tweaks

README.md

@@ -4,7 +4,7 @@ NIFTy - Numerical Information Field Theory
 [![coverage report](https://gitlab.mpcdf.mpg.de/ift/NIFTy/badges/NIFTy_4/coverage.svg)](https://gitlab.mpcdf.mpg.de/ift/NIFTy/commits/NIFTy_4)
 
 **NIFTy** project homepage:
-[https://www.mpa-garching.mpg.de/ift/nifty/](https://www.mpa-garching.mpg.de/ift/nifty/)
+[http://ift.pages.mpcdf.de/NIFTy](http://ift.pages.mpcdf.de/NIFTy)
 
 Summary
 -------
@@ -31,33 +31,6 @@ point sets, *n*-dimensional regular grids, spherical spaces, their
 harmonic counterparts, and product spaces constructed as combinations of
 those.
 
-### Class & Feature Overview
-
-The NIFTy library features three main classes: **Space**s that represent
-certain grids, **Field**s that are defined on spaces, and **LinearOperator**s
-that apply to fields.
-
--   [Spaces](https://www.mpa-garching.mpg.de/ift/nifty/space.html)
-    -   `RGSpace` - *n*-dimensional regular Euclidean grid
-    -   `LMSpace` - spherical harmonics
-    -   `GLSpace` - Gauss-Legendre grid on the 2-sphere
-    -   `HPSpace` - [HEALPix](https://sourceforge.net/projects/healpix/)
-        grid on the 2-sphere
--   [Fields](https://www.mpa-garching.mpg.de/ift/nifty/field.html)
-    -   `Field` - generic class for (discretized) fields
-
-<!-- -->
-
-    Field.conjugate     Field.dim          Field.norm
-    Field.vdot          Field.weight
-
--   [Operators](https://www.mpa-garching.mpg.de/ift/nifty/operator.html)
-    -   `DiagonalOperator` - purely diagonal matrices in a specified
-        basis
-    -   `FFTOperator` - conversion between spaces and their harmonic
-                        counterparts
-    -   (and more)
--   (and more)
 
 Installation
 ------------
@@ -137,7 +110,7 @@ following command in the repository root:
 ### First Steps
 
 For a quick start, you can browse through the [informal
-introduction](https://www.mpa-garching.mpg.de/ift/nifty/start.html) or
+introduction](http://ift.pages.mpcdf.de/NIFTy/start.html) or
 dive into NIFTy by running one of the demonstrations, e.g.:
 
     python demos/wiener_filter_via_curvature.py

docs/source/conf.py

@@ -116,7 +116,7 @@ exclude_patterns = []
 
 # If true, the current module name will be prepended to all description
 # unit titles (such as .. function::).
-#add_module_names = True
+add_module_names = False
 
 # If true, sectionauthor and moduleauthor directives will be shown in the
 # output. They are ignored by default.

docs/source/index.rst

@@ -28,6 +28,7 @@ Contents
 
    ift
    start
+   installation
    code
 
 Indices and tables

docs/source/start.rst

@@ -16,7 +16,7 @@ a continuous signal field is to be recovered.
 It is achieved by means of an object-oriented infrastructure that comprises, among others, abstract classes for :ref:`Domains <domains>`, :ref:`Fields <fields>`, and :ref:`Operators <operators>`.
 All those are covered in this tutorial.
 
-You should be able to import NIFTy4 like this after a successful `installation <install.html>`_.
+You should be able to import NIFTy4 like this after a successful `installation <installation.html>`_.
 
 >>> import nifty4 as ift
 
@@ -31,7 +31,7 @@ From such a perspective,
 - IFT problems largely consist of *minimization* problems involving a large number of equations.
 - The equations are built mostly from the application of *linear operators*, but there may also be nonlinear functions involved.
 - The unknowns in the equations represent either continuous physical *fields*, or they are simply individual measured *data* points.
-- The locations and volume elements attached to discretized *field* values are supplied by *domain* objects. There are many variants of such discretized *domain*s supported by NIFTy4, including Cartesian and spherical geometries and their harmonic counterparts. *Fields* can live on arbitrary products of such *domains*.
+- The locations and volume elements attached to discretized *field* values are supplied by *domain* objects. There are many variants of such discretized *domains* supported by NIFTy4, including Cartesian and spherical geometries and their harmonic counterparts. *Fields* can live on arbitrary products of such *domains*.
 
 In the following sections, the concepts briefly presented here will be discussed in more detail; this is done in reversed order of their introduction, to avoid forward references.
 
@@ -49,6 +49,7 @@ A domain must be able to answer the following queries:
 - the shape of the array that is supposed to hold them
 - equality/inequality to another :py:class:`Domain` instance
 
+
 Unstructured domains
 ....................
 
@@ -76,8 +77,9 @@ Examples for structured domains are
 
 Among these, :py:class:`RGSpace` can be harmonic or not (depending on constructor arguments), :py:class:`GLSpace` is a pure position domain (i.e. nonharmonic), and :py:class:`LMSpace` is always harmonic.
 
-Full domains
-............
+
+Combinations of domains
+.......................
 
 A field can live on a single domain, but it can also live on a product of domains (or no domain at all, in which case it is a scalar).
 The tuple of domain on which a field lives is described by the :py:class:`DomainTuple` class.