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Example:
a dataset containing 10x10 spectra, each with spectral axis [960nm ... 1000nm] with 1024 points.
When loading a NRB spectrum with spectral axis [940nm ... 1020nm] with 2048 points (same step size) the error "NRB was the wrong shape" occurs.
Also it seems that crikit applies the HSI data calibration to the NRB data, as long as shape fits. For this example, it is possible to load a NRB spectrum [940nm ... 980nm] with 1024 points, but a message occurs: "Something failed in meta_process: Spectra rep-calib". The NRB spectrum is shown shifted to the HSI spectrum [960nm ... 1000nm].
The rep-calib message also occurs if the NRB spectral axis is exactly the same as the HSI spectral axis.
I don't know if this is an consequence of issue #38
Workaround: Crop the NRB data beforehand to fit the spectral axis of the HSI data
The text was updated successfully, but these errors were encountered:
Example:
a dataset containing 10x10 spectra, each with spectral axis [960nm ... 1000nm] with 1024 points.
When loading a NRB spectrum with spectral axis [940nm ... 1020nm] with 2048 points (same step size) the error "NRB was the wrong shape" occurs.
Also it seems that crikit applies the HSI data calibration to the NRB data, as long as shape fits. For this example, it is possible to load a NRB spectrum [940nm ... 980nm] with 1024 points, but a message occurs: "Something failed in meta_process: Spectra rep-calib". The NRB spectrum is shown shifted to the HSI spectrum [960nm ... 1000nm].
The rep-calib message also occurs if the NRB spectral axis is exactly the same as the HSI spectral axis.
I don't know if this is an consequence of issue #38
Workaround: Crop the NRB data beforehand to fit the spectral axis of the HSI data
The text was updated successfully, but these errors were encountered: