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:
Python
import numpy as np
a = np.array([1+0j, 2+3j, 5, 4.5, 7j])
res = np.isreal(a)
print(res)
Output[ 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.
Python
import numpy as np
a = np.array([1, 2.5, 0, -3])
res = np.isreal(a)
print(res)
Output[ 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.
Python
import numpy as np
a = np.array([[1+0j, 3+4j], [5, 0-2j]])
res = np.isreal(a)
print(res)
Output[[ 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.
Python
import numpy as np
a = np.array([2+0j, 3+1j, 4, 5-2j])
res = a[np.isreal(a)]
print(res)
Explanation: We use the Boolean mask returned by np.isreal() to extract only the real values from the array. Complex numbers are excluded.
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