doc: shorter references

pygsp/__init__.py

@@ -4,16 +4,16 @@
 The :mod:`pygsp` package is mainly organized around the following three
 modules:
 
-* :mod:`pygsp.graphs` to create and manipulate various kinds of graphs,
-* :mod:`pygsp.filters` to create and manipulate various graph filters,
-* :mod:`pygsp.operators` to apply various operators to graph signals.
+* :mod:`.graphs` to create and manipulate various kinds of graphs,
+* :mod:`.filters` to create and manipulate various graph filters,
+* :mod:`.operators` to apply various operators to graph signals.
 
 Moreover, the following modules provide additional functionality:
 
-* :mod:`pygsp.plotting` to plot,
-* :mod:`pygsp.features` to compute features on graphs,
-* :mod:`pygsp.optimization` to help solving convex optimization problems,
-* :mod:`pygsp.utils` for various utilities.
+* :mod:`.plotting` to plot,
+* :mod:`.features` to compute features on graphs,
+* :mod:`.optimization` to help solving convex optimization problems,
+* :mod:`.utils` for various utilities.
 
 """
 

pygsp/filters/__init__.py

@@ -8,32 +8,32 @@
 filters, usually centered around different frequencies, applied to a single
 graph.
 
-See the :class:`pygsp.filters.Filter` base class for the documentation of the
+See the :class:`Filter` base class for the documentation of the
 interface to the filter object. Derived classes implement various common graph
 filters.
 
 **Filterbank of N filters**
 
-* :class:`pygsp.filters.Abspline`
-* :class:`pygsp.filters.Gabor`
-* :class:`pygsp.filters.HalfCosine`
-* :class:`pygsp.filters.Itersine`
-* :class:`pygsp.filters.MexicanHat`
-* :class:`pygsp.filters.Meyer`
-* :class:`pygsp.filters.SimpleTf`
-* :class:`pygsp.filters.WarpedTranslates`
+* :class:`Abspline`
+* :class:`Gabor`
+* :class:`HalfCosine`
+* :class:`Itersine`
+* :class:`MexicanHat`
+* :class:`Meyer`
+* :class:`SimpleTf`
+* :class:`WarpedTranslates`
 
 **Filterbank of 2 filters: low pass and high pass**
 
-* :class:`pygsp.filters.Regular`
-* :class:`pygsp.filters.Held`
-* :class:`pygsp.filters.Simoncelli`
-* :class:`pygsp.filters.Papadakis`
+* :class:`Regular`
+* :class:`Held`
+* :class:`Simoncelli`
+* :class:`Papadakis`
 
 **Low pass filter**
 
-* :class:`pygsp.filters.Heat`
-* :class:`pygsp.filters.Expwin`
+* :class:`Heat`
+* :class:`Expwin`
 
 Moreover, two approximation methods are provided for fast filtering. The
 computational complexity of filtering with those approximations is linear with
@@ -43,15 +43,15 @@
 
 **Chebyshev polynomials**
 
-* :class:`pygsp.filters.compute_cheby_coeff`
-* :class:`pygsp.filters.compute_jackson_cheby_coeff`
-* :class:`pygsp.filters.cheby_op`
-* :class:`pygsp.filters.cheby_rect`
+* :func:`compute_cheby_coeff`
+* :func:`compute_jackson_cheby_coeff`
+* :func:`cheby_op`
+* :func:`cheby_rect`
 
 **Lanczos algorithm**
 
-* :class:`pygsp.filters.lanczos`
-* :class:`pygsp.filters.lanczos_op`
+* :func:`lanczos`
+* :func:`lanczos_op`
 
 """
 

pygsp/graphs/__init__.py

@@ -5,40 +5,40 @@
 object is either constructed from an adjacency matrix, or by instantiating one
 of the built-in graph models.
 
-The :class:`pygsp.graphs.Graph` base class allows to construct a graph object
-from any adjacency matrix and provides a common interface to that object.
+The :class:`Graph` base class allows to construct a graph object from any
+adjacency matrix and provides a common interface to that object.
 
 Derived classes implement various graph models.
 
