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library(Tides)
#generate date time sequence for 6 sec frequency series
dt<-read.table("clipboard",header=FALSE,colClasses=c("character","character","numeric","numeric"),col.names=c("Date","Time","wlev","stage"))
dt$DateTime<-as.POSIXct(paste(dt$Date,dt$Time),format="%Y%j %H%M")
dt2<-data.frame(dt$DateTime,dt$stage)
names(dt2)<-c("time","h")
dt2<-dt2[complete.cases(dt2),]
TidalCharacteristics(dt2,0.4,dtMax=1680)

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library(shiny)
library(maps)
library(maptools)
library(ggplot2)
library(plyr)
library(XML)

# Define server logic required to plot various variables against mpg
shinyServer(function(input, output, session) {
  

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Lesson 00 - Setup + R Intro

Start Rstudio Create Project Create a Data Directory and Rscript

Explain:

• diff btw console and script
• + sign means waiting for more input

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1 + 1

# assign b to 2
b <- 2
a <- 3
b <- a
a <- 6

# exploring sqrt function
b <- 4

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# work-through of https://github.com/USGS-R/mda.lakes/issues/91

set.seed(443)

trend = 0.04 #in units per year, kinda like wtemp
freq = 26 #sample freq
year = (1:(30*freq)/freq)

yobs = 10*sin(year*2*pi)+ 10 + trend*year + rnorm(length(year), sd=0)
ymod = 10*sin(year*2*pi) + 10 + (trend*max(year)/2)

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lagpad <- function(x, k) {
    c(rep(NA, k), x)[1 : length(x)] 
}

level_pool_routing <- function(lt, qh, area, delta_t, initial_outflow, initial_storage, linear.fit){
  
  lt$ii <- apply(cbind(lagpad(lt$inflow, 1), lt$inflow), 1, sum)

  if(is.null(qh$storage)){
    qh$storage <- area * qh$elevation

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library(WikipediR)
library(rvest)

get_lake_wiki <- function(lake_name){
  res <- WikipediR::page_content("en", "wikipedia", page_name = lake_name,
                                 as_wikitext = FALSE)
  res <- res$parse$text[[1]]
  
  res <- xml2::read_html(res)
  res <- rvest::html_nodes(res, "table")

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# http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0081457

library(fulltext)
library(alm)

query <- ft_search(query = "Estimating Summer Nutrient Concentrations in
          Northeastern Lakes from SPARROW Load Predictions and Modeled
          Lake Depth and Volume", from = "plos")
doi <- ft_links(query)$plos$ids
alm_ids(doi = doi, info = "detail")$data$info$title

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# https://www.reddit.com/r/mildlyinteresting/comments/5k4eqd/the_first_100_positive_integers_in_alphabetical
# https://imgur.com/Ylmw8K6
source("https://raw.githubusercontent.com/ateucher/useful_code/master/R/numbers2words.r")

dt <- numbers2words(1:100)
dt <- order(dt)
dt <- matrix(dt, nrow = 10, byrow = TRUE)

knitr::kable(data.frame(dt), caption = "The first one hundred natural numbers in alphabetical order")

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# need to apt-get:
# * libdvdcsss2
# * handbrake-cli

handbrake_scan <- function(source){
  cli <- paste0("HandBrakeCLI -i ", source, " --scan")
  system(cli)
}

handbrake_scan("/media/user/disc")