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defchararray.py
""" 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 from .._utils import set_module from .numerictypes import ( bytes_, str_, integer, int_, object_, bool_, character) from .numeric import ndarray, compare_chararrays from .numeric import array as narray from numpy.core.multiarray import _vec_string from numpy.core import overrides from numpy.compat import asbytes import numpy __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' ] _globalvar = 0 array_function_dispatch = functools.partial( overrides.array_function_dispatch, module='numpy.char') def _is_unicode(arr): """Returns True if arr is a string or a string array with a dtype that represents a unicode string, otherwise returns False. """ if (isinstance(arr, str) or issubclass(numpy.asarray(arr).dtype.type, str)): return True return False def _to_bytes_or_str_array(result, output_dtype_like=None): """ Helper function to cast a result back into an array with the appropriate dtype if an object array must be used as an intermediary. """ ret = numpy.asarray(result.tolist()) dtype = getattr(output_dtype_like, 'dtype', None) if dtype is not None: return ret.astype(type(dtype)(_get_num_chars(ret)), copy=False) return ret def _clean_args(*args): """ Helper function for delegating arguments to Python string functions. Many of the Python string operations that have optional arguments do not use 'None' to indicate a default value. In these cases, we need to remove all None arguments, and those following them. """ newargs = [] for chk in args: if chk is None: break newargs.append(chk) return newargs def _get_num_chars(a): """ Helper function that returns the number of characters per field in a string or unicode array. This is to abstract out the fact that for a unicode array this is itemsize / 4. """ if issubclass(a.dtype.type, str_): return a.itemsize // 4 return a.itemsize 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. 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 """ 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 """ 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 """ 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 """ 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 """ return compare_chararrays(x1, x2, '<', True) def _unary_op_dispatcher(a): return (a,) @array_function_dispatch(_unary_op_dispatcher) def str_len(a): """ Return len(a) element-wise. Parameters ---------- a : array_like of str or unicode Returns ------- out : ndarray Output array of integers See Also -------- len Examples -------- >>> a = np.array(['Grace Hopper Conference', 'Open Source Day']) >>> np.char.str_len(a) array([23, 15]) >>> a = np.array([u'\u0420', u'\u043e']) >>> np.char.str_len(a) array([1, 1]) >>> a = np.array([['hello', 'world'], [u'\u0420', u'\u043e']]) >>> np.char.str_len(a) array([[5, 5], [1, 1]]) """ # Note: __len__, etc. currently return ints, which are not C-integers. # Generally intp would be expected for lengths, although int is sufficient # due to the dtype itemsize limitation. return _vec_string(a, int_, '__len__') @array_function_dispatch(_binary_op_dispatcher) def add(x1, x2): """ Return element-wise string concatenation for two arrays of str or unicode. Arrays `x1` and `x2` must have the same shape. Parameters ---------- x1 : array_like of str or unicode Input array. x2 : array_like of str or unicode Input array. Returns ------- add : ndarray Output array of `bytes_` or `str_`, depending on input types of the same shape as `x1` and `x2`. """ arr1 = numpy.asarray(x1) arr2 = numpy.asarray(x2) out_size = _get_num_chars(arr1) + _get_num_chars(arr2) if type(arr1.dtype) != type(arr2.dtype): # Enforce this for now. The solution to it will be implement add # as a ufunc. It never worked right on Python 3: bytes + unicode gave # nonsense unicode + bytes errored, and unicode + object used the # object dtype itemsize as num chars (worked on short strings). # bytes + void worked but promoting void->bytes is dubious also. raise TypeError( "np.char.add() requires both arrays of the same dtype kind, but " f"got dtypes: '{arr1.dtype}' and '{arr2.dtype}' (the few cases " "where this used to work often lead to incorrect results).") return _vec_string(arr1, type(arr1.dtype)(out_size), '__add__', (arr2,)) def _multiply_dispatcher(a, i): return (a,) @array_function_dispatch(_multiply_dispatcher) 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 of str or unicode i : array_like of ints Returns ------- out : ndarray Output array of str or unicode, depending on input types Examples -------- >>> a = np.array(["a", "b", "c"]) >>> np.char.multiply(x, 3) array(['aaa', 'bbb', 'ccc'], dtype='<U3') >>> i = np.array([1, 2, 3]) >>> np.char.multiply(a, i) array(['a', 'bb', 'ccc'], dtype='<U3') >>> np.char.multiply(np.array(['a']), i) array(['a', 