RE: Why can't numpy array be restored to saved value?
> -Original Message- > From: Christian Gollwitzer > Sent: Thursday, November 26, 2020 3:26 AM > To: python-list@python.org > Subject: Re: Why can't numpy array be restored to saved value? > > Am 25.11.20 um 07:47 schrieb pjfarl...@earthlink.net: > > Why isn't the final value of the numpy array npary in the following code the > > same as the initial value before some but not all elements of the array were > > changed to a new value? > > > > I know I am missing something basic here. I thought I understood the > > concepts of immutable vs mutable values but obviously I missed something. > > > > Because this does not copy the array, rather it creates a view into the > original array. This is an optimization to avoid copying. If you want a > copy, do svary = npary.copy() Thank you for the explanation. I did indeed find that using the copy() function did what I needed to do. Peter -- https://mail.python.org/mailman/listinfo/python-list
RE: Why can't numpy array be restored to saved value?
> -Original Message- > From: Greg Ewing > Sent: Thursday, November 26, 2020 12:01 AM > To: python-list@python.org > Subject: Re: Why can't numpy array be restored to saved value? > > On 25/11/20 7:47 pm, pjfarl...@earthlink.net wrote: > > Why isn't the final value of the numpy array npary in the following code the > > same as the initial value before some but not all elements of the array were > > changed to a new value? > > Slicing a numpy array doesn't copy anything, it just > gives you another view of the underlying data. > > This is a trap you need to watch out for, since it's > different from the way sequences normally behave in > Python. > > -- > Greg Thank you for that explanation. I will certainly watch out for it in the future. Peter -- https://mail.python.org/mailman/listinfo/python-list
Re: Why can't numpy array be restored to saved value?
Am 25.11.20 um 07:47 schrieb pjfarl...@earthlink.net: Why isn't the final value of the numpy array npary in the following code the same as the initial value before some but not all elements of the array were changed to a new value? I know I am missing something basic here. I thought I understood the concepts of immutable vs mutable values but obviously I missed something. My environment is Win10-64, Python 3.8.5, numpy 1.19.2. Code and output follows. TIA for any help you can provide to cure my ignorance. Peter --- nptest.py --- import numpy as np import sys if len(sys.argv) > 0: try: asz = int(sys.argv[1]) + 0 except: asz = 4 npary = np.full([asz, asz, asz], 0, dtype=np.int32) print("Array before change=\n{}".format(npary)) svary = npary[:, :, :] Because this does not copy the array, rather it creates a view into the original array. This is an optimization to avoid copying. If you want a copy, do svary = npary.copy() Christian -- https://mail.python.org/mailman/listinfo/python-list
Re: Why can't numpy array be restored to saved value?
On 25/11/20 7:47 pm, pjfarl...@earthlink.net wrote: Why isn't the final value of the numpy array npary in the following code the same as the initial value before some but not all elements of the array were changed to a new value? Slicing a numpy array doesn't copy anything, it just gives you another view of the underlying data. This is a trap you need to watch out for, since it's different from the way sequences normally behave in Python. -- Greg -- https://mail.python.org/mailman/listinfo/python-list
RE: Why can't numpy array be restored to saved value?
