validate_no_formula_duplication: Ensure no duplicate terms appear in 'formula'
In DavisVaughan/hardhat: Construct Modeling Packages

Description Usage Arguments Value Validation See Also Examples

validate - asserts the following:

formula must not have duplicates terms on the left and right hand side of the formula.

check - returns the following:

ok A logical. Does the check pass?
duplicates A character vector. The duplicate terms.

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validate_no_formula_duplication(formula, original = FALSE)

check_no_formula_duplication(formula, original = FALSE)

`formula`	A formula to check.
`original`	A logical. Should the original names be checked, or should the names after processing be used? If `FALSE`, `y ~ log(y)` is allowed because the names are `"y"` and `"log(y)"`, if `TRUE`, `y ~ log(y)` is not allowed because the original names are both `"y"`.

validate_no_formula_duplication() returns formula invisibly.

check_no_formula_duplication() returns a named list of two components, ok and duplicates.

hardhat provides validation functions at two levels.

check_*(): check a condition, and return a list. The list always contains at least one element, ok, a logical that specifies if the check passed. Each check also has check specific elements in the returned list that can be used to construct meaningful error messages.
validate_*(): check a condition, and error if it does not pass. These functions call their corresponding check function, and then provide a default error message. If you, as a developer, want a different error message, then call the check_*() function yourself, and provide your own validation function.

Other validation functions: validate_column_names(), validate_outcomes_are_binary(), validate_outcomes_are_factors(), validate_outcomes_are_numeric(), validate_outcomes_are_univariate(), validate_prediction_size(), validate_predictors_are_numeric()

# All good
check_no_formula_duplication(y ~ x)

# Not good!
check_no_formula_duplication(y ~ y)

# This is generally okay
check_no_formula_duplication(y ~ log(y))

# But you can be more strict
check_no_formula_duplication(y ~ log(y), original = TRUE)

# This would throw an error
try(validate_no_formula_duplication(log(y) ~ log(y)))