Prepare Data for TNA Analysis

Prepare simulated or real data for use with tna::tna() and related functions. Handles various input formats and ensures the output is compatible with TNA models.

Usage

prepare_for_tna(
  data,
  type = c("sequences", "long", "auto"),
  state_names = NULL,
  id_col = "Actor",
  time_col = "Time",
  action_col = "Action",
  validate = TRUE
)

Arguments

data

Data frame containing sequence data.

type

Character. Type of input data:

"sequences"

Wide format with one row per sequence (default).

"long"

Long format with one row per action.

"auto"

Automatically detect format based on column names.

state_names

Character vector. Expected state names, or NULL to extract from data. Default: NULL.

id_col

Character. Name of ID column for long format data. Default: "Actor".

time_col

Character. Name of time column for long format data. Default: "Time".

action_col

Character. Name of action column for long format data. Default: "Action".

validate

Logical. Whether to validate that all actions are in state_names. Default: TRUE.

Value

A data frame ready for use with TNA functions. For "sequences" type, returns a data frame where each row is a sequence and columns are time points (V1, V2, ...). For "long" type, converts to wide format first.

Details

This function performs several preparations:

1. Converts long format to wide format if needed.

2. Validates that all actions/states are recognized.

3. Removes any non-sequence columns (e.g., id, metadata).

4. Converts factors to characters.

5. Ensures consistent column naming (V1, V2, ...).

See also

wide_to_long, long_to_wide for format conversions.

Examples

# \donttest{
# From wide format sequences
sequences <- data.frame(
  V1 = c("A","B","C","A"), V2 = c("B","C","A","B"),
  V3 = c("C","A","B","C"), V4 = c("A","B","A","B")
)
tna_data <- prepare_for_tna(sequences, type = "sequences")
# }