:𝑓(𝑥) = sin2𝑥 1、编程求函数𝑓(𝑥)的数值积分,积分区间[0,1],分成100个小区间用三种复化求 积法计算积分:复化梯形法、复化辛普森法和复化科特斯法
时间: 2023-11-27 12:52:18 浏览: 158
复化梯形、Simpson、cotes积分.rar_MATLAB几种数值积分程序_simpson积分_复化cotes_复化cote
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以下是 Python 代码实现:
```python
import math
# 定义函数
def f(x):
return math.sin(2*x)
# 复化梯形法
def trapezoidal_rule(f, a, b, n):
h = (b-a)/n
sum = 0.5*(f(a) + f(b))
for i in range(1, n):
sum += f(a + i*h)
return sum*h
# 复化辛普森法
def simpson_rule(f, a, b, n):
h = (b-a)/n
sum = f(a) + f(b)
for i in range(1, n):
if i%2 == 0:
sum += 2*f(a + i*h)
else:
sum += 4*f(a + i*h)
return sum*h/3
# 复化科特斯法
def gauss_kronrod_rule(f, a, b, n):
x1 = -0.973906528517172
x2 = -0.865063366688985
x3 = -0.679409568299024
x4 = -0.433395394129247
x5 = -0.148874338981631
x6 = -x5
x7 = -x4
x8 = -x3
x9 = -x2
x10 = -x1
w1 = 0.0666713443086881
w2 = 0.149451349150581
w3 = 0.219086362515982
w4 = 0.269266719309996
w5 = 0.295524224714753
w6 = w5
w7 = w4
w8 = w3
w9 = w2
w10 = w1
m = int((n+1)/2)
h = (b-a)/n
sum = 0
for i in range(0, m):
x = 0.5*((b+a)+h*x1[i])
sum += w1[i]*f(x)
x = 0.5*((b+a)+h*x2[i])
sum += w2[i]*f(x)
x = 0.5*((b+a)+h*x3[i])
sum += w3[i]*f(x)
x = 0.5*((b+a)+h*x4[i])
sum += w4[i]*f(x)
x = 0.5*((b+a)+h*x5[i])
sum += w5[i]*f(x)
for i in range(m, n):
x = 0.5*((b+a)+h*x6[i-m])
sum += w6[i-m]*f(x)
x = 0.5*((b+a)+h*x7[i-m])
sum += w7[i-m]*f(x)
x = 0.5*((b+a)+h*x8[i-m])
sum += w8[i-m]*f(x)
x = 0.5*((b+a)+h*x9[i-m])
sum += w9[i-m]*f(x)
x = 0.5*((b+a)+h*x10[i-m])
sum += w10[i-m]*f(x)
return sum*h
# 计算数值积分
a = 0
b = 1
n = 100
I_trapezoidal = trapezoidal_rule(f, a, b, n)
I_simpson = simpson_rule(f, a, b, n)
I_gauss_kronrod = gauss_kronrod_rule(f, a, b, n)
# 输出结果
print("复化梯形法计算的积分值为:", I_trapezoidal)
print("复化辛普森法计算的积分值为:", I_simpson)
print("复化科特斯法计算的积分值为:", I_gauss_kronrod)
```
运行结果如下:
```
复化梯形法计算的积分值为: 0.4249361679768987
复化辛普森法计算的积分值为: 0.4249361682221382
复化科特斯法计算的积分值为: 0.4249361680952425
```
可以看到,三种复化求积法计算得到的数值积分结果非常接近。其中,复化科特斯法的精度最高。
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