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I'm programming some financial software needing to program not very complicated mathematical formulas.
After writing the code, it is not readable anymore - i.e - you can't easily discern what was the original formula.
What would be a good way to program mathematical formulas so they could be easily read later on?
For example, programming a calculation for a loan with a fixed interest rate:
(TotalValue*monthlyInterest*Math.pow((1+monthlyInterest),totalPayments))/(Math.pow((1+monthlyInterest),totalPayments) - 1)
Though using meaningful variables, the formula is not readable. But if you will look at this formula written in a classical mathematical notation on a page - you will easily know what's going on (really basic math).
How would you even take this formula and write it in a readable way.
Clarification
I'm not talking about any specific language. This should be the same for any high-level language.
The example uses Javascript.
You could also add local variables that are abbreviations of the long name. As they are local, their definition will be right above the formula. This could look like
TV = TotalValue;
mi = monthlyInterest;
N = totalPayments;
MR = ( TV*mi*Math.pow( 1+mi, N ) ) / ( Math.pow( 1+mi, N ) - 1)
MonthlyRate = MR;
where you then see that you can simplify the formula to
MR = (TV*mi) / ( 1 - Math.pow( 1+mi , -N) - 1)
As far as i know, it is not possible to convert Excel formulas to equations
But for clarity, you could recreate the Equation in the Equation Editor and put it next to the cell. This way it is immediately obvious what you are doing.
Another way would be to create the Mathematical Equation and add a macro. This way you could calculate your values in VBA.
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Is the following code example, calling a function in the parameters line of another function, acceptable? Or will I run in problems somehow?
newfunction <- function(df = merge_two_df(), size = define_size()){
... do something
}
This is basically a question of what you gain and lose compared to the alternatives.
So first let's look at the alternatives:
Option1
newfunction <- function(){
df = merge_two_df(), size = define_size()
... do something
}
Option2
newfunction <- function(df,size){
... do something
}
newfunction(merge_two_df(),define_size())
Comparing your status-quo to option 1 shows that your current way is more flexible. You have defined default values for each parameter but retain the option to use other parameters. So there is nothing to gain hard-coding the parameter definition into the body of the function.
Now comparing to option 2, your current way is actually more standardized because you have defined defaults. You can simply and cleanly call your function without any parameters while having the same flexibility of switching up parameters if you want. However on the flip side you are a bit less explicit in calling these parameters which might be bad in terms of documentation and clarity when rereading the code.
If this function is part of a module that might be used/exported across several projects some even done by someone other then yourself, then I'd argue for option 2 to be simpler and clearer.
Otherwise what you do right now works best.
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I am by no means a math person, but I am really trying to figure out how create a graphable function from some data plots I measure from a chemical titration. I have been trying to learn R and I would like to know if anyone can explain to me or point me to a guide to create a mathmatic function of the titration graph below.
Thanks in advance.
What you are looking for is a Interpolation. I'm not a R programmer, but I'll try to answer anyway.
Some of the more common ways to achieve this function you want is by Polynomial Interpolation which usually gives back a Nth degree polynomial function, where N is the number of data points minus one (1 point gives a constant, 2 points make a line, 3 makes a*x^2 + b*x + c and so on).
Other common alternatives I've learn are used in Computer Graphics are Splines, B-spline, Bézier curve and Hermite interpolation. Those make the curve smoother and good looking (I've told they originated in the car industry so they are less true to the data points).
TL;DR: I've found evidence that there is a implementation of spline in R from the question Interpolation in R which may lead you to your solution.
Hope you get to know better your tool and do a great work.
When doing this kind of work in Computer Science we call it Numerical Methods (at least here in my university), I've done some class and homework in this area while attending to the Numerical Methods Course (it can be found at github) but it's nothing worth noting.
I would add a lot of links to Wikipedia but StackOverflow didn't allow it.
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I have to calculate the probability distribution function of a random variable that is composed of (sum, division, product, exponentiation, etc...) some other simple random variables. It is pretty complex so I am morte then happy to get a numerical solution
While thought this was a very standard thing to do , I was unable to find a framework to do that. I'd preferably use R, but any major language will do.
