/+dub.sdl:
dependency "mir-algorithm" version="~>2.0.0"
+/
void main()
{
import mir.ndslice;
auto matrix = slice!double(3, 4);
matrix[] = 0;
matrix.diagonal[] = 1;
auto row = matrix[2];
row[3] = 6;
assert(matrix[2, 3] == 6); // D & C index order
import mir.stdio;
matrix.writeln;
// prints [[1.0, 0.0, 0.0, 0.0], [0.0, 1.0, 0.0, 0.0], [0.0, 0.0, 1.0, 6.0]]
}
/+dub.sdl:
dependency "mir-algorithm" version="~>2.0.0"
+/
void main()
{
import mir.ndslice;
import std.stdio : writefln;
enum fmt = "%(%(%.2f %)\n%)\n";
// Magic sqaure.
// `a` is lazy, each element is computed on-demand.
auto a = magic(5).as!float;
writefln(fmt, a);
// 5x5 grid on sqaure [1, 2] x [0, 1] with values x * x + y.
// `b` is lazy, each element is computed on-demand.
auto b = linspace!float([5, 5], [1f, 2f], [0f, 1f]).map!"a * a + b";
writefln(fmt, b);
// allocate a 5 x 5 contiguous matrix
auto c = slice!float(5, 5);
c[] = transposed(a + b / 2); // no memory allocations here
// 1. b / 2 - lazy element-wise operation with scalars
// 2. a + (...) - lazy element-wise operation with other slices
// Both slices must be `contiguous` or one-dimensional.
// 3. transposed(...) - trasposes matrix view. The result is `universal` (numpy-like) matrix.
// 5. c[] = (...) -- performs element-wise assignment.
writefln(fmt, c);
}
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