How to extract the spectra range within a roi mask?

I am learning hyperspectral data analysis, so my question may sound simple.

I am reading a hypercube by using the following command:

import spectral.io.envi as envi

hc = envi.open('cube_envi32.hdr','cube_envi32.dat')

'hc' has the following shape:

# Rows:            512
    # Samples:         640
    # Bands:            92
    Interleave:        BSQ
    Quantization:  32 bits
    Data format:   float32
(512, 640, 92)

I want to extract the spectral (or pixel values of within a specific binary mask, as shown with rectangle here:

My question includes two parts:

1. which python library is suitable for spectra analysis and working with hypercubes?
2. what command should I write to extract the spectra values of the region of interest?

Thanks

You can use the spectral module and numpy to read the data.

If you know the bounding coordinates of your rectangle, you can simply use

region = hc[i_start:i_stop, j_start:j_stop]

If you have an arbitrary mask (mask is not necessarily a rectangular subregion) and can load the entire image into memory, then you can use numpy syntax to read the spectra. Suppose your mask m has a value of 1 for pixels you want to read. Then you can do this:

pixels = hc.load().asarray[m == 1]

If you can't (or don't want to) read the entire image, you can read the masked pixels into a list like so:

pixels = [hc[i, j] for (i, j) in np.argwhere(m == 1)]