What is another way to solve this quadratic problem within CPLEX? - dynamic-programming

I would like to know if there is another form of coding that could be used (within CPLEX) to have the same results as in the code below:
dvar int+ n[1..2];
dexpr float z = - 3*n[1]^2 - 4*n[2]^2 - 4*n[1]*n[2]
+ 5000*n[1] + 2000*n[2];
maximize z;
subject to {
ct1: - 7*n[1] - 2*n[2] <= -3000;
ct2: - 5 * n[1] - 3 *n[2] <= -2000;
}

within CPLEX you could also use Constraint Programming:
using CP;
dvar int+ n[1..2] in 0..10000;
dexpr float z = - 3*n[1]^2 - 4*n[2]^2 - 4*n[1]*n[2]
+ 5000*n[1] + 2000*n[2];
maximize z;
subject to {
ct1: - 7*n[1] - 2*n[2] <= -3000;
ct2: - 5 * n[1] - 3 *n[2] <= -2000;
}
gives the same result but relies on CPOptimizer

Related

Is there a way to prevent quaternions from misbehaving?

I am working on a game engine, and I ran into this problem when creating a position rotation scale component. The position and scale work just fine, but when I recalculate the rotation quaternion it will invert itself (i.e. point in the opposite direction). What we do is simple -
Whenever the parent quaternion is changed:
We rotate the parent accordingly - Fine
We calculate the child's local rotation (relative to parent) - Fine
We multiply the parent rotation by the child's local rotation - Not fine.
What we are doing is literally (q2/q1)*q2 -> q2*q1^-1*q2
I am using the http://www.technologicalutopia.com/sourcecode/xnageometry/quaternion.cs.htm implementation, where multiplying quaternions will rotate the first by the second, and dividing does the inverse.
I have spent weeks on this problem, so any help is appreciated. :)
There appears to be an error in the CreateFromRotationMatrix method code in the link you posted. My calculations show that all of the difference calculations have the wrong sign. The corrected code would be this, changes where annotated:
public static Quaternion CreateFromRotationMatrix(Matrix matrix)
{
double num8 = (matrix.M11 + matrix.M22) + matrix.M33;
Quaternion quaternion;
if (num8 > 0.0)
{
double num = (double)sqrt((double)(num8 + 1.0));
quaternion.W = num * 0.5;
num = 0.5 / num;
quaternion.X =-(matrix.M23 - matrix.M32) * num; // -
quaternion.Y =-(matrix.M31 - matrix.M13) * num; // -
quaternion.Z =-(matrix.M12 - matrix.M21) * num; // -
return quaternion;
}
if ((matrix.M11 >= matrix.M22) && (matrix.M11 >= matrix.M33))
{
double num7 = (double)sqrt((double)(((1.0 + matrix.M11) - matrix.M22) - matrix.M33));
double num4 = 0.5 / num7;
quaternion.X = 0.5 * num7;
quaternion.Y = (matrix.M12 + matrix.M21) * num4;
quaternion.Z = (matrix.M13 + matrix.M31) * num4;
quaternion.W =-(matrix.M23 - matrix.M32) * num4; // -
return quaternion;
}
if (matrix.M22 > matrix.M33)
{
double num6 = (double)sqrt((double)(((1.0 + matrix.M22) - matrix.M11) - matrix.M33));
double num3 = 0.5 / num6;
quaternion.X = (matrix.M21 + matrix.M12) * num3;
quaternion.Y = 0.5 * num6;
quaternion.Z = (matrix.M32 + matrix.M23) * num3;
quaternion.W =-(matrix.M31 - matrix.M13) * num3; // -
return quaternion;
}
double num5 = (double)sqrt((double)(((1.0 + matrix.M33) - matrix.M11) - matrix.M22));
double num2 = 0.5 / num5;
quaternion.X = (matrix.M31 + matrix.M13) * num2;
quaternion.Y = (matrix.M32 + matrix.M23) * num2;
quaternion.Z = 0.5 * num5;
quaternion.W =-(matrix.M12 - matrix.M21) * num2; // -
return quaternion;
}
A sample run with a MATLAB mex file (qstuff) as a driver:
>> q2
q2 =
0.531932290454131 -0.391764141068189 0.538459173155997 0.523097137240767
>> qstuff('CreateFromRotationMatrix',qstuff('ToMatrix',q2))
ans =
0.531932290454131 0.391764141068189 -0.538459173155998 -0.523097137240767
>> qstuff('CreateFromRotationMatrixNew',qstuff('ToMatrix',q2))
ans =
0.531932290454131 -0.391764141068189 0.538459173155998 0.523097137240767
The original code doesn't reproduce the quaternion, but the corrected code does.

