Danlwd Grindeq Math Utilities Review

matrix = [[4, 7], [2, 6]] inv_matrix, cond_num = linalg.inv_with_condition(matrix) print(f"Inverse: inv_matrix, Condition number: cond_num")

Getting started with Danlwd Grindeq Math Utilities depends on your ecosystem. Currently, the library supports C++ (native), Python bindings (via PyBind11), and Rust. danlwd grindeq math utilities

def mean(data: List[float]) -> float: """Arithmetic mean.""" return sum(data) / len(data) if data else 0.0 matrix = [[4, 7], [2, 6]] inv_matrix, cond_num = linalg

def variance(data: List[float], sample: bool = True) -> float: """Variance (sample=True for Bessel's correction).""" if len(data) < 2: return 0.0 mu = mean(data) ss = sum((x - mu) ** 2 for x in data) return ss / (len(data) - 1 if sample else len(data)) coeffs: [a0, a1, a2,

def stdev(data: List[float], sample: bool = True) -> float: """Standard deviation.""" return math.sqrt(variance(data, sample))

def poly_eval(coeffs: List[float], x: float) -> float: """ Evaluate polynomial at x. coeffs: [a0, a1, a2, ...] for a0 + a1x + a2x^2 + ... """ result = 0.0 for power, c in enumerate(coeffs): result += c * (x ** power) return result