Quick way to extend a set if we know elements are unique in python

Quick way to extend a set if we know elements are unique in python

In Python, extending a set with unique elements is a straightforward process. You can use the update() method or the union (|) operator to add elements to a set while ensuring uniqueness. Here's how you can do it:

Using the update() method:

my_set = {1, 2, 3} new_elements = {3, 4, 5} my_set.update(new_elements) print(my_set)

Using the union (|) operator:

my_set = {1, 2, 3} new_elements = {3, 4, 5} my_set |= new_elements print(my_set)

Both of these approaches will extend the my_set with the elements from new_elements, and any duplicates will automatically be removed since sets in Python do not allow duplicate values.

Examples

  1. "Upsample numpy array with nearest neighbor tiling"

    • Upsamples a numpy array using nearest neighbor tiling to increase its dimensions.
    import numpy as np arr = np.array([[1, 2], [3, 4]]) scale = (2, 2) upsampled_arr = np.tile(arr, scale) # Upsample by tiling

  2. "How to expand a numpy array by repeating elements"

    • Expands a numpy array by repeating its elements to achieve upsampling.
    import numpy as np arr = np.array([[5, 6], [7, 8]]) repeats = (2, 2) upsampled_arr = np.repeat(arr, repeats, axis=(0, 1)) # Upsample with repeat

  3. "Upsample numpy array by tiling"

    • Upsamples a numpy array by tiling to create a larger array.
    import numpy as np arr = np.array([1, 2, 3]) upsampled_arr = np.tile(arr, (3, 1)) # Upsample by tiling along one axis

  4. "Numpy repeat array elements for upsampling"

    • Repeats elements in a numpy array to upsample.
    import numpy as np arr = np.array([[9, 10], [11, 12]]) repeats = (2, 2) upsampled_arr = np.repeat(arr, repeats, axis=(0, 1)) # Repeat elements for upsampling

  5. "Nearest neighbor upsampling in numpy"

    • Upsamples a numpy array using the nearest neighbor method by tiling.
    import numpy as np arr = np.array([[13, 14], [15, 16]]) scale = (2, 2) upsampled_arr = np.tile(arr, scale) # Tiling for nearest neighbor upsampling

  6. "Tiling numpy array for quick upsampling"

    • Upsamples a numpy array by tiling to create a larger array.
    import numpy as np arr = np.array([[17, 18], [19, 20]]) scale = (2, 2) upsampled_arr = np.tile(arr, scale) # Quick tiling for upsampling

  7. "Repeat numpy array elements to upsample"

    • Uses the repeat method to upsample a numpy array by repeating elements.
    import numpy as np arr = np.array([[21, 22], [23, 24]]) repeats = (2, 2) upsampled_arr = np.repeat(arr, repeats, axis=(0, 1)) # Repeat elements for upsampling

  8. "Upsampling numpy array by repeating and tiling"

    • Upsamples a numpy array by repeating and tiling to increase its dimensions.
    import numpy as np arr = np.array([[25, 26], [27, 28]]) upsampled_arr = np.tile(arr, (2, 2)) # Upsample by tiling

  9. "Using numpy to upsample with nearest neighbor tiling"

    • Uses numpy to upsample a multidimensional array by nearest neighbor tiling.
    import numpy as np arr = np.array([[29, 30], [31, 32]]) scale = (2, 2) upsampled_arr = np.tile(arr, scale) # Upsample with nearest neighbor tiling

  10. "Expand numpy array using tiling for upsampling"

    • Upsamples a numpy array by expanding its size with tiling.
    import numpy as np arr = np.array([[33, 34], [35, 36]]) upsampled_arr = np.tile(arr, (2, 2)) # Expand by tiling for upsampling

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