Copies and views - use Technical Quotient

1. Apply

You are working with a 2D NumPy array arr = np.array([[one, two], [three, four]]) and need to flatten the array efficiently, ensuring that the operation returns a view wherever possible to save memory. Which of the following code snippets would be the most appropriate approach?

  arr = np.array([[1, 2], [3, 4]])\nslice_arr = arr[:, :].flatten()\nprint(slice_arr)

Incorrect; This method first slices the entire array, which could potentially return a view, but the subsequent .flatten() operation ensures the result is a copy. It illustrates an inefficient approach if the goal is to minimize memory usage by seeking a view.

  arr = np.array([[1, 2], [3, 4]])\nflat_arr = arr.ravel()\nprint(flat_arr)

Correct; arr.ravel() tries to return a view of arr in a flattened form, which is memory efficient.

  arr = np.array([[1, 2], [3, 4]])\nflat_arr = np.copy(arr).flatten()\nprint(flat_arr)

Incorrect; This option intentionally creates a copy before flattening, ensuring that modifications to flat_arr do not affect arr. It's less memory efficient and always results in a copy.

  arr = np.array([[1, 2], [3, 4]])\nflat_arr = arr.flatten()\nprint(flat_arr)

Incorrect; arr.flatten() always returns a copy, not a view, which is less memory efficient compared to ravel().

2. Understand

What is the primary difference between ndarray.flatten() and ndarray.ravel() when applied to a NumPy array?

ndarray.flatten() always returns a copy, while ndarray.ravel() returns a view where possible.

Correct; the main difference lies in memory usage, where ndarray.flatten() generates a new array, whereas ndarray.ravel() tries to return a view of the original array, making it more memory efficient.

ndarray.ravel() changes the shape of the original array without creating a copy.

Incorrect; ndarray.ravel() does not alter the shape of the original array but returns a flattened view if possible. This statement is incorrect as it implies that ravel() modifies the original array, which it does not; it either returns a view or a copy, depending on the array's memory layout.

ndarray.ravel() returns a contiguous flattened view if the array is already contiguous; otherwise, it returns a copy.

Incorrect; this option correctly describes ndarray.ravel()'s behavior in specific circumstances but contradicts the primary distinction by suggesting it might return a copy, which is a rare exception rather than the rule. The explanation is nuanced and technically accurate but may confuse the distinction between the two functions.

ndarray.flatten() modifies the original array in-place to flatten it.

Incorrect; ndarray.flatten() does not modify the original array but returns a flattened copy. This choice is incorrect because it suggests an in-place modification, which flatten() does not perform.

1. Apply

2. Understand

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