-* :class:`pygsp.graphs.Airfoil`
-* :class:`pygsp.graphs.BarabasiAlbert`
-* :class:`pygsp.graphs.Comet`
-* :class:`pygsp.graphs.Community`
-* :class:`pygsp.graphs.DavidSensorNet`
-* :class:`pygsp.graphs.ErdosRenyi`
-* :class:`pygsp.graphs.FullConnected`
-* :class:`pygsp.graphs.Grid2d`
-* :class:`pygsp.graphs.Logo`
-* :class:`pygsp.graphs.LowStretchTree`
-* :class:`pygsp.graphs.Minnesota`
-* :class:`pygsp.graphs.Path`
-* :class:`pygsp.graphs.RandomRegular`
-* :class:`pygsp.graphs.RandomRing`
-* :class:`pygsp.graphs.Ring`
-* :class:`pygsp.graphs.Sensor`
-* :class:`pygsp.graphs.StochasticBlockModel`
-* :class:`pygsp.graphs.SwissRoll`
-* :class:`pygsp.graphs.Torus`
+* :class:`Airfoil`
+* :class:`BarabasiAlbert`
+* :class:`Comet`
+* :class:`Community`
+* :class:`DavidSensorNet`
+* :class:`ErdosRenyi`
+* :class:`FullConnected`
+* :class:`Grid2d`
+* :class:`Logo`
+* :class:`LowStretchTree`
+* :class:`Minnesota`
+* :class:`Path`
+* :class:`RandomRegular`
+* :class:`RandomRing`
+* :class:`Ring`
+* :class:`Sensor`
+* :class:`StochasticBlockModel`
+* :class:`SwissRoll`
+* :class:`Torus`
 
-Derived classes from :class:`pygsp.graphs.NNGraph` implement nearest-neighbors
-graphs constructed from point clouds.
+Derived classes from :class:`NNGraph` implement nearest-neighbors graphs
+constructed from point clouds.
 
-* :class:`pygsp.graphs.Bunny`
-* :class:`pygsp.graphs.Cube`
-* :class:`pygsp.graphs.ImgPatches`
-* :class:`pygsp.graphs.Grid2dImgPatches`
-* :class:`pygsp.graphs.Sphere`
-* :class:`pygsp.graphs.TwoMoons`
+* :class:`Bunny`
+* :class:`Cube`
+* :class:`ImgPatches`
+* :class:`Grid2dImgPatches`
+* :class:`Sphere`
+* :class:`TwoMoons`
 
 """
 

pygsp/operators/__init__.py

@@ -5,33 +5,33 @@
 
 **Differential operators**
 
-* :func:`pygsp.operators.grad`: compute the gradient of a graph signal
-* :func:`pygsp.operators.div`: compute the divergence of a graph signal
+* :func:`grad`: compute the gradient of a graph signal
+* :func:`div`: compute the divergence of a graph signal
 
 **Transforms** (frequency and vertex-frequency)
 
-* :func:`pygsp.operators.gft`: graph Fourier transform (GFT)
-* :func:`pygsp.operators.igft`: inverse graph Fourier transform
-* :func:`pygsp.operators.gft_windowed`: windowed GFT
-* :func:`pygsp.operators.gft_windowed_gabor`: Gabor windowed GFT
-* :func:`pygsp.operators.gft_windowed_normalized`: normalized windowed GFT
+* :func:`gft`: graph Fourier transform (GFT)
+* :func:`igft`: inverse graph Fourier transform
+* :func:`gft_windowed`: windowed GFT
+* :func:`gft_windowed_gabor`: Gabor windowed GFT
+* :func:`gft_windowed_normalized`: normalized windowed GFT
 
 **Localization**
 
-* :func:`pygsp.operators.localize`: localize a kernel
-* :func:`pygsp.operators.modulate`: generalized modulation operator
-* :func:`pygsp.operators.translate`: generalized translation operator
+* :func:`localize`: localize a kernel
+* :func:`modulate`: generalized modulation operator
+* :func:`translate`: generalized translation operator
 
 **Reduction** Functionalities for the reduction of graphs' vertex set while keeping the graph structure.
 
-* :func:`pygsp.operators.tree_multiresolution`: compute a multiresolution of trees
-* :func:`pygsp.operators.graph_multiresolution`: compute a pyramid of graphs
-* :func:`pygsp.operators.kron_reduction`: compute the Kron reduction
-* :func:`pygsp.operators.pyramid_analysis`: analysis operator for graph pyramid
-* :func:`pygsp.operators.pyramid_synthesis`: synthesis operator for graph pyramid
-* :func:`pygsp.operators.pyramid_cell2coeff`: keep only the necessary coefficients
-* :func:`pygsp.operators.interpolate`: interpolate a signal
-* :func:`pygsp.operators.graph_sparsify`: sparsify a graph
+* :func:`tree_multiresolution`: compute a multiresolution of trees
+* :func:`graph_multiresolution`: compute a pyramid of graphs
+* :func:`kron_reduction`: compute the Kron reduction
+* :func:`pyramid_analysis`: analysis operator for graph pyramid
+* :func:`pyramid_synthesis`: synthesis operator for graph pyramid
+* :func:`pyramid_cell2coeff`: keep only the necessary coefficients
+* :func:`interpolate`: interpolate a signal
+* :func:`graph_sparsify`: sparsify a graph
 
 """