Running 2-parameter sensitivity analyses

Running 2-parameter sensitivity analyses

analyze_sensitivity(
  data,
  funct,
  test1 = NA,
  values1,
  test2 = NA,
  values2,
  element_out = 1,
  ...
)

Arguments

data

Dataframe

funct

Function to use - do not use parentheses

test1

Input parameter to vary and test

values1

Values of test1 to use

test2

Input parameter to vary and test

values2

Values of test2 to use

element_out

List element to compile

...

Additional arguments required for the function

Value

analyze_sensitivity runs a 2-parameter sensitivity analysis. Note that any parameter value combinations that break the input function WILL break this function. For 1-parameter sensitivity analysis, use test1 only.

Examples

# \donttest{
# Read in your data
# Note that this data is coming from data supplied by the package
# hence the complicated argument in read.csv()
# This dataset is a CO2 by light response curve for a single sunflower
data <- read.csv(system.file("extdata", "A_Ci_Q_data_1.csv",
  package = "photosynthesis"
))

# Define a grouping factor based on light intensity to split the ACi
# curves
data$Q_2 <- as.factor((round(data$Qin, digits = 0)))

# Convert leaf temperature to K
data$T_leaf <- data$Tleaf + 273.15

# Run a sensitivity analysis on gamma_star and mesophyll conductance
# at 25 Celsius for one individual curve
# pars <- analyze_sensitivity(
#   data = data[data$Q_2 == 1500, ],
#   funct = fit_aci_response,
#   varnames = list(
#     A_net = "A",
#     T_leaf = "T_leaf",
#     C_i = "Ci",
#     PPFD = "Qin"
#   ),
#   useg_mct = TRUE,
#   test1 = "gamma_star25",
#   element_out = 1,
#   test2 = "g_mc25",
#   fitTPU = TRUE,
#   Ea_gamma_star = 0,
#   Ea_g_mc = 0,
#   values1 = seq(
#     from = 20,
#     to = 40,
#     by = 2
#   ),
#   values2 = seq(
#     from = 0.5,
#     to = 2,
#     by = 0.1
#   )
# )

# Graph V_cmax
# ggplot(pars, aes(x = gamma_star25, y = g_mc25, z = V_cmax)) +
#   geom_tile(aes(fill = V_cmax)) +
#   labs(
#     x = expression(Gamma * "*"[25] ~ "(" * mu * mol ~ mol^
#       {
#         -1
#       } * ")"),
#     y = expression(g[m][25] ~ "(" * mu * mol ~ m^{
#       -2
#     } ~ s^{
#       -1
#     } ~ Pa^
#       {
#         -1
#       } * ")")
#   ) +
#   scale_fill_distiller(palette = "Greys") +
#   geom_contour(colour = "Black", size = 1) +
#   theme_bw()
# # }