.log()

In NumPy, the .log() method is used to calculate the natural logarithm (base-e) of each element in an array. It is widely used in scientific computations, data analysis, and mathematical applications where logarithmic scaling is essential.

Syntax

numpy.log(array, out=None, where=True)

• array: An array-like structure containing the elements for which the natural logarithm will be applied.
• out (Optional): An array where the resulting logarithms are stored. If not provided, a new array is created to hold the results.
• where (Optional): An array of boolean values that determines which elements undergo logarithm computation:
  • For elements where the condition is True, the natural logarithm is calculated.
  • For elements where the condition is False, the original element remains unchanged.
  • If where is not specified, the natural logarithm is computed for all elements in the input.

Example

The below example demonstrates the use of the .log() method:

import numpy as np

arr = np.array([1, np.e, 10, 100])
result = np.log(arr)

print(result)

The code above will generate the following output:

[0.         1.         2.30258509 4.60517019]

Codebyte Example

In this codebyte example, the .log() method only computes the natural logarithm of positive elements in the array:

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