Quadratic functions in c - quadratic

I have almost everything working except for solving for X in line 25 i keep getting an error saying " term does not evaluate to a function taking 1787 arguments" i had it giving me a 1 or a 0 but as i kept messing with it i lost where i was at and saved over the copy. still new to posting sorry if its hard to read
#include <stdio.h>
#include <math.h>
void quadratic_function()
{
int a,b,c; // variables
long int result; // my X in the quadractic function
long int y,x; // the result
long int quadratic;
printf("enter values for a,b,c\n");
scanf("%i\n %i\n %i", &a,&b,&c);
printf("A=%i B=%i C=%i\n", a,b,c); //Displays Variables
y= pow(b, 2);
result= (y)*-4*(a)*(c); // b^2-4ac
printf("\n%li\n",result);
if (result<0)
printf("Imaginary Number"); // if negative
else (result>0);
x=(-b/2*(a)) +- (sqrt(pow(b, 2)) (-4*(a)*(c))) / (2*(a));
//solving for x
printf("\n %li\n",x);
a = a*x;
b = b*x;
quadratic=pow(a, 2)*(b)*(c); // if positive
//printf("Quadratic equation equal to %li",quadratic); // result
}
int main()
{
quadratic_function();
return 0;
}

The first thing I noticed is that you were trying to do the + and - portions of the quadratic equation at the same time. The equation
x = (-b +- sqrt(b^2 - 4ac)) / 2a
means the same as
x = (-b + sqrt(b^2 - 4ac)) / 2a AND x = (-b - sqrt(b^2 - 4ac)) / 2a
In other words, the equation has two answers if b^2 - 4ac is greater than 0, one answer if it is 0, and no answer if it is negative.
Another thing, the line else (result>0); doesn't really do anything. The rest of the code after that will execute even if you get b^2 - 4ac < 0
Finally, I wasn't entirely sure about your groupings or C++'s precedence with the negative sign, so I changed your parentheses around a bit.
y = pow(b, 2);
result = (y) - (4*a*c); // b^2-4ac
printf("\n%li\n", result);
if (result < 0) {
printf("Imaginary Number"); // if negative
} else if (result == 0) {
x = (-b) / (2 * a); // sqrt(0) = 0, so don't bother calculating it
a = a*x;
b = b*x;
quadratic=pow(a, 2)*(b)*(c);
printf("Quadratic equation equal to %li",quadratic); // result
} else if (result > 0) {
// solve for (-b + sqrt(b^2 - 4ac)) / 2a
x = ((-b) + sqrt(pow(b, 2) - (4 * a * c))) / (2 * a);
printf("\n %li\n",x);
a = a*x;
b = b*x;
quadratic=pow(a, 2)*(b)*(c);
printf("Quadratic equation equal to %li",quadratic); // result
// do it again for (-b - sqrt(b^2 - 4ac)) / 2a
x = ((-b) - sqrt(pow(b, 2) - (4 * a * c))) / (2 * a);
printf("\n %li\n",x);
a = a*x;
b = b*x;
quadratic=pow(a, 2)*(b)*(c);
printf("Quadratic equation equal to %li",quadratic);
}

Related

Normalize any value in range (-inf...+inf) to (0...1). Is it possible?

If we have concrete range of max..min value it is quite easy to normalize it to 0..1 float values, but if we don't have concrete limits? Is it possible to build universal function to have output between 0 and 1? In my mind I think it is impossible but I am not math expert.
I'm searching for implementation on JavaScript or PHP, but any code on C/C++/Python/Delphi is OK to provide examples ( if there are some )
There are many ways to do this. I'll leave out mapping -inf and +inf, which can be done with conditional statements.
exp(x) / (1 + exp(x)) or the equivalent 1 / (1 + exp(-x)) where exp is the exponential function. This is a logistic function.
atan(x) / pi + 1 / 2
(tanh(x) + 1) / 2
(1 + x / sqrt(1 + x*x)) / 2
(1 + x / (1 + abs(x)) / 2
(erf(x) + 1) / 2
You have probably noticed that most of these take a mapping to (-1, 1) and change it to (0, 1). The former is usually easier. Here is a graph of these functions:
In my Python 3.5.2, the fastest was (1 + x / (1 + abs(x)) * 0.5.
