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# numpy.finfo

class `numpy.``finfo`

  Machine limits for floating point types.

  Parameters: | dtype : floating point type, dtype, or instance The kind of floating point data type to get information about.
  Attributes: | eps : floating point number of the appropriate type The smallest representable number such that `1.0 + eps != 1.0`. epsneg : floating point number of the appropriate type The smallest representable number such that `1.0 - epsneg != 1.0`. iexp : int The number of bits in the exponent portion of the floating point representation. machar : MachAr The object which calculated these parameters and holds more detailed information. machep : int The exponent that yields `eps`. max : floating point number of the appropriate type The largest representable number. maxexp : int The smallest positive power of the base (2) that causes overflow. min : floating point number of the appropriate type The smallest representable number, typically `-max`. minexp : int The most negative power of the base (2) consistent with there being no leading 0s in the mantissa. negep : int The exponent that yields `epsneg`. nexp : int The number of bits in the exponent including its sign and bias. nmant : int The number of bits in the mantissa. precision : int The approximate number of decimal digits to which this kind of float is precise. resolution : floating point number of the appropriate type The approximate decimal resolution of this type, i.e. `10**-precision`. tiny : floating point number of the appropriate type The smallest-magnitude usable number.

  See also

  `numpy.lib.machar.MachAr`
    The implementation of the tests that produce this information.
  `iinfo`
    The equivalent for integer data types.

  Notes

  For developers of numpy: do not instantiate this at the module level. The initial calculation of these parameters is expensive and negatively impacts import times. These objects are cached, so calling `finfo()` repeatedly inside your functions is not a problem.

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