Giving this a little more thought, I can visualize a "predictive focus tool" that could set the correct initial position and step size based on local conditions and the parameters of the rig being measured, by using a feedback loop created by logging the values of the independent variables (that have a significant enough effect to bother with) of each focus attempt, including the available weather data, into a text file database. This would need to be performed against the same starfield for some base number of repetitions at different weather conditions. You'd need to input the measured step distance measured, and the tool would use the telescope parameters configured elsewhere to calculate things like step-width of the CFZ and use the curves generated by the data set at each variable point to build a mesh of actual resulting values, that could be used as a predictor for focus setting(s) that should be pretty accurate once it has enough training runs in it. So as a user, you'd do the measurement, configure the tool with it, and select a reliable and non-variable star (like polaris, for example), run "Train Focuser" (autofocus that saves values to training file). Then, every time you set up, point to Polaris, and run "Train Focuser" again. Do it enough times, and it should get pretty good at predicting focus position for a given set of conditions. The mesh generated, likely might have value elsewhere in the software as well, since it effectively models the performance of your rig at a given location over time.

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