Squashed 'third_party/eigen/' changes from 61d72f6..cf794d3
Change-Id: I9b814151b01f49af6337a8605d0c42a3a1ed4c72
git-subtree-dir: third_party/eigen
git-subtree-split: cf794d3b741a6278df169e58461f8529f43bce5d
diff --git a/doc/AsciiQuickReference.txt b/doc/AsciiQuickReference.txt
index b9f497f..0ca54ce 100644
--- a/doc/AsciiQuickReference.txt
+++ b/doc/AsciiQuickReference.txt
@@ -32,17 +32,19 @@
B << A, A, A; // B is three horizontally stacked A's.
A.fill(10); // Fill A with all 10's.
-// Eigen // Matlab
-MatrixXd::Identity(rows,cols) // eye(rows,cols)
-C.setIdentity(rows,cols) // C = eye(rows,cols)
-MatrixXd::Zero(rows,cols) // zeros(rows,cols)
-C.setZero(rows,cols) // C = ones(rows,cols)
-MatrixXd::Ones(rows,cols) // ones(rows,cols)
-C.setOnes(rows,cols) // C = ones(rows,cols)
-MatrixXd::Random(rows,cols) // rand(rows,cols)*2-1 // MatrixXd::Random returns uniform random numbers in (-1, 1).
-C.setRandom(rows,cols) // C = rand(rows,cols)*2-1
-VectorXd::LinSpaced(size,low,high) // linspace(low,high,size)'
-v.setLinSpaced(size,low,high) // v = linspace(low,high,size)'
+// Eigen // Matlab
+MatrixXd::Identity(rows,cols) // eye(rows,cols)
+C.setIdentity(rows,cols) // C = eye(rows,cols)
+MatrixXd::Zero(rows,cols) // zeros(rows,cols)
+C.setZero(rows,cols) // C = zeros(rows,cols)
+MatrixXd::Ones(rows,cols) // ones(rows,cols)
+C.setOnes(rows,cols) // C = ones(rows,cols)
+MatrixXd::Random(rows,cols) // rand(rows,cols)*2-1 // MatrixXd::Random returns uniform random numbers in (-1, 1).
+C.setRandom(rows,cols) // C = rand(rows,cols)*2-1
+VectorXd::LinSpaced(size,low,high) // linspace(low,high,size)'
+v.setLinSpaced(size,low,high) // v = linspace(low,high,size)'
+VectorXi::LinSpaced(((hi-low)/step)+1, // low:step:hi
+ low,low+step*(size-1)) //
// Matrix slicing and blocks. All expressions listed here are read/write.
@@ -82,17 +84,20 @@
// Of particular note is Eigen's swap function which is highly optimized.
// Eigen // Matlab
-R.row(i) = P.col(j); // R(i, :) = P(:, i)
+R.row(i) = P.col(j); // R(i, :) = P(:, j)
R.col(j1).swap(mat1.col(j2)); // R(:, [j1 j2]) = R(:, [j2, j1])
-// Views, transpose, etc; all read-write except for .adjoint().
+// Views, transpose, etc;
// Eigen // Matlab
R.adjoint() // R'
-R.transpose() // R.' or conj(R')
-R.diagonal() // diag(R)
+R.transpose() // R.' or conj(R') // Read-write
+R.diagonal() // diag(R) // Read-write
x.asDiagonal() // diag(x)
-R.transpose().colwise().reverse(); // rot90(R)
-R.conjugate() // conj(R)
+R.transpose().colwise().reverse() // rot90(R) // Read-write
+R.rowwise().reverse() // fliplr(R)
+R.colwise().reverse() // flipud(R)
+R.replicate(i,j) // repmat(P,i,j)
+
// All the same as Matlab, but matlab doesn't have *= style operators.
// Matrix-vector. Matrix-matrix. Matrix-scalar.
