"""
This module contains a set of functions for vectorized string
operations and methods.
.. note::
The `chararray` class exists for backwards compatibility with
Numarray, it is not recommended for new development. Starting from numpy
1.4, if one needs arrays of strings, it is recommended to use arrays of
`dtype` `object_`, `bytes_` or `str_`, and use the free functions
in the `numpy.char` module for fast vectorized string operations.
Some methods will only be available if the corresponding string method is
available in your version of Python.
The preferred alias for `defchararray` is `numpy.char`.
"""
import functools
import numpy as np
from .._utils import set_module
from .numerictypes import bytes_, str_, character
from .numeric import ndarray, array as narray, asarray as asnarray
from numpy._core.multiarray import compare_chararrays
from numpy._core import overrides
from numpy.strings import *
from numpy.strings import (
multiply as strings_multiply,
partition as strings_partition,
rpartition as strings_rpartition,
)
from numpy._core.strings import (
_split as split,
_rsplit as rsplit,
_splitlines as splitlines,
_join as join,
)
__all__ = [
'equal', 'not_equal', 'greater_equal', 'less_equal',
'greater', 'less', 'str_len', 'add', 'multiply', 'mod', 'capitalize',
'center', 'count', 'decode', 'encode', 'endswith', 'expandtabs',
'find', 'index', 'isalnum', 'isalpha', 'isdigit', 'islower', 'isspace',
'istitle', 'isupper', 'join', 'ljust', 'lower', 'lstrip', 'partition',
'replace', 'rfind', 'rindex', 'rjust', 'rpartition', 'rsplit',
'rstrip', 'split', 'splitlines', 'startswith', 'strip', 'swapcase',
'title', 'translate', 'upper', 'zfill', 'isnumeric', 'isdecimal',
'array', 'asarray', 'compare_chararrays', 'chararray'
]
array_function_dispatch = functools.partial(
overrides.array_function_dispatch, module='numpy.char')
def _binary_op_dispatcher(x1, x2):
return (x1, x2)
@array_function_dispatch(_binary_op_dispatcher)
def equal(x1, x2):
"""
Return (x1 == x2) element-wise.
Unlike `numpy.equal`, this comparison is performed by first
stripping whitespace characters from the end of the string. This
behavior is provided for backward-compatibility with numarray.
Parameters
----------
x1, x2 : array_like of str or unicode
Input arrays of the same shape.
Returns
-------
out : ndarray
Output array of bools.
Examples
--------
>>> import numpy as np
>>> y = "aa "
>>> x = "aa"
>>> np.char.equal(x, y)
array(True)
See Also
--------
not_equal, greater_equal, less_equal, greater, less
"""
return compare_chararrays(x1, x2, '==', True)
@array_function_dispatch(_binary_op_dispatcher)
def not_equal(x1, x2):
"""
Return (x1 != x2) element-wise.
Unlike `numpy.not_equal`, this comparison is performed by first
stripping whitespace characters from the end of the string. This
behavior is provided for backward-compatibility with numarray.
Parameters
----------
x1, x2 : array_like of str or unicode
Input arrays of the same shape.
Returns
-------
out : ndarray
Output array of bools.
See Also
--------
equal, greater_equal, less_equal, greater, less
Examples
--------
>>> import numpy as np
>>> x1 = np.array(['a', 'b', 'c'])
>>> np.char.not_equal(x1, 'b')
array([ True, False, True])
"""
return compare_chararrays(x1, x2, '!=', True)
@array_function_dispatch(_binary_op_dispatcher)
def greater_equal(x1, x2):
"""
Return (x1 >= x2) element-wise.
Unlike `numpy.greater_equal`, this comparison is performed by
first stripping whitespace characters from the end of the string.
This behavior is provided for backward-compatibility with
numarray.
Parameters
----------
x1, x2 : array_like of str or unicode
Input arrays of the same shape.
Returns
-------
out : ndarray
Output array of bools.
See Also
--------
equal, not_equal, less_equal, greater, less
Examples
--------
>>> import numpy as np
>>> x1 = np.array(['a', 'b', 'c'])
>>> np.char.greater_equal(x1, 'b')
array([False, True, True])
"""
return compare_chararrays(x1, x2, '>=', True)
@array_function_dispatch(_binary_op_dispatcher)
def less_equal(x1, x2):
"""
Return (x1 <= x2) element-wise.
