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extend matlab conversion table
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@ -43,6 +43,8 @@ MatrixXd::Random(rows,cols) // rand(rows,cols)*2-1 // MatrixXd::R
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C.setRandom(rows,cols) // C = rand(rows,cols)*2-1
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VectorXd::LinSpaced(size,low,high) // linspace(low,high,size)'
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v.setLinSpaced(size,low,high) // v = linspace(low,high,size)'
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VectorXi::LinSpaced(((hi-low)/step)+1, // low:step:hi
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low,low+step*(size-1))
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// Matrix slicing and blocks. All expressions listed here are read/write.
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@ -85,13 +87,15 @@ P.bottomRightCorner<rows,cols>() // P(end-rows+1:end, end-cols+1:end)
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R.row(i) = P.col(j); // R(i, :) = P(:, i)
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R.col(j1).swap(mat1.col(j2)); // R(:, [j1 j2]) = R(:, [j2, j1])
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// Views, transpose, etc; all read-write except for .adjoint().
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// Views, transpose, etc;
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// Eigen // Matlab
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R.adjoint() // R'
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R.transpose() // R.' or conj(R')
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R.diagonal() // diag(R)
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R.transpose() // R.' or conj(R') // Read-write
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R.diagonal() // diag(R) // Read-write
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x.asDiagonal() // diag(x)
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R.transpose().colwise().reverse(); // rot90(R)
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R.transpose().colwise().reverse() // rot90(R) // Read-write
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R.replicate(i,j) // repmat(P,i,j)
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// All the same as Matlab, but matlab doesn't have *= style operators.
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// Matrix-vector. Matrix-matrix. Matrix-scalar.
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@ -134,6 +138,8 @@ R.array().abs() // abs(P)
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R.cwiseAbs2() // abs(P.^2)
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R.array().abs2() // abs(P.^2)
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(R.array() < s).select(P,Q ); // (R < s ? P : Q)
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R = (Q.array()==0).select(P,A) // R(Q==0) = P(Q==0)
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// Reductions.
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int r, c;
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