Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

imthresh, ncc, ftshow, imgaussiannoise, fixed imfilter #557

Merged
merged 7 commits into from
Mar 9, 2012
Merged

imthresh, ncc, ftshow, imgaussiannoise, fixed imfilter #557

merged 7 commits into from
Mar 9, 2012

Conversation

stefan-k
Copy link
Contributor

@stefan-k stefan-k commented Mar 9, 2012

conv2 doesn't work for imfilter, so I implemented the convolution directly in imfilter.

The other functions are just some small ones:

  • imthresh: thresholding
  • ncc: normalized cross correlation
  • ftshow: displays fourier transformed image
  • imgaussiannoise: adds gaussian noise to image

@JeffBezanson
Copy link
Member

Another good patch! Sorry about conv2; I changed it to match what I felt people would expect. Maybe we should have an option or separate function for the centered version.

A[:] can be replaced with just A in all cases I believe.

There is something strange in imgaussiannoise; you assign tmp to a zeros array and then immediately overwrite the variable.

@stefan-k
Copy link
Contributor Author

stefan-k commented Mar 9, 2012

I think it is better to have conv2 the way it is now. I wasn't happy about the changes I made to conv2 and I'm glad it got changed back.
I can write the centered versions if someone has an idea for a function name ;)

I use A[:] because mean(A,x) computes the mean in dimension x and there is no mean(A). Also, I need two vectors for the dot product.

You are right about imgaussiannoise, I don't know how that happend ;)

@JeffBezanson
Copy link
Member

Darn, I thought mean(A) existed. Oh well.

JeffBezanson added a commit that referenced this pull request Mar 9, 2012
@JeffBezanson
Merge pull request #557 from stefan-k/master
dc37c60 
imthresh, ncc, ftshow, imgaussiannoise, fixed imfilter
@JeffBezanson JeffBezanson merged commit dc37c60 into JuliaLang:master Mar 9, 2012
@martinholters martinholters mentioned this pull request Apr 21, 2016
Merged
Keno pushed a commit that referenced this pull request Oct 9, 2023
@KristofferC
fix an issue with detecting llvmcalls when they are interpolated (#557)
bc3ee6c
dkarrasch pushed a commit that referenced this pull request Nov 4, 2024
@DilumAluthgeBot @DilumAluthge
🤖 [backports-release-1.10] Bump the SparseArrays stdlib from 279b363 to
5549ee2 
8c84b8c (#56431)

Stdlib: SparseArrays
URL: https://github.com/JuliaSparse/SparseArrays.jl.git
Stdlib branch: release-1.10
Julia branch: backports-release-1.10
Old commit: 279b363
New commit: 8c84b8c
Julia version: 1.10.6
SparseArrays version: 1.10.0(Does not match)
Bump invoked by: @IanButterworth
Powered by:
[BumpStdlibs.jl](https://github.com/JuliaLang/BumpStdlibs.jl)

Diff:
JuliaSparse/SparseArrays.jl@279b363...8c84b8c

```
$ git log --oneline 279b363..8c84b8c
8c84b8c Merge pull request #572 from JuliaSparse/backports-release-1.10
ec38631 Update ci.yml with more architectures
46c8f7e Merge branch 'release-1.10' into backports-release-1.10
2d762b3 Manual commit for PR #550 to backport to 1.10 (#577)
5c37298 Add versions to include arch
b539588 Update CI
fa49620 Disable nested dissection
d2a80a6 Change default QR tolerance to match SPQR (#557)
9b8cd14 SparseMatrixCSC constructor with a Tuple of Integers (#523)
546be18 Fix docs conflict when building as part of full Julia docs (#430)
30fbfc6 Test suite: activate a temp project if we need to install Aqua.jl during the test suite (#425)
91b0aa5 doc: move solvers doc to `src\solvers.md` (#576)
5d3724a Inline sparse-times-dense in-place multiplication
```

Co-authored-by: Dilum Aluthge <dilum@aluthge.com>
N5N3 pushed a commit that referenced this pull request Nov 11, 2024
@DilumAluthgeBot @DilumAluthge @N5N3
🤖 [backports-release-1.10] Bump the SparseArrays stdlib from 279b363 to
c6be3e9 
8c84b8c (#56431)

Stdlib: SparseArrays
URL: https://github.com/JuliaSparse/SparseArrays.jl.git
Stdlib branch: release-1.10
Julia branch: backports-release-1.10
Old commit: 279b363
New commit: 8c84b8c
Julia version: 1.10.6
SparseArrays version: 1.10.0(Does not match)
Bump invoked by: @IanButterworth
Powered by:
[BumpStdlibs.jl](https://github.com/JuliaLang/BumpStdlibs.jl)

