exception handling and making plotting routines more compact

[cchrisgong]

1. exception handling when DTcoup is uncoupled, and no dieter datas are present

read.gdx(gdx, 'qm_budget', 'm') %>% 
  rename('t' = 1, 'regi' = 2)

can generalize functions reading tall or ttot

  vm_cesIO <- read.gdx(gdxName, 'vm_cesIO', factors = FALSE,
                     colNames = c('t', 'regi', 'pf', 'value'))

this would allow other performance type improvement (combine entities of the same unit, etc)

4. a third alternative besides explicit function and loops

   lapply(iterations, 
       function(iteration) {
            read.gdx(paste0('/tmp/input_', iteration, '.gdx'), 'vm_cesIO', 
                     colNames = c('t', 'regi', 'pf', 'value'), 
                     factors = FALSE) %>% 
                mutate(iteration = iteration) %>% 
                slice_sample(n = 3)
        }) %>% 
     bind_rows()

In summary,

loops:
pro: a bit more readable than functions,
con: if used in another script, need to be imported somehow (true? if so how)

functions:
pro: can be reused for multiple variables and parameters (esp of the same units, can be processed similarly)
con: can have a centralized script, where all var and par are read in, then in plotting scripts they can be adjusted and plotted