Added more documentation

README.md

@@ -16,10 +16,10 @@ It even comes with an integrated Chapman Enskog analysis based on sympy!
 
 Common test scenarios can be set up quickly:
 ```python
-from lbmpy.scenarios import create_channel
 from pystencils import Target
+from lbmpy.session import *
 
-ch = create_channel(domain_size=(300, 100, 100), force=1e-7, method="trt",
+ch = create_channel(domain_size=(300, 100, 100), force=1e-7, method=Method.TRT,
                     equilibrium_order=2, compressible=True,
                     relaxation_rates=[1.97, 1.6], optimization={'target': Target.GPU})
 ```

doc/notebooks/03_tutorial_lbm_formulation.ipynb

@@ -69,11 +69,11 @@
 method
 ```
 
 %%%% Output: execute_result
 
-    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f0d442c0fa0>
+    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f49aed671c0>
 
 %% Cell type:markdown id: tags:
 
 The first column labeled "Moment" defines the collision space and thus the transformation matrix $C$.
 The remaining columns specify the equilibrium vector in moment space $c^{(eq)}$ and the corresponding relaxation rate.
@@ -131,11 +131,11 @@
 method.stencil
 ```
 
 %%%% Output: execute_result
 
-    <lbmpy.stencils.LBStencil at 0x7f0d442f2a90>
+    <lbmpy.stencils.LBStencil at 0x7f49aedd27c0>
 
 %% Cell type:markdown id: tags:
 
 ### Orthogonal MRTs
 
@@ -153,11 +153,11 @@
 weighted_ortho_mrt
 ```
 
 %%%% Output: execute_result
 
-    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f0d39ecaee0>
+    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f49aea33850>
 
 %% Cell type:code id: tags:
 
 ``` python
 lbm_config = LBMConfig(stencil=Stencil.D2Q9, method=Method.MRT, weighted=False)
@@ -165,11 +165,11 @@
 ortho_mrt
 ```
 
 %%%% Output: execute_result
 
-    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f0d39f23760>
+    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f49aeb64fa0>
 
 %% Cell type:markdown id: tags:
 
 One can check if a method is orthogonalized:
 
@@ -202,11 +202,11 @@
 central_moment_method
 ```
 
 %%%% Output: execute_result
 
-    <lbmpy.methods.momentbased.centralmomentbasedmethod.CentralMomentBasedLbMethod at 0x7f0d39c84d90>
+    <lbmpy.methods.momentbased.centralmomentbasedmethod.CentralMomentBasedLbMethod at 0x7f49aeadb0a0>
 
 %% Cell type:markdown id: tags:
 
 The shift to the central moment space is done by applying a so-called shift matrix. Usually, this introduces a high numerical overhead. This problem is solved with lbmpy because each transformation stage can be specifically optimised individually. Therefore, it is possible to derive a CLBM with only a little numerical overhead.
 
@@ -318,11 +318,11 @@
 create_lb_method(LBMConfig(stencil=Stencil.D2Q9, method=Method.MRT, nested_moments=moments))
 ```
 
 %%%% Output: execute_result
 
-    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f0d39cceac0>
+    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f49ae9359d0>
 
 %% Cell type:markdown id: tags:
 
 If one needs to also specify custom equilibrium moments the following approach can be used
 
@@ -353,11 +353,11 @@
 method
 ```
 
 %%%% Output: execute_result
 
-    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f0d39bf1c10>
+    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f49ae8e9c10>
 
 %% Cell type:markdown id: tags:
 
 Instead of manually defining all entries in the method table, *lbmpy* has functions to fill the table according to a specific pattern. For example:
 - for a full stencil (D2Q9, D3Q27) there exist exactly 9 or 27 linearly independent moments. These can either be taken as they are, or orthogonalized using Gram-Schmidt, weighted Gram-Schmidt or a Hermite approach
@@ -379,11 +379,11 @@
 method
 ```
 
 %%%% Output: execute_result
 
-    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f0d39bfbc70>
+    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f49ae8ca190>
 
 %% Cell type:markdown id: tags:
 
 Our customized method can be directly passed into one of the scenarios. We can for example set up a channel flow with it. Since we used symbols as relaxation rates, we have to pass them in as `kernel_params`.
 

lbmpy/creationfunctions.py

@@ -9,9 +9,11 @@ Method parameters
 
 General:
 
-- ``stencil='D2Q9'``: stencil name e.g. 'D2Q9', 'D3Q19'. See :func:`pystencils.stencils.get_stencil` for details
-- ``method='srt'``: name of lattice Boltzmann method. This determines the selection and relaxation pattern of
-  moments/cumulants, i.e. which moment/cumulant basis is chosen, and which of the basis vectors are relaxed together
+- ``stencil=Stencil.D2Q9``: All stencils are defined in :class: `lbmpy.enums.Stencil`.
+  From that :class:`lbmpy.stencils.LBStenil` class will be created.
+- ``method=Method.SRT``: name of lattice Boltzmann method. Defined by :class: `lbmpy.enums.Method`.
+  This determines the selection and relaxation pattern of moments/cumulants, i.e. which moment/cumulant
+  basis is chosen, and which of the basis vectors are relaxed together
 
     - ``srt``: single relaxation time (:func:`lbmpy.methods.create_srt`)
     - ``trt``: two relaxation time, first relaxation rate is for even moments and determines the viscosity (as in SRT),
@@ -46,10 +48,7 @@ General:
   compressible.
 - ``equilibrium_order=2``: order in velocity, at which the equilibrium moment/cumulant approximation is
   truncated. Order 2 is sufficient to approximate Navier-Stokes
-- ``force_model=None``: possible values: ``None``, ``'simple'``, ``'luo'``, ``'guo'``/``'schiller'``,
-  ``'buick'``/``'silva'``, ``'edm'``/``'kupershtokh'``, ``'he'``, ``'shanchen'``, ``'cumulant'``,
-  or an instance of a class implementing the same methods as the classes in :mod:`lbmpy.forcemodels`. 
-  For details, see :mod:`lbmpy.forcemodels`
+- ``force_model=None``: possibilities are defined in :class: `lbmpy.enums.ForceModel`
 - ``force=(0,0,0)``: either constant force or a symbolic expression depending on field value
 - ``maxwellian_moments=True``: way to compute equilibrium moments/cumulants, if False the standard
   discretized LBM equilibrium is used, otherwise the equilibrium moments are computed from the continuous Maxwellian.
@@ -182,6 +181,11 @@ Kernel functions are created in three steps:
 
 The function :func:`create_lb_function` runs the whole pipeline, the other functions in this module
 execute this pipeline only up to a certain step. Each function optionally also takes the result of the previous step.
+Each of those functions is configured with three data classes. One to define the lattice Boltzmann method itself.
+This class is called `LBMConfig`. The second one determines optimisations which are specific to the LBM. Optimisations
+like the common supexpression elimination. The config class is called `LBMOptimisation`. The third
+data class determines hardware optimisation. This can be found in the pystencils module as `CreateKernelConfig`.
+With this class for example the target of the generated code is specified.
 
 For example, to modify the AST one can run::