If you don't mind bit-dibbling and are confident that code uses IEEE binary 64-bit floating point, some fast code with only a few FP math operations
// If double is 64-bit and same endian as integer
double noramlize01(double x) {
assert(x == x); // fail if x is NaN
union {
double d;
int64_t i64;
uint64_t u64;
} u = {x};
double d;
if (u.i64 < 0) {
u.u64 -= 0x8000000000000000;
d = (double) -u.i64;
} else {
d = (double) u.i64;
}
return d/(+2.0 * 0x7ff0000000000000) + 0.5;
}
// Similar test code as this answer
-inf 0.0000000000000000
-1.797693e+308 0.0000000000000000
-3.141593e+00 0.24973844740430023
-2.718282e+00 0.24979014633262589
-1.000000e+00 0.25012212994626282
-2.225074e-308 0.49975574010747437
-4.940656e-324 0.50000000000000000
-0.000000e+00 0.50000000000000000
0.000000e+00 0.50000000000000000
4.940656e-324 0.50000000000000000
2.225074e-308 0.50024425989252563
1.000000e+00 0.74987787005373718
2.718282e+00 0.75020985366737414
3.141593e+00 0.75026155259569971
1.797693e+308 1.0000000000000000
inf 1.0000000000000000
With nearly all programming of floating point numbers, the values are distributed logarithmically. Therefore first take the log() of the value to begin mapping paying attention to edge case concerns.
double map(double x, double x0, double x1, double y0, double y1) {
return (x - x0) / (x1 - x0) * (y1 - y0) + y0;
}
double noramlize01(double x) {
assert(x == x); // fail is x is NaN
// These values only need to be calculated once.
double logxmin = log(DBL_TRUE_MIN); // e.g. -323.306...
double logxmax = log(DBL_MAX); // e.g. 308.254...
double y;
if (x < -DBL_MAX) y = 0.0;
else if (x < 0.0) {
y = map(log(-x), logxmax, logxmin, nextafter(0.0,1.0), nextafter(0.5,0.0));
} else if (x == 0.0) {
y = 0.5;
} else if (x <= DBL_MAX) {
y = map(log(x), logxmin, logxmax, nextafter(0.5,1.0), nextafter(1.0,0.5));
} else {
y = 1.0;
}
return y;
}
double round_n(double x, unsigned n) {
return x * n;
}
void testr(double x) {
printf("% 20e %#.17g\n", x, noramlize01(x));
//printf("% 20e %.17f\n", -x, noramlize01(-x));
}
int main(void) {
double t[] = {0.0, DBL_TRUE_MIN, DBL_MIN, 1/M_PI, 1/M_E,
1.0, M_E, M_PI, DBL_MAX, INFINITY};
for (unsigned i = sizeof t/sizeof t[0]; i > 0; i--) {
testr(-t[i-1]);
}
for (unsigned i = 0; i < sizeof t/sizeof t[0]; i++) {
testr(t[i]);
}
}
Sample output
-inf 0.0000000000000000
-1.797693e+308 4.9406564584124654e-324
-3.141593e+00 0.24364835649917244
-2.718282e+00 0.24369811843639441
-1.000000e+00 0.24404194470924687
-3.678794e-01 0.24438577098209935
-3.183099e-01 0.24443553291932130
-2.225074e-308 0.48760724499523350
-4.940656e-324 0.49999999999999994
-0.000000e+00 0.50000000000000000
0.000000e+00 0.50000000000000000
4.940656e-324 0.50000000000000011
2.225074e-308 0.51239275500476655
3.183099e-01 0.75556446708067870
3.678794e-01 0.75561422901790065
1.000000e+00 0.75595805529075311
2.718282e+00 0.75630188156360556
3.141593e+00 0.75635164350082751
1.797693e+308 0.99999999999999989
inf 1.0000000000000000

How to get a logarithmic distribution from an interval

I am currently trying to cut an interval into not equal-width slices. In fact I want the width of each slice to follow a logarithmic rule. For instance the first interval is supposed to be bigger than the second one, etc.
I have a hard time remembering my mathematics lectures. So assuming I know a and b which are respectively the lower and upper boundaries of my interval I, and n is the number of slices:
how can I find the lower and upper boundaries of each slice (following a logarithmic scale)?
In other word, here's what I have done to get equal-width interval:
for (i = 1; i< p; i++) {
start = lower + i -1 + ((i-1) * size_piece);
if (i == p-1 ) {
end = upper;
} else {
end = start + size_piece;
}
//function(start, end)
}
Where: p-1= number of slices, and size_piece = |b-a|.
What I want to get now is start and end values, but following a logarithmic scale instead of an arithmetic scale (which are going to be called in some function in the for loop).
Thanks in advance for your help.
