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Given a point in 3D space, what are the three angles (e.g. Euler angles) needed to transform a line to point to that object?
Imagine I have a line (or a box) in 3D and I want to transform its heading, pitch, and bank to point to the 3D point from the origin, what values would I use for those angles?
I can't figure out the math to calculate the angles to point to a location such as (1,2,3).
Note: Instead of "yaw, pitch, roll", I'm going to use the conventions "heading, pitch, bank" as defined by 3D Math Primer for Graphics and Game Development by Fletcher Dunn.
Firstly, notice that in a 2D coordinate system, you only need a single angle + magnitude to "point" to any point in 2D.
Similarly, in a 3D coordinate system, you only need two angles + magnitude to "point" to any point in 3D. The last angle ("bank" or "roll") does not affect the location of a point in 3D. Instead it "spins" the arrow that would point to it. If the object is 360 degrees symmetrical, you won't see spin affecting the object at all. If the object is not symmetrical (e.g. an airplane) it will affect the object (e.g. tilting one wing towards the ground and the other towards the sky).
So the original question actually becomes, "how do I find the heading angle, pitch angle, and magnitude to "point" to any point in 3D space?"
You can easily figure this out using trigonometry functions. Imagine we have the point (1,2,3) and we're trying to calculate the heading, pitch, magnitude.
For the following example, let's use this diagram, where the left axis is X, up is Y, and right is Z. The point (1,2,3), then is represented by the blue sphere.
1. Find the magnitude
First, let's find the easiest value, the magnitude. Luckily for us, the magnitude (length) between any two points is easy to find no matter how many dimensions we are in, simply by using the Pythagorean theorem. Since we are in 3D and we're calculating the distance from the origin to our point, our distance formula becomes:
magnitude = sqrt(x*x + y*y + z*z)
Plugging in our actual values:
magnitude = sqrt(1*1 + 2*2 + 3*3)
= 3.7416573868
So our magnitude (or length) is ~3.741.
2. Find the heading
Next, to find the heading, notice that we just care about rotation about the XZ plane, and we don't care about the Y-axis at all. If we were to "flatten" the 3D space into 2D, it becomes trivial to find the heading.
We can draw a triangle that forms a 90 degree angle with the X-axis (red triangle) and then calculate that angle. Recall from trigonometry tan(angle) = opposite / adjacent, and solving for angle, we get angle = arctan(opposite / adjacent).
In this case "adjacent" is a known quantity (redAdjacent = x = 1), and "opposite" is known too (redOpposite = z = 3). Instead of using arctan to solve the equation though, we want to use atan2 since it'll handle all the different cases of x and y for us.
So we have:
heading = atan2(redOpposite, redAdjacent)
Plugging in our actual values:
heading = atan2(3, 1)
= 1.249045772398
so our heading is 1.249 rad, or ~72°.
3. Find the pitch
Finally we need to find the pitch. Similarly to what we did with the heading, we can flatten the the 3D space into 2D along the plane that contains these three points: (A) the origin (0,0,0), (B) our point (1,2,3), and (C) our point as it would project onto the XZ plane (1,0,3) (e.g. by setting 0 for the Y-value).
If we draw a triangle between all 3 of these points, you will notice that they form a right-triangle again (green triangle). We can simply calculate the angle using arctan2 again.
We already calculated the green hypotenuse in step 1 (i.e. the magnitude of our vector):
greenHypotenuse = sqrt(x*x + y*y + z*z)
= 3.7416573868
We also know the opposite of the green triangle is the same as the y-value:
greenOpposite = y
= 2
Using the pythagorean theorem, we can find the length of the adjacent angle:
greenOpposite^2 + greenAdjacent^2 = greenHypotenuse^2
y*y + greenAdjacent^2 = x*x + y*y + z*z
greenAdjacent^2 = x*x + z*z
greenAdjacent = sqrt(x*x + z*z)
Notice that another way to calculate the adjacent length of the green triangle is to notice that redHypotenuse == greenAdjacent, and we could find redHypotenuse using:
redHypotenuse^2 = redAdjacent^2 + redOpposite^2
= x*x + z*z
redHypotenuse = sqrt(x*x + z*z)
Plugging in actual values, we get:
greenAdjacent = sqrt(1*1 + 3*3)
= 3.1622776602
So now that we know the adjacent and opposite lengths of the green triangle, we can use arctan2 again:
pitch = atan2(greenOpposite, greenAdjacent)
= atan2(2, 3.1622776602)
= 0.563942641356
So our pitch is 0.5634 radians, or about 32°.
