The documentation at : https://numpy.org/doc/stable/user/basics.indexing.html?highlight=slice does say that slicing creates a view into the original, and not a new object.
So it isn't a bug - it is entirely expected behaviour
To Quote :
NumPy slicing creates a view instead of a copy as in the case of
built-in Python sequences such as string, tuple and list.
Care must be taken when extracting
a small portion from a large array which becomes useless after the
extraction, because the small portion extracted contains a reference
to the large original array whose memory will not be released until
all arrays derived from it are garbage-collected. In such cases an
explicit copy() is recommended.
------ Original Message ------
From: "Leon fevang-gunn" <leon.fevanggunn@gmail.com>
To: docs@python.org
Sent: Monday, 18 Jul, 22 At 15:59
Subject: [docs] Suspected bugHello.So I managed to fix it, but I think I had an experience with a bug... It seems that a slice of a numpy array gave me some trouble. Only after redefining the slice as a numpy array would the code run as normal again. In other words:NOT working:zk = np.array(list1)zk2 = zk[a:b]Working:zk = np.array(list1)zk2 = np.array(zk[a:b])I also checked and it does say that a slice of an array should be an array:in: zk[a:b]out: arra(list1[a:b])The problem was that it would link the two variables zk and zk2 together:zk = array1zk2 = array1[a:b]When i changed zk2[0] to a different value, the corresponding element, zk[a], also changes. So for example:zk = np.array([1,2,3,4,5])zk2 = np.array(zk[1:4])in: print(zk)print(zk2)out: array([1,2,3,4,5])array([2,3,4])in: zk_2[0] = 0print(zk)print(zk2)out: array([1,0,3,4,5])array([0,3,4])Additional information:- zk is read in from a .csv file using pandas.- I am using Spyder/Anaconda- When i change a value of zk_2 in the command window, zk remains the sameAllright, thought I would let someone know. Let me know if you need additional information.Kind regards,Leon
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