numpy.set_printoptions¶
- 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.
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
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'
See also
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)