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Friday, March 24, 2017

I/O with NumPy

The ndarray objects can be saved to and loaded from the disk files. The IO functions available are −
  • load() and save() functions handle /numPy binary files (with npy extension)
  • loadtxt() and savetxt() functions handle normal text files
NumPy introduces a simple file format for ndarray objects. This .npy file stores data, shape, dtype and other information required to reconstruct the ndarray in a disk file such that the array is correctly retrieved even if the file is on another machine with different architecture.

numpy.save()

The numpy.save() file stores the input array in a disk file with npy extension.
import numpy as np 
a = np.array([1,2,3,4,5]) 
np.save('outfile',a)
To reconstruct array from outfile.npy, use load() function.
import numpy as np 
b = np.load('outfile.npy') 
print b 
It will produce the following output −
array([1, 2, 3, 4, 5])
The save() and load() functions accept an additional Boolean parameter allow_pickles. A pickle in Python is used to serialize and de-serialize objects before saving to or reading from a disk file.

savetxt()

The storage and retrieval of array data in simple text file format is done with savetxt() and loadtxt() functions.

Example

import numpy as np 

a = np.array([1,2,3,4,5]) 
np.savetxt('out.txt',a) 
b = np.loadtxt('out.txt') 
print b 
It will produce the following output −
[ 1.  2.  3.  4.  5.] 
The savetxt() and loadtxt() functions accept additional optional parameters such as header, footer, and delimiter.

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