Source code for arkouda.scipy.special._math

from typing import Union
from warnings import warn

import numpy as np

from arkouda.numeric import log
from arkouda.pdarrayclass import pdarray

[docs] def xlogy(x: Union[pdarray, np.float64], y: pdarray): """ Computes x * log(y). Parameters ---------- x : pdarray or np.float64 x must have a datatype that is castable to float64 y : pdarray Returns ------- arkouda.pdarrayclass.pdarray Examples -------- >>> import arkouda as ak >>> ak.connect() >>> from arkouda.scipy.special import xlogy >>> xlogy( ak.array([1, 2, 3, 4]), ak.array([5,6,7,8])) array([1.6094379124341003 3.5835189384561099 5.8377304471659395 8.317766166719343]) >>> xlogy( 5.0, ak.array([1, 2, 3, 4])) array([0.00000000000000000 3.4657359027997265 5.4930614433405491 6.9314718055994531]) """ if not isinstance(x, (np.float64, pdarray)) and np.can_cast(x, np.float64): x = np.float64(x) if isinstance(x, pdarray) and isinstance(y, pdarray): if x.size == y.size: return x * log(y) else: msg = "x and y must have the same size." warn(msg, UserWarning) return None elif isinstance(x, np.float64) and isinstance(y, pdarray): return x * log(y) else: msg = "x and y must both be pdarrays or x must be castable to float64 and y must be a pdarray." warn(msg, UserWarning) return None