tests/testthat/_snaps/utils.md

In postcard: Estimating Marginal Effects with Prognostic Covariate Adjustment

deparse_fun_body produces character string of function body

Code
  extpkg_body
Output
  [1] "UseMethod(\"t\")"

Code
  predef_body
Output
  [1] "{\n    z <- x + y\n    return(z)\n}"

is_response_in_data correctly gives error when column not in data [plain]

Code
  is_response_in_data(formula = C ~ A, data = dat)
Condition
  Error in `is_response_in_data()`:
  ! Tried to create formula to fit prognostic model but did not find the response variable `C` specified in the primary formula. Provide a formula manually through the argument `prog_formula`.

is_response_in_data correctly gives error when column not in data [ansi]

Code
  is_response_in_data(formula = C ~ A, data = dat)
Condition
  [1m[33mError[39m in `is_response_in_data()`:[22m
  [1m[22m[33m![39m Tried to create formula to fit prognostic model but did not find the response variable `C` specified in the primary formula. Provide a formula manually through the argument `prog_formula`.

is_response_in_data correctly gives error when column not in data [unicode]

Code
  is_response_in_data(formula = C ~ A, data = dat)
Condition
  Error in `is_response_in_data()`:
  ! Tried to create formula to fit prognostic model but did not find the response variable `C` specified in the primary formula. Provide a formula manually through the argument `prog_formula`.

is_response_in_data correctly gives error when column not in data [fancy]

Code
  is_response_in_data(formula = C ~ A, data = dat)
Condition
  [1m[33mError[39m in `is_response_in_data()`:[22m
  [1m[22m[33m![39m Tried to create formula to fit prognostic model but did not find the response variable `C` specified in the primary formula. Provide a formula manually through the argument `prog_formula`.

print_symbolic_differentiation provides message [plain]

Code
  print_symbolic_differentiation(ate, "psi1", add_string = "test string add")
Message
  i Symbolically deriving partial derivative of the function 'psi1 - psi0' with respect to 'psi1' as: '1'.
  * test string add
Output
  function (psi0, psi1) 
  1

print_symbolic_differentiation provides message [ansi]

Code
  print_symbolic_differentiation(ate, "psi1", add_string = "test string add")
Message
  [36mi[39m Symbolically deriving partial derivative of the function 'psi1 - psi0' with respect to 'psi1' as: '1'.
  * test string add
Output
  function (psi0, psi1) 
  1

print_symbolic_differentiation provides message [unicode]

Code
  print_symbolic_differentiation(ate, "psi1", add_string = "test string add")
Message
  ℹ Symbolically deriving partial derivative of the function 'psi1 - psi0' with respect to 'psi1' as: '1'.
  • test string add
Output
  function (psi0, psi1) 
  1

print_symbolic_differentiation provides message [fancy]

Code
  print_symbolic_differentiation(ate, "psi1", add_string = "test string add")
Message
  [36mℹ[39m Symbolically deriving partial derivative of the function 'psi1 - psi0' with respect to 'psi1' as: '1'.
  • test string add
Output
  function (psi0, psi1) 
  1

postcard documentation built on April 12, 2025, 1:57 a.m.