Solving Newton interpolation with c

In summary: The code is available online for free.Is it?? The code is available online for free, but it is restricted to use on one computer. You are not allowed to copy or distribute the code.
  • #1
dabillionaire
2
0
Hi,

i have no idea how to start up my program on Newton interpolation. i have solved it manually but I am clueless on how 2 start my program. below represnts the input which i want 2 solve. every 4 lines represnts one problem. the 1st line- n,m where n is no of data points and m is no of evaluation pts. 2nd and 3rd line represent x and y of n pts. 4th line is m @ which it is to be evaluated. the function is sinx. can anyone help me out??


3 2
0.1 0.4 0.5
3.1 3.2 4.1
1.5 1.6
3 5
1.0 2.0 3.0
1.7 1.8 1.1
1.1 1.2 1.4 1.3 1.8
15 5
0.1 0.4 0.5 1.2 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 2.95
3.1 3.2 4.1 2.7 1.9 1.7 1.8 1.1 1.7 1.8 1.1 1.7 1.8 1.1 2.3
1.0 1.2 1.6 2.0 2.5

ma output is supposed to be in d form

e1 fN(e1)
e2 fN(e2)
.
.
em fN(em)
 
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  • #2
e1, e2 and em represent the fourth line of each problem
 
  • #3
Numerical recipes ( http://www.nr.com/ ) is the classic book on doing this sort of thing.
The code is available online for free. The book is sometimes available depending on what they feel like that day.

You can usually pick up the older editions of the Fortran/Pascal or C versions cheaply.
 
  • #4
mgb_phys said:
Numerical recipes ( http://www.nr.com/ ) is the classic book on doing this sort of thing.
The code is available online for free.
Is it?? They have the most restrictive terms for its code one can find for a book. Is the code for the old version now free (in whatever sense)? I can't find it on their website, only links to buy its code cd-rom.

The book is sometimes available depending on what they feel like that day.
LMAO. How true, how true. :rofl:
 
  • #5
It's not there anymore, sometimes you can read the whole book online, sometimes you can download the code - they are an amazing bunch.

The license for the code used to say something like -
"you can't copy this code from the disk, you can type it out of the book but you can't change anything. We own the copyright on the algorithms - you can't use the algorithms and change the code."

There was a bunch of lecturers who boycotted the book and lobbyed CUP to stop publishing it. It would be a bit embarrasing when CUP would have to sue the Cambridge University Library.
 
  • #6
Yeah. It was noted in an http://www.accu.org/" review of the 2nd edition C version that one can't even typed the code into one's own computer if you didn't own the book. i.e. you got it out of the library / workplace etc.

The 2nd edition C version said:
* You can type the programs from this book directly into your computer. In this case, the only kind of license available to you is the free "immediate license" (see below). You are not authorized to transfer or distribute a machine-readable copy to any other person, nor to have any other person type the programs into a computer on your behalf. ...
* ["Immediate License"] If you are the individual owner of a copy of this book and you type one or more of its routines into your computer, we authorize you to use them on that compuerter for your own personal and noncommercial purposes. You are not authorized to transfer or distribute machine-readable copies to any other person, or to use the routines on more than one machine, or to distribute executable programs containing our routines. This is the only free license.

So you have to own the book, you're not allowed to have another person type the code in for you. It's only available for personal use, and only on 1 computer each time you type the code in, specifically the one you typed the code in on. If you want to use the code (for personal use) on more than one computer, you have to type it in each time.
 
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  • #7
And worst of all they have the C arrays start from 1 (or they do in my 1988 'C' edition)
 
  • #8
There were some weird C compilers back in early DOS days that used something called an option-base setting, defined in a header file: 0 = normal C; 1= arrays start at 1 like BASIC. I don't know why.

Since everything in Numerical Recipes is available thru the GNU Scientific library, just pitch the damn thing. GSL is free.
 
  • #9
I think my 'C' edition was a too close copy of the Fortran one.

The explanations of the algorithms are still quite good. Even if you are going to use NAG or GSL it's a good first place to look for which algorithm you should use and what the problems might be.
 

1. What is Newton interpolation with c?

Newton interpolation with c is a mathematical method used to approximate a function or set of data points using a polynomial curve. It involves using known data points and their corresponding values to calculate a polynomial equation that can then be used to estimate values for other points within the given range.

2. How is Newton interpolation with c different from other interpolation methods?

Newton interpolation with c is based on the Newton polynomial, which is a more efficient and accurate way of calculating the interpolation polynomial compared to other methods such as Lagrange interpolation. It also allows for easier incorporation of new data points without having to redo the entire calculation.

3. What is the role of the constant term (c) in Newton interpolation?

The constant term (c) in Newton interpolation is used to represent the unknown coefficients of the polynomial equation. It is calculated using a divided difference table, which is a method of organizing and simplifying the calculation process.

4. What are the limitations of Newton interpolation with c?

One limitation of Newton interpolation with c is that it can only be used on equally spaced data points. It also becomes less accurate as the degree of the polynomial increases, and may not be suitable for highly oscillatory functions.

5. How is Newton interpolation with c used in real-world applications?

Newton interpolation with c has various applications in fields such as engineering, economics, and computer graphics. It can be used to approximate and interpolate data points in order to make predictions, analyze trends, and create smooth curves for visualization purposes.

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