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Fix for case where there is a masked column to aggregate #45

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Aug 19, 2021
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Fix for case where there is a masked column to aggregate #45

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6 changes: 4 additions & 2 deletions stellarphot/differential_photometry/aij_rel_fluxes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -60,7 +60,6 @@ def calc_aij_relative_flux(star_data, comp_stars,
# Not sure this is really close enough for a good match...
good = d2d < 1 * u.arcsec


error_column_name = 'noise-aij'
# Calculate comp star counts for each time

Expand All @@ -72,8 +71,11 @@ def calc_aij_relative_flux(star_data, comp_stars,
# np.isnan(comp_fluxes[error_column_name]).sum())
# print(star_data[good][flux_column_name][np.isnan(comp_fluxes[flux_column_name])])

# Check whether any of the columns are masked, but with no masked values,
# and convert to regular column...eventually

comp_fluxes = comp_fluxes.group_by('date-obs')
comp_totals = comp_fluxes.groups.aggregate(np.add)[flux_column_name]
comp_totals = comp_fluxes.groups.aggregate(np.sum)[flux_column_name]
comp_errors = comp_fluxes.groups.aggregate(_add_in_quadrature)[error_column_name]

comp_total_vector = np.ones_like(star_data[flux_column_name])
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