Diff:
JuliaSparse/SparseArrays.jl@279b363...8c84b8c

```
$ git log --oneline 279b363..8c84b8c
8c84b8c Merge pull request #572 from JuliaSparse/backports-release-1.10
ec38631 Update ci.yml with more architectures
46c8f7e Merge branch 'release-1.10' into backports-release-1.10
2d762b3 Manual commit for PR #550 to backport to 1.10 (#577)
5c37298 Add versions to include arch
b539588 Update CI
fa49620 Disable nested dissection
d2a80a6 Change default QR tolerance to match SPQR (#557)
9b8cd14 SparseMatrixCSC constructor with a Tuple of Integers (#523)
546be18 Fix docs conflict when building as part of full Julia docs (#430)
30fbfc6 Test suite: activate a temp project if we need to install Aqua.jl during the test suite (#425)
91b0aa5 doc: move solvers doc to `src\solvers.md` (#576)
5d3724a Inline sparse-times-dense in-place multiplication
```

Co-authored-by: Dilum Aluthge <dilum@aluthge.com>
ViralBShah pushed a commit that referenced this pull request Nov 12, 2024
@DilumAluthgeBot @DilumAluthge
🤖 [master] Bump the SparseArrays stdlib from 0dd8d45 to 14333ea (#56531)
c4802e1 
Stdlib: SparseArrays
URL: https://github.com/JuliaSparse/SparseArrays.jl.git
Stdlib branch: main
Julia branch: master
Old commit: 0dd8d45
New commit: 14333ea
Julia version: 1.12.0-DEV
SparseArrays version: 1.12.0
Bump invoked by: @ViralBShah
Powered by:
[BumpStdlibs.jl](https://github.com/JuliaLang/BumpStdlibs.jl)

Diff:
JuliaSparse/SparseArrays.jl@0dd8d45...14333ea

```
$ git log --oneline 0dd8d45..14333ea
14333ea Break recursion (#579)
07cf4a6 Update ci.yml (#578)
33491e0 added diagonal-sparse multiplication (#564)
8f02b7f doc: move solvers doc to `src\solvers.md` (#576)
485fd4b Inline sparse-times-dense in-place multiplication (#567)
f10d4da added specialized method for 3-argument dot with diagonal matrix (#565)
70c06b1 Diagonal-sandwiched triple product for SparseMatrixCSC (#562)
313a04f Change default QR tolerance to match SPQR (#557)
81d49e9 Update ci.yml (#558)
```

Co-authored-by: Dilum Aluthge <dilum@aluthge.com>
KristofferC pushed a commit that referenced this pull request Nov 20, 2024
@DilumAluthgeBot @DilumAluthge
🤖 [backports-release-1.11] Bump the SparseArrays stdlib from cb602d7 …
d59d80b 
…to 2420351 (#56608)

Stdlib: SparseArrays
URL: https://github.com/JuliaSparse/SparseArrays.jl.git
Stdlib branch: release-1.11
Julia branch: backports-release-1.11
Old commit: cb602d7
New commit: 2420351
Julia version: 1.11.1
SparseArrays version: 1.11.0(Does not match)
Bump invoked by: @dkarrasch
Powered by:
[BumpStdlibs.jl](https://github.com/JuliaLang/BumpStdlibs.jl)

Diff:
JuliaSparse/SparseArrays.jl@cb602d7...2420351

```
$ git log --oneline cb602d7..2420351
2420351 Allow for duplicate docstrings in linalg docs (#584)
0a1c886 Merge pull request #571 from JuliaSparse/backports-release-1.11
298f5e1 Break recursion (#579)
7bc65ab Update CI
fcc6102 Do not use nested dissection by default. (#550)
8534357 Update ci.yml: run CI and docs on v1.11
66d65fd Change default QR tolerance to match SPQR (#557)
8a48327 test: Don't use GPL module when Base.USE_GPL_LIBS=false (#535)
8dd8300 SparseMatrixCSC constructor with a Tuple of Integers (#523)
aa66624 doc: move solvers doc to `src\solvers.md` (#576)
8a85fbe Inline sparse-times-dense in-place multiplication
```

Co-authored-by: Dilum Aluthge <dilum@aluthge.com>
@ElOceanografo ElOceanografo mentioned this pull request Nov 16, 2020
Open
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Reviewers
No reviews
Assignees
No one assigned
Labels
None yet
Projects
None yet
Milestone
No milestone
Development

Successfully merging this pull request may close these issues.
2 participants
@stefan-k @JeffBezanson