Unlike `numpy.less_equal`, this comparison is performed by first
stripping whitespace characters from the end of the string. This
behavior is provided for backward-compatibility with numarray.
Parameters
----------
x1, x2 : array_like of str or unicode
Input arrays of the same shape.
Returns
-------
out : ndarray
Output array of bools.
See Also
--------
equal, not_equal, greater_equal, greater, less
Examples
--------
>>> import numpy as np
>>> x1 = np.array(['a', 'b', 'c'])
>>> np.char.less_equal(x1, 'b')
array([ True, True, False])
"""
return compare_chararrays(x1, x2, '<=', True)
@array_function_dispatch(_binary_op_dispatcher)
def greater(x1, x2):
"""
Return (x1 > x2) element-wise.
Unlike `numpy.greater`, this comparison is performed by first
stripping whitespace characters from the end of the string. This
behavior is provided for backward-compatibility with numarray.
Parameters
----------
x1, x2 : array_like of str or unicode
Input arrays of the same shape.
Returns
-------
out : ndarray
Output array of bools.
See Also
--------
equal, not_equal, greater_equal, less_equal, less
Examples
--------
>>> import numpy as np
>>> x1 = np.array(['a', 'b', 'c'])
>>> np.char.greater(x1, 'b')
array([False, False, True])
"""
return compare_chararrays(x1, x2, '>', True)
@array_function_dispatch(_binary_op_dispatcher)
def less(x1, x2):
"""
Return (x1 < x2) element-wise.
Unlike `numpy.greater`, this comparison is performed by first
stripping whitespace characters from the end of the string. This
behavior is provided for backward-compatibility with numarray.
Parameters
----------
x1, x2 : array_like of str or unicode
Input arrays of the same shape.
Returns
-------
out : ndarray
Output array of bools.
See Also
--------
equal, not_equal, greater_equal, less_equal, greater
Examples
--------
>>> import numpy as np
>>> x1 = np.array(['a', 'b', 'c'])
>>> np.char.less(x1, 'b')
array([True, False, False])
"""
return compare_chararrays(x1, x2, '<', True)
def multiply(a, i):
"""
Return (a * i), that is string multiple concatenation,
element-wise.
Values in ``i`` of less than 0 are treated as 0 (which yields an
empty string).
Parameters
----------
a : array_like, with `np.bytes_` or `np.str_` dtype
i : array_like, with any integer dtype
Returns
-------
out : ndarray
Output array of str or unicode, depending on input types
Notes
-----
This is a thin wrapper around np.strings.multiply that raises
`ValueError` when ``i`` is not an integer. It only
exists for backwards-compatibility.
Examples
--------
>>> import numpy as np
>>> a = np.array(["a", "b", "c"])
>>> np.strings.multiply(a, 3)
array(['aaa', 'bbb', 'ccc'], dtype='<U3')
>>> i = np.array([1, 2, 3])
>>> np.strings.multiply(a, i)
array(['a', 'bb', 'ccc'], dtype='<U3')
>>> np.strings.multiply(np.array(['a']), i)
array(['a', 'aa', 'aaa'], dtype='<U3')
>>> a = np.array(['a', 'b', 'c', 'd', 'e', 'f']).reshape((2, 3))
>>> np.strings.multiply(a, 3)
array([['aaa', 'bbb', 'ccc'],
['ddd', 'eee', 'fff']], dtype='<U3')
>>> np.strings.multiply(a, i)
array([['a', 'bb', 'ccc'],
['d', 'ee', 'fff']], dtype='<U3')
"""
try:
return strings_multiply(a, i)
except TypeError:
raise ValueError("Can only multiply by integers")
def partition(a, sep):
"""
Partition each element in `a` around `sep`.
Calls :meth:`str.partition` element-wise.
For each element in `a`, split the element as the first
occurrence of `sep`, and return 3 strings containing the part
before the separator, the separator itself, and the part after
the separator. If the separator is not found, return 3 strings
containing the string itself, followed by two empty strings.
Parameters
----------
a : array-like, with ``StringDType``, ``bytes_``, or ``str_`` dtype
Input array
sep : {str, unicode}
Separator to split each string element in `a`.
Returns
-------
out : ndarray
Output array of ``StringDType``, ``bytes_`` or ``str_`` dtype,
depending on input types. The output array will have an extra
dimension with 3 elements per input element.
Examples
--------
>>> import numpy as np
>>> x = np.array(["Numpy is nice!"])