Never mind, I found the numpy.copy function does what I need. Revised code below works. Sorry for wasting bandwidth. Peter --- nptest.py --- import numpy as np import sys if len(sys.argv) > 0: try: asz = int(sys.argv[1]) + 0 except: asz = 4 npary = np.full([asz, asz, asz], 0, dtype=np.int32) print("Array before change=\n{}".format(npary)) svary = np.copy(npary, order='C') npary[1:-1, 1:-1, 1:-1] = 1 print("Array after change=\n{}".format(npary)) npary = svary print("Array after restore=\n{}".format(npary)) --- nptest.py --- > -Original Message- > From: pjfarl...@earthlink.net > Sent: Wednesday, November 25, 2020 1:48 AM > To: 'python-list@python.org' > Subject: Why can't numpy array be restored to saved value? > > Why isn't the final value of the numpy array npary in the following code the > same as the initial value before some but not all elements of the array were > changed to a new value? > > I know I am missing something basic here. I thought I understood the concepts > of immutable vs mutable values but obviously I missed something. > > My environment is Win10-64, Python 3.8.5, numpy 1.19.2. > > Code and output follows. TIA for any help you can provide to cure my > ignorance. > > Peter > > --- nptest.py --- > import numpy as np > import sys > > if len(sys.argv) > 0: > try: > asz = int(sys.argv[1]) + 0 > except: > asz = 4 > > npary = np.full([asz, asz, asz], 0, dtype=np.int32) > print("Array before change=\n{}".format(npary)) > svary = npary[:, :, :] > npary[1:-1, 1:-1, 1:-1] = 1 > print("Array after change=\n{}".format(npary)) > npary = svary[:, :, :] > print("Array after restore=\n{}".format(npary)) > --- nptest.py --- > > --- output --- > Array before change= > [[[0 0 0 0] > [0 0 0 0] > [0 0 0 0] > [0 0 0 0]] > > [[0 0 0 0] > [0 0 0 0] > [0 0 0 0] > [0 0 0 0]] > > [[0 0 0 0] > [0 0 0 0] > [0 0 0 0] > [0 0 0 0]] > > [[0 0 0 0] > [0 0 0 0] > [0 0 0 0] > [0 0 0 0]]] > Array after change= > [[[0 0 0 0] > [0 0 0 0] > [0 0 0 0] > [0 0 0 0]] > > [[0 0 0 0] > [0 1 1 0] > [0 1 1 0] > [0 0 0 0]] > > [[0 0 0 0] > [0 1 1 0] > [0 1 1 0] > [0 0 0 0]] > > [[0 0 0 0] > [0 0 0 0] > [0 0 0 0] > [0 0 0 0]]] > Array after restore= > [[[0 0 0 0] > [0 0 0 0] > [0 0 0 0] > [0 0 0 0]] > > [[0 0 0 0] > [0 1 1 0] > [0 1 1 0] > [0 0 0 0]] > > [[0 0 0 0] > [0 1 1 0] > [0 1 1 0] > [0 0 0 0]] > > [[0 0 0 0] > [0 0 0 0] > [0 0 0 0] > [0 0 0 0]]] > --- output --- -- https://mail.python.org/mailman/listinfo/python-list
Why can't numpy array be restored to saved value?
Why isn't the final value of the numpy array npary in the following code the same as the initial value before some but not all elements of the array were changed to a new value? I know I am missing something basic here. I thought I understood the concepts of immutable vs mutable values but obviously I missed something. My environment is Win10-64, Python 3.8.5, numpy 1.19.2. Code and output follows. TIA for any help you can provide to cure my ignorance. Peter --- nptest.py --- import numpy as np import sys if len(sys.argv) > 0: try: asz = int(sys.argv[1]) + 0 except: asz = 4 npary = np.full([asz, asz, asz], 0, dtype=np.int32) print("Array before change=\n{}".format(npary)) svary = npary[:, :, :] npary[1:-1, 1:-1, 1:-1] = 1 print("Array after change=\n{}".format(npary)) npary = svary[:, :, :] print("Array after restore=\n{}".format(npary)) --- nptest.py --- --- output --- Array before change= [[[0 0 0 0] [0 0 0 0] [0 0 0 0] [0 0 0 0]] [[0 0 0 0] [0 0 0 0] [0 0 0 0] [0 0 0 0]] [[0 0 0 0] [0 0 0 0] [0 0 0 0] [0 0 0 0]] [[0 0 0 0] [0 0 0 0] [0 0 0 0] [0 0 0 0]]] Array after change= [[[0 0 0 0] [0 0 0 0] [0 0 0 0] [0 0 0 0]] [[0 0 0 0] [0 1 1 0] [0 1 1 0] [0 0 0 0]] [[0 0 0 0] [0 1 1 0] [0 1 1 0] [0 0 0 0]] [[0 0 0 0] [0 0 0 0] [0 0 0 0] [0 0 0 0]]] Array after restore= [[[0 0 0 0] [0 0 0 0] [0 0 0 0] [0 0 0 0]] [[0 0 0 0] [0 1 1 0] [0 1 1 0] [0 0 0 0]] [[0 0 0 0] [0 1 1 0] [0 1 1 0] [0 0 0 0]] [[0 0 0 0] [0 0 0 0] [0 0 0 0] [0 0 0 0]]] --- output --- -- https://mail.python.org/mailman/listinfo/python-list