Load Compressed Data using numpy.load
Completion requirements
As data arrays get larger and larger, it becomes necessary to compress them if they are to be saved to a file. Data science and machine learning applications using numpy often deal with saving and loading compressed data in the form of files with .npz extensions. This material introduces how to load compressed numpy files.
Load compressed data (.npz) from file using numpy.load
When using numpy.load you can pass the file name, and if the extension is .npz, it will first decompress the file:np.savez_compressed('filename.npz', array1=array1, array2=array2)
b = np.load('filename.npz')
and do
b['array1'] and so forth to retrieve the data from each array...You can also use the
f attribute, which leaves you with a np.ndarray:
images = np.load('images.npz')
images = images.f.arr_0
The name/key of the array inside the .npz-file (e.g.
arr_0) can be found throughimages.keys()
Note: The
f attribute is not documented in the docstring of load. When load reads an npz file, it returns an instance of the class NpzFile. This class is available as numpy.lib.npyio.NpzFile. The docstring of the NpzFile class describes the f attribute.
Source: newbedev, https://newbedev.com/load-compressed-data-npz-from-file-using-numpy-load 
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Last modified: Friday, 23 September 2022, 2:10 PM