Looks good. Does matplotlib still pass all regression tests with this change?
(See here for information on running the regression tests: http://matplotlib.sourceforge.net/devel/coding_guide.html?highlight=nosetests#testing). Cheers, Mike On 07/06/2011 08:33 AM, Martin Teichmann wrote: > Dear list, > > I was just trying to shear an image to be plotted with > matplotlib (to get some snazzy 3D effect) and realized > that it's apparently not possible. Investigating further, > I realized that the underlying agg library indeed supports > shearing, as it simply uses an affine matrix for its > transforms (very much like the rest of matplotlib), > but it does not export that feature to matplotlib. > > So, I just quickly added some code to actually > access the transformation matrix in the C++ code, > so that one can use it from within python. The next > step would be to hook that up to the usual code used > in matplotlib. > > A patch is attached at the end of this post. > > Greetings > > Martin > > --------------- patch follows ----------------------- > > commit b7d0d23d90460ee790f1e94f387070a69be661c8 > Author: Martin Teichmann<martin@renoir.(none)> > Date: Wed Jul 6 14:04:44 2011 +0200 > > Make affine transformations work for images > > The current code only supports scaling and maybe rotation of > images, but not all affine transformations, although it is > already prepared to do so. > > This patch adds a method set_matrix to the C++ image handling code, > so that one can set (and thus perform) arbitrary affine transformations. > > It also fixes a little bug which introduced weird side effects > if images were resized more than once. > > diff --git a/src/_image.cpp b/src/_image.cpp > index 3278b6c..7d40664 100644 > --- a/src/_image.cpp > +++ b/src/_image.cpp > @@ -92,7 +92,6 @@ Image::apply_rotation(const Py::Tuple& args) > > agg::trans_affine M = agg::trans_affine_rotation(r * agg::pi / 180.0); > srcMatrix *= M; > - imageMatrix *= M; > return Py::Object(); > } > > @@ -156,7 +155,6 @@ Image::apply_scaling(const Py::Tuple& args) > //printf("applying scaling %1.2f, %1.2f\n", sx, sy); > agg::trans_affine M = agg::trans_affine_scaling(sx, sy); > srcMatrix *= M; > - imageMatrix *= M; > > return Py::Object(); > } > @@ -179,7 +177,6 @@ Image::apply_translation(const Py::Tuple& args) > //printf("applying translation %1.2f, %1.2f\n", tx, ty); > agg::trans_affine M = agg::trans_affine_translation(tx, ty); > srcMatrix *= M; > - imageMatrix *= M; > > return Py::Object(); > } > @@ -285,7 +282,6 @@ Image::reset_matrix(const Py::Tuple& args) > > args.verify_length(0); > srcMatrix.reset(); > - imageMatrix.reset(); > > return Py::Object(); > } > @@ -316,6 +312,31 @@ Image::get_matrix(const Py::Tuple& args) > return ret; > } > > +char Image::set_matrix__doc__[] = > + "set_matrix(m11,m21,m12,m22,m13,m23)\n" > + "\n" > + "Set the affine transformation matrix\n" > + " /m11,m12,m13\\\n" > + " /m21,m22,m23|\n" > + " \\ 0 , 0 , 1 /" > + ; > + > +Py::Object > +Image::set_matrix(const Py::Tuple& args) > +{ > + _VERBOSE("Image::set_matrix"); > + > + args.verify_length(6); > + > + double m[6]; > + for (int i = 0;i< 6;i++) > + { > + m[i] = Py::Float(args[i]); > + } > + srcMatrix.load_from(m); > + return Py::Object(); > +} > + > char Image::resize__doc__[] = > "resize(width, height, norm=1, radius=4.0)\n" > "\n" > @@ -376,8 +397,7 @@ Image::resize(const Py::Tuple& args, const Py::Dict& > kwargs) > > ras.clip_box(0, 0, numcols, numrows); > > - //srcMatrix *= resizingMatrix; > - //imageMatrix *= resizingMatrix; > + imageMatrix = srcMatrix; > imageMatrix.invert(); > interpolator_type interpolator(imageMatrix); > > @@ -733,6 +753,7 @@ Image::init_type() > add_varargs_method("get_size_out",&Image::get_size_out, > Image::get_size_out__doc__); > add_varargs_method("reset_matrix",&Image::reset_matrix, > Image::reset_matrix__doc__); > add_varargs_method("get_matrix",&Image::get_matrix, > Image::get_matrix__doc__); > + add_varargs_method("set_matrix",&Image::set_matrix, > Image::set_matrix__doc__); > add_keyword_method("resize",&Image::resize, Image::resize__doc__); > add_varargs_method("set_interpolation", > &Image::set_interpolation, Image::set_interpolation__doc__); > add_varargs_method("set_resample",&Image::set_resample, > Image::set_resample__doc__); > diff --git a/src/_image.h b/src/_image.h > index 8a3be54..89a923c 100644 > --- a/src/_image.h > +++ b/src/_image.h > @@ -34,6 +34,7 @@ public: > Py::Object buffer_rgba(const Py::Tuple& args); > Py::Object reset_matrix(const Py::Tuple& args); > Py::Object get_matrix(const Py::Tuple& args); > + Py::Object set_matrix(const Py::Tuple& args); > Py::Object resize(const Py::Tuple& args, const Py::Dict& kwargs); > Py::Object get_aspect(const Py::Tuple& args); > Py::Object get_size(const Py::Tuple& args); > @@ -105,6 +106,7 @@ private: > static char buffer_rgba__doc__[]; > static char reset_matrix__doc__[]; > static char get_matrix__doc__[]; > + static char set_matrix__doc__[]; > static char resize__doc__[]; > static char get_aspect__doc__[]; > static char get_size__doc__[]; > > ------------------------------------------------------------------------------ > All of the data generated in your IT infrastructure is seriously valuable. > Why? It contains a definitive record of application performance, security > threats, fraudulent activity, and more. Splunk takes this data and makes > sense of it. IT sense. And common sense. > http://p.sf.net/sfu/splunk-d2d-c2 > _______________________________________________ > Matplotlib-devel mailing list > Matplotlib-devel@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel ------------------------------------------------------------------------------ All of the data generated in your IT infrastructure is seriously valuable. Why? It contains a definitive record of application performance, security threats, fraudulent activity, and more. Splunk takes this data and makes sense of it. IT sense. And common sense. http://p.sf.net/sfu/splunk-d2d-c2 _______________________________________________ Matplotlib-devel mailing list Matplotlib-devel@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
