I am doing a simple calculator in xcode. I have done the basic functions such as +,/, -,1/x, √. Now i am trying to do the % functionality. Not sure how to start on this.. Need some guidance on this...
Edited:
5/8% = 62.5
5x8%=0.4
5+8% = 5.4
5-8% = 4.6
It should be able to handle different functions before it.. That's why i am confused...
If you mean the modulo operator:
For integers simply use
int result = a % b;
For floats use fmod (math.h)
float result = fmod(a, b);
If you mean the percent operator you have to remember that taking X percent of something is the same as multiplying it with X/100:
float result = a * X / 100.f; // result will be X percent of a.
EDIT (to answer your edited question):
That's not how a percentage operator works on any calculator I know. The percentage sign is just a division by 100. So in your example:
5/8% = 5/8/100 = 0.00625
5x8% = 5x8/100 = 0.4
5+8% = 5+8/100 = 5.08
5-8% = 5-8/100 = 4.92
I think what you mean by 5+8% is actually 5+5x8% or 5+5x8/100.
Related
I'd like to be able to use the vDSP_biquad function as a one pole filter.
My one pole filter looks like this :
output[i] = onePole->z1 = input[i] * onePole->a0 + onePole->z1 * onePole->b1;
where
b1 = exp(-2.0 * M_PI * (_frequency / sampleRate));
a0 = 1.0 - b1;
This one pole works great, but of course it's not optimized, which is why I'd like to use the Accelerate Framework to speed it up.
Because vDSP_biquad uses the Direct Form II of the biquad implementation, it seems to me I should be able to set the coefficients to use it as a one-pole filter. https://en.wikipedia.org/wiki/Digital_biquad_filter#Direct_form_2
filter->omega = 2 * M_PI * freq / sampleRate;
filter->b1 = exp(-filter->omega);
filter->b0 = 1 - filter->b1;
filter->b2 = 0;
filter->a1 = 0;
filter->a2 = 0;
However, this does not work as a one pole filter. (The implementation of biquad is fine, I use it for many other filter types, it's just these coefficients don't have the desired effect).
What am I doing wrong?
Also open to hearing other ways to optimize a one-pole filter with Accelerate or otherwise.
The formula in the Apple docs is:
y[n] = b0*x[n] + b1*x[n-1] + b2*x[n-2] - a1*y[n-1] - a2*y[n-2]
In your above code, you're using b1 which is two inputs ago. For a one-pole, you'll need to use the previous output, y[n-1].
So I think the coefficients you want are:
a1 = -exp(-2.0 * M_PI * (_frequency / sampleRate))
b0 = 1.0 + a1
Apologies if this has been asked already - not sure what to search for.
Simple bit of code:
double x = 4505;
double y = 1000;
double z = 1000000;
double result = (x * y) / z;
Answer should be 4.505; but I get:
result = 4.5049999999999999
The values of x, y and z could be anything, and sometimes I need that level of precision in the result but I can't see why this is happening.
The Question is how to I remove the rounding error so that I can re-run further calculations on the decimal value without getting erroneous results and at the same time maintain high level of precision for numbers that need it.
It's simply a Floating Point Rounding Error. Also there is this.
If you want result rounded to 3 decimal places, then use:
result = floor(result * 1000.0) / 1000.0;
or just during presentation:
NSLog(#"result = %.3f", result);
I'm trying to build a simple program to price call options using the black scholes formula http://en.wikipedia.org/wiki/Black%E2%80%93Scholes. I'm trying to figure our the best way to get probabilities from a normal distribution. For example if I were to do this by hand and I got the value of as d1=0.43 than I'd look up 0.43 in this table http://www.math.unb.ca/~knight/utility/NormTble.htm and get the value 0.6664.
I believe that there are no functions in c or objective-c to find the normal distribution. I'm also thinking about creating a 2 dimensional array and looping through until I find the desired value. Or maybe I can define 300 doubles with the corresponding value and loop through those until I get the appropriate result. Any thoughts on the best approach?
You need to define what it is you are looking for more clearly. Based on what you posted, it appears you are looking for the cumulative distribution function or P(d < d1) where d1 is measured in standard deviations and d is a normal distribution: by your example, if d1 = 0.43 then P(d < d1) = 0.6664.
The function you want is called the error function erf(x) and there are some good approximations for it.
Apparently erf(x) is part of the standard math.h in C. (not sure about objective-c but I assume it probably contains it as well).
But erf(x) is not exactly the function you need. The general form P(d < d1) can be calculated from erf(x) in the following formula:
P(d<d1) = f(d1,sigma) = (erf(x/sigma/sqrt(2))+1)/2
where sigma is the standard deviation. (in your case you can use sigma = 1.)
You can test this on Wolfram Alpha for example: f(0.43,1) = (erf(0.43/sqrt(2))+1)/2 = 0.666402 which matches your table.
