Otherwise, a naive loop may perform as well or better than a vector.I need your help with programming. The size of the initial guesses, x0, is larger than O(100) elements.
Some or all of the extra arguments, args, are also arrays so that aĬlass of similar problems can be solved together. The initial guesses, x0, are all relatively the same distance from When newton is used with arrays, it is best suited for the following Is recommended for general use in one dimensional problems Interval where the function changes sign. Safer algorithms are brentq, brenth, ridder, and bisect,īut they all require that the root first be bracketed in an Consequently, the result should be verified. Here is the step size and there is no guarantee that a zero Is approximately the square (cube for Halley) of the errorĪfter the (n-1)th step. The actual error in the estimated zero after the nth iteration This means that if the function is well-behaved The Halley method is cubic, and the secant method is The convergence rate of the Newton-Raphson method is quadratic, Interface to root solvers for multi-input, multi-output functions Interface to root solvers for scalar functions root zero_der ndarray of bool, optionalįor vector functions, indicates which elements had a zero derivative. Present if full_output=True and x0 is non-scalar.įor vector functions, indicates which elements converged successfully. R.converged is True if the routine converged. Object containing information about the convergence. Present if full_output=True and x0 is scalar. Returns : root float, sequence, or ndarrayĮstimated location where function is zero. The `disp` keyword cannot be renamed for backwards compatibility. Note: this has little to do with displaying, however, Otherwise, the convergence status is recorded in a The error message containing the number of iterations and currentįunction value. If True, raise a RuntimeError if the algorithm didn’t converge, with If True and x0 is non-scalar, the return value is (x, converged, zero_der) (see Returns section for details). Is the root and r is a RootResults object. If True and x0 is scalar, the return value is (x, r), where x If full_output is False (default), the root is returned. If it is not None, then Halley’s methodĪnother estimate of the zero that should be somewhere near theĪctual zero. If it is None (default), then the normal Newton-Raphson The second order derivative of the function when available andĬonvenient. If func is complex-valued,Ī larger tol is recommended as both the real and imaginary parts args tuple, optionalĮxtra arguments to be used in the function call. Is None (default), then the secant method is used. The derivative of the function when available and convenient. If not scalar, then func must be vectorized and returnĪ sequence or array of the same shape as its first argument. x0 float, sequence, or ndarrayĪn initial estimate of the zero that should be somewhere near theĪctual zero. Single variable of the form f(x,a,b,c.), where a,b,c.Īre extra arguments that can be passed in the args parameter. For problems involving several variables, see root. Newton is for finding roots of a scalar-valued functions of a single (second) derivative of func with respect to its only variable evaluated Then its return must also have the same shape: each element is the first In this case, func must be vectorized to return a sequence or array of The zeros of the function from each (scalar) starting point in x0. If x0 is a sequence with more than one item, newton returns an array: If the second orderĭerivative fprime2 of func is also provided, then Halley’s method is Is provided, otherwise the secant method is used. The Newton-Raphson method is used if the derivative fprime of func newton ( func, x0, fprime = None, args = (), tol = 1.48e-08, maxiter = 50, fprime2 = None, x1 = None, rtol = 0.0, full_output = False, disp = True ) #įind a zero of a real or complex function using the Newton-Raphsonįind a zero of the scalar-valued function func given a nearby scalar
Statistical functions for masked arrays (
K-means clustering and vector quantization (
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