numpy.MachAr

class numpy.MachAr(float_conv=<type 'float'>, int_conv=<type 'int'>, float_to_float=<type 'float'>, float_to_str=<function <lambda> at 0x126bdc80>, title='Python floating point number')

Diagnosing machine parameters.

Attributes:

ibeta : int

Radix in which numbers are represented.

it : int

Number of base-ibeta digits in the floating point mantissa M.

machep : int

Exponent of the smallest (most negative) power of ibeta that, added to 1.0, gives something different from 1.0

eps : float

Floating-point number beta**machep (floating point precision)

negep : int

Exponent of the smallest power of ibeta that, substracted from 1.0, gives something different from 1.0.

epsneg : float

Floating-point number beta**negep.

iexp : int

Number of bits in the exponent (including its sign and bias).

minexp : int

Smallest (most negative) power of ibeta consistent with there being no leading zeros in the mantissa.

xmin : float

Floating point number beta**minexp (the smallest [in magnitude] usable floating value).

maxexp : int

Smallest (positive) power of ibeta that causes overflow.

xmax : float

(1-epsneg) * beta**maxexp (the largest [in magnitude] usable floating value).

irnd : int

In range(6), information on what kind of rounding is done in addition, and on how underflow is handled.

ngrd : int

Number of ‘guard digits’ used when truncating the product of two mantissas to fit the representation.

epsilon : float

Same as eps.

tiny : float

Same as xmin.

huge : float

Same as xmax.

precision : float

- int(-log10(eps))

resolution : float

`` - 10**(-precision)``

References

[1]	Press, Teukolsky, Vetterling and Flannery, “Numerical Recipes in C++,” 2nd ed, Cambridge University Press, 2002, p. 31.