matplotlib-users Mailing List for matplotlib

On 09/13/2011 06:36 AM, Leidner, Mark wrote:
>
> Dear Python/Matplotlib/Ogr Users:
>
> We are recent converts to Python, and are having trouble with some of
> its functionalities.
> We'd like to submit our case for your consideration in hopes to get some
> educated help on the subject.
>
> The problem:
> When trying to use contour collections generated by contourf, the
> resulting shapefile contains overly simplified contours which poorly
> approximate the underlying field.
>
> To reproduce the problem, we wrote a python script that specifies a 2-d
> analytical shape. This shape has small noise perturbations added, in
> order to simulate natural geophysical fields (wind speed, for example).
Your illustration seems horrendously complex. Can you distill it down 
to a simplest-possible case? Doing so might help you figure out where 
the problem is. I don't think it has anything to do with path 
simplification, because that occurs when the path is rendered. If I 
understand correctly, what mpl is plotting directly from your data is 
fine; you are running into surprises with the shapefile that you are 
generating from what mpl is using for its plotting. So, the problem 
would seem to be in the generation of the shapefile, not in mpl.
Eric
> .
> The shape is being sliced by contourf command, and the resulting
> collection is being plotted as a PDF file (PostScript) and converted to
> an output Shapefile using OGR module.
>
> We also wrote several functions, defined inside the script, that take
> care of unpacking and exporting the contour collections as polygon or
> multipolygon shapefile entities thru OGR shapefile methods.
>
> Two zoomed in views are attached (screenshot_* attachments): (1) a
> portion of the PDF figure, and (2) a visualization of the shapefile data
> for the same area. The PDF figure shows a contour line with fine scale
> structure (the fine structures are the noise we added) while a lack of
> fine structure is seen in the output shapefile. The PDF plot is what we
> expect. The output shapefile geometry is very different from what we
> would expect.
>
> We can't understand how a call to contourf can produce a plot that looks
> right AND shapefile data (taken from contourf's collections) that appear
> to grossly simplify the geometry. We expect that both the plot and the
> shapefile come from the same contourf function results, yet look totally
> different.
>
> We'd like to ask whether anyone else encountered limitations regarding
> the complexity of shapefiles written out by python?
> Is this a possible problem with matplotlib.pyplot.contourf.collections
> method?
>
> We would appreciate your help very much!
> Test script and the resulting shapefile data set are attached.
>
> Thank you!
>
> ------------------------------------------------------------------------
>
> ------------------------------------------------------------------------
>
> S. Mark Leidner
> Staff Scientist/Oklahoma Business Development
> Atmospheric and Environmental Research, Inc.
> 350 David L. Boren Blvd, Suite 1535
> Norman, OK 73072-7264 USA
> ph: +1 405 325-1137
> cell: +1 781 354-5969
>
>
> Sergey Vinogradov, Ph.D., Staff Scientist
> Atmospheric and Environmental Research, Inc.
> 131 Hartwell Ave., Lexington, MA 02421, USA
> Phone: 1-781-761-2256 se...@ae...
> Fax: 1-781-761-2299 http://www.aer.com
> Web page :: http://ocean.mit.edu/~svinogra
>
>
>
>
>
>
>
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On Tue, Sep 13, 2011 at 1:02 PM, Leidner, Mark <mle...@ae...> wrote:
> Ben,
>
> Good to hear from you.
>
> We are using matplotlib v1.0.1_5 on an install from Macports.
>
> Hearing that there is simplification logic is very intriguing.
>
> Mark
>
>
Try this and tell me if the results are better. Right before the line where
you call to_polygons(), add this line:
multipolygon.should_simplify = False
The simplification logic gets triggered automatically if the
rcParam['path.simplify'] is True and if there are more them 128 vertices and
those vertices are all simple LINETO segments. I think in your situation,
this is true. So, we can force a non-simplification directly like above, or
set your rcParams file with path.simplify to False (but this may make graph
rendering significantly slower and more resource intensive overall).
The path simplification logic is designed so that one does not see any
visual differences, however, there might need to be some additional logic
for those who are accessing the path directly.
I hope this helps!
Ben Root

