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|
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|
|
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line : str or bytes
|
Line to be decoded.
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|
Parameters
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ndtype : dtype
|
Data-type of a structured array.
|
|
Raises
|
------
|
AttributeError
|
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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|
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|
|
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|
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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('int64')]
|
>>> np.lib._iotools.flatten_dtype(dt, flatten_base=True)
|
[dtype('S4'),
|
dtype('float64'),
|
dtype('float64'),
|
dtype('int64'),
|
dtype('int64'),
|
dtype('int64'),
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dtype('int64'),
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|
dtype('int64')]
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|
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|
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|
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|
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|
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|
|
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|
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|
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|
|
Parameters
|
----------
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excludelist : sequence, optional
|
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|
list ['return', 'file', 'print']. Excluded names are appended an
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underscore: for example, `file` becomes `file_` if supplied.
|
deletechars : str, optional
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|
names.
|
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|
* If True, field names are case-sensitive.
|
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|
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|
|
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|
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|
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)
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>>> validator(['excl', 'field2', 'no_q', 'with space', 'CaSe'])
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('EXCL', 'FIELD2', 'NO_Q', 'WITH_SPACE', 'CASE')
|
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|
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|
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|
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|
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|
|
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boolval : bool
|
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|
|
Raises
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------
|
ValueError
|
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|
|
Examples
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>>> np.lib._iotools.str2bool('TRUE')
|
True
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False
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Attributes
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func : function
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Function used for the conversion.
|
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Default value to return when the input corresponds to a missing
|
value.
|
type : type
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Type of the output.
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_status : int
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Integer representing the order of the conversion.
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Sequence of tuples (dtype, function, default value) to evaluate in
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|
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|
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|
|
Parameters
|
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|
func : var
|
Function, or sequence of functions
|
|
Examples
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>>> import dateutil.parser
|
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|
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|
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Convenience function to create a `np.dtype` object.
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The function processes the input `dtype` and matches it with the given
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names.
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Parameters
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----------
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ndtype : var
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Definition of the dtype. Can be any string or dictionary recognized
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by the `np.dtype` function, or a sequence of types.
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names : str or sequence, optional
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Sequence of strings to use as field names for a structured dtype.
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For convenience, `names` can be a string of a comma-separated list
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defaultfmt : str, optional
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Format string used to define missing names, such as ``"f%i"``
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(default) or ``"fields_%02i"``.
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validationargs : optional
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A series of optional arguments used to initialize a
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`NameValidator`.
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Examples
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--------
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>>> np.lib._iotools.easy_dtype(float)
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dtype('float64')
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>>> np.lib._iotools.easy_dtype("i4, f8")
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dtype([('f0', '<i4'), ('f1', '<f8')])
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>>> np.lib._iotools.easy_dtype("i4, f8", defaultfmt="field_%03i")
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dtype([('field_000', '<i4'), ('field_001', '<f8')])
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>>> np.lib._iotools.easy_dtype((int, float, float), names="a,b,c")
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dtype([('a', '<i8'), ('b', '<f8'), ('c', '<f8')])
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>>> np.lib._iotools.easy_dtype(float, names="a,b,c")
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dtype([('a', '<f8'), ('b', '<f8'), ('c', '<f8')])
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