560 lines
18 KiB
Python
560 lines
18 KiB
Python
"""Machine limits for Float32 and Float64 and (long double) if available...
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"""
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from __future__ import division, absolute_import, print_function
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__all__ = ['finfo', 'iinfo']
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import warnings
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from .machar import MachAr
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from . import numeric
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from . import numerictypes as ntypes
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from .numeric import array, inf
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from .umath import log10, exp2
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from . import umath
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def _fr0(a):
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"""fix rank-0 --> rank-1"""
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if a.ndim == 0:
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a = a.copy()
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a.shape = (1,)
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return a
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def _fr1(a):
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"""fix rank > 0 --> rank-0"""
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if a.size == 1:
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a = a.copy()
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a.shape = ()
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return a
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_convert_to_float = {
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ntypes.csingle: ntypes.single,
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ntypes.complex_: ntypes.float_,
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ntypes.clongfloat: ntypes.longfloat
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}
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# Parameters for creating MachAr / MachAr-like objects
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_title_fmt = 'numpy {} precision floating point number'
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_MACHAR_PARAMS = {
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ntypes.double: dict(
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itype = ntypes.int64,
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fmt = '%24.16e',
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title = _title_fmt.format('double')),
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ntypes.single: dict(
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itype = ntypes.int32,
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fmt = '%15.7e',
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title = _title_fmt.format('single')),
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ntypes.longdouble: dict(
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itype = ntypes.longlong,
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fmt = '%s',
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title = _title_fmt.format('long double')),
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ntypes.half: dict(
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itype = ntypes.int16,
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fmt = '%12.5e',
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title = _title_fmt.format('half'))}
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class MachArLike(object):
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""" Object to simulate MachAr instance """
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def __init__(self,
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ftype,
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**kwargs):
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params = _MACHAR_PARAMS[ftype]
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float_conv = lambda v: array([v], ftype)
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float_to_float = lambda v : _fr1(float_conv(v))
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self._float_to_str = lambda v: (params['fmt'] %
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array(_fr0(v)[0], ftype))
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self.title = params['title']
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# Parameter types same as for discovered MachAr object.
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self.epsilon = self.eps = float_to_float(kwargs.pop('eps'))
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self.epsneg = float_to_float(kwargs.pop('epsneg'))
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self.xmax = self.huge = float_to_float(kwargs.pop('huge'))
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self.xmin = self.tiny = float_to_float(kwargs.pop('tiny'))
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self.ibeta = params['itype'](kwargs.pop('ibeta'))
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self.__dict__.update(kwargs)
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self.precision = int(-log10(self.eps))
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self.resolution = float_to_float(float_conv(10) ** (-self.precision))
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# Properties below to delay need for float_to_str, and thus avoid circular
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# imports during early numpy module loading.
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# See: https://github.com/numpy/numpy/pull/8983#discussion_r115838683
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@property
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def _str_eps(self):
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return self._float_to_str(self.eps)
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@property
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def _str_epsneg(self):
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return self._float_to_str(self.epsneg)
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@property
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def _str_xmin(self):
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return self._float_to_str(self.xmin)
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@property
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def _str_xmax(self):
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return self._float_to_str(self.xmax)
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@property
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def _str_resolution(self):
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return self._float_to_str(self.resolution)
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# Known parameters for float16
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# See docstring of MachAr class for description of parameters.
