In MATLAB (and many other similar languages), we can construct such a matrix with
mat = zeros(A,B,C)
It does not appear that there is such a convenience constructor in Stata [J(.,.,.) appears to only construct 2D matrices]. Is there any way to construct a 3D matrix?
Strictly a matrix is two-dimensional, or one-dimensional as a special case. But we know what you mean.
Mata supports associative arrays.
In Stata, people would be more likely to set up a data structure with several variables as row identifier, column identifier, layer identifier, whatever, whatever else, and so on.
Related
I want to create a matrix in Armadillo, which can keep different datatypes in a matrix. For example, I want to have a matrix with three integer columns, a float column, and a column with enumeration value. Is there any solution?
Armadillo matrices store all elements internally as a standard C array of the element datatype. That means all elements must have the same type. This makes sense for armadillo since it is intended to be used for linear algebra and numerical computations, and not as a general container.
For your particular case it is probably better to simply create separated objects. You could, for instance, create a matrix of integers (arma::imat or arma::umat depending if you want sign), a vector of floats (arma::vec) and for the column of enumeration you could use std::vector.
Then you can create a struct with three fields to store these objects (or use a tuple) if you always want to keep them together (to easily pass them as arguments, for instance).
I understand what an array and a matrix is. I want to learn how to create 3D graphics and I want to know if a multi-demionsional array is the same as a matrix.
There are several uses of the term "matrix". Normally however we say that a matrix is a 2-dimensional array of scalar (integer or floating point) values, with known dimensions, an entry for every position (no missing values allowed), and arranged such that the columns represent observations about or operations on the rows of another matrix. So if we have a matrix with four columns, it only makes sense if we have another matrix or vector with four rows to which the four columns apply.
So the obvious way to represent a matrix in C++ is as a 2D array. But 2D arrays aren't identical with matrices. You might have a 2D array that is not a matrix (missing values which are uninitialised or nan), or a matrix that is not a 2D array (we could represent as a 1D array and do the index calculations manually, or as a "sparse matrix" where most values are expected to be zero and we just have a list of non-zero values).
Matrix is an abstract mathematical concept that can be modeled in C++ using a number of ways:
A two-dimensional array,
An array of pointers to arrays with arrays of identical size
A std::vector<std::vector<T>>
An std::array<N,std::array<M,T>>
A library-specific opaque implementation
The actual implementation is always specific to the drawing library that you have in mind.
Can anybody suggest a good C++ library for storing Multi-dimensional Sparse Matrix that focuses on the compression of data in matrix. The number of dimensions of the matrix will be huge (say, 80 dimensions). Any help is most welcome :).
EDIT:
The matrix is highly sparse, in the order of 0.0000001 (or) 1x10-6.
In c# I have used key value pairs or "dictionaries" to store sparse populated arrays. I think for 80 dimensions you would have to construct a string based key. Use a single function to create the key it should all remain consistent. Simply concatenate a comma separated list of the dimensions. Unfortunately I'm not aware of a good key pair, dictionary library for c++. Possibly STL if you have used it before but I would not recommend it otherwise.
I'm trying to write a C++ program that needs to store and adjust data in a 3D array. The size is given by the user and doesn't change throughout the run, and I don't need to perform any complicated matrix operations on it. I just need it to be optimized to set and get from given 3D coordinates (I do quite some iterations over all the members, and it's a big array). What's the best way to go about defining that array? Vector of vector of vector? Arrays of vectors? CvMat/IplImage with multi channels? Should I even keep it as 3D or just turn it into one very long interleaved vector and calculate indexes accordingly?
Thanks!
I would go with your last option, a single large array with transformed indices. If all you want to do is read and write known indices, this is probably the most efficient structure, both in terms of storage and speed. You can also wrap this in a class and overload operator () to make it easy to access 3D coordinates, for eg. you could write a(1,2,3) = 10; and the overloaded operator could take care transforming the 3D coordinates into a linear index. Iterating over such an array would also be quite simple since there's only one dimension.
It depends on what you mean by efficient, but have you looked at KD Trees?
I have a dense matrix where the indices correspond to genes. While gene identifiers are often integers, they are not contiguous integers. They could be strings instead, too.
I suppose I could use a boost sparse matrix of some sort with integer keys, and it wouldn't matter if they're contiguous. Or would this still occupy a great deal of space, particularly if some genes have identifiers that are nine digits?
Further, I am concerned that sparse storage is not appropriate, since this is an all-by-all matrix (there will be a distance in each and every cell, provided the gene exists).
I'm unlikely to need to perform any matrix operations (e.g., matrix multiplication). I will need to pull vectors out of the matrix (slices).
It seems like the best type of matrix would be keyed by a Boost unordered_map (a hash map), or perhaps even simply an STL map.
Am I looking at this the wrong way? Do I really need to roll my own? I thought I saw such a class somewhere before.
Thanks!
You could use a std::map to map the gene identifiers to unique, consecutively assigned integers (every time you add a new gene identifier to the map, you can give it the map's size as its identifier, assuming you never remove genes from the map).
If you want to be able to search for the identifier of a gene based on its unique integer, you can use a second map or you could use a boost::bimap, which provides a bidirectional mapping of elements.
As for which matrix container to use, you might consider boost::ublas::matrix; it provides vector-like access to rows and columns of the matrix.
If you don't need matrix operations, you don't need a matrix. A 2D map with string keys can be done with map<map<string> > in plain C++, or using a hash map accordingly from Boost.
There is Boost.MultiArray which will allow you to manage with non-continuous indexes.
If you want an efficient implementation working with matrices with static size, there is also Boost.LA, which in now on the review schedule.
And las there is also NT2 which should be submitted to Boost soon.