Re: [Numpy-discussion] Convolve returning zero array
Hi Peter, At first I used numarray 0.6. This morning I have installed 0.8 but the results are the same. I will try the convolve functions in the nd_image package. Thanks, Remco Jager MAPPER Lithography Lorentzweg 1 2628 CJ Delft, The Netherlands tel.: +31 (0)15 2789439 fax: +31 (0)15-2789473 http://www.mapperlithography.com This e-mail, attachments and (any part of) its content are (i) intended for the named addressee(s) only and (ii) strictly confidential and proprietary. All rights are reserved by MAPPER Lithography. Any unauthorized use, disclosure and/or copying are strictly prohibited, except with prior and express written permission by MAPPER Lithography. Should you have received this e-mail, attachments and its content by mistake, please bring this to our attention and destroy this e-mail and attachments in full. Thank you. |---------+----------------------------> | | Peter Verveer | | | <verveer@embl-hei| | | delberg.de> | | | | | | 15/12/2003 12:04 | | | | |---------+---------------------------->
------------------------------------------------------------------------------------------------------------------------------| | | | To: R.Jager@mapperlithography.com, numpy-discussion@lists.sourceforge.net | | cc: | | Subject: Re: [Numpy-discussion] Convolve returning zero array | ------------------------------------------------------------------------------------------------------------------------------|
Hi list,
I already posted this on the numarray forum on freshmeat, but Jay T Miller advised me to post my problem to this list. OK, now for the problem: I
to convolve a Gaussian distribution with a binary pattern. For small values of the sigma of the Gaussian distribution the convolution returns an array of zeros. For a large value the results are OK. I did some more research and found out that the zero array is returned if the length of the Gaussian is smaller than the length of the binary pattern. In the function call the Gaussian is the kernel and the binary pattern is the data. The convolution mode is 'SAME'. I have swapped the data and kernel in the convolve function call, but this has no influence on the result, as this is swapped again in convolve.py. A quick and dirty workaround is to always make the Gaussian distribution longer than the binary pattern, but for very large binary patterns this increases the calculation time significantly. Does anyone have an idea how to solve
properly?
Met vriendelijke groeten,
Remco Jager
MAPPER Lithography Lorentzweg 1 2628 CJ Delft, The Netherlands tel.: +31 (0)15 2789439 fax: +31 (0)15-2789473 http://www.mapperlithography.com
This e-mail, attachments and (any part of) its content are (i) intended for the named addressee(s) only and (ii) strictly confidential and
Hi Remco, Sounds like a bug. Which version of numarray do you use? Version 0.8 of numarray should have appeared on sourceforge now. If the convolve in that version does still not work, you could try out the convolution function in the new nd_image package that is part of numarray 0.8. If that does not work, let me know since I am the author of that package, and will fix problems with it. Cheers, Peter On Monday 15 December 2003 11:24, R.Jager@mapperlithography.com wrote: try this proprietary.
All rights are reserved by MAPPER Lithography. Any unauthorized use, disclosure and/or copying are strictly prohibited, except with prior and express written permission by MAPPER Lithography. Should you have received this e-mail, attachments and its content by mistake, please bring this to our attention and destroy this e-mail and attachments in full. Thank you.
------------------------------------------------------- This SF.net email is sponsored by: SF.net Giveback Program. Does SourceForge.net help you be more productive? Does it help you create better code? SHARE THE LOVE, and help us help YOU! Click Here: http://sourceforge.net/donate/ _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
-- Dr. Peter J. Verveer Cell Biology and Cell Biophysics Programme European Molecular Biology Laboratory Meyerhofstrasse 1 D-69117 Heidelberg Germany Tel. : +49 6221 387245 Fax : +49 6221 387306
1. Can you post an example? 2. Whenever convolution runs slow because the arrays are large, use FFT (with a proper padding) --- it can be an order of magnitude (or more) faster. Nadav. R.Jager@mapperlithography.com wrote:
Hi Peter,
At first I used numarray 0.6. This morning I have installed 0.8 but the results are the same. I will try the convolve functions in the nd_image package.