Conclusion
If you were to draw a line from the origin, with length 3.741, heading 1.249 rad, and pitch 0.564 rad, it would extend from (0,0,0) to (1,2,3).
I have two rectangles where one is a clipping for the other one.
Now I want to rotate the bigger rectangle around the center of the clipping rectangle and adjust x/y values.
How can I calculate the new x/y values after rotation?
I actually just want to rotate the x/y of the bigger box around the center of the smaller box. So the x/y point of the bigger box is relative to the top/left point of the smaller box. I have the width and height of the smaller box so I can calculate x/y point of the big box relative to the center of small box. The angle to rotate is in degrees. The rotation can be any degree, for example 10.
You can do as follows:
determine the angle by which you want to rotate, make sure it suitable for the trigonometric functions (sin(), cos(), ...), i.e. right angle is usually Pi/2
in case of rotating counterclockwise, it is negative
determine the coordinates of c, as cx,cy
process each of the corners of the rectanlge, one by one, for a total of four
for each corner P, currently at coordinates px,py and to move to px2,py2
determine angle between current P and C, using atan2(py-cy, px-cx)
to get from degrees to radians (for use with trigonometry) calculate radians=(pi*degrees)/180.0
add the desired rotation angle to that current angle, to get newangle
determine the distance of current P to C, sqrt((px-cx)(px-cx) + (py-cy)(py-cy))
multiply the distance (which is not changing by rotation), with the appropriate trigonometric function
px2 = distance * cos(newangle)
py2 = distance * sin(newangle)
If you want to rotate a given point P around a point C, which are defined in the same coordinate system you can use a simple rotation matrix. Calculate the P coordinates with respect to C (subtraction), then apply rotation with the matrix and go back to original coordinates by adding C again.
All that matters is the coordinates of the rotation center and the angle.
The most compact formulation is by means of complex numbers (of which I hope you have some understanding; you actually don't need a complex data type, you can expand the formulas).
Let C be the center and α the angle. Then for any point P, the image Q is given by
Q = (P - C) cis(α) + C
where cis(α) = cos(α) + i sin(α).
The inverse rotation is simply given by
P = (Q - C) cis(-α) + C.
I have 2 circles that collide in a certain collision point and under a certain collision angle which I calculate using this formula :
C1(x1,y1) C2(x2,y2)
and the angle between the line uniting their centre and the x axis is
X = arctg (|y2 - y1| / |x2 - x1|)
and what I want is to translate the circle on top under the same angle that collided with the other circle. I mean with the angle X and I don't know what translation coordinates should I give for a proper and a straight translation!
For what I think you mean, here's how to do it cleanly.
Think in vectors.
Suppose the centre of the bottom circle has coordinates (x1,y1), and the centre of the top circle has coordinates (x2,y2). Then define two vectors
support = (x1,y1)
direction = (x2,y2) - (x1,y1)
now, the line between the two centres is fully described by the parametric representation
line = support + k*direction
with k any value in (-inf,+inf). At the initial time, substituting k=1 in the equation above indeed give the coordinates of the top circle. On some later time t, the value of k will have increased, and substituting that new value of k in the equation will give the new coordinates of the centre of the top circle.
How much k increases at value t is equal to the speed of the circle, and I leave that entirely up to you :)
Doing it this way, you never need to mess around with any angles and/or coordinate transformations etc. It even works in 3D (provided you add in z-coordinates everywhere).
