I was contacted by someone using our package to let us know that they were unable to get the example with missing species to run without it crashing. This occurs before the MCMC starts. I have located the issue and added a fix.
Essentially, when we had missing species, the matrix dataConstants would end up with NAs for the entries. Then, in getODEGradient, the calculation of XODE <- X + auxVars$dataConstants would result in a column of NAs for the missing species. This caused the predictions from the ODEs to result in NAs and when the likelihood is calculated, it crashes since it cannot deal with NAs.
I have changed the calculation of dataConstants to be calculated with for the observed variables instead of the total number of columns in the dataset. I will push a change to git and we can then push to CRAN with the rest of our other changes.
One other problem I did see however when tinkering with this is that showPlot=T doesn't work correctly when we have missing species, since the ylim values are not calculated properly. Is there a chance you could have a look at this? I can have a look, but I am tied up at the moment.
I was contacted by someone using our package to let us know that they were unable to get the example with missing species to run without it crashing. This occurs before the MCMC starts. I have located the issue and added a fix.
Essentially, when we had missing species, the matrix dataConstants would end up with NAs for the entries. Then, in getODEGradient, the calculation of XODE <- X + auxVars$dataConstants would result in a column of NAs for the missing species. This caused the predictions from the ODEs to result in NAs and when the likelihood is calculated, it crashes since it cannot deal with NAs.
I have changed the calculation of dataConstants to be calculated with for the observed variables instead of the total number of columns in the dataset. I will push a change to git and we can then push to CRAN with the rest of our other changes.
One other problem I did see however when tinkering with this is that showPlot=T doesn't work correctly when we have missing species, since the ylim values are not calculated properly. Is there a chance you could have a look at this? I can have a look, but I am tied up at the moment.