60%] (Sampling) Chain 1: Iteration: 140 / 200 [ 70%] (Sampling) Chain 1: Iteration: 160 / 200 [ 80%] (Sampling) Chain 1: Iteration: 180 / 200 [ 90%] (Sampling) SAMPLING FOR MODEL 'distribution_covariate_model' NOW (CHAIN 2). Chain 2: Chain 2: Gradient evaluation took 4.9e-05 seconds Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.49 seconds. Chain 2: Adjust your expectations accordingly! Chain 2: Chain 2: Chain 2: WARNING: There aren't enough warmup iterations to fit the Chain 2: three stages of adaptation as currently configured. Chain 2: Reducing each adaptation stage to 15%/75%/10% of Chain 2: the given number of warmup iterations: Chain 2: init_buffer = 15 Chain 2: adapt_window = 75 Chain 2: term_buffer = 10 Chain 2: Chain 2: Iteration: 1 / 200 [ 0%] (Warmup) Chain 1: Iteration: 200 / 200 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 0.166 seconds (Warm-up) Chain 1: 0.142 seconds (Sampling) Chain 1: 0.308 seconds (Total) Chain 1: Chain 2: Iteration: 20 / 200 [ 10%] (Warmup) Chain 2: Iteration: 40 / 200 [ 20%] (Warmup) Chain 2: Iteration: 60 / 200 [ 30%] (Warmup) Chain 2: Iteration: 80 / 200 [ 40%] (Warmup) Chain 2: Iteration: 100 / 200 [ 50%] (Warmup) Chain 2: Iteration: 101 / 200 [ 50%] (Sampling) Chain 2: Iteration: 120 / 200 [ 60%] (Sampling) Chain 2: Iteration: 140 / 200 [ 70%] (Sampling) Chain 2: Iteration: 160 / 200 [ 80%] (Sampling) Chain 2: Iteration: 180 / 200 [ 90%] (Sampling) Chain 2: Iteration: 200 / 200 [100%] (Sampling) Chain 2: Chain 2: Elapsed Time: 0.384 seconds (Warm-up) Chain 2: 0.256 seconds (Sampling) Chain 2: 0.64 seconds (Total) Chain 2: SAMPLING FOR MODEL 'distribution_covariate_model' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 5.7e-05 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.57 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: WARNING: No variance estimation is Chain 1: performed for num_warmup < 20 Chain 1: Chain 1: Iteration: 1 / 1 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 0 seconds (Warm-up) Chain 1: 0 seconds (Sampling) Chain 1: 0 seconds (Total) Chain 1: SAMPLING FOR MODEL 'distribution_covariate_model' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 4.1e-05 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.41 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: WARNING: No variance estimation is Chain 1: performed for num_warmup < 20 Chain 1: Chain 1: Iteration: 1 / 1 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 0 seconds (Warm-up) Chain 1: 0 seconds (Sampling) Chain 1: 0 seconds (Total) Chain 1: Joining with `by = join_by(regions)` Joining with `by = join_by(regions)` Joining with `by = join_by(regions)` Joining with `by = join_by(regions)` Joining with `by = join_by(regions)` Joining with `by = join_by(regions, times)` Joining with `by = join_by(regions, times)` Joining with `by = join_by(regions, times)` Joining with `by = join_by(regions, times)` Joining with `by = join_by(regions, times)` Joining with `by = join_by(regions)` Joining with `by = join_by(regions)` Joining with `by = join_by(regions)` Joining with `by = join_by(regions)` Joining with `by = join_by(regions)` Joining with `by = join_by(regions)` Joining with `by = join_by(regions)` Joining with `by = join_by(regions)` Joining with `by = join_by(regions)` Joining with `by = join_by(regions)` Attaching package: 'dplyr' The following object is masked from 'package:testthat': matches The following objects are masked from 'package:stats': filter, lag The following objects are masked from 'package:base': intersect, setdiff, setequal, union [ FAIL 0 | WARN 9 | SKIP 0 | PASS 21 ] [ FAIL 0 | WARN 9 | SKIP 0 | PASS 21 ] There were 13 warnings (use warnings() to see them) > > proc.time() user system elapsed 16.53 1.39 27.48