If I have understood your question, this C++ program will show you a practical example of the algorithm that can be used:
#include <iostream>
#include <cmath>
void my_function( double a, double b ) {
// print out the lower and upper bounds of the slice
std::cout << a << " -- " << b << '\n';
}
int main() {
double start = 0.0, end = 1.0;
int n_slices = 7;
// I want to create 7 slices in a segment of length = end - start
// whose extremes are logarithmically distributed:
// | 1 | 2 | 3 | 4 | 5 |6 |7|
// +-----------------+----------+------+----+---+--+-+
// start end
double scale = (end - start) / log(1.0 + n_slices);
double lower_bound = start;
for ( int i = 0; i < n_slices; ++i ) {
// transform to the interval (1,n_slices+1):
// 1 2 3 4 5 6 7 8
// +-----------------+----------+------+----+---+--+-+
// start end
double upper_bound = start + log(2.0 + i) * scale;
// use the extremes in your function
my_function(lower_bound,upper_bound);
// update
lower_bound = upper_bound;
}
return 0;
}
The output (the extremes of the slices) is:
0 -- 0.333333
0.333333 -- 0.528321
0.528321 -- 0.666667
0.666667 -- 0.773976
0.773976 -- 0.861654
0.861654 -- 0.935785
0.935785 -- 1

Optimization of Fibonacci sequence generating algorithm

As we all know, the simplest algorithm to generate Fibonacci sequence is as follows:
if(n<=0) return 0;
else if(n==1) return 1;
f(n) = f(n-1) + f(n-2);
But this algorithm has some repetitive calculation. For example, if you calculate f(5), it will calculate f(4) and f(3). When you calculate f(4), it will again calculate both f(3) and f(2). Could someone give me a more time-efficient recursive algorithm?
I have read about some of the methods for calculating Fibonacci with efficient time complexity following are some of them -
Method 1 - Dynamic Programming
Now here the substructure is commonly known hence I'll straightly Jump to the solution -
static int fib(int n)
{
int f[] = new int[n+2]; // 1 extra to handle case, n = 0
int i;
f[0] = 0;
f[1] = 1;
for (i = 2; i <= n; i++)
{
f[i] = f[i-1] + f[i-2];
}
return f[n];
}
A space-optimized version of above can be done as follows -
static int fib(int n)
{
int a = 0, b = 1, c;
if (n == 0)
return a;
for (int i = 2; i <= n; i++)
{
c = a + b;
a = b;
b = c;
}
return b;
}
Method 2- ( Using power of the matrix {{1,1},{1,0}} )
This an O(n) which relies on the fact that if we n times multiply the matrix M = {{1,1},{1,0}} to itself (in other words calculate power(M, n )), then we get the (n+1)th Fibonacci number as the element at row and column (0, 0) in the resultant matrix. This solution would have O(n) time.
The matrix representation gives the following closed expression for the Fibonacci numbers:
fibonaccimatrix
static int fib(int n)
{
int F[][] = new int[][]{{1,1},{1,0}};
if (n == 0)
return 0;
power(F, n-1);
return F[0][0];
}
/*multiplies 2 matrices F and M of size 2*2, and
puts the multiplication result back to F[][] */
static void multiply(int F[][], int M[][])
{
int x = F[0][0]*M[0][0] + F[0][1]*M[1][0];
int y = F[0][0]*M[0][1] + F[0][1]*M[1][1];
int z = F[1][0]*M[0][0] + F[1][1]*M[1][0];
int w = F[1][0]*M[0][1] + F[1][1]*M[1][1];
F[0][0] = x;
F[0][1] = y;
F[1][0] = z;
F[1][1] = w;
}
/*function that calculates F[][] raise to the power n and puts the
result in F[][]*/
static void power(int F[][], int n)
{
int i;
int M[][] = new int[][]{{1,1},{1,0}};
// n - 1 times multiply the matrix to {{1,0},{0,1}}
for (i = 2; i <= n; i++)
multiply(F, M);
}
This can be optimized to work in O(Logn) time complexity. We can do recursive multiplication to get power(M, n) in the previous method.
static int fib(int n)
{
int F[][] = new int[][]{{1,1},{1,0}};
if (n == 0)
return 0;
power(F, n-1);
return F[0][0];
}
static void multiply(int F[][], int M[][])
{
int x = F[0][0]*M[0][0] + F[0][1]*M[1][0];
int y = F[0][0]*M[0][1] + F[0][1]*M[1][1];
int z = F[1][0]*M[0][0] + F[1][1]*M[1][0];
int w = F[1][0]*M[0][1] + F[1][1]*M[1][1];
F[0][0] = x;
F[0][1] = y;
F[1][0] = z;
F[1][1] = w;
}
static void power(int F[][], int n)
{
if( n == 0 || n == 1)
return;
int M[][] = new int[][]{{1,1},{1,0}};
power(F, n/2);
multiply(F, F);
if (n%2 != 0)
multiply(F, M);
}
Method 3 (O(log n) Time)
Below is one more interesting recurrence formula that can be used to find nth Fibonacci Number in O(log n) time.
