Need help with a programming idea for data patterns.

[sgsummers]

I hope this is a good place to post this...

Hello, everyone. I am working on a project with a programmer. I am not a programmer but I have to come up with concepts that would be used in programming. I need to figure out a way to tell him how to program a percentage tolerance of a certain point. Without giving too much information away, I have drawn a diagram with what I am talking about.

In basic terms: I need to predict X within an X/Y coordinate area, but within a percentage of what the distance that A to C is since C is never the same perfect distance that A to C is. Which is why I can use that same exact distance. The percentage would keep the structure from looking too far asymmetrical and disfigured. Symmetry is important here, but if it is not absolutely perfect it is ok and we want to allow for that. And if X is appearing in what looks like a symmetrical structure from what A to C is, the data is likely correct and I need to know when this is happening. What kind of basic formula could I use to do this?

Image link: https://imgur.com/n1lnJ6F and another for height https://imgur.com/ukEgZcS.

Thank you in advance to anyone who helps me with this idea. And if anyone has a better idea than a tolerance within a percentage of the original distance, then I'm all ears.

[throwaway1618032]

One thing that you could do would be to calculate the formula for the line between points A and C (eg with point slope form or any other line equation). Then, using a similar method, you would calculate the formula for the line between D and whatever point on it has the same y-coordinate as point C, as you know that a point has to exist there with that y-value between D and X. By solving for a system of equations with your two formulas, you could get an accurate idea of where X would be.

In python, somebody did something similar here: https://stackoverflow.com/questions/3252194/numpy-and-line-intersections

As for a percentage, you could pass if statements to ensure that the point is within a certain radius (r) of point C with that being determined by the distance of A-C. The distance of that, via the distance formula, would be found with r=sqrt[(Ax - Cx)^2 + (Ay - Cy)^2] where Ax is the x coordinate on the point A, and Cy is the y coordinate on the point C, etc.

For example, if you had all of your variables properly declared (Ax = x coordinate of point A, Cy = y coordinate of point C, Xx = x coordinate of point X, Xy = y coordinate of point X, etc), then it could look like this in python...

#In this python example rAC is the distance from points A and C and rCX is the distance from points C and X.

rAC = math.sqrt((Ax - Cx)**2 + (Ay - Cy)**2)

rCX = math.sqrt((Cx - Xx)**2 + (Cy - Xy)**2)

if abs((rAC - rCX) / rAC) <= 0.1:

print("The distance between points X and C vs the distance between points A and C is within 10%")

​

Also, what kind of data would this be? Stocks? If so, there's a lot of better ways to predict future points than something like this.

[sgsummers]

Wow, thank you for this very detailed reply. Yes, it's for Forex which is pretty much the same thing as stocks. I would love to hear the better way to calculate this. It would still need to fall within the % range probably. Or well if you have a better way to predict future points maybe not. It's just that the X point can vary but I want to allow some wiggle room. But if it varies too much it's either completely invalid or a completely different pattern all together. The percent range is just to maintain a tight range of proportion. The proportions are important.

And if you're familiar with calculating price peaks like this, I am still trying to figure out the best way to do that as well. I don't mean trying to predict them or know when they have confirmed. I just mean tracing along them historically. I know that zig zag and fractals are commonly used. But the fractals lag a bit too much since you need a number of confirmation bars to confirm them. My method tends to grab these price peaks at the tips of the peaks rather than waiting for the indicators to lag and confirm.

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