def observableFractionCMDX(self, mask, distance_modulus, mass_min=0.1):
"""
Compute observable fraction of stars with masses greater than mass_min in each
pixel in the interior region of the mask.
ADW: Careful, this function is fragile! The selection here should
be the same as mask.restrictCatalogToObservable space. However,
for technical reasons it is faster to do the calculation with
broadcasting here.
ADW: Could this function be even faster / more readable?
ADW: Should this include magnitude error leakage?
"""
mass_init_array,mass_pdf_array,mass_act_array,mag_1_array,mag_2_array = self.sample(mass_min=mass_min,full_data_range=False)
mag = mag_1_array if self.band_1_detection else mag_2_array
color = mag_1_array - mag_2_array
# ADW: Only calculate observable fraction over interior pixels...
pixels = mask.roi.pixels_interior
mag_1_mask = mask.mask_1.mask_roi_sparse[mask.roi.pixel_interior_cut]
mag_2_mask = mask.mask_2.mask_roi_sparse[mask.roi.pixel_interior_cut]
# ADW: Restrict mag and color to range of mask with sufficient solid angle
cmd_cut = ugali.utils.binning.take2D(mask.solid_angle_cmd,color,mag+distance_modulus,
mask.roi.bins_color, mask.roi.bins_mag) > 0
# Pre-apply these cuts to the 1D mass_pdf_array to save time
mass_pdf_cut = mass_pdf_array*cmd_cut
# Create 2D arrays of cuts for each pixel
mask_1_cut = (mag_1_array+distance_modulus)[:,np.newaxis] < mag_1_mask
mask_2_cut = (mag_2_array+distance_modulus)[:,np.newaxis] < mag_2_mask
mask_cut_repeat = mask_1_cut & mask_2_cut
observable_fraction = (mass_pdf_cut[:,np.newaxis]*mask_cut_repeat).sum(axis=0)
return observable_fraction
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