I've written a a little function that gives me out a value based on a sine wave when I put in a float between 0 and 1. I'm using it to lerp things around in a game.
public static class Utilities
{
public static float SineMe(float prop)
{
float output = (prop*180f)-90f;
output = Mathf.Sin(output*Mathf.Deg2Rad);
output = (output+1f)/2f;
return output;
}
}
It works fine.. But I was wondering is there a mathematical way of altering the sine wave so I can make it 'steeper' or 'shallower' in the middle?
In the diagram below the blue curve is a sine wave, I'm wondering if I can make it more like the green line.
What you're showing already isn't really sine - the range of sine is between -1 and +1. You're applying the linear function f(x) = (x+1)/2 to change that range. So place another function between the sine and that transform.
To change the shape, you need a non-linear function. So, here's a cubic equation you might try...
g(x) = Ax^3 + Bx^2 + Cx + D
D = 0
C = p
B = 3 - 3C
A = 1 - (B + C)
The parameter p should be given a value between 0.0 and 9.0. If it's 1.0, g(x) is the identity function (the output is the unmodified input). With values between 0.0 and 1.0, it will tend to "fatten" your sine wave (push it away from 0.0 and towards 1.0 or -1.0) which is what you seem to require.
I once "designed" this function as a way to get "fractal waveforms". Using values of p between 1.0 and 9.0 (and particularly between around 3.0 and 6.0) iterative application of this formula is chaotic. I stole the idea from the population fluctuation modelling chaotic function by R. M. May, but that's a quadratic - I wanted something symmetric, so I needed a cubic function. Not really relevant here, and a pretty aweful idea as it happens. Although you certainly get chaotic waveforms, what that really means is huge problems with aliassing - change the sample rate and you get a very different sound. Still, without the iteration, maybe this will give you what you need.
If you iterate enough times with p between 0.0 and 1.0, you end up with a square wave with slightly rounded corners.
Most likely you can just choose a value of p between 0.0 and 1.0, apply that function once, then apply your function to change the range and you'll get what you want.
By the way, there's already a comment suggesting a cheat sheet of "easing functions". "Easing" is a term from animation, and computer animation software often uses Bezier curves for that purpose - the same Bezier curves that vector graphics software often uses. Bezier curves come in quadratic and cubic variants, with cubic being the more common. So what this is doing probably isn't that different. However, cubic Bezier easing gives you more control - you can control the "ease-in" independently of the "ease-out", where my function only provides one parameter.
You can use the y(x) = 1-(1-x)^n function when x = [0..1], as a transform function.
You will just have to replace x by the absolute value of your sinus and report the sign of sinus to the result. In that way you can tweak the sinus slope by increasing n. So what you want is this:
float sinus = Mathf.Sin(output*Mathf.Deg2Rad);
int sign = (sinus >= 0 ? 1 : -1);
int n = 4; // slope parameter
float waveform = sign * ( 1-Mathf.Pow(1-Mathf.Abs(sinus), n) );
You can root the sine function to make it steeper (only working for positive values). The higher the root, the steeper the sine.
Graph of a steeper sine wave function
I discovered this nifty trick for a steeper sine wave (0..1).
f(x) = cos(sin(x)^3)^10
If you need (-1..1):
2 * (f(x) - 0.5)
I think I found the solution.
(0.5+sin(x*π-π/2)/2)^((2*(1-x))^k)
in the interval x = [0.0, 1.0]
with k that control the steepness.
k=0.0 for the unmodified sinus (purple)
k=1.0 (green)
k=2.0 (blue)
https://www.desmos.com/calculator/wdtfsassev
I was looking for a similar function, not for the whole sine but just half the period.
I bumped into the Logistic function:
f(x) = L / (1 + e^(-k(x-x0)))
where
e = the natural logarithm base (also known as Euler's number),
x0 = the x-value of the sigmoid's midpoint,
L = the curve's maximum value, and
k = the steepness of the curve.
See https://en.wikipedia.org/wiki/Logistic_function
Works for me
what about
sign(sin(x))*sqrt(abs(sin(x))
https://www.desmos.com/calculator/5nn34xqkfr
Related
I am given 3 values y0, y1, y2. They are supposed to be evenly spaced, say x0 = -0.5, x1 = 0.5, x2 = 1.5. And to be able to draw a spline through all of them, the derivatives at all points are said to be dy/dx = 0.
Now the result of rendering two Catmull-Rom-Splines (which is done via GLSL fragment shader, including a nonlinear transformation) looks pretty rigit. I.e. where the curve bends, it does so smoothly, though, but the bending area is very small. Zooming out makes the bends look too sharp.
I wanted to switch to TCB-Splines (aka. Kochanek-Bartels Splines), as those provide a tension parameter - thus I hoped I could smooth the look. But I realized that all TCB-Parameters applied to a zero tangent won't do any good.
Any ideas how I could get a smoother looking curve?
The tangent vector for a 2d parametric curve f(t)=(x(t), y(t)) is defined as f'(t)=(dx(t)/dt, dy(t)/dt). When you require your curve to have dy/dx = 0 at some points, it simply means the tangent vector at those points will go horizontally (i.e., dy/dt = 0). It does not necessarily mean the tangent vector itself is a zero vector. So, you should still be able to use TCB spline to do whatever you want to do.
Obviously nobody had a good answer, but as it's my job, I found a solution: The Points are evenly spaced, and the idea is to make transitions smoother. Now it's given, that the tangents are zero at all given Points, so it is most likely that close to the points we get the strongest curvature y''(x). This means, we'd like to stretch these "areas around the points".
Considering that currently we use Catmull-Rom-Splines, sectioned between the points. That makes y(x) => y(t) , t(x) = x-x0.
This t(x) needs to be stretched around the 0- and the 1-areas. So the cosine function jumped into my mind:
Replacing t(x) = x-x0 with t(x) = 0.5 * (1.0 - cos( PI * ( x-x0 ) ) did the job for me.
Short explanation:
cosine in the range [0,PI] runs smoothly from 1 to -1.
we want to run from 0 to 1, though
so flip it: 1-cos() -> now it runs from 0 to 2
halve that: 0.5*xxx -> now it runs from 0 to 1
Another problem was to find the correct tangents. Normally, calculating such a spline using Matrix-Vector-Math, you simply derive your t-vector to get the tangents, so deriving [t³ t² t 1] yields [3t² 2t 1 0]. But here, t is not simple. Using this I found the right derived vector:
| 0.375*PI*sin(PI*t)(1-cos(PI*t))² |
| 0.500*PI*sin(PI*t)(1-cos(PI*t)) |
| 0.500*PI*sin(PI*t) |
| 0 |
I've been trying to get the correct normals for a sphere I'm messing with using a vertex shader. The algorithm can be boiled down simply to
vert.xyz += max(0, sin(time + 0.004*vert.x))*10*normal.xyz
This causes a wave to roll across the sphere.
In order to make my normals correct, I need to transform them as well. I can take the tangent vector at a given x,y,z, get a perpendicular vector (0, -vert.z, vert.y), and then cross the tangent with the perp vector.
I've been having some issue with the math though, and it's become a personal vendetta at this point. I've solved for the derivative hundreds of times but I keep getting it incorrect. How can I get the tangent?
Breaking down the above line, I can make a math function
f(x,y,z) = max(0, sin(time + 0.004*x))*10*Norm(x,y,z) + (x,y,z)
where Norm(..) is Normalize((x,y,z) - CenterOfSphere)
After applying f(x,y,z), unchanged normals
What is the correct f '(x,y,z)?
I've accounted for the weirdness caused by the max in f(...), so that's not the issue.
Edit: The most successful algorithm I have right now is as follows:
Tangent vector.x = 0.004*10*cos(0.004*vert.x + time)*norm.x + 10*sin(0.004*vert.x + time) + 1
Tangent vector.y = 10*sin(0.004*vert.x + time) + 1
Tangent vector.z = 10*sin(0.004*vert.x + time) + 1
2nd Tangent vector.x = 0
2nd Tangent vector.y = -norm.z
2nd Tangent vector.z = norm.y
Normalize both, and perform Cross(Tangent2, Tangent1). Normalize again, and done (it should be Cross(Tangent1, Tangent2), but this seems to have better results... more hints of an issue in my math!).
