Return the base 10 logarithm of the input array element-wise in Numpy

NumpyServer Side ProgrammingProgramming

To return the base 10 logarithm of the input array, element-wise, use the numpy.log10() method in Python Numpy. For real-valued input data types, log10 always returns real output. For each value that cannot be expressed as a real number or infinity, it yields nan and sets the invalid floating point error flag.

Returns the logarithm to the base 10 of x, element-wise. NaNs are returned where x is negative. This is a scalar if x is a scalar.

The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

Steps

At first, import the required library −

import numpy as np

Create an array using the array() method −

arr = np.array([1e-15, 10000])

Display the array −

print("Array...\n", arr)

Get the type of the array −

print("\nOur Array type...\n", arr.dtype)

Get the dimensions of the Array −

print("\nOur Array Dimension...\n",arr.ndim)

Get the shape of the Array −

print("\nOur Array Shape...\n",arr.shape)

To return the base 10 logarithm of the input array, element-wise, use the numpy.log10() method. For real-valued input data types, log10 always returns real output. For each value that cannot be expressed as a real number or infinity, it yields nan and sets the invalid floating point error flag −

print("\nResult...\n",np.log10(arr))

Example

import numpy as np

# Create an array using the array() method
arr = np.array([1e-15, 10000])

# Display the array
print("Array...\n", arr)

# Get the type of the array
print("\nOur Array type...\n", arr.dtype)

# Get the dimensions of the Array
print("\nOur Array Dimension...\n",arr.ndim)

# Get the shape of the Array
print("\nOur Array Shape...\n",arr.shape)

# To return the base 10 logarithm of the input array, element-wise, use the numpy.logaddexp() method in Python Numpy
# For real-valued input data types, log10 always returns real output.
# For each value that cannot be expressed as a real number or infinity,
# it yields nan and sets the invalid floating point error flag.
print("\nResult...\n",np.log10(arr))

Output

Array...
[1.e-15 1.e+04]

Our Array type...
float64

Our Array Dimension...
1

Our Array Shape...
(2,)

Result...
[-15. 4.]
raja
Updated on 08-Feb-2022 10:03:06

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