How to print the full NumPy array, without truncation?

StackOverflow

When I print a numpy array, I get a truncated representation, but I want the full array.

Is there any way to do this?

Examples:

>>> numpy.arange(10000)
array([   0,    1,    2, ..., 9997, 9998, 9999])

>>> numpy.arange(10000).reshape(250,40)
array([[   0,    1,    2, ...,   37,   38,   39],
       [  40,   41,   42, ...,   77,   78,   79],
       [  80,   81,   82, ...,  117,  118,  119],
       ..., 
       [9880, 9881, 9882, ..., 9917, 9918, 9919],
       [9920, 9921, 9922, ..., 9957, 9958, 9959],
       [9960, 9961, 9962, ..., 9997, 9998, 9999]])

Answer rating: 772

Use numpy.set_printoptions:

import sys
import numpy
numpy.set_printoptions(threshold=sys.maxsize)

Answer rating: 261

import numpy as np
np.set_printoptions(threshold=np.inf)

I suggest using np.inf instead of np.nan which is suggested by others. They both work for your purpose, but by setting the threshold to "infinity" it is obvious to everybody reading your code what you mean. Having a threshold of "not a number" seems a little vague to me.

Answer rating: 134

The previous answers are the correct ones, but as a weaker alternative you can transform into a list:

>>> numpy.arange(100).reshape(25,4).tolist()

[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11], [12, 13, 14, 15], [16, 17, 18, 19], [20, 21,
22, 23], [24, 25, 26, 27], [28, 29, 30, 31], [32, 33, 34, 35], [36, 37, 38, 39], [40, 41,
42, 43], [44, 45, 46, 47], [48, 49, 50, 51], [52, 53, 54, 55], [56, 57, 58, 59], [60, 61,
62, 63], [64, 65, 66, 67], [68, 69, 70, 71], [72, 73, 74, 75], [76, 77, 78, 79], [80, 81,
82, 83], [84, 85, 86, 87], [88, 89, 90, 91], [92, 93, 94, 95], [96, 97, 98, 99]]

Answer rating: 110




Temporary setting

If you use NumPy 1.15 (released 2018-07-23) or newer, you can use the printoptions context manager:

with numpy.printoptions(threshold=numpy.inf):
    print(arr)

(of course, replace numpy by np if that"s how you imported numpy)

The use of a context manager (the with-block) ensures that after the context manager is finished, the print options will revert to whatever they were before the block started. It ensures the setting is temporary, and only applied to code within the block.

See numpy.printoptions documentation for details on the context manager and what other arguments it supports.





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