numpy.save and numpy.load

The goal

Let’s save and load data under numpy. This can be more complicated than expected.

np.save and np.load

A normal np.save and np.load cycle may look like this:

import numpy as np

rng = np.random.default_rng()

a_original: np.ndarray = rng.random((100, 10))

np.save("a.npy", a_original)
a_load: np.ndarray = np.load("a.npy")

print(np.abs(a_original - a_load).sum()) # -> 0.0

np.savez

We can save more than one variable into one file. We need to use np.savez for this. Now the file extension is npz instead of npy. This is required!

import numpy as np

rng = np.random.default_rng()

a_original = rng.random((100, 10))
b_original = rng.random((100, 10))
c_original = rng.random((100, 10))

np.savez("c.npz", a_original=a_original, b_original=b_original, c_original=c_original)

np_file = np.load("c.npz")

np_file_keys: list = list(np_file.keys())
print(np_file_keys) # -> ['a_original', 'b_original', 'c_original']

Please don’t use savez like this because this can cause human errors down the road:

import numpy as np

rng = np.random.default_rng()

a_original = rng.random((100, 10))
b_original = rng.random((100, 10))
c_original = rng.random((100, 10))

# np.savez("c.npz", a_original=a_original, b_original=b_original, c_original=c_original)
np.savez("d.npz", a_original, b_original, c_original)

np_file = np.load("d.npz")

np_file_keys: list = list(np_file.keys())
print(np_file_keys) # -> ['arr_0', 'arr_1', 'arr_2']

You don’t need to keep the variable name but keep it human readable:

import numpy as np

rng = np.random.default_rng()

a_original = rng.random((100, 10))
b_original = rng.random((100, 10))
c_original = rng.random((100, 10))
d_original = rng.random((100, 10))

np.savez("e.npz", what=a_original, a=b_original, nice=c_original, day=d_original)

np_file = np.load("e.npz")

np_file_keys: list = list(np_file.keys())
print(np_file_keys) # -> ['what', 'a', 'nice', 'day']

Now we can work with the file and the stored variables:

import numpy as np

rng = np.random.default_rng()

a_original = rng.random((100, 10))
b_original = rng.random((100, 10))
c_original = rng.random((100, 10))

np.savez("c.npz", a_original=a_original, b_original=b_original, c_original=c_original)

np_file = np.load("c.npz")

print(np.abs(a_original - np_file["a_original"]).sum())  # -> 0.0
print(np.abs(b_original - np_file["b_original"]).sum())  # -> 0.0
print(np.abs(c_original - np_file["c_original"]).sum())  # -> 0.0

np.savez_compressed

We can compress the data too:

import numpy as np

rng = np.random.default_rng()

a_original = rng.random((100, 10))
b_original = rng.random((100, 10))
c_original = rng.random((100, 10))

np.savez_compressed(
    "f.npz", a_original=a_original, b_original=b_original, c_original=c_original
)

np_file = np.load("f.npz")

print(np.abs(a_original - np_file["a_original"]).sum())  # -> 0.0
print(np.abs(b_original - np_file["b_original"]).sum())  # -> 0.0
print(np.abs(c_original - np_file["c_original"]).sum())  # -> 0.0

Text files numpy.savetxt and numpy.loadtxt

numpy.savetxt(fname, X, fmt='%.18e', delimiter=' ', newline='\n', header='', footer='', comments='# ', encoding=None)

Save an array to a text file.

import numpy as np

rng = np.random.default_rng()

a_original = rng.random((100, 10))

np.savetxt("data.txt", a_original)

numpy.loadtxt(fname, dtype=<class 'float'>, comments='#', delimiter=None, converters=None, skiprows=0, usecols=None, unpack=False, ndmin=0, encoding='bytes', max_rows=None, *, quotechar=None, like=None)

Load data from a text file.

import numpy as np

rng = np.random.default_rng()

a_original = rng.random((100, 10))

np.savetxt("data.txt", a_original)

a_load = np.loadtxt("data.txt")

print(a_original.shape)  # -> (100, 10)
print(a_load.shape)  # -> (100, 10)
print(np.abs(a_original - a_load).sum())  # -> 0.0

numpy.genfromtxt

This is an optional topic!

numpy.genfromtxt(fname, dtype=<class 'float'>, comments='#', delimiter=None, skip_header=0, skip_footer=0, converters=None, missing_values=None, filling_values=None, usecols=None, names=None, excludelist=None, deletechars=" !#$%&'()*+, -./:;<=>?@[\\]^{|}~", replace_space='_', autostrip=False, case_sensitive=True, defaultfmt='f%i', unpack=None, usemask=False, loose=True, invalid_raise=True, max_rows=None, encoding='bytes', *, ndmin=0, like=None)

Load data from a text file, with missing values handled as specified.

Each line past the first skip_header lines is split at the delimiter character, and characters following the comments character are discarded.

The source code is Open Source and can be found on GitHub.