If n is even then k = n/2:
F(n) = [2*F(k-1) + F(k)]*F(k)
If n is odd then k = (n + 1)/2
F(n) = F(k)*F(k) + F(k-1)*F(k-1)
How does this formula work?
The formula can be derived from the above matrix equation.
fibonaccimatrix
Taking determinant on both sides, we get
(-1)n = Fn+1Fn-1 – Fn2
Moreover, since AnAm = An+m for any square matrix A, the following identities can be derived (they are obtained from two different coefficients of the matrix product)
FmFn + Fm-1Fn-1 = Fm+n-1
By putting n = n+1,
FmFn+1 + Fm-1Fn = Fm+n
Putting m = n
F2n-1 = Fn2 + Fn-12
F2n = (Fn-1 + Fn+1)Fn = (2Fn-1 + Fn)Fn (Source: Wiki)
To get the formula to be proved, we simply need to do the following
If n is even, we can put k = n/2
If n is odd, we can put k = (n+1)/2
public static int fib(int n)
{
if (n == 0)
return 0;
if (n == 1 || n == 2)
return (f[n] = 1);
// If fib(n) is already computed
if (f[n] != 0)
return f[n];
int k = (n & 1) == 1? (n + 1) / 2
: n / 2;
// Applyting above formula [See value
// n&1 is 1 if n is odd, else 0.
f[n] = (n & 1) == 1? (fib(k) * fib(k) +
fib(k - 1) * fib(k - 1))
: (2 * fib(k - 1) + fib(k))
* fib(k);
return f[n];
}
Method 4 - Using a formula
In this method, we directly implement the formula for the nth term in the Fibonacci series. Time O(1) Space O(1)
Fn = {[(√5 + 1)/2] ^ n} / √5
static int fib(int n) {
double phi = (1 + Math.sqrt(5)) / 2;
return (int) Math.round(Math.pow(phi, n)
/ Math.sqrt(5));
}
Reference: http://www.maths.surrey.ac.uk/hosted-sites/R.Knott/Fibonacci/fibFormula.html
Look here for implementation in Erlang which uses formula
. It shows nice linear resulting behavior because in O(M(n) log n) part M(n) is exponential for big numbers. It calculates fib of one million in 2s where result has 208988 digits. The trick is that you can compute exponentiation in O(log n) multiplications using (tail) recursive formula (tail means with O(1) space when used proper compiler or rewrite to cycle):
% compute X^N
power(X, N) when is_integer(N), N >= 0 ->
power(N, X, 1).
power(0, _, Acc) ->
Acc;
power(N, X, Acc) ->
if N rem 2 =:= 1 ->
power(N - 1, X, Acc * X);
true ->
power(N div 2, X * X, Acc)
end.
where X and Acc you substitute with matrices. X will be initiated with and Acc with identity I equals to .
One simple way is to calculate it iteratively instead of recursively. This will calculate F(n) in linear time.
def fib(n):
a,b = 0,1
for i in range(n):
a,b = a+b,a
return a
Hint: One way you achieve faster results is by using Binet's formula:
Here is a way of doing it in Python:
from decimal import *
def fib(n):
return int((Decimal(1.6180339)**Decimal(n)-Decimal(-0.6180339)**Decimal(n))/Decimal(2.236067977))
you can save your results and use them :
public static long[] fibs;
public long fib(int n) {
fibs = new long[n];
return internalFib(n);
}
public long internalFib(int n) {
if (n<=2) return 1;
fibs[n-1] = fibs[n-1]==0 ? internalFib(n-1) : fibs[n-1];
fibs[n-2] = fibs[n-2]==0 ? internalFib(n-2) : fibs[n-2];
return fibs[n-1]+fibs[n-2];
}
F(n) = (φ^n)/√5 and round to nearest integer, where φ is the golden ratio....
φ^n can be calculated in O(lg(n)) time hence F(n) can be calculated in O(lg(n)) time.
// D Programming Language
void vFibonacci ( const ulong X, const ulong Y, const int Limit ) {
// Equivalent : if ( Limit != 10 ). Former ( Limit ^ 0xA ) is More Efficient However.
if ( Limit ^ 0xA ) {
write ( Y, " " ) ;
vFibonacci ( Y, Y + X, Limit + 1 ) ;
} ;
} ;
// Call As
// By Default the Limit is 10 Numbers
vFibonacci ( 0, 1, 0 ) ;
EDIT: I actually think Hynek Vychodil's answer is superior to mine, but I'm leaving this here just in case someone is looking for an alternate method.
I think the other methods are all valid, but not optimal. Using Binet's formula should give you the right answer in principle, but rounding to the closest integer will give some problems for large values of n. The other solutions will unnecessarily recalculate the values upto n every time you call the function, and so the function is not optimized for repeated calling.
