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    precision : int or None, optional
        Number of digits of precision for floating point output (default 8).
        May be None if `floatmode` is not `fixed`, to print as many digits as
        necessary to uniquely specify the value.
    threshold : int, optional
        Total number of array elements which trigger summarization
        rather than full repr (default 1000).
        To always use the full repr without summarization, pass `sys.maxsize`.
    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 ' ', 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. (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.bytes_` and `numpy.str_`
        - 'object' : `np.object_` arrays

        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'
    floatmode : str, optional
        Controls the interpretation of the `precision` option for
        floating-point types. Can take the following values
        (default maxprec_equal):

        * '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.
    legacy : string 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. This also
        enables 1.21 legacy printing mode (described below).

        If set to the string `'1.21'` enables 1.21 legacy printing mode. This
        approximates numpy 1.21 print output of complex structured dtypes
        by not inserting spaces after commas that separate fields and after
        colons.

        If set to `False`, disables legacy mode.

        Unrecognized strings will be ignored with a warning for forward
        compatibility.

        .. versionadded:: 1.14.0
        .. versionchanged:: 1.22.0

    See Also
    --------
    get_printoptions, printoptions, set_string_function, array2string

    Notes
    -----
    `formatter` is always reset with a call to `set_printoptions`.

    Use `printoptions` as a context manager to set the values temporarily.

    Examples
    --------
    Floating point precision can be set:

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

    Long arrays can be summarised:

    >>> np.set_printoptions(threshold=5)
    >>> np.arange(10)
    array([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)

    Also to temporarily override options, use `printoptions` as a context manager:

    >>> with np.printoptions(precision=2, suppress=True, threshold=5):
    ...     np.linspace(0, 10, 10)
    array([ 0.  ,  1.11,  2.22, ...,  7.78,  8.89, 10.  ])

    r8r9rMr.r7rOrN)rf�_format_options�updaterrWrX)r2r0r/r4r3r5r6r8r7r1r9�optr;r;r?rts
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    Return the current print options.

    Returns
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        Dictionary of current print options with keys

          - precision : int
          - threshold : int
          - edgeitems : int
          - linewidth : int
          - suppress : bool
          - nanstr : str
          - infstr : str
          - formatter : dict of callables
          - sign : str

        For a full description of these options, see `set_printoptions`.

    See Also
    --------
    set_printoptions, printoptions, set_string_function

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    >>> from numpy.testing import assert_equal
    >>> with np.printoptions(precision=2):
    ...     np.array([2.0]) / 3
    array([0.67])

    The `as`-clause of the `with`-statement gives the current print options:

    >>> with np.printoptions(precision=2) as opts:
    ...      assert_equal(opts, np.get_printoptions())

    See Also
    --------
    set_printoptions, get_printoptions

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    a : ndarray
        Input array.
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        Defaults to ``numpy.get_printoptions()['linewidth']``.
    precision : int or None, optional
        Floating point precision.
        Defaults to ``numpy.get_printoptions()['precision']``.
    suppress_small : bool, optional
        Represent numbers "very close" to zero as zero; default is False.
        Very close is defined by precision: if the precision is 8, e.g.,
        numbers smaller (in absolute value) than 5e-9 are represented as
        zero.
        Defaults to ``numpy.get_printoptions()['suppress']``.
    separator : str, optional
        Inserted between elements.
    prefix : str, optional
    suffix : str, optional
        The length of the prefix and suffix strings are used to respectively
        align and wrap the output. An array is typically printed as::

          prefix + array2string(a) + suffix

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        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:: 1.14.0
    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
        - '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'
    threshold : int, optional
        Total number of array elements which trigger summarization
        rather than full repr.
        Defaults to ``numpy.get_printoptions()['threshold']``.
    edgeitems : int, optional
        Number of array items in summary at beginning and end of
        each dimension.
        Defaults to ``numpy.get_printoptions()['edgeitems']``.
    sign : string, 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']``.
    floatmode : str, 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.
    legacy : string 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.

        .. versionadded:: 1.14.0

    Returns
    -------
    array_str : str
        String representation of the array.

    Raises
    ------
    TypeError
        if a callable in `formatter` does not return a string.

