Finds the ranges df of this redox sensor at given inaccuracies — ranges

Adding this method on 31 May 2020, hoping this style will depreciate getErrorTable in the future.

# S4 method for redoxSensor
ranges_df(
  object,
  inaccuracies = c(0.02),
  Emin = -400,
  Emax = -200,
  temp = 295.15,
  by = 0.01,
  name = "Sensor",
  thresholds = c(0.5, 1, 1.5, 2, 2.5)
)

Arguments

object	A redoxSensor object
inaccuracies	(optional, default: c(0.02)) A vector of inaccuracies (e.g. 0.02 for 2% error), always relative
Emin	(optional, default: -400) The minimum redox potential, in mV, for which to record error
Emax	(optional, default: -200) The maximum redox potential, in mV, for which to record error
temp	(optional, default: 295.15) the temperature (in Kelvin) at which measurements were made
by	(optional, default: 0.01) The granularity of the error table--e.g., by = 0.01 would record 275 and 275.01, etc.
name	(optional, default: "Sensor") A name for this sensor
thresholds	A vector of error thresholds (e.g. c(0.5, 1) for 0.5mV and 1mV)

Value

A dataframe of suited ranges with these columns: 'Sensor_Name': the name of the sensor 'Minimum': the minimum redox potential (mV) measurable at the given inaccuracy 'Maximum': the maximum redox potential (mV) measurable at the given inaccuracy 'Inaccuracy': the inaccuracy associated with this row (relative) 'error_thresh': the error threshold associated with this row (mV)

Examples

my_sensor <- new("redoxSensor", new("Sensor", Rmin = 1, Rmax = 5, delta = 0.2), e0 = -250)
ranges_df(my_sensor)
#>   Sensor_Name Minimum Maximum Inaccuracy error_thresh
#> 1 Sensor_0.02      NA      NA       0.02          0.5
#> 2 Sensor_0.02 -256.99 -222.08       0.02          1.0
#> 3 Sensor_0.02 -264.86 -214.32       0.02          1.5
#> 4 Sensor_0.02 -269.44 -209.77       0.02          2.0
#> 5 Sensor_0.02 -272.67 -206.56       0.02          2.5