# 需要導入模塊: from skimage import measure [as 別名]

# 或者: from skimage.measure import marching_cubes [as 別名]

def compute_marching_cubes_regular_grid(self, level: float, scalar_field,

mask_array=None,

rescale=False, **kwargs):

"""Compute the surface (vertices and edges) of a given surface by computing

marching cubes (by skimage)

Args:

level (float): value of the scalar field at the surface

scalar_field (np.array): scalar_field vector objects

mask_array (np.array): mask vector with trues where marching cubes has to be performed

rescale (bool): if True surfaces will be located between 0 and 1

**kwargs: skimage.measure.marching_cubes_lewiner args (see below)

Returns:

list: vertices, simplices, normals, values

See Also:

:func:`skimage.measure.marching_cubes`

"""

vertices, simplices, normals, values = measure.marching_cubes(

scalar_field.reshape(self.grid.regular_grid.resolution[0],

self.grid.regular_grid.resolution[1],

self.grid.regular_grid.resolution[2]),

level,

spacing=self.grid.regular_grid.get_dx_dy_dz(rescale=rescale),

mask=mask_array,

**kwargs)

if rescale is True:

loc_0 = self.grid.regular_grid.extent_r[[0, 2, 4]] + \

np.array(self.grid.regular_grid.get_dx_dy_dz(rescale=True)) / 2

vertices += np.array(loc_0).reshape(1, 3)

else:

loc_0 = self.grid.regular_grid.extent[[0, 2, 4]] + \

np.array(self.grid.regular_grid.get_dx_dy_dz(rescale=False)) / 2

vertices += np.array(loc_0).reshape(1, 3)

return [vertices, simplices, normals, values]

# def mask_topo(self, mask_matrix):

# """Add the masked elements of the topography to the masking matrix"""

# x = ~self.grid.regular_grid.mask_topo

# a = (np.swapaxes(x, 0, 1) * mask_matrix)

# return a