In my opinion the best thing to do is to define a global array and then to add new values to the array IF needed. In Python:
import numpy
fibo=numpy.array([1,1])
last_index=fibo.size
def fib(n):
global fibo,last_index
if (n>0):
if(n>last_index):
for i in range(last_index+1,n+1):
fibo=numpy.concatenate((fibo,numpy.array([fibo[i-2]+fibo[i-3]])))
last_index=fibo.size
return fibo[n-1]
else:
print "fib called for index less than 1"
quit()
Naturally, if you need to call fib for n>80 (approximately) then you will need to implement arbitrary precision integers, which is easy to do in python.
This will execute faster, O(n)
def fibo(n):
a, b = 0, 1
for i in range(n):
if i == 0:
print(i)
elif i == 1:
print(i)
else:
temp = a
a = b
b += temp
print(b)
n = int(input())
fibo(n)

Interpolating values between interval, interpolation as per Bezier curve

To implement a 2D animation I am looking for interpolating values between two key frames with the velocity of change defined by a Bezier curve. The problem is Bezier curve is represented in parametric form whereas requirement is to be able to evaluate the value for a particular time.
To elaborate, lets say the value of 10 and 40 is to be interpolated across 4 seconds with the value changing not constantly but as defined by a bezier curve represented as 0,0 0.2,0.3 0.5,0.5 1,1.
Now if I am drawing at 24 frames per second, I need to evaluate the value for every frame. How can I do this ? I looked at De Casteljau algorithm and thought that dividing the curve into 24*4 pieces for 4 seconds would solve my problem but that sounds erroneous as time is along the "x" axis and not along the curve.
To further simplify
If I draw the curve in a plane, the x axis represents the time and the y axis the value I am looking for. What I actually require is to to be able to find out "y" corresponding to "x". Then I can divide x in 24 divisions and know the value for each frame
I was facing the same problem: Every animation package out there seems to use Bézier curves to control values over time, but there is no information out there on how to implement a Bézier curve as a y(x) function. So here is what I came up with.
A standard cubic Bézier curve in 2D space can be defined by the four points P0=(x0, y0) .. P3=(x3, y3).
P0 and P3 are the end points of the curve, while P1 and P2 are the handles affecting its shape. Using a parameter t ϵ [0, 1], the x and y coordinates for any given point along the curve can then be determined using the equations
A) x = (1-t)3x0 + 3t(1-t)2x1 + 3t2(1-t)x2 + t3x3 and
B) y = (1-t)3y0 + 3t(1-t)2y1 + 3t2(1-t)y2 + t3y3.
What we want is a function y(x) that, given an x coordinate, will return the corresponding y coordinate of the curve. For this to work, the curve must move monotonically from left to right, so that it doesn't occupy the same x coordinate more than once on different y positions. The easiest way to ensure this is to restrict the input points so that x0 < x3 and x1, x2 ϵ [x0, x3]. In other words, P0 must be to the left of P3 with the two handles between them.
In order to calculate y for a given x, we must first determine t from x. Getting y from t is then a simple matter of applying t to equation B.
I see two ways of determining t for a given y.
First, you might try a binary search for t. Start with a lower bound of 0 and an upper bound of 1 and calculate x for these values for t via equation A. Keep bisecting the interval until you get a reasonably close approximation. While this should work fine, it will neither be particularly fast nor very precise (at least not both at once).
The second approach is to actually solve equation A for t. That's a bit tough to implement because the equation is cubic. On the other hand, calculation becomes really fast and yields precise results.
Equation A can be rewritten as
(-x0+3x1-3x2+x3)t3 + (3x0-6x1+3x2)t2 + (-3x0+3x1)t + (x0-x) = 0.
Inserting your actual values for x0..x3, we get a cubic equation of the form at3 + bt2 + c*t + d = 0 for which we know there is only one solution within [0, 1]. We can now solve this equation using an algorithm like the one posted in this Stack Overflow answer.