Ben,
Good to hear from you.
We are using matplotlib v1.0.1_5 on an install from Macports.
Hearing that there is simplification logic is very intriguing.
Mark
On 09/13/11, Benjamin Root <ben...@ou...> wrote:
> On Tue, Sep 13, 2011 at 11:36 AM, Leidner, Mark <mle...@ae...> wrote:
> 
> > 
> > 
> > 
> > 
> > Dear Python/Matplotlib/Ogr Users:
> > 
> > We are recent converts to Python, and are having trouble with some of its functionalities.
> > We'd like to submit our case for your consideration in hopes to get some educated help on the subject.
> > 
> > 
> > 
> > The problem:
> > When trying to use contour collections generated by contourf, the resulting shapefile contains overly simplified contours which poorly approximate the underlying field.
> > 
> > To reproduce the problem, we wrote a python script that specifies a 2-d analytical shape. This shape has small noise perturbations added, in order to simulate natural geophysical fields (wind speed, for example).
> > 
> > 
> > .
> > The shape is being sliced by contourf command, and the resulting collection is being plotted as a PDF file (PostScript) and converted to an output Shapefile using OGR module.
> > 
> > 
> > We also wrote several functions, defined inside the script, that take care of unpacking and exporting the contour collections as polygon or multipolygon shapefile entities thru OGR shapefile methods.
> > 
> > 
> > 
> > Two zoomed in views are attached (screenshot_* attachments): (1) a portion of the PDF figure, and (2) a visualization of the shapefile data for the same area. The PDF figure shows a contour line with fine scale structure (the fine structures are the noise we added) while a lack of fine structure is seen in the output shapefile. The PDF plot is what we expect. The output shapefile geometry is very different from what we would expect.
> > 
> > 
> > 
> > 
> > We can't understand how a call to contourf can produce a plot that looks right AND shapefile data (taken from contourf's collections) that appear to grossly simplify the geometry. We expect that both the plot and the shapefile come from the same contourf function results, yet look totally different. 
> > 
> > 
> > 
> > We'd like to ask whether anyone else encountered limitations regarding the complexity of shapefiles written out by python?
> > Is this a possible problem with matplotlib.pyplot.contourf.collections method?
> > 
> > 
> > We would appreciate your help very much!
> > 
> > Test script and the resulting shapefile data set are attached.
> > 
> > Thank you!
> > 
> > 
> > 
> > 
> 
> I am not able to run the test case because I don't have osgeo (also note that Nio isn't used in the given example). However, I might have a guess as to what is going on. In mpl, there is path simplication logic to reduce complexity of the paths. There have been bugs in the past with this logic, and so it would be valuable to know what version of matplotlib you are using.
> 
> 
> 
> This simplification code is probably being activated within the call to to_polygons(). Which version of matplotlib are you using?
> 
> Ben Root
> 
> 
> 
> 
> 
> 

On Tue, Sep 13, 2011 at 11:36 AM, Leidner, Mark <mle...@ae...> wrote:
>
> Dear Python/Matplotlib/Ogr Users:
>
> We are recent converts to Python, and are having trouble with some of its
> functionalities.
> We'd like to submit our case for your consideration in hopes to get some
> educated help on the subject.
>
> The problem:
> When trying to use contour collections generated by contourf, the resulting
> shapefile contains overly simplified contours which poorly approximate the
> underlying field.
>
> To reproduce the problem, we wrote a python script that specifies a 2-d
> analytical shape. This shape has small noise perturbations added, in order
> to simulate natural geophysical fields (wind speed, for example).
> .
> The shape is being sliced by contourf command, and the resulting collection
> is being plotted as a PDF file (PostScript) and converted to an output
> Shapefile using OGR module.
>
> We also wrote several functions, defined inside the script, that take care
> of unpacking and exporting the contour collections as polygon or
> multipolygon shapefile entities thru OGR shapefile methods.
>
> Two zoomed in views are attached (screenshot_* attachments): (1) a portion
> of the PDF figure, and (2) a visualization of the shapefile data for the
> same area. The PDF figure shows a contour line with fine scale structure
> (the fine structures are the noise we added) while a lack of fine structure
> is seen in the output shapefile. The PDF plot is what we expect. The
> output shapefile geometry is very different from what we would expect.
>
> We can't understand how a call to contourf can produce a plot that looks
> right AND shapefile data (taken from contourf's collections) that appear to
> grossly simplify the geometry. We expect that both the plot and the
> shapefile come from the same contourf function results, yet look totally
> different.
>
> We'd like to ask whether anyone else encountered limitations regarding the
> complexity of shapefiles written out by python?
> Is this a possible problem with matplotlib.pyplot.contourf.collections
> method?
>
> We would appreciate your help very much!
> Test script and the resulting shapefile data set are attached.
>
> Thank you!
>
>
I am not able to run the test case because I don't have osgeo (also note
that Nio isn't used in the given example). However, I might have a guess as
to what is going on. In mpl, there is path simplication logic to reduce
complexity of the paths. There have been bugs in the past with this logic,
and so it would be valuable to know what version of matplotlib you are
using.
This simplification code is probably being activated within the call to
to_polygons(). Which version of matplotlib are you using?
Ben Root

Dear Python/Matplotlib/Ogr Users:
We are recent converts to Python, and are having trouble with some of its functionalities.
We'd like to submit our case for your consideration in hopes to get some educated help on the subject.
The problem:
When trying to use contour collections generated by contourf, the resulting shapefile contains overly simplified contours which poorly approximate the underlying field.
To reproduce the problem, we wrote a python script that specifies a 2-d analytical shape. This shape has small noise perturbations added, in order to simulate natural geophysical fields (wind speed, for example).
.
The shape is being sliced by contourf command, and the resulting collection is being plotted as a PDF file (PostScript) and converted to an output Shapefile using OGR module.
We also wrote several functions, defined inside the script, that take care of unpacking and exporting the contour collections as polygon or multipolygon shapefile entities thru OGR shapefile methods.
Two zoomed in views are attached (screenshot_* attachments): (1) a portion of the PDF figure, and (2) a visualization of the shapefile data for the same area. The PDF figure shows a contour line with fine scale structure (the fine structures are the noise we added) while a lack of fine structure is seen in the output shapefile. The PDF plot is what we expect. The output shapefile geometry is very different from what we would expect.
We can't understand how a call to contourf can produce a plot that looks right AND shapefile data (taken from contourf's collections) that appear to grossly simplify the geometry. We expect that both the plot and the shapefile come from the same contourf function results, yet look totally different. 
We'd like to ask whether anyone else encountered limitations regarding the complexity of shapefiles written out by python?
Is this a possible problem with matplotlib.pyplot.contourf.collections method?
We would appreciate your help very much!
Test script and the resulting shapefile data set are attached.
Thank you!
S. Mark Leidner
Staff Scientist/Oklahoma Business Development
Atmospheric and Environmental Research, Inc.
350 David L. Boren Blvd, Suite 1535
Norman, OK 73072-7264 USA
ph: +1 405 325-1137
cell: +1 781 354-5969
Sergey Vinogradov, Ph.D.,      Staff Scientist
Atmospheric and Environmental Research, Inc.
131 Hartwell Ave., Lexington, MA 02421, USA
Phone: 1-781-761-2256     se...@ae...
Fax:   1-781-761-2299    http://www.aer.com
Web page ::    http://ocean.mit.edu/~svinogra

Answering my own question... It's a question of order. I needed to
set_yscale('log') before calling clabel.
Jon
> Hi all,
> 
> I've run into a problem with a contour plot that has a
> logarithmic
> y-axis. The spacing around the inline contour label is too
> large,
> leading to a large segment of the contour being blocked
> out/erased. I
> tried making the plot with a linear axis and it didn't happen
> in that
> case, so I'm thinking that it has to do with the contour
> labeling
> routine not understanding logarithmic scaling. Attached is a
> plot
> demonstrating the problem. Is there a solution for this?
> 
> Jon Slavin

Hi all,
I've run into a problem with a contour plot that has a logarithmic
y-axis. The spacing around the inline contour label is too large,
leading to a large segment of the contour being blocked out/erased. I
tried making the plot with a linear axis and it didn't happen in that
case, so I'm thinking that it has to do with the contour labeling
routine not understanding logarithmic scaling. Attached is a plot
demonstrating the problem. Is there a solution for this?
Jon Slavin