如何使用sympy定义条件函数? [英] How do I define a conditional function using sympy?

问题描述

我希望能够定义一个表达式，该表达式将在其定义的位置使用变量的所有值，并在未定义时将表达式的值为 0 . 与此类似:-

    import numpy as np
    import sympy as sp

    def expr(k1, k2):
        x, y =sp.symbols('x y')
        if x == k1 :
            fn = 0
        else:
            fn = np.divide(1,(x-k1)*(y-k2))
        return fn, x, y

    f,x, y = expr(1,2)
    print(f)
    fx = f.subs({x:1,y:4})
    print(fx)

那么一旦定义了函数，将如何检查相等性或条件性?

f pn = 1/(x-1)(y-2);如何将x = 1或y = 2设置为0?

解决方案

您应在函数内部定义一个函数，然后将其返回.像这样:

import numpy as np
import sympy as sp

def expr(k1, k2):
    x, y =sp.symbols('x y')
    def fn(x, y):
        if x==k1:
            return 0
        else:
            return np.divide(1, (x-k1)*(y-k2))
    return fn, x, y


f, x, y = expr(1, 2)
print(f(x, y))
print(f(1, 4))

这是注释中要求使用sp.lambdify的一种方法:

x_dot = 1 / ((x - 1) * (y - 2))
f = lambda a, b : 0 if a==1 or b==2 else sp.lambdify((x,y), xdot, "numpy")(a,b)

另一种选择是使用sp.subs

f = lambda a, b: 0 if a==1 or b==2 else float(x_dot.subs({x:a, y:b}))

I want to be able to define an expression which takes all the values of variable where it is defined and evaluates the expression as 0 when it is not defined. Similar to this: -

    import numpy as np
    import sympy as sp

    def expr(k1, k2):
        x, y =sp.symbols('x y')
        if x == k1 :
            fn = 0
        else:
            fn = np.divide(1,(x-k1)*(y-k2))
        return fn, x, y

    f,x, y = expr(1,2)
    print(f)
    fx = f.subs({x:1,y:4})
    print(fx)

So how is the equality or conditionality going to be checked once the function has been defined?

fn = 1/ (x-1)(y-2); How to set it as 0 for x=1 or y=2?

解决方案

You should define a function inside your function and then return it. Like this:

import numpy as np
import sympy as sp

def expr(k1, k2):
    x, y =sp.symbols('x y')
    def fn(x, y):
        if x==k1:
            return 0
        else:
            return np.divide(1, (x-k1)*(y-k2))
    return fn, x, y


f, x, y = expr(1, 2)
print(f(x, y))
print(f(1, 4))

EDIT:

Here is one way to use sp.lambdify as asked in the comments:

x_dot = 1 / ((x - 1) * (y - 2))
f = lambda a, b : 0 if a==1 or b==2 else sp.lambdify((x,y), xdot, "numpy")(a,b)

Another option is to use sp.subs

f = lambda a, b: 0 if a==1 or b==2 else float(x_dot.subs({x:a, y:b}))

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