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

Question

I just discovered a logical bug in my code which was causing all sorts of problems  I was inadvertently doing a bitwise AND instead of a logical AND   I changed the code from   r   mlab csv2rec datafile  delimiter      names COL HEADERS  mask     r  dt    gt   startdate   amp   r  dt    lt   enddate   selected   r mask    TO   r   mlab csv2rec datafile  delimiter      names COL HEADERS  mask     r  dt    gt   startdate  and  r  dt    lt   enddate   selected   r mask    To my surprise  I got the rather cryptic error message      ValueError  The truth value of an array with more than one element is   ambiguous  Use a any   or a all     Why was a similar error not emitted when I use a bitwise operation - and how do I fix this

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Taking up  ZF007 s answer  this is not answering your question as a whole  but can be the solution for the same error  I post it here since I have not found a direct solution as an answer to this error message elsewhere on Stack Overflow  The error appears when you check whether an array was empty or not   if np array  1 2    print 1  -- gt  ValueError  The truth value of an array with more than one element is ambiguous  Use a any   or a all     if np array  1 2   0   print 1  -- gt  no ValueError  but  if np array     0   print 1  -- gt  IndexError  index 0 is out of bounds for axis 0 with size 0   if np array  1    print 1  -- gt  no ValueError  but again will not help at an array with many elements   if np array      print 1  -- gt  DeprecationWarning  The truth value of an empty array is ambiguous  Returning False  but in future this will result in an error  Use  array size  gt  0  to check that an array is not empty    Doing so   if np array     size  print 1  solved the error

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The reason for the exception is that and implicitly calls bool  First on the left operand and  if the left operand is True  then on the right operand  So x and y is equivalent to bool x  and bool y     However the bool on a numpy ndarray  if it contains more than one element  will throw the exception you have seen    gt  gt  gt  import numpy as np  gt  gt  gt  arr   np array  1  2  3    gt  gt  gt  bool arr  ValueError  The truth value of an array with more than one element is ambiguous  Use a any   or a all     The bool   call is implicit in and  but also in if  while  or  so any of the following examples will also fail    gt  gt  gt  arr and arr ValueError  The truth value of an array with more than one element is ambiguous  Use a any   or a all     gt  gt  gt  if arr  pass ValueError  The truth value of an array with more than one element is ambiguous  Use a any   or a all     gt  gt  gt  while arr  pass ValueError  The truth value of an array with more than one element is ambiguous  Use a any   or a all     gt  gt  gt  arr or arr ValueError  The truth value of an array with more than one element is ambiguous  Use a any   or a all     There are more functions and statements in Python that hide bool calls  for example 2  lt  x  lt  10 is just another way of writing 2  lt  x and x  lt  10  And the and will call bool  bool 2  lt  x  and bool x  lt  10    The element-wise equivalent for and would be the np logical and function  similarly you could use np logical or as equivalent for or    For boolean arrays - and comparisons like  lt    lt             gt   and  gt  on NumPy arrays return boolean NumPy arrays - you can also use the element-wise bitwise functions  and operators   np bitwise and   amp  operator    gt  gt  gt  np logical and arr  gt  1  arr  lt  3  array  False   True  False   dtype bool    gt  gt  gt  np bitwise and arr  gt  1  arr  lt  3  array  False   True  False   dtype bool    gt  gt  gt   arr  gt  1   amp   arr  lt  3  array  False   True  False   dtype bool    and bitwise or    operator     gt  gt  gt  np logical or arr  lt   1  arr  gt   3  array   True  False   True   dtype bool    gt  gt  gt  np bitwise or arr  lt   1  arr  gt   3  array   True  False   True   dtype bool    gt  gt  gt   arr  lt   1     arr  gt   3  array   True  False   True   dtype bool    A complete list of logical and binary functions can be found in the NumPy documentation     Logic functions   Binary operations

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This typed error-message also shows while an if-statement comparison is done where there is an array and for example a bool or int  See for example       code snippet      if dataset    bool                code snippet       This clause has dataset as array and bool is euhm the  open door     True or False   In case the function is wrapped within a try-statement you will receive with except Exception as error  the message without its error-type       The truth value of an array with more than one element is ambiguous  Use a any   or a all

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r is a numpy  rec array  So r  dt    gt   startdate is also a  boolean  array  For numpy arrays the  amp  operation returns the elementwise-and of the two boolean arrays   The NumPy developers felt there was no one commonly understood way to evaluate an array in boolean context  it could mean True if any element is True  or it could mean True if all elements are True  or True if the array has non-zero length  just to name three possibilities   Since different users might have different needs and different assumptions  the NumPy developers refused to guess and instead decided to raise a ValueError whenever one tries to evaluate an array in boolean context  Applying and to two numpy arrays causes the two arrays to be evaluated in boolean context  by calling   bool   in Python3 or   nonzero   in Python2    Your original code   mask     r  dt    gt   startdate   amp   r  dt    lt   enddate   selected   r mask    looks correct  However  if you do want and  then instead of a and b use  a-b  any   or  a-b  all

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try this    numpy array r    or     numpy array yourvariable    followed by the command to compare whatever you wish to

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I had the same problem  i e  indexing with multi-conditions  here it s finding data in a certain date range   The  a-b  any   or  a-b  all   seem not working  at least for me    Alternatively I found another solution which works perfectly for my desired functionality  The truth value of an array with more than one element is ambigous when trying to index an array    Instead of using suggested code above  simply using a numpy logical and a b  would work  Here you may want to rewrite the code as   selected    r numpy logical and r  dt    gt   startdate  r  dt    lt   enddate

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if you work with pandas what solved the issue for me was that i was trying to do calculations when I had NA values  the solution was to run   df   df dropna    And after that the calculation that failed

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

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