Math.Net Exponential Moving Average

I'm using simple moving average in Math.Net, but now that I also need to calculate EMA (exponential moving average) or any kind of weighted moving average, I don't find it in the library.
I looked over all methods under MathNet.Numerics.Statistics and beyond, but didn't find anything similar.
Is it missing in library or I need to reference some additional package?
I don't see any EMA in MathNet.Numerics, however it's trivial to program. The routine below is based on the definition at Investopedia.
public double[] EMA(double[] x, int N)
{
// x is the input series
// N is the notional age of the data used
// k is the smoothing constant
double k = 2.0 / (N + 1);
double[] y = new double[x.Length];
y[0] = x[0];
for (int i = 1; i < x.Length; i++) y[i] = k * x[i] + (1 - k) * y[i - 1];
return y;
}
Occasionally I found this package: https://daveskender.github.io/Stock.Indicators/docs/INDICATORS.html It targets to the latest .NET framework and has very detailed documents.
Try this:
public IEnumerable<double> EMA(IEnumerable<double> items, int notationalAge)
{
double k = 2.0d / (notationalAge + 1), prev = 0.0d;
var e = items.GetEnumerator();
if (!e.MoveNext()) yield break;
yield return prev = e.Current;
while(e.MoveNext())
{
yield return prev = (k * e.Current) + (1 - k) * prev;
}
}
It will still work with arrays, but also List, Queue, Stack, IReadOnlyCollection, etc.
Although it's not explicitly stated I also get the sense this is working with money, in which case it really ought to use decimal instead of double.

Mathematics - Distribute a list of numbers over an interval

My problem is simple.
I am searching a mathematical function to distribute number over an interval.
For example I have this list :
[2; 4; 9; 14]
And in my case I wish
2 -> 1 = f(2)
14 -> 20 = f(14)
4 -> f(4) = ?
9 -> f(9) = ?
This is just an example I am searching for f(x).
Someone would have any idea ?
Thanks for advance ! :)
If you want a linear function, then:
f(x) = lowerFunc + (x - lowerX) * (upperFunc - lowerFunc) / (upperX - lowerX),
where:
lowerFunc: function value at the lower end
upperFunc: function value at the upper end
lowerX: x parameter at the lower end
upperX: x parameter at the upper end.
For your example:
f(x) = 1 + (x - 2) * (20 - 1) / (14 - 2)
= 1 + (x - 2) * 19/12
f(2) = 1
f(4) = 4.1666
f(9) = 12.08333
f(14) = 20

Matlab Integration of exponential function

clear all
clc
syms x;
A=(x^3)/(exp(x)-1);
B=int(A,0,1)
When I run this code then it shows an expression like below
B =
log(1 - exp(1)) + 3*polylog(2, exp(1)) - 6*polylog(3, exp(1)) + 6*polylog(4, exp(1)) - limit(x^3*log(1 - exp(x)) + 6*polylog(4, exp(x)) + 3*x^2*polylog(2, exp(x)) - x^4/4 - 6*x*polylog(3, exp(x)), x == 0, Right) - 1/4
What is the polylog in the expression. But, i need one definite value, Is there any way to solve this issue so that i get a value. please anyone help me......
X = eps:0.01:1;
Y = (X.^3)./(exp(X)-1.0);
Z = trapz(X,Y);

How do I convert the 2 control points of a cubic curve to the single control point of a quadratic curve?

