bla.py

bla.py

def laplacian(grid: Grid, f: Field[I, J, K, Matrix[3, 3, dtype]]):
    def stencil((i, j, k), m):
        return l2_norm(m @ [1, 2, 3])
        
    #def stencil(i, j, k, val):
    #    if (i, j, k) in grid[(I, J, K), "interior"]:
    #      return -4*f[i, j, k]+f[i-1, j, k]+f[i+1, j, k]+f[i, j-1, k]+f[i, j+1, k]
    #    else:
            ...
    #return Field(f.domain, stencil)
    return map(stencil, graph(f))
    return map(stencil, zip(f.domain, f.image))
    
    
    phi = Field(domain, Lambda((Index(I), Index(J), Index(K)), Constant(0)))
phi2 = Field(domain, Lambda((Index(I), Index(J), Index(K)), Constant(1)))

val = phi[Index(I)+1, Index(J), Index(K)]+phi2[Index(I)+1, Index(J), Index(K)]

val2 = simplify(val)

val3 = val2+1

bla = 1+1

phi = LazyField()

def laplacian(f: Field):
    def stencil(i, j, k):
        return -4*f[i, j, k]+f[i-1, j, k]+f[i+1, j, k]+f[i, j-1, k]+f[i, j+1, k]
    return map(stencil, f)


def laplacian(f: Field):
    def stencil(i, j, k):
        switch({
           (i, j, k) in grid[((I, J, K), "north")]: 1,

           (i, j, k) in grid[((I, J, K), "interior")]: (-4 * f + f[i-1] + f[i+1] + f[j-1] + f[j+1])
       })
        return -4*f[i, j, k]+f[i-1, j, k]+f[i+1, j, k]+f[i, j-1, k]+f[i, j+1, k]
    return Field(f.domain, stencil)
    #return map(stencil, f)

def getitem(f: Field, indices):
    Index(domain, dim)-1 == Index(translate(domain, (dim: -1)), dim)

@dispatch
def translate(domain: Domain, offset: Tuple[Dimension, Int]):

declare("translate", Domain, Tuple[Dimension, Int])

laplacian(laplacian(phi))