mowater: Datasets for Data Science

#' Reverse Osmosis Filter Trials
#'
#' The reverse osmosis data set contains experiment data from a hydrokinetic
#' reverse osmosis pilot study, which ran 11 experiments. During the beginning of each trial, the System Mode
#' is set to fixed flux to acheive steady state conditions. Then, the System mode is changed to
#' cycle feed pressure. To simulate the increase and decrease of pressure when non-continuous
#' tidal energy is used to power the system, a sine wave is used to set the operating
#' pressure between two values. There are two modes which cycle feed pressure:
#' high and low. The system is controlled by a “feed pump” and a “reject value”
#' which generates pressure across the membrane. Observations are collected every minute.
#'
#' @docType data
#'
#' @usage data(reverse_osmosis)
#'
#' @format An object of class \code{"data.frame"} with 25844 rows
#' and 23 variables. Operational variables are flow rate, temperature, pressure,
#' and flux. Variables of interest are those that measure conductivity.
#'
#' @source  Dr. Kirby Sitterley in collaboration with the National Renewable Energy Laboratory and Dr. Tzahi Cath from the Department of Civil and Environmental Engineering at Colorado School of Mines.
#'
#' @examples
#' #- conductivity
#' cols = c("yellow2", "turquoise4", "maroon4")
#' ts.plot(reverse_osmosis$reject_conductivity_ms,
#' ylim = c(0, 1000), main = "Conductivity", col = cols[1])
#' lines(reverse_osmosis$permeate_conductivity_low_us, col = cols[2])
#' lines(reverse_osmosis$permeate_conductivity_high_us, col = cols[3])
#' legend(2500, 1000, c("cond rej", "cond lo", "cond hi"),
#' col = cols, pch = "l", bg = "white")
#'
"reverse_osmosis"