ndarray.resize that preserve view content ?
Hi, given A=empty([10,10]), I would like to keep A[:5,:5] as a contiguous memory segment. How to do it efficiently? Thanks.
On Wed, Aug 4, 2010 at 09:29, Antoine Dechaume <boolegue@gmail.com> wrote:
Hi,
given A=empty([10,10]), I would like to keep A[:5,:5] as a contiguous memory segment.
How to do it efficiently?
I'm not sure I understand what you want. Your Subject line and the body of your email conflict with each other. Can you try to explain what you want in other words? -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco
I forgot to refer to resize, sorry about that. A[:5,:5] shows the data I want, but it's not contiguous in memory. A.resize(5,5) is contiguous, but do not contains the data I want. How to get both efficiently? On Wed, Aug 4, 2010 at 5:01 PM, Robert Kern <robert.kern@gmail.com> wrote:
On Wed, Aug 4, 2010 at 09:29, Antoine Dechaume <boolegue@gmail.com> wrote:
Hi,
given A=empty([10,10]), I would like to keep A[:5,:5] as a contiguous memory segment.
How to do it efficiently?
I'm not sure I understand what you want. Your Subject line and the body of your email conflict with each other. Can you try to explain what you want in other words?
-- Robert Kern
"I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
A[:5,:5] shows the data I want, but it's not contiguous in memory. A.resize(5,5) is contiguous, but do not contains the data I want.
How to get both efficiently?
A[:5,:5].copy() will give you a new, contiguous array that has the same contents as A[5:,5:], but in a new chunk of memory. Is this what you need? On Aug 4, 2010, at 11:17 AM, Antoine Dechaume wrote:
I forgot to refer to resize, sorry about that.
A[:5,:5] shows the data I want, but it's not contiguous in memory. A.resize(5,5) is contiguous, but do not contains the data I want.
How to get both efficiently?
On Wed, Aug 4, 2010 at 5:01 PM, Robert Kern <robert.kern@gmail.com> wrote: On Wed, Aug 4, 2010 at 09:29, Antoine Dechaume <boolegue@gmail.com> wrote:
Hi,
given A=empty([10,10]), I would like to keep A[:5,:5] as a contiguous memory segment.
How to do it efficiently?
I'm not sure I understand what you want. Your Subject line and the body of your email conflict with each other. Can you try to explain what you want in other words?
-- Robert Kern
"I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Yes it is, but is there a way to do it in-place? On Wed, Aug 4, 2010 at 5:20 PM, Zachary Pincus <zachary.pincus@yale.edu>wrote:
A[:5,:5] shows the data I want, but it's not contiguous in memory. A.resize(5,5) is contiguous, but do not contains the data I want.
How to get both efficiently?
A[:5,:5].copy() will give you a new, contiguous array that has the same contents as A[5:,5:], but in a new chunk of memory. Is this what you need?
On Aug 4, 2010, at 11:17 AM, Antoine Dechaume wrote:
I forgot to refer to resize, sorry about that.
A[:5,:5] shows the data I want, but it's not contiguous in memory. A.resize(5,5) is contiguous, but do not contains the data I want.
How to get both efficiently?
On Wed, Aug 4, 2010 at 5:01 PM, Robert Kern <robert.kern@gmail.com> wrote: On Wed, Aug 4, 2010 at 09:29, Antoine Dechaume <boolegue@gmail.com> wrote:
Hi,
given A=empty([10,10]), I would like to keep A[:5,:5] as a contiguous memory segment.
How to do it efficiently?
I'm not sure I understand what you want. Your Subject line and the body of your email conflict with each other. Can you try to explain what you want in other words?
-- Robert Kern
"I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
On Wed, Aug 4, 2010 at 10:31, Antoine Dechaume <boolegue@gmail.com> wrote:
Yes it is, but is there a way to do it in-place?
No. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco
Yes it is, but is there a way to do it in-place?
So you want the first 25 elements of the array (in a flat "contiguous" view) to contain the 25 elements of A[:5,:5]? This will do that, but having to do stuff like this (rather than just copying the memory region) might be indicative that maybe your code design might not really be right. (Why does it absolutely have to be in-place? Memory pressure?) In [34]: a = numpy.array(numpy.arange(100, dtype=int).reshape(10,10)) In [35]: a Out[35]: array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [10, 11, 12, 13, 14, 15, 16, 17, 18, 19], [20, 21, 22, 23, 24, 25, 26, 27, 28, 29], [30, 31, 32, 33, 34, 35, 36, 37, 38, 39], [40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [50, 51, 52, 53, 54, 55, 56, 57, 58, 59], [60, 61, 62, 63, 64, 65, 66, 67, 68, 69], [70, 71, 72, 73, 74, 75, 76, 77, 78, 79], [80, 81, 82, 83, 84, 85, 86, 87, 88, 89], [90, 91, 92, 93, 94, 95, 96, 97, 98, 99]]) In [36]: a[:5,:5] Out[36]: array([[ 0, 1, 2, 3, 4], [10, 11, 12, 13, 14], [20, 21, 22, 23, 24], [30, 31, 32, 33, 34], [40, 41, 42, 43, 44]]) In [37]: a.flat[:25] = a[:5,:5] In [38]: a.resize((5,5)) --------------------------------------------------------------------------- ValueError Traceback (most recent call last) /Users/zpincus/<ipython console> in <module>() ValueError: cannot resize an array that has been referenced or is referencing another array in this way. Use the resize function In [39]: b = numpy.ndarray(buffer=a, shape=(5,5), dtype=int) In [40]: b Out[40]: array([[ 0, 1, 2, 3, 4], [10, 11, 12, 13, 14], [20, 21, 22, 23, 24], [30, 31, 32, 33, 34], [40, 41, 42, 43, 44]]) In [41]: b.flags.c_contiguous Out[41]: True In [42]: b.flags.owndata Out[42]: False Zach
On Wed, Aug 4, 2010 at 5:20 PM, Zachary Pincus <zachary.pincus@yale.edu
wrote: A[:5,:5] shows the data I want, but it's not contiguous in memory. A.resize(5,5) is contiguous, but do not contains the data I want.
