C++: generate multidimensional vector of unknown depth - c++

Question

I have a function in C++ (call it
"weightmatrix") that takes a vector of size n as input, which contains a series of numbers a, b, c..., and returns an n-dimensional vector made up of subvectors of size c, b, a...
That was complicated sounding. Basically, in practice it should look like this:
vector<int> vector_sizes = {2, 3, 1};
cout << "Resulting matrix: " << weightmatrix(vector_sizes); // Function takes vector of size 3
/* Returns the following 3 dimensional matrix:
{ { {0, 0},
{0, 0},
{0, 0} },
{0, 0, 0} }
*/
It's a weird one, I know. I just need to generate a vector without knowing beforehand how many dimensions it will be. Any help or advice you could throw in my way would be awesome.

Answer 1

Here is a solution using a template MultiVector class that returns a MultiVectorView from it's operator[].
The underlying data is stored in a plain std::vector but can be accessed with the vec[x][y][z] syntax.
There is no checking for correct usage, and only very basic functionality is implemented but it gives an idea how it could be done.
#include <iostream>
#include <vector>
template <typename T>
class MultiVector;
template <typename T>
class MultiVectorView {
public:
MultiVectorView(MultiVector<T>& vec_, int index_, int dimension_) : vec(vec_), index(index_), dimension(dimension_) {}
MultiVector<T>& vec;
int index;
int dimension;
MultiVectorView& operator[](std::size_t n_index) {
int index_multiplyer = 1;
for (int i=0; i<dimension; ++i)
index_multiplyer *= vec.dimensions[i];
index += n_index*index_multiplyer;
dimension++;
return *this;
}
operator T() {
return vec.content[index];
}
MultiVectorView& operator=(T val) {
vec.content[index] = val;
return *this;
}
};
template <typename T>
class MultiVector {
public:
MultiVector(std::vector<int> dimensions_) : dimensions(dimensions_) {
int size = dimensions[0];
for (int i = 1; i<dimensions.size(); ++i)
size *= dimensions[i];
content.resize(size);
}
MultiVectorView<T> operator[](std::size_t index) {
return MultiVectorView<T>(*this, index, 1);
}
std::vector<T> content;
std::vector<int> dimensions;
};
int main() {
std::vector<int> v = {2,3,2};
MultiVector<int> test(v);
int tmp = 0;
for (int x = 0; x < v[0]; ++x)
for (int y = 0; y < v[1]; ++y)
for (int z = 0; z < v[2]; ++z) {
test[x][y][z] = tmp++;
}
for (int i=0; i<test.content.size(); ++i)
std::cout << std::endl << test.content[i] << " ";
int b = test[1][2][1];
std::cout << std::endl << "b = " << b << std::endl << "test[0][1][1] = " << test[0][1][1] << std::endl;
}

Answer 2

I took the hint of Galik to make a small sample:
#include <cassert>
#include <iostream>
#include <vector>
template <typename ELEM>
class NDArrayT {
private:
// dimensions
std::vector<size_t> _dims;
// data
std::vector<ELEM> _data;
public:
NDArrayT(const std::vector<size_t> &dims):
_dims(dims)
{
size_t size = _dims.empty() ? 0 : 1;
for (size_t dim : _dims) size *= dim;
_data.resize(size);
}
NDArrayT(
const std::vector<size_t> &dims,
const std::vector<ELEM> &data):
NDArrayT<ELEM>(dims)
{
assert(_data.size() == data.size());
std::copy(data.begin(), data.end(), _data.begin());
}
ELEM& operator[](const std::vector<size_t> &indices)
{
size_t i = 0, j = 0;
for (size_t n = _dims.size(); j < n; ++j) {
i *= _dims[j]; i += indices[j];
}
return _data[i];
}
const ELEM& operator[](const std::vector<size_t> &indices) const
{
size_t i = 0, j = 0;
for (size_t n = _dims.size(); j < n; ++j) {
i *= _dims[j]; i += indices[j];
}
return _data[i];
}
};
using namespace std;
ostream& operator<<(ostream &out, const vector<size_t> &values)
{
const char *sep = "";
for (size_t value : values) {
out << sep << value; sep = ", ";
}
return out;
}
bool inc(vector<size_t> &indices, const vector<size_t> &dims)
{
for (size_t i = indices.size(); i--;) {
if (++indices[i] < dims[i]) return false;
indices[i] = 0;
}
return true; // overflow
}
int main()
{
// build sample data
vector<double> data(2 * 3 * 4);
for (size_t i = data.size(); i--;) data[i] = (double)i;
// build sample array
typedef NDArrayT<double> NDArrayDouble;
const vector<size_t> dims = { 2, 3, 4 };
NDArrayDouble a(dims, data);
// print sample array (check subscript)
vector<size_t> indices(dims.size(), 0);
do {
cout << "a[" << indices << "]: " << a[indices] << endl;
} while (!inc(indices, dims));
// done
return 0;
}
Compiled and tested on ideone.
Output is:
a[0, 0, 0]: 0
a[0, 0, 1]: 1
a[0, 0, 2]: 2
a[0, 0, 3]: 3
a[0, 1, 0]: 4
a[0, 1, 1]: 5
a[0, 1, 2]: 6
a[0, 1, 3]: 7
a[0, 2, 0]: 8
a[0, 2, 1]: 9
a[0, 2, 2]: 10
a[0, 2, 3]: 11
a[1, 0, 0]: 12
a[1, 0, 1]: 13
a[1, 0, 2]: 14
a[1, 0, 3]: 15
a[1, 1, 0]: 16
a[1, 1, 1]: 17
a[1, 1, 2]: 18
a[1, 1, 3]: 19
a[1, 2, 0]: 20
a[1, 2, 1]: 21
a[1, 2, 2]: 22
a[1, 2, 3]: 23
The "arithmetic" to manage multi-dimensional arrays in contiguous memory is actually quite simple. I guess, the most "revolutionary" idea of this sample is the operator[]() which uses a std::vector<size_t> to provide the indices for each dimension.
While I was writing this down, a lot of alternatives for indexing came in my mind. – There is much space for fantasy...
E.g. for linear (one-dimensional) access, a second operator[] for size_t might be provided as well.