lbmpy/methods/cumulantbased/__init__.py → src/lbmpy/methods/cumulantbased/__init__.py

 from .cumulantbasedmethod import CumulantBasedLbMethod
 from .galilean_correction import add_galilean_correction
+from .fourth_order_correction import add_fourth_order_correction
 
-__all__ = ['CumulantBasedLbMethod', 'add_galilean_correction']
+__all__ = ['CumulantBasedLbMethod', 'add_galilean_correction', 'add_fourth_order_correction']

lbmpy/methods/cumulantbased/cumulant_simplifications.py → src/lbmpy/methods/cumulantbased/cumulant_simplifications.py

@@ -16,11 +16,8 @@ def insert_logs(ac, **kwargs):
 def insert_log_products(ac, **kwargs):
     def callback(asm):
         rhs = asm.rhs
-        if isinstance(rhs, sp.log):
+        if rhs.find(sp.log):
             return True
-        if isinstance(rhs, sp.Mul):
-            if any(isinstance(arg, sp.log) for arg in rhs.args):
-                return True
         return False
 
     return insert_subexpressions(ac, callback, **kwargs)

lbmpy/methods/cumulantbased/cumulantbasedmethod.py → src/lbmpy/methods/cumulantbased/cumulantbasedmethod.py

@@ -23,7 +23,7 @@ class CumulantBasedLbMethod(AbstractLbMethod):
     This class implements cumulant-based lattice boltzmann methods which relax all the non-conserved quantities
     as either monomial or polynomial cumulants. It is mostly inspired by the work presented in :cite:`geier2015`.
 
-    This method is implemented modularily as the transformation from populations to central moments to cumulants
+    This method is implemented modularly as the transformation from populations to central moments to cumulants
     is governed by subclasses of :class:`lbmpy.moment_transforms.AbstractMomentTransform`
     which can be specified by constructor argument. This allows the selection of the most efficient transformation
     for a given setup.
@@ -124,7 +124,7 @@ class CumulantBasedLbMethod(AbstractLbMethod):
     @property
     def zeroth_order_equilibrium_moment_symbol(self, ):
         """Returns a symbol referring to the zeroth-order moment of this method's equilibrium distribution,
-        which is the area under it's curve
+        which is the area under its curve
         (see :attr:`lbmpy.equilibrium.AbstractEquilibrium.zeroth_order_moment_symbol`)."""
         return self._equilibrium.zeroth_order_moment_symbol
 

lbmpy/methods/momentbased/entropic.py → src/lbmpy/methods/momentbased/entropic.py

@@ -286,7 +286,7 @@ def _get_relaxation_rates(collision_rule):
     omega_s = get_shear_relaxation_rate(method)
 
     # if the shear relaxation rate is not specified as a symbol look for its symbolic counter part in the subs dict
-    for symbolic_rr, rr in method.subs_dict_relxation_rate.items():
+    for symbolic_rr, rr in method.subs_dict_relaxation_rate.items():
         if omega_s == rr:
             omega_s = symbolic_rr
 

lbmpy/moment_transforms/cumulanttransforms.py → src/lbmpy/moment_transforms/cumulanttransforms.py

@@ -67,10 +67,10 @@ class CentralMomentsToCumulantsByGeneratingFunc(AbstractMomentTransform):
         self.cumulant_exponents = self.moment_exponents
         self.cumulant_polynomials = self.moment_polynomials
 
-        if(len(self.cumulant_exponents) != stencil.Q):
+        if len(self.cumulant_exponents) != stencil.Q:
             raise ValueError("Number of cumulant exponent tuples must match stencil size.")
 
-        if(len(self.cumulant_polynomials) != stencil.Q):
+        if len(self.cumulant_polynomials) != stencil.Q:
             raise ValueError("Number of cumulant polynomials must match stencil size.")
 
         self.central_moment_exponents = self.compute_required_central_moments()

lbmpy/moments.py → src/lbmpy/moments.py

@@ -86,8 +86,8 @@ def moment_permutations(exponent_tuple):
 def moments_of_order(order, dim=3, include_permutations=True):
     """All tuples of length 'dim' which sum equals 'order'"""
     for item in __fixed_sum_tuples(dim, order, ordered=not include_permutations):
-        assert(len(item) == dim)
-        assert(sum(item) == order)
+        assert len(item) == dim
+        assert sum(item) == order
         yield item