The subpackage RTModel.plotmodel contains functions for plotting the astrometric centroid trajectory and comparing with the observations.
Assuming you have a completed run on some astrophotometric event in its directory /astroevent001, we proceed as for purely photometric events to plot the light curve as usual
import RTModel.plotmodel as plm
import glob
event = '/astroevent001'
models = glob.glob(event +'/FinalModels/*')
model = models[0] # let's plot the first of the best models
myplot = plm.plotmodel(eventname = event, modelfile = model)
The output will look like this
We note that the parameters table contains the assessment for the four additional astrometric parameters muS_Dec, muS_RA, piS, thetaE, as explained before.
Now, to see the trajectory of the centroid in the sky, we just type
myplot.showastrometry()
Only the first astrometric series found is displayed, since the centroid trajectory also depends on the blending fraction, which varies for each telescope/filter. If we want to show a specific astrometric series, we just have to add the number of the telescope in the order it appears in the legend of the light curve, starting from zero: myplot.showastrometry(1).
In the example shown above, we note that the error bars are much larger than the astrometric displacement, having assumed an uncertainty of 1 milliarcsecond in our simulation. Astrometric data in the years following the microlensing peak are very precious to fix the proper motion and the source parallax. As explained in Data pre-processing, we have let RTModel re-bin the data giving more weight to data in the peak season. Therefore, the data in the following years have been re-binned and appear with smaller error bars.
In alternative, we may show the Right Ascension or Declination as functions of time with the following functions.
myplot.showastrometryRA()
myplot.showastrometryDec()
They both accept the telescope number as optional argument.