'aa', 'aaa'], dtype='<U3') >>> a = np.array(['a', 'b', 'c', 'd', 'e', 'f']).reshape((2, 3)) >>> np.char.multiply(a, 3) array([['aaa', 'bbb', 'ccc'], ['ddd', 'eee', 'fff']], dtype='<U3') >>> np.char.multiply(a, i) array([['a', 'bb', 'ccc'], ['d', 'ee', 'fff']], dtype='<U3') """ a_arr = numpy.asarray(a) i_arr = numpy.asarray(i) if not issubclass(i_arr.dtype.type, integer): raise ValueError("Can only multiply by integers") out_size = _get_num_chars(a_arr) * max(int(i_arr.max()), 0) return _vec_string( a_arr, type(a_arr.dtype)(out_size), '__mul__', (i_arr,)) def _mod_dispatcher(a, values): return (a, values) @array_function_dispatch(_mod_dispatcher) def mod(a, values): """ Return (a % i), that is pre-Python 2.6 string formatting (interpolation), element-wise for a pair of array_likes of str or unicode. Parameters ---------- a : array_like of str or unicode values : array_like of values These values will be element-wise interpolated into the string. Returns ------- out : ndarray Output array of str or unicode, depending on input types See Also -------- str.__mod__ """ return _to_bytes_or_str_array( _vec_string(a, object_, '__mod__', (values,)), a) @array_function_dispatch(_unary_op_dispatcher) def capitalize(a): """ Return a copy of `a` with only the first character of each element capitalized. Calls `str.capitalize` element-wise. For 8-bit strings, this method is locale-dependent. Parameters ---------- a : array_like of str or unicode Input array of strings to capitalize. Returns ------- out : ndarray Output array of str or unicode, depending on input types See Also -------- str.capitalize Examples -------- >>> c = np.array(['a1b2','1b2a','b2a1','2a1b'],'S4'); c array(['a1b2', '1b2a', 'b2a1', '2a1b'], dtype='|S4') >>> np.char.capitalize(c) array(['A1b2', '1b2a', 'B2a1', '2a1b'], dtype='|S4') """ a_arr = numpy.asarray(a) return _vec_string(a_arr, a_arr.dtype, 'capitalize') def _center_dispatcher(a, width, fillchar=None): return (a,) @array_function_dispatch(_center_dispatcher) def center(a, width, fillchar=' '): """ Return a copy of `a` with its elements centered in a string of length `width`. Calls `str.center` element-wise. Parameters ---------- a : array_like of str or unicode width : int The length of the resulting strings fillchar : str or unicode, optional The padding character to use (default is space). Returns ------- out : ndarray Output array of str or unicode, depending on input types See Also -------- str.center Notes ----- This function is intended to work with arrays of strings. The fill character is not applied to numeric types. Examples -------- >>> c = np.array(['a1b2','1b2a','b2a1','2a1b']); c array(['a1b2', '1b2a', 'b2a1', '2a1b'], dtype='<U4') >>> np.char.center(c, width=9) array([' a1b2 ', ' 1b2a ', ' b2a1 ', ' 2a1b '], dtype='<U9') >>> np.char.center(c, width=9, fillchar='*') array(['***a1b2**', '***1b2a**', '***b2a1**', '***2a1b**'], dtype='<U9') >>> np.char.center(c, width=1) array(['a', '1', 'b', '2'], dtype='<U1') """ a_arr = numpy.asarray(a) width_arr = numpy.asarray(width) size = int(numpy.max(width_arr.flat)) if numpy.issubdtype(a_arr.dtype, numpy.bytes_): fillchar = asbytes(fillchar) return _vec_string( a_arr, type(a_arr.dtype)(size), 'center', (width_arr, fillchar)) def _count_dispatcher(a, sub, start=None, end=None): return (a,) @array_function_dispatch(_count_dispatcher) def count(a, sub, start=0, end=None): """ Returns an array with the number of non-overlapping occurrences of substring `sub` in the range [`start`, `end`]. Calls `str.count` element-wise. Parameters ---------- a : array_like of str or unicode sub : str or unicode The substring to search for. start, end : int, optional Optional arguments `start` and `end` are interpreted as slice notation to specify the range in which to count. Returns ------- out : ndarray Output array of ints. See Also -------- str.count Examples -------- >>> c = np.array(['aAaAaA', ' aA ', 'abBABba']) >>> c array(['aAaAaA', ' aA ', 'abBABba'], dtype='<U7') >>> np.char.count(c, 'A') array([3, 1, 1]) >>> np.char.count(c, 'aA') array([3, 1, 0]) >>> np.char.count(c, 'A', start=1, end=4) array([2, 1, 1]) >>> np.char.count(c, 'A', start=1, end=3) array([1, 0, 0]) """ return _vec_string(a, int_, 'count', [sub, start] + _clean_args(end)) def _code_dispatcher(a, encoding=None, errors=None): return (a,) @array_function_dispatch(_code_dispatcher) def decode(a, encoding=None, errors=None): r""" Calls ``bytes.decode`` element-wise. The set of available codecs comes from the Python standard library, and may be extended at runtime. For more information, see the :mod:`codecs` module. Parameters ---------- a : array_like of str or unicode encoding : str, optional The name of an encoding errors : str, optional Specifies how to handle encoding errors Returns ------- out : ndarray See Also -------- :py:meth:`bytes.decode` Notes ----- The type of the result will depend on the encoding specified. Examples -------- >>> c = np.array([b'\x81\xc1\x81\xc1\x81\xc1', b'@@\x81\xc1@@', ... b'\x81\x82\xc2\xc1\xc2\x82\x81']) >>> c array([b'\x81\xc1\x81\xc1\x81\xc1', b'@@\x81\xc1@@', ... b'\x81\x82\xc2\xc1\xc2\x82\x81'], dtype='|S7') >>> np.char.decode(c, encoding='cp037') array(['aAaAaA', ' aA ', 'abBABba'], dtype='<U7') """ return _to_bytes_or_str_array( _vec_string(a, object_, 'decode', _clean_args(encoding, errors))) @array_function_dispatch(_code_dispatcher) def encode(a, encoding=None, errors=None): """ Calls `str.encode` element-wise. The set of available codecs comes from the Python standard library, and may be extended at runtime. For more information, see the codecs module. Parameters ---------- a : array_like of str or unicode encoding : str, optional The name of an encoding errors : str, optional Specifies how to handle encoding errors Returns ------- out : ndarray See Also -------- str.encode Notes ----- The type of the result will depend on the encoding specified. """ return _to_bytes_or_str_array( _vec_string(a, object_, 'encode', _clean_args(encoding, errors))) def _endswith_dispatcher(a, suffix, start=None, end=None): return (a,) @array_function_dispatch(_endswith_dispatcher) def endswith(a, suffix, start=0, end=None): """ Returns a boolean array which is `True` where the string element in `a` ends with `suffix`, otherwise `False`. Calls `str.endswith` element-wise. Parameters ---------- a : array_like of str or unicode suffix : str start, end : int, optional With optional `start`, test beginning at that position. With optional `end`, stop comparing at that position. Returns ------- out : ndarray Outputs an array of bools. See Also -------- str.endswith Examples -------- >>> s = np.array(['foo', 'bar']) >>> s[0] = 'foo' >>> s[1] = 'bar' >>> s array(['foo', 'bar'], dtype='<U3') >>> np.char.endswith(s, 'ar') array([False, True]) >>> np.char.endswith(s, 'a', start=1, end=2) array([False, True]) """ return _vec_string( a, bool_, 'endswith', [suffix, start] + _clean_args(end)) def _expandtabs_dispatcher(a, tabsize=None): return (a,) @array_function_dispatch(_expandtabs_dispatcher) def expandtabs(a, tabsize=8): """ Return a copy of each string element where all tab characters are replaced by one or more spaces. Calls `str.expandtabs` element-wise. Return a copy of each string element where all tab characters are replaced by one or more spaces, depending on the current column and the given `tabsize`. The column number is reset to zero after each newline occurring in the string. This doesn't understand other non-printing characters or escape sequences. Parameters ---------- a : array_like of str or unicode Input array tabsize : int, optional Replace tabs with `tabsize` number of spaces. If not given defaults to 8 spaces. Returns ------- out : ndarray Output array of str or unicode, depending on input type See Also -------- str.expandtabs """ return _to_bytes_or_str_array( _vec_string(a, object_, 'expandtabs', (tabsize,)), a) @array_function_dispatch(_count_dispatcher) def find(a, sub, start=0, end=None): """ For each element, return the lowest index in the string where substring `sub` is found. Calls `str.find` element-wise. For each element, return the lowest index in the string where substring `sub` is found, such that `sub` is contained in the range [`start`, `end`]. Parameters ---------- a : array_like of str or unicode sub : str or unicode start, end : int, optional Optional arguments `start` and `end` are interpreted as in slice notation. Returns ------- out : ndarray or int Output array of ints. Returns -1 if `sub` is not found. See Also -------- str.find Examples -------- >>> a = np.array(["NumPy is a Python library"]) >>> np.char.find(a, "Python", start=0, end=None) array([11]) """ return _vec_string( a, int_, 'find', [sub, start] + _clean_args(end)) @array_function_dispatch(_count_dispatcher) def index(a, sub, start=0, end=None): """ Like `find`, but raises `ValueError` when the substring is not found. Calls `str.index` element-wise. Parameters ---------- a : array_like of str or unicode sub : str or unicode start, end : int, optional Returns ------- out : ndarray Output array of ints. Returns -1 if `sub` is not found. See Also -------- find, str.find Examples -------- >>> a = np.array(["Computer Science"]) >>> np.char.index(a, "Science", start=0, end=None) array([9]) """ return _vec_string( a, int_, 'index', [sub, start] + _clean_args(end)) @array_function_dispatch(_unary_op_dispatcher) def isalnum(a): """ Returns true for each element if all characters in the string are alphanumeric and there is at least one character, false otherwise. Calls `str.isalnum` element-wise. For 8-bit strings, this method is locale-dependent. Parameters ---------- a : array_like of str or unicode Returns ------- out : ndarray Output array of str or unicode, depending on input type See Also -------- str.isalnum """ return _vec_string(a, bool_, 'isalnum') @array_function_dispatch(_unary_op_dispatcher) def isalpha(a): """ Returns true for each element if all characters in the string are alphabetic and there is at least one character, false otherwise. Calls `str.isalpha` element-wise. For 8-bit strings, this method is locale-dependent. Parameters ---------- a : array_like of str or unicode Returns ------- out : ndarray Output array of bools See Also -------- str.isalpha """ return _vec_string(a, bool_, 'isalpha') @array_function_dispatch(_unary_op_dispatcher) def isdigit(a): """ Returns true for each element if all characters in the string are digits and there is at least one character, false otherwise. Calls `str.isdigit` element-wise. For 8-bit strings, this method is locale-dependent. Parameters ---------- a : array_like of str or unicode Returns ------- out : ndarray Output array of bools See Also -------- str.isdigit Examples -------- >>> a = np.array(['a', 'b', '0']) >>> np.char.isdigit(a) array([False, False, True]) >>> a = np.array([['a', 'b', '0'], ['c', '1', '2']]) >>> np.char.isdigit(a) array([[False, False, True], [False, True, True]]) """ return _vec_string(a, bool_, 'isdigit') @array_function_dispatch(_unary_op_dispatcher) def islower(a): """ Returns true for each element if all cased characters in the string are lowercase and there is at least one cased character, false otherwise. Calls `str.islower` element-wise. For 8-bit strings, this method is locale-dependent. Parameters ---------- a : array_like of str or unicode Returns ------- out : ndarray Output array of bools See Also -------- str.islower """ return _vec_string(a, bool_, 'islower') @array_function_dispatch(_unary_op_dispatcher) def isspace(a): """ Returns true for each element if there are only whitespace characters in the string and there is at least one character, false otherwise. Calls `str.isspace` element-wise. For 8-bit strings, this method is locale-dependent. Parameters ---------- a : array_like of str or unicode Returns ------- out : ndarray Output array of bools See Also -------- str.isspace """ return _vec_string(a, bool_, 'isspace') @array_function_dispatch(_unary_op_dispatcher) def istitle(a): """ Returns true for each element if the element is a titlecased string and there is at least one character, false otherwise. Call `str.istitle` element-wise. For 8-bit strings, this method is locale-dependent. Parameters ---------- a : array_like of str or unicode Returns ------- out : ndarray Output array of bools See Also -------- str.istitle """ return _vec_string(a, bool_, 'istitle') @array_function_dispatch(_unary_op_dispatcher) def isupper(a): """ Return true for each element if all cased characters in the string are uppercase and there is at least one character, false otherwise. Call `str.isupper` element-wise. For 8-bit strings, this method is locale-dependent. Parameters ---------- a : array_like of str or unicode Returns ------- out : ndarray Output array of bools See Also -------- str.isupper Examples -------- >>> str = "GHC" >>> np.char.isupper(str) array(True) >>> a = np.array(["hello", "HELLO", "Hello"]) >>> np.char.isupper(a) array([False, True, False]) """ return _vec_string(a, bool_, 'isupper') def _join_dispatcher(sep, seq): return (sep, seq) @array_function_dispatch(_join_dispatcher) def join(sep, seq): """ Return a string which is the concatenation of the strings in the sequence `seq`. Calls `str.join` element-wise. Parameters ---------- sep : array_like of str or unicode seq : array_like of str or unicode Returns ------- out : ndarray Output array of str or unicode, depending on input types See Also -------- str.join Examples -------- >>> np.char.join('-', 'osd') array('o-s-d', dtype='<U5') >>> np.char.join(['-', '.'], ['ghc', 'osd']) array(['g-h-c', 'o.s.d'], dtype='<U5') """ return _to_bytes_or_str_array( _vec_string(sep, object_, 'join', (seq,)), seq) def _just_dispatcher(a, width, fillchar=None): return (a,) @array_function_dispatch(_just_dispatcher) def ljust(a, width, fillchar=' '): """ Return an array with the elements of `a` left-justified in a string of length `width`. Calls `str.ljust` element-wise. Parameters ---------- a : array_like of str or unicode width : int The length of the resulting strings fillchar : str or unicode, optional The character to use for padding Returns ------- out : ndarray Output array of str or unicode, depending on input type See Also -------- str.ljust """ a_arr = numpy.asarray(a) width_arr = numpy.asarray(width) size = int(numpy.max(width_arr.flat)) if numpy.issubdtype(a_arr.dtype, numpy.bytes_): fillchar = asbytes(fillchar) return _vec_string( a_arr, type(a_arr.dtype)(size), 