Numpy bug？ （python3）

Question

import numpy as np
mainList = []
numpyArray0 = np.array([1,2,3])
numpyArray1 = np.array([4,5,6])
mainList.append(numpyArray0)
mainList.append(numpyArray1)

print("numpyArray0 in mainList:")
try:
  print(numpyArray0 in mainList)
except ValueError:
  print("ValueError")

print("numpyArray1 in mainList:")
try:
  print(numpyArray1 in mainList)
except ValueError:
  print("ValueError")

print("mainList in numpyArray0:")
try:
  print(mainList in numpyArray0)
except ValueError:
  print("ValueError")

print("mainList in numpyArray1:")
try:
  print(mainList in numpyArray1)
except ValueError:
  print("ValueError")

print(numpyArray1 in mainList)

So I have the above code basically it creates 2 numpy arrays inside a normal python list (mainList) and then it checks to see if those 2 arrays are inside the list. The code should output:

numpyArray0 in mainList:
True
numpyArray1 in mainList:
**True**
mainList in numpyArray0:
True
mainList in numpyArray1:
True
**True**

But instead of outputing the above it outputs the following:

numpyArray0 in mainList:
True
numpyArray1 in mainList:
ValueError
mainList in numpyArray0:
True
mainList in numpyArray1:
True
Traceback (most recent call last):
  File "/home/user/Documents/pythonCode/temp.py", line 31, in <module>
    print(numpyArray1 in mainList)
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Am I doing anything incorrectly? Note that I tried updating python, numpy, and my os (debian) before running the code.

Answer 1

numpyArray0 in mainList calls list.__contains__ . A list's __contains__ method calls PyObject_RichCompareBool for each element of the list to check if the elements are equal. As it happens, PyObject_RichCompareBool checks for identity equality first, and then does a full comparison.

numpyArray0 is mainList[0] returns True , so full comparison is never done. If full comparison was done, numpy would raise ValueError since a numpy array cannot be interepreted as a boolean.

numpyArray1 in mainList shows that as well (since identity comparison fails for numpyArray1 vs mainList[0] .

Answer 2

看起来它是与Numpy数组的==运算符重载方式相关的众所周知的功能 。

Answer 3

here the gist:

>>> numpyArray1 in mainList
....    
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

this will work:

>>> any([list(numpyArray1) == list(litem)  for litem in mainList])

True

Answer 4

Compare the same operations with lists instead of numpy arrays :

In[171]: mainList = []
In[172]: list0 = [1,2,3]
In[173]: list1 = [4,5,6]
In[174]: mainList.append(list0)
In[175]: mainList.append(list1)
In[176]: list0 in mainList
Out[176]: True
In[177]: list1 in mainList
Out[177]: True

What am I trying to show with this?

Two things.

1. That the right answer of OP question gave DYZ , not Alok Singhal .
2. That the OP question is suspiciously similar to the reported bug. Compare with this part of reported issue in Python member operation does not work on lists because of overloaded ndarray equality #10400 :

 cache = [] cache.append(numpy.ndarray([1,2,3])) cache.append(numpy.ndarray([4,5,6])) numpy.ndarray([4,5,6]) in cache