Say I have an arbitrary set of latitude and longitude pairs representing points on some simple, closed curve. In Cartesian space I could easily calculate the area enclosed by such a curve using Green's Theorem. What is the analogous approach to calculating the area on the surface of a sphere? I guess what I am after is (even some approximation of) the algorithm behind Matlab's areaint function.
There several ways to do this.
1) Integrate the contributions from latitudinal strips. Here the area of each strip will be (Rcos(A)(B1-B0))(RdA), where A is the latitude, B1 and B0 are the starting and ending longitudes, and all angles are in radians.
2) Break the surface into spherical triangles, and calculate the area using Girard's Theorem, and add these up.
3) As suggested here by James Schek, in GIS work they use an area preserving projection onto a flat space and calculate the area in there.
From the description of your data, in sounds like the first method might be the easiest. (Of course, there may be other easier methods I don't know of.)
Edit – comparing these two methods:
On first inspection, it may seem that the spherical triangle approach is easiest, but, in general, this is not the case. The problem is that one not only needs to break the region up into triangles, but into spherical triangles, that is, triangles whose sides are great circle arcs. For example, latitudinal boundaries don't qualify, so these boundaries need to be broken up into edges that better approximate great circle arcs. And this becomes more difficult to do for arbitrary edges where the great circles require specific combinations of spherical angles. Consider, for example, how one would break up a middle band around a sphere, say all the area between lat 0 and 45deg into spherical triangles.
In the end, if one is to do this properly with similar errors for each method, method 2 will give fewer triangles, but they will be harder to determine. Method 1 gives more strips, but they are trivial to determine. Therefore, I suggest method 1 as the better approach.
I rewrote the MATLAB's "areaint" function in java, which has exactly the same result.
"areaint" calculates the "suface per unit", so I multiplied the answer by Earth's Surface Area (5.10072e14 sq m).
private double area(ArrayList<Double> lats,ArrayList<Double> lons)
{
double sum=0;
double prevcolat=0;
double prevaz=0;
double colat0=0;
double az0=0;
for (int i=0;i<lats.size();i++)
{
double colat=2*Math.atan2(Math.sqrt(Math.pow(Math.sin(lats.get(i)*Math.PI/180/2), 2)+ Math.cos(lats.get(i)*Math.PI/180)*Math.pow(Math.sin(lons.get(i)*Math.PI/180/2), 2)),Math.sqrt(1- Math.pow(Math.sin(lats.get(i)*Math.PI/180/2), 2)- Math.cos(lats.get(i)*Math.PI/180)*Math.pow(Math.sin(lons.get(i)*Math.PI/180/2), 2)));
double az=0;
if (lats.get(i)>=90)
{
az=0;
}
else if (lats.get(i)<=-90)
{
az=Math.PI;
}
else
{
az=Math.atan2(Math.cos(lats.get(i)*Math.PI/180) * Math.sin(lons.get(i)*Math.PI/180),Math.sin(lats.get(i)*Math.PI/180))% (2*Math.PI);
}
if(i==0)
{
colat0=colat;
az0=az;
}
if(i>0 && i<lats.size())
{
sum=sum+(1-Math.cos(prevcolat + (colat-prevcolat)/2))*Math.PI*((Math.abs(az-prevaz)/Math.PI)-2*Math.ceil(((Math.abs(az-prevaz)/Math.PI)-1)/2))* Math.signum(az-prevaz);
}
prevcolat=colat;
prevaz=az;
}
sum=sum+(1-Math.cos(prevcolat + (colat0-prevcolat)/2))*(az0-prevaz);
return 5.10072E14* Math.min(Math.abs(sum)/4/Math.PI,1-Math.abs(sum)/4/Math.PI);
}
You mention "geography" in one of your tags so I can only assume you are after the area of a polygon on the surface of a geoid. Normally, this is done using a projected coordinate system rather than a geographic coordinate system (i.e. lon/lat). If you were to do it in lon/lat, then I would assume the unit-of-measure returned would be percent of sphere surface.
