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R-common/R/unit-converters-electrochem...

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R

#' AVS -> SHE
#'
#' Converts from absolute vacuum scale (AVS) to SHE scale
#'
#' @param avs Potential in AVS scale
#'
#' @return potential in SHE scale (numeric)
#' @export
AVS2SHE <- function(avs) {
.Deprecated("as.SHE")
she <- -(4.5 + avs)
return(she)
}
#' SHE -> AVS
#'
#' Converts from SHE scale to absolute vacuum (AVS) scale
#'
#' @param she Potential in SHE scale
#'
#' @return potential in AVS scale (numeric)
#' @export
SHE2AVS <- function(she) {
.Deprecated("as.SHE")
avs <- -(4.5 + she)
return(avs)
}
#' Get standardised name of reference electrode
#'
#' Given a reference electrode label, this function returns its canonical name
#' (as defined by this package).
#' This function tries to match against as many variations as possible for each
#' reference electrode.
#' The entire point of this function is to decrease the mental load on the user
#' by not requiring them to remember a particular label or name for each reference
#' electrode, instead almost any sufficiently distinct label or string will still
#' be correctly identified.
#'
#' @param refname string or a vector of strings
#'
#' @return vector with corresponding "canonical" name or empty string (if none found)
#' @export
RefCanonicalName <- function(refname) {
# scale names
electrode.system <- list()
electrode.system[["SHE"]] <-
c("SHE",
"Standard hydrogen",
"Standard hydrogen electrode")
electrode.system[["AgCl/Ag"]] <-
c("AgCl/Ag",
"Ag/AgCl",
"AgCl",
"Silver-Silver chloride",
"Silver chloride",
"SSC") # Sometimes used abbr. for Saturated Silver Chloride
electrode.system[["Hg2Cl2/Hg"]] <-
c("Hg2Cl2/Hg",
"Hg/Hg2Cl2",
"Hg2Cl2",
"Calomel-Mercury",
"Mercury-Calomel",
"Calomel",
"SCE")
electrode.system[["AVS"]] <-
c("AVS",
"Vacuum",
"Vacuum scale",
"Absolute",
"Absolute scale",
"Absolute vacuum scale")
electrode.system[["Li"]] <-
c("Li",
"Li/Li+",
"Li+/Li",
"Lithium")
electrode.system[["Na"]] <-
c("Na",
"Na+/Na",
"Na/Na+",
"Sodium")
electrode.system[["Mg"]] <-
c("Mg",
"Mg2+/Mg",
"Mg/Mg2+",
"Magnesium")
# if no argument or empty string supplied as arg, return the the entire list as df
# to give the user a nice overview of all available options
if (missing(refname) || refname == "") {
max.row.length <- 0
for (i in 1:length(electrode.system)) {
# find the longest row and save its length
this.row.length <- length(electrode.system[[i]])
if (this.row.length > max.row.length) max.row.length <- this.row.length
}
# initialise an empty df with dimensions that fit electrode.system
overview.names <-
data.frame(
structure(dimnames =
list(
# rownames
seq(1, length(electrode.system)),
# colnames
c("canonical", paste0("option", seq(1, max.row.length - 1)))),
matrix("",
nrow = length(electrode.system),
ncol = max.row.length,
byrow = TRUE)),
stringsAsFactors = FALSE)
# now populate the df
for (i in 1:length(electrode.system)) {
this.row.length <- length(electrode.system[[i]])
overview.names[i,1:this.row.length] <- electrode.system[[i]]
}
message(paste0("You did not specify any reference electrode name.\n",
"Here are the options supported by this function (case-insensitive):"))
print(knitr::kable(overview.names))
}
# defining refname in this manner makes sure to get all possible combinations
# but there might be a number of duplicates, but those we can
# get rid of in the next step
electrode <-
data.frame(refname =
# here we create lower-case version of electrode.system,
# a version with symbols (-/) subbed with spaces,
# and a lower-case with symbols subbed with spaces
c(unname(unlist(electrode.system)),
tolower(unname(unlist(electrode.system))),
gsub("[-/]", " ", unname(unlist(electrode.system))),
gsub("[-/]", " ", tolower(unname(unlist(electrode.system))))),
refcanon =
rep(sub("[0-9]$", "", names(unlist(electrode.system))),
4), # this number needs to equal number of elements in c() above!