How to get both efficiently?
A[:5,:5].copy() will give you a new, contiguous array that has the same contents as A[5:,5:], but in a new chunk of memory. Is this what you need?
On Aug 4, 2010, at 11:17 AM, Antoine Dechaume wrote:
I forgot to refer to resize, sorry about that.
A[:5,:5] shows the data I want, but it's not contiguous in memory. A.resize(5,5) is contiguous, but do not contains the data I want.
How to get both efficiently?
On Wed, Aug 4, 2010 at 5:01 PM, Robert Kern <robert.kern@gmail.com> wrote: On Wed, Aug 4, 2010 at 09:29, Antoine Dechaume <boolegue@gmail.com> wrote:
Hi,
given A=empty([10,10]), I would like to keep A[:5,:5] as a contiguous memory segment.
How to do it efficiently?
I'm not sure I understand what you want. Your Subject line and the body of your email conflict with each other. Can you try to explain what you want in other words?
-- Robert Kern
"I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Oh and PS. Robert's right that there's no general way to do this! What I have only works because the data existing in the first 25 elements of A that get clobbered by the copy operation aren't the same data that are being copied (or where they are, the new copy is identical to the old one). Other slices won't have this property... A[:] = A[::-1] e.g. will fail totally. On Aug 4, 2010, at 11:52 AM, Zachary Pincus wrote:
Yes it is, but is there a way to do it in-place?
So you want the first 25 elements of the array (in a flat "contiguous" view) to contain the 25 elements of A[:5,:5]? This will do that, but having to do stuff like this (rather than just copying the memory region) might be indicative that maybe your code design might not really be right. (Why does it absolutely have to be in-place? Memory pressure?)
In [34]: a = numpy.array(numpy.arange(100, dtype=int).reshape(10,10))
In [35]: a Out[35]: array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [10, 11, 12, 13, 14, 15, 16, 17, 18, 19], [20, 21, 22, 23, 24, 25, 26, 27, 28, 29], [30, 31, 32, 33, 34, 35, 36, 37, 38, 39], [40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [50, 51, 52, 53, 54, 55, 56, 57, 58, 59], [60, 61, 62, 63, 64, 65, 66, 67, 68, 69], [70, 71, 72, 73, 74, 75, 76, 77, 78, 79], [80, 81, 82, 83, 84, 85, 86, 87, 88, 89], [90, 91, 92, 93, 94, 95, 96, 97, 98, 99]])
In [36]: a[:5,:5] Out[36]: array([[ 0, 1, 2, 3, 4], [10, 11, 12, 13, 14], [20, 21, 22, 23, 24], [30, 31, 32, 33, 34], [40, 41, 42, 43, 44]])
In [37]: a.flat[:25] = a[:5,:5]
In [38]: a.resize((5,5)) --------------------------------------------------------------------------- ValueError Traceback (most recent call last)
/Users/zpincus/<ipython console> in <module>()
ValueError: cannot resize an array that has been referenced or is referencing another array in this way. Use the resize function
In [39]: b = numpy.ndarray(buffer=a, shape=(5,5), dtype=int) In [40]: b
Out[40]: array([[ 0, 1, 2, 3, 4], [10, 11, 12, 13, 14], [20, 21, 22, 23, 24], [30, 31, 32, 33, 34], [40, 41, 42, 43, 44]])
In [41]: b.flags.c_contiguous Out[41]: True
In [42]: b.flags.owndata Out[42]: False
Zach
On Wed, Aug 4, 2010 at 5:20 PM, Zachary Pincus <zachary.pincus@yale.edu
wrote: A[:5,:5] shows the data I want, but it's not contiguous in memory. A.resize(5,5) is contiguous, but do not contains the data I want.
How to get both efficiently?
A[:5,:5].copy() will give you a new, contiguous array that has the same contents as A[5:,5:], but in a new chunk of memory. Is this what you need?
On Aug 4, 2010, at 11:17 AM, Antoine Dechaume wrote:
I forgot to refer to resize, sorry about that.
A[:5,:5] shows the data I want, but it's not contiguous in memory. A.resize(5,5) is contiguous, but do not contains the data I want.
How to get both efficiently?
On Wed, Aug 4, 2010 at 5:01 PM, Robert Kern <robert.kern@gmail.com> wrote: On Wed, Aug 4, 2010 at 09:29, Antoine Dechaume <boolegue@gmail.com> wrote:
Hi,
given A=empty([10,10]), I would like to keep A[:5,:5] as a contiguous memory segment.
How to do it efficiently?
I'm not sure I understand what you want. Your Subject line and the body of your email conflict with each other. Can you try to explain what you want in other words?
-- Robert Kern
"I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
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participants (3)
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Antoine Dechaume -
Robert Kern -
Zachary Pincus