>>> np.char.partition(x, " ")
array([['Numpy', ' ', 'is nice!']], dtype='<U8')
See Also
--------
str.partition
"""
return np.stack(strings_partition(a, sep), axis=-1)
def rpartition(a, sep):
"""
Partition (split) each element around the right-most separator.
Calls :meth:`str.rpartition` element-wise.
For each element in `a`, split the element as the last
occurrence of `sep`, and return 3 strings containing the part
before the separator, the separator itself, and the part after
the separator. If the separator is not found, return 3 strings
containing the string itself, followed by two empty strings.
Parameters
----------
a : array-like, with ``StringDType``, ``bytes_``, or ``str_`` dtype
Input array
sep : str or unicode
Right-most separator to split each element in array.
Returns
-------
out : ndarray
Output array of ``StringDType``, ``bytes_`` or ``str_`` dtype,
depending on input types. The output array will have an extra
dimension with 3 elements per input element.
See Also
--------
str.rpartition
Examples
--------
>>> import numpy as np
>>> a = np.array(['aAaAaA', ' aA ', 'abBABba'])
>>> np.char.rpartition(a, 'A')
array([['aAaAa', 'A', ''],
[' a', 'A', ' '],
['abB', 'A', 'Bba']], dtype='<U5')
"""
return np.stack(strings_rpartition(a, sep), axis=-1)
@set_module("numpy.char")
class chararray(ndarray):
"""
chararray(shape, itemsize=1, unicode=False, buffer=None, offset=0,
strides=None, order=None)
Provides a convenient view on arrays of string and unicode values.
.. note::
The `chararray` class exists for backwards compatibility with
Numarray, it is not recommended for new development. Starting from numpy
1.4, if one needs arrays of strings, it is recommended to use arrays of
`dtype` `~numpy.object_`, `~numpy.bytes_` or `~numpy.str_`, and use
the free functions in the `numpy.char` module for fast vectorized
string operations.
Versus a NumPy array of dtype `~numpy.bytes_` or `~numpy.str_`, this
class adds the following functionality:
1) values automatically have whitespace removed from the end
when indexed
2) comparison operators automatically remove whitespace from the
end when comparing values
3) vectorized string operations are provided as methods
(e.g. `.endswith`) and infix operators (e.g. ``"+", "*", "%"``)
chararrays should be created using `numpy.char.array` or
`numpy.char.asarray`, rather than this constructor directly.
This constructor creates the array, using `buffer` (with `offset`
and `strides`) if it is not ``None``. If `buffer` is ``None``, then
constructs a new array with `strides` in "C order", unless both
``len(shape) >= 2`` and ``order='F'``, in which case `strides`
is in "Fortran order".
Methods
-------
astype
argsort
copy
count
decode
dump
dumps
encode
endswith
expandtabs
fill
find
flatten
getfield
index
isalnum
isalpha
isdecimal
isdigit
islower
isnumeric
isspace
istitle
isupper
item
join
ljust
lower
lstrip
nonzero
put
ravel
repeat
replace
reshape
resize
rfind
rindex
rjust
rsplit
rstrip
searchsorted
setfield
setflags
sort
split
splitlines
squeeze
startswith
strip
swapaxes
swapcase
take
title
tofile
tolist
tostring
translate
transpose
upper
view
zfill
Parameters
----------
shape : tuple
Shape of the array.
itemsize : int, optional
Length of each array element, in number of characters. Default is 1.
unicode : bool, optional
Are the array elements of type unicode (True) or string (False).
Default is False.
buffer : object exposing the buffer interface or str, optional
Memory address of the start of the array data. Default is None,
in which case a new array is created.
offset : int, optional
Fixed stride displacement from the beginning of an axis?
Default is 0. Needs to be >=0.
strides : array_like of ints, optional
Strides for the array (see `~numpy.ndarray.strides` for
full description). Default is None.
order : {'C', 'F'}, optional
The order in which the array data is stored in memory: 'C' ->
"row major" order (the default), 'F' -> "column major"
(Fortran) order.
