savez_compressed(file, *args, **kwds)
Provide arrays as keyword arguments to store them under the corresponding name in the output file: savez(fn, x=x, y=y)
.
If arrays are specified as positional arguments, i.e., savez(fn,
x, y)
, their names will be :None:None:`arr_0`, :None:None:`arr_1`, etc.
The .npz
file format is a zipped archive of files named after the variables they contain. The archive is compressed with zipfile.ZIP_DEFLATED
and each file in the archive contains one variable in .npy
format. For a description of the .npy
format, see numpy.lib.format
.
When opening the saved .npz
file with load
a NpzFile
object is returned. This is a dictionary-like object which can be queried for its list of arrays (with the .files
attribute), and for the arrays themselves.
Either the filename (string) or an open file (file-like object) where the data will be saved. If file is a string or a Path, the .npz
extension will be appended to the filename if it is not already there.
Arrays to save to the file. Please use keyword arguments (see :None:None:`kwds` below) to assign names to arrays. Arrays specified as args will be named "arr_0", "arr_1", and so on.
Arrays to save to the file. Each array will be saved to the output file with its corresponding keyword name.
Save several arrays into a single file in compressed .npz
format.
numpy.load
Load the files created by savez_compressed.
numpy.save
Save a single array to a binary file in NumPy format.
numpy.savetxt
Save an array to a file as plain text.
numpy.savez
Save several arrays into an uncompressed .npz
file format
>>> test_array = np.random.rand(3, 2)
... test_vector = np.random.rand(4)
... np.savez_compressed('/tmp/123', a=test_array, b=test_vector)
... loaded = np.load('/tmp/123.npz')
... print(np.array_equal(test_array, loaded['a'])) True
>>> print(np.array_equal(test_vector, loaded['b'])) TrueSee :
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.sparse._matrix_io.save_npz
numpy.savez
numpy.savetxt
numpy.load
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