'ljust', (width_arr, fillchar)) @array_function_dispatch(_unary_op_dispatcher) def lower(a): """ Return an array with the elements converted to lowercase. Call `str.lower` element-wise. For 8-bit strings, this method is locale-dependent. Parameters ---------- a : array_like, {str, unicode} Input array. Returns ------- out : ndarray, {str, unicode} Output array of str or unicode, depending on input type See Also -------- str.lower Examples -------- >>> c = np.array(['A1B C', '1BCA', 'BCA1']); c array(['A1B C', '1BCA', 'BCA1'], dtype='<U5') >>> np.char.lower(c) array(['a1b c', '1bca', 'bca1'], dtype='<U5') """ a_arr = numpy.asarray(a) return _vec_string(a_arr, a_arr.dtype, 'lower') def _strip_dispatcher(a, chars=None): return (a,) @array_function_dispatch(_strip_dispatcher) def lstrip(a, chars=None): """ For each element in `a`, return a copy with the leading characters removed. Calls `str.lstrip` element-wise. Parameters ---------- a : array-like, {str, unicode} Input array. chars : {str, unicode}, optional The `chars` argument is a string specifying the set of characters to be removed. If omitted or None, the `chars` argument defaults to removing whitespace. The `chars` argument is not a prefix; rather, all combinations of its values are stripped. Returns ------- out : ndarray, {str, unicode} Output array of str or unicode, depending on input type See Also -------- str.lstrip Examples -------- >>> c = np.array(['aAaAaA', ' aA ', 'abBABba']) >>> c array(['aAaAaA', ' aA ', 'abBABba'], dtype='<U7') The 'a' variable is unstripped from c[1] because whitespace leading. >>> np.char.lstrip(c, 'a') array(['AaAaA', ' aA ', 'bBABba'], dtype='<U7') >>> np.char.lstrip(c, 'A') # leaves c unchanged array(['aAaAaA', ' aA ', 'abBABba'], dtype='<U7') >>> (np.char.lstrip(c, ' ') == np.char.lstrip(c, '')).all() ... # XXX: is this a regression? This used to return True ... # np.char.lstrip(c,'') does not modify c at all. False >>> (np.char.lstrip(c, ' ') == np.char.lstrip(c, None)).all() True """ a_arr = numpy.asarray(a) return _vec_string(a_arr, a_arr.dtype, 'lstrip', (chars,)) def _partition_dispatcher(a, sep): return (a,) @array_function_dispatch(_partition_dispatcher) def partition(a, sep): """ Partition each element in `a` around `sep`. Calls `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, {str, unicode} Input array sep : {str, unicode} Separator to split each string element in `a`. Returns ------- out : ndarray, {str, unicode} Output array of str or unicode, depending on input type. The output array will have an extra dimension with 3 elements per input element. See Also -------- str.partition """ return _to_bytes_or_str_array( _vec_string(a, object_, 'partition', (sep,)), a) def _replace_dispatcher(a, old, new, count=None): return (a,) @array_function_dispatch(_replace_dispatcher) def replace(a, old, new, count=None): """ For each element in `a`, return a copy of the string with all occurrences of substring `old` replaced by `new`. Calls `str.replace` element-wise. Parameters ---------- a : array-like of str or unicode old, new : str or unicode count : int, optional If the optional argument `count` is given, only the first `count` occurrences are replaced. Returns ------- out : ndarray Output array of str or unicode, depending on input type See Also -------- str.replace Examples -------- >>> a = np.array(["That is a mango", "Monkeys eat mangos"]) >>> np.char.replace(a, 'mango', 'banana') array(['That is a banana', 'Monkeys eat bananas'], dtype='<U19') >>> a = np.array(["The dish is fresh", "This is it"]) >>> np.char.replace(a, 'is', 'was') array(['The dwash was fresh', 'Thwas was it'], dtype='<U19') """ return _to_bytes_or_str_array( _vec_string(a, object_, 'replace', [old, new] + _clean_args(count)), a) @array_function_dispatch(_count_dispatcher) def rfind(a, sub, start=0, end=None): """ For each element in `a`, return the highest index in the string where substring `sub` is found, such that `sub` is contained within [`start`, `end`]. Calls `str.rfind` element-wise. Parameters ---------- a : array-like of str or unicode sub : str or unicode start, end : int, optional Optional arguments `start` and `end` are interpreted as in slice notation. Returns ------- out : ndarray Output array of ints. Return -1 on failure. See Also -------- str.rfind """ return _vec_string( a, int_, 'rfind', [sub, start] + _clean_args(end)) @array_function_dispatch(_count_dispatcher) def rindex(a, sub, start=0, end=None): """ Like `rfind`, but raises `ValueError` when the substring `sub` is not found. Calls `str.rindex` element-wise. Parameters ---------- a : array-like of str or unicode sub : str or unicode start, end : int, optional Returns ------- out : ndarray Output array of ints. See Also -------- rfind, str.rindex """ return _vec_string( a, int_, 