tidywater (version 0.7.0)

solvect_o3_once: Apply `solvect_o3` to a data frame and create new columns with ct and log removals.

Description

This function allows solvect_o3 to be added to a piped data frame. Three additional columns will be added to the data frame; ct_required (mg/L*min), ct_actual (mg/L*min), glog_removal

Usage

solvect_o3_once(
  df,
  input_water = "defined_water",
  time = 0,
  dose = 0,
  kd = 0,
  baffle = 0,
  water_prefix = TRUE
)

Value

A data frame containing the original data frame and columns for required CT, actual CT, and giardia log removal.

Arguments

df

a data frame containing a water class column, which has already been computed using define_water_chain

input_water

name of the column of Water class data to be used as the input for this function. Default is "defined_water".

time

Retention time of disinfection segment in minutes.

dose

Ozone dose (mg/L as O3). This value can also be the y intercept of the decay curve (often slightly lower than ozone dose.)

kd

First order decay constant. This parameter is optional. If not specified, the default ozone decay equations will be used.

baffle

Baffle factor - unitless value between 0 and 1.

water_prefix

name of the input water used for the calculation will be appended to the start of output columns. Default is TRUE.

Details

The data input comes from a `water` class column, initialized in define_water_chain.

For large datasets, using `fn_once` or `fn_chain` may take many minutes to run. These types of functions use the furrr package for the option to use parallel processing and speed things up. To initialize parallel processing, use `plan(multisession)` or `plan(multicore)` (depending on your operating system) prior to your piped code with the `fn_once` or `fn_chain` functions. Note, parallel processing is best used when your code block takes more than a minute to run, shorter run times will not benefit from parallel processing.

Examples

library(dplyr)
ct_calc <- water_df %>%
  define_water_chain() %>%
  solvect_o3_once(dose = 2, kd = -0.5, time = 10)

ozone_resid <- water_df %>%
  mutate(br = 50) %>%
  define_water_chain() %>%
  mutate(
    dose = rep(seq(1, 4, 1), 3),
    time = rep(seq(2, 8, 2), 3),
    baffle = .5
  ) %>%
  solvect_o3_once()