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Module « numpy »

Fonction array2string - module numpy

Signature de la fonction array2string

def array2string(a, max_line_width=None, precision=None, suppress_small=None, separator=' ', prefix='', style=<no value>, formatter=None, threshold=None, edgeitems=None, sign=None, floatmode=None, suffix='', *, legacy=None) 

Description

array2string.__doc__

    Return a string representation of an array.

    Parameters
    ----------
    a : array_like
        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 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

        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:: 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.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'
    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]'