NumPy log2()

The numpy.log2() function computes the base-2 logarithm of each element in an input array.

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numpy.log2(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True)

Parameter	Type	Description
`x`	array_like	Input values for which base-2 logarithm is computed.
`out`	ndarray, None, or tuple of ndarray and None, optional	Optional output array where the result is stored. If None, a new array is created.
`where`	array_like, optional	Boolean mask specifying which elements to compute. Elements where `where=False` retain their original value.
`casting`	str, optional	Defines the casting behavior when computing the logarithm.
`order`	str, optional	Memory layout order of the output array.
`dtype`	data-type, optional	Defines the data type of the output array.
`subok`	bool, optional	Determines if subclasses of ndarray are preserved in the output.

Returns an array containing the base-2 logarithm of the input values. If the input is a scalar, a scalar is returned.

Examples

Here, we compute the base-2 logarithm of a single number.

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import numpy as np

# Define a number
num = 8

# Compute the base-2 logarithm
result = np.log2(num)

# Print the result
print("log2(8):", result)

log2(8): 3.0