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a bag of minor suggestions #48
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Some cosmetic suggestions for tooltips:
Also, the current plot title only reflects one of the input images (or models), which is a bit confusing. May I suggest adding the names to the axis labels instead, so that they say e.g. "log S1: model_or_image_name" and "log S2: model_or_image_name". Then you just need to figure out an elegant way to display both model names in the position offset plot... maybe in the legend of the right plot, instead of "Model 1" and "Model 2"? Then the title of the left plot can be "Position offsets". Finally, for filenames, may I suggest |
It gives an overall sense of how well the source fluxes in one sky model fit the other, meaning that a value close to 1 implies a perfect correlation between the two sky models. This cannot be solely relied on but can be used in conjunction with the RMSE which provides the average deviation of the flux differences in units of source flux densities. (It is sensitive to outliers). And then the intercept and the gradient are used to further confirm that the fit follows the expected fit, which is c=0, g=1.
Taking care of this.
The solid blue line is the fit (as indicated in the legend)
Taking care of this. |
With the help of
|
(Continued from https://github.com/o-smirnov/meerkat-open-time/issues/18, as this is a more appropriate place)
All right, aimfast works like a charm now @Athanaseus (me having zapped the Island of Doom)!
Some questions/suggestions:
What does "R2" mean? https://en.wikipedia.org/wiki/Coefficient_of_determination?
Can we also fit a slope through a 0 intercept (and show it on the same plot)?
I find "intercept" a bit difficult to interpret. As reported above, it's the log of a fitted flux offset, I think. Might be good to convert it back into mJy?
I assume the solid blue line is slope 1, intercept 0? In this case please draw it until (0,0), as that makes it clearer what it is. Also, suggest swapping linestyles. The fitted slope(s) are the important lines so should be a solid color, the slope=1 line should be less prominent (i.e. dashed), but maybe that's just me.
Finally: in the plot above, it's clear the slope doesn't actually fit the (brighter) sources all that well, they all seem to lie above it consistently. I think it's that cluster of weak peripheral sources below the slope that's biasing the fit (and yay for the colour scheme, we wouldn't be able to diagnose the problem so easily without it!) We could think of clever schemes to downweigh peripheral sources, but for a start, could we add an option for a distance cutoff?
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