The following is a little C# class demonstrating this approach. It should be simple enough to convert it to a language of your choice.
using System;
public class Point {
public Point(double x, double y) {
X = x;
Y = y;
}
public double X { get; private set; }
public double Y { get; private set; }
}
public class BezierCurve {
public BezierCurve(Point p0, Point p1, Point p2, Point p3) {
P0 = p0;
P1 = p1;
P2 = p2;
P3 = p3;
}
public Point P0 { get; private set; }
public Point P1 { get; private set; }
public Point P2 { get; private set; }
public Point P3 { get; private set; }
public double? GetY(double x) {
// Determine t
double t;
if (x == P0.X) {
// Handle corner cases explicitly to prevent rounding errors
t = 0;
} else if (x == P3.X) {
t = 1;
} else {
// Calculate t
double a = -P0.X + 3 * P1.X - 3 * P2.X + P3.X;
double b = 3 * P0.X - 6 * P1.X + 3 * P2.X;
double c = -3 * P0.X + 3 * P1.X;
double d = P0.X - x;
double? tTemp = SolveCubic(a, b, c, d);
if (tTemp == null) return null;
t = tTemp.Value;
}
// Calculate y from t
return Cubed(1 - t) * P0.Y
+ 3 * t * Squared(1 - t) * P1.Y
+ 3 * Squared(t) * (1 - t) * P2.Y
+ Cubed(t) * P3.Y;
}
// Solves the equation ax³+bx²+cx+d = 0 for x ϵ ℝ
// and returns the first result in [0, 1] or null.
private static double? SolveCubic(double a, double b, double c, double d) {
if (a == 0) return SolveQuadratic(b, c, d);
if (d == 0) return 0;
b /= a;
c /= a;
d /= a;
double q = (3.0 * c - Squared(b)) / 9.0;
double r = (-27.0 * d + b * (9.0 * c - 2.0 * Squared(b))) / 54.0;
double disc = Cubed(q) + Squared(r);
double term1 = b / 3.0;
if (disc > 0) {
double s = r + Math.Sqrt(disc);
s = (s < 0) ? -CubicRoot(-s) : CubicRoot(s);
double t = r - Math.Sqrt(disc);
t = (t < 0) ? -CubicRoot(-t) : CubicRoot(t);
double result = -term1 + s + t;
if (result >= 0 && result <= 1) return result;
} else if (disc == 0) {
double r13 = (r < 0) ? -CubicRoot(-r) : CubicRoot(r);
double result = -term1 + 2.0 * r13;
if (result >= 0 && result <= 1) return result;
result = -(r13 + term1);
if (result >= 0 && result <= 1) return result;
} else {
q = -q;
double dum1 = q * q * q;
dum1 = Math.Acos(r / Math.Sqrt(dum1));
double r13 = 2.0 * Math.Sqrt(q);
double result = -term1 + r13 * Math.Cos(dum1 / 3.0);
if (result >= 0 && result <= 1) return result;
result = -term1 + r13 * Math.Cos((dum1 + 2.0 * Math.PI) / 3.0);
if (result >= 0 && result <= 1) return result;
result = -term1 + r13 * Math.Cos((dum1 + 4.0 * Math.PI) / 3.0);
if (result >= 0 && result <= 1) return result;
}
return null;
}
// Solves the equation ax² + bx + c = 0 for x ϵ ℝ
// and returns the first result in [0, 1] or null.
private static double? SolveQuadratic(double a, double b, double c) {
double result = (-b + Math.Sqrt(Squared(b) - 4 * a * c)) / (2 * a);
if (result >= 0 && result <= 1) return result;
result = (-b - Math.Sqrt(Squared(b) - 4 * a * c)) / (2 * a);
if (result >= 0 && result <= 1) return result;
return null;
}
private static double Squared(double f) { return f * f; }
private static double Cubed(double f) { return f * f * f; }
private static double CubicRoot(double f) { return Math.Pow(f, 1.0 / 3.0); }
}
You have a few options:
Let's say your curve function F(t) takes a parameter t that ranges from 0 to 1 where F(0) is the beginning of the curve and F(1) is the end of the curve.
You could animate motion along the curve by incrementing t at a constant change per unit of time.
So t is defined by function T(time) = Constant*time
For example, if your frame is 1/24th of a second, and you want to move along the curve at a rate of 0.1 units of t per second, then each frame you increment t by 0.1 (t/s) * 1/24 (sec/frame).
A drawback here is that your actual speed or distance traveled per unit time will not be constant. It will depends on the positions of your control points.
If you want to scale speed along the curve uniformly you can modify the constant change in t per unit time. However, if you want speeds to vary dramatically you will find it difficult to control the shape of the curve. If you want the velocity at one endpoint to be much larger, you must move the control point further away, which in turn pulls the shape of the curve towards that point. If this is a problem, you may consider using a non constant function for t. There are a variety of approaches with different trade-offs, and we need to know more details about your problem to suggest a solution. For example, in the past I have allowed users to define the speed at each keyframe and used a lookup table to translate from time to parameter t such that there is a linear change in speed between keyframe speeds (it's complicated).
Another common hangup: If you are animating by connecting several Bezier curves, and you want the velocity to be continuous when moving between curves, then you will need to constrain your control points so they are symmetrical with the adjacent curve. Catmull-Rom splines are a common approach.
