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Exo-TiC / ExoTiC-ISM

This is a repository for the reduction pipeline detailed in Wakeford, et al., 2016, ApJ. The method implements marginalization across a series of models to represent stochastic models for observatory and instrument systematics. This is primarily for HST WFC3, however, may be extended to STIS in the future.
MIT License
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Adjust figures for masked arrays and fix up for PDF report #53

Closed ivalaginja closed 4 years ago

ivalaginja commented 5 years ago

Also, the output PDF will need to include a statement that the systematic model array was masked to remove N models which did not satisfy the positive AIC condition - the figures should then possibly include blank spots for masked results while keeping the used model in the correct number position on Figure 1

Originally posted by @hrwakeford in https://github.com/hrwakeford/ExoTiC-ISM/pull/46#issuecomment-517743855

We started using masked arrays in PR #46 AIC so that we can ignore models yielding negative AIC. Turns out that masked data points get completely ignored when we plot those arrays, however we would like to have them included in the plots but just be marked differently.

We need to adjust the figures for inclusion in the report anyway, currently they're quite all over the place.

ivalaginja commented 4 years ago

matplotlib treats masked arrays just as we want them to be displayed, such that the masked data points simply don't appear in the plots but the overall data shape gets retained. The rest of the work concerning the PDF report plots is being done in #80.