修改龙格库塔bug
This commit is contained in:
2
279-3.py
2
279-3.py
@@ -7,7 +7,7 @@ def ClassicRK(x0,y0,h,xk,fxy):
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k2 = fxy(x0+h/2,y0+h*k1/2)
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k3 = fxy(x0+h/2,y0+h*k2/2)
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k4 = fxy(x0+h,y0+h*k3)
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y0 += h*(k1+4*k2+k3)/6
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y0 += h*(k1+2*k2+2*k3+k4)/6
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x0 += h
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result.append((x0,y0))
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return result
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29
按方法整理/常微分方程-经典龙格-库塔格式.py
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29
按方法整理/常微分方程-经典龙格-库塔格式.py
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@@ -0,0 +1,29 @@
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import math
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#经典R-K，龙格-库塔法
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def ClassicRK(x0,y0,h,xk,fxy):
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k1=k2=k3=k4=0
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result = [(x0,y0)]
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while x0<=xk:
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k1 = fxy(x0,y0)
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k2 = fxy(x0+h/2,y0+h*k1/2)
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k3 = fxy(x0+h/2,y0+h*k2/2)
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k4 = fxy(x0+h,y0+h*k3)
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y0 += h*(k1+2*k2+2*k3+k4)/6
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x0 += h
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result.append((x0,y0))
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return result
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if __name__=="__main__":
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##########################################################################
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x0 = 0 # x的初始值（左边界）换成题干里面的#################
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y0 = -1 # y的初始值换成题干里面的#################
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fxy = lambda x,y: x + y #f(x,y)换成题干里面的#################
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real_fx = lambda x: -x-1 #真实函数换成题干里面的#################
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h = 0.1 #步长换成题干里面的#################
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xk = 2 #x的右边界换成题干里面的#################
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result = ClassicRK(x0, y0, h, xk, fxy)
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print("x\ty\t\treal_y\t\t\t误差")
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for x, y in result:
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print(f"{x:.2f}\t{y:.10f}\t\t{real_fx(x):.10f}\t\t\t{abs(y - real_fx(x)):.5f}")
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62
按方法整理/矩阵-SOR逐次超松弛迭代法.py
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62
按方法整理/矩阵-SOR逐次超松弛迭代法.py
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@@ -0,0 +1,62 @@
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import math
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#模 范数
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def Norm(x,v):
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if len(x[0]) == 1:
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if v == 1:
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return sum([abs(i[0]) for i in x])
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elif v == 2:
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return (sum([i[0]**2 for i in x]))**0.5
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elif v == float("inf"):
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return max([abs(i[0]) for i in x])
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else:
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if v == 1:
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return max([sum([abs(x[i][j]) for i in range(len(x))]) for j in range(len(x[0]))])
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elif v == float("inf"):
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return max([sum([abs(i) for i in x[j]]) for j in range(len(x))])
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return None
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#SOR方法 逐次超松弛迭代
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def SOR(A,b,x,w,err,N):
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count = 0
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n = len(A)
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while True:
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count += 1
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for i in range(n):
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sum1 = sum(A[i][j] * x[j] for j in range(i))
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sum2 = sum(A[i][j] * x[j] for j in range(i, n))
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x[i] += w*(b[i] - sum1 - sum2) / A[i][i]
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r = [[b[i] - sum(A[i][j] * x[j] for j in range(len(A[0])))] for i in range(n)]
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err_now = Norm(r, float("inf"))
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x_t = [round(i,5) for i in x]
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print(f"第{count}次迭代, 误差 = {err_now:.5}, x = {x_t}")
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if err_now < err:
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return x, count, 1
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if count > N:
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return None,count, 0
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if __name__ == "__main__":
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##########################################################################
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#把矩阵改成题干的矩阵，b改成题干结果，err精度要求修改##########################
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A = [
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[4,-1,0,-1,0,0],
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[-1,4,-1,0,-1,0],
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[0,-1,4,0,0,-1],
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[-1,0,0,4,-1,0],
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[0,-1,0,-1,4,-1],
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[0,0,-1,0,-1,4]
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]
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b = [2,3,2,2,1,2]
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x = [0,0, 0, 0, 0, 0] # 初始解
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err = 1e-5 # 精度要求
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w = 1 # 松弛因子,题干要求 P201
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x1,k,sta = SOR(A, b, x, w, err, 100)
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print(f"w = {w}, 解为: {x1}, 迭代次数: {k}, 状态: {'收敛' if sta == 1 else '未收敛'}")
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w = 1.1
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x = [0, 0, 0, 0, 0, 0]
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x2,k,sta = SOR(A, b, x, w, err, 100)
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print(f"w = {w}, 解为: {x2}, 迭代次数: {k}, 状态: {'收敛' if sta == 1 else '未收敛'}")
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94
按方法整理/矩阵-特征值-谱半径.py
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94
按方法整理/矩阵-特征值-谱半径.py
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@@ -0,0 +1,94 @@
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import math
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#抛物线法解方程
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def MullerSolve(fx,x0,x1,x2,err1,err2,N):
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count = 0
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f0 = fx(x0)
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f1 = fx(x1)
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f2 = fx(x2)
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q = (x2 - x1) / (x1 - x0)
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p = 0
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a = 0
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b = 0
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c = 0
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while True:
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p = (x2 - x0) / (x1 - x0)
