View source: R/plot_c3_aci_fit.R
| plot_c3_aci_fit | R Documentation |
Plots the output from fit_c3_aci or
fit_c3_variable_j.
plot_c3_aci_fit(
fit_results,
identifier_column_name,
x_name,
plot_operating_point = TRUE,
plot_Ad = FALSE,
a_column_name = 'A',
cc_column_name = 'Cc',
ci_column_name = 'Ci',
...
)
fit_results |
A list of three |
identifier_column_name |
The name of a column in each element of |
x_name |
The name of the column that should be used for the x-axis in the plot. This
should refer to either |
plot_operating_point |
A logical value indicating whether to plot the operating point. |
plot_Ad |
A logical value indicating whether to plot the RuBP-depletion-limited net
CO2 assimilation rate ( |
a_column_name |
The name of the columns in the elements of |
cc_column_name |
The name of the columns in the elements of |
ci_column_name |
The name of the columns in the elements of |
... |
Additional arguments to be passed to |
This is a convenience function for plotting the results of a C3 A-Ci curve
fit. It is typically used for displaying several fits at once, in which case
fit_results is actually the output from calling
consolidate on a list created by calling by.exdf
with FUN = fit_c3_aci or FUN = fit_c3_variable_j.
The resulting plot will show curves for the fitted rates An, Ac,
Aj, and Ap, along with points for the measured values of
A, and (optionally) the estimated operating point. The x-axis can be
set to either Ci or Cc.
Internally, this function uses xyplot to perform the
plotting. Optionally, additional arguments can be passed to xyplot.
These should typically be limited to things like xlim, ylim,
main, and grid, since many other xyplot arguments will be
set internally (such as xlab, ylab, auto, and others).
See the help file for fit_c3_aci for an example using this
function.
A trellis object created by lattice::xyplot.
# Read an example Licor file included in the PhotoGEA package
licor_file <- read_gasex_file(
PhotoGEA_example_file_path('c3_aci_1.xlsx')
)
# Define a new column that uniquely identifies each curve
licor_file[, 'species_plot'] <-
paste(licor_file[, 'species'], '-', licor_file[, 'plot'] )
# Organize the data
licor_file <- organize_response_curve_data(
licor_file,
'species_plot',
c(9, 10, 16),
'CO2_r_sp'
)
# Calculate the total pressure in the Licor chamber
licor_file <- calculate_total_pressure(licor_file)
# Calculate temperature-dependent values of C3 photosynthetic parameters
licor_file <- calculate_temperature_response(licor_file, c3_temperature_param_bernacchi)
# For these examples, we will use a faster (but sometimes less reliable)
# optimizer so they run faster
optimizer <- optimizer_nmkb(1e-7)
# Fit all curves in the data set
aci_results <- consolidate(by(
licor_file,
licor_file[, 'species_plot'],
fit_c3_aci,
Ca_atmospheric = 420,
optim_fun = optimizer
))
# View the fits for each species / plot
plot_c3_aci_fit(aci_results, 'species_plot', 'Ci')
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