hypot

hypot(x1: array, x2: array, /) → array

Computes the square root of the sum of squares for each element x1_i of the input array x1 with the respective element x2_i of the input array x2.

Note

The value computed by this function may be interpreted as the length of the hypotenuse of a right-angled triangle with sides of length x1_i and x2_i, the distance of a point (x1_i, x2_i) from the origin (0, 0), or the magnitude of a complex number x1_i + x2_i * 1j.

Parameters:

  • x1 (array) – first input array. Should have a real-valued floating-point data type.

  • x2 (array) – second input array. Must be compatible with x1 (see Broadcasting). Should have a real-valued floating-point data type.

Returns:

out (array) – an array containing the element-wise results. The returned array must have a real-valued floating-point data type determined by Type Promotion Rules.

Notes

The purpose of this function is to avoid underflow and overflow during intermediate stages of computation. Accordingly, conforming implementations should not use naive implementations.

Special Cases

For real-valued floating-point operands,

  • If x1_i is +infinity or -infinity and x2_i is any value, including NaN, the result is +infinity.

  • If x2_i is +infinity or -infinity and x1_i is any value, including NaN, the result is +infinity.

  • If x1_i is either +0 or -0, the result is equivalent to abs(x2_i).

  • If x2_i is either +0 or -0, the result is equivalent to abs(x1_i).

  • If x1_i is a finite number or NaN and x2_i is NaN, the result is NaN.

  • If x2_i is a finite number or NaN and x1_i is NaN, the result is NaN.

  • Underflow may only occur when both arguments are subnormal and the correct result is also subnormal.

For real-valued floating-point operands, hypot(x1, x2) must equal hypot(x2, x1), hypot(x1, -x2), hypot(-x1, x2), and hypot(-x1, -x2).

Note

IEEE 754-2019 requires support for subnormal (a.k.a., denormal) numbers, which are useful for supporting gradual underflow. However, hardware support for subnormal numbers is not universal, and many platforms (e.g., accelerators) and compilers support toggling denormals-are-zero (DAZ) and/or flush-to-zero (FTZ) behavior to increase performance and to guard against timing attacks.

Accordingly, conforming implementations may vary in their support for subnormal numbers.

New in version 2023.12.