Hello,
I have encountered a weird plotting issue recently using a recent mpl clone. See the linked pdfs for better demonstration of the issue:
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_newmpl.pdf
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_oldmpl.pdf
newmpl file is created using the latest master branch (cloned and setup today)
oldmpl is created using mpl v1.1.0 (https://github.com/downloads/matplotlib/matplotlib/matplotlib-1.1.0.tar.gz)
Scroll down to page 4 in each file and you will see the wrong plotted behavior of alwp_lcl (black line) variable on newmpl file comparing to the correct version that is shown on oldmpl.
I was trying to figure out a way to correct this and I raised y-axis max to 2400 and then the line looks fine. However I have other data that show similar wrong behaviors, so I decided to try earlier mpl versions since I know that those plots were looking correct earlier (at least a few months back). Trying v1.1.x branch gave me the same results. Note that these data contain “nans”. Are nan handling changed in recent mpl code or the way the data is plotted out of margins? I can’t reproduce this with synthetic data.
Any ideas as to what could be going wrong here?
Thanks.
···
–
Gökhan
I do recall some changes were made for v1.1.x with regards to autoscaling. Another change was also made with respect to Bbox clipping. I can’t recall enough details to know if they are a part of this issue.
Ben Root
···
On Tuesday, May 15, 2012, Gökhan Sever wrote:
Hello,
I have encountered a weird plotting issue recently using a recent mpl clone. See the linked pdfs for better demonstration of the issue:
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_newmpl.pdf
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_oldmpl.pdf
newmpl file is created using the latest master branch (cloned and setup today)
oldmpl is created using mpl v1.1.0 (https://github.com/downloads/matplotlib/matplotlib/matplotlib-1.1.0.tar.gz)
Scroll down to page 4 in each file and you will see the wrong plotted behavior of alwp_lcl (black line) variable on newmpl file comparing to the correct version that is shown on oldmpl.
I was trying to figure out a way to correct this and I raised y-axis max to 2400 and then the line looks fine. However I have other data that show similar wrong behaviors, so I decided to try earlier mpl versions since I know that those plots were looking correct earlier (at least a few months back). Trying v1.1.x branch gave me the same results. Note that these data contain “nans”. Are nan handling changed in recent mpl code or the way the data is plotted out of margins? I can’t reproduce this with synthetic data.
Any ideas as to what could be going wrong here?
Thanks.
–
Gökhan
There have been changes to that code lately. Is there any way you
can pack up a small script and data to reproduce this? Then I can
poke at it and see what I find (it would also make a good regression
test).
Mike
···
On 05/15/2012 07:57 PM, Gökhan Sever wrote:
Hello,
I have encountered a weird plotting issue recently using a
recent mpl clone. See the linked pdfs for better demonstration
of the issue:
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_newmpl.pdf
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_oldmpl.pdf
newmpl file is created using the latest master branch
(cloned and setup today)
oldmpl is created using mpl v1.1.0 (https://github.com/downloads/matplotlib/matplotlib/matplotlib-1.1.0.tar.gz)
Scroll down to page 4 in each file and you will see the
wrong plotted behavior of alwp_lcl (black line) variable on
newmpl file comparing to the correct version that is shown
on oldmpl.
I was trying to figure out a way to correct this and I
raised y-axis max to 2400 and then the line looks fine.
However I have other data that show similar wrong behaviors,
so I decided to try earlier mpl versions since I know that
those plots were looking correct earlier (at least a few
months back). Trying v1.1.x branch gave me the same results.
Note that these data contain “nans”. Are nan handling
changed in recent mpl code or the way the data is plotted
out of margins? I can’t reproduce this with synthetic data.
Hi Mike,
Could you inform me about your progress? I can test your sample script. I was thinking to test from v1.1.x branch downwards to spot the source of the issue, but I just don’t know how to clone at particular commit in git.
Thank you.
···
On Wed, May 16, 2012 at 6:51 AM, Michael Droettboom <mdroe@…86…> wrote:
Nevermind -- I've got something to reproduce this and am looking
into it now.
Mike
On 05/16/2012 08:13 AM, Michael Droettboom wrote:
On 05/15/2012 07:57 PM, Gökhan Sever wrote:
Hello,
I have encountered a weird plotting issue recently using a
recent mpl clone. See the linked pdfs for better demonstration
of the issue:
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_newmpl.pdf
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_oldmpl.pdf
newmpl file is created using the latest master branch
(cloned and setup today)
oldmpl is created using mpl v1.1.0 (https://github.com/downloads/matplotlib/matplotlib/matplotlib-1.1.0.tar.gz)
Scroll down to page 4 in each file and you will see the
wrong plotted behavior of alwp_lcl (black line) variable
on newmpl file comparing to the correct version that is
shown on oldmpl.
I was trying to figure out a way to correct this and I
raised y-axis max to 2400 and then the line looks fine.
However I have other data that show similar
wrong behaviors, so I decided to try earlier mpl versions
since I know that those plots were looking correct earlier
(at least a few months back). Trying v1.1.x branch gave me
the same results. Note that these data contain “nans”. Are
nan handling changed in recent mpl code or the way the
data is plotted out of margins? I can’t reproduce this
with synthetic data.
There have been changes to that code lately. Is there any way you
can pack up a small script and data to reproduce this? Then I can
poke at it and see what I find (it would also make a good
regression test).
Mike
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–
Gökhan
I have a proposed solution here:
[https://github.com/matplotlib/matplotlib/pull/872](https://github.com/matplotlib/matplotlib/pull/872)
Git bisect found that the first commit where this happens was here:
https://github.com/matplotlib/matplotlib/commit/4cd75cdf
This is the script I used to reproduce -- I assume it's the same
thing you’re seeing:
from matplotlib import pyplot as plt
import numpy as np
x = np.linspace(0, 3.14 * 2, 3000)
y = np.sin(x)
x[::100] = np.nan
plt.plot(x, y)
plt.ylim(-0.25, 0.25)
plt.show()
Mike
···
On 05/16/2012 10:44 AM, Gökhan Sever wrote:
Hi Mike,
Could you inform me about your progress? I can test your
sample script. I was thinking to test from v1.1.x branch
downwards to spot the source of the issue, but I just don’t know
how to clone at particular commit in git.
Thank you.
On Wed, May 16, 2012 at 6:51 AM, > Michael Droettboom <mdroe@...86...> wrote:
Nevermind -- I've got
something to reproduce this and am looking into it now.
Mike
On 05/16/2012 08:13 AM, Michael Droettboom wrote:
On 05/15/2012 07:57 PM, Gökhan Sever > > > wrote:
Hello,
I have encountered a weird plotting issue
recently using a recent mpl clone. See the
linked pdfs for better demonstration of the
issue:
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_newmpl.pdf
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_oldmpl.pdf
newmpl file is created using the latest
master branch (cloned and setup today)
oldmpl is created using mpl v1.1.0 (https://github.com/downloads/matplotlib/matplotlib/matplotlib-1.1.0.tar.gz)
Scroll down to page 4 in each file and
you will see the wrong plotted behavior of
alwp_lcl (black line) variable on newmpl
file comparing to the correct version that
is shown on oldmpl.
I was trying to figure out a way to
correct this and I raised y-axis max to 2400
and then the line looks fine. However I have
other data that show similar
wrong behaviors, so I decided to try earlier
mpl versions since I know that those plots
were looking correct earlier (at least a few
months back). Trying v1.1.x branch gave me
the same results. Note that these data
contain “nans”. Are nan handling changed in
recent mpl code or the way the data is
plotted out of margins? I can’t reproduce
this with synthetic data.
There have been changes to that code lately. Is
there any way you can pack up a small script and
data to reproduce this? Then I can poke at it and
see what I find (it would also make a good
regression test).
Mike
------------------------------------------------------------------------------
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will include endpoint security, mobile security and the
latest in malware
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–
Gökhan
Could you inform me about your progress? I can test your
sample script. I was thinking to test from v1.1.x branch
downwards to spot the source of the issue, but I just don’t know
how to clone at particular commit in git.
Also, to answer this question directly -- "git bisect" is a great
way to find this:
http://git-scm.com/book/en/Git-Tools-Debugging-with-Git#Binary-Search
Cheers,
Mike
···
On 05/16/2012 10:44 AM, Gökhan Sever wrote:
Thank you.
On Wed, May 16, 2012 at 6:51 AM, > Michael Droettboom <mdroe@...86...> wrote:
Nevermind -- I've got
something to reproduce this and am looking into it now.
Mike
On 05/16/2012 08:13 AM, Michael Droettboom wrote:
On 05/15/2012 07:57 PM, Gökhan Sever > > > wrote:
Hello,
I have encountered a weird plotting issue
recently using a recent mpl clone. See the
linked pdfs for better demonstration of the
issue:
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_newmpl.pdf
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_oldmpl.pdf
newmpl file is created using the latest
master branch (cloned and setup today)
oldmpl is created using mpl v1.1.0 (https://github.com/downloads/matplotlib/matplotlib/matplotlib-1.1.0.tar.gz)
Scroll down to page 4 in each file and
you will see the wrong plotted behavior of
alwp_lcl (black line) variable on newmpl
file comparing to the correct version that
is shown on oldmpl.
I was trying to figure out a way to
correct this and I raised y-axis max to 2400
and then the line looks fine. However I have
other data that show similar
wrong behaviors, so I decided to try earlier
mpl versions since I know that those plots
were looking correct earlier (at least a few
months back). Trying v1.1.x branch gave me
the same results. Note that these data
contain “nans”. Are nan handling changed in
recent mpl code or the way the data is
plotted out of margins? I can’t reproduce
this with synthetic data.
There have been changes to that code lately. Is
there any way you can pack up a small script and
data to reproduce this? Then I can poke at it and
see what I find (it would also make a good
regression test).
Mike
------------------------------------------------------------------------------
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Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. [http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/](http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/)
_______________________________________________
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will include endpoint security, mobile security and the
latest in malware
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–
Gökhan
Hmm, how can I test this change the easiest way?
Clone the master and replace with your changes? or can I directly clone your experimental branch?
···
On Wed, May 16, 2012 at 8:52 AM, Michael Droettboom <mdroe@…86…> wrote:
I have a proposed solution here:
[https://github.com/matplotlib/matplotlib/pull/872](https://github.com/matplotlib/matplotlib/pull/872)
Git bisect found that the first commit where this happens was here:
[https://github.com/matplotlib/matplotlib/commit/4cd75cdf](https://github.com/matplotlib/matplotlib/commit/4cd75cdf)
This is the script I used to reproduce -- I assume it's the same
thing you’re seeing:
from matplotlib import pyplot as plt
import numpy as np
x = np.linspace(0, 3.14 * 2, 3000)
y = np.sin(x)
x[::100] = np.nan
plt.plot(x, y)
plt.ylim(-0.25, 0.25)
plt.show()
Mike
On 05/16/2012 10:44 AM, Gökhan Sever wrote:
Hi Mike,
Could you inform me about your progress? I can test your
sample script. I was thinking to test from v1.1.x branch
downwards to spot the source of the issue, but I just don’t know
how to clone at particular commit in git.
Thank you.
On Wed, May 16, 2012 at 6:51 AM, > > Michael Droettboom <mdroe@...86...> wrote:
Nevermind -- I've got
something to reproduce this and am looking into it now.
Mike
On 05/16/2012 08:13 AM, Michael Droettboom wrote:
On 05/15/2012 07:57 PM, Gökhan Sever > > > > wrote:
Hello,
I have encountered a weird plotting issue
recently using a recent mpl clone. See the
linked pdfs for better demonstration of the
issue:
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_newmpl.pdf
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_oldmpl.pdf
newmpl file is created using the latest
master branch (cloned and setup today)
oldmpl is created using mpl v1.1.0 (https://github.com/downloads/matplotlib/matplotlib/matplotlib-1.1.0.tar.gz)
Scroll down to page 4 in each file and
you will see the wrong plotted behavior of
alwp_lcl (black line) variable on newmpl
file comparing to the correct version that
is shown on oldmpl.
I was trying to figure out a way to
correct this and I raised y-axis max to 2400
and then the line looks fine. However I have
other data that show similar
wrong behaviors, so I decided to try earlier
mpl versions since I know that those plots
were looking correct earlier (at least a few
months back). Trying v1.1.x branch gave me
the same results. Note that these data
contain “nans”. Are nan handling changed in
recent mpl code or the way the data is
plotted out of margins? I can’t reproduce
this with synthetic data.
There have been changes to that code lately. Is
there any way you can pack up a small script and
data to reproduce this? Then I can poke at it and
see what I find (it would also make a good
regression test).
Mike
------------------------------------------------------------------------------
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latest in malware
threats. [http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/](http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/)
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–
Gökhan
–
Gökhan
Bisecting is definitely a better idea than my one-by-one setup iteration 
Thanks for sharing the tip.
···
On Wed, May 16, 2012 at 8:54 AM, Michael Droettboom <mdroe@…120…86…> wrote:
On 05/16/2012 10:44 AM, Gökhan Sever wrote:
Could you inform me about your progress? I can test your
sample script. I was thinking to test from v1.1.x branch
downwards to spot the source of the issue, but I just don’t know
how to clone at particular commit in git.
Also, to answer this question directly -- "git bisect" is a great
way to find this:
[http://git-scm.com/book/en/Git-Tools-Debugging-with-Git#Binary-Search](http://git-scm.com/book/en/Git-Tools-Debugging-with-Git#Binary-Search)
Cheers,
Mike
Thank you.
On Wed, May 16, 2012 at 6:51 AM, > > Michael Droettboom <mdroe@...86...> wrote:
Nevermind -- I've got
something to reproduce this and am looking into it now.
Mike
On 05/16/2012 08:13 AM, Michael Droettboom wrote:
On 05/15/2012 07:57 PM, Gökhan Sever > > > > wrote:
Hello,
I have encountered a weird plotting issue
recently using a recent mpl clone. See the
linked pdfs for better demonstration of the
issue:
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_newmpl.pdf
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_oldmpl.pdf
newmpl file is created using the latest
master branch (cloned and setup today)
oldmpl is created using mpl v1.1.0 (https://github.com/downloads/matplotlib/matplotlib/matplotlib-1.1.0.tar.gz)
Scroll down to page 4 in each file and
you will see the wrong plotted behavior of
alwp_lcl (black line) variable on newmpl
file comparing to the correct version that
is shown on oldmpl.
I was trying to figure out a way to
correct this and I raised y-axis max to 2400
and then the line looks fine. However I have
other data that show similar
wrong behaviors, so I decided to try earlier
mpl versions since I know that those plots
were looking correct earlier (at least a few
months back). Trying v1.1.x branch gave me
the same results. Note that these data
contain “nans”. Are nan handling changed in
recent mpl code or the way the data is
plotted out of margins? I can’t reproduce
this with synthetic data.
There have been changes to that code lately. Is
there any way you can pack up a small script and
data to reproduce this? Then I can poke at it and
see what I find (it would also make a good
regression test).
Mike
------------------------------------------------------------------------------
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latest in malware
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–
Gökhan
–
Gökhan
You can either clone my fork and then checkout the branch with the
change:
git checkout clipping-bug
Or, in an existing clone of the main repository, add my fork as a
remote
git remote add mdboom git fetch mdboom
git checkout mdboom/clipping-bug
Or, since the diff is only a few lines in path_converters.h, you
could just apply it manually.
