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        ValueError:具有多个元素的数组的真值不明确.使用 a.any() 或 a.all()

        ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()(ValueError:具有多个元素的数组的真值不明确.使用 a.any() 或 a.all())

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                  本文介绍了ValueError:具有多个元素的数组的真值不明确.使用 a.any() 或 a.all()的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着跟版网的小编来一起学习吧!


                  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"] >= startdate) & (r["dt"] <= enddate))
                  selected = r[mask]


                  r = mlab.csv2rec(datafile, delimiter=',', names=COL_HEADERS)
                  mask = ((r["dt"] >= startdate) and (r["dt"] <= 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?


                  r is a numpy (rec)array. So r["dt"] >= startdate is also a (boolean) array. For numpy arrays the & 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"] >= startdate) & (r["dt"] <= 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().

                  这篇关于ValueError:具有多个元素的数组的真值不明确.使用 a.any() 或 a.all()的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持跟版网!



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