Examples
--------
>>> import numpy as np
>>> charar = np.char.chararray((3, 3))
>>> charar[:] = 'a'
>>> charar
chararray([[b'a', b'a', b'a'],
[b'a', b'a', b'a'],
[b'a', b'a', b'a']], dtype='|S1')
>>> charar = np.char.chararray(charar.shape, itemsize=5)
>>> charar[:] = 'abc'
>>> charar
chararray([[b'abc', b'abc', b'abc'],
[b'abc', b'abc', b'abc'],
[b'abc', b'abc', b'abc']], dtype='|S5')
"""
def __new__(subtype, shape, itemsize=1, unicode=False, buffer=None,
offset=0, strides=None, order='C'):
if unicode:
dtype = str_
else:
dtype = bytes_
# force itemsize to be a Python int, since using NumPy integer
# types results in itemsize.itemsize being used as the size of
# strings in the new array.
itemsize = int(itemsize)
if isinstance(buffer, str):
# unicode objects do not have the buffer interface
filler = buffer
buffer = None
else:
filler = None
if buffer is None:
self = ndarray.__new__(subtype, shape, (dtype, itemsize),
order=order)
else:
self = ndarray.__new__(subtype, shape, (dtype, itemsize),
buffer=buffer,
offset=offset, strides=strides,
order=order)
if filler is not None:
self[...] = filler
return self
def __array_wrap__(self, arr, context=None, return_scalar=False):
# When calling a ufunc (and some other functions), we return a
# chararray if the ufunc output is a string-like array,
# or an ndarray otherwise
if arr.dtype.char in "SUbc":
return arr.view(type(self))
return arr
def __array_finalize__(self, obj):
# The b is a special case because it is used for reconstructing.
if self.dtype.char not in 'VSUbc':
raise ValueError("Can only create a chararray from string data.")
def __getitem__(self, obj):
val = ndarray.__getitem__(self, obj)
if isinstance(val, character):
return val.rstrip()
return val
# IMPLEMENTATION NOTE: Most of the methods of this class are
# direct delegations to the free functions in this module.
# However, those that return an array of strings should instead
# return a chararray, so some extra wrapping is required.
def __eq__(self, other):
"""
Return (self == other) element-wise.
See Also
--------
equal
"""
return equal(self, other)
def __ne__(self, other):
"""
Return (self != other) element-wise.
See Also
--------
not_equal
"""
return not_equal(self, other)
def __ge__(self, other):
"""
Return (self >= other) element-wise.
See Also
--------
greater_equal
"""
return greater_equal(self, other)
def __le__(self, other):
"""
Return (self <= other) element-wise.
See Also
--------
less_equal
"""
return less_equal(self, other)
def __gt__(self, other):
"""
Return (self > other) element-wise.
See Also
--------
greater
"""
return greater(self, other)
def __lt__(self, other):
"""
Return (self < other) element-wise.
See Also
--------
less
"""
return less(self, other)
def __add__(self, other):
"""
Return (self + other), that is string concatenation,
element-wise for a pair of array_likes of str or unicode.
See Also
--------
add
"""
return add(self, other)
def __radd__(self, other):
"""
Return (other + self), that is string concatenation,
element-wise for a pair of array_likes of `bytes_` or `str_`.
See Also
--------
add
"""
return add(other, self)
def __mul__(self, i):
"""
Return (self * i), that is string multiple concatenation,
element-wise.
See Also
--------
multiply
"""
return asarray(multiply(self, i))
def __rmul__(self, i):
"""
Return (self * i), that is string multiple concatenation,
element-wise.
See Also
--------
multiply
"""
return asarray(multiply(self, i))
def __mod__(self, i):
"""
Return (self % i), that is pre-Python 2.6 string formatting
(interpolation), element-wise for a pair of array_likes of `bytes_`
or `str_`.
See Also
--------
mod
"""
return asarray(mod(self, i))
def __rmod__(self, other):
return NotImplemented
def argsort(self, axis=-1, kind=None, order=None):
"""
Return the indices that sort the array lexicographically.
For full documentation see `numpy.argsort`, for which this method is
in fact merely a "thin wrapper."
Examples
--------
>>> c = np.array(['a1b c', '1b ca', 'b ca1', 'Ca1b'], 'S5')
>>> c = c.view(np.char.chararray); c
chararray(['a1b c', '1b ca', 'b ca1', 'Ca1b'],
dtype='|S5')
>>> c[c.argsort()]
chararray(['1b ca', 'Ca1b', 'a1b c', 'b ca1'],
dtype='|S5')
"""
return self.__array__().argsort(axis, kind, order)
argsort.__doc__ = ndarray.argsort.__doc__
def capitalize(self):
"""
Return a copy of `self` with only the first character of each element
capitalized.
