cuvis.r

cuvis.r provides R bindings to the Cubert CUVIS SDK for reading, calibrating, and exporting hyperspectral data from Cubert cameras.

This is the R equivalent of cuvis.python.

Prerequisites

1. Install the Cubert CUVIS SDK (>= 3.4.0) from cloud.cubert-gmbh.de
2. Set the CUVIS_SDK environment variable to the install directory
3. (Optional) Download sample data from cloud.cubert-gmbh.de

Installation

# install.packages("remotes")
remotes::install_github("cttir/cuvis.r")

Quick Start

library(cuvis.r)

cuvis_init()

# Load a session file
session <- cuvis_session("path/to/measurement.cu3s")
print(session)

# Extract the data cube
mesu <- cuvis_get_measurement(session, 1)
ctx <- cuvis_processing_context(session)
cuvis_reprocess(ctx, mesu, mode = "raw")
cube <- cuvis_get_cube(mesu)
dim(cube)                        # [rows, cols, bands]
attr(cube, "wavelengths")        # wavelengths in nm

# Calibrate to reflectance
cuvis_reprocess(ctx, mesu, mode = "reflectance")
ref_cube <- cuvis_get_cube(mesu)

# Export to ENVI
cuvis_export_envi(mesu, "output/")

cuvis_shutdown()

Full Calibration Workflow

cuvis_init()

session <- cuvis_session("measurement.cu3s")
mesu <- cuvis_get_measurement(session, 1)

# Load separate dark/white reference files
dark_session <- cuvis_session("dark.cu3s")
white_session <- cuvis_session("white.cu3s")

ctx <- cuvis_processing_context(session)
cuvis_set_reference(ctx, cuvis_get_measurement(dark_session, 1), "dark")
cuvis_set_reference(ctx, cuvis_get_measurement(white_session, 1), "white")

cuvis_reprocess(ctx, mesu, mode = "reflectance")
ref_cube <- cuvis_get_cube(mesu)

cuvis_shutdown()

API Reference

Function	Description
cuvis_init()	Initialize the CUVIS SDK
cuvis_shutdown()	Release SDK resources
cuvis_available()	Check if SDK is linked
cuvis_session(path)	Load a .cu3s session file
cuvis_get_measurement(session, i)	Extract measurement by index
cuvis_get_metadata(mesu)	Get measurement metadata
cuvis_get_cube(mesu)	Extract 3D data array
cuvis_get_wavelengths(mesu)	Get wavelength vector
cuvis_processing_context(session)	Create calibration context
cuvis_set_reference(ctx, mesu, type)	Set dark/white reference
cuvis_reprocess(ctx, mesu, mode)	Reprocess to target level
cuvis_export_envi(mesu, dir)	Export to ENVI format
cuvis_export_tiff(mesu, dir)	Export to TIFF format
cuvis_export_session(mesu, dir)	Export to .cu3s format

Integration with hyperspectR

cuvis.r is designed as the I/O backend for hyperspectR:

library(hyperspectR)

# hyperspectR uses cuvis.r internally for .cu3s files
cube <- hs_read_cubert("measurement.cu3s")

Use of LLM tools

Portions of this package were prepared with assistance from large language model tooling for narrowly defined, non-authorial tasks: copyediting, prose smoothing, Markdown/LaTeX formatting, scaffolding of boilerplate files (CI configs, build scripts), code refactoring. The tools used were Chat AI, the LLM service of KISSKI (GWDG), and a self-hosted Mistral Small (24B, Apache-2.0) run locally via Ollama and the ollamar R package — local inference only, with no data sent to third parties for the self-hosted model.

License

Apache License 2.0