NumPy: Test whether any array element along a given axis evaluates to True
Test Any Element is True
Write a NumPy program to test whether any array element along a given axis evaluates to True.
Note: 0 evaluates to False in python.
Pictorial Presentation:
Sample Solution:
Python Code:
# Importing the NumPy library with an alias 'np'
import numpy as np
# Checking if any elements along a specified axis evaluate to True or non-zero
print(np.any([[False,False],[False,False]])) # Evaluates to False because all elements in the array are False
print(np.any([[True,True],[True,True]])) # Evaluates to True because at least one element in the array is True
# Checking if any elements in an iterable evaluate to True or non-zero
print(np.any([10, 20, 0, -50])) # Evaluates to True because at least one element in the list is non-zero and evaluates to True
print(np.any([10, 20, -50])) # Evaluates to True because all elements in the list are non-zero and evaluate to True
Sample Output:
False True True True
Explanation:
In the above code –
print(np.any([[False,False],[False,False]])): np.any checks if any element of the input array is True. In this case, all elements are False, so the output is False.
print(np.any([[True,True],[True,True]])): np.any checks if any element of the input array is True. In this case, all elements are True, so the output is True.
print(np.any([10, 20, 0, -50])): np.any checks if any element of the input array is non-zero. In this case, there are non-zero elements in the array (10, 20, and -50), so the output is True.
print(np.any([10, 20, -50])): np.any checks if any element of the input array is non-zero. In this case, all elements are non-zero, so the output is True.
For more Practice: Solve these Related Problems:
- Utilize np.any to determine if at least one element in an array evaluates to True.
- Apply np.any along different axes of a multi-dimensional array to observe varying results.
- Create a custom implementation that mimics np.any using vectorized operations.
- Test arrays with mixed data types to ensure proper boolean conversion before applying np.any.
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