我遇到了一个scipy函数，无论传递给它什么，它似乎都返回一个numpy数组。在我的应用程序中，我只需要能够传递标量和列表，因此唯一的“问题”是当我将标量传递给函数时，将返回带有一个元素的数组（当我期望标量时）。我应该忽略这种行为，还是修改函数以确保在传递标量时返回标量？

示例代码：

#! /usr/bin/env python

import scipy
import scipy.optimize
from numpy import cos

# This a some function we want to compute the inverse of
def f(x):
    y = x + 2*cos(x)
    return y

# Given y, this returns x such that f(x)=y
def f_inverse(y):

    # This will be zero if f(x)=y
    def minimize_this(x):
        return y-f(x)

    # A guess for the solution is required
    x_guess = y
    x_optimized = scipy.optimize.fsolve(minimize_this, x_guess) # THE PROBLEM COMES FROM HERE
    return x_optimized

# If I call f_inverse with a list, a numpy array is returned
print f_inverse([1.0, 2.0, 3.0])
print type( f_inverse([1.0, 2.0, 3.0]) )

# If I call f_inverse with a tuple, a numpy array is returned
print f_inverse((1.0, 2.0, 3.0))
print type( f_inverse((1.0, 2.0, 3.0)) )

# If I call f_inverse with a scalar, a numpy array is returned
print f_inverse(1.0)
print type( f_inverse(1.0) )

# This is the behaviour I expected (scalar passed, scalar returned).
# Adding [0] on the return value is a hackey solution (then thing would break if a list were actually passed).
print f_inverse(1.0)[0] # <- bad solution
print type( f_inverse(1.0)[0] )

在我的系统上，此输出为：

[ 2.23872989  1.10914418  4.1187546 ]
<type 'numpy.ndarray'>
[ 2.23872989  1.10914418  4.1187546 ]
<type 'numpy.ndarray'>
[ 2.23872989]
<type 'numpy.ndarray'>
2.23872989209
<type 'numpy.float64'>

我正在使用MacPorts提供的SciPy 0.10.1和Python 2.7.3。

解

阅读以下答案后，我决定采用以下解决方案。将回车线替换为f_inverse：

if(type(y).__module__ == np.__name__):
    return x_optimized
else:
    return type(y)(x_optimized)

这将return type(y)(x_optimized)导致返回类型与调用该函数的类型相同。不幸的是，如果y是一个numpy类型，则此方法不起作用，因此if(type(y).__module__ == np.__name__)使用此处介绍的思想来检测numpy类型并将其排除在类型转换之外。