Problem some constant expressions are neither Float,Integer,Rational but
don't have arguments.

>>> isinstance(pi, Integer)
False
>>> isinstance(pi, Float)
False
>>> isinstance(pi, Rational)
False
>>> pi.args
()

Sum and Product have a indexing variable which is a Atom but not a free
symbol

... or code will be executed when pytest is collecting the tests.
I found out that I can use "-s" to convince vim-test to show me test
output.

- str(e) did work in previous pytest version
- but the correct usage is str(e.value)
- in newer pytest version the string for the e object is changed so
  the tests did not work any more

- numpy constants get directly their numpy type
- integer functions check for integer types at construction

Markus Holzer authored 5 years ago and Markus Holzer committed 5 years ago

derive gradient weights of other direction with
already calculated weights of one direction
via rotation and apply them to a field.

as_matrix gives now a deprecated warning and as_array is no newly implemented to replace it. as_array works with MutableDenseNDimArray now instead of Matrix

This commit avoid dependency of core pystencils on jinja2.
However this could make the printing of some AST-nodes less elegant.

Stephan Seitz authored 5 years ago and Martin Bauer committed 5 years ago

- rename header Field.h is not a unique name in waLBerla context
- add PyStencilsField.h
- bindings were lacking data type

- backend, target and compile are now normal members of the
  KernelFunction node and populated in constructor

DestructuringBindingsForFieldClass defines all field-related variables
in its subordinated block.
However, it leaves a TypedSymbol of type 'Field' for each field
undefined.
By that trick we can generate kernels that accept structs as
kernelparameters.
Either to include a pystencils specific Field struct of the following
definition:

```cpp
template<DTYPE_T, DIMENSION>
struct Field
{
    DTYPE_T* data;
    std::array<DTYPE_T, DIMENSION> shape;
    std::array<DTYPE_T, DIMENSION> stride;
}

or to be able to destructure user defined types like `pybind11::array`,
`at::Tensor`, `tensorflow::Tensor`

```

This enables astnodes.Nodes to have a member required_global_declarations
by which they can specify a global declaration required for their usage.

- previous method did not work with kernels generated for walberla where
  block size changes are made at runtime
- device query does not always work, since the compile system may have
  no GPU or not the same GPU
-> max block size is passed as parameter and only optionally determined
   by a device query

Block.subs method tried to be too smart:
a = field[..]
b = a + b

was "simplified" incorrectly to
b = field[...] + b

- stencil plotting & transformation now in ps.stencil
- additional documentation & notebooks