'rindex', [sub, start] + _clean_args(end)) @array_function_dispatch(_just_dispatcher) def rjust(a, width, fillchar=' '): """ Return an array with the elements of `a` right-justified in a string of length `width`. Calls `str.rjust` element-wise. Parameters ---------- a : array_like of str or unicode width : int The length of the resulting strings fillchar : str or unicode, optional The character to use for padding Returns ------- out : ndarray Output array of str or unicode, depending on input type See Also -------- str.rjust """ a_arr = numpy.asarray(a) width_arr = numpy.asarray(width) size = int(numpy.max(width_arr.flat)) if numpy.issubdtype(a_arr.dtype, numpy.bytes_): fillchar = asbytes(fillchar) return _vec_string( a_arr, type(a_arr.dtype)(size), 'rjust', (width_arr, fillchar)) @array_function_dispatch(_partition_dispatcher) def rpartition(a, sep): """ Partition (split) each element around the right-most separator. Calls `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 of str or unicode Input array sep : str or unicode Right-most separator to split each element in array. Returns ------- out : ndarray Output array of string or unicode, depending on input type. The output array will have an extra dimension with 3 elements per input element. See Also -------- str.rpartition """ return _to_bytes_or_str_array( _vec_string(a, object_, 'rpartition', (sep,)), a) def _split_dispatcher(a, sep=None, maxsplit=None): return (a,) @array_function_dispatch(_split_dispatcher) def rsplit(a, sep=None, maxsplit=None): """ For each element in `a`, return a list of the words in the string, using `sep` as the delimiter string. Calls `str.rsplit` element-wise. Except for splitting from the right, `rsplit` behaves like `split`. Parameters ---------- a : array_like of str or unicode sep : str or unicode, optional If `sep` is not specified or None, any whitespace string is a separator. maxsplit : int, optional If `maxsplit` is given, at most `maxsplit` splits are done, the rightmost ones. Returns ------- out : ndarray Array of list objects See Also -------- str.rsplit, split """ # This will return an array of lists of different sizes, so we # leave it as an object array return _vec_string( a, object_, 'rsplit', [sep] + _clean_args(maxsplit)) def _strip_dispatcher(a, chars=None): return (a,) @array_function_dispatch(_strip_dispatcher) def rstrip(a, chars=None): """ For each element in `a`, return a copy with the trailing characters removed. Calls `str.rstrip` element-wise. Parameters ---------- a : array-like of str or unicode chars : str or unicode, optional The `chars` argument is a string specifying the set of characters to be removed. If omitted or None, the `chars` argument defaults to removing whitespace. The `chars` argument is not a suffix; rather, all combinations of its values are stripped. Returns ------- out : ndarray Output array of str or unicode, depending on input type See Also -------- str.rstrip Examples -------- >>> c = np.array(['aAaAaA', 'abBABba'], dtype='S7'); c array(['aAaAaA', 'abBABba'], dtype='|S7') >>> np.char.rstrip(c, b'a') array(['aAaAaA', 'abBABb'], dtype='|S7') >>> np.char.rstrip(c, b'A') array(['aAaAa', 'abBABba'], dtype='|S7') """ a_arr = numpy.asarray(a) return _vec_string(a_arr, a_arr.dtype, 'rstrip', (chars,)) @array_function_dispatch(_split_dispatcher) def split(a, sep=None, maxsplit=None): """ For each element in `a`, return a list of the words in the string, using `sep` as the delimiter string. Calls `str.split` element-wise. Parameters ---------- a : array_like of str or unicode sep : str or unicode, optional If `sep` is not specified or None, any whitespace string is a separator. maxsplit : int, optional If `maxsplit` is given, at most `maxsplit` splits are done. Returns ------- out : ndarray Array of list objects See Also -------- str.split, rsplit """ # This will return an array of lists of different sizes, so we # leave it as an object array return _vec_string( a, object_, 'split', [sep] + _clean_args(maxsplit)) def _splitlines_dispatcher(a, keepends=None): return (a,) @array_function_dispatch(_splitlines_dispatcher) def splitlines(a, keepends=None): """ For each element in `a`, return a list of the lines in the element, breaking at line boundaries. Calls `str.splitlines` element-wise. Parameters ---------- a : array_like of str or unicode keepends : bool, optional Line breaks are not included in the resulting list unless keepends is given and true. Returns ------- out : ndarray Array of list objects See Also -------- str.splitlines """ return _vec_string( a, object_, 'splitlines', _clean_args(keepends)) def _startswith_dispatcher(a, prefix, start=None, end=None): return (a,) @array_function_dispatch(_startswith_dispatcher) def startswith(a, prefix, start=0, end=None): """ Returns a boolean array which is `True` where the string element in `a` starts