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authorAdrian Kummerlaender2019-10-21 18:42:24 +0200
committerAdrian Kummerlaender2019-10-21 18:48:38 +0200
commit82a44e0d64afb8818ea98d68dc08108885d503c2 (patch)
tree6e8f08acd83b2886cd296ed3831acc83e309906c /boltzgen/lbm/model/characteristics.py
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Pull in basics from symlbm_playground
It's time to extract the generator-part of my GPU LBM playground and turn it into a nice reusable library. The goal is to produce a framework that can be used to generate collision and streaming programs from symbolic descriptions. i.e. it should be possible to select a LB model, the desired boundary conditions as well as a data structure / streaming model and use this information to automatically generate matching OpenCL / CUDA / C++ programs.
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+from sympy import *
+
+# copy of `sympy.integrals.quadrature.gauss_hermite` sans evaluation
+def gauss_hermite(n):
+ x = Dummy("x")
+ p = hermite_poly(n, x, polys=True)
+ p1 = hermite_poly(n-1, x, polys=True)
+ xi = []
+ w = []
+ for r in p.real_roots():
+ xi.append(r)
+ w.append(((2**(n-1) * factorial(n) * sqrt(pi))/(n**2 * p1.subs(x, r)**2)))
+ return xi, w
+
+# determine weights of a d-dimensional LBM model on velocity set c
+# (only works for velocity sets that result into NSE-recovering LB models when
+# plugged into Gauss-Hermite quadrature without any additional arguments
+# i.e. D2Q9 and D3Q27 but not D3Q19)
+def weights(d, c):
+ _, omegas = gauss_hermite(3)
+ return list(map(lambda c_i: Mul(*[ omegas[1+c_i[iDim]] for iDim in range(0,d) ]) / pi**(d/2), c))
+
+# determine lattice speed of sound using directions and their weights
+def c_s(d, c, w):
+ speeds = set([ sqrt(sum([ w[i] * c_i[j]**2 for i, c_i in enumerate(c) ])) for j in range(0,d) ])
+ assert len(speeds) == 1 # verify isotropy
+ return speeds.pop()