print_graphs | R Documentation |
Printing graphs to system
print_graphs(
data,
path,
output_type = "jpeg",
height = 5,
width = 5,
res = 600,
units = "in",
pdf_filename,
...
)
data |
List of graphs |
path |
File path for printing our graphs. Use "./" to set to current working directory |
output_type |
Type of output file, jpeg or pdf |
height |
Height of jpegs |
width |
Width of jpegs |
res |
Resolution of jpegs |
units |
Units of height and width |
pdf_filename |
Filename for pdf option |
... |
Further arguments for jpeg() and pdf() |
print_graphs creates graph files in current working directory from a list of graphs
# 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"
))
# Fit many AQ curves
# Set your grouping variable
# Here we are grouping by CO2_s and individual
data$C_s <- (round(data$CO2_s, digits = 0))
# For this example we need to round sequentially due to CO2_s setpoints
data$C_s <- as.factor(round(data$C_s, digits = -1))
# To fit one AQ curve
fit <- fit_aq_response(data[data$C_s == 600, ],
varnames = list(
A_net = "A",
PPFD = "Qin"
)
)
# Print model summary
summary(fit[[1]])
# Print fitted parameters
fit[[2]]
# Print graph
fit[[3]]
# Fit many curves
fits <- fit_many(
data = data,
varnames = list(
A_net = "A",
PPFD = "Qin",
group = "C_s"
),
funct = fit_aq_response,
group = "C_s"
)
# Look at model summary for a given fit
# First set of double parentheses selects an individual group value
# Second set selects an element of the sublist
summary(fits[[3]][[1]])
# Print the parameters
fits[[3]][[2]]
# Print the graph
fits[[3]][[3]]
# Compile graphs into a list for plotting
fits_graphs <- compile_data(fits,
list_element = 3
)
# Print graphs to pdf
# Uncomment to run
# print_graphs(data = fits_graphs,
# output_type = "pdf",
# path = tempdir(),
# pdf_filename = "mygraphs.pdf")
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