Thanks,
Remco Jager
MAPPER Lithography Lorentzweg 1 2628 CJ Delft, The Netherlands tel.: +31 (0)15 2789439 fax: +31 (0)15-2789473 http://www.mapperlithography.com
This e-mail, attachments and (any part of) its content are (i) intended for the named addressee(s) only and (ii) strictly confidential and proprietary. All rights are reserved by MAPPER Lithography. Any unauthorized use, disclosure and/or copying are strictly prohibited, except with prior and express written permission by MAPPER Lithography. Should you have received this e-mail, attachments and its content by mistake, please bring this to our attention and destroy this e-mail and attachments in full. Thank you.
|---------+----------------------------> | | Peter Verveer | | | <verveer@embl-hei| | | delberg.de> | | | | | | 15/12/2003 12:04 | | | | |---------+---------------------------->
------------------------------------------------------------------------------------------------------------------------------| | | | To: R.Jager@mapperlithography.com, numpy-discussion@lists.sourceforge.net | | cc: | | Subject: Re: [Numpy-discussion] Convolve returning zero array | ------------------------------------------------------------------------------------------------------------------------------|
Hi Remco,
Sounds like a bug. Which version of numarray do you use? Version 0.8 of numarray should have appeared on sourceforge now. If the convolve in that version does still not work, you could try out the convolution function in the new nd_image package that is part of numarray 0.8. If that does not work, let me know since I am the author of that package, and will fix problems with it.
Cheers, Peter
On Monday 15 December 2003 11:24, R.Jager@mapperlithography.com wrote:
Hi list,
I already posted this on the numarray forum on freshmeat, but Jay T
Miller
advised me to post my problem to this list. OK, now for the problem: I
try
to convolve a Gaussian distribution with a binary pattern. For small
values
of the sigma of the Gaussian distribution the convolution returns an
array
of zeros. For a large value the results are OK. I did some more research and found out that the zero array is returned if the length of the Gaussian is smaller than the length of the binary pattern. In the function call the Gaussian is the kernel and the binary pattern is the data. The convolution mode is 'SAME'. I have swapped the data and kernel in the convolve function call, but this has no influence
on
the result, as this is swapped again in convolve.py. A quick and dirty workaround is to always make the Gaussian distribution longer than the binary pattern, but for very large binary patterns this increases the calculation time significantly. Does anyone have an idea how to solve
this
properly?
Met vriendelijke groeten,
Remco Jager
MAPPER Lithography Lorentzweg 1 2628 CJ Delft, The Netherlands tel.: +31 (0)15 2789439 fax: +31 (0)15-2789473 http://www.mapperlithography.com
This e-mail, attachments and (any part of) its content are (i) intended
for
the named addressee(s) only and (ii) strictly confidential and
proprietary.
All rights are reserved by MAPPER Lithography. Any unauthorized use, disclosure and/or copying are strictly prohibited, except with prior and express written permission by MAPPER Lithography. Should you have
received
this e-mail, attachments and its content by mistake, please bring this to our attention and destroy this e-mail and attachments in full. Thank you.
------------------------------------------------------- This SF.net email is sponsored by: SF.net Giveback Program. Does SourceForge.net help you be more productive? Does it help you create better code? SHARE THE LOVE, and help us help YOU! Click Here: http://sourceforge.net/donate/ _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
-- Dr. Peter J. Verveer Cell Biology and Cell Biophysics Programme European Molecular Biology Laboratory Meyerhofstrasse 1 D-69117 Heidelberg Germany Tel. : +49 6221 387245 Fax : +49 6221 387306
------------------------------------------------------- This SF.net email is sponsored by: SF.net Giveback Program. Does SourceForge.net help you be more productive? Does it help you create better code? SHARE THE LOVE, and help us help YOU! Click Here: http://sourceforge.net/donate/ _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
participants (2)
-
Nadav Horesh -
R.Jagerļ¼ mapperlithography.com