Make Diagonal Matrix

Name: TensorTonic
Author: TensorTonic

Linear Algebra

Easy

Given a vector $\mathbf{v}\in\mathbb{R}^{N}$ , construct an $N\times N$ matrix whose main diagonal contains $\mathbf{v}$ and whose remaining entries are zero:

D_{ij}=\begin{cases}v_i,&i=j\\0,&i\ne j\end{cases}

Here, $i$ and $j$ are row and column indices. Construct the matrix without np.diag and return it as a NumPy array.

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Examples

Input: v = [3, 5]

Output: [[3, 0], [0, 5]]

Explanation: The two vector values occupy positions (0, 0) and (1, 1).

Input: v = [1.5]

Output: [[1.5]]

Input: v = [0, 0, 2]

Output: [[0, 0, 0], [0, 0, 0], [0, 0, 2]]

Hint 1

Initialize the output with np.zeros((values.size, values.size), dtype=values.dtype).

Hint 2

Assign with matrix[np.arange(values.size), np.arange(values.size)] = values.

Requirements

Create a square zero matrix with the same dtype as the input vector
Place each vector element at the matching row and column index
Do not use np.diag
Return a NumPy array of shape (N, N)

Constraints

v is a nonempty one-dimensional numeric list
Use NumPy only

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