Add sector-reduced AK and error correlation plots to visualization no…#427
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sarahhancock wants to merge 1 commit into
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Add sector-reduced AK and error correlation plots to visualization no…#427sarahhancock wants to merge 1 commit into
sarahhancock wants to merge 1 commit into
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Name and Institution (Required)
Name: Sarah Hancock
Institution: Harvard ACMG
Describe the update
This pull requst adds two new diagnostic plots to the visualization notebook using the sector summation matrix W (p × n), where rows give the fractional contribution of each sector to the prior emission estimate in each grid cell (following Nesser et al., 2024).
Sector-reduced averaging kernel (
ROI_sector_reduced_averaging_kernel.png):Computes A_red = W A W* (eq. 5) using the pseudoinverse W* to show the sensitivity of each sector's posterior estimate to the true value and the spurious information from other sectors.
Sector-reduced posterior error correlations (
ROI_sector_reduced_error_correlation.png):Derived from Ŝ_red = W Ŝ W^T (eq. 4), converted to a correlation matrix, showing the inversion's ability to separate between emission sectors.
New utility functions added to
utils.py:build_sector_weight_matrix— constructs W from prior emission fractions by sectorreduce_matrix_by_sector— applies sector reduction to A or Ŝ (eqs. 4–5)covariance_to_correlation— converts Ŝ_red to a correlation matrix