NumPy: Create a 1-D array of 20 element spaced evenly on a log scale between 2. and 5., exclusive
20 Log-Spaced Values (2–5)
Write a NumPy program to create a 1-D array of 20 elements spaced evenly on a log scale between 2. and 5., exclusive.
Sample Solution:
Python Code:
# Importing the NumPy library with an alias 'np'
import numpy as np
# Generating an array of 20 values logarithmically spaced between 10^2 and 10^5 (excluding the endpoint)
x = np.logspace(2., 5., 20, endpoint=False)
# Printing the generated array
print(x)
Sample Output:
[ 100. 141.25375446 199.5262315 281.83829313
398.10717055 562.34132519 794.32823472 1122.0184543
1584.89319246 2238.72113857 3162.27766017 4466.83592151
6309.5734448 8912.50938134 12589.25411794 17782.79410039
25118.8643151 35481.33892336 50118.72336273 70794.57843841]
Explanation:
In the above code -
x = np.logspace(2., 5., 20, endpoint=False): This line creates a NumPy array ‘x’ using the np.logspace() function. The function takes four arguments: the start value (2.0), the stop value (5.0), the number of samples to generate (20), and whether to include the endpoint (False). It generates a sequence of 20 values that are evenly spaced on a logarithmic scale between 10^2 (100) and 10^5 (100000), excluding the endpoint.
For more Practice: Solve these Related Problems:
- Generate a 1D array of 20 logarithmically spaced values between 10^2 and 10^5 using np.logspace.
- Create a function that returns a log-spaced array and then computes the logarithm of each element to verify spacing.
- Validate that each value in the array is a power of 10 and that the sequence is strictly increasing.
- Compare the output of np.logspace with a manually computed logarithmic scale to ensure accuracy.
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