I finally got Alexia's new crl working. As far as I can tell the only difference is that getximat expects the errors in xi as an input. For now I am just inputting an identity matrix, as I will need to get the errors by bootstrapping and haven't done that yet.
The function getximat wants a matrix that is the same size as the length of the xiss matrix:
xierr = N.identity(xispec.shape[1],float)
I am reconstructing from 0 to 0.5 Gpc/h using 20 bins. I am renormalizing the reconstructed redshift distribution by the following:
sum(photometric data)/sum(reconstructed data)
This gives the same "number" of objects in both sets.
The function getximat wants a matrix that is the same size as the length of the xiss matrix:
xierr = N.identity(xispec.shape[1],float)
I am reconstructing from 0 to 0.5 Gpc/h using 20 bins. I am renormalizing the reconstructed redshift distribution by the following:
sum(photometric data)/sum(reconstructed data)
This gives the same "number" of objects in both sets.
This is the first reasonable reconstruction I have ever generated. This makes me very very happy. I'm going to play with different binning and selection functions next, but I would like to have at least one blog entry which has a happy ending.
Dear Jess, You Rock! Love, Alexia
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