diff options
Diffstat (limited to 'symbolic')
-rw-r--r-- | symbolic/D2Q9.py | 41 | ||||
-rw-r--r-- | symbolic/D3Q19.py | 41 | ||||
-rw-r--r-- | symbolic/generator.py | 46 |
3 files changed, 46 insertions, 82 deletions
diff --git a/symbolic/D2Q9.py b/symbolic/D2Q9.py index 8d42245..22f7ed5 100644 --- a/symbolic/D2Q9.py +++ b/symbolic/D2Q9.py @@ -1,5 +1,4 @@ from sympy import * -from sympy.codegen.ast import Assignment q = 9 d = 2 @@ -8,43 +7,3 @@ c = [ Matrix(x) for x in [(-1, 1), ( 0, 1), ( 1, 1), (-1, 0), ( 0, 0), ( 1, 0), w = [ Rational(*x) for x in [(1,36), (1,9), (1,36), (1,9), (4,9), (1,9), (1,36), (1,9), (1,36)] ] c_s = sqrt(Rational(1,3)) - -f_next = symarray('f_next', q) -f_curr = symarray('f_curr', q) - -def moments(f = f_curr, optimize = True): - rho = symbols('rho') - u = Matrix(symarray('u', d)) - - exprs = [ Assignment(rho, sum(f)) ] - - for i, u_i in enumerate(u): - exprs.append(Assignment(u_i, sum([ (c_j*f[j])[i] for j, c_j in enumerate(c) ]) / sum(f))) - - if optimize: - return cse(exprs, optimizations='basic', symbols=numbered_symbols(prefix='m')) - else: - return ([], exprs) - -def equilibrium(): - rho = symbols('rho') - u = Matrix(symarray('u', d)) - - f_eq = [] - - for i, c_i in enumerate(c): - f_eq_i = w[i] * rho * ( 1 - + c_i.dot(u) / c_s**2 - + c_i.dot(u)**2 / (2*c_s**4) - - u.dot(u) / (2*c_s**2) ) - f_eq.append(f_eq_i) - - return f_eq - -def bgk(tau, f_eq = equilibrium(), optimize = True): - exprs = [ Assignment(f_next[i], f_curr[i] + 1/tau * ( f_eq_i - f_curr[i] )) for i, f_eq_i in enumerate(f_eq) ] - - if optimize: - return cse(exprs, optimizations='basic') - else: - return ([], exprs) diff --git a/symbolic/D3Q19.py b/symbolic/D3Q19.py index 789b083..4e84908 100644 --- a/symbolic/D3Q19.py +++ b/symbolic/D3Q19.py @@ -1,5 +1,4 @@ from sympy import * -from sympy.codegen.ast import Assignment q = 19 d = 3 @@ -17,43 +16,3 @@ w = [Rational(*x) for x in [ ]] c_s = sqrt(Rational(1,3)) - -f_next = symarray('f_next', q) -f_curr = symarray('f_curr', q) - -def moments(f = f_curr, optimize = True): - rho = symbols('rho') - u = Matrix(symarray('u', d)) - - exprs = [ Assignment(rho, sum(f)) ] - - for i, u_i in enumerate(u): - exprs.append(Assignment(u_i, sum([ (c_j*f[j])[i] for j, c_j in enumerate(c) ]) / sum(f))) - - if optimize: - return cse(exprs, optimizations='basic', symbols=numbered_symbols(prefix='m')) - else: - return ([], exprs) - -def equilibrium(): - rho = symbols('rho') - u = Matrix(symarray('u', d)) - - f_eq = [] - - for i, c_i in enumerate(c): - f_eq_i = w[i] * rho * ( 1 - + c_i.dot(u) / c_s**2 - + c_i.dot(u)**2 / (2*c_s**4) - - u.dot(u) / (2*c_s**2) ) - f_eq.append(f_eq_i) - - return f_eq - -def bgk(tau, f_eq = equilibrium(), optimize = True): - exprs = [ Assignment(f_next[i], f_curr[i] + 1/tau * ( f_eq_i - f_curr[i] )) for i, f_eq_i in enumerate(f_eq) ] - - if optimize: - return cse(exprs, optimizations='basic') - else: - return ([], exprs) diff --git a/symbolic/generator.py b/symbolic/generator.py new file mode 100644 index 0000000..e57154c --- /dev/null +++ b/symbolic/generator.py @@ -0,0 +1,46 @@ +from sympy import * +from sympy.codegen.ast import Assignment + +class LBM(): + def __init__(self, descriptor): + self.descriptor = descriptor + self.f_next = symarray('f_next', descriptor.q) + self.f_curr = symarray('f_curr', descriptor.q) + + def moments(self, optimize = True): + 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='basic', symbols=numbered_symbols(prefix='m')) + else: + return ([], exprs) + + def equilibrium(self): + rho = symbols('rho') + u = Matrix(symarray('u', self.descriptor.d)) + + 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, tau, f_eq, optimize = True): + exprs = [ Assignment(self.f_next[i], self.f_curr[i] + 1/tau * (f_eq_i - self.f_curr[i])) for i, f_eq_i in enumerate(f_eq) ] + + if optimize: + return cse(exprs, optimizations='basic') + else: + return ([], exprs) |