NumPy expm1() Function

---

---

The NumPy expm1() function is used to compute e^x 1 for each element x in an input array. It calculates the exponential of each element and subtracts 1.

This function can be applied to scalars, lists, or NumPy arrays and will return an array of the same shape with the result of the operation.

Syntax

Following is the syntax of the NumPy expm1() function −

numpy.expm1(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 applies the exponential operation to each element of the array or the 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 ^ 1, computed element-wise for each element in the input array x. If out is provided, it returns a reference to out.

Example: Basic Usage of expm1() Function

In the following example, we use the expm1() function to compute ^ 1 for each element in an array −

import numpy as np

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

# Applying expm1 to each element
result = np.expm1(arr)
print(result)

The output obtained will be −

[ 1.71828183  6.3890561  19.08553692]

Example: expm1() Function with Broadcasting

In this example, we demonstrate the use of broadcasting with the expm1() function. We create a 2-dimensional array and apply expm1 on it −

import numpy as np

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

# Applying expm1 to each element
result = np.expm1(arr)
print(result)

This will produce the following result −

[[1.71828183 6.3890561 ]
 [19.08553692 53.59815003]]

Example: expm1() Function on Negative Values

In this example, we apply the expm1() function to an array with negative values −

import numpy as np

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

# Applying expm1 to each element
result = np.expm1(arr)
print(result)

The output obtained is:

[-0.63212056 -0.86466472 -0.95021293]

Example: expm1() Function with Scalar Input

In this example, we apply expm1() function to a scalar value −

import numpy as np

# Scalar value
scalar = 1

# Applying expm1 to the scalar
result = np.expm1(scalar)
print(result)

The output obtained is:

1.718281828459045