numpy.load¶

numpy.load(file,mmap_mode=None,allow_pickle=True,fix_imports=True,encoding='ASCII')[source]¶

Load arrays or pickled objects from.npy,.npz or pickled files.

Parameters:	file:file-like object, string, or pathlib.Path The file to read. File-like objects must support theseek() andread() methods. Pickled files require that thefile-like object support thereadline() method as well. mmap_mode:{None, ‘r+’, ‘r’, ‘w+’, ‘c’}, optional If not None, then memory-map the file, using the given mode (seenumpy.memmap for a detailed description of the modes). Amemory-mapped array is kept on disk. However, it can be accessedand sliced like any ndarray. Memory mapping is especially usefulfor accessing small fragments of large files without reading theentire file into memory. allow_pickle:bool, optional Allow loading pickled object arrays stored in npy files. Reasons fordisallowing pickles include security, as loading pickled data canexecute arbitrary code. If pickles are disallowed, loading objectarrays will fail.Default: True fix_imports:bool, optional Only useful when loading Python 2 generated pickled files on Python 3,which includes npy/npz files containing object arrays. Iffix_importsis True, pickle will try to map the old Python 2 names to the new namesused in Python 3. encoding:str, optional What encoding to use when reading Python 2 strings. Only useful whenloading Python 2 generated pickled files in Python 3, which includesnpy/npz files containing object arrays. Values other than ‘latin1’,‘ASCII’, and ‘bytes’ are not allowed, as they can corrupt numericaldata. Default: ‘ASCII’
Returns:	result:array, tuple, dict, etc. Data stored in the file. For.npz files, the returned instanceof NpzFile class must be closed to avoid leaking file descriptors.
Raises:	IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given.

See also

save,savez,savez_compressed,loadtxt

memmap

Create a memory-map to an array stored in a file on disk.

lib.format.open_memmap

Create or load a memory-mapped.npy file.

Notes

• If the file contains pickle data, then whatever object is storedin the pickle is returned.

• If the file is a.npy file, then a single array is returned.

• If the file is a.npz file, then a dictionary-like object isreturned, containing{filename:array} key-value pairs, one foreach file in the archive.

• If the file is a.npz file, the returned value supports thecontext manager protocol in a similar fashion to the open function:

  withload('foo.npz')asdata:a=data['a']

  The underlying file descriptor is closed when exiting the ‘with’block.

Examples

Store data to disk, and load it again:

>>>np.save('/tmp/123',np.array([[1,2,3],[4,5,6]]))>>>np.load('/tmp/123.npy')array([[1, 2, 3],       [4, 5, 6]])

Store compressed data to disk, and load it again:

>>>a=np.array([[1,2,3],[4,5,6]])>>>b=np.array([1,2])>>>np.savez('/tmp/123.npz',a=a,b=b)>>>data=np.load('/tmp/123.npz')>>>data['a']array([[1, 2, 3],       [4, 5, 6]])>>>data['b']array([1, 2])>>>data.close()

Mem-map the stored array, and then access the second rowdirectly from disk:

>>>X=np.load('/tmp/123.npy',mmap_mode='r')>>>X[1,:]memmap([4, 5, 6])