This yields this
Get tangent/normal by derivate of function can sometimes fail if your surface points are nonlinearly distributed and or some math singularity is present or if you make a math mistake (which is the case in 99.99%). Anyway you can always use the geometric approach:
1. you can get the tangents easy by
U(x,y,z)=f(x+d,y,z)-f(x,y,z);
V(x,y,z)=f(x,y+d,z)-f(x,y,z);
where d is some small enough step
and f(x,y,z) is you current surface point computation
not sure why you use 3 input variables I would use just 2
but therefore if the shifted point is the same as unshifted
use this instead =f(x,y,z+d)-f(x,y,z);
at the end do not forget to normalize U,V size to unit vector
2. next step
if bullet 1 leads to correct normals
then you can simply solve the U,V algebraically
so rewrite U(x,y,z)=f(x+d,y,z)-f(x,y,z); to full equation
by substituting f(x,y,z) with the surface point equation
and simplify
[notes]
sometimes well selected d can simplify normalization to multipliyng by a constant
you should add normals visualization for example like this:
to actually see what is really happening (for debug purposses)
I'm learning Unity3d + some basic maths I've forgotten by messing around.
Heres what I'm doing now..
As you can probably tell the sides of this shape form a parabola.
The distance they are out from the centre is the base radius + the height squared * by a constant (0.05 in this image)
The code generating this is very simple..
for (int changer = 1; changer > -2; changer-=2) {
Vector3 newPos = new Vector3(
transform.position.x
,transform.position.y + currentheight*changer
,transform.position.z - RadiusAtZero -(Mathf.Pow(currentheight,2)*CurveMultiplier)
);
var newFleck = Instantiate(Fleck, newPos, Quaternion.identity)as GameObject;
newFleck.transform.RotateAround(transform.position,Vector3.up,angle*changer);
FleckList.Add(newFleck );
}
Btw the for loop and 'changer' mirror everything so 'currentheight' is really just the distance from the centreline of the parabola.
Anyway I'd like to make the cubes (or flecks as I've called them) be angled so that they are tangentional to the parabola I have made.
I need to determine the angle of a tangent to the parabola at particular point.
I found this
to find the line tangent to y=x^2 -3 at (1, -2) we can simultaneously solve
y=x^2 -3 and y+2=m(x-1) and set the discriminant equal to zero
But I dont know how to implement this. Also I reckon my 'CurveMultiplier' constant makes my parabola equation different from that one.
Can someone write some code that determines the angle? (and also maybe explain it)
Update.
Here is fixed version using the derivative of the equation. (Also I have changed from boxes to tetrahedrons and few other superficial things)
The easiest solution is to use a derivative for the parabolic equation.
In your picture then I'll assume Y is vertical, X horizontal, and Z in/out of the screen. Then the parabola being rotated, based upon your description, is:
f(h) = 0.05*h^2 + R
(h is height, R is base radius). If you imagine a plane containing the Y axis, you can rotate the plane around the Y axis at any angle and the dual parabola looks the same.
The derivative of a parabolic equation of the form f(x) = C*h^2 + R is f'(x) = 2*C*h, which is the slope of the tangent at h. In this specific case, that would be:
f'(h) = 0.1*h
Since the cross-sectional plane has an angle relative to X and Z axes, then that tangent will also have the same angular component (you have a rotated parabola).
Depending upon the units given for the constants in f(h), particularly the 0.05 value, you may have to adjust this for the correct results.
I would like to draw an animation of a polar curve (a spiral) being graphed. I am using javascript and canvas. Currently, I am using setInterval to call a draw function, which graphs an x and y coordinate found from a parametric representation of the polar curve (x and y in terms of theta). I am incrementing theta by 0.01, from 0 to 2*pi, once for every call to draw(). The problem is that I wish for the animation to draw the same amount of the curve for each call to draw, so that the drawing appears to progress with uniform speed. It doesn't matter if the time between each call to draw is different; I just need the speed (in terms of pixels drawn / # of calls to draw) to be constant for the entire awing. In other words, I need the arc length of the segment of the polar graph drawn for each call to draw to be the same. I have no idea how to go about this. Any help/sugestions would be greatly appreciated. Thanks
Let f(z) be the theta variable you are referring to in your question. Here are two parametric equations that should be very similar to what you have:
x(f(z)) = f(z)cos(f(z))
y(f(z)) = f(z)sin(f(z))
We can define the position p(f(z)) at f(z) as
p(f(z)) = [x(f(z)), y(f(z))]
The speed s(f(z)) at f(z) is the length of the derivative of p at f(z).