@@ -104,37 +109,40 @@
R -= Q; R /= s;
// Vectorized operations on each element independently
-// Eigen // Matlab
-R = P.cwiseProduct(Q); // R = P .* Q
-R = P.array() * s.array();// R = P .* s
-R = P.cwiseQuotient(Q); // R = P ./ Q
-R = P.array() / Q.array();// R = P ./ Q
-R = P.array() + s.array();// R = P + s
-R = P.array() - s.array();// R = P - s
-R.array() += s; // R = R + s
-R.array() -= s; // R = R - s
-R.array() < Q.array(); // R < Q
-R.array() <= Q.array(); // R <= Q
-R.cwiseInverse(); // 1 ./ P
-R.array().inverse(); // 1 ./ P
-R.array().sin() // sin(P)
-R.array().cos() // cos(P)
-R.array().pow(s) // P .^ s
-R.array().square() // P .^ 2
-R.array().cube() // P .^ 3
-R.cwiseSqrt() // sqrt(P)
-R.array().sqrt() // sqrt(P)
-R.array().exp() // exp(P)
-R.array().log() // log(P)
-R.cwiseMax(P) // max(R, P)
-R.array().max(P.array()) // max(R, P)
-R.cwiseMin(P) // min(R, P)
-R.array().min(P.array()) // min(R, P)
-R.cwiseAbs() // abs(P)
-R.array().abs() // abs(P)
-R.cwiseAbs2() // abs(P.^2)
-R.array().abs2() // abs(P.^2)
-(R.array() < s).select(P,Q); // (R < s ? P : Q)
+// Eigen // Matlab
+R = P.cwiseProduct(Q); // R = P .* Q
+R = P.array() * s.array(); // R = P .* s
+R = P.cwiseQuotient(Q); // R = P ./ Q
+R = P.array() / Q.array(); // R = P ./ Q
+R = P.array() + s.array(); // R = P + s
+R = P.array() - s.array(); // R = P - s
+R.array() += s; // R = R + s
+R.array() -= s; // R = R - s
+R.array() < Q.array(); // R < Q
+R.array() <= Q.array(); // R <= Q
+R.cwiseInverse(); // 1 ./ P
+R.array().inverse(); // 1 ./ P
+R.array().sin() // sin(P)
+R.array().cos() // cos(P)
+R.array().pow(s) // P .^ s
+R.array().square() // P .^ 2
+R.array().cube() // P .^ 3
+R.cwiseSqrt() // sqrt(P)
+R.array().sqrt() // sqrt(P)
+R.array().exp() // exp(P)
+R.array().log() // log(P)
+R.cwiseMax(P) // max(R, P)
+R.array().max(P.array()) // max(R, P)
+R.cwiseMin(P) // min(R, P)
+R.array().min(P.array()) // min(R, P)
+R.cwiseAbs() // abs(P)
+R.array().abs() // abs(P)
+R.cwiseAbs2() // abs(P.^2)
+R.array().abs2() // abs(P.^2)
+(R.array() < s).select(P,Q ); // (R < s ? P : Q)
+R = (Q.array()==0).select(P,R) // R(Q==0) = P(Q==0)
+R = P.unaryExpr(ptr_fun(func)) // R = arrayfun(func, P) // with: scalar func(const scalar &x);
+
// Reductions.
int r, c;
@@ -165,12 +173,12 @@
x.cross(y) // cross(x, y) Requires #include <Eigen/Geometry>
//// Type conversion
-// Eigen // Matlab
-A.cast<double>(); // double(A)
-A.cast<float>(); // single(A)
-A.cast<int>(); // int32(A)
-A.real(); // real(A)
-A.imag(); // imag(A)
+// Eigen // Matlab
+A.cast<double>(); // double(A)
+A.cast<float>(); // single(A)
+A.cast<int>(); // int32(A)
+A.real(); // real(A)
+A.imag(); // imag(A)
// if the original type equals destination type, no work is done
// Note that for most operations Eigen requires all operands to have the same type: