Drawing opposite lines in JES (Python) - python

So I have a random point on a canvas that will draw a line to a random point along a line across the bottom of the canvas. From that random point along the bottom of the canvas, I want to draw a line that diverges in the opposite direction (think of it like a " V ").
I'm having a serious issue conceptualizing what I need to do in order to accomplish getting the proper X coordinate for the second line that will be drawn (the Y-Coordinates will obviously be equal). I'm trying to do this using the addLine function in JES
If anyone could point me in the right direction I'd greatly appreciate it

It sounds like you basically want to just make an isosceles triangle here, so that the two legs of your V will be equal, though opposite in angle.
This doesn't define a strict angle between your two legs (which sounds like it's alright), but only that the x distance between both points and your point on the bottom of the canvas is equal.
Specifically, if you've got some code like this:
first_point = (a, b)
bottom_point = (c, d)
You want to make sure that the second_point is parallel though opposite to the first point, so the y coordinate should be the same, and the distance in the x-direction should be the same as the distance to the bottom_point, though in the opposite direction.
third_point_x = c - (a - c)
third_point = (third_point_x, b)
Hope that helps, let me know if you've got any more questions.

Related

Find an object that other canvas object is overlapping with - Python tkinter

I want to detect with what canvas object block. We have block, circle and triangle canvas objects.
I know there is if block in canvas.find_overlapping(x1,y1,x2,y2): method but doesn't shows with what object is block overlapping. It just shows if block is touching with any other canvas object.
overlapping_object=canvas.find_overlapping(block), overlapping_object could be a list that shows tags of objects that is block touching with.
How to make overlapping_object=canvas.find_overlapping(block) but it's correct. This one I typed here is just how could it look.
Thanks for any help!
I'm making 2D minecraft in tkinter and this is the thing that can really speed up my process.
If you're not willing to use other libraries and only tkinter, I don't think there's a built in function in tkinter that will allow it. I am also not sure why everything must be done in tkinter as it's not at all unusual for programs to use multiple libraries. Personally, given tikinter's limitations, I would use pygame to track polygons and their intersection but would never draw them. Short of using a third library (tikinter, python default, and other), there is one other approach. I mean it's really the only appraoch.
good ole fashioned math.
https://algs4.cs.princeton.edu/93intersection/
Here's some documentation on how to go about doing that. I wish you luck.
EDIT:
I think I accidentally found the answer to your question using math while studying for some other stuff. Still no way IN tkinter but here's a math explanation.
circle with center (x,y) and radius r
Polygon with z number of sides with x*2-1 number of points(x,y)
If you take iterate the lines of the polygon and put them through the following maths
Line J (x1,y1)(x2,y2)
m of Line J = (y1-y2)/(x1-x2)
create line P from circle center to P1 of LineJ
create line O from circle center to P2 of LineJ
Now we have a triangle
take the inverse cosine and length of P and O to get angle of the triangle you just made.
Make a right triangle by bisecting the triangle with line K starting at circle center and going out at the angle you just calculated.
Now you have line P and 1/2 angle of line P to line K
Now to find the intercept of that mid angle line
Tan(1/2 angle) = slope or m of the new line
using the x,y of the circle center calculate the slope intercept formula y=mx+b and get b
Now take the slope intercept formula for line J and set it equal to the slope intercept of the new line
line J (mx + b) = y = line P (mx + b)
Solve for y
Then plug y in the slope intercept for either and solve for x.
Once you've done this you have 4 points. The three points of the triangle, the point that makes a perpendicular line to center of circle from line J.
If any 3 of those points to the center of the circle in distance is smaller than r, they overlap. If they are are all > r then they don't overlap.

Python-Creating List Of Grid Positions Within A Certain Bound Given A Distance

two scenarios
I have an x axis size, a y axis size, a render distance, a list of grid position numbers and a central grid position.
I am trying to create a list of all the grid positions within the render distance of a central grid position.
The size of the x and y axis may be different independently. Optimally this algorithm would not attempt to get positions where the render distance extends over the side of the x or y axis.
Thanks.
I'm writing this to help you answer your own question in the style that I would go about it. As with anything in coding, what you need to do is be able to break down a big problem into multiple smaller ones.
Design two functions to convert to and from (x, y) coordinates (optional, it'll make your life easier, but won't be as efficient, personally I would avoid this for a bit of a challenge).
Given n, size and distance, calculate up, down, left and right. If the size is different for different axis, then just provide the function with the correct one.
eg.
def right(n, size, distance):
return n + size * distance
def down(n, size, distance):
return n - distance
Given size, make sure the above functions don't go off the edge of the grid. Converting the points to (x, y) coordinates for this part may help.
Now you have the sides of the square, run the functions again to get the corners. For example, to get the top right corner, you could do right(up(*args)) or up(right(*args))
With the corners, you can now calculate what's in your square. Converting the points to (x, y) coordinates will make it easier.

How to get start and end coordinates (x, y) of major axis of a rotating ellipse in opencv?

I am performing motion tracking of an object, and I am trying to identify the front and back of the object. The object is asymmetrical, which means that the centroid of the contour is closer to the front than the back. Using this information, I am approaching this as follows:
Draw contours of object
Find centroid
centroidx, centroidy = int(moments['m10']/moments['m00']), int(moments['m10']/moments['m00'])
Draw bounding ellipse
cv2.fitEllipse(contour)
Calculate major axis length as follows (and as shown in the figure)
MAx, MAy = int(0.5 * ellipseMajorAxisx*math.sin(ellipseAngle)), int(0.5 * ellipseMajorAxisy*math.cos(ellipseAngle))
Calculate beginning and ending x, y coordinates of the major axis
MAxtop, MAytop = int(ellipseCentrex + MAx), int(ellipseCentrey + MAy)
MAxbot, MAybot = int(ellipseCentrex - MAx), int(ellipseCentrey - MAy)
Identify which of the points is closer to the centroid of the contour
distancetop = math.sqrt((centroidx - MAxtop)**2 + (centroidy - MAytop)**2)
distancebot = math.sqrt((centroidx - MAxbot)**2 + (centroidy - MAybot)**2)
min(distancetop, distancebot)
The problem I am encountering is, while I get the "front" end of the ellipse correct most of the time, occasionally the point is a little bit away. As far as I have observed, this seems to be happening such that the x value is correct, but y value is different (in effect, I think this represents the major axis of an ellipse that is perpendicular to mine). I am not sure if this is an issue with opencv's calculation of angles or (more than likely) my calculations are incorrect. I do realize this is a complicated example, hope my figures help!
EDIT: When I get the wrong point, it is not from a perpendicular ellipse, but of a mirror image of my ellipse. And it happens with the x values too, not just y.
After following ssm's suggestion below, I am getting the desired point most of the time. The point still goes wrong occasionally, but "snaps back" into place soon after. For example, this is a few frames when this happens:
By the way, the above images are after "correcting" for angle by using this code:
if angle > 90:
angle = 180 - angle
If I do not do the correction, I get the wrong point at other times, as shown below for the same frames.
So it looks like I get it right for some angles with angle correction and the other angles without correction. How do I get all the right points in both conditions?
(White dot inside the ellipse is the centroid of the contour, whereas the dot on or outside the ellipse is the point I am getting)
I think your only problem is MAytop. You can consider doing the following:
if ycen<yc:
# switch MAytop and MAybot
temp = MAytop
MAytop = MAybot
MAybot = temp
You may have to do a similar check on the x - scale

Monte Carlo Method, Darts in overlapping area of two circles

I am trying to estimate the value of pi using a monte carlo simulation. I need to use two unit circles that are a user input distance from the origin. I understand how this problem works with a single circle, I just don't understand how I am meant to use two circles. Here is what I have got so far (this is the modified code I used for a previous problem the used one circle with radius 2.
import random
import math
import sys
def main():
numDarts=int(sys.argv[1])
distance=float(sys.argv[2])
print(montePi(numDarts,distance))
def montePi(numDarts,distance):
if distance>=1:
return(0)
inCircle=0
for I in range(numDarts):
x=(2*(random.random()))-2
y=random.random()
d=math.sqrt(x**2+y**2)
if d<=2 and d>=-2:
inCircle=inCircle+1
pi=inCircle/numDarts*4
return pi
main()
I need to change this code to work with 2 unit circles, but I do not understand how to use trigonometry to do this, or am I overthinking the problem? Either way help will be appreciated as I continue trying to figure this out.
What I do know is that I need to change the X coordinate, as well as the equation that determines "d" (d=math.sqrt(x*2+y*2)), im just not sure how.
These are my instructions-
Write a program called mcintersection.py that uses the Monte Carlo method to
estimate the area of this shape (and prints the result). Your program should take
two command-line parameters: distance and numDarts. The distance parameter
specifies how far away the circles are from the origin on the x-axis. So if distance
is 0, then both circles are centered on the origin, and completely overlap. If
distance is 0.5 then one circle is centered at (-0.5, 0) and the other at (0.5, 0). If
distance is 1 or greater, then the circles do not overlap at all! In that last case, your
program can simply output 0. The numDarts parameter should specify the number
of random points to pick in the Monte Carlo process.
In this case, the rectangle should be 2 units tall (with the top at y = 1 and the
bottom at y = -1). You could also safely make the rectangle 2 units wide, but this
will generally be much bigger than necessary. Instead, you should figure out
exactly how wide the shape is, based on the distance parameter. That way you can
use as skinny a rectangle as possible.
If I understand the problem correctly, you have two unit circles centered at (distance, 0) and (-distance, 0) (that is, one is slightly to the right of the origin and one is slightly to the left). You're trying to determine if a given point, (x, y) is within both circles.
The simplest approach might be to simply compute the distance between the point and the center of each of the circles. You've already done this in your previous code, just repeat the computation twice, once with the offset distance inverted, then use and to see if your point is in both circles.
But a more elegant solution would be to notice how your two circles intersect each other exactly on the y-axis. To the right of the axis, the left circle is completely contained within the right one. To the left of the y-axis, the right circle is entirely within the left circle. And since the shape is symmetrical, the two halves are of exactly equal size.
This means you can limit your darts to only hitting on one side of the axis, and then get away with just a single distance test:
def circle_intersection_area(num_darts, distance):
if distance >= 1:
return 0
in_circle = 0
width = 1-distance # this is enough to cover half of the target
for i in range(num_darts):
x = random.random()*width # random value from 0 to 1-distance
y = random.random()*2 - 1 # random value from -1 to 1
d = math.sqrt((x+distance)**2 + y**2) # distance from (-distance, 0)
if d <= 1:
in_circle += 1
sample_area = width * 2
target_area = sample_area * (in_circle / num_darts)
return target_area * 2 # double, since we were only testing half the target

Finding all points common to two circles

In Python, how would one find all integer points common to two circles?
For example, imagine a Venn diagram-like intersection of two (equally sized) circles, with center-points (x1,y1) and (x2,y2) and radii r1=r2. Additionally, we already know the two points of intersection of the circles are (xi1,yi1) and (xi2,yi2).
How would one generate a list of all points (x,y) contained in both circles in an efficient manner? That is, it would be simple to draw a box containing the intersections and iterate through it, checking if a given point is within both circles, but is there a better way?
Keep in mind that there are four cases here.
Neither circle intersects, meaning the "common area" is empty.
One circle resides entirely within the other, meaning the "common area" is the smaller/interior circle. Also note that a degenerate case of this is if they are the same concentric circle, which would have to be the case given the criteria that they are equal-diameter circles that you specified.
The two circles touch at one intersection point.
The "general" case where there are going to be two intersection points. From there, you have two arcs that define the enclosed area. In that case, the box-drawing method could work for now, I'm not sure there's a more efficient method for determining what is contained by the intersection. Do note, however, if you're just interested in the area, there is a formula for that.
You may also want to look into the various clipping algorithms used in graphics development. I have used clipping algorithms to solve alot of problems similar to what you are asking here.
If the locations and radii of your circles can vary with a granularity less than your grid, then you'll be checking a bunch of points anyway.
You can minimize the number of points you check by defining the search area appropriately. It has a width equal to the distance between the points of intersection, and a height equal to
r1 + r2 - D
with D being the separation of the two centers. Note that this rectangle in general is not aligned with the X and Y axes. (This also gives you a test as to whether the two circles intersect!)
Actually, you'd only need to check half of these points. If the radii are the same, you'd only need to check a quarter of them. The symmetry of the problem helps you there.
You're almost there.
Iterating over the points in the box should be fairly good, but you can do better if for the second coordinate you iterate directly between the limits.
Say you iterate along the x axis first, then for the y axis, instead of iterating between bounding box coords figure out where each circle intersects the x line, more specifically you are interested in the y coordinate of the intersection points, and iterate between those (pay attention to rounding)
When you do this, because you already know you are inside the circles you can skip the checks entirely.
If you have a lot of points then you skip a lot of checks and you might get some performance improvements.
As an additional improvement you can pick the x axis or the y axis to minimize the number of times you need to compute intersection points.
So you want to find the lattice points that are inside both circles?
The method you suggested of drawing a box and iterating through all the points in the box seems the simplest to me. It will probably be efficient, as long as the number of points in the box is comparable to the number of points in the intersection.
And even if it isn't as efficient as possible, you shouldn't try to optimize it until you have a good reason to believe it's a real bottleneck.
I assume by "all points" you mean "all pixels". Suppose your display is NX by NY pixels. Have two arrays
int x0[NY], x1[NY]; initially full of -1.
The intersection is lozenge-shaped, between two curves.
Iterate x,y values along each curve. At each y value (that is, where the curve crosses y + 0.5), store the x value in the array. If x0[y] is -1, store it in x0, else store it in x1.
Also keep track of the lowest and highest values of y.
When you are done, just iterate over the y values, and at each y, iterate over the x values between x0 and x1, that is, for (ix = x0[iy]; ix < x1[iy]; ix++) (or the reverse).
It's important to understand that pixels are not the points where x and y are integers. Rather pixels are the little squares between the grid lines. This will prevent you from having edge-case problems.

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