Print an integer array as hexadecimal numbers

Question

I have an array created by using

array1 = np.array([[25, 160, 154, 233], [61, 244, 198, 248], [227, 226, 141, 72 ], [190, 43, 42, 8]],np.int) ;

which displays as

[[25, 160, 154, 233] [61, 244, 198, 248] [227, 226, 141, 72] [190, 43, 42 , 8]]

How do I display this array as hexadecimal numbers like this:

[[0x04, 0xe0, 0x48, 0x28] [0x66, 0xcb, 0xf8, 0x06] [0x81, 0x19, 0xd3, 0x26] [0xe5, 0x9a, 0x7a, 0x4c]]

Note: numbers in hex may not be real conversions of numbers in int. I have filled hex array just to give example of what I need.

What version of numpy are you using (np.version.version)?

Steven Rumbalski
– Steven Rumbalski

2012-02-25 21:25:49 +00:00
Commented Feb 25, 2012 at 21:25 — Steven Rumbalski
– Steven Rumbalski, Commented Feb 25, 2012 at 21:25

Justin Peel · Accepted Answer · 2012-02-25 21:17:11Z

41

You can set the print options for numpy to do this.

import numpy as np np.set_printoptions(formatter={'int':hex}) np.array([1,2,3,4,5])

gives

array([0x1L, 0x2L, 0x3L, 0x4L, 0x5L])

The L at the end is just because I am on a 64-bit platform and it is sending longs to the formatter. To fix this you can use

np.set_printoptions(formatter={'int':lambda x:hex(int(x))})

edited Feb 25, 2012 at 21:17

answered Feb 25, 2012 at 21:10

Justin Peel

47.1k6 gold badges62 silver badges81 bronze badges

Sign up to request clarification or add additional context in comments.

2 Comments

Steven Rumbalski Over a year ago

FYI for the OP. The formatter parameter for set_printoptions appears in the 2.0 docs, but not in 1.6. So I imagine it's a new feature. If you have an older version, you could roll your own formatting function and supply it to numpy with numpy.set_string_function. The function you supply would need to format the whole array rather than a single item like in Justin's answer.

Serhii Hrynko Over a year ago

For those like myself who doesn't want print options to be changed in a global scope there is a numpy.printoptions helper method now, that you can use like: with np.printoptions(formatter={'int':hex}):

strcat · Accepted Answer · 2012-02-25 21:08:39Z

Python has a built-in hex function for converting integers to their hex representation (a string). You can use numpy.vectorize to apply it over the elements of the multidimensional array.

>>> import numpy as np >>> A = np.array([[1,2],[3,4]]) >>> vhex = np.vectorize(hex) >>> vhex(A) array([['0x1', '0x2'], ['0x3', '0x4']], dtype='<U8')

There might be a built-in method of doing this with numpy which would be a better choice if speed is an issue.

The vectorize is handy when only an occasional hex string is needed. Otherwise would need to original=get_printoptions(), set_printoptions(hex), print hex, set_printoptions(original)

El Barto · Accepted Answer · 2012-02-25 21:10:35Z

If what you're looking for it's just for display you can do something like this:

>>> a = [6, 234, 8, 9, 10, 1234, 555, 98] >>> print '\n'.join([hex(i) for i in a]) 0x6 0xea 0x8 0x9 0xa 0x4d2 0x22b 0x62

Ameer · Accepted Answer · 2012-02-25 21:13:55Z

Just throwing in my two cents you could do this pretty simply using list comprehension if it's always a 2d array like that

a = [[1,2],[3,4]] print [map(hex, l) for l in a]

which gives you [['0x1', '0x2'], ['0x3', '0x4']]

Gordon Bailey · Accepted Answer · 2012-02-25 21:08:43Z

3

This one-liner should do the job:

print '[' + '],\n['.join(','.join(hex(n) for n in ar) for ar in array1) + ']'

answered Feb 25, 2012 at 21:08

Gordon Bailey

3,93122 silver badges30 bronze badges

3 Comments

Steven Rumbalski Over a year ago

-0, due to the existence of numpy.set_printoptions.

Gordon Bailey Over a year ago

Yes, that's definitely a better solution. Question asker, please see Justin Peel's answer, and don't use mine.

std''OrgnlDave Over a year ago

Numpy is absolutely a better solution! If you have access to numpy.

senderle · Accepted Answer · 2012-02-25 21:09:58Z

It should be possible to get the behavior you want with numpy.set_printoptions, using the formatter keyword arg. It takes a dictionary with a type specification (i.e. 'int') as key and a callable object returning the string to print. I'd insert code but my old version of numpy doesn't have the functionality yet. (ugh.)

xyzzyqed · Accepted Answer · 2021-02-16 14:39:44Z

I'm using vectorized np.base_repr since I needed my result rjusted with padded 0's

import numpy as np width = 4 base = 16 array1 = np.array([[25, 160, 154, 233], [61, 244, 198, 248], [227, 226, 141, 72 ], [190, 43, 42, 8]],np.int) base_v = np.vectorize(np.base_repr) padded = np.char.rjust(base_v(array1, base), width, '0') result = np.char.add('0x', padded)

Output:

[['0x0019' '0x00A0' '0x009A' '0x00E9'] ['0x003D' '0x00F4' '0x00C6' '0x00F8'] ['0x00E3' '0x00E2' '0x008D' '0x0048'] ['0x00BE' '0x002B' '0x002A' '0x0008']]

mVChr · Accepted Answer · 2012-02-25 21:16:00Z

array1_hex = np.array([[hex(int(x)) for x in y] for y in array1]) print array1_hex # => array([['0x19', '0xa0', '0x9a', '0xe9'], # ['0x3d', '0xf4', '0xc6', '0xf8'], # ['0xe3', '0xe2', '0x8d', '0x48'], # ['0xbe', '0x2b', '0x2a', '0x8']], # dtype='|S4')

This answer fails with error: TypeError: 'int' object is not iterable

Collectives™ on Stack Overflow

Print an integer array as hexadecimal numbers

8 Answers 8

2 Comments

3 Comments

Comments

Comments

3 Comments

Comments

Comments

1 Comment

Linked

Hot Network Questions

Collectives™ on Stack Overflow

8 Answers 8

2 Comments

3 Comments

Comments

Comments

3 Comments

Comments

Comments

1 Comment

Linked

Related