检查变量是否为None或numpy.array时发生ValueError [英] ValueError when checking if variable is None or numpy.array

问题描述

我想检查变量是否为None或numpy.array.我已经实现了check_a函数来做到这一点.

I'd like to check if variable is None or numpy.array. I've implemented check_a function to do this.

def check_a(a):
    if not a:
        print "please initialize a"

a = None
check_a(a)
a = np.array([1,2])
check_a(a)

但是，此代码引发ValueError.什么是直截了当的方式?

But, this code raises ValueError. What is the straight forward way?

ValueError                                Traceback (most recent call last)
<ipython-input-41-0201c81c185e> in <module>()
      6 check_a(a)
      7 a = np.array([1,2])
----> 8 check_a(a)

<ipython-input-41-0201c81c185e> in check_a(a)
      1 def check_a(a):
----> 2     if not a:
      3         print "please initialize a"
      4 
      5 a = None

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

推荐答案

使用not a测试a是否为None假定a的其他可能值的真实值为True.但是，大多数NumPy数组根本没有真值，因此not不能应用于它们.

Using not a to test whether a is None assumes that the other possible values of a have a truth value of True. However, most NumPy arrays don't have a truth value at all, and not cannot be applied to them.

如果要测试对象是否为None，最通用，最可靠的方法是直接对None使用is检查:

If you want to test whether an object is None, the most general, reliable way is to literally use an is check against None:

if a is None:
    ...
else:
    ...

这不依赖于具有真值的对象，因此它适用于NumPy数组.

This doesn't depend on objects having a truth value, so it works with NumPy arrays.

请注意，测试必须是is，而不是==. is是对象身份测试. ==就是参数说的是什么，NumPy数组说这是广播的元素等式比较，产生一个布尔数组:

Note that the test has to be is, not ==. is is an object identity test. == is whatever the arguments say it is, and NumPy arrays say it's a broadcasted elementwise equality comparison, producing a boolean array:

>>> a = numpy.arange(5)
>>> a == None
array([False, False, False, False, False])
>>> if a == None:
...     pass
...
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: The truth value of an array with more than one element is ambiguous.
 Use a.any() or a.all()

---

另一方面，如果要测试对象是否为NumPy数组，则可以测试其类型:

---

On the other side of things, if you want to test whether an object is a NumPy array, you can test its type:

# Careful - the type is np.ndarray, not np.array. np.array is a factory function.
if type(a) is np.ndarray:
    ...
else:
    ...

您还可以使用isinstance，对于该类型的子类(如果需要的话)，它还将返回True.考虑到np.matrix的可怕和不兼容，您可能实际上不希望这样做:

You can also use isinstance, which will also return True for subclasses of that type (if that is what you want). Considering how terrible and incompatible np.matrix is, you may not actually want this:

# Again, ndarray, not array, because array is a factory function.
if isinstance(a, np.ndarray):
    ...
else:
    ...    

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