numpy.isreal() tests element-wise whether each value in the input array is a real number (i.e., not complex). It returns a Boolean result as a boolean array. Example:

import numpy as np
a = np.array([1+0j, 2+3j, 5, 4.5, 7j])
res = np.isreal(a)
print(res)

[ True False  True  True False]

Explanation: np.isreal() returns True for real numbers (even if written with +0j) and False for complex numbers with a non-zero imaginary part like 2+3j or 7j.

Syntax

numpy.isreal(x)]

Parameters: x is the input array or scalar (can be complex).

Returns: A Boolean array of the same shape as x.

• Returns True for elements that are real.
• Returns False for elements that have a non-zero imaginary part.

Examples

Example 1: In this example, we use np.isreal() with a purely real-valued array.

import numpy as np
a = np.array([1, 2.5, 0, -3])
res = np.isreal(a)
print(res)

[ True  True  True  True]

Explanation: All elements in the array are real numbers, so np.isreal() returns True for each one.

Example 2: In this example, we use a 2D array with both real and complex values to check element-wise real status.

import numpy as np
a = np.array([[1+0j, 3+4j], [5, 0-2j]])
res = np.isreal(a)
print(res)

[[ True False]
 [ True False]]

Explanation:

• 1+0j and 5 are real, so they return True.
• 3+4j and 0-2j have imaginary parts, so they return False.

Example 3: In this example, we filter out only real values from an array that includes complex numbers.

import numpy as np
a = np.array([2+0j, 3+1j, 4, 5-2j])
res = a[np.isreal(a)]
print(res)

[2.+0.j 4.+0.j]

Explanation: We use the Boolean mask returned by np.isreal() to extract only the real values from the array. Complex numbers are excluded.