avni.mapping.common module#
- avni.mapping.common.interp_weights(xyz, uvw, d: int = 3)[source]#
Get weights for interpolation
First, a call to
scipy.spatial.qhull.Delaunay()is made to triangulate the irregular grid coordinates. Second, for each point in the new grid, the triangulation is searched to find in which triangle (actually, in which simplex, which in your 3D case will be in which tetrahedron) does it lay. Third, barycentric coordinates of each new grid point with respect to the vertices of the enclosing simplex are computed.- Parameters
- xyz
Locations of an irregular grid
- uvw
Locations to find
- dint, optional
Some integer that probably denotes dimensions, by default 3
- Returns
- vertices, weights
Vertices of the simplex and weights to use
- avni.mapping.common.interpolate(values, vtx, wts, fill_value=nan)[source]#
Interpolate based on values, faster form of
scipy.interpolate.griddata()An interpolated values is computed for that grid point, using the barycentric coordinates, and the values of the function at the vertices of the enclosing simplex.
- Parameters
- values
_description_
- vtx_type_
_description_
- wts_type_
_description_
- fill_value_type_, optional
_description_, by default np.nan
- Returns
- _type_
_description_