- bugfix in vector-typing of piecewise functions
- cast_function is now a sympy atom - fixes problems with sympy > 1.1
- replace_inner_stride_with_one is a bit faster now

- defined ordering of headers
- lbm split kernels produced different ordering of assignments due to
  usage of a set

- new time loop caches all kernel functions with their argument dict
  -> inner loop just calls C functions with cached kwargs

- not generic enough - does not work if there a multiple blocks

- better latex display for indirect accesses
- new field type 'custom': only custom fields can be accessed indirectly
  no static bounds check possible for custom fields

- option to allocate more memory at end of line and do not generate a
  tail loop, if loop range is not divisible by SIMD width

- different approach in pystencils: absolute indexing

- support aligned load/stores
- nontemporal stores
- aligned memory allocation for arrays and temporary buffers

- vectorization for loops with ranges that are not a multiple of vector width
- vectorization for variable sized loops if special transformation
  replace_inner_stride_with_one is run

- SSA form is checked
- loop independence condition is checked
- bug fix in Field.create_generic when using index_shape

- when running multiple pystencils instances, sometimes errors happened
  because one process might have partially written a cached file, which
  is already read before writing was finished
-> switched to "atomic write" (only on linux yet) that uses os.rename
   which is guaranteed to be atomic

- removed warnings
- added flake8 as CI target

- test run again
- notebooks not yet

- Previously sympy.Eq was used to represent assignments. However Eq
  represents equality not assignment. This means that sometimes sympy
  "simplified" an equation like a = a  to True,
-> replaced sp.Eq by pystencils.Assignment everywhere
- renamed EquationCollection to AssignmentCollection

- now an lbMethod or updateRule can be passed in directly
- made method/update rule/ast function independent i.e. no function
  uses the same parameters as on of the others

- 3 phase model works now with step sytem

- previously all objects where cached by id()
- for waLBerla simulations in each time step a new np.array view
  is created from the waLBerla field. Each of these views has a
  different id -> caching did not work for waLBerla setups
- changed hash for numpy arrays: instead of id, a tuple of
  (dataPtr, strides, shapes) is used as hash input

- scaling interface width eta instead of surface tensions tau to correct
  interface profile & surface tensions