# brainpy.math.finfo#

class brainpy.math.finfo(dtype)[source]#

Machine limits for floating point types.

bits#

The number of bits occupied by the type.

Type:

int

eps#

The difference between 1.0 and the next smallest representable float larger than 1.0. For example, for 64-bit binary floats in the IEEE-754 standard, `eps = 2**-52`, approximately 2.22e-16.

Type:

float

epsneg#

The difference between 1.0 and the next smallest representable float less than 1.0. For example, for 64-bit binary floats in the IEEE-754 standard, `epsneg = 2**-53`, approximately 1.11e-16.

Type:

float

iexp#

The number of bits in the exponent portion of the floating point representation.

Type:

int

machar#

The object which calculated these parameters and holds more detailed information.

Type:

MachAr

machep#

The exponent that yields eps.

Type:

int

max#

The largest representable number.

Type:

floating point number of the appropriate type

maxexp#

The smallest positive power of the base (2) that causes overflow.

Type:

int

min#

The smallest representable number, typically `-max`.

Type:

floating point number of the appropriate type

minexp#

The most negative power of the base (2) consistent with there being no leading 0’s in the mantissa.

Type:

int

negep#

The exponent that yields epsneg.

Type:

int

nexp#

The number of bits in the exponent including its sign and bias.

Type:

int

nmant#

The number of bits in the mantissa.

Type:

int

precision#

The approximate number of decimal digits to which this kind of float is precise.

Type:

int

resolution#

The approximate decimal resolution of this type, i.e., `10**-precision`.

Type:

floating point number of the appropriate type

tiny#

The smallest positive floating point number with full precision (see Notes).

Type:

float

Parameters:

dtype (float, dtype, or instance) – Kind of floating point data-type about which to get information.

`MachAr`

The implementation of the tests that produce this information.

`iinfo`

The equivalent for integer data types.

`spacing`

The distance between a value and the nearest adjacent number

`nextafter`

The next floating point value after x1 towards x2

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.

Note that `tiny` is not actually the smallest positive representable value in a NumPy floating point type. As in the IEEE-754 standard , NumPy floating point types make use of subnormal numbers to fill the gap between 0 and `tiny`. However, subnormal numbers may have significantly reduced precision .

References

__init__()#

Methods