Question

我有一个给定的功能

def unnorm(x, alpha, beta):
    return (1 + alpha * x + beta * x ** 2)

然后我将其集成以查找范围内的规范化常量，并将其转换为lambda函数，该函数采用与unnorm相同的参数。现在，为了创建一个合适的对象，我将这些函数组合在一起：

def normalized(x, alpha, beta):
    return unnorm(x, alpha, beta) * norm(x, alpha, beta)

哪一个很好，但仍有重复，并从全局命名空间中提取名称。

如何以更干净的方式组合这两个功能，而无需重新编写参数？ E.g

def normalized(func, normalizer):
    return func * normalizer

完整代码：

import sympy
import numpy as np
import inspect

def normalize_function(f, xmin, xmax):
    """
    Normalizes function to PDF in the given range
    """
    # Get function arguments
    fx_args = inspect.getfullargspec(f).args
    # Convert to symbolic notation
    symbolic_args = sympy.symbols(fx_args)
    # Find definite integral
    fx_definite_integral = sympy.integrate(f(*symbolic_args), (symbolic_args[0], xmin, xmax))
    # Convert to a normalization multiplication term, as a real function
    N = sympy.lambdify(expr = 1 / fx_definite_integral, args = symbolic_args)
    return N

def unnorm(x, alpha, beta):
    return (1 + alpha * x + beta * x ** 2)

norm = normalize_function(unnorm, -1, 1)

# How do I condense this to a generic expression?
def normalized(x, alpha, beta):
    return unnorm(x, alpha, beta) * norm(x, alpha, beta)

x = np.random.random(100)

print(normalized(x, alpha = 0.5, beta = 0.5))

Answer 1

我认为你现在正在做的事情没有任何问题。但出于审美目的，这里有几个具有一些最小功能的替代方案。

def doubler(x, y, z):
    return 2*(x + y + z)

def halver(x, y, z):
    return 0.5*(x + y + z)

def doubler_halver_sumprod(*args):
    return doubler(*args) * halver(*args)

dhs = lambda *args: doubler(*args) * halver(*args)

doubler_halver_sumprod(1, 2, 3)  # 36
dhs(1, 2, 3)                     # 36

如果你想要一个真正可扩展的功能方法，一次提取参数，这可能有效：

from operator import mul, methodcaller
from functools import reduce

def prod(iterable):
    return reduce(mul, iterable, 1)

def doubler(x, y, z):
    return 2*(x + y + z)

def halver(x, y, z):
    return 0.5*(x + y + z)

def dhs2(*args):
    return prod(map(methodcaller('__call__', *args), (doubler, halver)))

def dhs3(*args):
    return prod(f(*args) for f in (doubler, halver))

dhs2(1, 2, 3)  # 36
dhs3(1, 2, 3)  # 36

Answer 2

好吧，一种方法是为函数实现*等等的装饰器：

class composable:
    def __init__(self, func):
        self.func = func

    def __call__(self, *args, **kwargs):
        return self.func(*args, **kwargs)

    def __mul__(self, other):
        if callable(other):
            def wrapper(*args, **kwargs):
                return self(*args, **kwargs) * other(*args, **kwargs)
            return self.__class__(wrapper)
        return NotImplemented

@composable
def f(x):
    return 2 * x

@composable
def g(x):
    return x + 1

h = f * g # (2*x) * (x+1)
print(h(2))
# 12

您需要为__add__，__sub__，__div__添加类似的定义，并且可能需要为反向方法__rmul__添加等等。

如何组合两个采用相同参数的函数？

2 个答案: