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title: "Data and interoperability"
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```{r setup, include=FALSE}
library(hypermodR)
knitr::opts_chunk$set(collapse = TRUE, comment = "#>", error = FALSE)
```
The task is lossless access to synthetic spectra. Observation IDs identify rows;
subjects identify independent biological units. Wavelengths are in nm. S3
conversion and S4 access are separate contracts.

```{r containers}
x <- hm_example()
y <- unserialize(serialize(x, NULL))
if (!isTRUE(all(methods::is(y, "HMDataset"), identical(x, y)))) {
  cli::cli_abort("Example assertion failed.", class = "hm_example_error")
}
z <- hm_spectra(y, list(observation_id = x@observations$observation_id[1:3]))
if (!isTRUE(all(identical(dim(z$values), c(3L, 8L))))) {
  cli::cli_abort("Example assertion failed.", class = "hm_example_error")
}
class(z)
```

Use `hm_as_dataset()` for supported hyperspectR, hyperannotatR and cuvis.r source
classes; `hm_as_hsi_cube()` supplies the reverse cube pathway. Companion-package
versions and real object conformance require their own fixtures. Annotation
handoffs use `hm_annotation_contract()`, `hm_export_annotations()` and
`hm_stage_annotations()` with immutable image, label-map and revision identity.
A common class name is insufficient evidence of compatibility. Spatial datasets
need explicit geometry and explicit `hm_pool()` before a spectrum model; RGB
and parameter maps are distinct assets, never replacements for full spectra.