numpy.set_printoptions

numpy.set_printoptions(precision=None, threshold=None, edgeitems=None, linewidth=None, suppress=None, nanstr=None, infstr=None, formatter=None, sign=None)

Set printing options.

These options determine the way floating point numbers, arrays and other NumPy objects are displayed.

Parameters:

precision : int, optional

Number of digits of precision for floating point output (default 8).

threshold : int, optional

Total number of array elements which trigger summarization rather than full repr (default 1000).

edgeitems : int, optional

Number of array items in summary at beginning and end of each dimension (default 3).

linewidth : int, optional

The number of characters per line for the purpose of inserting line breaks (default 75).

suppress : bool, optional

If True, always print floating point numbers using fixed point notation, in which case numbers equal to zero in the current precision will print as zero. If False, then scientific notation is used when absolute value of the smallest number is < 1e-4 or the ratio of the maximum absolute value to the minimum is > 1e3. The default is False.

nanstr : str, optional

String representation of floating point not-a-number (default nan).

infstr : str, optional

String representation of floating point infinity (default inf).

sign : string, either ‘-‘, ‘+’, ‘ ‘ or ‘legacy’, optional

Controls printing of the sign of floating-point types. If ‘+’, always print the sign of positive values. If ‘ ‘, always prints a space (whitespace character) in the sign position of positive values. If ‘-‘, omit the sign character of positive values. If ‘legacy’, print a space for positive values except in 0d arrays. (default ‘-‘)

formatter : dict of callables, optional

If not None, the keys should indicate the type(s) that the respective formatting function applies to. Callables should return a string. Types that are not specified (by their corresponding keys) are handled by the default formatters. Individual types for which a formatter can be set are:

- 'bool'
- 'int'
- 'timedelta' : a `numpy.timedelta64`
- 'datetime' : a `numpy.datetime64`
- 'float'
- 'longfloat' : 128-bit floats
- 'complexfloat'
- 'longcomplexfloat' : composed of two 128-bit floats
- 'numpystr' : types `numpy.string_` and `numpy.unicode_`
- 'object' : `np.object_` arrays
- 'str' : all other strings

Other keys that can be used to set a group of types at once are:

- 'all' : sets all types
- 'int_kind' : sets 'int'
- 'float_kind' : sets 'float' and 'longfloat'
- 'complex_kind' : sets 'complexfloat' and 'longcomplexfloat'
- 'str_kind' : sets 'str' and 'numpystr'

See also

get_printoptions, set_string_function, array2string

Notes

formatter is always reset with a call to set_printoptions.

Examples

Floating point precision can be set:

>>> np.set_printoptions(precision=4)
>>> print(np.array([1.123456789]))
[ 1.1235]

Long arrays can be summarised:

>>> np.set_printoptions(threshold=5)
>>> print(np.arange(10))
[0 1 2 ..., 7 8 9]

Small results can be suppressed:

>>> eps = np.finfo(float).eps
>>> x = np.arange(4.)
>>> x**2 - (x + eps)**2
array([ -4.9304e-32,  -4.4409e-16,   0.0000e+00,   0.0000e+00])
>>> np.set_printoptions(suppress=True)
>>> x**2 - (x + eps)**2
array([-0., -0.,  0.,  0.])

A custom formatter can be used to display array elements as desired:

>>> np.set_printoptions(formatter={'all':lambda x: 'int: '+str(-x)})
>>> x = np.arange(3)
>>> x
array([int: 0, int: -1, int: -2])
>>> np.set_printoptions()  # formatter gets reset
>>> x
array([0, 1, 2])

To put back the default options, you can use:

>>> np.set_printoptions(edgeitems=3,infstr='inf',
... linewidth=75, nanstr='nan', precision=8,
... suppress=False, threshold=1000, formatter=None)