Be sure to remove your build directory before rebuilding: distutils
doesn’t pick up header file changes.
Mike
···
git://github.com/mdboom/matplotlib.git
On Wed, May 16, 2012 at 8:52 AM, Michael Droettboom <mdroe@…86…>
wrote:
I have a
proposed solution here:
[https://github.com/matplotlib/matplotlib/pull/872](https://github.com/matplotlib/matplotlib/pull/872)
Git bisect found that the first commit where this
happens was here:
[https://github.com/matplotlib/matplotlib/commit/4cd75cdf](https://github.com/matplotlib/matplotlib/commit/4cd75cdf)
This is the script I used to reproduce -- I assume
it’s the same thing you’re seeing:
from matplotlib import pyplot as plt
import numpy as np
x = np.linspace(0, 3.14 * 2, 3000)
y = np.sin(x)
x[::100] = np.nan
plt.plot(x, y)
plt.ylim(-0.25, 0.25)
plt.show()
Mike
On 05/16/2012 10:44 AM, Gökhan Sever wrote:
Hi Mike,
Could you inform me about your progress?
I can test your sample script. I was
thinking to test from v1.1.x branch
downwards to spot the source of the issue,
but I just don’t know how to clone at
particular commit in git.
Thank you.
On Wed, May 16,
2012 at 6:51 AM, Michael Droettboom <mdroe@…86…>
wrote:
Nevermind -- I've got something to
reproduce this and am looking into it
now.
Mike
On 05/16/2012 08:13 AM, Michael
Droettboom wrote:
On 05/15/2012 07:57 PM,
Gökhan Sever wrote:
Hello,
I have encountered a
weird plotting issue
recently using a recent mpl
clone. See the linked pdfs
for better demonstration of
the issue:
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_newmpl.pdf
http://atmos.uwyo.edu/~gsever/data/vocals_RF04_NU05_oldmpl.pdf
newmpl file is
created using the latest
master branch (cloned
and setup today)
oldmpl is created
using mpl v1.1.0 (https://github.com/downloads/matplotlib/matplotlib/matplotlib-1.1.0.tar.gz)
Scroll down to page 4
in each file and you
will see the wrong
plotted behavior of
alwp_lcl (black line)
variable on newmpl file
comparing to the correct
version that is shown on
oldmpl.
I was trying to
figure out a way to
correct this and I
raised y-axis max to
2400 and then the line
looks fine. However I
have other data that
show similar
wrong behaviors, so I
decided to try earlier
mpl versions since I
know that those plots
were looking correct
earlier (at least a few
months back). Trying
v1.1.x branch gave me
the same results. Note
that these data contain
“nans”. Are nan handling
changed in recent mpl
code or the way the data
is plotted out of
margins? I can’t
reproduce this
with synthetic data.
There have been changes to that
code lately. Is there any way
you can pack up a small script
and data to reproduce this?
Then I can poke at it and see
what I find (it would also make
a good regression test).
Mike
------------------------------------------------------------------------------
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Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. [http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/](http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/)
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Exclusive live event will cover all the
ways today’s security and
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Gökhan
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Gökhan
Here are my steps following your 2nd suggestion:
1-) Cloned the master:
git clone git://github.com/matplotlib/matplotlib.git
2-) go into matplotlib dir and then execute:
sudo python setupegg.py develop
Tested my existing code and verified that the plotting error I reported in the first message was still there.
3-) in the matplotlib dir I executed the 3 commands you typed to get your fork
4-) Removed the build dir in matplotlib folder then re-executed setupegg.py script
5-) Testing with your change my plot looks fine now, lines are drawn correctly.
Thanks for easy to follow instructions and quick response.
···
On Wed, May 16, 2012 at 9:30 AM, Michael Droettboom <mdroe@…86…> wrote:
Or, in an existing clone of the main repository, add my fork as a
remote
git remote add mdboom git://github.com/mdboom/matplotlib.git
git fetch mdboom
git checkout mdboom/clipping-bug