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_f16 = ntypes.float16
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_float16_ma = MachArLike(_f16,
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machep=-10,
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negep=-11,
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minexp=-14,
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maxexp=16,
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it=10,
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iexp=5,
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ibeta=2,
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irnd=5,
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ngrd=0,
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eps=exp2(_f16(-10)),
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epsneg=exp2(_f16(-11)),
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huge=_f16(65504),
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tiny=_f16(2 ** -14))
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# Known parameters for float32
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_f32 = ntypes.float32
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_float32_ma = MachArLike(_f32,
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machep=-23,
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negep=-24,
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minexp=-126,
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maxexp=128,
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it=23,
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iexp=8,
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ibeta=2,
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irnd=5,
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ngrd=0,
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eps=exp2(_f32(-23)),
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epsneg=exp2(_f32(-24)),
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huge=_f32((1 - 2 ** -24) * 2**128),
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tiny=exp2(_f32(-126)))
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# Known parameters for float64
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_f64 = ntypes.float64
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_epsneg_f64 = 2.0 ** -53.0
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_tiny_f64 = 2.0 ** -1022.0
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_float64_ma = MachArLike(_f64,
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machep=-52,
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negep=-53,
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minexp=-1022,
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maxexp=1024,
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it=52,
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iexp=11,
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ibeta=2,
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irnd=5,
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ngrd=0,
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eps=2.0 ** -52.0,
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epsneg=_epsneg_f64,
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huge=(1.0 - _epsneg_f64) / _tiny_f64 * _f64(4),
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tiny=_tiny_f64)
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# Known parameters for IEEE 754 128-bit binary float
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_ld = ntypes.longdouble
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_epsneg_f128 = exp2(_ld(-113))
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_tiny_f128 = exp2(_ld(-16382))
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# Ignore runtime error when this is not f128
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with numeric.errstate(all='ignore'):
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_huge_f128 = (_ld(1) - _epsneg_f128) / _tiny_f128 * _ld(4)
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_float128_ma = MachArLike(_ld,
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machep=-112,
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negep=-113,
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minexp=-16382,
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maxexp=16384,
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it=112,
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iexp=15,
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ibeta=2,
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irnd=5,
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ngrd=0,
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eps=exp2(_ld(-112)),
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epsneg=_epsneg_f128,
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huge=_huge_f128,
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tiny=_tiny_f128)
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# Known parameters for float80 (Intel 80-bit extended precision)
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_epsneg_f80 = exp2(_ld(-64))
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_tiny_f80 = exp2(_ld(-16382))
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# Ignore runtime error when this is not f80
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with numeric.errstate(all='ignore'):
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_huge_f80 = (_ld(1) - _epsneg_f80) / _tiny_f80 * _ld(4)
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_float80_ma = MachArLike(_ld,
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machep=-63,
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negep=-64,
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minexp=-16382,
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maxexp=16384,
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it=63,
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iexp=15,
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ibeta=2,
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irnd=5,
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ngrd=0,
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eps=exp2(_ld(-63)),
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epsneg=_epsneg_f80,
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huge=_huge_f80,
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tiny=_tiny_f80)
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# Guessed / known parameters for double double; see:
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# https://en.wikipedia.org/wiki/Quadruple-precision_floating-point_format#Double-double_arithmetic
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# These numbers have the same exponent range as float64, but extended number of
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# digits in the significand.
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_huge_dd = (umath.nextafter(_ld(inf), _ld(0))
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if hasattr(umath, 'nextafter') # Missing on some platforms?
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else _float64_ma.huge)
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_float_dd_ma = MachArLike(_ld,
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machep=-105,
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negep=-106,
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minexp=-1022,
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maxexp=1024,
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it=105,
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iexp=11,
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ibeta=2,
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irnd=5,
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ngrd=0,
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eps=exp2(_ld(-105)),
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epsneg= exp2(_ld(-106)),
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huge=_huge_dd,
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tiny=exp2(_ld(-1022)))
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# Key to identify the floating point type. Key is result of
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# ftype('-0.1').newbyteorder('<').tobytes()
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# See:
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# https://perl5.git.perl.org/perl.git/blob/3118d7d684b56cbeb702af874f4326683c45f045:/Configure
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_KNOWN_TYPES = {
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b'\x9a\x99\x99\x99\x99\x99\xb9\xbf' : _float64_ma,
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b'\xcd\xcc\xcc\xbd' : _float32_ma,
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b'f\xae' : _float16_ma,
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# float80, first 10 bytes containing actual storage
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b'\xcd\xcc\xcc\xcc\xcc\xcc\xcc\xcc\xfb\xbf' : _float80_ma,
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# double double; low, high order (e.g. PPC 64)
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b'\x9a\x99\x99\x99\x99\x99Y<\x9a\x99\x99\x99\x99\x99\xb9\xbf' :
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_float_dd_ma,
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# double double; high, low order (e.g. PPC 64 le)
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b'\x9a\x99\x99\x99\x99\x99\xb9\xbf\x9a\x99\x99\x99\x99\x99Y<' :
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_float_dd_ma,
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# IEEE 754 128-bit binary float
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b'\x9a\x99\x99\x99\x99\x99\x99\x99\x99\x99\x99\x99\x99\x99\xfb\xbf' :
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_float128_ma,
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}
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def _get_machar(ftype):
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""" Get MachAr instance or MachAr-like instance
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Get parameters for floating point type, by first trying signatures of
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various known floating point types, then, if none match, attempting to
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identify parameters by analysis.
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Parameters
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----------
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ftype : class
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Numpy floating point type class (e.g. ``np.float64``)
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Returns
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-------
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ma_like : instance of :class:`MachAr` or :class:`MachArLike`
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Object giving floating point parameters for `ftype`.
