NumPy reciprocal() Function

---

---

The NumPy reciprocal() function is used to compute the reciprocal (1/x) of each element in an input array. It calculates 1/x for each element x in the array.

This function can be applied to scalars, lists, or NumPy arrays and will return an array of the same shape with the reciprocal of each input value.

Syntax

Following is the syntax of the NumPy reciprocal() function −

numpy.reciprocal(x, /, out=None, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])

Parameters

This function accepts the following parameters −

• x: The input array or scalar. The function computes the reciprocal of each element of the array or scalar.
• out (optional): A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned.
• where (optional): This condition is broadcast over the input. At locations where the condition is True, the result will be computed. Otherwise, the result will retain its original value.
• casting (optional): Controls what kind of data casting may occur. Defaults to 'same_kind'.
• order (optional): Controls the memory layout order of the result. 'C' means C-order, 'F' means Fortran-order, 'A' means 'F' if inputs are all F, 'C' otherwise, 'K' means match the layout of the inputs as closely as possible.
• dtype (optional): The type of the returned array and of the accumulator in which the elements are processed. The dtype of x is used by default unless dtype is specified.
• subok (optional): If True, then sub-classes will be passed-through, otherwise the returned array will be forced to be a base-class array.

Return Value

This function returns an array where each element is the reciprocal (1/) of the corresponding element in the input array x. If out is provided, it returns a reference to out.

Example: Basic Usage of reciprocal() Function

In the following example, we use the reciprocal() function to compute the reciprocal of each element in a 1-dimensional array −

import numpy as np

# Creating a 1-dimensional array
arr = np.array([1, 2, 3, 4])

# Applying reciprocal to each element
result = np.reciprocal(arr)
print(result)

The output obtained will be −

[1 0 0 0]

Example: reciprocal() Function with Broadcasting

In this example, we demonstrate the use of broadcasting with the reciprocal() function. We create a 2-dimensional array and apply reciprocal on it −

import numpy as np

# Creating a 2-dimensional array
arr = np.array([[1, 2, 3], [4, 5, 6]])

# Applying reciprocal to each element
result = np.reciprocal(arr)
print(result)

This will produce the following result −

[[1 0 0]
 [0 0 0]]

Example: reciprocal() with Scalar

In this example, we apply the reciprocal() function to a scalar value −

import numpy as np

# Scalar value
scalar = 4

# Applying reciprocal to the scalar
result = np.reciprocal(scalar)
print(result)

The output obtained is −

0

Example: reciprocal() Function with Zero

In this example, we apply the reciprocal() function to an array with zero. Since the reciprocal of zero is undefined, a warning will be raised −

import numpy as np

# Creating a 1-dimensional array with zero
arr = np.array([1, 0, 3])

# Applying reciprocal to each element
result = np.reciprocal(arr)
print(result)

This will produce the following warning −

/home/cg/root/673acdd6238d1/main.py:7: RuntimeWarning: divide by zero encountered in reciprocal
  result = np.reciprocal(arr)
/home/cg/root/673acdd6238d1/main.py:7: RuntimeWarning: invalid value encountered in reciprocal
  result = np.reciprocal(arr)
[                   1 -9223372036854775808                    0]