stringsAsFactors = FALSE)
# detect and remove duplicates
electrode <-
electrode[!duplicated(electrode$refname),]
# reset row numbering in dataframe just for good measure
row.names(electrode) <- 1:dim(electrode)[1]
# pre-allocate the return vector
refcanon <- rep("", length(refname))
# now all we have to do is check each user-submitted refname against
# electrode$refname and return the value on the same row but next column
for (i in 1:length(refname)) {
refcanon[i] <-
electrode$refcanon[which(electrode$refname == refname[i])]
}
return(refcanon)
}
#' Potentials as SHE
#'
#' This function just outputs a tidy dataframe with potential vs SHE for
#' different scales, electrolytes, concentrations, and temperatures.
#' Using data from literature.
#'
#' @return tidy dataframe with the following columns
#' \tabular{ll}{
#' \code{electrode} \tab reference electrode \cr
#' \code{electrolyte} \tab electrolyte \cr
#' \code{conc.num} \tab concentration of electrolyte, mol/L \cr
#' \code{conc.string} \tab concentration of electrolyte, as string, may also note temperature at which conc \cr
#' \code{temp} \tab temperature / degrees Celsius \cr
#' \code{SHE} \tab potential vs SHE / volt \cr
#' \code{sid} \tab set id, just for housekeeping inside this function \cr
#' \code{reference} \tab BibTeX reference \cr
#' \code{dEdT} \tab temperature coefficient / volt/kelvin \cr
#' }
#' @export
potentials.as.SHE <- function() {
# scale name should be one of canonical (see RefCanonicalName)
# follow the convention of "each row one observation" (at different temperatures)
# all potentials vs SHE
potentials <-
as.data.frame(matrix(data =
# electrode # electrolyte # conc/M # conc label # temp # pot vs SHE # set id # ref
c("AgCl/Ag", "NaCl(aq)", "5.9", "saturated", "25", "0.2630", "9", "CRC 97th ed., 97-05-22",
"AgCl/Ag", "KCl(aq)", "3.5", "3.5M at 25C", "10", "0.215", "1", "Sawyer1995",
"AgCl/Ag", "KCl(aq)", "3.5", "3.5M at 25C", "15", "0.212", "1", "Sawyer1995",
"AgCl/Ag", "KCl(aq)", "3.5", "3.5M at 25C", "20", "0.208", "1", "Sawyer1995",
"AgCl/Ag", "KCl(aq)", "3.5", "3.5M at 25C", "25", "0.205", "1", "Sawyer1995",
"AgCl/Ag", "KCl(aq)", "3.5", "3.5M at 25C", "30", "0.201", "1", "Sawyer1995",
"AgCl/Ag", "KCl(aq)", "3.5", "3.5M at 25C", "35", "0.197", "1", "Sawyer1995",
"AgCl/Ag", "KCl(aq)", "3.5", "3.5M at 25C", "40", "0.193", "1", "Sawyer1995",
"AgCl/Ag", "KCl(aq)", "4.2", "saturated", "10", "0.214", "2", "Sawyer1995",
"AgCl/Ag", "KCl(aq)", "4.2", "saturated", "15", "0.209", "2", "Sawyer1995",
"AgCl/Ag", "KCl(aq)", "4.2", "saturated", "20", "0.204", "2", "Sawyer1995",
"AgCl/Ag", "KCl(aq)", "4.2", "saturated", "25", "0.199", "2", "Sawyer1995",
"AgCl/Ag", "KCl(aq)", "4.2", "saturated", "30", "0.194", "2", "Sawyer1995",
"AgCl/Ag", "KCl(aq)", "4.2", "saturated", "35", "0.189", "2", "Sawyer1995",
"AgCl/Ag", "KCl(aq)", "4.2", "saturated", "40", "0.184", "2", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "0.1", "0.1M at 25C", "10", "0.336", "3", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "0.1", "0.1M at 25C", "15", "0.336", "3", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "0.1", "0.1M at 25C", "20", "0.336", "3", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "0.1", "0.1M at 25C", "25", "0.336", "3", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "0.1", "0.1M at 25C", "30", "0.335", "3", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "0.1", "0.1M at 25C", "35", "0.334", "3", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "0.1", "0.1M at 25C", "40", "0.334", "3", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "1.0", "1.0M at 25C", "10", "0.287", "4", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "1.0", "1.0M at 25C", "20", "0.284", "4", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "1.0", "1.0M at 25C", "25", "0.283", "4", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "1.0", "1.0M at 25C", "30", "0.282", "4", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "1.0", "1.0M at 25C", "40", "0.278", "4", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "3.5", "3.5M at 25C", "10", "0.256", "5", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "3.5", "3.5M at 25C", "15", "0.254", "5", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "3.5", "3.5M at 25C", "20", "0.252", "5", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "3.5", "3.5M at 25C", "25", "0.250", "5", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "3.5", "3.5M at 25C", "30", "0.248", "5", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "3.5", "3.5M at 25C", "35", "0.246", "5", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "3.5", "3.5M at 25C", "40", "0.244", "5", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "4.2", "saturated", "10", "0.254", "6", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "4.2", "saturated", "15", "0.251", "6", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "4.2", "saturated", "20", "0.248", "6", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "4.2", "saturated", "25", "0.244", "6", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "4.2", "saturated", "30", "0.241", "6", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "4.2", "saturated", "35", "0.238", "6", "Sawyer1995",
"Hg2Cl2/Hg", "KCl(aq)", "4.2", "saturated", "40", "0.234", "6", "Sawyer1995",
"AVS", "", "", "", "25", "-4.44", "7", "Trasatti1986",
"SHE", "", "", "", "-273.15", "0.00", "8", "Inzelt2013",
"SHE", "", "", "", "0", "0.00", "8", "Inzelt2013",
"SHE", "", "", "", "25", "0.00", "8", "Inzelt2013",
# arbitrary max T=580C (temp at which sodalime glass loses rigidity)
"SHE", "", "", "", "580", "0.00", "8", "Inzelt2013",
"Li", "", "1.0", "1.0M at 25C", "25", "-3.0401", "10", "CRC 97th ed., 97-05-22",
"Na", "", "1.0", "1.0M at 25C", "25", "-2.71", "11", "CRC 97th ed., 97-05-22",
"Mg", "", "1.0", "1.0M at 25C", "25", "-2.372", "12", "CRC 97th ed., 97-05-22"),
ncol = 8,
byrow = TRUE), stringsAsFactors = FALSE)
colnames(potentials) <-
c("electrode",
"electrolyte",
"conc.num",
"conc.string",
"temp",
"SHE",
"sid",
"reference")
# convert these columns to type numeric
potentials[, c("conc.num", "temp", "SHE")] <-
as.numeric(as.character(unlist(potentials[, c("conc.num", "temp", "SHE")])))
# make room for a dE/dT column
potentials$dEdT <- as.numeric(NA)
# calculate temperature coefficient (dE/dT) for each scale, concentration, and electrolyte (ie. set id)
for (s in 1:length(unique(potentials$sid))) {
# sid column eas added to data just to make this calculation here easier
subspot <- potentials[which(potentials$sid == unique(potentials$sid)[s]), ]
# a linear fit will give us temperature coefficient as slope
lm.subspot <- stats::lm(SHE ~ temp, data = subspot)
potentials[which(potentials$sid == unique(potentials$sid)[s]), "dEdT"] <-
lm.subspot$coefficients[2]
}
return(potentials)
}
#' Convert from electrochemical or physical scale to SHE
#'
#' Convert an arbitrary number of potentials against any known electrochemical
#' scale (or the electronic vacuum scale) to potential vs SHE.
#'
#' @param potential potential in volt
#' @param scale name of the original scale
#' @param electrolyte optional, specify electrolyte solution, e.g., "KCl(aq)". Must match value in \code{as.SHE.data$electrolyte}.
#' @param concentration of electrolyte in mol/L, or as the string "saturated"
#' @param temperature of system in degrees Celsius
#' @param as.SHE.data dataframe with dataset
#'
#' @return potential in SHE scale
#' @export
as.SHE <- function(potential,
scale,
electrolyte = "",
concentration = "saturated",
temperature = 25,
as.SHE.data = potentials.as.SHE()) {
# if the supplied temperature does not exist in the data, this function will attempt to interpolate
# note that concentration has to match, no interpolation is attempted for conc
# make this work for arbitrary-length vectors of potential and scale
# make sure potential and scale args have the same length
if (length(potential) == 0 | length(scale) == 0) {
stop("Arguments potential or scale cannot be empty!")
