"""
numerictypes: Define the numeric type objects
This module is designed so "from numerictypes import \\*" is safe.
Exported symbols include:
Dictionary with all registered number types (including aliases):
typeDict
Type objects (not all will be available, depends on platform):
see variable sctypes for which ones you have
Bit-width names
int8 int16 int32 int64 int128
uint8 uint16 uint32 uint64 uint128
float16 float32 float64 float96 float128 float256
complex32 complex64 complex128 complex192 complex256 complex512
datetime64 timedelta64
c-based names
bool_
object_
void, str_, unicode_
byte, ubyte,
short, ushort
intc, uintc,
intp, uintp,
int_, uint,
longlong, ulonglong,
single, csingle,
float_, complex_,
longfloat, clongfloat,
As part of the type-hierarchy: xx -- is bit-width
generic
+-> bool_ (kind=b)
+-> number (kind=i)
| integer
| signedinteger (intxx)
| byte
| short
| intc
| intp int0
| int_
| longlong
+-> unsignedinteger (uintxx) (kind=u)
| ubyte
| ushort
| uintc
| uintp uint0
| uint_
| ulonglong
+-> inexact
| +-> floating (floatxx) (kind=f)
| | half
| | single
| | float_ (double)
| | longfloat
| \\-> complexfloating (complexxx) (kind=c)
| csingle (singlecomplex)
| complex_ (cfloat, cdouble)
| clongfloat (longcomplex)
+-> flexible
| character
| void (kind=V)
|
| str_ (string_, bytes_) (kind=S) [Python 2]
| unicode_ (kind=U) [Python 2]
|
| bytes_ (string_) (kind=S) [Python 3]
| str_ (unicode_) (kind=U) [Python 3]
|
\\-> object_ (not used much) (kind=O)
"""
from __future__ import division, absolute_import, print_function
import types as _types
import sys
import numbers
import warnings
from numpy.compat import bytes, long
from numpy.core.multiarray import (
typeinfo, ndarray, array, empty, dtype, datetime_data,
datetime_as_string, busday_offset, busday_count, is_busday,
busdaycalendar
)
# we add more at the bottom
__all__ = ['sctypeDict', 'sctypeNA', 'typeDict', 'typeNA', 'sctypes',
'ScalarType', 'obj2sctype', 'cast', 'nbytes', 'sctype2char',
'maximum_sctype', 'issctype', 'typecodes', 'find_common_type',
'issubdtype', 'datetime_data', 'datetime_as_string',
'busday_offset', 'busday_count', 'is_busday', 'busdaycalendar',
]
# we don't export these for import *, but we do want them accessible
# as numerictypes.bool, etc.
if sys.version_info[0] >= 3:
from builtins import bool, int, float, complex, object, str
unicode = str
else:
from __builtin__ import bool, int, float, complex, object, unicode, str
# String-handling utilities to avoid locale-dependence.
# "import string" is costly to import!
# Construct the translation tables directly
# "A" = chr(65), "a" = chr(97)
_all_chars = [chr(_m) for _m in range(256)]
_ascii_upper = _all_chars[65:65+26]
_ascii_lower = _all_chars[97:97+26]
LOWER_TABLE = "".join(_all_chars[:65] + _ascii_lower + _all_chars[65+26:])
UPPER_TABLE = "".join(_all_chars[:97] + _ascii_upper + _all_chars[97+26:])
def english_lower(s):
""" Apply English case rules to convert ASCII strings to all lower case.
This is an internal utility function to replace calls to str.lower() such
that we can avoid changing behavior with changing locales. In particular,
Turkish has distinct dotted and dotless variants of the Latin letter "I" in
both lowercase and uppercase. Thus, "I".lower() != "i" in a "tr" locale.
Parameters
----------
s : str
Returns
-------
lowered : str
Examples
--------
>>> from numpy.core.numerictypes import english_lower
>>> english_lower('ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789_')
'abcdefghijklmnopqrstuvwxyzabcdefghijklmnopqrstuvwxyz0123456789_'
>>> english_lower('')
''
"""
lowered = s.translate(LOWER_TABLE)
return lowered
def english_upper(s):
""" Apply English case rules to convert ASCII strings to all upper case.
This is an internal utility function to replace calls to str.upper() such
that we can avoid changing behavior with changing locales. In particular,
Turkish has distinct dotted and dotless variants of the Latin letter "I" in
both lowercase and uppercase. Thus, "i".upper() != "I" in a "tr" locale.
