1 files changed, 2 insertions, 78 deletions
diff --git a/boltzgen/lbm/__init__.py b/boltzgen/lbm/__init__.py
index 3f608cb..276c0bb 100644
--- a/boltzgen/lbm/__init__.py
+++ b/boltzgen/lbm/__init__.py
@@ -1,78 +1,2 @@
-from sympy import *
-from sympy.codegen.ast import Assignment
-
-import boltzgen.utility.optimizations as optimizations
-from boltzgen.lbm.model.characteristics import weights, c_s
-
-
-def assign(names, definitions):
-    return list(map(lambda x: Assignment(*x), zip(names, definitions)))
-
-class LBM:
-    def __init__(self, descriptor, tau, optimize = True):
-        self.descriptor = descriptor
-        self.tau        = tau
-        self.optimize   = optimize
-
-        if self.tau <= 0.5:
-            raise Exception('Relaxation time must be larger than 0.5')
-
-        self.f_next = symarray('f_next', descriptor.q)
-        self.f_curr = symarray('f_curr', descriptor.q)
-
-        if not hasattr(descriptor, 'w'):
-            self.descriptor.w = weights(descriptor.d, descriptor.c)
-
-        if not hasattr(descriptor, 'c_s'):
-            self.descriptor.c_s = c_s(descriptor.d, descriptor.c, self.descriptor.w)
-
-    def moments(self, optimize = None):
-        if optimize is None:
-            optimize = self.optimize
-
-        rho = symbols('rho')
-        u   = Matrix(symarray('u', self.descriptor.d))
-
-        exprs = [ Assignment(rho, sum(self.f_curr)) ]
-
-        for i, u_i in enumerate(u):
-            exprs.append(
-                Assignment(u_i, sum([ (c_j*self.f_curr[j])[i] for j, c_j in enumerate(self.descriptor.c) ]) / sum(self.f_curr)))
-
-        if optimize:
-            return cse(exprs, optimizations=optimizations.custom, symbols=numbered_symbols(prefix='m'))
-        else:
-            return ([], exprs)
-
-    def equilibrium(self, resolve_moments = False):
-        rho = symbols('rho')
-        u   = Matrix(symarray('u', self.descriptor.d))
-
-        if resolve_moments:
-            moments = self.moments(optimize = False)[1]
-            rho = moments[0].rhs
-            for i, m in enumerate(moments[1:]):
-                u[i] = m.rhs
-
-        f_eq = []
-
-        for i, c_i in enumerate(self.descriptor.c):
-            f_eq_i = self.descriptor.w[i] * rho * ( 1
-                                                  + c_i.dot(u)    /    self.descriptor.c_s**2
-                                                  + c_i.dot(u)**2 / (2*self.descriptor.c_s**4)
-                                                  - u.dot(u)      / (2*self.descriptor.c_s**2) )
-            f_eq.append(f_eq_i)
-
-        return f_eq
-
-    def bgk(self, f_eq, optimize = None):
-        if optimize is None:
-            optimize = self.optimize
-
-        exprs = [ self.f_curr[i] + 1/self.tau * (f_eq_i - self.f_curr[i]) for i, f_eq_i in enumerate(f_eq) ]
-
-        if optimize:
-            subexprs, f = cse(exprs, optimizations=optimizations.custom)
-            return (subexprs, assign(self.f_next, f))
-        else:
-            return ([], assign(self.f_next, exprs))
+from . import model
+from . import lattice