test-size.R cannot run under test_package('nimble', 'size')

To reproduce
library(methods)
library(testthat)
library(nimble)
test_file('inst/tests/test-size.R')  # PASSES
test_package('nimble', 'size')  # FAILS

It runs for me on Ubuntu 16.04. Can you provide more details of the failure?

Here is a failing test on travis, and below is a failing test on my Ubuntu 16.04 box on devel branch
library(nimble)
library(testthat)
test_package('nimble', 'size')
..### Testing scalar stochastic, parameter expression  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, parameter expression with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, parameter expression non-scalar, no indices  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
12### Testing scalar stochastic, parameter expression non-scalar, no indices with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, parameter expression non-scalar, RHS index  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
34### Testing scalar stochastic, parameter expression non-scalar, RHS index with RHS constant ###
defining model...
Error in 2[1, 1] : incorrect number of dimensions
In addition: Warning messages:
1: Placing tests in `inst/tests/` is deprecated. Please use `tests/testthat/` instead
2: In replaceConstantsRecurse(x, constEnv, constNames) :
  Code mu1 was given as known but evaluates to a non-scalar.  This is probably not what you want.
3: In replaceConstantsRecurse(x, constEnv, constNames) :
  Code mu2 was given as known but evaluates to a non-scalar.  This is probably not what you want.
4: In code[[2]] == names(dimensionsList) :
  longer object length is not a multiple of shorter object length
5: In replaceConstantsRecurse(x, constEnv, constNames) :
  Code mu1 was given as known but evaluates to a non-scalar.  This is probably not what you want.
6: In replaceConstantsRecurse(x, constEnv, constNames) :
  Code mu2 was given as known but evaluates to a non-scalar.  This is probably not what you want.
.### Testing scalar stochastic, parameter expression non-scalar  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
56### Testing scalar stochastic, parameter expression non-scalar with RHS constant ###
defining model...
Adding mu1,mu2 as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, parameter expression non-scalar, demotion  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, parameter expression non-scalar, demotion with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, non-scalar parameter  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, non-scalar parameter with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, non-scalar parameter, demotion  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
78### Testing scalar stochastic, non-scalar parameter, demotion with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, non-scalar value  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of distribution argument(s) 'value' does not match required dimension(s) for the distribution 'dnorm'. Necessary dimension(s) are 0.
In addition: Warning messages:
1: In code[[2]] == names(dimensionsList) :
  longer object length is not a multiple of shorter object length
2: In code[[2]] == names(dimensionsList) :
  longer object length is not a multiple of shorter object length
3: In code[[2]] == names(dimensionsList) :
  longer object length is not a multiple of shorter object length
4: In model$logProb_y[1] <<- dnorm(model$y[1:2], mean = model$mu[1],  :
  number of items to replace is not a multiple of replacement length
.### Testing scalar stochastic, non-scalar value with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of distribution argument(s) 'value' does not match required dimension(s) for the distribution 'dnorm'. Necessary dimension(s) are 0.
In addition: Warning message:
In model$logProb_y[1] <<- dnorm(model$y[1:2], mean = 1, sd = 1,  :
  number of items to replace is not a multiple of replacement length
.### Testing scalar stochastic, non-scalar value and parameter  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of distribution argument(s) 'value,mean' does not match required dimension(s) for the distribution 'dnorm'. Necessary dimension(s) are 0,0.
In addition: Warning message:
In model$logProb_y[1] <<- dnorm(model$y[1:2], mean = model$mu1[1:2,  :
  number of items to replace is not a multiple of replacement length
.### Testing scalar stochastic, non-scalar value and parameter with RHS constant ###
defining model...
Adding mu1,mu2 as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of distribution argument(s) 'value,mean' does not match required dimension(s) for the distribution 'dnorm'. Necessary dimension(s) are 0,0.
In addition: Warning message:
In model$logProb_y[1] <<- dnorm(model$y[1:2], mean = model$mu1[1:2,  :
  number of items to replace is not a multiple of replacement length
.### Testing scalar stochastic, scalar within multivar variable  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, scalar within multivar variable with RHS constant ###
defining model...
Error in addMissingIndexingRecurse(code[[i]], dimensionsList) :
  inconsistent dimensionality provided for node 'mu'
.### Testing scalar stochastic, scalar within multivar variable 2  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, scalar within multivar variable 2 with RHS constant ###
defining model...
Error in addMissingIndexingRecurse(code[[i]], dimensionsList) :
  inconsistent dimensionality provided for node 'mu'
9### Testing scalar stochastic, scalar within multivar variable 3  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, scalar within multivar variable 3 with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing mv param stochastic, basic  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing mv param stochastic, basic with RHS constant ###
defining model...
Adding p as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing mv param stochastic, no indices  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of 'prob' does not match required dimension for the distribution 'dcat'. Necessary dimension is 1. You may need to include explicit indexing information, e.g., variable_name[1:2].
.### Testing mv param stochastic, no indices with RHS constant ###
defining model...
Error in replaceConstantsRecurse(x, constEnv, constNames) :
  Error, hit end
In addition: Warning message:
In replaceConstantsRecurse(x, constEnv, constNames) :
  Code p was given as known but evaluates to a non-scalar.  This is probably not what you want.
.### Testing mv param stochastic, scalar param  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of distribution argument(s) 'prob' does not match required dimension(s) for the distribution 'dcat'. Necessary dimension(s) are 1. You may need to ensure that you have explicit vectors and not one-row or one-column matrices.
.### Testing mv param stochastic, scalar param with RHS constant ###
defining model...
Error in addMissingIndexingRecurse(code[[i]], dimensionsList) :
  inconsistent dimensionality provided for node 'p'
.### Testing mv param stochastic, scalar param, no indices  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of 'prob' does not match required dimension for the distribution 'dcat'. Necessary dimension is 1. You may need to include explicit indexing information, e.g., variable_name[1:2].
.### Testing mv param stochastic, scalar param, no indices with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of distribution argument(s) 'prob' does not match required dimension(s) for the distribution 'dcat'. Necessary dimension(s) are 1. You may need to ensure that you have explicit vectors and not one-row or one-column matrices.
.### Testing mv param stochastic, parameter expression  with RHS variable ###
defining model...
Error in checkMultivarExpr() :
  Error with parameter 'prob' of distribution 'dcat': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing mv param stochastic, parameter expression with RHS constant ###
defining model...
Error in checkMultivarExpr() :
  Error with parameter 'prob' of distribution 'dcat': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing mv param stochastic, parameter expression, matrices  with RHS variable ###
defining model...