I've answered a similar question here. Basically if you know the control points before hand then you can transform the f(t) function into a y(x) function. To not have to do it all by hand you can use services like Wolfram Alpha to help you with the math.

Mathematically Find Max Value without Conditional Comparison

----------Updated ------------
codymanix and moonshadow have been a big help thus far. I was able to solve my problem using the equations and instead of using right shift I divided by 29. Because with 32bits signed 2^31 = overflows to 29. Which works!
Prototype in PHP
$r = $x - (($x - $y) & (($x - $y) / (29)));
Actual code for LEADS (you can only do one math function PER LINE!!! AHHHH!!!)
DERIVDE1 = IMAGE1 - IMAGE2;
DERIVED2 = DERIVED1 / 29;
DERIVED3 = DERIVED1 AND DERIVED2;
MAX = IMAGE1 - DERIVED3;
----------Original Question-----------
I don't think this is quite possible with my application's limitations but I figured it's worth a shot to ask.
I'll try to make this simple. I need to find the max values between two numbers without being able to use a IF or any conditional statement.
In order to find the the MAX values I can only perform the following functions
Divide, Multiply, Subtract, Add, NOT, AND ,OR
Let's say I have two numbers
A = 60;
B = 50;
Now if A is always greater than B it would be simple to find the max value
MAX = (A - B) + B;
ex.
10 = (60 - 50)
10 + 50 = 60 = MAX
Problem is A is not always greater than B. I cannot perform ABS, MAX, MIN or conditional checks with the scripting applicaiton I am using.
Is there any way possible using the limited operation above to find a value VERY close to the max?
finding the maximum of 2 variables:
max = a-((a-b)&((a-b)>>31))
where >> is bitwise right-shift (also called SHR or ASR depeding on signedness).
Instead of 31 you use the number of bits your numbers have minus one.
I guess this one would be the most simplest if we manage to find difference between two numbers (only the magnitude not sign)
max = ((a+b)+|a-b|)/2;
where |a-b| is a magnitude of difference between a and b.
If you can't trust your environment to generate the appropriate branchless operations when they are available, see this page for how to proceed. Note the restriction on input range; use a larger integer type for the operation if you cannot guarantee your inputs will fit.
Solution without conditionals. Cast to uint then back to int to get abs.
int abs (a) { return (int)((unsigned int)a); }
int max (a, b) { return (a + b + abs(a - b)) / 2; }
int max3 (a, b, c) { return (max(max(a,b),c); }
Using logical operations only, short circuit evaluation and assuming the C convention of rounding towards zero, it is possible to express this as:
int lt0(int x) {
return x && (!!((x-1)/x));
}
int mymax(int a, int b) {
return lt0(a-b)*b+lt0(b-a)*a;
}
The basic idea is to implement a comparison operator that will return 0 or 1. It's possible to do a similar trick if your scripting language follows the convention of rounding toward the floor value like python does.
function Min(x,y:integer):integer;
Var
d:integer;
abs:integer;
begin
d:=x-y;
abs:=d*(1-2*((3*d) div (3*d+1)));
Result:=(x+y-abs) div 2;
end;
Hmmm. I assume NOT, AND, and OR are bitwise? If so, there's going to be a bitwise expression to solve this. Note that A | B will give a number >= A and >= B. Perhaps there's a pruning method for selecting the number with the most bits.
To extend, we need the following to determine whether A (0) or B (1) is greater.
truth table:
0|0 = 0
0|1 = 1
1|0 = 0
1|1 = 0
!A and B
therefore, will give the index of the greater bit. Ergo, compare each bit in both numbers, and when they are different, use the above expression (Not A And B) to determine which number was greater. Start from the most significant bit and proceed down both bytes. If you have no looping construct, manually compare each bit.
