np.unravel_index() for multi-dim positions in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does np.unravel_index() do in NumPy?

It converts a flat (1D) index into a tuple of coordinate indices for a given shape of a multi-dimensional array.

beginner

How do you use np.unravel_index() to find the 2D position of the flat index 5 in a shape (3, 4)?

Use np.unravel_index(5, (3, 4)). It returns (1, 1), meaning row 1, column 1 in the 3x4 array.

intermediate

What is the output of np.unravel_index([3, 7], (3, 3))?

It returns two arrays: (array([1, 2]), array([0, 1])) which correspond to the row and column indices for flat indices 3 and 7 in a 3x3 array.

beginner

Why is np.unravel_index() useful in real life?

It helps find the position in multi-dimensional data when you only have a single flat index, like finding a seat in a theater when you know the seat number but not the row and column.

intermediate

What happens if you provide a flat index that is out of bounds for the given shape in np.unravel_index()?

NumPy raises an error because the flat index does not fit inside the array shape. The index must be less than the total number of elements.

What does np.unravel_index(8, (3, 3)) return?

A (2, 2)

B (1, 2)

C (0, 8)

D Error

The flat index 8 corresponds to row 2, column 2 in a 3x3 array.

If you have a flat index array [0, 4, 7] and shape (3, 3), what does np.unravel_index() return?

A ([0, 1, 2], [0, 2, 1])

B ([0, 1, 2], [0, 0, 1])

C Error

D ([0, 1, 2], [0, 1, 1])

Flat indices 0, 4, 7 correspond to positions (0,0), (1,1), and (2,1) respectively.

What is the required input for np.unravel_index()?

A Only array shape

B Multi-dimensional index and array shape

C Flat index and array shape

D Only flat index

You need a flat index (or indices) and the shape of the array to convert to multi-dimensional indices.

What happens if you pass a flat index equal to the total number of elements in the array to np.unravel_index()?

A Returns (0, 0, ...)

B Raises an error

C Returns last element's position

D Returns None

Flat indices must be less than the total number of elements; otherwise, an error is raised.

Which of these is a valid use case for np.unravel_index()?

A Finding multi-dimensional coordinates from a flat index

B Flattening a multi-dimensional array

C Sorting array elements

D Calculating mean of array

np.unravel_index() converts flat indices to multi-dimensional coordinates.

Explain how np.unravel_index() helps convert a flat index into multi-dimensional coordinates. Give a simple example.

Think about how a single number can point to a position in a grid.

Describe what happens if you provide an out-of-range flat index to np.unravel_index(). Why is this important?

Consider what happens if you try to find a seat number that doesn't exist.