See Also
--------
char.capitalize
"""
return asarray(capitalize(self))
def center(self, width, fillchar=' '):
"""
Return a copy of `self` with its elements centered in a
string of length `width`.
See Also
--------
center
"""
return asarray(center(self, width, fillchar))
def count(self, sub, start=0, end=None):
"""
Returns an array with the number of non-overlapping occurrences of
substring `sub` in the range [`start`, `end`].
See Also
--------
char.count
"""
return count(self, sub, start, end)
def decode(self, encoding=None, errors=None):
"""
Calls ``bytes.decode`` element-wise.
See Also
--------
char.decode
"""
return decode(self, encoding, errors)
def encode(self, encoding=None, errors=None):
"""
Calls :meth:`str.encode` element-wise.
See Also
--------
char.encode
"""
return encode(self, encoding, errors)
def endswith(self, suffix, start=0, end=None):
"""
Returns a boolean array which is `True` where the string element
in `self` ends with `suffix`, otherwise `False`.
See Also
--------
char.endswith
"""
return endswith(self, suffix, start, end)
def expandtabs(self, tabsize=8):
"""
Return a copy of each string element where all tab characters are
replaced by one or more spaces.
See Also
--------
char.expandtabs
"""
return asarray(expandtabs(self, tabsize))
def find(self, sub, start=0, end=None):
"""
For each element, return the lowest index in the string where
substring `sub` is found.
See Also
--------
char.find
"""
return find(self, sub, start, end)
def index(self, sub, start=0, end=None):
"""
Like `find`, but raises :exc:`ValueError` when the substring is not
found.
See Also
--------
char.index
"""
return index(self, sub, start, end)
def isalnum(self):
"""
Returns true for each element if all characters in the string
are alphanumeric and there is at least one character, false
otherwise.
See Also
--------
char.isalnum
"""
return isalnum(self)
def isalpha(self):
"""
Returns true for each element if all characters in the string
are alphabetic and there is at least one character, false
otherwise.
See Also
--------
char.isalpha
"""
return isalpha(self)
def isdigit(self):
"""
Returns true for each element if all characters in the string are
digits and there is at least one character, false otherwise.
See Also
--------
char.isdigit
"""
return isdigit(self)
def islower(self):
"""
Returns true for each element if all cased characters in the
string are lowercase and there is at least one cased character,
false otherwise.
See Also
--------
char.islower
"""
return islower(self)
def isspace(self):
"""
Returns true for each element if there are only whitespace
characters in the string and there is at least one character,
false otherwise.
See Also
--------
char.isspace
"""
return isspace(self)
def istitle(self):
"""
Returns true for each element if the element is a titlecased
string and there is at least one character, false otherwise.
See Also
--------
char.istitle
"""
return istitle(self)
def isupper(self):
"""
Returns true for each element if all cased characters in the
string are uppercase and there is at least one character, false
otherwise.
See Also
--------
char.isupper
"""
return isupper(self)
def join(self, seq):
"""
Return a string which is the concatenation of the strings in the
sequence `seq`.
See Also
--------
char.join
"""
return join(self, seq)
def ljust(self, width, fillchar=' '):
"""
Return an array with the elements of `self` left-justified in a
string of length `width`.
See Also
--------
char.ljust
"""
return asarray(ljust(self, width, fillchar))
def lower(self):
"""
Return an array with the elements of `self` converted to
lowercase.
See Also
--------
char.lower
"""
return asarray(lower(self))
def lstrip(self, chars=None):
"""
For each element in `self`, return a copy with the leading characters
removed.
See Also
--------
char.lstrip
"""
return lstrip(self, chars)
def partition(self, sep):
"""
Partition each element in `self` around `sep`.
See Also
--------
partition
"""
return asarray(partition(self, sep))
def replace(self, old, new, count=None):
"""
For each element in `self`, return a copy of the string with all
occurrences of substring `old` replaced by `new`.
See Also
--------
char.replace
"""
return replace(self, old, new, count if count is not None else -1)
def rfind(self, sub, start=0, end=None):
"""
For each element in `self`, return the highest index in the string
where substring `sub` is found, such that `sub` is contained
within [`start`, `end`].
See Also
--------
char.rfind
"""
return rfind(self, sub, start, end)
def rindex(self, sub, start=0, end=None):
"""
Like `rfind`, but raises :exc:`ValueError` when the substring `sub` is
not found.
