我正在尝试实现rk4函数来求解2个微分方程。我有这个实现Runge Kutta 4方法的代码:
//RK4 method
func rk4_func(y_array: [Double], f_array: [(([Double], Double) -> Double)], t_val: Double, h_val: Double) -> [Double] {
let length = y_array.count
let t_half_step = t_val + h_val / 2.0
let t_step = t_val + h_val
var k1 = [Double](repeating: 0.0, count: length)
var k2 = [Double](repeating: 0.0, count: length)
var k3 = [Double](repeating: 0.0, count: length)
var k4 = [Double](repeating: 0.0, count: length)
var w = [Double](repeating: 0.0, count: length)
var result = [Double](repeating: 0.0, count: length)
for i in 0...length {
k1[i] = h_val * f_array[i](y_array, t_val)
w[i] = y_array[i] + k1[i]/2.0
}
for i in 0...length {
k2[i] = h_val * f_array[i](w, t_half_step)
w[i] = y_array[i] + k2[i]/2.0
}
for i in 0...length {
k3[i] = h_val * f_array[i](w, t_half_step)
w[i] = y_array[i] + k3[i]
}
for i in 0...length {
k4[i] = h_val * f_array[i](w, t_step)
}
for i in 0...length {
result[i] = y_array[i] + (k1[i] + 2.0*k2[i] + 2.0*k3[i] + k4[i])/6.0
}
print(result)
return result;
}
但现在我需要实际 使用 ,这是我感到困惑的部分。如果有人有数值计算微分方程解的经验,那将有所帮助。
答案 0 :(得分:0)
y
是当前状态的向量(实现为double数组)。 f_array
是指向函数doty = f_array(y,t)
的函数指针。
t_val
是当前状态的时间,h_val
是时间步长。
rk4_func
的一次通话执行从t_val
到t_val+h_val
和
返回新状态y_next = rk4_func(y, f_array, t, h)
。
人们必须学习语言内部。希望,也就是说,为了使代码正常工作,f_array[0](y_array, t_val)
的第一次调用计算完整的向量/数组值结果,并进一步调用只提取缓存结果的组件。
在https://github.com/pdemarest/swift-rk4找到的原始代码严重缺乏其RK4实现和语言标准的过时。在https://swift.sandbox.bluemix.net/测试的工作版本是
import Foundation
func RK4step(y: [Double], f: ([Double], Double) -> [Double], t: Double, h: Double) -> [Double] {
let length = y.count
var w = [Double](repeating: 0.0, count: length )
var result = [Double](repeating: 0.0, count: length)
let k1 = f(y,t)
assert(k1.count == y.count, "States and Derivatives must be the same length")
for i in 0..<length { w[i] = y[i] + 0.5*h*k1[i] }
let k2 = f(w, t+0.5*h)
for i in 0..<length { w[i] = y[i] + 0.5*h*k2[i] }
let k3 = f(w,t+0.5*h)
for i in 0..<length { w[i] = y[i] + h*k3[i]
}
let k4 = f(w,t+h)
for i in 0..<length {
result[i] = y[i] + (k1[i] + 2.0*k2[i] + 2.0*k3[i] + k4[i])*h/6.0
}
return result;
}
func test_exp(){
// Integrate: y' = y
// y_0 = 1.0
// from 0 to 2.0
var y = [1.0]
func deriv (y: [Double], t: Double) -> [Double] {
return [ y[0] ]
}
var t = 0.0
let h = 0.1
while t < 2.0 {
y = RK4step(y:y, f:deriv, t:t, h:h)
t += h
print("t: \(t), y: \(y[0]) exact: \(exp(t))\n")
}
let exact = exp(2.0)
let error = abs(y[0] - exact)
assert(error < pow(h, 4.0))
print("y: \(y[0]) exact: \(exact) error: \(error)\n")
}
print("testing...\n")
test_exp()
对于Volterra-Lotka动力学,人们必须改变
var y = [150.0, 5.0]
let a = 5.0
let b = 1.0
let eps = 0.1
let m = 5.0
func deriv (y: [Double], t: Double) -> [Double] {
let p = y[0]
let q = y[1]
return [ a*p-b*p*q, eps*b*p*q - m*q ]
}
具有正确修复的全局常量a,b,eps,m
和二维初始值。在需要时添加打印语句。