I need to use the equivalent of Excel's TINV function in a C++ code with no statistics library linked to it.
The problem is I don't know the maths behind Student's law.
Do you think it will be reasonable to reimplement this function from scratch without using a statistics library?
I don't have access to C++11, in that case I would use std::student_t_distribution.
If yes, please provide me references to code it.
If no, do you know a lightweight library that provides it?
Thank you.
Boost has a math library with statistics functions. Here is an example on how to use it for the student's t-test
http://www.boost.org/doc/libs/1_43_0/libs/math/doc/sf_and_dist/html/math_toolkit/dist/stat_tut/weg/st_eg/two_sample_students_t.html
Given the lack to this tool means you may have to write one. I'm already assuming that you looked and could not find one. The math isn't that bad though. It's just testing to see if two observed distributions have the same mean. www.r-tutor.com has a good tutorial on this distribution. Math World shows the deeper context. Happy hunting.
It's too much work without using a statistics library.
What I am gonna do is generate numeric values in Excel for the range of values I need and copy it in an array in my code.
Hardcore style.
Related
When I was using a matlab, I was using the method filloutliers. I was wondering if there is something similar to that in C++.
In other words, I want to know if there is any sort of a built-in method in a certain library that detect outliers in a data set and replace them.
No, there's no built-in standard library facility which does that. Numerical analysis is not a focus or a strong point of C++, though of course there are numerical analysis libraries available out there (available via a Google search). Note that Matlab's method is a very particular one: there's no precise and universal definition of an "outlier" (some would say there's no such thing as an outlier). So expect to have to come up with your own opinion of how to classify a point as an outlier.
Is there any best approach or template to follow, while doing this?
I mean two things in particular, because for me it is problematic to imagine how it would go in c++:
expanding arrays on go, where they are expanded during program and i dont know whethere the final size will be e.g. 10 or 100000.
plots. I have never done any plot in c++ as I always have been doing it in matlab when necessary.
So what templates or rules should I follow, and how could I cope with those two things?
I found that eigen library would be useful for matrices (dynamically expanding also?), but as I am not sure, want to ask first to be sure of a right approach. Nothing i know about plots.
Please add some link for me to learn from, if useful.
Thanks!
expanding arrays on go, where they are expanded during program and i dont know whethere the final size will be e.g. 10 or 100000.
The solution to this is simple: look up std::vector (or std::deque) both provide this behaviour. (With "subtle" differences between a deque and a vector).
plots. I have never done any plot in c++ as I always have been doing it in matlab when necessary.
For this you'll have to search for a library that can do this, first you'll have to look into a graphical window library such as Qt. And then you'll have to look up some library that can plot data in a graph form.
Though for this matlab will probably always be the "easier/better" choice; C++ has nothing to help you with this.
Also remember: first learn the language, then learn libraries!
For plotting using QT, QWT is basically all you need as it provides all the non trivial kind of charts one may need.
I've been wanting to write my own multithreaded realtime raytracer in C++, but I don't want to implement all the vector and matrix logic that comes with it. I figured I'd do some research to find a good library for this, but I haven't had much success...
It's important that the implementation is fast, and preferably that it comes with some friendly licensing. I've read that boost has basic algebra, but I couldn't find anything on how good it was regarding its speed.
For the rest, Google gave me Armadillo, which claims to be very fast, and compares itself to certain other libraries that I haven't heard of.
Then I got Seldon, which also claims to be efficient and convenient, although I couldn't find out where exactly they are on the scale.
Lastly I read about Eigen, which I've also seen mentioned here on StackOverflow while searching here.
In the CG lecture at my university, they use HLSL for the algebra (making the students implement/optimise parts of the raytracer), which got me thinking whether or not I could use GLSL for this. Again, I have no idea what option is most efficient, or what the general consensus is on algebra libraries. I was hoping SO could help me out here, so I can get started with some real development :)
PS: I tried linking to sites, but I don't have enough rep yet
I'd recommend writing your own routines. When I wrote my raytracer, I found that most of the algebra used the same small collection of methods. Basically all you need is a vector class that supports addition, subtraction, etc. And from there all you really need is Dot and Cross.
And to be honest using GLSL isn't going to give you much more than that anyways (they only support dot, cross and simple vector math, everything else must be hand coded). I'd also recommend prototyping in C++ then moving to CUDA afterwards. It's rather difficult to debug a GPU code, so you can get it working in the CPU then recode it a bit to work in CUDA.
In reality raytracers are fairly simple. It's making them fast that is hard. It's the acceleration structures that are going to take most of your time and optimization. At least it did for me.
You should take look at http://ompf.org/forum/
This forum treats of realtime raytracing, mostly in C++. It will give you pointers, and sample source.