Having searched the web, I see various people in various forums alluding to approximating a cubic curve with a quadratic one. But I can't find the formula.
What I want is this:
input: startX, startY, control1X, control1Y, control2X, control2Y, endX, endY
output: startX, startY, controlX, controlY, endX, endY
Actually, since the starting and ending points will be the same, all I really need is...
input: startX, startY, control1X, control1Y, control2X, control2Y, endX, endY
output: controlX, controlY
As mentioned, going from 4 control points to 3 is normally going to be an approximation. There's only one case where it will be exact - when the cubic bezier curve is actually a degree-elevated quadratic bezier curve.
You can use the degree elevation equations to come up with an approximation. It's simple, and the results are usually pretty good.
Let's call the control points of the cubic Q0..Q3 and the control points of the quadratic P0..P2. Then for degree elevation, the equations are:
Q0 = P0
Q1 = 1/3 P0 + 2/3 P1
Q2 = 2/3 P1 + 1/3 P2
Q3 = P2
In your case you have Q0..Q3 and you're solving for P0..P2. There are two ways to compute P1 from the equations above:
P1 = 3/2 Q1 - 1/2 Q0
P1 = 3/2 Q2 - 1/2 Q3
If this is a degree-elevated cubic, then both equations will give the same answer for P1. Since it's likely not, your best bet is to average them. So,
P1 = -1/4 Q0 + 3/4 Q1 + 3/4 Q2 - 1/4 Q3
To translate to your terms:
controlX = -0.25*startX + .75*control1X + .75*control2X -0.25*endX
Y is computed similarly - the dimensions are independent, so this works for 3d (or n-d).
This will be an approximation. If you need a better approximation, one way to get it is by subdividing the initial cubic using the deCastlejau algorithm, and then degree-reduce each segment. If you need better continuity, there are other approximation methods that are less quick and dirty.
The cubic can have loops and cusps, which quadratic cannot have. This means that there are not simple solutions nearly never. If cubic is already a quadratic, then the simple solution exists. Normally you have to divide cubic to parts that are quadratics. And you have to decide what are the critical points for subdividing.
http://fontforge.org/bezier.html#ps2ttf says:
"Other sources I have read on the net suggest checking the cubic spline for points of inflection (which quadratic splines cannot have) and forcing breaks there. To my eye this actually makes the result worse, it uses more points and the approximation does not look as close as it does when ignoring the points of inflection. So I ignore them."
This is true, the inflection points (second derivatives of cubic) are not enough. But if you take into account also local extremes (min, max) which are the first derivatives of cubic function, and force breaks on those all, then the sub curves are all quadratic and can be presented by quadratics.
I tested the below functions, they work as expected (find all critical points of cubic and divides the cubic to down-elevated cubics). When those sub curves are drawn, the curve is exactly the same as original cubic, but for some reason, when sub curves are drawn as quadratics, the result is nearly right, but not exactly.
So this answer is not for strict help for the problem, but those functions provide a starting point for cubic to quadratic conversion.
To find both local extremes and inflection points, the following get_t_values_of_critical_points() should provide them. The
function compare_num(a,b) {