Parameters
----------
s : str
Returns
-------
uppered : str
Examples
--------
>>> from numpy.core.numerictypes import english_upper
>>> english_upper('ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789_')
'ABCDEFGHIJKLMNOPQRSTUVWXYZABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789_'
>>> english_upper('')
''
"""
uppered = s.translate(UPPER_TABLE)
return uppered
def english_capitalize(s):
""" Apply English case rules to convert the first character of an ASCII
string to upper case.
This is an internal utility function to replace calls to str.capitalize()
such that we can avoid changing behavior with changing locales.
Parameters
----------
s : str
Returns
-------
capitalized : str
Examples
--------
>>> from numpy.core.numerictypes import english_capitalize
>>> english_capitalize('int8')
'Int8'
>>> english_capitalize('Int8')
'Int8'
>>> english_capitalize('')
''
"""
if s:
return english_upper(s[0]) + s[1:]
else:
return s
sctypeDict = {} # Contains all leaf-node scalar types with aliases
sctypeNA = {} # Contails all leaf-node types -> numarray type equivalences
allTypes = {} # Collect the types we will add to the module here
def _evalname(name):
k = 0
for ch in name:
if ch in '0123456789':
break
k += 1
try:
bits = int(name[k:])
except ValueError:
bits = 0
base = name[:k]
return base, bits
def bitname(obj):
"""Return a bit-width name for a given type object"""
name = obj.__name__
base = ''
char = ''
try:
if name[-1] == '_':
newname = name[:-1]
else:
newname = name
info = typeinfo[english_upper(newname)]
assert(info[-1] == obj) # sanity check
bits = info[2]
except KeyError: # bit-width name
base, bits = _evalname(name)
char = base[0]
if name == 'bool_':
char = 'b'
base = 'bool'
elif name == 'void':
char = 'V'
base = 'void'
elif name == 'object_':
char = 'O'
base = 'object'
bits = 0
elif name == 'datetime64':
char = 'M'
elif name == 'timedelta64':
char = 'm'
if sys.version_info[0] >= 3:
if name == 'bytes_':
char = 'S'
base = 'bytes'
elif name == 'str_':
char = 'U'
base = 'str'
else:
if name == 'string_':
char = 'S'
base = 'string'
elif name == 'unicode_':
char = 'U'
base = 'unicode'
bytes = bits // 8
if char != '' and bytes != 0:
char = "%s%d" % (char, bytes)
return base, bits, char
def _add_types():
for a in typeinfo.keys():
name = english_lower(a)
if isinstance(typeinfo[a], tuple):
typeobj = typeinfo[a][-1]
# define C-name and insert typenum and typechar references also
allTypes[name] = typeobj
sctypeDict[name] = typeobj
sctypeDict[typeinfo[a][0]] = typeobj
sctypeDict[typeinfo[a][1]] = typeobj
else: # generic class
allTypes[name] = typeinfo[a]
_add_types()
def _add_aliases():
for a in typeinfo.keys():
name = english_lower(a)
if not isinstance(typeinfo[a], tuple):
continue
typeobj = typeinfo[a][-1]
# insert bit-width version for this class (if relevant)
base, bit, char = bitname(typeobj)
if base[-3:] == 'int' or char[0] in 'ui':
continue
if base != '':
myname = "%s%d" % (base, bit)
if ((name != 'longdouble' and name != 'clongdouble') or
myname not in allTypes.keys()):
allTypes[myname] = typeobj
sctypeDict[myname] = typeobj
if base == 'complex':
na_name = '%s%d' % (english_capitalize(base), bit//2)
elif base == 'bool':
na_name = english_capitalize(base)
sctypeDict[na_name] = typeobj
else:
na_name = "%s%d" % (english_capitalize(base), bit)
sctypeDict[na_name] = typeobj
sctypeNA[na_name] = typeobj
sctypeDict[na_name] = typeobj
sctypeNA[typeobj] = na_name
sctypeNA[typeinfo[a][0]] = na_name
if char != '':
sctypeDict[char] = typeobj
sctypeNA[char] = na_name
_add_aliases()