} else if (length(potential) != length(scale)) {
stop("Arguments potential and scale must have equal number of elements")
}
arglength <- length(potential)
# make the args concentration, temperature and electrolyte this same length,
# unless the user supplied them (only necessary for > 1)
if (arglength > 1) {
# handle two cases:
# 1. user did not touch concentration, temperature and electrolyte args.
# Assume they forgot and reset their length and print a message
# 2. user did change concentration or temperature or electrolyte, but still failed to
# ensure length equal to arglength. In this case, abort.
# note: we can get the default value set in the function call using formals()
if (identical(concentration, formals(as.SHE)$concentration) &
identical(temperature, formals(as.SHE)$temperature) &
identical(electrolyte, formals(as.SHE)$electrolyte)) {
# case 1
# message("NOTE: default concentration and temperature values used for all potentials and scales.")
message(paste0("Default concentration (", formals(as.SHE)$concentration, "), temperature (", formals(as.SHE)$temperature, "C) used for all supplied potential and scale values."))
concentration <- rep(concentration, arglength)
temperature <- rep(temperature, arglength)
electrolyte <- rep(electrolyte, arglength)
} else {
# case 2
stop("Concentration, temperature and electrolyte arguments must have the same number of elements as potential and scale!")
}
}
## we can now safely assume that length(<args>) == arglength
# place args into a single dataframe
# this way, we can correlate columns to each other by row
df <-
data.frame(potential = potential,
scale = common::RefCanonicalName(scale),
electrolyte = electrolyte,
concentration = concentration,
temperature = temperature,
stringsAsFactors = FALSE)
# add column to keep track of vacuum scale
df$vacuum <- as.logical(FALSE)
# add column to hold calc potential vs SHE
df$SHE <- as.numeric(NA)
# SHE scale special considerations
# 1. concentration is constant
if (any(df$scale == common::RefCanonicalName("SHE"))) {
df$concentration[which(df$scale == common::RefCanonicalName("SHE"))] <- ""
df$electrolyte[which(df$scale == common::RefCanonicalName("SHE"))] <- ""
}
# AVS scale special considerations
# 1. concentration is meaningless
# 2. direction is opposite of electrochemical scales, requiring change of sign
if (any(df$scale == common::RefCanonicalName("AVS"))) {
# concentration is meaningless for AVS (no electrolyte)
# so for those rows, we'll reset it
df$concentration[which(df$scale == common::RefCanonicalName("AVS"))] <- ""
df$electrolyte[which(df$scale == common::RefCanonicalName("AVS"))] <- ""
df$vacuum[which(df$scale == common::RefCanonicalName("AVS"))] <- TRUE
}
# now just work our way through df, line-by-line to determine potential as SHE
# all necessary conditions should be recorded right here in df
for (p in 1:dim(df)[1]) {
# Fixed a bug 2018-03-04
# Issue: if scale was {Li,Na,Mg} the default electrolyte string "saturated" caused
# zero rows to be returned in the subset.SHE.data match, with error returned to user.
# Fixed by making the matching more step-wise:
# + first, subset against electrode scale. If only one row, done. If more,
# + subset against either conc.string or conc.num. Stop if zero rows (error), otherwise proceed.
subset.scale <- subset(as.SHE.data, electrode == df$scale[p])
if (dim(subset.scale)[1] > 1) {
# continue matching, now against conc.string or conc.num
if (is.character(df$concentration[p])) {
subset.concentration <-
subset(subset.scale, conc.string == df$concentration[p])
} else {
subset.concentration <-
subset(subset.scale, conc.num == df$concentration[p])
}
# stop if the resulting dataframe after matching contains no rows
if (dim(subset.concentration)[1] == 0) {
stop("Sorry, it seems we failed to find any matching entries in potentials.as.SHE().")