If you want to do this with a more "GIS" flavor, then you need to select an unit-of-measure for your area and find an appropriate projection that preserves area (not all do). Since you are talking about calculating an arbitrary polygon, I would use something like a Lambert Azimuthal Equal Area projection. Set the origin/center of the projection to be the center of your polygon, project the polygon to the new coordinate system, then calculate the area using standard planar techniques.
If you needed to do many polygons in a geographic area, there are likely other projections that will work (or will be close enough). UTM, for example, is an excellent approximation if all of your polygons are clustered around a single meridian.
I am not sure if any of this has anything to do with how Matlab's areaint function works.
I don't know anything about Matlab's function, but here we go. Consider splitting your spherical polygon into spherical triangles, say by drawing diagonals from a vertex. The surface area of a spherical triangle is given by
R^2 * ( A + B + C - \pi)
where R is the radius of the sphere, and A, B, and C are the interior angles of the triangle (in radians). The quantity in the parentheses is known as the "spherical excess".
Your n-sided polygon will be split into n-2 triangles. Summing over all the triangles, extracting the common factor of R^2, and bringing all of the \pi together, the area of your polygon is
R^2 * ( S - (n-2)\pi )
where S is the angle sum of your polygon. The quantity in parentheses is again the spherical excess of the polygon.
[edit] This is true whether or not the polygon is convex. All that matters is that it can be dissected into triangles.
You can determine the angles from a bit of vector math. Suppose you have three vertices A,B,C and are interested in the angle at B. We must therefore find two tangent vectors (their magnitudes are irrelevant) to the sphere from point B along the great circle segments (the polygon edges). Let's work it out for BA. The great circle lies in the plane defined by OA and OB, where O is the center of the sphere, so it should be perpendicular to the normal vector OA x OB. It should also be perpendicular to OB since it's tangent there. Such a vector is therefore given by OB x (OA x OB). You can use the right-hand rule to verify that this is in the appropriate direction. Note also that this simplifies to OA * (OB.OB) - OB * (OB.OA) = OA * |OB| - OB * (OB.OA).
You can then use the good ol' dot product to find the angle between sides: BA'.BC' = |BA'|*|BC'|*cos(B), where BA' and BC' are the tangent vectors from B along sides to A and C.
[edited to be clear that these are tangent vectors, not literal between the points]
Here is a Python 3 implementation, loosely inspired by the above answers:
def polygon_area(lats, lons, algorithm = 0, radius = 6378137):
"""
Computes area of spherical polygon, assuming spherical Earth.
Returns result in ratio of the sphere's area if the radius is specified.
Otherwise, in the units of provided radius.
lats and lons are in degrees.
"""
from numpy import arctan2, cos, sin, sqrt, pi, power, append, diff, deg2rad
lats = np.deg2rad(lats)
lons = np.deg2rad(lons)
# Line integral based on Green's Theorem, assumes spherical Earth
#close polygon
if lats[0]!=lats[-1]:
lats = append(lats, lats[0])
lons = append(lons, lons[0])
#colatitudes relative to (0,0)
a = sin(lats/2)**2 + cos(lats)* sin(lons/2)**2
colat = 2*arctan2( sqrt(a), sqrt(1-a) )
#azimuths relative to (0,0)
az = arctan2(cos(lats) * sin(lons), sin(lats)) % (2*pi)
# Calculate diffs
# daz = diff(az) % (2*pi)
daz = diff(az)
daz = (daz + pi) % (2 * pi) - pi
deltas=diff(colat)/2
colat=colat[0:-1]+deltas
# Perform integral
integrands = (1-cos(colat)) * daz
# Integrate
area = abs(sum(integrands))/(4*pi)
area = min(area,1-area)
if radius is not None: #return in units of radius
return area * 4*pi*radius**2
else: #return in ratio of sphere total area
return area
Please find a somewhat more explicit version (and with many more references and TODOs...) here.
You could also have a look at this code of the spherical_geometry package: Here and here. It does provide two different methods for calculating the area of a spherical polygon.
