hlsimulator: Simulate Hook and Line Survey

#' Exponential Fish Sampling
#' Function that samples based on exponential function. Catch probabilities depend on number
#' of fish and probabilities of catching each species. 

#'Function to fish the population
#'@param nfish1 Number of fish1
#'@param nfish2 Number of fish2
#'@param prob1 Probability of catching fish1
#'@param prob2 Probability of catching fish2
#'@param comp_coeff Competition coefficient. Higher the value the more likely to catch 
#' species1. Specified in ctl file. If NA, use other probability formulation

#'@examples
#' Put Example Here
#'@export


sample_exp <- function(nfish1, nfish2, prob1, prob2, comp_coeff){
  #------------------------------------------------
  #Define probabilities based on number of fish
  #Might need to adjust the shape of this curve
  #Can adjust these to account for behavior of certain species
  p1 <- 1 - exp(-nfish1 * prob1) #prob1 is catchability for species 1
  p2 <- 1 - exp(-nfish2 *  prob2) #prob2 is catchability for species 2

  #Probability of catching a fish
  hook_prob <- 1 - ((1 - p1) * (1 - p2))
  
  fish <- rbinom(n = 1, size = 1,  prob = hook_prob)  #bernoulli trial
  #------------------------------------------------
  # Which fish was caught?
  #initially declare both as 0
  fish1 <- 0
  fish2 <- 0
  
  if(fish == 1){
    #ratio of catchabilities between two species
    c1 <- prob1 / (prob1 + prob2) #equivalent to competition coefficient

    #Adjust proportion of fish based on catchability ratios
    prop1 <- (c1 * nfish1) / ((c1 * nfish1) + (1 - c1) * nfish2)
  
    fish1 <- rbinom(n = 1, size = 1, prob = prop1)  
  }

  if(fish1 == 0 & fish == 1) fish2 <- 1

  #Return values as data frame
  return(data.frame(fish1 = fish1, fish2 = fish2))

}



#Test the function

#Define function arguments
# nsamps <- 100
# fish1 <- 1
# fish2 <- 3
# prob1 <- .03
# prob2 <- .01
# comp_coeff <- 0.3 #comp_coeff no longer does anything in the function


# #setup output
# temp_fish12 <- data.frame(nsamps = 1:nsamps, fish1 = rep(999, nsamps),
#       fish2 = rep(999, nsamps))
      
# for(nn in 1:nsamps){                    
#   temp_samp <- sample_exp(nfish1 = fish1, nfish2 = fish2, 
#     prob1 = prob1, prob2 = prob2, comp_coeff = comp_coeff)

#   #Make sure that catch of fish can't exceed number of fish      
#   if(fish1 - temp_samp$fish1 < 0) {
#     print('sp1')
#     temp_samp$fish1 <- 0
#   }

#   if(fish2 - temp_samp$fish2 < 0){
#     print('sp2')
#     # browser()
#     temp_samp$fish2 <- 0
#   }

#   temp_fish12[nn, 2:3] <- temp_samp
  
#   #update counts of fish1 and fish2
#   fish1 <- fish1 - temp_samp$fish1
#   fish2 <- fish2 - temp_samp$fish2

#   #Change the probabilities if there aren't any more fish
#   if(fish1 == 0) prob1 <- 0
#   if(fish2 == 0) prob2 <- 0
# }

# #Check results
# colSums(temp_fish12[, c(2, 3)])