prefix + array2string(a) + suffix
The output is left-padded by the length of the prefix string, and
wrapping is forced at the column max_line_width - len(suffix).
It should be noted that the content of prefix and suffix strings are
not included in the output.
style_NoValue, optional
Has no effect, do not use.
Deprecated since version 1.14.0.
formatterdict 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
‘void’ : type numpy.void
‘numpystr’ : types numpy.bytes_ and numpy.str_
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 ‘numpystr’
thresholdint, optional
Total number of array elements which trigger summarization
rather than full repr.
Defaults to numpy.get_printoptions()['threshold'].
edgeitemsint, optional
Number of array items in summary at beginning and end of
each dimension.
Defaults to numpy.get_printoptions()['edgeitems'].
signstring, either ‘-’, ‘+’, or ‘ ‘, 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.
Defaults to numpy.get_printoptions()['sign'].
Changed in version 2.0: The sign parameter can now be an integer type, previously
types were floating-point types.
floatmodestr, optional
Controls the interpretation of the precision option for
floating-point types.
Defaults to numpy.get_printoptions()['floatmode'].
Can take the following values:
‘fixed’: Always print exactly precision fractional digits,
even if this would print more or fewer digits than
necessary to specify the value uniquely.
‘unique’: Print the minimum number of fractional digits necessary
to represent each value uniquely. Different elements may
have a different number of digits.  The value of the
precision option is ignored.
‘maxprec’: Print at most precision fractional digits, but if
an element can be uniquely represented with fewer digits
only print it with that many.
‘maxprec_equal’: Print at most precision fractional digits,
but if every element in the array can be uniquely
represented with an equal number of fewer digits, use that
many digits for all elements.
legacystring or False, optional
If set to the string '1.13' enables 1.13 legacy printing mode. This
approximates numpy 1.13 print output by including a space in the sign
position of floats and different behavior for 0d arrays. If set to
False, disables legacy mode. Unrecognized strings will be ignored
with a warning for forward compatibility.
Returns:
array_strstr
String representation of the array.
Raises:
TypeError
if a callable in formatter does not return a string.
Notes
If a formatter is specified for a certain type, the precision keyword is
ignored for that type.
This is a very flexible function; array_repr and array_str are using
array2string internally so keywords with the same name should work
identically in all three functions.
Examples
>>> import numpy as np
>>> x = np.array([1e-16,1,2,3])
>>> np.array2string(x, precision=2, separator=',',
...                       suppress_small=True)
'[0.,1.,2.,3.]'
>>> x  = np.arange(3.)
>>> np.array2string(x, formatter={'float_kind':lambda x: "%.2f" % x})
'[0.00 1.00 2.00]'
>>> x  = np.arange(3)
>>> np.array2string(x, formatter={'int':lambda x: hex(x)})
'[0x0 0x1 0x2]'