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Warns
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-----
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UserWarning
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If the binary signature of the float type is not in the dictionary of
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known float types.
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"""
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params = _MACHAR_PARAMS.get(ftype)
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if params is None:
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raise ValueError(repr(ftype))
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# Detect known / suspected types
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key = ftype('-0.1').newbyteorder('<').tobytes()
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ma_like = _KNOWN_TYPES.get(key)
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# Could be 80 bit == 10 byte extended precision, where last bytes can be
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# random garbage. Try comparing first 10 bytes to pattern.
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if ma_like is None and ftype == ntypes.longdouble:
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ma_like = _KNOWN_TYPES.get(key[:10])
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if ma_like is not None:
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return ma_like
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# Fall back to parameter discovery
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warnings.warn(
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'Signature {} for {} does not match any known type: '
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'falling back to type probe function'.format(key, ftype),
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UserWarning, stacklevel=2)
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return _discovered_machar(ftype)
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def _discovered_machar(ftype):
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""" Create MachAr instance with found information on float types
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"""
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params = _MACHAR_PARAMS[ftype]
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return MachAr(lambda v: array([v], ftype),
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lambda v:_fr0(v.astype(params['itype']))[0],
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lambda v:array(_fr0(v)[0], ftype),
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lambda v: params['fmt'] % array(_fr0(v)[0], ftype),
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params['title'])
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class finfo(object):
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"""
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finfo(dtype)
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Machine limits for floating point types.
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Attributes
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----------
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bits : int
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The number of bits occupied by the type.
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eps : float
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The smallest representable positive number such that
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``1.0 + eps != 1.0``. Type of `eps` is an appropriate floating
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point type.
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epsneg : floating point number of the appropriate type
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The smallest representable positive number such that
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``1.0 - epsneg != 1.0``.
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iexp : int
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The number of bits in the exponent portion of the floating point
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representation.
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machar : MachAr
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The object which calculated these parameters and holds more
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detailed information.
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machep : int
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The exponent that yields `eps`.
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max : floating point number of the appropriate type
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The largest representable number.
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maxexp : int
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The smallest positive power of the base (2) that causes overflow.
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min : floating point number of the appropriate type
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The smallest representable number, typically ``-max``.
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minexp : int
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The most negative power of the base (2) consistent with there
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being no leading 0's in the mantissa.
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negep : int
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The exponent that yields `epsneg`.
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nexp : int
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The number of bits in the exponent including its sign and bias.
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nmant : int
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The number of bits in the mantissa.
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precision : int
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The approximate number of decimal digits to which this kind of
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float is precise.
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resolution : floating point number of the appropriate type
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The approximate decimal resolution of this type, i.e.,
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``10**-precision``.
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tiny : float
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The smallest positive usable number. Type of `tiny` is an
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appropriate floating point type.
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Parameters
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----------
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dtype : float, dtype, or instance
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Kind of floating point data-type about which to get information.
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See Also
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--------
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MachAr : The implementation of the tests that produce this information.
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iinfo : The equivalent for integer data types.
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Notes
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-----
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For developers of NumPy: do not instantiate this at the module level.
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The initial calculation of these parameters is expensive and negatively
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impacts import times. These objects are cached, so calling ``finfo()``
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repeatedly inside your functions is not a problem.
