python - 识别和修复浮点除以零错误 (Python)

Question

我有一段代码，打算在脚本中使用，通过将误差拟合到多项式来使用梯形规则查找数值积分中的误差。这段代码引发了浮点除以零错误，我不明白为什么或如何修复它。

有人可以帮我找到答案吗？

def trap(f,a,b,dx,exact):
    N = int(numpy.round(float(b-a)/dx))
    w=(b-a)/N
    sum = f(a)/2.0 + f(b)/2.0
    for i in range(1,N):
        sum += f(a+i*w)
    area = sum * w
    errorf = exact-area
    # If the error crosses 0, a polynomial approximation
    # to the absolute value will go crazy.
    return errorf

此替代方法会引发相同的错误

# alternate way to handle dx not a divisor of b-a
def alt_trap(f,a,b,dx,exact):
    N = int(numpy.floor(float(b-a)/dx))
    sum = f(a)/2.0 + f(a+N*dx)/2.0
    for i in range(1,N):
        sum+= f(a+i*dx)
    area = sum*dx
    # now add one trapezoid between a+Ndx and b
    area += 1/2*(b-(a+N*dx))*(f(b)+f(a+N*dx))
    errorf = exact-area
    return errorf

Answer 1

dx 是唯一可能为 0 并抛出 ZeroDivisionError 的参数。您可以捕获异常并决定做什么或修复输入 - 取决于您的逻辑。

为了提供默认值，只需添加:

dx = dx or 0.0000001 # 0 is false and python is awesome to support this syntax

如果你想 try catch 异常(最好请求原谅而不是许可)

import sys # At the top
...
try:
    N = int(numpy.floor(float(b-a)/dx))
except ZeroDivisionError, e:
    print a, b, dx 
    N = sys.maxint