I'm trying to make a triangle (isosceles triangle) to move around the screen and at the same time slightly rotate it when a user presses a directional key (like right or left).
I would like the nose (top point) of the triangle to lead the triangle at all times. (Like that old asteroids game).
My problem is with the maths behind this. At every X time interval, I want the triangle to move in "some direction", I need help finding this direction (x and y increments/decrements).
I can find the center point (Centroid) of the triangle, and I have the top most x an y points, so I have a line vector to work with, but not a clue as to "how" to work with it.
I think it has something to do with the old Sin and Cos methods and the amount (angle) that the triangle has been rotated, but I'm a bit rusty on that stuff.
Any help is greatly appreciated.
The arctangent (inverse tangent) of vy/vx, where vx and vy are the components of your (centroid->tip) vector, gives you the angle the vector is facing.
The classical arctangent gives you an angle normalized to -90° < r < +90° degrees, however, so you have to add or subtract 90 degrees from the result depending on the sign of the result and the sign of vx.
Luckily, your standard library should proive an atan2() function that takes vx and vy seperately as parameters, and returns you an angle between 0° and 360°, or -180° and +180° degrees. It will also deal with the special case where vx=0, which would result in a division by zero if you were not careful.
See http://www.arctangent.net/atan.html or just search for "arctangent".
Edit: I've used degrees in my post for clarity, but Java and many other languages/libraries work in radians where 180° = π.
You can also just add vx and vy to the triangle's points to make it move in the "forward" direction, but make sure that the vector is normalized (vx² + vy² = 1), else the speed will depend on your triangle's size.
#Mark:
I've tried writing a primer on vectors, coordinates, points and angles in this answer box twice, but changed my mind on both occasions because it would take too long and I'm sure there are many tutorials out there explaining stuff better than I ever can.
Your centroid and "tip" coordinates are not vectors; that is to say, there is nothing to be gained from thinking of them as vectors.
The vector you want, vForward = pTip - pCentroid, can be calculated by subtracting the coordinates of the "tip" corner from the centroid point. The atan2() of this vector, i.e. atan2(tipY-centY, tipX-centX), gives you the angle your triangle is "facing".
As for what it's relative to, it doesn't matter. Your library will probably use the convention that the increasing X axis (---> the right/east direction on presumably all the 2D graphs you've seen) is 0° or 0π. The increasing Y (top, north) direction will correspond to 90° or (1/2)π.
It seems to me that you need to store the rotation angle of the triangle and possibly it's current speed.
x' = x + speed * cos(angle)
y' = y + speed * sin(angle)
Note that angle is in radians, not degrees!
Radians = Degrees * RadiansInACircle / DegreesInACircle
RadiansInACircle = 2 * Pi
DegressInACircle = 360
For the locations of the vertices, each is located at a certain distance and angle from the center. Add the current rotation angle before doing this calculation. It's the same math as for figuring the movement.
Here's some more:
Vectors represent displacement. Displacement, translation, movement or whatever you want to call it, is meaningless without a starting point, that's why I referred to the "forward" vector above as "from the centroid," and that's why the "centroid vector," the vector with the x/y components of the centroid point doesn't make sense. Those components give you the displacement of the centroid point from the origin. In other words, pOrigin + vCentroid = pCentroid. If you start from the 0 point, then add a vector representing the centroid point's displacement, you get the centroid point.
Note that:
vector + vector = vector
(addition of two displacements gives you a third, different displacement)
point + vector = point
(moving/displacing a point gives you another point)
point + point = ???
(adding two points doesn't make sense; however:)
point - point = vector
(the difference of two points is the displacement between them)
Now, these displacements can be thought of in (at least) two different ways. The one you're already familiar with is the rectangular (x, y) system, where the two components of a vector represent the displacement in the x and y directions, respectively. However, you can also use polar coordinates, (r, Θ). Here, Θ represents the direction of the displacement (in angles relative to an arbitary zero angle) and r, the distance.
