numpy.float_power(arr1, arr2, out = None, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None) :
Array element from first array is raised to the power of element from second element(all happens element-wise). Both arr1 and arr2 must have same shape.
float_power differs from the power function in that integers, float16, and float32 are promoted to floats with a minimum precision of float64 such that result is always inexact. This function will return a usable result for negative powers and seldom overflow for +ve powers.
arr1 : [array_like]Input array or object which works as base. arr2 : [array_like]Input array or object which works as exponent. out : [ndarray, optional]Output array with same dimensions as Input array, placed with result. **kwargs : Allows you to pass keyword variable length of argument to a function. It is used when we want to handle named argument in a function. where : [array_like, optional]True value means to calculate the universal functions(ufunc) at that position, False value means to leave the value in the output alone.
An array with elements of arr1 raised to exponents in arr2
Code 1 : arr1 raised to arr2
arr1 : [2, 2, 2, 2, 2] arr1 : [2, 3, 4, 5, 6] Output array : [ 4. 8. 16. 32. 64.]
Code 2 : elements of arr1 raised to exponent 2
arr1 : [0 1 2 3 4 5 6 7] Output array : [ 0. 1. 4. 9. 16. 25. 36. 49.]
Code 3 : float_power handling results if arr2 has -ve elements
arr1 : [2, 2, 2, 2, 2] arr2 : [2, -3, 4, -5, 6] Output array : [ 4.00000000e+00 1.25000000e-01 1.60000000e+01 3.12500000e-02 6.40000000e+01]
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