dwbapst

## To install the latest version from Github:
# install.packages("devtools")
# devtools::install_github("tylermorganwall/rayshader")
## also marmap
# install.packages("marmap")

## load these libraries (?)
# library(rayshader)
# library(marmap)
## now just imported...

dwbapst

dwbapst

    
  # Pokemon GO nest migration table - oddish removed, with gen 5 and no Eevee - 10-03-19
  
    # taxa in full nesting list not in NEW nesting list
    removeTaxaNew <- c("Oddish", "Eevee") 
    
    # taxa in full nesting list not in OLD nesting list
      # this is often an empty set because
        # the nesting list was fully utilized before an event
      # if full list before migration, just do `""`

dwbapst

# persistent_rb_eng_via_nohup.R



# to initiate rb:
 mkfifo in_revbayes
# nohup rb <in_revbayes >out.txt &

# to run a sample of code (here 'x = 3+111')
# (echo -e "x = 3+111\n" && cat) > in_revbayes &

dwbapst

Programming and How To Use Code from Other People in Your Code

In programming, we often "borrow, reuse or steal" other people's code. This can make the line between what is plagiarized work and what is original work unclear. So, let's dive in a little to how code is reused, and what proper reuse and attribution look like.

Essentially, All Programming is Borrowing

First, all programming depends on previous programming: the code you will be write in this class (and pretty much any other data science class) relies on a language (R, Python, Java, etc) with a wide number of commands, and the commands available in the languages are what make the language useful. (In R, and many other languages, we refer to 'functions', not commands.) Those 'functions' themselves are pre-packaged segments of code that we can call upon by simply uttering the necessary command -- and they were written by previous developers. So, anyone who develops using such programming languages automatically relies on other people's work

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paleotree in Methods in Ecology and Evolution: A Retrospective

David Bapst

Texas A&M University

[email protected]

How I Ended Up Writing About My R Package in Methods in Ecology and Evolution Back In 2012

dwbapst

nruns <- 1000000 # one million runs

probability of getting a perfect wild pokemon without weather boosting

minIV <- 0
maxIV <- 15

perfects <- 0
for(i in 1:nruns){

pokemon <- sample(x = minIV:maxIV, size = 3, replace = TRUE)