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# Return evenly spaced numbers on a log scale and set the number of samples to generate in Numpy

To return evenly spaced numbers on a log scale, use the **numpy.logspace()** method in Python Numpy. The 1st parameter is the "**start**" i.e. the start of the sequence. The 2nd parameter is the " **end**" i.e. the end of the sequence. The 3rd parameter is the num i.e. the number of samples to generate. Default is 50.

In linear space, the sequence starts at base ** start (base to the power of start) and ends with base ** stop (see endpoint below). The start is the base ** start is the starting value of the sequence. The stop is the base ** stop is the final value of the sequence, unless endpoint is False. In that case, num + 1 values are spaced over the interval in log-space, of which all but the last are returned. The base of the log space. The step size between the elements in ln(samples) / ln(base) (or log_base(samples)) is uniform. Default is 10.0.

The axis in the result to store the samples. Relevant only if start or stop are array-like. By default (0), the samples will be along a new axis inserted at the beginning. Use -1 to get an axis at the end.

## Steps

At first, import the required library −

import numpy as np

To return evenly spaced numbers on a log scale, use the numpy.logspace() method −

arr = np.logspace(100.0, 200.0, num = 10) print("Array...

", arr)

Get the array type −

print("

Type...

", arr.dtype)

Get the dimensions of the Array −

print("

Dimensions...

",arr.ndim)

Get the shape of the Array −

print("

Shape...

",arr.shape)

Get the number of elements −

print("

Number of elements...

",arr.size)

## Example

import numpy as np # To return evenly spaced numbers on a log scale, use the numpy.logspace() method in Python Numpy # The 1st parameter is the "start" i.e. the start of the sequence # The 2nd parameter is the "end" i.e. the end of the sequence # The 3rd parameter is the num i.e the number of samples to generate. Default is 50. arr = np.logspace(100.0, 200.0, num = 10) print("Array...

", arr) # Get the array type print("

Type...

", arr.dtype) # Get the dimensions of the Array print("

Dimensions...

",arr.ndim) # Get the shape of the Array print("

Shape...

",arr.shape) # Get the number of elements print("

Number of elements...

",arr.size)

## Output

Array... [1.00000000e+100 1.29154967e+111 1.66810054e+122 2.15443469e+133 2.78255940e+144 3.59381366e+155 4.64158883e+166 5.99484250e+177 7.74263683e+188 1.00000000e+200] Type... float64 Dimensions... 1 Shape... (10,) Number of elements... 10

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