matrices.py

import numpy as np

def get_random_array(n: int) -> np.ndarray:
    return np.random.randn(n, n) + 1j * np.random.randn(n, n)

class RandomMatrixBuilder:
    @staticmethod
    def build(n: int) -> np.ndarray:
        return get_random_array(n)
    
class DiagonalMatrixBuilder:
    @staticmethod
    def build(n: int, diag_values: np.ndarray | None = None) -> np.ndarray:
        if diag_values is None:
            diag_values = np.random.randn(n) + 1j * np.random.randn(n)
        return np.diag(diag_values)
    
class UnitaryMatrixBuilder:
    @staticmethod
    def build(n: int) -> np.ndarray:
        # Generate a random complex matrix and perform QR decomposition
        z = get_random_array(n)
        q, r = np.linalg.qr(z)
        # Ensure the diagonal of R has positive real parts to get a unitary matrix
        d = np.diag(r)
        ph = d / np.abs(d)
        return q * ph