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File: //opt/alt/python37/lib64/python3.7/site-packages/numpy/lib/__pycache__/_iotools.cpython-37.pyc
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        Data-type of a structured array.

    Raises
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        If `ndtype` does not have a `names` attribute.

    Examples
    --------
    >>> dt = np.dtype([('name', 'S4'), ('x', float), ('y', float)])
    >>> np.lib._iotools.has_nested_fields(dt)
    False

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    Parameters
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    ndtype : dtype
        The datatype to collapse
    flatten_base : bool, optional
       If True, transform a field with a shape into several fields. Default is
       False.

    Examples
    --------
    >>> dt = np.dtype([('name', 'S4'), ('x', float), ('y', float),
    ...                ('block', int, (2, 3))])
    >>> np.lib._iotools.flatten_dtype(dt)
    [dtype('|S4'), dtype('float64'), dtype('float64'), dtype('int32')]
    >>> np.lib._iotools.flatten_dtype(dt, flatten_base=True)
    [dtype('|S4'), dtype('float64'), dtype('float64'), dtype('int32'),
     dtype('int32'), dtype('int32'), dtype('int32'), dtype('int32'),
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        If an integer or a sequence of integers, width(s) of each field.
    comments : str, optional
        Character used to mark the beginning of a comment. Default is '#'.
    autostrip : bool, optional
        Whether to strip each individual field. Default is True.

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        Wrapper to strip each member of the output of `method`.

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            The result of wrapping `method`. `wrapped` takes a single input
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    Object to validate a list of strings to use as field names.

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    the exclusion list are appended a '_' character.

    Once an instance has been created, it can be called with a list of
    names, and a list of valid names will be created.  The `__call__`
    method accepts an optional keyword "default" that sets the default name
    in case of ambiguity. By default this is 'f', so that names will
    default to `f0`, `f1`, etc.

    Parameters
    ----------
    excludelist : sequence, optional
        A list of names to exclude. This list is appended to the default
        list ['return', 'file', 'print']. Excluded names are appended an
        underscore: for example, `file` becomes `file_` if supplied.
    deletechars : str, optional
        A string combining invalid characters that must be deleted from the
        names.
    case_sensitive : {True, False, 'upper', 'lower'}, optional
        * If True, field names are case-sensitive.
        * If False or 'upper', field names are converted to upper case.
        * If 'lower', field names are converted to lower case.

        The default value is True.
    replace_space : '_', optional
        Character(s) used in replacement of white spaces.

    Notes
    -----
    Calling an instance of `NameValidator` is the same as calling its
    method `validate`.

    Examples
    --------
    >>> validator = np.lib._iotools.NameValidator()
    >>> validator(['file', 'field2', 'with space', 'CaSe'])
    ['file_', 'field2', 'with_space', 'CaSe']

    >>> validator = np.lib._iotools.NameValidator(excludelist=['excl'],
                                                  deletechars='q',
                                                  case_sensitive='False')
    >>> validator(['excl', 'field2', 'no_q', 'with space', 'CaSe'])
    ['excl_', 'field2', 'no_', 'with_space', 'case']

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            reduces its length to zero.
        nbfields : integer, optional
            Final number of validated names, used to expand or shrink the
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        Returns
        -------
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    Tries to transform a string supposed to represent a boolean to a boolean.

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    Raises
    ------
    ValueError
        If the string is not 'True' or 'False' (case independent)

    Examples
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    Attributes
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    func : function
        Function used for the conversion.
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        Default value to return when the input corresponds to a missing
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    type : type
        Type of the output.
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        Integer representing the order of the conversion.
    _mapper : sequence of tuples
        Sequence of tuples (dtype, function, default value) to evaluate in
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    _locked : bool
        Holds `locked` parameter.

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    dtype_or_func : {None, dtype, function}, optional
        If a `dtype`, specifies the input data type, used to define a basic
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        Value to return by default, that is, when the string to be
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            A string representing a standard input value of the converter.
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            Whether the StringConverter should be locked to prevent
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        Definition of the dtype. Can be any string or dictionary recognized
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    names : str or sequence, optional
        Sequence of strings to use as field names for a structured dtype.
        For convenience, `names` can be a string of a comma-separated list
        of names.
    defaultfmt : str, optional
        Format string used to define missing names, such as ``"f%i"``
        (default) or ``"fields_%02i"``.
    validationargs : optional
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    Examples
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    >>> np.lib._iotools.easy_dtype(float)
    dtype('float64')
    >>> np.lib._iotools.easy_dtype("i4, f8")
    dtype([('f0', '<i4'), ('f1', '<f8')])
    >>> np.lib._iotools.easy_dtype("i4, f8", defaultfmt="field_%03i")
    dtype([('field_000', '<i4'), ('field_001', '<f8')])

    >>> np.lib._iotools.easy_dtype((int, float, float), names="a,b,c")
    dtype([('a', '<i8'), ('b', '<f8'), ('c', '<f8')])
    >>> np.lib._iotools.easy_dtype(float, names="a,b,c")
    dtype([('a', '<f8'), ('b', '<f8'), ('c', '<f8')])

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