diff --git a/README.md b/README.md
index 9dafe3089779e04981fffa7d118dcc17a4623c26..5e4fed4ef44951659dbad55afaa1fd5413f96f29 100644
--- a/README.md
+++ b/README.md
@@ -4,7 +4,7 @@ NIFTy - Numerical Information Field Theory
[](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
diff --git a/docs/source/conf.py b/docs/source/conf.py
index 694a039241724379947aa62126f924f03ae7d596..440e025d3eff4653db8a7bdc4c75fdbe862657aa 100644
--- a/docs/source/conf.py
+++ b/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.
diff --git a/docs/source/index.rst b/docs/source/index.rst
index 4ee1b28b95e0f171f56ac7766ce4bb240ce744ec..29b2810881d0c95497c23b93f596789803bba0db 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -28,6 +28,7 @@ Contents
ift
start
+ installation
code
Indices and tables
diff --git a/docs/source/start.rst b/docs/source/start.rst
index d6a40344d8111ebd9e4c2d858b4f7df4b2f72657..8a866939de9c2a72a331a9e5db15a7da0124f016 100644
--- a/docs/source/start.rst
+++ b/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.