riptable.Utils.common

Logic / helper functions used throughout the riptable benchmark suite.

Classes

cached_weakref_property

Functions

integer_range(dtype[, include_invalid])	Given an integer dtype, return the range [lo, hi] of values representable
integer_valid_range(dtype)	Given an integer dtype, return the range [lo, hi] of valid values
rand_floats(gen[, low, high, size, dtype, include_invalid])	Generate a random array of floating-point values with the specified length and dtype.
rand_integers(gen[, size, dtype, include_invalid])	Generate a random array of integers with the specified length and dtype.
trial_size([low, high, scale_factor])	Generates a list of input sizes to benchmark against.
zeros_eager(shape, dtype)

Attributes

_DOUBLING_TRIAL_16
_DOUBLING_TRIAL_32
_DOUBLING_TRIAL_MAX
_INT_16_MAX
_INT_32_MAX
_INT_MAX
_SEED	Value used to seed random number generators so we get "random" data for
_dtypes_by_group
cached_property
dtypes_by_group	np.typecodes but the value for each entry is a list containing the

class riptable.Utils.common.cached_weakref_property(func)

_NO_OBJECT

_WEAKREF_CACHE_NAME = '_weakref_cache'

__get__(instance, owner=None)

__set_name__(owner, name)

riptable.Utils.common.integer_range(dtype, include_invalid=False)

Given an integer dtype, return the range [lo, hi] of values representable by the type, optionally excluding the invalid value (if any) for the type.

riptable.Utils.common.integer_valid_range(dtype)

Given an integer dtype, return the range [lo, hi] of valid values representable by that dtype.

Parameters:

dtype (data-type) – An integer dtype.

riptable.Utils.common.rand_floats(gen, low=0.0, high=1.0, size=None, dtype=np.float64, include_invalid=False)

Generate a random array of floating-point values with the specified length and dtype.

The elements of the array are drawn from the uniform distribution over the range [low, high).

riptable.Utils.common.rand_integers(gen, size=None, dtype=np.int64, include_invalid=False)

Generate a random array of integers with the specified length and dtype.

The elements of the array will span the representable range of the dtype, optionally including the ‘invalid’ value for the type. The elements of the array are drawn from the ‘discrete uniform’ distribution.

riptable.Utils.common.trial_size(low=250, high=_INT_16_MAX, scale_factor=2)

Generates a list of input sizes to benchmark against.

riptable.Utils.common.zeros_eager(shape, dtype)

riptable.Utils.common._DOUBLING_TRIAL_16

riptable.Utils.common._DOUBLING_TRIAL_32

riptable.Utils.common._DOUBLING_TRIAL_MAX

riptable.Utils.common._INT_16_MAX

riptable.Utils.common._INT_32_MAX

riptable.Utils.common._INT_MAX

riptable.Utils.common._SEED = 1234

Value used to seed random number generators so we get “random” data for the benchmarks while also allowing the benchmarks to be repeatable.

riptable.Utils.common._dtypes_by_group

riptable.Utils.common.cached_property

riptable.Utils.common.dtypes_by_group: Mapping[str, List[numpy.dtype]]

np.typecodes but the value for each entry is a list containing the dtypes corresponding to the typecode(s) for the original entry.

See also

riptable.rt_enum.NumpyCharTypes