if (a < b) return -1;
if (a > b) return 1;
return 0;
}
function find_inflection_points(p1x,p1y,p2x,p2y,p3x,p3y,p4x,p4y)
{
var ax = -p1x + 3*p2x - 3*p3x + p4x;
var bx = 3*p1x - 6*p2x + 3*p3x;
var cx = -3*p1x + 3*p2x;
var ay = -p1y + 3*p2y - 3*p3y + p4y;
var by = 3*p1y - 6*p2y + 3*p3y;
var cy = -3*p1y + 3*p2y;
var a = 3*(ay*bx-ax*by);
var b = 3*(ay*cx-ax*cy);
var c = by*cx-bx*cy;
var r2 = b*b - 4*a*c;
var firstIfp = 0;
var secondIfp = 0;
if (r2>=0 && a!==0)
{
var r = Math.sqrt(r2);
firstIfp = (-b + r) / (2*a);
secondIfp = (-b - r) / (2*a);
if ((firstIfp>0 && firstIfp<1) && (secondIfp>0 && secondIfp<1))
{
if (firstIfp>secondIfp)
{
var tmp = firstIfp;
firstIfp = secondIfp;
secondIfp = tmp;
}
if (secondIfp-firstIfp >0.00001)
return [firstIfp, secondIfp];
else return [firstIfp];
}
else if (firstIfp>0 && firstIfp<1)
return [firstIfp];
else if (secondIfp>0 && secondIfp<1)
{
firstIfp = secondIfp;
return [firstIfp];
}
return [];
}
else return [];
}
function get_t_values_of_critical_points(p1x, p1y, c1x, c1y, c2x, c2y, p2x, p2y) {
var a = (c2x - 2 * c1x + p1x) - (p2x - 2 * c2x + c1x),
b = 2 * (c1x - p1x) - 2 * (c2x - c1x),
c = p1x - c1x,
t1 = (-b + Math.sqrt(b * b - 4 * a * c)) / 2 / a,
t2 = (-b - Math.sqrt(b * b - 4 * a * c)) / 2 / a,
tvalues=[];
Math.abs(t1) > "1e12" && (t1 = 0.5);
Math.abs(t2) > "1e12" && (t2 = 0.5);
if (t1 >= 0 && t1 <= 1 && tvalues.indexOf(t1)==-1) tvalues.push(t1)
if (t2 >= 0 && t2 <= 1 && tvalues.indexOf(t2)==-1) tvalues.push(t2);
a = (c2y - 2 * c1y + p1y) - (p2y - 2 * c2y + c1y);
b = 2 * (c1y - p1y) - 2 * (c2y - c1y);
c = p1y - c1y;
t1 = (-b + Math.sqrt(b * b - 4 * a * c)) / 2 / a;
t2 = (-b - Math.sqrt(b * b - 4 * a * c)) / 2 / a;
Math.abs(t1) > "1e12" && (t1 = 0.5);
Math.abs(t2) > "1e12" && (t2 = 0.5);
if (t1 >= 0 && t1 <= 1 && tvalues.indexOf(t1)==-1) tvalues.push(t1);
if (t2 >= 0 && t2 <= 1 && tvalues.indexOf(t2)==-1) tvalues.push(t2);
var inflectionpoints = find_inflection_points(p1x, p1y, c1x, c1y, c2x, c2y, p2x, p2y);
if (inflectionpoints[0]) tvalues.push(inflectionpoints[0]);
if (inflectionpoints[1]) tvalues.push(inflectionpoints[1]);
tvalues.sort(compare_num);
return tvalues;
};
And when you have those critical t values (which are from range 0-1), you can divide the cubic to parts:
function CPoint()
{
var arg = arguments;
if (arg.length==1)
{
this.X = arg[0].X;
this.Y = arg[0].Y;
}
else if (arg.length==2)
{
this.X = arg[0];
this.Y = arg[1];
}
}
function subdivide_cubic_to_cubics()
{
var arg = arguments;
if (arg.length!=9) return [];
var m_p1 = {X:arg[0], Y:arg[1]};
var m_p2 = {X:arg[2], Y:arg[3]};
var m_p3 = {X:arg[4], Y:arg[5]};
var m_p4 = {X:arg[6], Y:arg[7]};
var t = arg[8];
var p1p = new CPoint(m_p1.X + (m_p2.X - m_p1.X) * t,
m_p1.Y + (m_p2.Y - m_p1.Y) * t);
var p2p = new CPoint(m_p2.X + (m_p3.X - m_p2.X) * t,
m_p2.Y + (m_p3.Y - m_p2.Y) * t);
var p3p = new CPoint(m_p3.X + (m_p4.X - m_p3.X) * t,
m_p3.Y + (m_p4.Y - m_p3.Y) * t);
var p1d = new CPoint(p1p.X + (p2p.X - p1p.X) * t,
p1p.Y + (p2p.Y - p1p.Y) * t);
var p2d = new CPoint(p2p.X + (p3p.X - p2p.X) * t,
p2p.Y + (p3p.Y - p2p.Y) * t);
var p1t = new CPoint(p1d.X + (p2d.X - p1d.X) * t,
p1d.Y + (p2d.Y - p1d.Y) * t);
return [[m_p1.X, m_p1.Y, p1p.X, p1p.Y, p1d.X, p1d.Y, p1t.X, p1t.Y],
[p1t.X, p1t.Y, p2d.X, p2d.Y, p3p.X, p3p.Y, m_p4.X, m_p4.Y]];
}
subdivide_cubic_to_cubics() in above code divides an original cubic curve to two parts by the value t. Because get_t_values_of_critical_points() returns t values as an array sorted by t value, you can easily traverse all t values and get the corresponding sub curve. When you have those divided curves, you have to divide the 2nd sub curve by the next t value.
