SymPy `solve` 无法求解矩阵方程 A*x = b 当符号被替换为具有 `subs` 的值时

Question

我有一个线性方程要求解，如Ax = b。我只想在符号中逐步显示，最后插入数字并用数字显示问题的解决方案。我在插入数字时遇到问题。如果先前计算的值是整数，则一切正常。当我输入带有小数的东西时，它会打印出来

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这是说明我的问题的简化代码：

Force = 100 #If I try to put in value of lets say 100.23 the problem happens
x_t = 15
L = 20
A, x, b = sym.symbols('A, x, b')
A_x, A_y, B_y = sym.symbols('A_x, A_y, B_y')
b, F, xt, l = sym.symbols('b, F, xt, L')

A = sym.Matrix([[1, 0, 0],
            [0, 1, 0],
            [0, 0, 1]])
b = sym.Matrix([[0],
            [F],
            [F*xt/l]])
x = sym.Matrix([[A_x],
            [A_y + B_y],
            [B_y]])

linear_eq = sym.Eq(A * x, b)
solution = sym.solve(linear_eq, x) #This always works fine(only symbols)
solution = sym.solve(linear_eq.subs( {F: Force, xt: x_t, l: L }), x )
solution

Answer 1

嗯，我不知道为什么solve 根本不起作用。不过，您可以使用LUsolve。这也适用于F: 100.23：

from sympy import *

A, x, b = symbols("A, x, b")
A_x, A_y, B_y = symbols("A_x, A_y, B_y")
b, F, x_t, L = symbols("b, F, x_t, L")

A = Matrix([
    [1, 0, 0],
    [0, 1, 0],
    [0, 0, 1]
])
x = Matrix([
    [A_x],
    [A_y + B_y],
    [B_y]
])
b = Matrix([
    [0],
    [F],
    [F * x_t / L]
])

solution = A.LUsolve(b.subs({
    F: 100.23,
    x_t: 15,
    L:20
}))
print(solution)

哪些打印：

Matrix([[0], [100.230000000000], [75.1725000000000]])