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In the current computation of the weights for pdfs with shared bins:
mask = (pzbins >= zmin) * (pzbins <= zmax) z_grid = pzbins[mask] pz_matrix = np.array(pzpdf)[:, mask] kernel_matrix = kernel(z_grid) return simpson(pz_matrix * kernel_matrix, x=z_grid, axis=1)
the precision is limited to the pdf bin sizes (pzbins). This can have a significant impact on the integral. For instance:
pzbins
and dz=0.05 is similar to what we might get from the PZ WG. So I propose to interpolate the pdf in finer bins before integration
dz=0.05
The text was updated successfully, but these errors were encountered:
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In the current computation of the weights for pdfs with shared bins:
the precision is limited to the pdf bin sizes (
pzbins
). This can have a significant impact on the integral. For instance:and
dz=0.05
is similar to what we might get from the PZ WG. So I propose to interpolate the pdf in finer bins before integrationThe text was updated successfully, but these errors were encountered: