Finding the Coordinates or Indices of Regions of Different Density in a Recovered Model

When computing a recovered model from gravity survey, I’m struggling to quantitatively analyse my results.

For example in the Sparse Norm Gravity Inversion example on the SimPEG documentation, the recovered model looks like a good fit to the true model but I am not sure how to quantitatively process the data

Is it possible to find the index or coordinates of the maximum density values on this recovered model, in the example above, and compare it to the true model to analyse the quality of the inversion?


Hi Rory,
the model is a numpy.ndarray so yo have access to all the tools from numpy (max, min, logic operators, filters etc.).
The mesh.gridCC property, which contains the locations of the cells center, is ordered as the model (or mesh.gridCC[actv] if you have an active cells mapping). So you can use the indexes you extracted from the model (like the index of the maximum) with mesh.gridCC to find its location.


Thanks for the help, it is much appreciated