The numpy.atanh() function is same as that of numpy.arctanh() function.
NumPy atanh()
The numpy.atanh() function computes the inverse hyperbolic tangent (atanh) of each element in an input array.
The input values must be in the range -1 < x < 1, as the function is undefined outside this range.
Syntax
numpy.atanh(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True)Parameters
| Parameter | Type | Description |
|---|---|---|
x | array_like | Input array containing values in the range (-1, 1). |
out | ndarray, None, or tuple of ndarray and None, optional | Optional output array where the result is stored. If None, a new array is created. |
where | array_like, optional | Boolean mask specifying which elements to compute. Elements where where=False retain their original value. |
casting | str, optional | Defines the casting behavior when computing the function. |
order | str, optional | Memory layout order of the output array. |
dtype | data-type, optional | Defines the data type of the output array. |
subok | bool, optional | Determines if subclasses of ndarray are preserved in the output. |
Return Value
Returns an array with the inverse hyperbolic tangent values of the input elements. If the input is a scalar, a scalar is returned.
Examples
1. Computing Inverse Hyperbolic Tangent of a Single Value
Here, we compute the inverse hyperbolic tangent of a single number within the valid range (-1, 1).
import numpy as np
# Define a value within the valid range (-1, 1)
value = 0.5
# Compute the inverse hyperbolic tangent
result = np.atanh(value)
# Print the result
print("atanh(0.5):", result)Output:
atanh(0.5): 0.5493061443340549
2. Computing Inverse Hyperbolic Tangent for an Array of Values
We compute the inverse hyperbolic tangent for multiple values in an array.
import numpy as np
# Define an array of values within the valid range (-1, 1)
values = np.array([-0.9, -0.5, 0, 0.5, 0.9])
# Compute the inverse hyperbolic tangent of each value
atanh_values = np.atanh(values)
# Print the results
print("Input values:", values)
print("Inverse hyperbolic tangent values:", atanh_values)Output:
Input values: [-0.9 -0.5 0. 0.5 0.9]
Inverse hyperbolic tangent values: [-1.47221949 -0.54930614 0. 0.54930614 1.47221949]
3. Using the out Parameter
Using an output array to store results instead of creating a new array.
import numpy as np
# Define an array of values within the valid range
values = np.array([-0.7, -0.3, 0.2, 0.6])
# Create an output array with the same shape
output_array = np.empty_like(values)
# Compute atanh and store the result in output_array
np.atanh(values, out=output_array)
# Print the results
print("Computed inverse hyperbolic tangent values:", output_array)Output:
Computed inverse hyperbolic tangent values: [-0.86730053 -0.3095196 0.20273255 0.69314718]
4. Using the where Parameter
Using a condition to compute atanh only for selected elements.
import numpy as np
# Define an array of values within the valid range
values = np.array([-0.8, -0.4, 0, 0.4, 0.8])
# Define a mask (compute atanh only where mask is True)
mask = np.array([True, False, True, False, True])
# Compute atanh values where mask is True
result = np.atanh(values, where=mask)
# Print the results
print("Computed inverse hyperbolic tangent values with mask:", result)Output:
Computed inverse hyperbolic tangent values with mask: [-1.09861229 0.5 0. 1.5 1.09861229]
The atanh values are computed only for elements where mask=True.