In this article, we will discuss how to return real parts if the input is complex with all imaginary parts close to zero in Python.
The numpy np.real_if_close() method is used to return the real parts if the input is a complex number with all imaginary parts close to zero. “Close to zero” is defined as tol * (machine epsilon of the type for a).
syntax: numpy.real_if_close(a, tol=100)
parameters:
- a: array like object. input array.
- tot: Machine epsilons tolerance for the complex component of the array’s elements.
returns:
out: The type of an is utilized for the output if an is true. The returning type is float if has complex elements.
Example 1:
In this example, the NumPy package is imported. An array is created using numpy.array() method which contains complex numbers where the imaginary parts are near 0 and np.real_if_close() returns the real parts. The shape, datatype, and dimensions of the array can be found by .shape, .dtype, and .ndim attributes.
Python3
import numpy as np # Creating an array array = np.array([1,2+3.e-18j,-3+4.e-14j]) print(array) # shape of the array is print("Shape of the array is : ",array.shape) # dimension of the array print("The dimension of the array is : ",array.ndim) # Datatype of the array print("Datatype of our Array is : ",array.dtype) # returning real part print(np.real_if_close(array, tol= 1000)) |
Output:
[ 1.+0.e+00j 2.+3.e-18j -3.+4.e-14j] Shape of the array is : (3,) The dimension of the array is : 1 Datatype of our Array is : complex128 [ 1. 2. -3.]
Example 2:
In this case, imaginary numbers are not close to zero so the same array is returned back.
Python3
import numpy as np # Creating an array array = np.array([1+5j,3-6j]) print(array) # shape of the array is print("Shape of the array is : ",array.shape) # dimension of the array print("The dimension of the array is : ",array.ndim) # Datatype of the array print("Datatype of our Array is : ",array.dtype) # returning real part print(np.real_if_close(array, tol= 1000)) |
Output:
[1.+5.j 3.-6.j] Shape of the array is : (2,) The dimension of the array is : 1 Datatype of our Array is : complex128 [1.+5.j 3.-6.j]
