Hi,
I think this means that your computer doesn't have enough RAM memory to
run your code.
Cheers,
Carlos
El 5/06/24 a las 15:39, demi held escribió:
The code I am attempting to use, when I run it tells me "Memory
Error". (screenshot of the message attached) I both do not know what
it mean
Hi,
A look at memory usage in the posted test cases indicates that address
space fragmentation is a major factor at least in my setup
Python 3.4.1 |Anaconda 2.1.0 (32-bit)| (default, Jun 11 2014, 17:29:32)
[MSC v.1600 32 bit (Intel)] running on 64 bit Windows 7.
Such fragmention is described in,
Maybe a bit off topic but still something that could be potentially
interesting and useful is that we could/should start compiling all these
"bugs" and turn them into unit tests so that future proofing is handled.
Not sure if for a IDE like spyder Travis (now that the move to github seems
inmi
On 10/06/2014 08:51 AM, Patrick Leinenkugel wrote:
Yes, I definitely used the same python distribution.
What perhaps is of interest to you is that I experienced different
tolerances in the Python IDLE of producing these arrays (3-5 arrays),
while with Spyder, it was either one or a maximum of two
I filed a ticket here:
https://code.google.com/p/spyderlib/issues/detail?can=2&q=1999&colspec=ID%20MS%20Stars%20Priority%20Modified%20Cat%20Type%20Status%20Owner%20Summary&id=1999
On Tue, Oct 7, 2014 at 10:20 AM, Jonno wrote:
> I don't know if it's the same issue but I'm also seeing a memory err
I don't know if it's the same issue but I'm also seeing a memory error only
in Spyder and I too have 32 bit Spyder & Python via Anaconda 2.0.1 on Win7
64 bit. I don't see the issue outside of Spyder but using the same Python
interpreter.
Interestingly this issue doesn't exist for a different machi
Yes, I definitely used the same python distribution.
What perhaps is of interest to you is that I experienced different
tolerances in the Python IDLE of producing these arrays (3-5 arrays), while
with Spyder, it was either one or a maximum of two arrays, that could be
created. So in all cases,
> > That is what I am trying to get a handle on. If it is just a straight
> > memory access problem due to memory restrictions in 32 bit Windows then
> > the second case should fail if the first does.
>
Just guessing, but maybe this is caused by fragmentation of the 32-bit
address space. Perh
On 09/26/2014 01:31 AM, Joseph Martinot-Lagarde wrote:
I don't know exactly why, but here are some hints:
- A 7000*7000 array of float64 takes 7000 * 7000 * 8 / 1024 / 1024 = 373
Mo of memory (headers are negligible)
- Each line where the arrays are created creates an additional temporary
array
I don't know exactly why, but here are some hints:
- A 7000*7000 array of float64 takes 7000 * 7000 * 8 / 1024 / 1024 = 373 Mo
of memory (headers are negligible)
- Each line where the arrays are created creates an additional temporary
array (because of the addition), so in spyder the problem ari
On 09/25/2014 01:01 AM, Patrick Leinenkugel wrote:
Hi Adrian,
I meanwhile figured out that it was not a problem of Spyder. I did not
expext that the 32-bit version was limited to so little processing
memory. I now installed a 64-bit version of WinPython including a 64-bit
version of Spyder and e
Hi,
That was what I was about to say. This is not a Spyder problem because I
got the same MemoryError in all programs I tried (IDLE, IPython terminal
and Qt console).
Also if you changed float64 for float32 in your dtypes, everything
worked fine, proving Joseph point. In any case, I'm glad t
Hi Adrian,
I meanwhile figured out that it was not a problem of Spyder. I did not
expext that the 32-bit version was limited to so little processing memory. I
now installed a 64-bit version of WinPython including a 64-bit version of
Spyder and everything works fine! Thanks a lot!
Am Mittwoch,
On 09/24/2014 02:25 AM, Joseph Martinot-Lagarde wrote:
On the contrary, this is a well tested combination and it is know to
work badly.
When using 32bit python, you're limited to around 2GB of memory,
whatever your total amount of RAM. If you want to use more memory, you
have to install a 64bit
On the contrary, this is a well tested combination and it is know to work
badly.
When using 32bit python, you're limited to around 2GB of memory, whatever
your total amount of RAM. If you want to use more memory, you have to
install a 64bit distribution of python. Python(x,y) is 32bits only for
On 09/23/2014 01:35 PM, Patrick Leinenkugel wrote:
Hi Adrian,
I use Python(x,y) Version 2.7.6.1 that includes Spyder 2.5.5 and Python
2.7.6 32bits. I then realized that there was a newer version of Spyder
and updated to Spyder 2.3.1 using the executable offered on the Spyder
website. But this c
16Gb of memory and a 32bit python distribution may be an not well tested
combination.
Shouldn't you try with a 64bit distribution ?
Le mardi 23 septembre 2014 22:35:48 UTC+2, Patrick Leinenkugel a écrit :
>
> Hi Adrian,
>
> I use Python(x,y) Version 2.7.6.1 that includes Spyder 2.5.5 and Python
Hi Adrian,
I use Python(x,y) Version 2.7.6.1 that includes Spyder 2.5.5 and Python
2.7.6 32bits. I then realized that there was a newer version of Spyder and
updated to Spyder 2.3.1 using the executable offered on the Spyder website.
But this could not be the reason, since the error also appea
On 09/23/2014 11:25 AM, Patrick Leinenkugel wrote:
Hi Adrian,
thanks for helping me out. To answer your questions:
1) On the Python console
So are you using the same Python when you are in Spyder as when you are
in the IDLE console?
Also are the numpy versions the same?
The reason I ask i
Hi Adrian,
thanks for helping me out. To answer your questions:
1) On the Python console
2) I am not familiar with IPython, yet.
3) The Python IDLE that is included within every pure Python distribution,
without installing other applications.
Cheers,
Patrick
Am Dienstag, 23. September 2014 19:
On 09/23/2014 04:04 AM, Patrick Leinenkugel wrote:
Hi,
I am using Spyder within python (x,y) (Version 2.7.6.1) on Windows.
Doing the following causes a MemoryError in my Spyder Python IDE:
|>>> from numpyimport *
a_flt= ones((7000,7000), dtype=float64)+4
b_flt= ones((7000,7000), dtype
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