fit_t_response(
  data,
  varnames = list(Par = "Par", T_leaf = "T_leaf"),
  model = c("Arrhenius", "Kruse", "Heskel", "Medlyn", "MMRT", "Quadratic", "Topt"),
  start = list(a = 1, b = 1, c = 1, dEa = 1, Ea_ref = 1, Par_ref = 1, Ea = 40000, Par25
    = 50, Hd = 2e+05, dS = 650, dCp = 1, dG = 1, dH = 1),
  setvar = "none",
  hdset = 2e+05,
  dSset = 650,
  title = NULL,
  ...
)

# Read in data
data <- read.csv(system.file("extdata", "A_Ci_T_data.csv",
  package = "photosynthesis"
),
stringsAsFactors = FALSE
)

library(tidyr)

# Round temperatures to group them appropriately
# Use sequential rounding
data$T2 <- round(data$Tleaf, 1)
data$T2 <- round(data$Tleaf, 0)

# Look at unique values to detect rounding issues
unique(data$T2)

# Some still did not round correctly,
# manually correct
for (i in 1:nrow(data)) {
  if (data$T2[i] == 18) {
    data$T2[i] <- 17
  }
  if (data$T2[i] == 23) {
    data$T2[i] <- 22
  }
  if (data$T2[i] == 28) {
    data$T2[i] <- 27
  }
  if (data$T2[i] == 33) {
    data$T2[i] <- 32
  }
  if (data$T2[i] == 38) {
    data$T2[i] <- 37
  }
}

# Make sure it is a character string for grouping
data$T2 <- as.character(data$T2)

# Create grouping variable by ID and measurement temperature
data <- unite(data,
  col = "ID2", c("ID", "T2"),
  sep = "_"
)

# Split by temperature group
data <- split(data, data$ID2)

# Obtain mean temperature for group so temperature
# response fitting is acceptable later, round to
# 2 decimal places
for (i in 1:length(data)) {
  data[[i]]$Curve_Tleaf <- round(mean(data[[i]]$Tleaf), 2)
}

# Convert from list back to dataframe
data <- do.call("rbind", data)

# Parse grouping variable by ID and measurement temperature
data <- separate(data,
  col = "ID2", into = c("ID", "T2"),
  sep = "_"
)

# Make sure number of values matches number of measurement
# temperatures. May vary slightly if plants had slightly
# different leaf temperatures during the measurements
unique(data$Curve_Tleaf)

# Create ID column to curve fit by ID and temperature
data <- unite(data,
  col = "ID2", c("ID", "Curve_Tleaf"),
  sep = "_"
)

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

# Fit many CO2 response curves
fits2 <- fit_many(
  data = data,
  group = "ID2",
  varnames = list(
    A_net = "A",
    C_i = "Ci",
    T_leaf = "T_leaf",
    PPFD = "Qin",
    g_mc = "g_mc"
  ),
  funct = fit_aci_response,
  alphag = 0
)

# Extract ACi parameters
pars <- compile_data(fits2,
  output_type = "dataframe",
  list_element = 1
)

# Extract ACi graphs
graphs <- compile_data(fits2,
  output_type = "list",
  list_element = 2
)

# Parse the ID variable
pars <- separate(pars, col = "ID", into = c("ID", "Curve_Tleaf"), sep = "_")

# Make sure curve leaf temperature is numeric
pars$Curve_Tleaf <- as.numeric(pars$Curve_Tleaf)
pars$T_leaf <- pars$Curve_Tleaf + 273.15

# Fit all models, set Hd to constant in Medlyn model
out <- fit_t_response(
  data = pars[pars$ID == "S2", ],
  varnames = list(
    Par = "V_cmax",
    T_leaf = "T_leaf"
  ),
  setvar = "Hd",
  hdset = 200000
)

out[["Arrhenius"]][["Graph"]]
out[["Heskel"]][["Graph"]]
out[["Kruse"]][["Graph"]]
out[["Medlyn"]][["Graph"]]
out[["MMRT"]][["Graph"]]
out[["Quadratic"]][["Graph"]]
out[["Topt"]][["Graph"]]