Create an array using files in numpy with numpy.fromfile() function
In this tutorial, you will learn how to create an array using files in numpy with numpy.fromfile() function.
Syntax:numpy.fromfile(file, dtype=float, count=-1, sep=”)
Construct an array from data in a text or binary file.
A highly efficient way of reading binary data with a known data-type, as well as parsing simply formatted text files. Data written using the tofile method can be read using this function.
Parameters:
file : file or str
Open file object or filename.
dtype : data-type
Data type of the returned array. For binary files, it is used to determine the size and byte-order of the items in the file.
count : int
Number of items to read. -1 means all items (i.e., the complete file).
sep : str
Separator between items if file is a text file. Empty (“”) separator means the file should be treated as binary. Spaces (” “) in the separator match zero or more whitespace characters. A separator consisting only of spaces must match at least one whitespace.
#creation of file array
dt = np.dtype([('time', [('min', int), ('sec', int)]), ('temp', float)])
x = np.zeros((1,), dtype=dt)
x['time']['min'] = 10; x['temp'] = 98.25
#load file
import numpy as np
import os
fname = os.tmpnam()
x.tofile(fname)
#The recommended way to store and load data:
np.save(fname, x)
np.load(fname + '.npy')
