Check Components for Missing Inputs at preStep() or init(), handle missing values gracefully

[rburghol]

If someone creates an equation that references variables that don't exist, this should not cause a catastrophic error, but should result in very stern warnings to the user. Default values of 0.0 should be set for any missing var.

• Each variable should be checked at start of simulation, maybe init() method or preStep() first time (see code below)
• Handle bad values after init(): Current behavior uses tryCatch() and proceeds without failing, but is less descriptive than the proposed approach would yield. See: R implementation of modelObject, modelSubObject and basic equation object OM #55

Pre Evaluation of Present Variables in init()

Consider this snippet of code, where for_suro is DEFINED, but pas_suro is UNDEFINED in the array data:

data <- list(
  for_suro = 1.1
)
eqstring <- 'for_suro + pas_suro'
eqx <- parse(text=eqstring)
eval(eqx, data)
   Error in eval(eqx, data) : object 'pas_suro' not found

We should be able to use getParseData(), which returns the following info about our expression:

eqinfo = getParseData(eqx)
  line1 col1 line2 col2 id parent  token terminal     text
7     1    1     1   19  7      0   expr    FALSE         
1     1    1     1    8  1      3 SYMBOL     TRUE for_suro
3     1    1     1    8  3      7   expr    FALSE         
2     1   10     1   10  2      7    '+'     TRUE        +
4     1   12     1   19  4      6 SYMBOL     TRUE pas_suro
6     1   12     1   19  6      7   expr    FALSE     

To extract those variables that are requested, we can use:

eqvars <- eqinfo[eqinfo$token == "SYMBOL",]
eqvars
  line1 col1 line2 col2 id parent  token terminal     text
1     1    1     1    8  1      3 SYMBOL     TRUE for_suro
4     1   12     1   19  4      6 SYMBOL     TRUE pas_suro

And then set defaults appropriately, perhaps at the "getInputs()" method of the Equation class.