Current File : //lib64/python3.9/site-packages/numpy/lib/__pycache__/_iotools.cpython-39.pyc
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d d � Zd"dd�ZG dd� d�ZG dd� d�Zdd� ZG dd� de�ZG dd� de�ZG dd� de�ZG d d � d �Zd#d d �ZdS )$zBA collection of functions designed to help I/O with ascii files.
zrestructuredtext en� N)�asbytes� asunicodec C s& t | �tu r"|du rd}| �|�} | S )ak Decode bytes from binary input streams.
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Parameters
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Line to be decoded.
encoding : str
Encoding used to decode `line`.
Returns
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Returns whether one or several fields of a dtype are nested.
Parameters
----------
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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Unpack a structured data-type by collapsing nested fields and/or fields
with a shape.
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Parameters
----------
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'),
dtype('int64'),
dtype('int64'),
dtype('int64')]
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Object to split a string at a given delimiter or at given places.
Parameters
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delimiter : str, int, or sequence of ints, optional
If a string, character used to delimit consecutive fields.
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`.
Parameters
----------
method : function
Function that takes a single argument and returns a sequence of
strings.
Returns
-------
wrapped : function
The result of wrapping `method`. `wrapped` takes a single input
argument and returns a list of strings that are stripped of
white-space.
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Object to validate a list of strings to use as field names.
The strings are stripped of any non alphanumeric character, and spaces
are replaced by '_'. During instantiation, the user can define a list
of names to exclude, as well as a list of invalid characters. Names in
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_Q', 'WITH_SPACE', 'CASE')
)�return�file�printz ~!@#$%^&*()-=+~\|]}[{';: /?.>,<Nr& c C s� |d u r g }|� | j� || _|d u r.| j}nt|�}|�d� || _|d u sV|du rbdd� | _nD|du st|�d�r�dd� | _n&|�d�r�d d� | _nd
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Validate a list of strings as field names for a structured array.
Parameters
----------
names : sequence of str
Strings to be validated.
defaultfmt : str, optional
Default format string, used if validating a given string
reduces its length to zero.
nbfields : integer, optional
Final number of validated names, used to expand or shrink the
initial list of names.
Returns
-------
validatednames : list of str
The list of validated field names.
Notes
-----
A `NameValidator` instance can be called directly, which is the
same as calling `validate`. For examples, see `NameValidator`.
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Tries to transform a string supposed to represent a boolean to a boolean.
Parameters
----------
value : str
The string that is transformed to a boolean.
Returns
-------
boolval : bool
The boolean representation of `value`.
Raises
------
ValueError
If the string is not 'True' or 'False' (case independent)
Examples
--------
>>> np.lib._iotools.str2bool('TRUE')
True
>>> np.lib._iotools.str2bool('false')
False
ZTRUETZFALSEFzInvalid booleanN)r[ r )�valuer
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Warning issued when a string converter has a problem.
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d��Z e dd� �Z!d#dd�Z"dd� Z#dd� Z$dd� Z%dd� Z&dd � Z'd d � Z(d$d d!�Z)d S )%�StringConverterab
Factory class for function transforming a string into another object
(int, float).
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missing value, a default value is returned.
Attributes
----------
func : function
Function used for the conversion.
default : any
Default value to return when the input corresponds to a missing
value.
type : type
Type of the output.
_status : int
Integer representing the order of the conversion.
_mapper : sequence of tuples
Sequence of tuples (dtype, function, default value) to evaluate in
order.
_locked : bool
Holds `locked` parameter.
Parameters
----------
dtype_or_func : {None, dtype, function}, optional
If a `dtype`, specifies the input data type, used to define a basic
function and a default value for missing data. For example, when
`dtype` is float, the `func` attribute is set to `float` and the
default value to `np.nan`. If a function, this function is used to
convert a string to another object. In this case, it is recommended
to give an associated default value as input.
default : any, optional
Value to return by default, that is, when the string to be
converted is flagged as missing. If not given, `StringConverter`
tries to supply a reasonable default value.
missing_values : {None, sequence of str}, optional
``None`` or sequence of strings indicating a missing value. If ``None``
then missing values are indicated by empty entries. The default is
``None``.
locked : bool, optional
Whether the StringConverter should be locked to prevent automatic
upgrade or not. Default is False.
Fr4 y z???c C s t �|�jS )z(Returns the dtype of the input variable.)r �array�dtype��cls�valr
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Upgrade the mapper of a StringConverter by adding a new function and
its corresponding default.
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default value (if any) is inserted in penultimate position of the
mapper. The corresponding type is estimated from the dtype of the
default value.
Parameters
----------
func : var
Function, or sequence of functions
Examples
--------
>>> import dateutil.parser
>>> import datetime
>>> dateparser = dateutil.parser.parse
>>> defaultdate = datetime.date(2000, 1, 1)
>>> StringConverter.upgrade_mapper(dateparser, default=defaultdate)
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Find the best converter for a given string, and return the result.
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converters in order. First the `func` method of the
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converters are tried. The order in which these other converters
are tried is determined by the `_status` attribute of the instance.
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value : str
The string to convert.
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The result of converting `value` with the appropriate converter.
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Set StringConverter attributes directly.
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converted is flagged as missing. If not given,
`StringConverter` tries to supply a reasonable default value.
testing_value : str, optional
A string representing a standard input value of the converter.
This string is used to help defining a reasonable default
value.
missing_values : {sequence of str, None}, optional
Sequence of strings indicating a missing value. If ``None``, then
the existing `missing_values` are cleared. The default is `''`.
locked : bool, optional
Whether the StringConverter should be locked to prevent
automatic upgrade or not. Default is False.
Notes
-----
`update` takes the same parameters as the constructor of
`StringConverter`, except that `func` does not accept a `dtype`
whereas `dtype_or_func` in the constructor does.
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Convenience function to create a `np.dtype` object.
The function processes the input `dtype` and matches it with the given
names.
Parameters
----------
ndtype : var
Definition of the dtype. Can be any string or dictionary recognized
by the `np.dtype` function, or a sequence of types.
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
A series of optional arguments used to initialize a
`NameValidator`.
Examples
--------
>>> 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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