tidywater (version 0.7.0)

blend_waters_chain: Apply `blend_waters` within a dataframe and output a column of `water` class to be chained to other tidywater functions

Description

This function allows blend_waters to be added to a piped data frame.

Usage

blend_waters_chain(df, waters, ratios, output_water = "blended_water")

Value

A data frame with a water class column containing updated ions and pH.

Arguments

df

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

waters

List of column names containing a water class to be blended

ratios

List of column names or vector of blend ratios in the same order as waters. (Blend ratios must sum to 1)

output_water

name of output column storing updated parameters with the class, water. Default is "blended_water".

Details

The data input comes from a `water` class column, initialized in define_water or balance_ions. The `water` class columns to use in the function are specified as function arguments. Ratios may be input as columns with varied ratios (in this case, input column names in the function arguments), OR input as numbers directly.

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.

See Also

blend_waters

Examples

library(purrr)
library(furrr)
library(tidyr)
library(dplyr)

example_df <- water_df %>%
  define_water_chain() %>%
  balance_ions_chain() %>%
  chemdose_ph_chain(naoh = 22) %>%
  mutate(
    ratios1 = .4,
    ratios2 = .6
  ) %>%
  blend_waters_chain(
    waters = c("defined_water", "dosed_chem_water"),
    ratios = c("ratios1", "ratios2"), output_water = "Blending_after_chemicals"
  )


example_df <- water_df %>%
  define_water_chain() %>%
  balance_ions_chain() %>%
  chemdose_ph_chain(naoh = 22, output_water = "dosed") %>%
  blend_waters_chain(waters = c("defined_water", "dosed", "balanced_water"), ratios = c(.2, .3, .5))

# \donttest{
# Initialize parallel processing
plan(multisession, workers = 2) # Remove the workers argument to use all available compute
example_df <- water_df %>%
  define_water_chain() %>%
  balance_ions_chain() %>%
  chemdose_ph_chain(naoh = 22, output_water = "dosed") %>%
  blend_waters_chain(waters = c("defined_water", "dosed", "balanced_water"), ratios = c(.2, .3, .5))

# Optional: explicitly close multisession processing
plan(sequential)
# }