Find the way to provide more efficient methods of calculation about py-ballisticcalc HOT 6 OPEN

This is implemented in pull request #50

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I implemented constant time-step calculation here: https://github.com/dbookstaber/py_ballistics/blob/time-step/py_ballisticcalc/trajectory_calc.py

However it looks like it will always take more iterations than the current method to achieve any particular level of precision, so I do not recommend pursuing this.

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but in addition to the number of iterations, it is necessary to take into account the time for performing the calculation, it may turn out that due to a decrease in the number of calculations, the number of iterations can be increased without losing performance

we have to make a profiling and performance comparing
u can use timeit built-in module to got time some function are executing

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By "iterations" I meant the number of passes through the #region Trajectory Loop to calculate any particular trajectory. (This is without regard to the zero-finding logic.)

I think the current method of setting the time step based on the velocity is optimal. Any other approach will create excess precision at some points and lower precision at others.

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To improve efficiency, JBM recommends switching from this simple integration approach to something like RK4, which is what he uses.

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I implemented RK4 integration in this branch. It is more robust than the Euler implementation we are running, meaning that as step_size increases errors grow more slowly. However on the example I studied it's not like orders of magnitude better.

This provides a foundation for some desirable improvements, including:

1. Adaptive step_size
2. I included two different RK4 implementations, one using time and the other using range.x as the independent variable. The latter (CalcMethod.RK_dx) version could particularly benefit TrajectoryCalc.zero_angle since, as long as zero_distance % step_size == 0 then it will end exactly at the distance of interest.

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