[FORGED] Newbie Question on R versus Matlab/Octave versus C

On Tue, 29 Jan 2019, Alan Feuerbacher wrote:

After my failed attempt at using Octave, I realized that most likely 
the main contributing factor was that I was not able to figure out an 
efficient data structure to model one person. But C lent itself 
perfectly to my idea of how to go about programming my simulation. So 
here's a simplified pseudocode sort of example of what I did:

Don't model one person... model an array of people.

To model a single reproducing woman I used this C construct:

typedef struct woman {
?int isAlive;
?int isPregnant;
?double age;
?. . .
} WOMAN;

# e.g.
Nwomen <- 100
women <- data.frame( isAlive = rep( TRUE, Nwomen )
 ?????????????????? , isPregnant = rep( FALSE, Nwomen )
 ?????????????????? , age = rep( 20, Nwomen )
 ?????????????????? )

Then I allocated memory for a big array of these things, using the C 
malloc() function, which gave me the equivalent of this statement:

WOMAN women[NWOMEN];? /* An array of NWOMEN woman-structs */

After some initialization I set up two loops:

for( j=0; j<numberOfYears; j++) {
?for(i=1; i< numberOfWomen; i++) {
?? updateWomen();
?}
}

for ( j in seq.int( numberOfYears ) {
 ? # let vectorized data storage automatically handle the other for loop
 ? women <- updateWomen( women )
}

The function updateWomen() figures out things like whether the woman 
becomes pregnant or gives birth on a given day, dies, etc.

You can use your "fixed size" allocation strategy with flags indicating 
whether specific rows are in use, or you can only work with valid rows 
and add rows as needed for children... best to compute a logical vector 
that identifies all of the birthing mothers as a subset of the data 
frame, and build a set of children rows using the birthing mothers data 
frame as input, and then rbind the new rows to the updated women 
dataframe as appropriate. The most clear approach for individual 
decision calculations is the use of the vectorized "ifelse" function, 
though under certain circumstances putting an indexed subset on the left 
side of an assignment can modify memory "in place" (the 
functional-programming restriction against this is probably a foreign 
idea to a dyed-in-the-wool C programmer, but R usually prevents you from 
modifying the variable that was input to a function, automatically 
making a local copy of the input as needed in order to prevent such 
backwash into the caller's context).