# Integers are handled so that the int32 and int64 types should agree
# exactly with NPY_INT32, NPY_INT64. We need to enforce the same checking
# as is done in arrayobject.h where the order of getting a bit-width match
# is long, longlong, int, short, char.
def _add_integer_aliases():
_ctypes = ['LONG', 'LONGLONG', 'INT', 'SHORT', 'BYTE']
for ctype in _ctypes:
val = typeinfo[ctype]
bits = val[2]
charname = 'i%d' % (bits//8,)
ucharname = 'u%d' % (bits//8,)
intname = 'int%d' % bits
UIntname = 'UInt%d' % bits
Intname = 'Int%d' % bits
uval = typeinfo['U'+ctype]
typeobj = val[-1]
utypeobj = uval[-1]
if intname not in allTypes.keys():
uintname = 'uint%d' % bits
allTypes[intname] = typeobj
allTypes[uintname] = utypeobj
sctypeDict[intname] = typeobj
sctypeDict[uintname] = utypeobj
sctypeDict[Intname] = typeobj
sctypeDict[UIntname] = utypeobj
sctypeDict[charname] = typeobj
sctypeDict[ucharname] = utypeobj
sctypeNA[Intname] = typeobj
sctypeNA[UIntname] = utypeobj
sctypeNA[charname] = typeobj
sctypeNA[ucharname] = utypeobj
sctypeNA[typeobj] = Intname
sctypeNA[utypeobj] = UIntname
sctypeNA[val[0]] = Intname
sctypeNA[uval[0]] = UIntname
_add_integer_aliases()
# We use these later
void = allTypes['void']
generic = allTypes['generic']
#
# Rework the Python names (so that float and complex and int are consistent
# with Python usage)
#
def _set_up_aliases():
type_pairs = [('complex_', 'cdouble'),
('int0', 'intp'),
('uint0', 'uintp'),
('single', 'float'),
('csingle', 'cfloat'),
('singlecomplex', 'cfloat'),
('float_', 'double'),
('intc', 'int'),
('uintc', 'uint'),
('int_', 'long'),
('uint', 'ulong'),
('cfloat', 'cdouble'),
('longfloat', 'longdouble'),
('clongfloat', 'clongdouble'),
('longcomplex', 'clongdouble'),
('bool_', 'bool'),
('unicode_', 'unicode'),
('object_', 'object')]
if sys.version_info[0] >= 3:
type_pairs.extend([('bytes_', 'string'),
('str_', 'unicode'),
('string_', 'string')])
else:
type_pairs.extend([('str_', 'string'),
('string_', 'string'),
('bytes_', 'string')])
for alias, t in type_pairs:
allTypes[alias] = allTypes[t]
sctypeDict[alias] = sctypeDict[t]
# Remove aliases overriding python types and modules
to_remove = ['ulong', 'object', 'unicode', 'int', 'long', 'float',
'complex', 'bool', 'string', 'datetime', 'timedelta']
if sys.version_info[0] >= 3:
# Py3K
to_remove.append('bytes')
to_remove.append('str')
to_remove.remove('unicode')
to_remove.remove('long')
for t in to_remove:
try:
del allTypes[t]
del sctypeDict[t]
except KeyError:
pass
_set_up_aliases()
# Now, construct dictionary to lookup character codes from types
_sctype2char_dict = {}
def _construct_char_code_lookup():
for name in typeinfo.keys():
tup = typeinfo[name]
if isinstance(tup, tuple):
if tup[0] not in ['p', 'P']:
_sctype2char_dict[tup[-1]] = tup[0]
_construct_char_code_lookup()
sctypes = {'int': [],
'uint':[],
'float':[],
'complex':[],
'others':[bool, object, bytes, unicode, void]}
def _add_array_type(typename, bits):
try:
t = allTypes['%s%d' % (typename, bits)]
except KeyError:
pass
else:
sctypes[typename].append(t)
def _set_array_types():
ibytes = [1, 2, 4, 8, 16, 32, 64]
fbytes = [2, 4, 8, 10, 12, 16, 32, 64]
for bytes in ibytes:
bits = 8*bytes
_add_array_type('int', bits)
_add_array_type('uint', bits)
for bytes in fbytes:
bits = 8*bytes
_add_array_type('float', bits)
_add_array_type('complex', 2*bits)
_gi = dtype('p')
if _gi.type not in sctypes['int']:
indx = 0
sz = _gi.itemsize
_lst = sctypes['int']
while (indx < len(_lst) and sz >= _lst[indx](0).itemsize):
indx += 1
sctypes['int'].insert(indx, _gi.type)
sctypes['uint'].insert(indx, dtype('P').type)
_set_array_types()
genericTypeRank = ['bool', 'int8', 'uint8', 'int16', 'uint16',
'int32', 'uint32', 'int64', 'uint64', 'int128',
'uint128', 'float16',
'float32', 'float64', 'float80', 'float96', 'float128',
'float256',
'complex32', 'complex64', 'complex128', 'complex160',
'complex192', 'complex256', 'complex512', 'object']
def maximum_sctype(t):
"""
Return the scalar type of highest precision of the same kind as the input.
