- single function to create kernel for specified target
- data type creation from string - reuse numpy functionality
- bugfixes in dot display

- renaming because of clashes with types.py from other packages

- first vectorization tests are running
- type system: use memoized getTypeOfExpression
- casts are done using sp.Function('cast')
- C backend adapted for vectorization support
- AST nodes can required optional headers

- support for kernels that run over walberla ghost layers

- old method produced unused variables
- old method was not deterministic in the output code i.e. ordering of
  the introduced constants
- moveConstantsBeforeLoops transformation was also not deterministic

- pystencils can create now a non-compilable kernel that can be
  analyzed by kerncraft

- cache relied on uniqueness of  python id()
- id may be reused if object is freed
-> object must be held alive
-> kernel keeps all it arguments it was ever called with, alive (problematic in terms of memory consumption)

-> smaller block

- abstraction layer for selecting CUDA block and grid sizes
  - line based (was implemented before)
  - block based (new, more flexible)
-  new conditional (if/else) ast node, which is necessary for indexing schemes (guarding if)

- bugfix for CUDA kernels with variable field sizes
- extended tests for pystencils gpu kernels

- windows support
- automatic caching and creation of shared library with all generated kernels
- restrict keyword and function prefixes are preprocessor macros now -> easier to generate one code for linux, cuda, windows

problem in moveConstantBeforeLoops transformation:

--> a should end up here
{
for() {
  const int a = 5;
}
for() {
  const int a = 5
}
}

the "a" of the lower loop was not moved up, since it could not move across first loop (which is wrong)

- added sphinx files for documentation generation
- collected kernel creation functions in new "cpu" and "cudagpu" modules