def test_numpy():
mg3d = molgrid.MGrid3d(3,3,3)
mg2f = molgrid.MGrid2f(2,4)
a2f = np.arange(27).astype(np.float32).reshape(3,-1)
a3d = np.arange(27).astype(np.float).reshape(3,3,-1)
g2f = molgrid.Grid2f(a2f)
g3d = molgrid.Grid3d(a3d)
g2f[0,0] = 100
g3d[0,0,0] = 101
assert a2f[0,0] == 100
assert a3d[0,0,0] == 101
mg2f.copyFrom(g2f)
mg3d.copyFrom(g3d)
assert mg2f[1,3] == 7
mg2f[1,3] = 200
assert g2f[1,3] == 12
assert a2f[1,3] == 12
mg2f.copyTo(g2f)
assert g2f[0,7] == 200
assert a2f[0,7] == 200
def test_clear():
g1 = molgrid.Grid1d(np.random.rand(20))
mg = molgrid.MGrid3d(4,5,6)
mg.copyFrom(np.random.rand(4,5,6))
mg.fill_zero()
g1.fill_zero()
assert np.all(g1.tonumpy() == 0)
assert np.all(mg.tonumpy() == 0)
def test_mgrid_copyto_tensor():
mg2 = molgrid.MGrid2f(3,4)
mg3 = molgrid.MGrid3d(3,4,2)
for i in range(3):
for j in range(4):
mg2[i,j] = i*j+1
for k in range(2):
mg3[i,j,k] = i*j+1+k
t2 = torch.FloatTensor(3,4)
t3 = torch.DoubleTensor(3,4,2)
mg2.copyTo(t2)
mg3.copyTo(t3)
for i in range(3):
for j in range(4):
assert t2[i,j] == i*j+1
for k in range(2):
assert t3[i,j,k] == i*j+1+k
def test_mgrid_copyfrom_tensor_cuda():
mg2 = molgrid.MGrid2f(3,4)
mg3 = molgrid.MGrid3d(3,4,2)
t2 = torch.cuda.FloatTensor(3,4)
t3 = torch.cuda.DoubleTensor(3,4,2)
for i in range(3):
for j in range(4):
t2[i,j] = i*j+1
for k in range(2):
t3[i,j,k] = i*j+1+k
mg2.copyFrom(t2)
mg3.copyFrom(t3)
for i in range(3):
for j in range(4):
assert mg2[i,j] == i*j+1
for k in range(2):
assert mg3[i,j,k] == i*j+1+k