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a = q**2 * f0 - q*p*f1 + q*f2
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b = q**2 *f0 - p**2 *f1 + (p + q)*f2
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c = p*f2
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h1 = 0
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if b.real < 0:
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h1 = -2 * c / (b - (b**2 - 4*a*c)**0.5)
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else:
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h1 = -2 * c / (b + (b**2 - 4*a*c)**0.5)
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x3 = x2 + h1 * (x2 - x1)
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f3 = fx(x3)
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k = err1 + 1
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if abs(f3) < 1:
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k = abs(x3 - x2)
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else:
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k = abs(x3 - x2) / abs(f3)
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if abs(f3) < err2 or k < err1:
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return x3, 1
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count += 1
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if count > N:
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return None, 0
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x0 = x1
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x1 = x2
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x2 = x3
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f0 = f1
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f1 = f2
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f2 = f3
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q = h1
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#计算矩阵的行列式
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def Det(A):
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if len(A) == 2:
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return A[0][0] * A[1][1] - A[0][1] * A[1][0]
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det = 0
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for c in range(len(A)):
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sub_matrix = [row[:c] + row[c+1:] for row in A[1:]]
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det += ((-1) ** c) * A[0][c] * Det(sub_matrix)
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return det
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if __name__ == "__main__":
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##########################################################################
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#把矩阵换成题干的矩阵，通常建议自己再验算一遍，这个能不能算不一定#########################
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A =[
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[1,0,1],
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[2,2,1],
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[-1,0,0]
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]
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lam = []
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count = 0
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k = -100
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fx = lambda x: Det([[A[i][j] - x * (1 if i == j else 0) for j in range(len(A))] for i in range(len(A))])
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k = 10
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while len(lam) < len(A):
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for i in range(-k,k):
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re,sta = MullerSolve(fx, i, i + 1, i + 2, 1e-10, 1e-10, 100)
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if sta == 1:
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a = round(re.real, 9)
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b = round(re.imag, 9)
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re_t = complex(a, b)
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if re_t not in lam:
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if re_t.imag != 0:
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lam.append(re_t)
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lam.append(re_t.conjugate())
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else:
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lam.append(a)
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if len(lam) == len(A):
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break
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k *= 10
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p = abs(lam[0])
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for i in range(len(lam)):
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print(f"λ{i+1} = {lam[i]}")
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if abs(lam[i]) > p:
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p = abs(lam[i])
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print(f"谱半径 = {p:.3f}")
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102
按方法整理/矩阵-迭代改善法.py
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102
按方法整理/矩阵-迭代改善法.py
Normal file
@@ -0,0 +1,102 @@
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import math
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#列主元高斯消元法
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def SovleRowMain(A,b,round_num=15):
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ks = 0.00000001
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n = len(A)
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if len(A[0]) != n:
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print("A要为方阵")
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return None, None, None, None
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if len(b) != n:
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print("b与A的行数不匹配")
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return None, None, None, None
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p = list(range(n))
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for i in range(n):
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row_max = abs(A[i][i])
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row_max_index = i
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for j in range(i + 1, n):
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if abs(A[j][i]) > row_max:
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row_max = abs(A[j][i])
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row_max_index = j
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A[i], A[row_max_index] = A[row_max_index], A[i]
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b[i], b[row_max_index] = b[row_max_index], b[i]
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p[i], p[row_max_index] = p[row_max_index], p[i]
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if abs(A[i][i]) < ks:
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print("A矩阵奇异，无法进行高斯消元")
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return None, None, None, None
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for j in range(i + 1, n):
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m = round(A[j][i] / A[i][i],round_num)
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A[j][i] = m
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for k in range(i + 1, n):
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A[j][k] -= round(m * A[i][k],round_num)
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b[j] -= round(m * b[i],round_num)
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if abs(A[n - 1][n - 1]) < ks:
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print("A矩阵奇异，无法进行高斯消元")
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return None, None, None, None
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# 回代求解
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b[n - 1] = round(b[n - 1]/A[n - 1][n - 1],round_num)
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for i in range(n - 2, -1, -1):
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for j in range(i + 1, n):
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b[i] -= round(A[i][j] * b[j],round_num)
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b[i] /= round(A[i][i])
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b = [round(b[i], round_num) for i in range(n)]
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# 得到L,U和P矩阵
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L = [[0 for i in range(n)] for j in range(n)]
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U = [[0 for i in range(n)] for j in range(n)]
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P = [[0 for i in range(n)] for j in range(n)]
