Document exdf columns by specifying units and categories — set_variable • PhotoGEA

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Sets the value, units, and/or category of a new or existing column of an exdf object.

Usage

set_variable(
    exdf_obj,
    name,
    units = NULL,
    category = NULL,
    value = NA,
    id_column = NULL,
    value_table = list()
  )

Arguments

exdf_obj: An exdf object.
name: The name of the column to be added to exdf_obj.
units: The units of the column to be added to exdf_obj.
category: The category of the column to be added to exdf_obj.
value: The value of the column to be added to exdf_obj.
id_column: The name of an identifier column in exdf_obj.
value_table: A list of named elements, where the name of each element is a possible value of the id_column and the value of each element is the corresponding value that the name column should take.

Details

This function attempts to set the value of a new or existing column in an exdf object according to the following rules:

The value of the name column of exdf_obj will be set to value; this assignment follows the usual rules; in other words, value could be a single value or a vector of length nrow(exdf_obj).
If units and categories are both NULL, the units and category will not be specified. In this case, if the name column already exists, its units and category will remain the same; if the name column is new, it will be initialized with NA for its units and category.
If either units _or_ category is not NULL, the units and category for the name column _will_ be specified. In this case, if one of units or category _is_ NULL, its value will be set to NA.
If id_column is not NULL, then the value_table will be used to set different values of the name column for each specified value of id_column. For example, if id_column is species and value_table = list(soybean = 1, tobacco = 2), then the name column will be set to 1 when species is 'soybean' and 2 when species is 'tobacco'. For any other values of species (such as 'maize'), the value of name will still be value. **Note**: values of the id_column will be converted using as.character before making comparisons.

Value

An exdf object with new and/or modified columns.

See also

Examples

# Create a simple exdf object with two columns (`A` and `B`) and default values
# for its units and categories.
simple_exdf <- exdf(data.frame(A = c(3, 2, 7, 9), B = c(4, 5, 1, 8)))

print(simple_exdf)
#>   A [NA] (NA) B [NA] (NA)
#> 1           3           4
#> 2           2           5
#> 3           7           1
#> 4           9           8

# Add a new column called 'C' with units 'u1' and category 'cat1' whose value is
# 1000.
simple_exdf <- set_variable(simple_exdf, 'C', 'u1', 'cat1', 1000)

# Set the value of the 'B' column to 2000 when 'A' is 3, to 3000 when 'A' is 9,
# and to 4000 for all other values of 'A'. Do not modify its units or category.
simple_exdf <- set_variable(
  simple_exdf,
  'B',
  value = 4000,
  id_column = 'A',
  value_table = list('3' = 2000, '9' = 3000)
)

print(simple_exdf)
#>   A [NA] (NA) B [NA] (NA) C [cat1] (u1)
#> 1           3        2000          1000
#> 2           2        4000          1000
#> 3           7        4000          1000
#> 4           9        3000          1000

# As a more realistic example, load a Licor file and set different values of
# mesophyll conductance for each species in the data set.
licor_file <- read_gasex_file(
  PhotoGEA_example_file_path('ball_berry_1.xlsx')
)

licor_file <- set_variable(
  licor_file,
  'gmc',
  'mol m^(-2) s^(-1) bar^(-1)',
  '',
  id_column = 'species',
  value_table = list(soybean = 0.9, tobacco = 1.1)
)

print(licor_file[, c('species', 'gmc'), TRUE])
#>    species [UserDefCon] (NA) gmc [] (mol m^(-2) s^(-1) bar^(-1))
#> 1                    soybean                                 0.9
#> 2                    soybean                                 0.9
#> 3                    soybean                                 0.9
#> 4                    soybean                                 0.9
#> 5                    soybean                                 0.9
#> 6                    soybean                                 0.9
#> 7                    soybean                                 0.9
#> 8                    soybean                                 0.9
#> 9                    soybean                                 0.9
#> 10                   soybean                                 0.9
#> 11                   soybean                                 0.9
#> 12                   soybean                                 0.9
#> 13                   soybean                                 0.9
#> 14                   soybean                                 0.9
#> 15                   soybean                                 0.9
#> 16                   soybean                                 0.9
#> 17                   soybean                                 0.9
#> 18                   soybean                                 0.9
#> 19                   soybean                                 0.9
#> 20                   soybean                                 0.9
#> 21                   soybean                                 0.9
#> 22                   tobacco                                 1.1
#> 23                   tobacco                                 1.1
#> 24                   tobacco                                 1.1
#> 25                   tobacco                                 1.1
#> 26                   tobacco                                 1.1
#> 27                   tobacco                                 1.1
#> 28                   tobacco                                 1.1