}
# Note: it's ok at this point if the resulting df contains more than one row as
# more matching will be done below
# If we haven't had reason to stop(), we should be good
# just housekeeping: rename the variable so we don't have to edit code below
subset.SHE.data <- subset.concentration
} else {
# just housekeeping: rename the variable so we don't have to change the code that follows
subset.SHE.data <- subset.scale
}
# use KCl(aq) as default to avoid aborting
# (good assumption at this point, as we always have KCl for the cases
# where an electrode system has more than one electrolyte)
default.electrolyte <- "KCl(aq)"
# If this subset contains more than one unique electrolyte (e.g., NaCl and KCl)
# the user MUST have made a choice (in the "electrolyte" argument) that results
# in a single electrolyte remaining, or else we will warn and abort
if (length(unique(subset.SHE.data$electrolyte)) > 1) {
# data (in subset.SHE.data) contains more than one electrolyte
# if user did not change electrolyte arg value, use default and issue warning
if (identical(electrolyte, formals(as.SHE)$electrolyte)) {
warning(paste0("You did not specify an electrolyte, but more than one ",
"is available for E = ", df$potential[p], " V vs ", df$scale[p], ".\n",
"Using electrolyte: ", default.electrolyte))
subset.SHE.data <-
subset(subset.SHE.data, electrolyte == default.electrolyte)
} else {
# else the user did change the electrolyte arg, use the user's value
subset.SHE.data <-
subset.SHE.data[which(subset.SHE.data$electrolyte == electrolyte), ]
# print only for debugging - disable before production!
print(subset.SHE.data)
# stop if the resulting dataframe contains no rows
if (dim(subset.SHE.data)[1] == 0) {
stop("Your choice of electrolyte does not match any data!")
}
}
} else {
# data only contains one electrolyte
# just check that it matches whatever the user supplied, if not,
# issue a warning (but don't abort, typically the user did not set it
# because they don't care and want whatever is in the data)
if (unique(subset.SHE.data$electrolyte) != electrolyte) {
warning(paste0("The requested electrolyte: ",
ifelse(electrolyte == "", "<none specified>", electrolyte),
" was not found for E = ", df$potential[p], " V vs ", df$scale[p], ".\n",
"My data only lists one electrolyte for that scale - return value calculated on that basis."))
subset.SHE.data <-
subset(subset.SHE.data, electrolyte == unique(subset.SHE.data$electrolyte))
} else {
subset.SHE.data <-
subset(subset.SHE.data, electrolyte == electrolyte)
}
}
# temperature
# either happens to match a temperature in the dataset, or we interpolate
# (under the assumption that potential varies linearly with temperature)
if (!any(subset.SHE.data$temp == df$temperature[p])) {
# sought temperature was not available in dataset, check that it falls inside
# note: important to use less/more-than-or-equal in case data only contains one value
if ((df$temperature[p] <= max(subset.SHE.data$temp)) &&
(df$temperature[p] >= min(subset.SHE.data$temp))) {
# within dataset range, do linear interpolation
lm.subset <- stats::lm(SHE ~ temp, data = subset.SHE.data)
# interpolated temperature, calculated based on linear regression
# (more accurate than simple linear interpolation with approx())
pot.interp <-
lm.subset$coefficients[2] * df$temperature[p] + lm.subset$coefficients[1]
### CALC POTENTIAL vs SHE
df$SHE[p] <-
ifelse(df$vacuum[p],
pot.interp - df$potential[p],
pot.interp + df$potential[p])
}
} else {
# requested temperature does exist in dataset
### CALC POTENTIAL vs SHE
df$SHE[p] <-
ifelse(df$vacuum[p],
subset(subset.SHE.data, temp == df$temperature[p])$SHE - df$potential[p],
subset(subset.SHE.data, temp == df$temperature[p])$SHE + df$potential[p])
}
}
return(df$SHE)
}
#' Convert from SHE scale to another electrochemical or physical scale
#'
#' Convert an arbitrary number of potentials vs SHE to another electrochemical
#' scale (or the vacuum scale).
#' The available target scales are those listed by \code{\link{potentials.as.SHE}}.
#'
#' @param potential potential in volt
#' @param scale name of the target scale
#' @param electrolyte optional, specify electrolyte solution, e.g., "KCl(aq)". Must match one of the values in \code{\link{potentials.as.SHE}$electrolyte}
#' @param concentration of electrolyte in mol/L, or as the string "saturated"
#' @param temperature of system in degrees Celsius
#' @param as.SHE.data by default this parameter reads the full dataset \code{\link{potentials.as.SHE}}
#'
#' @return potential in the specified target scale
#' @export
from.SHE <- function(potential,
scale,
electrolyte = "",
concentration = "saturated",
temperature = 25,
as.SHE.data = potentials.as.SHE()) {
# make this work for arbitrary-length vectors of potential and scale
# make sure potential and scale args have the same length
if (length(potential) == 0 | length(scale) == 0) {
stop("Arguments potential or scale cannot be empty!")
