Merge branch 'mr_corrections' into 'NIFTy_5'

Mr corrections

See merge request !285

README.md

@@ -4,7 +4,7 @@ NIFTy - Numerical Information Field Theory
 [![coverage report](https://gitlab.mpcdf.mpg.de/ift/NIFTy/badges/NIFTy_5/coverage.svg)](https://gitlab.mpcdf.mpg.de/ift/NIFTy/commits/NIFTy_5)
 
 **NIFTy** project homepage:
-[http://ift.pages.mpcdf.de/NIFTy](http://ift.pages.mpcdf.de/NIFTy)
+[http://ift.pages.mpcdf.de/nifty](http://ift.pages.mpcdf.de/nifty)
 
 Summary
 -------
@@ -116,7 +116,7 @@ following command in the repository root:
 ### First Steps
 
 For a quick start, you can browse through the [informal
-introduction](http://ift.pages.mpcdf.de/NIFTy/code.html) or
+introduction](http://ift.pages.mpcdf.de/nifty/code.html) or
 dive into NIFTy by running one of the demonstrations, e.g.:
 
     python3 demos/getting_started_1.py
@@ -130,7 +130,7 @@ phrase such as the following:
 > "Some of the results in this publication have been derived using the
 > NIFTy package [(https://gitlab.mpcdf.mpg.de/ift/NIFTy)](https://gitlab.mpcdf.mpg.de/ift/NIFTy)"
 
-and a citation to one of the [publications](http://ift.pages.mpcdf.de/NIFTy/citations.html).
+and a citation to one of the [publications](http://ift.pages.mpcdf.de/nifty/citations.html).
 
 
 ### Licensing terms

docs/source/ift.rst

@@ -4,7 +4,7 @@ IFT -- Information Field Theory
 Theoretical Background
 ----------------------
 
-`Information Field Theory <http://www.mpa-garching.mpg.de/ift/>`_ [1]_  (IFT) is information theory, the logic of reasoning under uncertainty, applied to fields.
+`Information Field Theory <https://www.mpa-garching.mpg.de/ift/>`_ [1]_  (IFT) is information theory, the logic of reasoning under uncertainty, applied to fields.
 A field can be any quantity defined over some space, e.g. the air temperature over Europe, the magnetic field strength in the Milky Way, or the matter density in the Universe.
 IFT describes how data and knowledge can be used to infer field properties.
 Mathematically it is a statistical field theory and exploits many of the tools developed for such.
@@ -21,15 +21,15 @@ NIFTy comes with reimplemented MAP and VI estimators.
 
 .. tip:: *In-a-nutshell introductions to information field theory* can be found in [2]_, [3]_, [4]_, and [5]_, with the latter probably being the most didactical.
 
-.. [1] T.A. Enßlin et al. (2009), "Information field theory for cosmological perturbation reconstruction and nonlinear signal analysis", PhysRevD.80.105005, 09/2009; `[arXiv:0806.3474] <http://www.arxiv.org/abs/0806.3474>`_
+.. [1] T.A. Enßlin et al. (2009), "Information field theory for cosmological perturbation reconstruction and nonlinear signal analysis", PhysRevD.80.105005, 09/2009; `[arXiv:0806.3474] <https://www.arxiv.org/abs/0806.3474>`_
 
-.. [2] T.A. Enßlin (2013), "Information field theory", proceedings of MaxEnt 2012 -- the 32nd International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering; AIP Conference Proceedings, Volume 1553, Issue 1, p.184; `[arXiv:1301.2556] <http://arxiv.org/abs/1301.2556>`_
+.. [2] T.A. Enßlin (2013), "Information field theory", proceedings of MaxEnt 2012 -- the 32nd International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering; AIP Conference Proceedings, Volume 1553, Issue 1, p.184; `[arXiv:1301.2556] <https://arxiv.org/abs/1301.2556>`_
 
-.. [3] T.A. Enßlin (2014), "Astrophysical data analysis with information field theory", AIP Conference Proceedings, Volume 1636, Issue 1, p.49; `[arXiv:1405.7701] <http://arxiv.org/abs/1405.7701>`_
+.. [3] T.A. Enßlin (2014), "Astrophysical data analysis with information field theory", AIP Conference Proceedings, Volume 1636, Issue 1, p.49; `[arXiv:1405.7701] <https://arxiv.org/abs/1405.7701>`_
 
 .. [4] Wikipedia contributors (2018), `"Information field theory" <https://en.wikipedia.org/w/index.php?title=Information_field_theory&oldid=876731720>`_, Wikipedia, The Free Encyclopedia.
 
-.. [5] T.A. Enßlin (2019), "Information theory for fields", accepted by Annalen der Physik; `[DOI] <https://doi.org/10.1002/andp.201800127>`_, `[arXiv:1804.03350] <http://arxiv.org/abs/1804.03350>`_
+.. [5] T.A. Enßlin (2019), "Information theory for fields", accepted by Annalen der Physik; `[DOI] <https://doi.org/10.1002/andp.201800127>`_, `[arXiv:1804.03350] <https://arxiv.org/abs/1804.03350>`_
 
 
 

docs/source/index.rst

@@ -27,7 +27,7 @@ Contents
 
    ift
    volume
-   Gallery <http://wwwmpa.mpa-garching.mpg.de/~ensslin/nifty-gallery/index.html>
+   Gallery <https://wwwmpa.mpa-garching.mpg.de/~ensslin/nifty-gallery/index.html>
    installation
    code
    citations

nifty5/domains/lm_space.py

@@ -96,7 +96,7 @@ class LMSpace(StructuredDomain):
     def _kernel(x, sigma):
         # cf. "All-sky convolution for polarimetry experiments"
         # by Challinor et al.
-        # http://arxiv.org/abs/astro-ph/0008228
+        # https://arxiv.org/abs/astro-ph/0008228
         from ..sugar import exp
         return exp((x+1.) * x * (-0.5*sigma*sigma))
 

nifty5/utilities.py

@@ -143,7 +143,7 @@ def memo(f):
 class _DocStringInheritor(type):
     """
     A variation on
-    http://groups.google.com/group/comp.lang.python/msg/26f7b4fcb4d66c95
+    https://groups.google.com/group/comp.lang.python/msg/26f7b4fcb4d66c95
     by Paul McGuire
     """
     def __new__(meta, name, bases, clsdict):