Parameters
----------
t : dtype or dtype specifier
The input data type. This can be a `dtype` object or an object that
is convertible to a `dtype`.
Returns
-------
out : dtype
The highest precision data type of the same kind (`dtype.kind`) as `t`.
See Also
--------
obj2sctype, mintypecode, sctype2char
dtype
Examples
--------
>>> np.maximum_sctype(int)
<type 'numpy.int64'>
>>> np.maximum_sctype(np.uint8)
<type 'numpy.uint64'>
>>> np.maximum_sctype(complex)
<type 'numpy.complex192'>
>>> np.maximum_sctype(str)
<type 'numpy.string_'>
>>> np.maximum_sctype('i2')
<type 'numpy.int64'>
>>> np.maximum_sctype('f4')
<type 'numpy.float96'>
"""
g = obj2sctype(t)
if g is None:
return t
t = g
name = t.__name__
base, bits = _evalname(name)
if bits == 0:
return t
else:
return sctypes[base][-1]
def issctype(rep):
"""
Determines whether the given object represents a scalar data-type.
Parameters
----------
rep : any
If `rep` is an instance of a scalar dtype, True is returned. If not,
False is returned.
Returns
-------
out : bool
Boolean result of check whether `rep` is a scalar dtype.
See Also
--------
issubsctype, issubdtype, obj2sctype, sctype2char
Examples
--------
>>> np.issctype(np.int32)
True
>>> np.issctype(list)
False
>>> np.issctype(1.1)
False
Strings are also a scalar type:
>>> np.issctype(np.dtype('str'))
True
"""
if not isinstance(rep, (type, dtype)):
return False
try:
res = obj2sctype(rep)
if res and res != object_:
return True
return False
except Exception:
return False
def obj2sctype(rep, default=None):
"""
Return the scalar dtype or NumPy equivalent of Python type of an object.
Parameters
----------
rep : any
The object of which the type is returned.
default : any, optional
If given, this is returned for objects whose types can not be
determined. If not given, None is returned for those objects.
Returns
-------
dtype : dtype or Python type
The data type of `rep`.
See Also
--------
sctype2char, issctype, issubsctype, issubdtype, maximum_sctype
Examples
--------
>>> np.obj2sctype(np.int32)
<type 'numpy.int32'>
>>> np.obj2sctype(np.array([1., 2.]))
<type 'numpy.float64'>
>>> np.obj2sctype(np.array([1.j]))
<type 'numpy.complex128'>
>>> np.obj2sctype(dict)
<type 'numpy.object_'>
>>> np.obj2sctype('string')
<type 'numpy.string_'>
>>> np.obj2sctype(1, default=list)
<type 'list'>
"""
# prevent abtract classes being upcast
if isinstance(rep, type) and issubclass(rep, generic):
return rep
# extract dtype from arrays
if isinstance(rep, ndarray):
return rep.dtype.type
# fall back on dtype to convert
try:
res = dtype(rep)
except Exception:
return default
else:
return res.type
def issubclass_(arg1, arg2):
"""
Determine if a class is a subclass of a second class.
`issubclass_` is equivalent to the Python built-in ``issubclass``,
except that it returns False instead of raising a TypeError if one
of the arguments is not a class.
Parameters
----------
arg1 : class
Input class. True is returned if `arg1` is a subclass of `arg2`.
arg2 : class or tuple of classes.
Input class. If a tuple of classes, True is returned if `arg1` is a
subclass of any of the tuple elements.
Returns
-------
out : bool
Whether `arg1` is a subclass of `arg2` or not.
See Also
--------
issubsctype, issubdtype, issctype
Examples
--------
>>> np.issubclass_(np.int32, int)
True
>>> np.issubclass_(np.int32, float)
False
"""
try:
return issubclass(arg1, arg2)
except TypeError:
return False
def issubsctype(arg1, arg2):
"""
Determine if the first argument is a subclass of the second argument.
Parameters
----------
arg1, arg2 : dtype or dtype specifier
Data-types.
Returns
-------
out : bool
The result.
See Also
--------
issctype, issubdtype,obj2sctype
Examples
--------
>>> np.issubsctype('S8', str)
True
>>> np.issubsctype(np.array([1]), int)
True
>>> np.issubsctype(np.array([1]), float)
False
"""
return issubclass(obj2sctype(arg1), obj2sctype(arg2))
def issubdtype(arg1, arg2):
"""
Returns True if first argument is a typecode lower/equal in type hierarchy.