When all splitting is proceeded, you have the control points of all sub curves. Now there are left only the cubic control point conversion to quadratic. Because all sub curves are now down-elevated cubics, the corresponding quadratic control points are easy to calculate. The first and last of quadratic control points are the same as cubic's (sub curve) first and last control point and the middle one is found in the point, where lines P1-P2 and P4-P3 crosses.
Conventions/terminology
Cubic defined by: P1/2 - anchor points, C1/C2 control points
|x| is the euclidean norm of x
mid-point approx of cubic: a quad that shares the same anchors with the cubic and has the control point at C = (3·C2 - P2 + 3·C1 - P1)/4
Algorithm
pick an absolute precision (prec)
Compute the Tdiv as the root of (cubic) equation sqrt(3)/18 · |P2 - 3·C2 + 3·C1 - P1|/2 · Tdiv ^ 3 = prec
if Tdiv < 0.5 divide the cubic at Tdiv. First segment [0..Tdiv] can be approximated with by a quadratic, with a defect less than prec, by the mid-point approximation. Repeat from step 2 with the second resulted segment (corresponding to 1-Tdiv)
0.5<=Tdiv<1 - simply divide the cubic in two. The two halves can be approximated by the mid-point approximation
Tdiv>=1 - the entire cubic can be approximated by the mid-point approximation
The "magic formula" at step 2 is demonstrated (with interactive examples) on this page.
Another derivation of tfinniga's answer:
First see Wikipedia Bezier curve
for the formulas for quadratic and cubic Bezier curves (also nice animations):
Q(t) = (1-t)^2 P0 + 2 (1-t) t Q + t^2 P3
P(t) + (1-t)^3 P0 + 3 (1-t)^2 t P1 + 3 (1-t) t^2 P2 + t^3 P3
Require these to match at the middle, t = 1/2:
(P0 + 2 Q + P3) / 4 = (P0 + 3 P1 + 3 P2 + P3) / 8
=> Q = P1 + P2 - (P0 + P1 + P2 + P3) / 4
(Q written like this has a geometric interpretation:
Pmid = middle of P0 P1 P2 P3
P12mid = midway between P1 and P2
draw a line from Pmid to P12mid, and that far again: you're at Q.
Hope this makes sense -- draw a couple of examples.)
In general, you'll have to use multiple quadratic curves - many cases of cubic curves can't be even vaguely approximated with a single quadratic curve.
There is a good article discussing the problem, and a number of ways to solve it, at http://www.timotheegroleau.com/Flash/articles/cubic_bezier_in_flash.htm (including interactive demonstrations).
I should note that Adrian's solution is great for single cubics, but when the cubics are segments of a smooth cubic spline, then using his midpoint approximation method causes slope continuity at the nodes of the segments to be lost. So the method described at http://fontforge.org/bezier.html#ps2ttf is much better if you are working with font glyphs or for any other reason you want to retain the smoothness of the curve (which is most probably the case).
Even though this is an old question, many people like me will see it in search results, so I'm posting this here.
I would probably draw a series of curves instead of trying to draw one curve using a different alg. Sort of like drawing two half circles to make up a whole circle.
Try looking for opensource Postcript font to Truetype font converters. I'm sure they have it. Postscript uses cubic bezier curves, whereas Truetype uses quadratic bezier curves. Good luck.

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