NumPy: Compute the natural logarithm of one plus each element of a given array in floating-point accuracy
Write a NumPy program to compute the natural logarithm of one plus each element of a given array in floating-point accuracy.
Sample Solution:
Python Code:
# Importing the NumPy library
import numpy as np
# Creating an array with two very small numbers
x = np.array([1e-99, 1e-100])
# Displaying the original array
print("Original array: ")
print(x)
# Calculating natural logarithm of one plus each element in the array
print("\nNatural logarithm of one plus each element:")
print(np.log1p(x))
Sample Output:
Original array: [1.e-099 1.e-100] Natural logarithm of one plus each element: [1.e-099 1.e-100]
Explanation:
In the above exercise –
x = np.array([1e-99, 1e-100]): This line creates a NumPy array x with two very small values - 1e-99 and 1e-100.
np.log1p(x): This line calculates the natural logarithm of 1 + x for each element of the x array. Since the values in the x array are very small, the values of 1 + x will be very close to 1, and the natural logarithm of 1 + x will be very close to x. Therefore, the output of np.log1p(x) will be very close to the values of x itself.
Python-Numpy Code Editor: