NumPy: Create a vector of size 10 with values ranging from 0 to 1, both excluded

Last update on April 26 2025 12:41:27 (UTC/GMT +8 hours)

Vector of Size 10 (0–1 Excluded)

Write a NumPy program to create a vector of size 10 with values ranging from 0 to 1, both excluded.

Pictorial Presentation:

Sample Solution:

Python Code:

# Importing the NumPy library and aliasing it as 'np'
import numpy as np

# Creating an array 'x' using NumPy's linspace function,
# generating 12 evenly spaced values between 0 and 1 (inclusive) with the 'endpoint' set to True,
# and selecting elements from index 1 to the second-to-last index using [1:-1]
x = np.linspace(0, 1, 12, endpoint=True)[1:-1]

# Printing the array 'x' that was created
print(x)

Sample Output:

[ 0.09090909  0.18181818  0.27272727  0.36363636  0.45454545  0.5454545
5                                                                      
  0.63636364  0.72727273  0.81818182  0.90909091]

Explanation:

In the above code –

x = np.linspace(0,1,12,endpoint=True): This line creates a 1D NumPy array with 12 evenly spaced values between 0 and 1 (both inclusive). The endpoint=True parameter ensures that the endpoint (1) is included in the array. The resulting array would look like this: [0., 0.09090909, 0.18181818, ..., 0.81818182, 0.90909091, 1.].

[1:-1]: This slice notation is applied to the array x to remove the first element (0.) and the last element (1.) of the array. The resulting array would look like this: [0.09090909, 0.18181818, ..., 0.81818182, 0.90909091].

print(x): This line prints the modified array after removing the first and the last elements: [0.09090909, 0.18181818, ..., 0.81818182, 0.90909091].

For more Practice: Solve these Related Problems:

• Write a NumPy program to create a vector of size 10 with values evenly spaced between 0 and 1, excluding the endpoints, using np.linspace.
• Implement a function that generates a vector with custom exclusion of boundary values and verifies its contents.
• Test the vector generation by ensuring that neither 0 nor 1 appears in the resulting array.
• Compare the outputs of np.linspace with and without endpoint exclusion to understand their differences.

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