} else if (length(potential) != length(scale)) {
stop("Arguments potential and scale must have the same number of elements")
}
arglength <- length(potential)
# make the args concentration, temperature and electrolyte this same length,
# unless the user supplied them (only necessary for > 1)
if (arglength > 1) {
# handle two cases:
# 1. user did not touch concentration, temperature and electrolyte args.
# Assume they forgot and reset their length and print a message
# 2. user did change concentration or temperature or electrolyte, but still failed to
# ensure length equal to arglength. In this case, abort.
# note: we can get the default value set in the function call using formals()
if (identical(concentration, formals(from.SHE)$concentration) &
identical(temperature, formals(from.SHE)$temperature) &
identical(electrolyte, formals(from.SHE)$electrolyte)) {
# case 1
message(paste0("Default concentration (", formals(from.SHE)$concentration, "), temperature (", formals(from.SHE)$temperature, "C) used for all supplied potential and scale values."))
concentration <- rep(concentration, arglength)
temperature <- rep(temperature, arglength)
electrolyte <- rep(electrolyte, arglength)
} else {
# case 2
stop("Concentration, temperature and electrolyte arguments must have the same number of elements as potential and scale!")
}
}
## we can now safely assume that length(<args>) == arglength
# place args into a single dataframe
# this way, we can correlate columns to each other by row
df <-
data.frame(potential = potential, # vs SHE
scale = common::RefCanonicalName(scale), # target scale
electrolyte = electrolyte,
concentration = concentration,
temperature = temperature,
stringsAsFactors = FALSE)
# # add column to keep track of vacuum scale
# df$vacuum <- as.logical(FALSE)
# # add column to hold calc potential vs target scale
# df$targetscale <- as.numeric(NA)
## Special considerations
# SHE scale independent of concentration, per definition
if (any(df$scale == common::RefCanonicalName("SHE"))) {
df$concentration[which(df$scale == common::RefCanonicalName("SHE"))] <- ""
df$electrolyte[which(df$scale == common::RefCanonicalName("SHE"))] <- ""
}
# AVS scale: concentration is meaningless (no electrolyte)
if (any(df$scale == common::RefCanonicalName("AVS"))) {
df$concentration[which(df$scale == common::RefCanonicalName("AVS"))] <- ""
df$electrolyte[which(df$scale == common::RefCanonicalName("AVS"))] <- ""
}
for (p in 1:dim(df)[1]) {
# First, subset against electrode scale. If as.SHE.data only contains one row
# for this electrode scale we are DONE. If not, proceed to subset against concentration
subset.scale <- subset(as.SHE.data, electrode == df$scale[p])
if (dim(subset.scale)[1] > 1) {
# continue matching, now against conc.string or conc.num
if (is.character(df$concentration[p])) {
subset.concentration <-
subset(subset.scale, conc.string == df$concentration[p])
} else {
subset.concentration <-
subset(subset.scale, conc.num == df$concentration[p])
}
# stop if the resulting dataframe after matching contains no rows
if (dim(subset.concentration)[1] == 0) {
stop("Sorry, it seems we failed to find any matching entries in potentials.as.SHE().")
}
# Note: it's ok at this point if the resulting df contains more than one row as
# more matching will be done below
# If we haven't had reason to stop(), we should be good
# just housekeeping: rename the variable so we don't have to edit code below
subset.SHE.data <- subset.concentration
} else {
# just housekeeping again
subset.SHE.data <- subset.scale
}
# use KCl(aq) as default to avoid aborting
# (good assumption at this point, as we always have KCl for the cases
# where an electrode system has more than one electrolyte)
default.electrolyte <- "KCl(aq)"
# If this subset contains more than one unique electrolyte (e.g., NaCl and KCl)
# the user MUST have made a choice (in the "electrolyte" argument) that results
# in a single electrolyte remaining, or else we will warn and abort
if (length(unique(subset.SHE.data$electrolyte)) > 1) {
# data (in subset.SHE.data) contains more than one electrolyte
# if user did not change electrolyte arg value, use default and issue warning
if (identical(electrolyte, formals(as.SHE)$electrolyte)) {
warning(paste0("You did not specify an electrolyte, but more than one ",
"is available for E = ", df$potential[p], " V vs ", df$scale[p], ".\n",
"We'll use the default electrolyte: ", default.electrolyte))
subset.SHE.data <-
subset(subset.SHE.data, electrolyte == default.electrolyte)
} else {
# else the user did change the electrolyte arg, use the user's value
subset.SHE.data <-
subset.SHE.data[which(subset.SHE.data$electrolyte == electrolyte), ]
