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Creating equally spaced arrays with precision using Python NumPy’s np.linspace

   September 12, 2023

np.linspace is a NumPy function used to create an array of evenly spaced values within a specified range, with a defined number of elements. It is a powerful tool for generating sequences of numbers with a specific precision and is widely used in scientific and numerical computing in Python.

Usage and purpose:

The primary purpose of np.linspace is to create NumPy arrays that represent sequences of evenly spaced values. It is used in various scenarios, including:

  1. Data Visualization: Generating evenly spaced values for plotting graphs and charts, such as creating a range of x-axis values.
  2. Simulation and Experimentation: Creating synthetic data for experimentation, simulations, and testing with controlled spacing.
  3. Numerical Analysis: In numerical analysis, np.linspace can be used for tasks like numerical integration or solving differential equations where equally spaced points are required.

Advantages of np.linspace :

  1. Precision: np.linspace allows you to specify the number of elements you want in the array, ensuring precise control over the generated sequence.
  2. Ease of Use: The function is straightforward to use, requiring you to specify the start and stop values, along with the number of elements.
  3. Seamless Integration: Arrays created using np.linspace can be seamlessly integrated with other NumPy functions and libraries for further data manipulation and analysis.

Disadvantages of np.linspace :

  1. Fixed number of elements: np.linspace generates an array with a fixed number of elements, which may not be suitable when you need dynamic spacing between values.

Example

Let’s create an example that uses np.linspace to generate a sequence of evenly spaced values representing website views over a 24-hour period.

import numpy as np
# Example for Freshers.in Python NumPy Training 
# Create a sequence of hourly website views for a day
start_time = 0  # Midnight
end_time = 24   # Midnight of the next day
num_hours = 24  # Number of hours in a day
views_per_hour = np.linspace(start_time, end_time, num_hours, endpoint=True)
print(views_per_hour)
print('\n')
views_per_hour = np.linspace(start_time, end_time, num_hours, endpoint=False)
print(views_per_hour)

Output

[ 0.          1.04347826  2.08695652  3.13043478  4.17391304  5.2173913
  6.26086957  7.30434783  8.34782609  9.39130435 10.43478261 11.47826087
 12.52173913 13.56521739 14.60869565 15.65217391 16.69565217 17.73913043
 18.7826087  19.82608696 20.86956522 21.91304348 22.95652174 24.        ]

[ 0.  1.  2.  3.  4.  5.  6.  7.  8.  9. 10. 11. 12. 13. 14. 15. 16. 17.
 18. 19. 20. 21. 22. 23.]

NumPy linspace @ Freshers.in

We import NumPy as np.
We use np.linspace to generate a sequence of values starting from start_time (midnight) to end_time (midnight of the next day) with num_hours elements. The endpoint=False parameter ensures that the endpoint (24) is not included in the sequence.
The output will display the sequence of hourly website views for a day, providing equally spaced values that can be used for various applications.

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