Error in checkMultivarExpr() :
  Error with parameter 'prob' of distribution 'dcat': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing mv param stochastic, parameter expression, matrices with RHS constant ###
defining model...
Error in checkMultivarExpr() :
  Error with parameter 'prob' of distribution 'dcat': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing mv param stochastic, parameter expression, matrices subindexing  with RHS variable ###
defining model...
Error in checkMultivarExpr() :
  Error with parameter 'prob' of distribution 'dcat': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing mv param stochastic, parameter expression, matrices subindexing with RHS constant ###
defining model...
Error in checkMultivarExpr() :
  Error with parameter 'prob' of distribution 'dcat': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing mv param stochastic, non-scalar value  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of distribution argument(s) 'value' does not match required dimension(s) for the distribution 'dcat'. Necessary dimension(s) are 0.
In addition: Warning message:
In model$logProb_y[1] <<- dcat(model$y[1:2], prob = model$p[1:3],  :
  number of items to replace is not a multiple of replacement length
.### Testing mv param stochastic, non-scalar value with RHS constant ###
defining model...
Adding p as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of distribution argument(s) 'value' does not match required dimension(s) for the distribution 'dcat'. Necessary dimension(s) are 0.
In addition: Warning message:
In model$logProb_y[1] <<- dcat(model$y[1:2], prob = model$p[1:3],  :
  number of items to replace is not a multiple of replacement length
.### Testing mv param stochastic, scalar value within multivar variable   with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing mv param stochastic, scalar value within multivar variable  with RHS constant ###
defining model...
Adding p as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing mv param stochastic, vector variable within matrix variable   with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing mv param stochastic, vector variable within matrix variable  with RHS constant ###
defining model...
Adding p as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing deterministic, basic  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic with node in variable, incorrect init size  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic with node in variable, incorrect init size with RHS constant ###
defining model...
Error in addMissingIndexingRecurse(code[[i]], dimensionsList) :
  inconsistent dimensionality provided for node 'a'
.### Testing deterministic, basic with node in variable  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic with node in variable with RHS constant ###
defining model...
Error in addMissingIndexingRecurse(code[[i]], dimensionsList) :
  inconsistent dimensionality provided for node 'a'
.### Testing deterministic, basic with node in variable 2  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic with node in variable 2 with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic with node in variable  3  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic with node in variable  3 with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, non-scalar expression, no indices  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
ab### Testing deterministic, non-scalar expression, no indices with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, non-scalar expression  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
cd### Testing deterministic, non-scalar expression with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, non-scalar expression with LHS indexing  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
ef### Testing deterministic, non-scalar expression with LHS indexing with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, non-scalar expression with RHS indexing  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, non-scalar expression with RHS indexing with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, non-scalar expression, dimension mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, non-scalar expression, dimension mismatch with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, vector value, dimension mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, vector value, dimension mismatch with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, vector value, missing indices  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, vector value, missing indices with RHS constant ###
defining model...
Error in replaceConstantsRecurse(x, constEnv, constNames) :
  Error, hit end
In addition: Warning messages:
1: In replaceConstantsRecurse(x, constEnv, constNames) :
  Code a was given as known but evaluates to a non-scalar.  This is probably not what you want.
2: In replaceConstantsRecurse(x, constEnv, constNames) :
  Code b was given as known but evaluates to a non-scalar.  This is probably not what you want.
3: In model$y[1] <<- model$a[1:2, 1:2] %*% model$b[1:2] :
  number of items to replace is not a multiple of replacement length
4: In model$y[1] <<- model$a[1:2, 1:2] %*% model$b[1:2] :
  number of items to replace is not a multiple of replacement length
5: In model$y[1] <<- model$a[1:2, 1:2] %*% model$b[1:2] :
  number of items to replace is not a multiple of replacement length
6: In model$y[1] <<- model$a[1:2, 1:2] %*% model$b[1:2] :
  number of items to replace is not a multiple of replacement length
7: In model$y[1] <<- model$a[1:2, 1:2] %*% model$b[1:2] :
  number of items to replace is not a multiple of replacement length
8: In model$y[1] <<- model$a[1:2, 1:2] %*% model$b[1:2] :
  number of items to replace is not a multiple of replacement length
9: In replaceConstantsRecurse(x, constEnv, constNames) :
  Code a was given as known but evaluates to a non-scalar.  This is probably not what you want.
10: In replaceConstantsRecurse(x, constEnv, constNames) :
  Code b was given as known but evaluates to a non-scalar.  This is probably not what you want.
F### Testing deterministic, basic vector  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic vector with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic vector, missing indices  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, missing indices with RHS constant ###
defining model...
Error in replaceConstantsRecurse(x, constEnv, constNames) :
  Error, hit end
In addition: Warning message:
In replaceConstantsRecurse(x, constEnv, constNames) :
  Code a was given as known but evaluates to a non-scalar.  This is probably not what you want.
.### Testing deterministic, basic vector, dimension mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, dimension mismatch with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, RHS dimension mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, RHS dimension mismatch with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, size mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, size mismatch with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, size mismatch 2  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, size mismatch 2 with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector dimension mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector dimension mismatch with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic matrix  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic matrix with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, nodes within multivar variables 1  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, nodes within multivar variables 1 with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, nodes within multivar variables, size mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, nodes within multivar variables, size mismatch with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, nodes within multivar variables, dim mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error in model$y[1:2, getNodeFunctionIndexedInfo(INDEXEDNODEINFO_, 1L)] <<- model$a[1:2,  :
  number of items to replace is not a multiple of replacement length

checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
F
Error in model$y[1:2, getNodeFunctionIndexedInfo(INDEXEDNODEINFO_, 1L)] <<- model$a[1:2,  :
  number of items to replace is not a multiple of replacement length
In addition: There were 30 warnings (use warnings() to see them)
.### Testing deterministic, nodes within multivar variables, dim mismatch with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error in model$y[1:2, getNodeFunctionIndexedInfo(INDEXEDNODEINFO_, 1L)] <<- model$a[1:2,  :
  number of items to replace is not a multiple of replacement length

checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
F
Error in model$y[1:2, getNodeFunctionIndexedInfo(INDEXEDNODEINFO_, 1L)] <<- model$a[1:2,  :
  number of items to replace is not a multiple of replacement length
.### Testing deterministic, nodes within multivar variables, input wrong dimension  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error in model$b[1:2, 1:2] : incorrect number of dimensions

checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
F
Error in model$b[1:2, 1:2] : incorrect number of dimensions
.### Testing deterministic, nodes within multivar variables, input wrong dimension with RHS constant ###
defining model...
Error in addMissingIndexingRecurse(code[[i]], dimensionsList) :
  inconsistent dimensionality provided for node 'b'
.### Testing multivar, basic  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing multivar, basic with RHS constant ###
defining model...
Adding mu,prec as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing multivar, expression as param  with RHS variable ###
defining model...
Error in checkMultivarExpr() :
  Error with parameter 'mean' of distribution 'dmnorm': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing multivar, expression as param with RHS constant ###
defining model...
Error in checkMultivarExpr() :
  Error with parameter 'mean' of distribution 'dmnorm': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing multivar, nested  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing multivar, nested with RHS constant ###
defining model...
Adding mu,prec as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing multivar, value missing index  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dmnorm_chol): 'x' and 'chol' are not of compatible sizes.
Error in model$logProb_y[1] <<- dmnorm_chol(model$y[1], mean = model$mu[1:2],  :
  replacement has length zero

checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of 'y' does not match required dimension for the distribution 'dmnorm'. Necessary dimension is 1. You may need to include explicit indexing information, e.g., variable_name[1:2].
.### Testing multivar, value missing index with RHS constant ###
defining model...
Adding mu,prec as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dmnorm_chol): 'x' and 'chol' are not of compatible sizes.
Error in model$logProb_y[1] <<- dmnorm_chol(model$y[1], mean = model$mu[1:2],  :
  replacement has length zero

checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of 'y' does not match required dimension for the distribution 'dmnorm'. Necessary dimension is 1. You may need to include explicit indexing information, e.g., variable_name[1:2].
.### Testing multivar, param missing index  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of 'mean' does not match required dimension for the distribution 'dmnorm'. Necessary dimension is 1. You may need to include explicit indexing information, e.g., variable_name[1:2].
.### Testing multivar, param missing index with RHS constant ###
defining model...
Error in replaceConstantsRecurse(x, constEnv, constNames) :
  Error, hit end
In addition: Warning message:
In replaceConstantsRecurse(x, constEnv, constNames) :
  Code mu was given as known but evaluates to a non-scalar.  This is probably not what you want.
.### Testing multivar, param wrong dimension  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error in chol.default(model$prec[1:2]) : 'a' must be a square matrix

checking model sizes and dimensions...Error in forwardsolve(t(cholesky), I) : invalid 'k' argument
Error in model$checkBasics() :
  Dimension of 'cholesky' does not match required dimension for the distribution 'dmnorm'. Necessary dimension is 2. You may need to include explicit indexing information, e.g., variable_name[1:2,1:2].
In addition: Warning message:
In model$checkBasics() :
  Unable to calculate parameter 'cov'; this may simply reflect that there are missing values in model variables.
.### Testing multivar, param wrong dimension with RHS constant ###
defining model...
Adding mu,prec as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error in chol.default(model$prec[1:2]) : 'a' must be a square matrix

checking model sizes and dimensions...Error in forwardsolve(t(cholesky), I) : invalid 'k' argument
Error in model$checkBasics() :
  Dimension of 'cholesky' does not match required dimension for the distribution 'dmnorm'. Necessary dimension is 2. You may need to include explicit indexing information, e.g., variable_name[1:2,1:2].
In addition: Warning message:
In model$checkBasics() :
  Unable to calculate parameter 'cov'; this may simply reflect that there are missing values in model variables.
.### Testing multivar, value wrong size  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dmnorm_chol): 'x' and 'chol' are not of compatible sizes.
Error in model$logProb_y[1] <<- dmnorm_chol(model$y[1:3], mean = model$mu[1:2],  :
  replacement has length zero

checking model sizes and dimensions...Error in model$checkBasics() :
  Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:3] ~ dmnorm(mean = mu[1:2], cholesky = lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,     1:2], prec_param = 1, .prec = prec[1:2, 1:2], lower = -Inf,     upper = Inf, .cov = calc_dmnormAltParams(lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,         1:2], 1, 0))
.### Testing multivar, value wrong size with RHS constant ###
defining model...
Adding mu,prec as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dmnorm_chol): 'x' and 'chol' are not of compatible sizes.
Error in model$logProb_y[1] <<- dmnorm_chol(model$y[1:3], mean = model$mu[1:2],  :
  replacement has length zero

checking model sizes and dimensions...Error in model$checkBasics() :
  Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:3] ~ dmnorm(mean = mu[1:2], cholesky = lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,     1:2], prec_param = 1, .prec = prec[1:2, 1:2], lower = -Inf,     upper = Inf, .cov = calc_dmnormAltParams(lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,         1:2], 1, 0))
.### Testing multivar, param wrong size  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
  Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:2] ~ dmnorm(mean = mu[1:3], cholesky = lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,     1:2], prec_param = 1, .prec = prec[1:2, 1:2], lower = -Inf,     upper = Inf, .cov = calc_dmnormAltParams(lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,         1:2], 1, 0))
.### Testing multivar, param wrong size with RHS constant ###
defining model...
Adding mu,prec as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
  Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:2] ~ dmnorm(mean = mu[1:3], cholesky = lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,     1:2], prec_param = 1, .prec = prec[1:2, 1:2], lower = -Inf,     upper = Inf, .cov = calc_dmnormAltParams(lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,         1:2], 1, 0))
.### Testing matrix dist, basic  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing matrix dist, basic with RHS constant ###
defining model...
Adding R as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing matrix dist, param wrong size  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dwish_chol): 'chol' must be a square matrix with the same dimensions as 'x'.
Error in model$logProb_y[1, 1] <<- dwish_chol(model$y[1:2, 1:2], cholesky = model$lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3,  :
  number of items to replace is not a multiple of replacement length

checking model sizes and dimensions...Error in model$checkBasics() :
  Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:2, 1:2] ~ dwish(cholesky = lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3,     1:3], df = df, scale_param = 0, .R = R[1:3, 1:3], lower = -Inf,     upper = Inf, .S = inverse(t(lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3,         1:3]) %*% lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3, 1:3]))
.### Testing matrix dist, param wrong size with RHS constant ###
defining model...
Adding R as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dwish_chol): 'chol' must be a square matrix with the same dimensions as 'x'.
Error in model$logProb_y[1, 1] <<- dwish_chol(model$y[1:2, 1:2], cholesky = model$lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3,  :
  number of items to replace is not a multiple of replacement length