See Also
--------
char.rindex
"""
return rindex(self, sub, start, end)
def rjust(self, width, fillchar=' '):
"""
Return an array with the elements of `self`
right-justified in a string of length `width`.
See Also
--------
char.rjust
"""
return asarray(rjust(self, width, fillchar))
def rpartition(self, sep):
"""
Partition each element in `self` around `sep`.
See Also
--------
rpartition
"""
return asarray(rpartition(self, sep))
def rsplit(self, sep=None, maxsplit=None):
"""
For each element in `self`, return a list of the words in
the string, using `sep` as the delimiter string.
See Also
--------
char.rsplit
"""
return rsplit(self, sep, maxsplit)
def rstrip(self, chars=None):
"""
For each element in `self`, return a copy with the trailing
characters removed.
See Also
--------
char.rstrip
"""
return rstrip(self, chars)
def split(self, sep=None, maxsplit=None):
"""
For each element in `self`, return a list of the words in the
string, using `sep` as the delimiter string.
See Also
--------
char.split
"""
return split(self, sep, maxsplit)
def splitlines(self, keepends=None):
"""
For each element in `self`, return a list of the lines in the
element, breaking at line boundaries.
See Also
--------
char.splitlines
"""
return splitlines(self, keepends)
def startswith(self, prefix, start=0, end=None):
"""
Returns a boolean array which is `True` where the string element
in `self` starts with `prefix`, otherwise `False`.
See Also
--------
char.startswith
"""
return startswith(self, prefix, start, end)
def strip(self, chars=None):
"""
For each element in `self`, return a copy with the leading and
trailing characters removed.
See Also
--------
char.strip
"""
return strip(self, chars)
def swapcase(self):
"""
For each element in `self`, return a copy of the string with
uppercase characters converted to lowercase and vice versa.
See Also
--------
char.swapcase
"""
return asarray(swapcase(self))
def title(self):
"""
For each element in `self`, return a titlecased version of the
string: words start with uppercase characters, all remaining cased
characters are lowercase.
See Also
--------
char.title
"""
return asarray(title(self))
def translate(self, table, deletechars=None):
"""
For each element in `self`, return a copy of the string where
all characters occurring in the optional argument
`deletechars` are removed, and the remaining characters have
been mapped through the given translation table.
See Also
--------
char.translate
"""
return asarray(translate(self, table, deletechars))
def upper(self):
"""
Return an array with the elements of `self` converted to
uppercase.
See Also
--------
char.upper
"""
return asarray(upper(self))
def zfill(self, width):
"""
Return the numeric string left-filled with zeros in a string of
length `width`.
See Also
--------
char.zfill
"""
return asarray(zfill(self, width))
def isnumeric(self):
"""
For each element in `self`, return True if there are only
numeric characters in the element.
See Also
--------
char.isnumeric
"""
return isnumeric(self)
def isdecimal(self):
"""
For each element in `self`, return True if there are only
decimal characters in the element.
See Also
--------
char.isdecimal
"""
return isdecimal(self)
@set_module("numpy.char")
def array(obj, itemsize=None, copy=True, unicode=None, order=None):
"""
Create a `~numpy.char.chararray`.
.. note::
This class is provided for numarray backward-compatibility.
New code (not concerned with numarray compatibility) should use
arrays of type `bytes_` or `str_` and use the free functions
in :mod:`numpy.char` for fast vectorized string operations instead.
Versus a NumPy array of dtype `bytes_` or `str_`, this
class adds the following functionality:
1) values automatically have whitespace removed from the end
when indexed
2) comparison operators automatically remove whitespace from the
end when comparing values
3) vectorized string operations are provided as methods
(e.g. `chararray.endswith <numpy.char.chararray.endswith>`)
and infix operators (e.g. ``+, *, %``)
Parameters
----------
obj : array of str or unicode-like
itemsize : int, optional
`itemsize` is the number of characters per scalar in the
resulting array. If `itemsize` is None, and `obj` is an
object array or a Python list, the `itemsize` will be
automatically determined. If `itemsize` is provided and `obj`
is of type str or unicode, then the `obj` string will be
chunked into `itemsize` pieces.
copy : bool, optional
If true (default), then the object is copied. Otherwise, a copy
will only be made if ``__array__`` returns a copy, if obj is a
nested sequence, or if a copy is needed to satisfy any of the other
requirements (`itemsize`, unicode, `order`, etc.).