Implementing "when they are different":
(A != B) AND (my logic here)
try this, (but be aware for overflows)
(Code in C#)
public static Int32 Maximum(params Int32[] values)
{
Int32 retVal = Int32.MinValue;
foreach (Int32 i in values)
retVal += (((i - retVal) >> 31) & (i - retVal));
return retVal;
}
You can express this as a series of arithmetic and bitwise operations, e.g.:
int myabs(const int& in) {
const int tmp = in >> ((sizeof(int) * CHAR_BIT) - 1);
return tmp - (in ^ tmp(;
}
int mymax(int a, int b) {
return ((a+b) + myabs(b-a)) / 2;
}
//Assuming 32 bit integers
int is_diff_positive(int num)
{
((num & 0x80000000) >> 31) ^ 1; // if diff positive ret 1 else 0
}
int sign(int x)
{
return ((num & 0x80000000) >> 31);
}
int flip(int x)
{
return x ^ 1;
}
int max(int a, int b)
{
int diff = a - b;
int is_pos_a = sign(a);
int is_pos_b = sign(b);
int is_diff_positive = diff_positive(diff);
int is_diff_neg = flip(is_diff_positive);
// diff (a - b) will overflow / underflow if signs are opposite
// ex: a = INT_MAX , b = -3 then a - b => INT_MAX - (-3) => INT_MAX + 3
int can_overflow = is_pos_a ^ is_pos_b;
int cannot_overflow = flip(can_overflow);
int res = (cannot_overflow * ( (a * is_diff_positive) + (b *
is_diff_negative)) + (can_overflow * ( (a * is_pos_a) + (b *
is_pos_b)));
return res;
}
This is my implementation using only +, -, *, %, / operators
using static System.Console;
int Max(int a, int b) => (a + b + Abs(a - b)) / 2;
int Abs(int x) => x * ((2 * x + 1) % 2);
WriteLine(Max(-100, -2) == -2); // true
WriteLine(Max(2, -100) == 2); // true
I just came up with an expression:
(( (a-b)-|a-b| ) / (2(a-b)) )*b + (( (b-a)-|b-a| )/(2(b-a)) )*a
which is equal to a if a>b and is equal to b if b>a
when a>b:
a-b>0, a-b = |a-b|, (a-b)-|a-b| = 0 so the coeficcient for b is 0
b-a<0, b-a = -|b-a|, (b-a)-|b-a| = 2(b-a)
so the coeficcient for a is 2(b-a)/2(b-a) which is 1
so it would ultimately return 0*b+1*a if a is bigger and vice versa
Find MAX between n & m
MAX = ( (n/2) + (m/2) + ( ((n/2) - (m/2)) * ( (2*((n/2) - (m/2)) + 1) % 2) ) )
Using #define in c:
#define MAX(n, m) ( (n/2) + (m/2) + ( ((n/2) - (m/2)) * ( (2*((n/2) - (m/2)) + 1) % 2) ) )
or
#define ABS(n) ( n * ( (2*n + 1) % 2) ) // Calculates abs value of n
#define MAX(n, m) ( (n/2) + (m/2) + ABS((n/2) - (m/2)) ) // Finds max between n & m
#define MIN(n, m) ( (n/2) + (m/2) - ABS((n/2) - (m/2)) ) // Finds min between n & m
please look at this program.. this might be the best answer till date on this page...
#include <stdio.h>
int main()
{
int a,b;
a=3;
b=5;
printf("%d %d\n",a,b);
b = (a+b)-(a=b); // this line is doing the reversal
printf("%d %d\n",a,b);
return 0;
}
If A is always greater than B .. [ we can use] .. MAX = (A - B) + B;
No need. Just use: int maxA(int A, int B){ return A;}
(1) If conditionals are allowed you do max = a>b ? a : b.
(2) Any other method either use a defined set of numbers or rely on the implicit conditional checks.
(2a) max = a-((a-b)&((a-b)>>31)) this is neat, but it only works if you use 32 bit numbers. You can expand it arbitrary large number N, but the method will fail if you try to find max(N-1, N+1). This algorithm works for finite state automata, but not a Turing machine.
(2b) Magnitude |a-b| is a condition |a-b| = a-b>0 a-b : b-a
What about:
Square root is also a condition. Whenever c>0 and c^2 = d we have second solution -c, because (-c)^2 = (-1)^2*c^2 = 1*c^2 = d. Square root returns the greatest in the pair. I comes with a build in int max(int c1, int c2){return max(c1, c2);}
Without comparison operator math is very symmetric as well as limited in power. Positive and negative numbers cannot be distinguished without if of some sort.
It depends which language you're using, but the Ternary Operator might be useful.
But then, if you can't perform conditional checks in your 'scripting application', you probably don't have the ternary operator.
using System;
namespace ConsoleApp2
{
class Program
{
static void Main(string[] args)
{
float a = 101, b = 15;
float max = (a + b) / 2 + ((a > b) ? a - b : b - a) / 2;
}
}
}
#region GetMaximumNumber
/// <summary>
/// Provides method to get maximum values.
/// </summary>
/// <param name="values">Integer array for getting maximum values.</param>
/// <returns>Maximum number from an array.</returns>
private int GetMaximumNumber(params int[] values)
{
// Declare to store the maximum number.
int maximumNumber = 0;
try
{
// Check that array is not null and array has an elements.
if (values != null &&
values.Length > 0)
{
// Sort the array in ascending order for getting maximum value.
Array.Sort(values);
// Get the last value from an array which is always maximum.
maximumNumber = values[values.Length - 1];
}
}
catch (Exception ex)
{
throw ex;
}
return maximumNumber;
}
#endregion

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