checking model sizes and dimensions...Error in model$checkBasics() :
  Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:2, 1:2] ~ dwish(cholesky = lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3,     1:3], df = 4, scale_param = 0, .R = R[1:3, 1:3], lower = -Inf,     upper = Inf, .S = inverse(t(lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3,         1:3]) %*% lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3, 1:3]))
.### Testing matrix dist, param wrong size 2  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error in chol.default(model$R[1:2, 1:3]) : 'a' must be a square matrix

checking model sizes and dimensions...Error in model$checkBasics() :
  Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:2, 1:2] ~ dwish(cholesky = lifted_chol_oPR_oB1to2_1to3_cB_cP[1:2,     1:3], df = df, scale_param = 0, .R = R[1:2, 1:3], lower = -Inf,     upper = Inf, .S = inverse(t(lifted_chol_oPR_oB1to2_1to3_cB_cP[1:2,         1:3]) %*% lifted_chol_oPR_oB1to2_1to3_cB_cP[1:2, 1:3]))
.### Testing matrix dist, param wrong size 2 with RHS constant ###
defining model...
Adding R as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error in chol.default(model$R[1:2, 1:3]) : 'a' must be a square matrix

checking model sizes and dimensions...Error in model$checkBasics() :
  Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:2, 1:2] ~ dwish(cholesky = lifted_chol_oPR_oB1to2_1to3_cB_cP[1:2,     1:3], df = 4, scale_param = 0, .R = R[1:2, 1:3], lower = -Inf,     upper = Inf, .S = inverse(t(lifted_chol_oPR_oB1to2_1to3_cB_cP[1:2,         1:3]) %*% lifted_chol_oPR_oB1to2_1to3_cB_cP[1:2, 1:3]))
.### Testing matrix dist, value missing index  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dwish_chol): 'x' and 'chol' must be real matrices.
Error in model$logProb_y[1] <<- dwish_chol(model$y[1], cholesky = model$lifted_chol_oPR_oB1to2_1to2_cB_cP[1:2,  :
  replacement has length zero

checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of 'y' does not match required dimension for the distribution 'dwish'. Necessary dimension is 2. You may need to include explicit indexing information, e.g., variable_name[1:2,1:2].
.### Testing matrix dist, value missing index with RHS constant ###
defining model...
Adding R as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dwish_chol): 'x' and 'chol' must be real matrices.
Error in model$logProb_y[1] <<- dwish_chol(model$y[1], cholesky = model$lifted_chol_oPR_oB1to2_1to2_cB_cP[1:2,  :
  replacement has length zero

checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of 'y' does not match required dimension for the distribution 'dwish'. Necessary dimension is 2. You may need to include explicit indexing information, e.g., variable_name[1:2,1:2].
.### Testing multivar, trunc  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing multivar, trunc with RHS constant ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing multivar, trunc, extra index  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of distribution argument(s) 'mean' does not match required dimension(s) for the distribution 'dnorm'. Necessary dimension(s) are 0.
In addition: Warning message:
In model$logProb_y[1] <<- dnorm(model$y[1], mean = model$mu[1:2],  :
  number of items to replace is not a multiple of replacement length
.### Testing multivar, trunc, extra index with RHS constant ###
defining model...
Adding mu as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
  Dimension of distribution argument(s) 'mean' does not match required dimension(s) for the distribution 'dnorm'. Necessary dimension(s) are 0.
In addition: Warning message:
In model$logProb_y[1] <<- dnorm(model$y[1], mean = model$mu[1:2],  :
  number of items to replace is not a multiple of replacement length
.### Testing LHS 0 dim, RHS 1 dim, determ ###
.### Testing LHS 0 dim, RHS 1 dim, stoch ###
.### Testing LHS 0 dim, RHS 2 dim, determ ###
.### Testing LHS 0 dim, RHS 2 dim, stoch ###
.### Testing LHS 1 dim, RHS 2 dim, determ ###
.### Testing LHS 1 dim, RHS 2 dim, stoch ###
.### Testing LHS 1 dim, RHS 0 dim, determ ###
.### Testing LHS 1 dim, RHS 0 dim, stoch ###
.### Testing LHS 2 dim, RHS 0 dim, determ ###
.### Testing LHS 2 dim, RHS 0 dim, stoch ###
.### Testing LHS 2 dim, RHS 1 dim, determ ###
.### Testing LHS 2 dim, RHS 1 dim, stoch ###
.

Failed -------------------------------------------------------------------------
1. Failure: Test 1 of size/dimension check: scalar stochastic, parameter expression non-scalar, no indices
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

2. Failure: Test 2 of size/dimension check: scalar stochastic, parameter expression non-scalar, no indices
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

3. Failure: Test 1 of size/dimension check: scalar stochastic, parameter expression non-scalar, RHS index
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

4. Failure: Test 2 of size/dimension check: scalar stochastic, parameter expression non-scalar, RHS index
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

5. Failure: Test 1 of size/dimension check: scalar stochastic, parameter expression non-scalar
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

6. Failure: Test 2 of size/dimension check: scalar stochastic, parameter expression non-scalar
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

7. Failure: Test 1 of size/dimension check: scalar stochastic, non-scalar parameter, demotion
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

8. Failure: Test 2 of size/dimension check: scalar stochastic, non-scalar parameter, demotion
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

9. Failure: Test 3 of size/dimension check: scalar stochastic, scalar within multivar variable 2
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match TRUE

10. Failure: Test 1 of size/dimension check: deterministic, non-scalar expression, no indices
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

11. Failure: Test 2 of size/dimension check: deterministic, non-scalar expression, no indices
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

12. Failure: Test 1 of size/dimension check: deterministic, non-scalar expression
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

13. Failure: Test 2 of size/dimension check: deterministic, non-scalar expression
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

14. Failure: Test 1 of size/dimension check: deterministic, non-scalar expression with LHS indexing
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

15. Failure: Test 2 of size/dimension check: deterministic, non-scalar expression with LHS indexing
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

DONE ===========================================================================
Error: Test failures

That's expected behavior. We expect those failures and when I set up that
test file I didn't know of expect_failure. Hence the hack to report "KNOWN
ISSUE".
On Fri, May 19, 2017 at 6:11 PM, Fritz Obermeyer<EMAIL_ADDRESS>wrote:

Here is a failing test on travis
https://travis-ci.org/nimble-dev/nimble/builds/234183789?utm_source=github_status&utm_medium=notification,
and below is a failing test on my Ubuntu 16.04 box on devel branch
library(nimble)
library(testthat)
test_package('nimble', 'size')
..### Testing scalar stochastic, parameter expression  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, parameter expression with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, parameter expression non-scalar, no indices  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
12### Testing scalar stochastic, parameter expression non-scalar, no indices with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, parameter expression non-scalar, RHS index  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
34### Testing scalar stochastic, parameter expression non-scalar, RHS index with RHS constant ###
defining model...
Error in 2[1, 1] : incorrect number of dimensions
In addition: Warning messages:
1: Placing tests in inst/tests/ is deprecated. Please use tests/testthat/ instead
2: In replaceConstantsRecurse(x, constEnv, constNames) :
Code mu1 was given as known but evaluates to a non-scalar.  This is probably not what you want.
3: In replaceConstantsRecurse(x, constEnv, constNames) :
Code mu2 was given as known but evaluates to a non-scalar.  This is probably not what you want.
4: In code[[2]] == names(dimensionsList) :
longer object length is not a multiple of shorter object length
5: In replaceConstantsRecurse(x, constEnv, constNames) :
Code mu1 was given as known but evaluates to a non-scalar.  This is probably not what you want.
6: In replaceConstantsRecurse(x, constEnv, constNames) :
Code mu2 was given as known but evaluates to a non-scalar.  This is probably not what you want.
.### Testing scalar stochastic, parameter expression non-scalar  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
56### Testing scalar stochastic, parameter expression non-scalar with RHS constant ###
defining model...
Adding mu1,mu2 as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, parameter expression non-scalar, demotion  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, parameter expression non-scalar, demotion with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, non-scalar parameter  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, non-scalar parameter with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, non-scalar parameter, demotion  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
78### Testing scalar stochastic, non-scalar parameter, demotion with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, non-scalar value  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of distribution argument(s) 'value' does not match required dimension(s) for the distribution 'dnorm'. Necessary dimension(s) are 0.
In addition: Warning messages:
1: In code[[2]] == names(dimensionsList) :
longer object length is not a multiple of shorter object length
2: In code[[2]] == names(dimensionsList) :
longer object length is not a multiple of shorter object length
3: In code[[2]] == names(dimensionsList) :
longer object length is not a multiple of shorter object length
4: In model$logProb_y[1] <<- dnorm(model$y[1:2], mean = model$mu[1],  :
number of items to replace is not a multiple of replacement length
.### Testing scalar stochastic, non-scalar value with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of distribution argument(s) 'value' does not match required dimension(s) for the distribution 'dnorm'. Necessary dimension(s) are 0.
In addition: Warning message:
In model$logProb_y[1] <<- dnorm(model$y[1:2], mean = 1, sd = 1,  :
number of items to replace is not a multiple of replacement length
.### Testing scalar stochastic, non-scalar value and parameter  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of distribution argument(s) 'value,mean' does not match required dimension(s) for the distribution 'dnorm'. Necessary dimension(s) are 0,0.
In addition: Warning message:
In model$logProb_y[1] <<- dnorm(model$y[1:2], mean = model$mu1[1:2,  :
number of items to replace is not a multiple of replacement length
.### Testing scalar stochastic, non-scalar value and parameter with RHS constant ###
defining model...
Adding mu1,mu2 as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of distribution argument(s) 'value,mean' does not match required dimension(s) for the distribution 'dnorm'. Necessary dimension(s) are 0,0.
In addition: Warning message:
In model$logProb_y[1] <<- dnorm(model$y[1:2], mean = model$mu1[1:2,  :
number of items to replace is not a multiple of replacement length
.### Testing scalar stochastic, scalar within multivar variable  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, scalar within multivar variable with RHS constant ###
defining model...
Error in addMissingIndexingRecurse(code[[i]], dimensionsList) :
inconsistent dimensionality provided for node 'mu'
.### Testing scalar stochastic, scalar within multivar variable 2  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, scalar within multivar variable 2 with RHS constant ###
defining model...
Error in addMissingIndexingRecurse(code[[i]], dimensionsList) :
inconsistent dimensionality provided for node 'mu'
9### Testing scalar stochastic, scalar within multivar variable 3  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing scalar stochastic, scalar within multivar variable 3 with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing mv param stochastic, basic  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing mv param stochastic, basic with RHS constant ###
defining model...
Adding p as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing mv param stochastic, no indices  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of 'prob' does not match required dimension for the distribution 'dcat'. Necessary dimension is 1. You may need to include explicit indexing information, e.g., variable_name[1:2].
.### Testing mv param stochastic, no indices with RHS constant ###
defining model...
Error in replaceConstantsRecurse(x, constEnv, constNames) :
Error, hit end
In addition: Warning message:
In replaceConstantsRecurse(x, constEnv, constNames) :
Code p was given as known but evaluates to a non-scalar.  This is probably not what you want.
.### Testing mv param stochastic, scalar param  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of distribution argument(s) 'prob' does not match required dimension(s) for the distribution 'dcat'. Necessary dimension(s) are 1. You may need to ensure that you have explicit vectors and not one-row or one-column matrices.
.### Testing mv param stochastic, scalar param with RHS constant ###
defining model...
Error in addMissingIndexingRecurse(code[[i]], dimensionsList) :
inconsistent dimensionality provided for node 'p'
.### Testing mv param stochastic, scalar param, no indices  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of 'prob' does not match required dimension for the distribution 'dcat'. Necessary dimension is 1. You may need to include explicit indexing information, e.g., variable_name[1:2].
.### Testing mv param stochastic, scalar param, no indices with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of distribution argument(s) 'prob' does not match required dimension(s) for the distribution 'dcat'. Necessary dimension(s) are 1. You may need to ensure that you have explicit vectors and not one-row or one-column matrices.
.### Testing mv param stochastic, parameter expression  with RHS variable ###
defining model...
Error in checkMultivarExpr() :
Error with parameter 'prob' of distribution 'dcat': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing mv param stochastic, parameter expression with RHS constant ###
defining model...
Error in checkMultivarExpr() :
Error with parameter 'prob' of distribution 'dcat': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing mv param stochastic, parameter expression, matrices  with RHS variable ###
defining model...
Error in checkMultivarExpr() :
Error with parameter 'prob' of distribution 'dcat': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing mv param stochastic, parameter expression, matrices with RHS constant ###
defining model...
Error in checkMultivarExpr() :
Error with parameter 'prob' of distribution 'dcat': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing mv param stochastic, parameter expression, matrices subindexing  with RHS variable ###
defining model...
Error in checkMultivarExpr() :
Error with parameter 'prob' of distribution 'dcat': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing mv param stochastic, parameter expression, matrices subindexing with RHS constant ###
defining model...
Error in checkMultivarExpr() :
Error with parameter 'prob' of distribution 'dcat': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing mv param stochastic, non-scalar value  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of distribution argument(s) 'value' does not match required dimension(s) for the distribution 'dcat'. Necessary dimension(s) are 0.
In addition: Warning message:
In model$logProb_y[1] <<- dcat(model$y[1:2], prob = model$p[1:3],  :
number of items to replace is not a multiple of replacement length
.### Testing mv param stochastic, non-scalar value with RHS constant ###
defining model...
Adding p as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of distribution argument(s) 'value' does not match required dimension(s) for the distribution 'dcat'. Necessary dimension(s) are 0.
In addition: Warning message:
In model$logProb_y[1] <<- dcat(model$y[1:2], prob = model$p[1:3],  :
number of items to replace is not a multiple of replacement length
.### Testing mv param stochastic, scalar value within multivar variable   with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing mv param stochastic, scalar value within multivar variable  with RHS constant ###
defining model...
Adding p as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing mv param stochastic, vector variable within matrix variable   with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing mv param stochastic, vector variable within matrix variable  with RHS constant ###
defining model...
Adding p as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing deterministic, basic  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic with node in variable, incorrect init size  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic with node in variable, incorrect init size with RHS constant ###
defining model...
Error in addMissingIndexingRecurse(code[[i]], dimensionsList) :
inconsistent dimensionality provided for node 'a'
.### Testing deterministic, basic with node in variable  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic with node in variable with RHS constant ###
defining model...
Error in addMissingIndexingRecurse(code[[i]], dimensionsList) :
inconsistent dimensionality provided for node 'a'
.### Testing deterministic, basic with node in variable 2  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic with node in variable 2 with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic with node in variable  3  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic with node in variable  3 with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, non-scalar expression, no indices  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
ab### Testing deterministic, non-scalar expression, no indices with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, non-scalar expression  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
cd### Testing deterministic, non-scalar expression with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, non-scalar expression with LHS indexing  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
ef### Testing deterministic, non-scalar expression with LHS indexing with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, non-scalar expression with RHS indexing  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, non-scalar expression with RHS indexing with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, non-scalar expression, dimension mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, non-scalar expression, dimension mismatch with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, vector value, dimension mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, vector value, dimension mismatch with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, vector value, missing indices  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, vector value, missing indices with RHS constant ###
defining model...
Error in replaceConstantsRecurse(x, constEnv, constNames) :
Error, hit end
In addition: Warning messages:
1: In replaceConstantsRecurse(x, constEnv, constNames) :
Code a was given as known but evaluates to a non-scalar.  This is probably not what you want.
2: In replaceConstantsRecurse(x, constEnv, constNames) :
Code b was given as known but evaluates to a non-scalar.  This is probably not what you want.
3: In model$y[1] <<- model$a[1:2, 1:2] %% model$b[1:2] :
number of items to replace is not a multiple of replacement length
4: In model$y[1] <<- model$a[1:2, 1:2] %% model$b[1:2] :
number of items to replace is not a multiple of replacement length
5: In model$y[1] <<- model$a[1:2, 1:2] %% model$b[1:2] :
number of items to replace is not a multiple of replacement length
6: In model$y[1] <<- model$a[1:2, 1:2] %% model$b[1:2] :
number of items to replace is not a multiple of replacement length
7: In model$y[1] <<- model$a[1:2, 1:2] %% model$b[1:2] :
number of items to replace is not a multiple of replacement length
8: In model$y[1] <<- model$a[1:2, 1:2] %% model$b[1:2] :
number of items to replace is not a multiple of replacement length
9: In replaceConstantsRecurse(x, constEnv, constNames) :
Code a was given as known but evaluates to a non-scalar.  This is probably not what you want.
10: In replaceConstantsRecurse(x, constEnv, constNames) :
Code b was given as known but evaluates to a non-scalar.  This is probably not what you want.
F### Testing deterministic, basic vector  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic vector with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic vector, missing indices  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, missing indices with RHS constant ###
defining model...
Error in replaceConstantsRecurse(x, constEnv, constNames) :
Error, hit end
In addition: Warning message:
In replaceConstantsRecurse(x, constEnv, constNames) :
Code a was given as known but evaluates to a non-scalar.  This is probably not what you want.
.### Testing deterministic, basic vector, dimension mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, dimension mismatch with RHS constant ###
defining model...
building model...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, RHS dimension mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, RHS dimension mismatch with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, size mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, size mismatch with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, size mismatch 2  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector, size mismatch 2 with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector dimension mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic vector dimension mismatch with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, basic matrix  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, basic matrix with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, nodes within multivar variables 1  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, nodes within multivar variables 1 with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing deterministic, nodes within multivar variables, size mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, nodes within multivar variables, size mismatch with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
FF### Testing deterministic, nodes within multivar variables, dim mismatch  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error in model$y[1:2, getNodeFunctionIndexedInfo(INDEXEDNODEINFO_, 1L)] <<- model$a[1:2,  :
number of items to replace is not a multiple of replacement length
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
F
Error in model$y[1:2, getNodeFunctionIndexedInfo(INDEXEDNODEINFO_, 1L)] <<- model$a[1:2,  :
number of items to replace is not a multiple of replacement length
In addition: There were 30 warnings (use warnings() to see them)
.### Testing deterministic, nodes within multivar variables, dim mismatch with RHS constant ###
defining model...
Adding a,b as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error in model$y[1:2, getNodeFunctionIndexedInfo(INDEXEDNODEINFO_, 1L)] <<- model$a[1:2,  :
number of items to replace is not a multiple of replacement length
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
F
Error in model$y[1:2, getNodeFunctionIndexedInfo(INDEXEDNODEINFO_, 1L)] <<- model$a[1:2,  :
number of items to replace is not a multiple of replacement length
.### Testing deterministic, nodes within multivar variables, input wrong dimension  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error in model$b[1:2, 1:2] : incorrect number of dimensions
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
F
Error in model$b[1:2, 1:2] : incorrect number of dimensions
.### Testing deterministic, nodes within multivar variables, input wrong dimension with RHS constant ###
defining model...
Error in addMissingIndexingRecurse(code[[i]], dimensionsList) :
inconsistent dimensionality provided for node 'b'
.### Testing multivar, basic  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing multivar, basic with RHS constant ###
defining model...
Adding mu,prec as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing multivar, expression as param  with RHS variable ###
defining model...
Error in checkMultivarExpr() :
Error with parameter 'mean' of distribution 'dmnorm': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing multivar, expression as param with RHS constant ###
defining model...
Error in checkMultivarExpr() :
Error with parameter 'mean' of distribution 'dmnorm': multivariate parameters cannot be expressions; please define the expression as a separate deterministic variable and use that variable as the parameter.
.### Testing multivar, nested  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing multivar, nested with RHS constant ###
defining model...
Adding mu,prec as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing multivar, value missing index  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dmnorm_chol): 'x' and 'chol' are not of compatible sizes.
Error in model$logProb_y[1] <<- dmnorm_chol(model$y[1], mean = model$mu[1:2],  :
replacement has length zero
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of 'y' does not match required dimension for the distribution 'dmnorm'. Necessary dimension is 1. You may need to include explicit indexing information, e.g., variable_name[1:2].
.### Testing multivar, value missing index with RHS constant ###
defining model...
Adding mu,prec as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dmnorm_chol): 'x' and 'chol' are not of compatible sizes.
Error in model$logProb_y[1] <<- dmnorm_chol(model$y[1], mean = model$mu[1:2],  :
replacement has length zero
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of 'y' does not match required dimension for the distribution 'dmnorm'. Necessary dimension is 1. You may need to include explicit indexing information, e.g., variable_name[1:2].
.### Testing multivar, param missing index  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of 'mean' does not match required dimension for the distribution 'dmnorm'. Necessary dimension is 1. You may need to include explicit indexing information, e.g., variable_name[1:2].
.### Testing multivar, param missing index with RHS constant ###
defining model...
Error in replaceConstantsRecurse(x, constEnv, constNames) :
Error, hit end
In addition: Warning message:
In replaceConstantsRecurse(x, constEnv, constNames) :
Code mu was given as known but evaluates to a non-scalar.  This is probably not what you want.
.### Testing multivar, param wrong dimension  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error in chol.default(model$prec[1:2]) : 'a' must be a square matrix
checking model sizes and dimensions...Error in forwardsolve(t(cholesky), I) : invalid 'k' argument
Error in model$checkBasics() :
Dimension of 'cholesky' does not match required dimension for the distribution 'dmnorm'. Necessary dimension is 2. You may need to include explicit indexing information, e.g., variable_name[1:2,1:2].
In addition: Warning message:
In model$checkBasics() :
Unable to calculate parameter 'cov'; this may simply reflect that there are missing values in model variables.
.### Testing multivar, param wrong dimension with RHS constant ###
defining model...
Adding mu,prec as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error in chol.default(model$prec[1:2]) : 'a' must be a square matrix
checking model sizes and dimensions...Error in forwardsolve(t(cholesky), I) : invalid 'k' argument
Error in model$checkBasics() :
Dimension of 'cholesky' does not match required dimension for the distribution 'dmnorm'. Necessary dimension is 2. You may need to include explicit indexing information, e.g., variable_name[1:2,1:2].
In addition: Warning message:
In model$checkBasics() :
Unable to calculate parameter 'cov'; this may simply reflect that there are missing values in model variables.
.### Testing multivar, value wrong size  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dmnorm_chol): 'x' and 'chol' are not of compatible sizes.
Error in model$logProb_y[1] <<- dmnorm_chol(model$y[1:3], mean = model$mu[1:2],  :
replacement has length zero
checking model sizes and dimensions...Error in model$checkBasics() :
Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:3] ~ dmnorm(mean = mu[1:2], cholesky = lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,     1:2], prec_param = 1, .prec = prec[1:2, 1:2], lower = -Inf,     upper = Inf, .cov = calc_dmnormAltParams(lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,         1:2], 1, 0))
.### Testing multivar, value wrong size with RHS constant ###
defining model...
Adding mu,prec as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dmnorm_chol): 'x' and 'chol' are not of compatible sizes.
Error in model$logProb_y[1] <<- dmnorm_chol(model$y[1:3], mean = model$mu[1:2],  :
replacement has length zero
checking model sizes and dimensions...Error in model$checkBasics() :
Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:3] ~ dmnorm(mean = mu[1:2], cholesky = lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,     1:2], prec_param = 1, .prec = prec[1:2, 1:2], lower = -Inf,     upper = Inf, .cov = calc_dmnormAltParams(lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,         1:2], 1, 0))
.### Testing multivar, param wrong size  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:2] ~ dmnorm(mean = mu[1:3], cholesky = lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,     1:2], prec_param = 1, .prec = prec[1:2, 1:2], lower = -Inf,     upper = Inf, .cov = calc_dmnormAltParams(lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,         1:2], 1, 0))
.### Testing multivar, param wrong size with RHS constant ###
defining model...
Adding mu,prec as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:2] ~ dmnorm(mean = mu[1:3], cholesky = lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,     1:2], prec_param = 1, .prec = prec[1:2, 1:2], lower = -Inf,     upper = Inf, .cov = calc_dmnormAltParams(lifted_chol_oPprec_oB1to2_1to2_cB_cP[1:2,         1:2], 1, 0))
.### Testing matrix dist, basic  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing matrix dist, basic with RHS constant ###
defining model...
Adding R as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions... note that missing values (NAs) or non-finite values were found in model variables: y. This is not an error, but some or all variables may need to be initialized for certain algorithms to operate properly.
model building finished.
..### Testing matrix dist, param wrong size  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dwish_chol): 'chol' must be a square matrix with the same dimensions as 'x'.
Error in model$logProb_y[1, 1] <<- dwish_chol(model$y[1:2, 1:2], cholesky = model$lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3,  :
number of items to replace is not a multiple of replacement length
checking model sizes and dimensions...Error in model$checkBasics() :
Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:2, 1:2] ~ dwish(cholesky = lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3,     1:3], df = df, scale_param = 0, .R = R[1:3, 1:3], lower = -Inf,     upper = Inf, .S = inverse(t(lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3,         1:3]) %*% lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3, 1:3]))
.### Testing matrix dist, param wrong size with RHS constant ###
defining model...
Adding R as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dwish_chol): 'chol' must be a square matrix with the same dimensions as 'x'.
Error in model$logProb_y[1, 1] <<- dwish_chol(model$y[1:2, 1:2], cholesky = model$lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3,  :
number of items to replace is not a multiple of replacement length
checking model sizes and dimensions...Error in model$checkBasics() :
Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:2, 1:2] ~ dwish(cholesky = lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3,     1:3], df = 4, scale_param = 0, .R = R[1:3, 1:3], lower = -Inf,     upper = Inf, .S = inverse(t(lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3,         1:3]) %*% lifted_chol_oPR_oB1to3_1to3_cB_cP[1:3, 1:3]))
.### Testing matrix dist, param wrong size 2  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error in chol.default(model$R[1:2, 1:3]) : 'a' must be a square matrix
checking model sizes and dimensions...Error in model$checkBasics() :
Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:2, 1:2] ~ dwish(cholesky = lifted_chol_oPR_oB1to2_1to3_cB_cP[1:2,     1:3], df = df, scale_param = 0, .R = R[1:2, 1:3], lower = -Inf,     upper = Inf, .S = inverse(t(lifted_chol_oPR_oB1to2_1to3_cB_cP[1:2,         1:3]) %*% lifted_chol_oPR_oB1to2_1to3_cB_cP[1:2, 1:3]))
.### Testing matrix dist, param wrong size 2 with RHS constant ###
defining model...
Adding R as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error in chol.default(model$R[1:2, 1:3]) : 'a' must be a square matrix
checking model sizes and dimensions...Error in model$checkBasics() :
Size/dimension mismatch amongst vectors and matrices in BUGS expression: y[1:2, 1:2] ~ dwish(cholesky = lifted_chol_oPR_oB1to2_1to3_cB_cP[1:2,     1:3], df = 4, scale_param = 0, .R = R[1:2, 1:3], lower = -Inf,     upper = Inf, .S = inverse(t(lifted_chol_oPR_oB1to2_1to3_cB_cP[1:2,         1:3]) %*% lifted_chol_oPR_oB1to2_1to3_cB_cP[1:2, 1:3]))
.### Testing matrix dist, value missing index  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dwish_chol): 'x' and 'chol' must be real matrices.
Error in model$logProb_y[1] <<- dwish_chol(model$y[1], cholesky = model$lifted_chol_oPR_oB1to2_1to2_cB_cP[1:2,  :
replacement has length zero
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of 'y' does not match required dimension for the distribution 'dwish'. Necessary dimension is 2. You may need to include explicit indexing information, e.g., variable_name[1:2,1:2].
.### Testing matrix dist, value missing index with RHS constant ###
defining model...
Adding R as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ... Error (C_dwish_chol): 'x' and 'chol' must be real matrices.
Error in model$logProb_y[1] <<- dwish_chol(model$y[1], cholesky = model$lifted_chol_oPR_oB1to2_1to2_cB_cP[1:2,  :
replacement has length zero
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of 'y' does not match required dimension for the distribution 'dwish'. Necessary dimension is 2. You may need to include explicit indexing information, e.g., variable_name[1:2,1:2].
.### Testing multivar, trunc  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing multivar, trunc with RHS constant ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...
model building finished.
..### Testing multivar, trunc, extra index  with RHS variable ###
defining model...
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of distribution argument(s) 'mean' does not match required dimension(s) for the distribution 'dnorm'. Necessary dimension(s) are 0.
In addition: Warning message:
In model$logProb_y[1] <<- dnorm(model$y[1], mean = model$mu[1:2],  :
number of items to replace is not a multiple of replacement length
.### Testing multivar, trunc, extra index with RHS constant ###
defining model...
Adding mu as data for building model.
building model...
setting data and initial values...
running calculate on model (any error reports that follow may simply reflect missing values in model variables) ...
checking model sizes and dimensions...Error in model$checkBasics() :
Dimension of distribution argument(s) 'mean' does not match required dimension(s) for the distribution 'dnorm'. Necessary dimension(s) are 0.
In addition: Warning message:
In model$logProb_y[1] <<- dnorm(model$y[1], mean = model$mu[1:2],  :
number of items to replace is not a multiple of replacement length
.### Testing LHS 0 dim, RHS 1 dim, determ ###
.### Testing LHS 0 dim, RHS 1 dim, stoch ###
.### Testing LHS 0 dim, RHS 2 dim, determ ###
.### Testing LHS 0 dim, RHS 2 dim, stoch ###
.### Testing LHS 1 dim, RHS 2 dim, determ ###
.### Testing LHS 1 dim, RHS 2 dim, stoch ###
.### Testing LHS 1 dim, RHS 0 dim, determ ###
.### Testing LHS 1 dim, RHS 0 dim, stoch ###
.### Testing LHS 2 dim, RHS 0 dim, determ ###
.### Testing LHS 2 dim, RHS 0 dim, stoch ###
.### Testing LHS 2 dim, RHS 1 dim, determ ###
.### Testing LHS 2 dim, RHS 1 dim, stoch ###
.
Failed -------------------------------------------------------------------------