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"""
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_finfo_cache = {}
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def __new__(cls, dtype):
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try:
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dtype = numeric.dtype(dtype)
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except TypeError:
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# In case a float instance was given
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dtype = numeric.dtype(type(dtype))
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obj = cls._finfo_cache.get(dtype, None)
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if obj is not None:
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return obj
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dtypes = [dtype]
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newdtype = numeric.obj2sctype(dtype)
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if newdtype is not dtype:
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dtypes.append(newdtype)
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dtype = newdtype
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if not issubclass(dtype, numeric.inexact):
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raise ValueError("data type %r not inexact" % (dtype))
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obj = cls._finfo_cache.get(dtype, None)
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if obj is not None:
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return obj
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if not issubclass(dtype, numeric.floating):
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newdtype = _convert_to_float[dtype]
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if newdtype is not dtype:
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dtypes.append(newdtype)
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dtype = newdtype
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obj = cls._finfo_cache.get(dtype, None)
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if obj is not None:
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return obj
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obj = object.__new__(cls)._init(dtype)
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for dt in dtypes:
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cls._finfo_cache[dt] = obj
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return obj
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def _init(self, dtype):
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self.dtype = numeric.dtype(dtype)
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machar = _get_machar(dtype)
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for word in ['precision', 'iexp',
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'maxexp', 'minexp', 'negep',
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'machep']:
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setattr(self, word, getattr(machar, word))
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for word in ['tiny', 'resolution', 'epsneg']:
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setattr(self, word, getattr(machar, word).flat[0])
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self.bits = self.dtype.itemsize * 8
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self.max = machar.huge.flat[0]
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self.min = -self.max
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self.eps = machar.eps.flat[0]
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self.nexp = machar.iexp
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self.nmant = machar.it
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self.machar = machar
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self._str_tiny = machar._str_xmin.strip()
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self._str_max = machar._str_xmax.strip()
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self._str_epsneg = machar._str_epsneg.strip()
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self._str_eps = machar._str_eps.strip()
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self._str_resolution = machar._str_resolution.strip()
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return self
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def __str__(self):
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fmt = (
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'Machine parameters for %(dtype)s\n'
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'---------------------------------------------------------------\n'
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'precision = %(precision)3s resolution = %(_str_resolution)s\n'
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'machep = %(machep)6s eps = %(_str_eps)s\n'
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'negep = %(negep)6s epsneg = %(_str_epsneg)s\n'
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'minexp = %(minexp)6s tiny = %(_str_tiny)s\n'
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'maxexp = %(maxexp)6s max = %(_str_max)s\n'
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'nexp = %(nexp)6s min = -max\n'
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'---------------------------------------------------------------\n'
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)
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return fmt % self.__dict__
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def __repr__(self):
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c = self.__class__.__name__
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d = self.__dict__.copy()
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d['klass'] = c
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return (("%(klass)s(resolution=%(resolution)s, min=-%(_str_max)s,"
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" max=%(_str_max)s, dtype=%(dtype)s)") % d)
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class iinfo(object):
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"""
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iinfo(type)
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Machine limits for integer types.
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Attributes
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----------
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bits : int
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The number of bits occupied by the type.
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min : int
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The smallest integer expressible by the type.
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max : int
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The largest integer expressible by the type.
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Parameters
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----------
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int_type : integer type, dtype, or instance
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The kind of integer data type to get information about.
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See Also
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--------
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finfo : The equivalent for floating point data types.
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Examples
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--------
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With types:
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>>> ii16 = np.iinfo(np.int16)
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>>> ii16.min
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-32768
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>>> ii16.max
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32767
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>>> ii32 = np.iinfo(np.int32)
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>>> ii32.min
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-2147483648
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>>> ii32.max
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2147483647
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With instances:
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>>> ii32 = np.iinfo(np.int32(10))
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>>> ii32.min
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-2147483648
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>>> ii32.max
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2147483647
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"""
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_min_vals = {}
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_max_vals = {}
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def __init__(self, int_type):
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try:
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self.dtype = numeric.dtype(int_type)
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|
except TypeError:
|
|
self.dtype = numeric.dtype(type(int_type))
|
|
self.kind = self.dtype.kind
|
|
self.bits = self.dtype.itemsize * 8
|
|
self.key = "%s%d" % (self.kind, self.bits)
|
|
if self.kind not in 'iu':
|
|
raise ValueError("Invalid integer data type.")
|
|
|
|
def min(self):
|
|
"""Minimum value of given dtype."""
|
|
if self.kind == 'u':
|
|
return 0
|
|
else:
|
|
try:
|
|
val = iinfo._min_vals[self.key]
|
|
except KeyError:
|
|
val = int(-(1 << (self.bits-1)))
|
|
iinfo._min_vals[self.key] = val
|
|
return val
|
|
|
|
min = property(min)
|
|
|
|
def max(self):
|
|
"""Maximum value of given dtype."""
|
|
try:
|
|
val = iinfo._max_vals[self.key]
|
|
except KeyError:
|
|
if self.kind == 'u':
|
|
val = int((1 << self.bits) - 1)
|
|
else:
|
|
val = int((1 << (self.bits-1)) - 1)
|
|
iinfo._max_vals[self.key] = val
|
|
return val
|
|
|
|
max = property(max)
|
|
|
|
def __str__(self):
|
|
"""String representation."""
|
|
fmt = (
|
|
'Machine parameters for %(dtype)s\n'
|
|
'---------------------------------------------------------------\n'
|
|
'min = %(min)s\n'
|
|
'max = %(max)s\n'
|
|
'---------------------------------------------------------------\n'
|
|
)
|
|
return fmt % {'dtype': self.dtype, 'min': self.min, 'max': self.max}
|
|
|
|
def __repr__(self):
|
|
return "%s(min=%s, max=%s, dtype=%s)" % (self.__class__.__name__,
|
|
self.min, self.max, self.dtype)
|
|
|