# print only for debugging - disable before production!
print(subset.SHE.data)
# stop if the resulting dataframe contains no rows
if (dim(subset.SHE.data)[1] == 0) {
stop("Your choice of electrolyte does not match any data!")
}
}
} else {
# data only contains one electrolyte
# just check that it matches whatever the user supplied, if not,
# issue a warning (but don't abort, typically the user did not set it
# because they don't care and want whatever is in the data)
if (unique(subset.SHE.data$electrolyte) != electrolyte) {
warning(paste0("The requested electrolyte: ",
ifelse(electrolyte == "", "<none specified>", electrolyte),
" was not found for E = ", df$potential[p], " V vs ", df$scale[p], ".\n",
"My data only lists one electrolyte for that scale - return value calculated on that basis."))
subset.SHE.data <-
subset(subset.SHE.data, electrolyte == unique(subset.SHE.data$electrolyte))
} else {
subset.SHE.data <-
subset(subset.SHE.data, electrolyte == electrolyte)
}
}
# temperature
# either happens to match a temperature in the dataset, or we interpolate
# (under the assumption that potential varies linearly with temperature)
if (!any(subset.SHE.data$temp == df$temperature[p])) {
# sought temperature was not available in dataset, check that it falls inside
# note: important to use less/more-than-or-equal in case data only contains one value
if ((df$temperature[p] <= max(subset.SHE.data$temp)) &&
(df$temperature[p] >= min(subset.SHE.data$temp))) {
# within dataset range, do linear interpolation
lm.subset <- stats::lm(SHE ~ temp, data = subset.SHE.data)
# interpolated temperature, calculated based on linear regression
# (more accurate than simple linear interpolation with approx())
pot.interp <-
lm.subset$coefficients[2] * df$temperature[p] + lm.subset$coefficients[1]
message("Calc potential using interp temperature")
### CALC POTENTIAL vs requested scale
if (df$scale[p] == common::RefCanonicalName("AVS")) {
# message("Target scale is AVS")
df$potentialvsscale[p] <-
pot.interp - df$potential[p]
} else {
# message("Target scale is not AVS")
df$potentialvsscale[p] <-
df$potential[p] - pot.interp
}
}
} else {
# requested temperature does exist in dataset
### CALC POTENTIAL vs requested scale
message("Calc potential using exact temperature match")
if (df$scale[p] == common::RefCanonicalName("AVS")) {
# message("Target scale is AVS")
df$potentialvsscale[p] <-
subset(subset.SHE.data, temp == df$temperature[p])$SHE - df$potential[p]
} else {
# message("Target scale is not AVS")
df$potentialvsscale[p] <-
df$potential[p] - subset(subset.SHE.data, temp == df$temperature[p])$SHE
}
}
}
return(df$potentialvsscale)
}
#' ConvertRefPotEC
#'
#' This function does the heavy lifting.
#' Converts from an electrochemical reference scale into another.
#' SHE: standard hydrogen electrode
#' Ag/AgCl: silver silver-chloride electrode (3M KCl)
#' SCE: saturated calomel electrode
#'
#' @param argpotential potential (numeric)
#' @param argrefscale input reference scale (character string)
#' @param valuerefscale output reference scale (character string)
#'
#' @return potential in output reference scale (numeric)
ConvertRefPotEC <- function(argpotential, argrefscale, valuerefscale) {
.Deprecated("as.SHE")
##### Add more reference electrodes here >>
refpotatSHEzero <- c( 0, -0.21, -0.24, 3)
refrownames <- c( "SHE", "Ag/AgCl", "SCE", "Li/Li+")
refcolnames <- c("SHE0", "AgCl0", "SCE0", "Li0")
##### Add more reference electrodes here <<
#
SHE0 <-
data.frame(matrix(refpotatSHEzero,
ncol = length(refpotatSHEzero),
byrow = T))
refpotmtx <- matrix(NA, length(SHE0), length(SHE0))
refpotmtx[,1] <- matrix(as.matrix(SHE0), ncol = 1, byrow = T)
for (c in 2:length(SHE0)) {
# loop over columns (except the first)
for (r in 1:length(SHE0)) {
# loop over rows
refpotmtx[r, c] <- refpotmtx[r, 1] - refpotmtx[c, 1]
}
}
refpotdf <- as.data.frame(refpotmtx)