Most of the time, as every cycle count, people do not rely on external vector math libs: optimizations depend on the compiler you're using, inlining, use of SSE (or kindof) or not, etc.
I recommend "IlmBase" that is part of the OpenEXR package. It's well-written C++, developed by ILM, and widely used by people who professionally write and use graphics software.
For my projects I used glm, maybe it would also suit you.
Note that libraries such as boost::ublas or seldon probably won't suit you, because they're BLAS-oriented (and I assume you're looking for a good 3D-driven linear algebra library).
Also, the dxmath DirectX library is pretty good, although sometimes hard to use, because of it's C-compatible style.
You might look at the source code for POVRAY
I am newbie for integer linear programming.
I plan to use a integer linear programming solver to solve my combinatorial optimization problem.
I am more familiar with C++/object oriented programming on an IDE.
Now I am using NetBeans with Cygwin to write my applications most of time.
May I ask if there is an easy use ILP solver for me?
Or it depends on the problem I want to solve ? I am trying to do some resources mapping optimization. Please let me know if any further information is required.
Thank you very much, Cassie.
If what you want is linear mixed integer programming, then I would point to Coin-OR (and specifically to the module CBC). It's Free software (as speech)
You can either use it with a specific language, or use C++.
Use C++ if you data requires lots of preprocessing, or if you want to put your hands into the solver (choosing pivot points, column generation, adding cuts and so on...).
Use the integrated language if you want to use the solver as a black box (you're just interested in the result and the problem is easy or classic enough to be solved without tweaking).
But in the tags you mention genetic algorithms and graphs algorithms. Maybe you should start by better defing your problem...
For graphs I like a lot Boost::Graph
I have used lp_solve ( http://lpsolve.sourceforge.net/5.5/ ) on a couple of occasions with success. It is mature, feature rich and is extremely well documented with lots of good advice if your linear programming skills are rusty. The integer linear programming is not a just an add on but is strongly emphasized with this package.
Just noticed that you say you are a 'newbie' at this. Well, then I strongly recommend this package since the documentation is full of examples and gentle tutorials. Other packages I have tried tend to assume a lot of the user.
For large problems, you might look at AMPL, which is an optimization interpreter with many backend solvers available. It runs as a separate process; C++ would be used to write out the input data.
Then you could try various state-of-the-art solvers.
Look into GLPK. Comes with a few examples, and works with a subset of AMPL, although IMHO works best when you stick to C/C++ for model setup. Copes with pretty big models too.
Linear Programming from Wikipedia covers a few different algorithms that you could do some digging into to see which may work best for you. Does that help or were you wanting something more specific?
I would need some basic vector mathematics constructs in an application. Dot product, cross product. Finding the intersection of lines, that kind of stuff.
I can do this by myself (in fact, have already) but isn't there a "standard" to use so bugs and possible optimizations would not be on me?
Boost does not have it. Their mathematics part is about statistical functions, as far as I was able to see.
Addendum:
Boost 1.37 indeed seems to have this. They also gracefully introduce a number of other solutions at the field, and why they still went and did their own. I like that.
Re-check that ol'good friend of C++ programmers called Boost. It has a linear algebra package that may well suits your needs.
I've not tested it, but the C++ eigen library is becoming increasingly more popular these days. According to them, they are on par with the fastest libraries around there and their API looks quite neat to me.
Armadillo
Armadillo employs a delayed evaluation
approach to combine several operations
into one and reduce (or eliminate) the
need for temporaries. Where
applicable, the order of operations is
optimised. Delayed evaluation and
optimisation are achieved through
recursive templates and template
meta-programming.
While chained operations such as
addition, subtraction and
multiplication (matrix and
element-wise) are the primary targets
for speed-up opportunities, other
operations, such as manipulation of
submatrices, can also be optimised.
Care was taken to maintain efficiency
for both "small" and "big" matrices.
I would stay away from using NRC code for anything other than learning the concepts.
I think what you are looking for is Blitz++
Check www.netlib.org, which is maintained by Oak Ridge National Lab and the University of Tennessee. You can search for numerical packages there. There's also Numerical Recipes in C++, which has code that goes with it, but the C++ version of the book is somewhat expensive and I've heard the code described as "terrible." The C and FORTRAN versions are free, and the associated code is quite good.
There is a nice Vector library for 3d graphics in the prophecy SDK:
Check out http://www.twilight3d.com/downloads.html
For linear algebra: try JAMA/TNT . That would cover dot products. (+matrix factoring and other stuff) As far as vector cross products (really valid only for 3D, otherwise I think you get into tensors), I'm not sure.
For an extremely lightweight (single .h file) library, check out CImg. It's geared towards image processing, but has no problem handling vectors.