Converts ratings arrays, ROC or FROC, *but not LROC*, to an
RJafroc dataset, thereby allowing the user to leverage the file I/O,
plotting and analyses capabilities of RJafroc.

`Df2RJafrocDataset(NL, LL, InputIsCountsTable = FALSE, ...)`

## Arguments

- NL
Non-lesion localizations array (or FP array for ROC data).

- LL
Lesion localizations array (or TP array for ROC data).

- InputIsCountsTable
If `TRUE`

, the `NL`

and `LL`

arrays
are rating-counts tables, with common lengths equal to the number of
ratings `R`

, if `FALSE`

, the default, these are arrays of lengths
`K1`

, the number of non-diseased cases, and `K2`

, the number of
diseased cases, respectively.

- ...
Other elements of RJafroc dataset that may, depending on the
context, need to be specified. `perCase`

**must** be specified if
an FROC dataset is to be returned. It is a `K2`

-length array
specifying the numbers of lesions in each diseased case in the dataset.

## Details

The function "senses" the data type (ROC or FROC) from the the
absence or presence of `perCase`

.

ROC data can be `NL[1:K1]`

and `LL[1:K2]`

or `NL[1:I,1:J,1:K1]`

and `LL[1:I,1:J,1:K2]`

.

FROC data can be `NL[1:K1,1:maxNL]`

and `LL[1:K2, 1:maxLL]`

or
`NL[1:I,1:J,1:K1,1:maxNL]`

and `LL[1:I,1:J,1:K2,1:maxLL]`

.

Here `maxNL/maxLL`

= maximum numbers of NLs/LLs, per case, over entire
dataset. Equal weights are assigned to every lesion (FROC data).
Consecutive characters/integers starting with "1" are assigned to
`IDs`

, `modalityID`

and `readerID`

.

## Examples

```
## Input as ratings arrays
set.seed(1);NL <- rnorm(5);LL <- rnorm(7)*1.5 + 2
dataset <- Df2RJafrocDataset(NL, LL)
## Input as counts tables
K1t <- c(30, 19, 8, 2, 1)
K2t <- c(5, 6, 5, 12, 22)
dataset <- Df2RJafrocDataset(K1t, K2t, InputIsCountsTable = TRUE)
```