Guess RelDataModel constraints based on the provided or existing tables

Usage

guess_constraints(
  x,
  data = NULL,
  env = parent.frame(n = 1),
  constraints = c("unique", "not nullable", "foreign keys")
)

Arguments

x: a RelDataModel
data: a named list of tables. All names of x should exist in data. If NULL, the data are taken from env.
env: the R environment in which to find the tables
constraints: the type of constraints to guess

Value

A RelDataModel

Details

The guessed constraints should be carefully review, especially the foreign keys.

Complex foreign keys involving multiple fields are not guessed.

Examples

## Read data files ----
to_read <- list.files(
   system.file("examples/HPO-subset", package="ReDaMoR"),
   full.names=TRUE
)
hpo_tables <- list()
for(f in to_read){
   hpo_tables[[sub("[.]txt$", "", basename(f))]] <- readr::read_tsv(f)
}
#> Rows: 89 Columns: 2
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: "\t"
#> chr (2): id, alt
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> Rows: 972 Columns: 2
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: "\t"
#> chr (2): id, descendant
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> Rows: 2594 Columns: 3
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: "\t"
#> chr (2): db, hp
#> dbl (1): id
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> Rows: 2337 Columns: 4
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: "\t"
#> chr (2): db, synonym
#> dbl (1): id
#> lgl (1): preferred
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> Rows: 1903 Columns: 3
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: "\t"
#> chr (2): db, label
#> dbl (1): id
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> Rows: 500 Columns: 4
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: "\t"
#> chr (3): id, name, description
#> dbl (1): level
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> Rows: 95 Columns: 2
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: "\t"
#> chr (2): id, parent
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> Rows: 2 Columns: 2
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: "\t"
#> chr  (1): url
#> date (1): current
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> Rows: 730 Columns: 3
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: "\t"
#> chr (3): id, synonym, type
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Build the model from a list of data frames ----
new_model <- df_to_model(
   list=names(hpo_tables), envir=as.environment(hpo_tables)
)
## Guess constraints and auto layout ----
new_model <- guess_constraints(new_model, data = hpo_tables) %>%
   auto_layout(lengthMultiplier=250)

## Plot the model ----
new_model %>%
   plot()