with `prefix`, otherwise `False`. Calls `str.startswith` element-wise. Parameters ---------- a : array_like of str or unicode prefix : str start, end : int, optional With optional `start`, test beginning at that position. With optional `end`, stop comparing at that position. Returns ------- out : ndarray Array of booleans See Also -------- str.startswith """ return _vec_string( a, bool_, 'startswith', [prefix, start] + _clean_args(end)) @array_function_dispatch(_strip_dispatcher) def strip(a, chars=None): """ For each element in `a`, return a copy with the leading and trailing characters removed. Calls `str.strip` element-wise. Parameters ---------- a : array-like of str or unicode chars : str or unicode, optional The `chars` argument is a string specifying the set of characters to be removed. If omitted or None, the `chars` argument defaults to removing whitespace. The `chars` argument is not a prefix or suffix; rather, all combinations of its values are stripped. Returns ------- out : ndarray Output array of str or unicode, depending on input type See Also -------- str.strip Examples -------- >>> c = np.array(['aAaAaA', ' aA ', 'abBABba']) >>> c array(['aAaAaA', ' aA ', 'abBABba'], dtype='<U7') >>> np.char.strip(c) array(['aAaAaA', 'aA', 'abBABba'], dtype='<U7') >>> np.char.strip(c, 'a') # 'a' unstripped from c[1] because whitespace leads array(['AaAaA', ' aA ', 'bBABb'], dtype='<U7') >>> np.char.strip(c, 'A') # 'A' unstripped from c[1] because (unprinted) ws trails array(['aAaAa', ' aA ', 'abBABba'], dtype='<U7') """ a_arr = numpy.asarray(a) return _vec_string(a_arr, a_arr.dtype, 'strip', _clean_args(chars)) @array_function_dispatch(_unary_op_dispatcher) def swapcase(a): """ Return element-wise a copy of the string with uppercase characters converted to lowercase and vice versa. Calls `str.swapcase` element-wise. For 8-bit strings, this method is locale-dependent. Parameters ---------- a : array_like, {str, unicode} Input array. Returns ------- out : ndarray, {str, unicode} Output array of str or unicode, depending on input type See Also -------- str.swapcase Examples -------- >>> c=np.array(['a1B c','1b Ca','b Ca1','cA1b'],'S5'); c array(['a1B c', '1b Ca', 'b Ca1', 'cA1b'], dtype='|S5') >>> np.char.swapcase(c) array(['A1b C', '1B cA', 'B cA1', 'Ca1B'], dtype='|S5') """ a_arr = numpy.asarray(a) return _vec_string(a_arr, a_arr.dtype, 'swapcase') @array_function_dispatch(_unary_op_dispatcher) def title(a): """ Return element-wise title cased version of string or unicode. Title case words start with uppercase characters, all remaining cased characters are lowercase. Calls `str.title` element-wise. For 8-bit strings, this method is locale-dependent. Parameters ---------- a : array_like, {str, unicode} Input array. Returns ------- out : ndarray Output array of str or unicode, depending on input type See Also -------- str.title Examples -------- >>> c=np.array(['a1b c','1b ca','b ca1','ca1b'],'S5'); c array(['a1b c', '1b ca', 'b ca1', 'ca1b'], dtype='|S5') >>> np.char.title(c) array(['A1B C', '1B Ca', 'B Ca1', 'Ca1B'], dtype='|S5') """ a_arr = numpy.asarray(a) return _vec_string(a_arr, a_arr.dtype, 'title') def _translate_dispatcher(a, table, deletechars=None): return (a,) @array_function_dispatch(_translate_dispatcher) def translate(a, table, deletechars=None): """ For each element in `a`, 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. Calls `str.translate` element-wise. Parameters ---------- a : array-like of str or unicode table : str of length 256 deletechars : str Returns ------- out : ndarray Output array of str or unicode, depending on input type See Also -------- str.translate """ a_arr = numpy.asarray(a) if issubclass(a_arr.dtype.type, str_): return _vec_string( a_arr, a_arr.dtype, 'translate', (table,)) else: return _vec_string( a_arr, a_arr.dtype, 'translate', [table] + _clean_args(deletechars)) @array_function_dispatch(_unary_op_dispatcher) def upper(a): """ Return an array with the elements converted to uppercase. Calls `str.upper` element-wise. For 8-bit strings, this method is locale-dependent. Parameters ---------- a : array_like, {str, unicode} Input array. Returns ------- out : ndarray, {str, unicode} Output array of str or unicode, depending on input type See Also -------- str.upper Examples -------- >>> c = np.array(['a1b c', '1bca', 'bca1']); c array(['a1b c', '1bca', 'bca1'], dtype='<U5') >>> np.char.upper(c) array(['A1B C', '1BCA', 'BCA1'], dtype='<U5') """ a_arr = numpy.asarray(a) return _vec_string(a_arr, a_arr.dtype, 'upper') def _zfill_dispatcher(a, width): return (a,) @array_function_dispatch(_zfill_dispatcher) def zfill(a, width): """ Return the numeric string left-filled with zeros Calls `str.zfill` element-wise. Parameters ---------- a : array_like, {str, unicode} Input array. width : int Width of string to left-fill