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for i in range(n):
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for j in range(n):
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if i == j:
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L[i][j] = 1
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U[i][j] = A[i][j]
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elif i < j:
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U[i][j] = A[i][j]
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else:
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L[i][j] = A[i][j]
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P[i][p[i]] = 1
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return P,L,U,b
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#迭代改善法
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def IterativeMethod(A, b, err, N, fake_round_num=15):
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b_c = [b[i] for i in range(len(b))]
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A_c = [[A[i][j] for j in range(len(A[0]))] for i in range(len(A))]
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P,L,U,x0 = SovleRowMain(A_c, b_c,fake_round_num)
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print(L)
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print(U)
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print(f"初始解为: {x0}")
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count = 0
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while count<N:
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r1 = [b[i] - sum([A[i][j] * x0[j] for j in range(len(A[0]))]) for i in range(len(A))]
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A_c = [[A[i][j] for j in range(len(A[0]))] for i in range(len(A))]
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d1 = SovleRowMain(A_c, r1,fake_round_num)[3]
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x0 = [x0[i] + d1[i] for i in range(len(x0))]
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print(f"第{count+1}次迭代, r{count+1} = {r1}, d{count+1} = {d1}, x{count+2} = {x0}")
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err_now = max(abs(r1[i]) for i in range(len(r1)))
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count += 1
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if err_now < err:
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break
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return x0,count
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if __name__ == "__main__":
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##########################################################################
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#把矩阵改成题干的矩阵，b改成题干结果，err精度要求修改##########################
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A = [
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[51,82],
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[151/3,81]
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]
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b = [235,232]
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err = 1e-4 # 精度要求
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N = 1000 # 迭代次数上限
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fake_round_num = 4 # 模拟的四舍五入精度，根据题目情况或者凑过程修改
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x = IterativeMethod(A, b, err, N, fake_round_num)[0]
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print(f"解为: {x}")
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# 先求范数与逆矩阵（条件数）
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69
按方法整理/矩阵-逆矩阵-条件数.py
Normal file
69
按方法整理/矩阵-逆矩阵-条件数.py
Normal file
@@ -0,0 +1,69 @@
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import math
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#模 范数
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def Norm(x,v):
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if len(x[0]) == 1:
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if v == 1:
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return sum([abs(i[0]) for i in x])
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elif v == 2:
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return (sum([i[0]**2 for i in x]))**0.5
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elif v == float("inf"):
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return max([abs(i[0]) for i in x])
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else:
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if v == 1:
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return max([sum([abs(x[i][j]) for i in range(len(x))]) for j in range(len(x[0]))])
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elif v == float("inf"):
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return max([sum([abs(i) for i in x[j]]) for j in range(len(x))])
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return None
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# 计算矩阵的行列式
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def Det(A):
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if len(A) == 2:
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return A[0][0] * A[1][1] - A[0][1] * A[1][0]
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det = 0
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for c in range(len(A)):
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sub_matrix = [row[:c] + row[c+1:] for row in A[1:]]
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det += ((-1) ** c) * A[0][c] * Det(sub_matrix)
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return det
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# 计算矩阵的逆矩阵
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def Inverse(A):
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n = len(A)
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# 计算代数余子式矩阵
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B = [[0 for i in range(n)] for j in range(n)]
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for i in range(n):
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for j in range(n):
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minor = [row[:j] + row[j+1:] for row in (A[:i] + A[i+1:])]
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B[j][i] = ((-1) ** (i + j)) * sum(minor[k][l] * (-1) ** (k + l) for k in range(n - 1) for l in range(n - 1))
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det = Det(A)
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print("det(A):",det)
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if det == 0:
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print("矩阵不可逆")
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return None
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A_inv = [[B[i][j] / det for j in range(n)] for i in range(n)]
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return A_inv
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# 计算矩阵的条件数
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def Cond(A,v):
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inv_A = Inverse(A)
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print(f"inv_A: {inv_A}, Norm(A, v): {Norm(A, v)}, Norm(inv_A, v): {Norm(inv_A, v)}")
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# print(inv_A,Norm(A, v), Norm(inv_A, v))
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return Norm(A, v) * Norm(inv_A, v)
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if __name__ == "__main__":
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##########################################################################
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# 把矩阵换成题干的矩阵 #########################
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A = [
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[1,2],
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[1.001,2.001]
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]
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# 把范数的种类数换成题干的要求，inf是无穷范数 #########################
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print(f"矩阵A的条件数为: {Cond(A, float('inf')):.5f}") # 1 1范数；2 2范数；float('inf') 无穷范数
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# 把矩阵换成题干的矩阵 #########################
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A = [
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[1,2],
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[3,4]
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]
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# 把范数的种类数换成题干的要求，inf是无穷范数 ########################
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print(f"矩阵A的条件数为: {Cond(A, float('inf')):.5f}") # 1 1范数；2 2范数；float('inf') 无穷范数
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