Removed joblib.cached-sphinx workaround / Caching fix

- sphinx detection is not reliable, e.g. jupyter notebooks have sphinx
  imported at startup -> no caching from notebooks
- explicitly added cached functions via autofunction to docs
- some functions do not support memory cache, because memory cache can't
  handle non-hashable parameters -> introduced diskcacheNoFallback
  decorator for these functions

creationfunctions.py

@@ -146,7 +146,7 @@ For example, to modify the AST one can run::
 """
 import sympy as sp
 from copy import copy
-from pystencils.cache import diskcache
+from pystencils.cache import diskcacheNoFallback
 from lbmpy.methods import createSRT, createTRT, createOrthogonalMRT, createKBCTypeTRT, \
     createRawMRT, createThreeRelaxationRateMRT
 from lbmpy.methods.entropic import addIterativeEntropyCondition, addEntropyCondition
@@ -300,7 +300,7 @@ def createLatticeBoltzmannAst(updateRule=None, optimizationParams={}, **kwargs):
     return res
 
 
-@diskcache
+@diskcacheNoFallback
 def createLatticeBoltzmannUpdateRule(lbMethod=None, optimizationParams={}, **kwargs):
     params, optParams = updateWithDefaultParameters(kwargs, optimizationParams)