data-frame-predicates {scrutiny}

Is an object a consistency test output tibble?

Description

• is_map_df() tests whether an object is the output of a scrutiny-style mapper function for consistency tests, like grim_map(). These mapper functions also include those produced by function_map(), function_map_seq(), and function_map_total_n().

• is_map_basic_df() is a variant of is_map_df() that tests whether an object is the output of a "basic" mapper function. This includes functions like grim_map() and those produced by function_map(), but not those produced by function_map_seq() or function_map_total_n().

• is_map_seq_df() tests whether an object is the output of a function that was produced by function_map_seq().

• is_map_total_n_df() tests whether an object is the output of a function that was produced by function_map_total_n().

Usage

is_map_df(x)

is_map_basic_df(x)

is_map_seq_df(x)

is_map_total_n_df(x)

Arguments

x

Object to be tested.

Details

Sections 3, 6, and 7 of vignette("consistency-tests-in-depth") discuss which function factories produce which functions, and which of these new, factory-made functions return which kinds of tibbles.

These tibbles are what the ⁠is_map_*()⁠ functions test for. As an example, function_map_seq() produces grim_map_seq(), and this new function returns a tibble. is_map_df() and is_map_seq_df() return TRUE for this tibble, but is_map_basic_df() and is_map_total_n_df() return FALSE.

For an overview, see the table at the end of vignette("consistency-tests-in-depth").

Value

Logical (length 1).

Examples

# Example test output:
df1 <- grim_map(pigs1)
df2 <- grim_map_seq(pigs1)
df3 <- grim_map_total_n(tibble::tribble(
  ~x1,    ~x2,   ~n,
  "3.43", "5.28", 90,
  "2.97", "4.42", 103
))

# All three tibbles are mapper output:
is_map_df(df1)
is_map_df(df2)
is_map_df(df3)

# However, only `df1` is the output of a
# basic mapper...
is_map_basic_df(df1)
is_map_basic_df(df2)
is_map_basic_df(df3)

# ...only `df2` is the output of a
# sequence mapper...
is_map_seq_df(df1)
is_map_seq_df(df2)
is_map_seq_df(df3)

# ...and only `df3` is the output of a
# total-n mapper:
is_map_total_n_df(df1)
is_map_total_n_df(df2)
is_map_total_n_df(df3)