Parameters
----------
arg1, arg2 : dtype_like
dtype or string representing a typecode.
Returns
-------
out : bool
See Also
--------
issubsctype, issubclass_
numpy.core.numerictypes : Overview of numpy type hierarchy.
Examples
--------
>>> np.issubdtype('S1', np.string_)
True
>>> np.issubdtype(np.float64, np.float32)
False
"""
if not issubclass_(arg1, generic):
arg1 = dtype(arg1).type
if not issubclass_(arg2, generic):
arg2_orig = arg2
arg2 = dtype(arg2).type
if not isinstance(arg2_orig, dtype):
# weird deprecated behaviour, that tried to infer np.floating from
# float, and similar less obvious things, such as np.generic from
# basestring
mro = arg2.mro()
arg2 = mro[1] if len(mro) > 1 else mro[0]
def type_repr(x):
""" Helper to produce clear error messages """
if not isinstance(x, type):
return repr(x)
elif issubclass(x, generic):
return "np.{}".format(x.__name__)
else:
return x.__name__
# 1.14, 2017-08-01
warnings.warn(
"Conversion of the second argument of issubdtype from `{raw}` "
"to `{abstract}` is deprecated. In future, it will be treated "
"as `{concrete} == np.dtype({raw}).type`.".format(
raw=type_repr(arg2_orig),
abstract=type_repr(arg2),
concrete=type_repr(dtype(arg2_orig).type)
),
FutureWarning, stacklevel=2
)
return issubclass(arg1, arg2)
# This dictionary allows look up based on any alias for an array data-type
class _typedict(dict):
"""
Base object for a dictionary for look-up with any alias for an array dtype.
Instances of `_typedict` can not be used as dictionaries directly,
first they have to be populated.
"""
def __getitem__(self, obj):
return dict.__getitem__(self, obj2sctype(obj))
nbytes = _typedict()
_alignment = _typedict()
_maxvals = _typedict()
_minvals = _typedict()
def _construct_lookups():
for name, val in typeinfo.items():
if not isinstance(val, tuple):
continue
obj = val[-1]
nbytes[obj] = val[2] // 8
_alignment[obj] = val[3]
if (len(val) > 5):
_maxvals[obj] = val[4]
_minvals[obj] = val[5]
else:
_maxvals[obj] = None
_minvals[obj] = None
_construct_lookups()
def sctype2char(sctype):
"""
Return the string representation of a scalar dtype.
Parameters
----------
sctype : scalar dtype or object
If a scalar dtype, the corresponding string character is
returned. If an object, `sctype2char` tries to infer its scalar type
and then return the corresponding string character.
Returns
-------
typechar : str
The string character corresponding to the scalar type.
Raises
------
ValueError
If `sctype` is an object for which the type can not be inferred.
See Also
--------
obj2sctype, issctype, issubsctype, mintypecode
Examples
--------
>>> for sctype in [np.int32, float, complex, np.string_, np.ndarray]:
... print(np.sctype2char(sctype))
l
d
D
S
O
>>> x = np.array([1., 2-1.j])
>>> np.sctype2char(x)
'D'
>>> np.sctype2char(list)
'O'
"""
sctype = obj2sctype(sctype)
if sctype is None:
raise ValueError("unrecognized type")
return _sctype2char_dict[sctype]
# Create dictionary of casting functions that wrap sequences
# indexed by type or type character
cast = _typedict()
try:
ScalarType = [_types.IntType, _types.FloatType, _types.ComplexType,
_types.LongType, _types.BooleanType,
_types.StringType, _types.UnicodeType, _types.BufferType]
except AttributeError:
# Py3K
ScalarType = [int, float, complex, int, bool, bytes, str, memoryview]
ScalarType.extend(_sctype2char_dict.keys())
ScalarType = tuple(ScalarType)
for key in _sctype2char_dict.keys():
cast[key] = lambda x, k=key: array(x, copy=False).astype(k)
# Create the typestring lookup dictionary
_typestr = _typedict()
for key in _sctype2char_dict.keys():
if issubclass(key, allTypes['flexible']):
_typestr[key] = _sctype2char_dict[key]
else:
_typestr[key] = empty((1,), key).dtype.str[1:]
# Make sure all typestrings are in sctypeDict
for key, val in _typestr.items():
if val not in sctypeDict:
sctypeDict[val] = key
# Add additional strings to the sctypeDict
if sys.version_info[0] >= 3:
_toadd = ['int', 'float', 'complex', 'bool', 'object',
'str', 'bytes', 'object', ('a', allTypes['bytes_'])]
else:
_toadd = ['int', 'float', 'complex', 'bool', 'object', 'string',
('str', allTypes['string_']),
'unicode', 'object', ('a', allTypes['string_'])]
for name in _toadd:
if isinstance(name, tuple):
sctypeDict[name[0]] = name[1]
else:
sctypeDict[name] = allTypes['%s_' % name]
del _toadd, name
# Now add the types we've determined to this module
for key in allTypes:
globals()[key] = allTypes[key]
__all__.append(key)
del key
typecodes = {'Character':'c',
'Integer':'bhilqp',
'UnsignedInteger':'BHILQP',
'Float':'efdg',
'Complex':'FDG',
'AllInteger':'bBhHiIlLqQpP',
'AllFloat':'efdgFDG',
'Datetime': 'Mm',
'All':'?bhilqpBHILQPefdgFDGSUVOMm'}
# backwards compatibility --- deprecated name
typeDict = sctypeDict
typeNA = sctypeNA
# b -> boolean
# u -> unsigned integer
# i -> signed integer
# f -> floating point
# c -> complex
# M -> datetime
# m -> timedelta
# S -> string
# U -> Unicode string
# V -> record
# O -> Python object
_kind_list = ['b', 'u', 'i', 'f', 'c', 'S', 'U', 'V', 'O', 'M', 'm']
__test_types = '?'+typecodes['AllInteger'][:-2]+typecodes['AllFloat']+'O'
__len_test_types = len(__test_types)
# Keep incrementing until a common type both can be coerced to
# is found. Otherwise, return None
def _find_common_coerce(a, b):
if a > b:
return a
try:
thisind = __test_types.index(a.char)
except ValueError:
return None
return _can_coerce_all([a, b], start=thisind)
# Find a data-type that all data-types in a list can be coerced to
def _can_coerce_all(dtypelist, start=0):
N = len(dtypelist)
if N == 0:
return None
if N == 1:
return dtypelist[0]
thisind = start
while thisind < __len_test_types:
newdtype = dtype(__test_types[thisind])
numcoerce = len([x for x in dtypelist if newdtype >= x])
if numcoerce == N:
return newdtype
thisind += 1
return None
def _register_types():
numbers.Integral.register(integer)
numbers.Complex.register(inexact)
numbers.Real.register(floating)
numbers.Number.register(number)
_register_types()
def find_common_type(array_types, scalar_types):
"""
Determine common type following standard coercion rules.
Parameters
----------
array_types : sequence
A list of dtypes or dtype convertible objects representing arrays.
scalar_types : sequence
A list of dtypes or dtype convertible objects representing scalars.
Returns
-------
datatype : dtype
The common data type, which is the maximum of `array_types` ignoring
`scalar_types`, unless the maximum of `scalar_types` is of a
different kind (`dtype.kind`). If the kind is not understood, then
None is returned.
See Also
--------
dtype, common_type, can_cast, mintypecode
Examples
--------
>>> np.find_common_type([], [np.int64, np.float32, complex])
dtype('complex128')
>>> np.find_common_type([np.int64, np.float32], [])
dtype('float64')
The standard casting rules ensure that a scalar cannot up-cast an
array unless the scalar is of a fundamentally different kind of data
(i.e. under a different hierarchy in the data type hierarchy) then
the array:
>>> np.find_common_type([np.float32], [np.int64, np.float64])
dtype('float32')
Complex is of a different type, so it up-casts the float in the
`array_types` argument:
>>> np.find_common_type([np.float32], [complex])
dtype('complex128')
Type specifier strings are convertible to dtypes and can therefore
be used instead of dtypes:
>>> np.find_common_type(['f4', 'f4', 'i4'], ['c8'])
dtype('complex128')
"""
array_types = [dtype(x) for x in array_types]
scalar_types = [dtype(x) for x in scalar_types]
maxa = _can_coerce_all(array_types)
maxsc = _can_coerce_all(scalar_types)
if maxa is None:
return maxsc
if maxsc is None:
return maxa
try:
index_a = _kind_list.index(maxa.kind)
index_sc = _kind_list.index(maxsc.kind)
except ValueError:
return None
if index_sc > index_a:
return _find_common_coerce(maxsc, maxa)
else:
return maxa