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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