def reduce_ugrid(ugrid, stride, chop):
'''Reduce the uniform grid
**Arguments:**
ugrid
The uniform integration grid.
stride
The reduction factor.
chop
The number of slices to chop of the grid in each direction.
Returns: a reduced ugrid object
'''
if (chop < 0):
raise ValueError('Chop must be positive or zero.')
if ((ugrid.shape - chop) % stride != 0).any():
raise ValueError('The stride is not commensurate with all three grid demsions.')
new_shape = (ugrid.shape-chop)/stride
grid_rvecs = ugrid.grid_rvecs*stride
new_ugrid = UniformGrid(ugrid.origin, grid_rvecs, new_shape, ugrid.pbc)
return new_ugrid
def write_random_lta_cube(dn, fn_cube):
sys = System.from_file(context.get_fn('test/lta_gulp.cif'))
ugrid = UniformGrid(np.zeros(3, float), sys.cell.rvecs * 0.1,
np.array([10, 10, 10]), np.array([1, 1, 1]))
cube_data = np.random.uniform(0, 1, ugrid.shape)
sys.update_grid(ugrid)
sys.extra['cube_data'] = cube_data
sys.to_file(os.path.join(dn, fn_cube))
return sys
def write_random_lta_cube(dn, fn_cube):
'''Write a randomized cube file'''
# start from an existing cube file
mol = IOData.from_file(context.get_fn('test/lta_gulp.cif'))
# Define a uniform grid with only 1000 points, to make the tests fast.
ugrid = UniformGrid(np.zeros(3, float), mol.cell.rvecs * 0.1,
np.array([10, 10, 10]), np.array([1, 1, 1]))
# Write to the file dn/fn_cube
mol.cube_data = np.random.uniform(0, 1, ugrid.shape)
mol.grid = ugrid
mol.to_file(os.path.join(dn, fn_cube))
return mol
def test_reduce_data1():
from horton import UniformGrid
data = np.random.normal(0, 1, (11, 21, 31))
grid_rvecs = np.identity(3, float) * 0.1
ugrid = UniformGrid(np.array([0.3, 0.2, -0.1]), grid_rvecs,
np.array(data.shape), np.array([1, 1, 0]))
data1, ugrid1 = reduce_data(data, ugrid, 10, 1)
assert data1.shape == (1, 2, 3)
assert (data1 == data[:-1:10, :-1:10, :-1:10]).all()
assert (ugrid1.origin == ugrid.origin).all()
assert abs(ugrid1.grid_rvecs - ugrid.grid_rvecs * 10).max() < 1e-10
assert (ugrid1.shape == [1, 2, 3]).all()
assert (ugrid1.pbc == ugrid.pbc).all()
data2, ugrid2 = reduce_data(data, ugrid, 5, 1)
assert data2.shape == (2, 4, 6)
assert (data2 == data[:-1:5, :-1:5, :-1:5]).all()
assert (ugrid2.origin == ugrid.origin).all()
assert abs(ugrid2.grid_rvecs - ugrid.grid_rvecs * 5).max() < 1e-10
assert (ugrid2.shape == [2, 4, 6]).all()
assert (ugrid2.pbc == ugrid.pbc).all()