There are two other things that are important:
If you are looking for P(d < d1) where d1 is large (greater in absolute value than about 3.0 * sigma) then you should really be using the complementary error function erfc(x) = 1-erf(x) which tells you how close P(d < d1) is to 0 or 1 without running into numerical errors. For d1 < -3*sigma, P(d < d1) = (erf(d1/sigma/sqrt(2))+1)/2 = erfc(-d1/sigma/sqrt(2))/2, and for d1 > 3*sigma, P(d < d1) = (erf(d1/sigma/sqrt(2))+1)/2 = 1 - erfc(d1/sigma/sqrt(2))/2 -- but don't actually compute that; instead leave it as 1 - K where K = erfc(d1/sigma/sqrt(2))/2. For example, if d1 = 5*sigma, then P(d < d1) = 1 - 2.866516*10-7
If for example your programming environment doesn't have erf(x) built into the available libraries, you need a good approximation. (I thought I had an easy one to use but I can't find it and I think it was actually for the inverse error function). I found this 1969 article by W. J. Cody which gives a good approximation for erf(x) if |x| < 0.5, and it's better to use erf(x) = 1 - erfc(x) for |x| > 0.5. For example, let's say you want erf(0.2) ≈ 0.2227025892105 from Wolfram Alpha; Cody says evaluate with x * R(x2) where R is a rational function you can get from his table.
If I try this in Javascript (coefficients from Table II of the Cody paper):
// use only for |x| <= 0.5
function erf1(x)
{
var y = x*x;
return x*(3.6767877 - 9.7970565e-2*y)/(3.2584593 + y);
}
then I get erf1(0.2) = 0.22270208866303123 which is pretty close, for a 1st-order rational function. Cody gives tables of coefficients for rational functions up to degree 4; here's degree 2:
// use only for |x| <= 0.5
function erf2(x)
{
var y = x*x;
return x*(21.3853322378 + 1.72227577039*y + 0.316652890658*y*y)
/ (18.9522572415 + 7.8437457083*y + y*y);
}
which gives you erf2(0.2) = 0.22270258922638206 which is correct out to 10 decimal places. The Cody paper also gives you similar formulas for erfc(x) where |x| is between 0.5 and 4.0, and a third formula for erfc(x) where |x| > 4.0, and you can check your results with Wolfram Alpha or known erfc(x) tables for accuracy if you like.
Hope this helps!
I need to divide one int into 2 other int's. the first int is not constant so one problem would be, what to do with odd numbers because I only want whole numbers. For example, if int = 5, then int(2) will = 2 and int(3) will = 3. Any help will greatly be appreciated.
Supposing you want to express x = a + b, where a and b are as close to x/2 as possible:
a = ceiling(x / 2.0);
b = floor(x / 2.0);
That's pseudo code, you have to find out the actual functions for floor and ceiling from your library. Make sure the division is performed as floating point numbers.
As pure integers:
a = x / 2 + (x % 2 == 0 ? 0 : 1);
b = x / 2
(This may be a bit fishy for negative numbers, because it'll depend on the behaviour of division and modulo for negative numbers.)
You can try ceil and floor functions from math to produce results like 2 and 3 for odd inputs;
int(2)=ceil(int/2); //will produce 3 for input 5
int(3)=floor(int/2); //will produce 2 for input 5
Well my answer is not in Objective-C but i guess you could translate this easily.
My idea is:
part1 = source_number div 2
part2 = source_number div 2 + (source_number mod 2)
This way the second number will be bigger if the starting number is an odd number.
I'm trying to make a generic equation which converts a value. Here are some examples.
9,873,912 -> 9,900,000
125,930 -> 126,000
2,345 -> 2,400
280 -> 300
28 -> 30
In general, x -> n
Basically, I'm making a graph and I want to make values look nicer. If it's a 6 digit number or higher, there should be at least 3 zeros. If it's a 4 digit number or less, there should be at least 2 digit numbers, except if it's a 2 digit number, 1 zero is fine.
(Ignore the commas. They are just there to help read the examples). Anyways, I want to convert a value x to this new value n. What is an equation g(x) which spits out n?
It is for an objective-c program (iPhone app).
Divide, truncate and multiply.
10**x * int(n / 10**(x-d))
What is "x"? In your examples it's about int(log10(n))-1.
What is "d"? That's the number of significant digits. 2 or 3.
Ahhh rounding is a bit awkward in programming in general. What I would suggest is dividing by the power of ten, int cast and multiplying back. Not remarkably efficient but it will work. There may be a library that can do this in Objective-C but that I do not know.
if ( x is > 99999 ) {
x = ((int)x / 1000) * 1000;
}
else if ( x > 999 ) {
x = ((int) x / 100) * 100;
}
else if ( x > 9 ) {
x = ((int) x / 10) * 10;
}
Use standard C functions like round() or roundf()... try man round at a command line, there are several different options depending on the data type. You'll probably want to scale the values first by dividing by an appropriate number and then multiplying the result by the same number, something like:
int roundedValue = round(someNumber/scalingFactor) * scalingFactor;