# 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