sympy lambdify RuntimeWarning:double_scalars中遇到无效值

时间:2012-09-03 21:27:25

标签: python numpy sympy

我正在使用sympy和numpy来解决以下问题:

给定点(x0,y0)和曲线y = a * x ** 2 + b * x + c,计算(x0,y0)到(x,y)的最小距离。

from sympy.core.symbol import symbols
from sympy.solvers.solvers import solve
from sympy.utilities.lambdify import lambdify

x, y = symbols('x y')    
a,b,c, x0, y0 = symbols('a b c x0 y0')
y = a*x**2 + b*x + c
dist2 = (x-x0)**2 + (y-y0)**2
sol = solve(dist2.diff(x), x)
dist2_diff_solve = lambdify( (x0,y0,a,b,c), solve(dist2.diff(x),x), modules='numpy')

到现在为止,一切都很好。我甚至可以得到一些结果:

dist2_diff_solve(1, 1, 1, 1, 1)

[0.31718264650678707, (-0.9085913232533936-0.8665105933073626j),    
(-0.9085913232533936+0.8665105933073626j)]

然而,对于另一组参数,我遇到了问题:

dist2_diff_solve(664515.9375, 3998106.0, 0.053674994761459802, -71340.561832823907,    23709057427.266102)

*** ValueError: negative number cannot be raised to a fractional power

我认为这是来自lambdify的错误,因为我可以执行以下操作:

sol[0].evalf(subs={x0:664515.9375, y0:3998106.0, a:0.053674994761459802, b:-71340.561832823907, c:23709057427.266102})
664515.759983973 + .0e-19*I

我需要lambdify,因为我需要一次计算大量(~100K)的计算(矢量化)。任何人都可以确认这是lambdify的错误吗?欢迎提出任何意见/建议。

1 个答案:

答案 0 :(得分:3)

我找到了一个相关的问题:negative pow in python

并简单地通过将+ 0j添加到a来解决了这个问题,即:

dist2_diff_solve(664515.9375+0j, 3998106.0, 0.053674994761459802, -71340.561832823907, 23709057427.266102)

[(664515.7418921513+3.552713678800501e-15j), (664600.9266076663+5.329070518200751e-15j), (664564.8069210749-1.4210854715202004e-14j)]