x'(f(z)) = f'(z)cos(f(z)) - f(z)f'(z)sin(f(z))
y'(f(z)) = f'(z)sin(f(z)) + f(z)f'(z)cos(f(z))
s(f(z)) = length(p'(f(z))) = length([x'(f(z)), y'(f(z))])
= length([f'(z)cos(f(z)) - f(z)f'(z)sin(f(z)), f'(z)sin(f(z)) + f(z)f'(z)cos(f(z))])
= sqrt([f'(z)cos(f(z))]2 + [f(z)f'(z)sin(f(z))]2 + [f'(z)sin(f(z))]2 + [f(z)f'(z)cos(f(z))]2)
= sqrt(f'(z) + [f(z)f'(z)]2)
If you want the speed s(f(z)) to be constant at C as z increases at a constant rate of 1, you need to solve this first-order nonlinear ordinary differential equation:
s(f(z)) = sqrt(f'(z) + [f(z)f'(z)]2) = C
http://www.wolframalpha.com/input/?i=sqrt%28f%27%28z%29+%2B+%5Bf%28z%29f%27%28z%29%5D%5E2%29+%3D+C
Solving this would give you a function theta = f(z) that you could use to compute theta as you keep increasing z. However, this differential equation has no closed form solution.
In other words, you'll have to make guesses at how much you should increase theta at each step, doing binary search on the delta to add to theta and line integrals over p(t) to evaluate how far each guess moves.
Easier method - change the parameter to setInterval proportional to the step arc length. That way you don't have to try to invert the arc length equation. If the interval starts getting too large, you can adjust the step size, but you can do so approximately.
I am looking for an (almost everywhere) differentiable function f(p1, p2, p3, p4) that given four points will give me a scale-agnostic measure for co-planarity. It is zero if the four points lie on the same plane and positive otherwise. Scale-agnostic means that, when I uniformly scale all points the planarity measure will return the same.
I came up with something that is quite complex and not easy to optimize. Define u=p2-p1, v=p3-p1, w=p4-p1. Then the planarity measure is:
[(u x v) * w]² / (|u x v|² |w|²)
where x means cross product and '*' means dot product.
The numerator is simply (the square of) the volume of the tetrahedron defined by the four points, and the denominator is a normalizing factor that makes this measure become simply the cosine of an angle. Because angles do not changed under uniform scale, this function satisfies all my requirements.
Does anybody know of something simpler?
Alex.
Edit:
I eventually used an Augmented Lagrangian method to perform optimization, so I don't need it to be scale agnostic. Just using the constraint (u x v) * w = 0 is enough, as the optimization procedure finds the correct Lagrange multiplier to compensate for the scale.
Your methods seems ok, I'd do something like this for efficient implementation:
Take u, v, w as you did
Normalize them: various tricks exist to evaluate the inverse square root efficiently with whatever precision you want, like this jewel. Most modern processors have builtins for this operation.
Take f = |det(u, v, w)| ( = (u x v) . w ). There are fast direct implementations for 3x3 matrices; see #batty's answer to this question.
This amounts to what you do without the squares. It is still homogeneous and almost everywhere differentiable. Take the square of the determinant if you want something differentiable everywhere.
EDIT: #phkahler implicitly suggested using the ratio of the radius of the inscribed sphere to the radius of the circumscribed sphere as a measure of planarity. This is a bounded differentiable function of the points, invariant by scaling. However, this is at least as difficult to compute as what you (and I) suggest. Especially computing the radius of the circumscribed sphere is very sensitive to roundoff errors.
A measure that should be symmetric with respect to point reorderings is:
((u x v).w)^2/(|u||v||w||u-v||u-w||v-w|)
which is proportional to the volume of the tetrahedron squared divided by all 6 edge lengths. It is not simpler than your formula or Alexandre C.'s, but it is not much more complicated. However, it does become unnecessarily singular when any two points coincide.
A better-behaved, order-insensitive formula is:
let a = u x v
b = v x w
c = w x u
(a.w)^2/(|a| + |b| + |c| + |a+b+c|)^3
which is something like the volume of the tetrahedron divided by the surface area, but raised to appropriate powers to make the whole thing scale-insensitive. This is also a bit more complex than your formula, but it works unless all 4 points are collinear.
How about
|(u x v) * w| / |u|^3
(and you can change |x| to (x)^2 if you think it's simpler).