Take the (1, 1) vector, for example. It represents a movement one unit to the right and one unit upwards in the coordinate system we're all used to seeing. The polar equivalent of this vector would be (1.414, 45°); the same movement, but represented as a "displacement of 1.414 units in the 45°-angle direction. (Again, using a convenient polar coordinate system where the East direction is 0° and angles increase counter-clockwise.)
The relationship between polar and rectangular coordinates are:
Θ = atan2(y, x)
r = sqrt(x²+y²) (now do you see where the right triangle comes in?)
and conversely,
x = r * cos(Θ)
y = r * sin(Θ)
Now, since a line segment drawn from your triangle's centroid to the "tip" corner would represent the direction your triangle is "facing," if we were to obtain a vector parallel to that line (e.g. vForward = pTip - pCentroid), that vector's Θ-coordinate would correspond to the angle that your triangle is facing.
Take the (1, 1) vector again. If this was vForward, then that would have meant that your "tip" point's x and y coordinates were both 1 more than those of your centroid. Let's say the centroid is on (10, 10). That puts the "tip" corner over at (11, 11). (Remember, pTip = pCentroid + vForward by adding "+ pCentroid" to both sides of the previous equation.) Now in which direction is this triangle facing? 45°, right? That's the Θ-coordinate of our (1, 1) vector!
keep the centroid at the origin. use the vector from the centroid to the nose as the direction vector. http://en.wikipedia.org/wiki/Coordinate_rotation#Two_dimensions will rotate this vector. construct the other two points from this vector. translate the three points to where they are on the screen and draw.
double v; // velocity
double theta; // direction of travel (angle)
double dt; // time elapsed
// To compute increments
double dx = v*dt*cos(theta);
double dy = v*dt*sin(theta);
// To compute position of the top of the triangle
double size; // distance between centroid and top
double top_x = x + size*cos(theta);
double top_y = y + size*sin(theta);
I can see that I need to apply the common 2d rotation formulas to my triangle to get my result, Im just having a little bit of trouble with the relationships between the different components here.
aib, stated that:
The arctangent (inverse tangent) of
vy/vx, where vx and vy are the
components of your (centroid->tip)
vector, gives you the angle the vector
is facing.
Is vx and vy the x and y coords of the centriod or the tip? I think Im getting confused as to the terminology of a "vector" here. I was under the impression that a Vector was just a point in 2d (in this case) space that represented direction.
So in this case, how is the vector of the centroid->tip calculated? Is it just the centriod?
meyahoocomlorenpechtel stated:
It seems to me that you need to store
the rotation angle of the triangle and
possibly it's current speed.
What is the rotation angle relative to? The origin of the triangle, or the game window itself? Also, for future rotations, is the angle the angle from the last rotation or the original position of the triangle?
Thanks all for the help so far, I really appreciate it!
you will want the topmost vertex to be the centroid in order to achieve the desired effect.
First, I would start with the centroid rather than calculate it. You know the position of the centroid and the angle of rotation of the triangle, I would use this to calculate the locations of the verticies. (I apologize in advance for any syntax errors, I have just started to dabble in Java.)
//starting point
double tip_x = 10;
double tip_y = 10;
should be
double center_x = 10;
double center_y = 10;
//triangle details
int width = 6; //base
int height = 9;
should be an array of 3 angle, distance pairs.
angle = rotation_angle + vertex[1].angle;
dist = vertex[1].distance;
p1_x = center_x + math.cos(angle) * dist;
p1_y = center_y - math.sin(angle) * dist;
// and the same for the other two points
Note that I am subtracting the Y distance. You're being tripped up by the fact that screen space is inverted. In our minds Y increases as you go up--but screen coordinates don't work that way.
The math is a lot simpler if you track things as position and rotation angle rather than deriving the rotation angle.
Also, in your final piece of code you're modifying the location by the rotation angle. The result will be that your ship turns by the rotation angle every update cycle. I think the objective is something like Asteroids, not a cat chasing it's tail!