knitr::opts_chunk$set(echo = TRUE) library(ESM262PackageAssignment)
Start by generating sample data: (a sample dataset is also stored in data subdirectory)
# possible fish species to sample from species = c("sockeye","chinook","sculpin","jellyfish","flounder") # typical prices for each possible fish prices = data.frame(fish = species, price = c(5, 40, 3, 1, 1)) # locations of fisheries locs = c("Earth", "Mars", "Europa", "Titan", "Venus") catches = matrix(nrow=length(species), ncol=length(locs) ) colnames(catches)=locs rownames(catches)=species # typical size of catch in each area locs = data.frame(name=locs, size = c(10000, 100, 20000, 500, 50)) # generate random catches close to typical sizes for each area for ( i in 1: length(species)) { for (j in 1:nrow(locs)) { catches[i,j] = round(rnorm(mean=locs$size[j], sd=0.1*locs$size[j], n=1)) } }
Now we can run the function with the example data:
fisheries_summary(catches = catches, prices = prices, plot=FALSE)
This time, make a plot as well
fisheries_summary(catches = example_catch, prices = prices, plot=TRUE)
We can run the growth rate function using the default parameters from Experiment A in Table 2 of Bjoornsson et al.
#growth rate at temp of 15 degrees Celsius growth_rate(15)
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