The tanh()
function calculates the hyperbolic tangent of each element in an array.
Example
import numpy as np
# create an array of values
values = np.array([-2, -1, 0, 1, 2])
# calculate the hyperbolic tangent of each value
result = np.tanh(values)
print(result)
# Output:[-0.96402758 -0.76159416 0. 0.76159416 0.96402758]
tanh() Syntax
The syntax of tanh()
is:
numpy.tanh(x, out = None, where = True, dtype = None)
tanh() Arguments
The tanh()
method takes following arguments:
x
- an input arrayout
(optional) - the output array where the result will be storedwhere
(optional) - a boolean array or condition indicating where to compute the hyperbolic tangentdtype
(optional) - data type of the output array
tanh() Return Value
The tanh()
method returns an array with the corresponding hyperbolic tangent values of its elements.
Example 1: Use of out and where in tanh()
import numpy as np
values = np.array([-1, 0, 1, 2, 3])
# create an output array of the same shape and data type as 'values', filled with zeros
result = np.zeros_like(values, dtype=float)
# calculate the hyperbolic tangent where values>=0 and store in result
np.tanh(values, out=result, where=(values >= 0))
print(result)
Output
[0. 0. 0.76159416 0.96402758 0.99505475]
Here,
out=result
specifies that the output of thenp.tanh()
function should be stored in the result arraywhere=(values >= 0)
specifies that the hyperbolic operation should only be applied to elements in values that are greater than or equal to 0.
Example 2: Use of dtype Argument in tanh()
import numpy as np
# create an array of values
values = np.array([-0.5, -0.2, 0, 0.2, 0.5])
# calculate the hyperbolic tangent of each value with a specific dtype
tanh_values_float = np.tanh(values, dtype=float)
tanh_values_complex = np.tanh(values, dtype=complex)
print("Hyperbolic tangents with 'float' dtype:")
print(tanh_values_float)
print("\nHyperbolic tangents with 'complex' dtype:")
print(tanh_values_complex)
Output
Hyperbolic tangents with 'float' dtype: [-0.46211716 -0.19737532 0. 0.19737532 0.46211716] Hyperbolic tangents with 'complex' dtype: [-0.46211716+0.j -0.19737532+0.j 0. +0.j 0.19737532+0.j 0.46211716+0.j]
Here, by specifying the desired dtype
, we can specify the data type of the output array according to our requirements.
Note: To learn more about the dtype
argument, please visit NumPy Data Types.