elements in `a`. Returns ------- out : ndarray, {str, unicode} Output array of str or unicode, depending on input type See Also -------- str.zfill """ a_arr = numpy.asarray(a) width_arr = numpy.asarray(width) size = int(numpy.max(width_arr.flat)) return _vec_string( a_arr, type(a_arr.dtype)(size), 'zfill', (width_arr,)) @array_function_dispatch(_unary_op_dispatcher) def isnumeric(a): """ For each element, return True if there are only numeric characters in the element. Calls `str.isnumeric` element-wise. Numeric characters include digit characters, and all characters that have the Unicode numeric value property, e.g. ``U+2155, VULGAR FRACTION ONE FIFTH``. Parameters ---------- a : array_like, unicode Input array. Returns ------- out : ndarray, bool Array of booleans of same shape as `a`. See Also -------- str.isnumeric Examples -------- >>> np.char.isnumeric(['123', '123abc', '9.0', '1/4', 'VIII']) array([ True, False, False, False, False]) """ if not _is_unicode(a): raise TypeError("isnumeric is only available for Unicode strings and arrays") return _vec_string(a, bool_, 'isnumeric') @array_function_dispatch(_unary_op_dispatcher) def isdecimal(a): """ For each element, return True if there are only decimal characters in the element. Calls `str.isdecimal` element-wise. Decimal characters include digit characters, and all characters that can be used to form decimal-radix numbers, e.g. ``U+0660, ARABIC-INDIC DIGIT ZERO``. Parameters ---------- a : array_like, unicode Input array. Returns ------- out : ndarray, bool Array of booleans identical in shape to `a`. See Also -------- str.isdecimal Examples -------- >>> np.char.isdecimal(['12345', '4.99', '123ABC', '']) array([ True, False, False, False]) """ if not _is_unicode(a): raise TypeError( "isdecimal is only available for Unicode strings and arrays") return _vec_string(a, bool_, 'isdecimal') @set_module('numpy') 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` `object_`, `bytes_` or `str_`, and use the free functions in the `numpy.char` module for fast vectorized string operations. Versus a regular NumPy array of type `str` or `unicode`, 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 `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 -------- >>> charar = np.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.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'): global _globalvar 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 _globalvar = 1 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 _globalvar = 0 return self def __array_finalize__(self, obj): # The b is a special case because it is used for reconstructing. if not _globalvar and self.dtype.char not in 'SUbc': raise ValueError("Can only create a chararray from string data.") def __getitem__(self, obj): val = ndarray.__getitem__(self, obj) if isinstance(val, character): temp = val.rstrip() if len(temp) == 0: val = '' else: val = temp 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 asarray(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 asarray(add(numpy.asarray(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.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 `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 `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 asarray(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 asarray(replace(self, old, new, count)) 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 `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 asarray(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 asarray(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 `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 <numpy.core.defchararray>` for fast vectorized string operations instead. Versus a regular NumPy array of type `str` or `unicode`, 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. `str.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 `chararray` can contain Unicode characters, when false only 8-bit characters. If unicode is None and `obj` is one of the following: - a `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', '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 = numpy.asarray(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 = numpy.asarray(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 `chararray`, copying the data only if necessary. Versus a regular NumPy array of type `str` or `unicode`, 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. `str.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 `chararray` can contain Unicode characters, when false only 8-bit characters. If unicode is None and `obj` is one of the following: - a `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). """ return array(obj, itemsize, copy=False, unicode=unicode, order=order)
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