names(refpotdf) <- refcolnames
row.names(refpotdf) <- refrownames
## So far we have made a matrix of all the possible combinations,
## given the vector refpotatSHEzero. The matrix is not strictly necessary,
## but it may prove useful later. It does.
#
# Match argrefscale to the refrownames
argmatch <- match(argrefscale, refrownames, nomatch = 0)
# Match valuerefscale to the refrownames
valuematch <- match(valuerefscale, refrownames, nomatch = 0)
# We simply assume that the match was well-behaved
valuepotential <- argpotential + refpotdf[valuematch, argmatch]
# Check that arg and value electrodes are within bounds for a match
if (argmatch == 0 || valuematch == 0) {
# No match
# Perform suitable action
message("Arg out of bounds in call to ConvertRefPot")
valuepotential <- NA
}
return(valuepotential)
}
#' Convert from one electrochemical scale to another
#'
#' @param argpotential potential (numeric)
#' @param argrefscale input reference scale (char string)
#' @param valuerefscale output reference scale (char string)
#'
#' @return potential in output reference scale (numeric)
#' @export
ConvertRefPot <- function(argpotential, argrefscale, valuerefscale) {
.Deprecated("as.SHE")
# You should check that argpotential is valid numeric
# IDEA: make a matrix out of these (scale names and flags)
# Valid scales
scale.names <- list()
scale.names[["SHE"]] <- c("SHE", "NHE", "she", "nhe")
scale.names[["AgCl"]] <- c("Ag/AgCl", "AgCl", "ag/agcl", "agcl")
scale.names[["SCE"]] <- c("SCE", "sce")
scale.names[["Li"]] <- c("Li/Li+", "Li", "Li+", "li", "li+", "li/li+")
scale.names[["AVS"]] <- c("AVS", "avs")
# Set flags
bool.flags <-
as.data.frame(matrix(0,
nrow = length(scale.names),
ncol = 2))
names(bool.flags) <- c("argref", "valueref")
row.names(bool.flags) <- names(scale.names)
# argrefscale
# Check that argrefscale is valid character mode
# ...
# steps through all scale names, "row-by-row",
# looking for any cell matching "argrefscale" string
# if found, save the position of that refelectrode (in scale.names) to
# that row and "argref" column of bool.flags
for (j in 1:length(row.names(bool.flags))) {
if (any(scale.names[[row.names(bool.flags)[j]]] == argrefscale)) {
bool.flags[row.names(bool.flags)[j], "argref"] <- j
}
}
# valuerefscale
# Check that valuerefscale is valid character mode
# ...
for (k in 1:length(row.names(bool.flags))) {
if (any(scale.names[[row.names(bool.flags)[k]]] == valuerefscale)) {
bool.flags[row.names(bool.flags)[k], "valueref"] <- k
}
}
# Depending on which flags are set, call the corresponding function
decision.vector <- colSums(bool.flags)
# Check if both scales are the same (no conversion needed). If so, abort gracefully.
# ...
if (decision.vector["argref"] == 5 || decision.vector["valueref"] == 5) {
# AVS is requested, deal with it it
if (decision.vector["argref"] == 5) {
# Conversion _from_ AVS
rnpotential <- ConvertRefPotEC(AVS2SHE(argpotential),
"SHE",
scale.names[[decision.vector["valueref"]]][1])
}
if (decision.vector["valueref"] == 5) {
# Conversion _to_ AVS
rnpotential <- SHE2AVS(ConvertRefPotEC(argpotential,
scale.names[[decision.vector["argref"]]][1],
"SHE"))
}
} else {
rnpotential <- ConvertRefPotEC(argpotential,
scale.names[[decision.vector["argref"]]][1],
scale.names[[decision.vector["valueref"]]][1])
}
return(rnpotential)
}