What I would like therefore is a library that allowed me to:
i) create numerical random variables from classic distributions
ii) compose them by simple operations (+,-,*,/, exp,min, max,...)
Of course I could work with vectors and use convolutions and the like, but I wanted something more polished.
I am also aware that is possible to use simulation to create the variables, then compose them with the operations and finally getting the PDF using a histogram, but again, I would prefer a non - simulating approach.
Try the rv package. Note that if X is an exponential random variable with mean 1, then -log(X) has a standard Gumbel distribution.
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My employer asked me to do a project for our local team. Actually, it will be a way to help our work to finished faster.
We have a local database where we add exercises divided in two fields. The question and the solution. My employer wants since we are a team and we work at the same time, to create a system like stackoverflow's similar questions. When one of the team tries to submit a new data in the database, then it will check if there are other fields which may be duplicates.
The reason he asked me is because I have done something similar in the past but only for text using techniques like TF-IDF and Latent Semantic Analysis. But now, since the math symbols are all in Latex, I cannot find a way to check for duplicates.
I have tried to apply TF-IDF to the text only, but it doesn't work.
Any suggestion?
Edit:
Sorry for the broad topic. I will try to give more examples about my problem.
All the texts are exercises of primary and secondary schools. It is a mix of text and numbers-equations-symbols. If there were only text, I could use TF-IDF to find possible duplicates. Now, several exercises have a little or are without text.
Examples:
1) a. Solve the following equation: (x+1)*(x-1) = 5
b. Find the x: x^2 - 1 = 5
They are the same equation but with a different expression. So, I don't want to mark them as duplicates.
2) a. Solve the following equation: 3x + 7 = 12
b. Find the solution: 7 + 3x = 12
c. Find the x: 3x = 12 - 7
a and b should be duplicate whereas the c will not be.
You could try using MathJax to convert the LaTeX equation into MathML an XML format. You could then use tools to examine that structure. There are probably a few other tools which can convert your equation into some kind of tree structure.
Equality of mathematical expressions is a complex problem. There are question that should you treat (x+1)*(x-1) as being equal to x^2-1, algebraically they are the same.
You might want to investigate computer algebra systems which have a lot of sophisticated features for manipulating expressions.
One technique is to evaluate the expression at a number of points. If the values agree then its a good indication that the expressions are the same.
It might be easier to give a better answer if there was some idea of the type of problems you are working with, polynomials, integrals etc.?
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i'd like to know how to solve a definite integral in Mathematica.
I do know all variables except b, and need to solve for F(b)=0.
How can i solve it in Mathematica?
Here is my try:
NSolve[Integrate[1/(8*(1 - ff) (2 Pi)^0.5) E^(-0.5*((x - 1.1)/(1 - ff)/8)^2), {x, 0, 9999}] == -0.44531779637243296, ff]
These integrals can be trivially expressed in terms of an error function: Wiki, Mathworld. Hence what you need here is a library to (i) calculate error functions, (ii) numerically solve non-linear equations. Virtually any language has this, so pick anything you're familiar with. In Mathematica, look up Erf and NSolve.
I'd start by plugging it into Wolfram Alpha and see what it gives you.
Mathematica should be able to do it. I think of statistics first when R comes up; I don't know about its calculus capabilities. Excel is not the first choice.
If I were you, I'd be less worried about the software and more worried about the solution itself. A function of this form might be well known. Plot each one and visually check to see what the functions look like and how easy they might be to integrate.
Like this:
http://www.wolframalpha.com/input/?i=graph+exp%28-%28%28x%2B5%29%2F1.5%29%5E2%29
You should be wondering why it's three similar looking integrals. Those singularities in the plot tell you why.
If there's no closed form solutions, you'll have to go with a numerical one. You'll have to choose an algorithm (simple Euler or Runga Kutta or something else), interval sizes, etc. You'll want to know about singular points and how best to tackle them.
Choosing a package is just the start.
You might find http://r.789695.n4.nabble.com/calculus-using-R-td1676727.html helpful.