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

Set printing options.

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


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

Whether or not suppress printing of small floating point values using scientific notation (default 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).

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
- 'numpy_str' : types `numpy.string_` and `numpy.unicode_`
- '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'


formatter is always reset with a call to set_printoptions.


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)

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