First of all, thanks so much for making these tools public. I encountered just a few issues when using pygsp.operators.reduction.graph_multiresolution in practice:
If a Graph object is fed to graph_sparsify instead of a weight matrix, there is no thresholding of small values, which lead in practice to nans in the resulting matrix
also in grap_sparsify a parameter q is computed, should be an int except for me it wasn't
in kron_reduction I encountered some numerical stability issues and non-zero diagonals after reduction, not 100% sure it is correct to do so but I just added a line to remove the diagonal of the resulting matrix
First of all, thanks so much for making these tools public. I encountered just a few issues when using
pygsp.operators.reduction.graph_multiresolution
in practice:Graph
object is fed tograph_sparsify
instead of a weight matrix, there is no thresholding of small values, which lead in practice to nans in the resulting matrixgrap_sparsify
a parameter q is computed, should be anint
except for me it wasn'tkron_reduction
I encountered some numerical stability issues and non-zero diagonals after reduction, not 100% sure it is correct to do so but I just added a line to remove the diagonal of the resulting matrix