@author: Dr. Stephanie Burg """ All of the matrices provided are of type numpy.ndarray and can be open using Python. To open the files with a .npy file extension can be opened using the following simple script import numpy as np matrix=np.load('path/filename') #where path is the location of the file and filename is the file to be opened To open the files with a .npz file extension which contain greyscale data (see the tables included in the manuscript), the same np.load() command can be used. However, this loads a python dictionary containing the zipped matrix. To access the unzipped matrix, the following simple script can be used import numpy as np matrix=np.load('path/filename') #where path is the location of the file and filename is the file to be opened matrix=matrix['arr_0'] Finally, to open .npz file extension which contain thresholded data (CY_thresholded.npz and LS_thresholded.npz), the data must be loaded, unzipped, unpacked and then reshaped. The following simple scripts can be used for CY_thresholded.npz and LS_thresholded.npz respectively. The relevant reshape values are also provided in the tables included in the manuscript) #for CY_thresholded.npz import numpy as np matrix=np.load('path/CY_thresholded.npz') #where path is the location of the file matrix=matrix['arr_0'] matrix=np.unpackbits(matrix) matrix=matrix.reshape(1000,2700,9400) #for LS_thresholded.npz import numpy as np matrix=np.load('path/LS_thresholded.npz') #where path is the location of the file matrix=matrix['arr_0'] matrix=np.unpackbits(matrix) matrix=matrix.reshape(1000,2800,14500) !!!CAUTION!!! some of these matrices are very large when unpacked and loaded into memory. Consult the unpacked matrix size given in the manuscript before attempting to load file to ensure you have enough memory.