classnumpy.finfo(dtype)
Machine limits for floating point types.
Parameters:dtypefloat, dtype, or instanceKind of floating point or complex floating point data-type about which to get information.
Attributes:bitsintThe number of bits occupied by the type.
dtypedtypeReturns the dtype for which
returns information. For complex input, the returned dtype is the associated float* dtype for its real and complex components.
epsfloatThe 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.
epsnegfloatThe 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.
iexpintThe number of bits in the exponent portion of the floating point representation.
machepintThe exponent that yields eps.
maxfloating point number of the appropriate typeThe largest representable number.
maxexpintThe smallest positive power of the base (2) that causes overflow. Corresponds to the C standard MAX_EXP.
minfloating point number of the appropriate typeThe smallest representable number, typically -max.
minexpintThe most negative power of the base (2) consistent with there being no leading 0’s in the mantissa. Corresponds to the C standard MIN_EXP - 1.
negepintThe exponent that yields
.
nexpintThe number of bits in the exponent including its sign and bias.
nmantintThe number of explicit bits in the mantissa (excluding the implicit leading bit for normalized numbers).
precisionintThe approximate number of decimal digits to which this kind of float is precise.
resolutionfloating point number of the appropriate typeThe approximate decimal resolution of this type, i.e., 10**-precision.
tinyfloatAn alias for smallest_normal, kept for backwards compatibility.
smallest_normalfloatThe smallest positive floating point number with 1 as leading bit in the mantissa following IEEE-754 (see Notes).
smallest_subnormalfloatThe smallest positive floating point number with 0 as leading bit in the mantissa following IEEE-754.
See also
The equivalent for integer data types.
The distance between a value and the nearest adjacent number
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 smallest_normal 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 smallest_normal. However, subnormal numbers may have significantly reduced precision
.
For longdouble, the representation varies across platforms. On most platforms it is IEEE 754 binary128 (quad precision) or binary64-extended (80-bit extended precision). On PowerPC systems, it may use the IBM double-double format (a pair of float64 values), which has special characteristics for precision and range.
This function can also be used for complex data types as well. If used, the output will be the same as the corresponding real float type (e.g. numpy.finfo(numpy.csingle) is the same as numpy.finfo(numpy.single)). However, the output is true for the real and imaginary components.
References
Examples
>>> importnumpyasnp>>> np.finfo(np.float64).dtypedtype('float64')>>> np.finfo(np.complex64).dtypedtype('float32')