    See Also
    --------
    array_str, array_repr, set_printoptions, get_printoptions

    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
    --------
    >>> 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]'

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        Value to format.
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        Maximum number of digits to print. May be None if `unique` is
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        If `True`, use a digit-generation strategy which gives the shortest
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        Controls post-processing trimming of trailing digits, as follows:

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        * '.' : trim all trailing zeros, leave decimal point
        * '0' : trim all but the zero before the decimal point. Insert the
          zero if it is missing.
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    sign : boolean, optional
        Whether to show the sign for positive values.
    pad_left : non-negative integer, optional
        Pad the left side of the string with whitespace until at least that
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    exp_digits : non-negative integer, optional
        Pad the exponent with zeros until it contains at least this many digits.
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    min_digits : non-negative integer or None, optional
        Minimum number of digits to print. This only has an effect for
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    Returns
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    rep : string
        The string representation of the floating point value

    See Also
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    format_float_positional

    Examples
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    >>> np.format_float_scientific(np.float32(np.pi))
    '3.1415927e+00'
    >>> s = np.float32(1.23e24)
    >>> np.format_float_scientific(s, unique=False, precision=15)
    '1.230000071797338e+24'
    >>> np.format_float_scientific(s, exp_digits=4)
    '1.23e+0024'
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        Value to format.
    precision : non-negative integer or None, optional
        Maximum number of digits to print. May be None if `unique` is
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        If `True`, use a digit-generation strategy which gives the shortest
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    Returns
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    rep : string
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    See Also
    --------
    format_float_scientific

    Examples
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    >>> np.format_float_positional(np.float32(np.pi))
    '3.1415927'
    >>> np.format_float_positional(np.float16(np.pi))
    '3.14'
    >>> np.format_float_positional(np.float16(0.3))
    '0.3'
    >>> np.format_float_positional(np.float16(0.3), unique=False, precision=10)
    '0.3000488281'
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        Input array.
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        Defaults to ``numpy.get_printoptions()['linewidth']``.
    precision : int, optional
        Floating point precision.
        Defaults to ``numpy.get_printoptions()['precision']``.
    suppress_small : bool, optional
        Represent numbers "very close" to zero as zero; default is False.
        Very close is defined by precision: if the precision is 8, e.g.,
        numbers smaller (in absolute value) than 5e-9 are represented as
        zero.
        Defaults to ``numpy.get_printoptions()['suppress']``.

    Returns
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    string : str
      The string representation of an array.

    See Also
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    array_str, array2string, set_printoptions

    Examples
    --------
    >>> np.array_repr(np.array([1,2]))
    'array([1, 2])'
    >>> np.array_repr(np.ma.array([0.]))
    'MaskedArray([0.])'
    >>> np.array_repr(np.array([], np.int32))
    'array([], dtype=int32)'

    >>> x = np.array([1e-6, 4e-7, 2, 3])
    >>> np.array_repr(x, precision=6, suppress_small=True)
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    Parameters
    ----------
    a : ndarray
        Input array.
    max_line_width : int, optional
        Inserts newlines if text is longer than `max_line_width`.
        Defaults to ``numpy.get_printoptions()['linewidth']``.
    precision : int, optional
        Floating point precision.
        Defaults to ``numpy.get_printoptions()['precision']``.
    suppress_small : bool, optional
        Represent numbers "very close" to zero as zero; default is False.
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        numbers smaller (in absolute value) than 5e-9 are represented as
        zero.
        Defaults to ``numpy.get_printoptions()['suppress']``.

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    '[0 1 2]'

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        to print arrays.
    repr : bool, optional
        If True (default), the function for pretty printing (``__repr__``)
        is set, if False the function that returns the default string
        representation (``__str__``) is set.

    See Also
    --------
    set_printoptions, get_printoptions

    Examples
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    >>> def pprint(arr):
    ...     return 'HA! - What are you going to do now?'
    ...
    >>> np.set_string_function(pprint)
    >>> a = np.arange(10)
    >>> a
    HA! - What are you going to do now?
    >>> _ = a
    >>> # [0 1 2 3 4 5 6 7 8 9]

    We can reset the function to the default:

    >>> np.set_string_function(None)
    >>> a
    array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

    `repr` affects either pretty printing or normal string representation.
    Note that ``__repr__`` is still affected by setting ``__str__``
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    >>> x = np.arange(4)
    >>> np.set_string_function(lambda x:'random', repr=False)
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    'random'
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    'array([0, 1, 2, 3])'

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