unicode : bool, optional
When true, the resulting `~numpy.char.chararray` can contain Unicode
characters, when false only 8-bit characters. If unicode is
None and `obj` is one of the following:
- a `~numpy.char.chararray`,
- an ndarray of type :class:`str_` or :class:`bytes_`
- a Python :class:`str` or :class:`bytes` object,
then the unicode setting of the output array will be
automatically determined.
order : {'C', 'F', 'A'}, optional
Specify the order of the array. If order is 'C' (default), then the
array will be in C-contiguous order (last-index varies the
fastest). If order is 'F', then the returned array
will be in Fortran-contiguous order (first-index varies the
fastest). If order is 'A', then the returned array may
be in any order (either C-, Fortran-contiguous, or even
discontiguous).
"""
if isinstance(obj, (bytes, str)):
if unicode is None:
if isinstance(obj, str):
unicode = True
else:
unicode = False
if itemsize is None:
itemsize = len(obj)
shape = len(obj) // itemsize
return chararray(shape, itemsize=itemsize, unicode=unicode,
buffer=obj, order=order)
if isinstance(obj, (list, tuple)):
obj = asnarray(obj)
if isinstance(obj, ndarray) and issubclass(obj.dtype.type, character):
# If we just have a vanilla chararray, create a chararray
# view around it.
if not isinstance(obj, chararray):
obj = obj.view(chararray)
if itemsize is None:
itemsize = obj.itemsize
# itemsize is in 8-bit chars, so for Unicode, we need
# to divide by the size of a single Unicode character,
# which for NumPy is always 4
if issubclass(obj.dtype.type, str_):
itemsize //= 4
if unicode is None:
if issubclass(obj.dtype.type, str_):
unicode = True
else:
unicode = False
if unicode:
dtype = str_
else:
dtype = bytes_
if order is not None:
obj = asnarray(obj, order=order)
if (copy or
(itemsize != obj.itemsize) or
(not unicode and isinstance(obj, str_)) or
(unicode and isinstance(obj, bytes_))):
obj = obj.astype((dtype, int(itemsize)))
return obj
if isinstance(obj, ndarray) and issubclass(obj.dtype.type, object):
if itemsize is None:
# Since no itemsize was specified, convert the input array to
# a list so the ndarray constructor will automatically
# determine the itemsize for us.
obj = obj.tolist()
# Fall through to the default case
if unicode:
dtype = str_
else:
dtype = bytes_
if itemsize is None:
val = narray(obj, dtype=dtype, order=order, subok=True)
else:
val = narray(obj, dtype=(dtype, itemsize), order=order, subok=True)
return val.view(chararray)
@set_module("numpy.char")
def asarray(obj, itemsize=None, unicode=None, order=None):
"""
Convert the input to a `~numpy.char.chararray`, copying the data only if
necessary.
Versus a NumPy array of dtype `bytes_` or `str_`, this
class adds the following functionality:
1) values automatically have whitespace removed from the end
when indexed
2) comparison operators automatically remove whitespace from the
end when comparing values
3) vectorized string operations are provided as methods
(e.g. `chararray.endswith <numpy.char.chararray.endswith>`)
and infix operators (e.g. ``+``, ``*``, ``%``)
Parameters
----------
obj : array of str or unicode-like
itemsize : int, optional
`itemsize` is the number of characters per scalar in the
resulting array. If `itemsize` is None, and `obj` is an
object array or a Python list, the `itemsize` will be
automatically determined. If `itemsize` is provided and `obj`
is of type str or unicode, then the `obj` string will be
chunked into `itemsize` pieces.
unicode : bool, optional
When true, the resulting `~numpy.char.chararray` can contain Unicode
characters, when false only 8-bit characters. If unicode is
None and `obj` is one of the following:
- a `~numpy.char.chararray`,
- an ndarray of type `str_` or `unicode_`
- a Python str or unicode object,
then the unicode setting of the output array will be
automatically determined.
order : {'C', 'F'}, optional
Specify the order of the array. If order is 'C' (default), then the
array will be in C-contiguous order (last-index varies the
fastest). If order is 'F', then the returned array
will be in Fortran-contiguous order (first-index varies the
fastest).
Examples
--------
>>> import numpy as np
>>> np.char.asarray(['hello', 'world'])
chararray(['hello', 'world'], dtype='<U5')
"""
return array(obj, itemsize, copy=False,
unicode=unicode, order=order)