Failure: Test 1 of size/dimension check: scalar stochastic, parameter expression non-scalar, no indices
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

Failure: Test 2 of size/dimension check: scalar stochastic, parameter expression non-scalar, no indices
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

Failure: Test 1 of size/dimension check: scalar stochastic, parameter expression non-scalar, RHS index
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

Failure: Test 2 of size/dimension check: scalar stochastic, parameter expression non-scalar, RHS index
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

Failure: Test 1 of size/dimension check: scalar stochastic, parameter expression non-scalar
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

Failure: Test 2 of size/dimension check: scalar stochastic, parameter expression non-scalar
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

Failure: Test 1 of size/dimension check: scalar stochastic, non-scalar parameter, demotion
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

Failure: Test 2 of size/dimension check: scalar stochastic, non-scalar parameter, demotion
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

Failure: Test 3 of size/dimension check: scalar stochastic, scalar within multivar variable 2
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match TRUE

Failure: Test 1 of size/dimension check: deterministic, non-scalar expression, no indices
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

Failure: Test 2 of size/dimension check: deterministic, non-scalar expression, no indices
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

Failure: Test 1 of size/dimension check: deterministic, non-scalar expression
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

Failure: Test 2 of size/dimension check: deterministic, non-scalar expression
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

Failure: Test 1 of size/dimension check: deterministic, non-scalar expression with LHS indexing
!is(result, "try-error") not equal to input$expectPass.
1 element mismatch
KNOWN ISSUE: Result does not match FALSE

Failure: Test 2 of size/dimension check: deterministic, non-scalar expression with L

While test_file and test_package both print "KNOWN ISSUE", the test_file version exits with return code 0 (and hence works on travis), whereas the test_package version exits with nonzero return code (and hence fails on travis). I can look into this next week, since I can reproduce on my machine.

hmm, I think we've been running test_size on travis for months now (and
current devel is passing travis, no?) ??? Confused about what might be
different here....
On Fri, May 19, 2017 at 10:12 PM, Fritz Obermeyer<EMAIL_ADDRESS>wrote:

While test_file and test_package both print "KNOWN ISSUE", the test_file
version exits with return code 0 (and hence works on travis), whereas the
test_package version exits with nonzero return code (and hence fails on
travis). I can look into this next week, since I can reproduce on my
machine.
—