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DM-14834: Use pybind11's native Eigen wrapping instead of ndarray EigenView #362

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Jun 29, 2018
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DM-14834: Use pybind11's native Eigen wrapping instead of ndarray EigenView #362

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e629baa
git hide .coverage
r-owen Jun 19, 2018
6022132
Fix oudated use of ndarray::Array::asEigen
r-owen Jun 19, 2018
1cc88c3
Include pybind11/eigen.h where appropriate
r-owen Jun 19, 2018
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1 change: 1 addition & 0 deletions .gitignore
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Expand Up @@ -13,6 +13,7 @@ core.*
.pytest_cache/
.sconf_temp
.sconsign.dblite
.coverage
config.log
memleak.fits
pytest_session.txt
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5 changes: 3 additions & 2 deletions python/lsst/afw/geom/ellipses/baseCore.cc
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Expand Up @@ -20,8 +20,9 @@
* see <https://www.lsstcorp.org/LegalNotices/>.
*/

#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
#include "pybind11/pybind11.h"
#include "pybind11/eigen.h"
#include "pybind11/stl.h"

#include "ndarray/pybind11.h"

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6 changes: 3 additions & 3 deletions python/lsst/afw/geom/ellipses/ellipse.cc
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Expand Up @@ -20,9 +20,9 @@
* see <https://www.lsstcorp.org/LegalNotices/>.
*/

#include <pybind11/pybind11.h>
//#include <pybind11/operators.h>
#include <pybind11/stl.h>
#include "pybind11/pybind11.h"
#include "pybind11/eigen.h"
#include "pybind11/stl.h"

#include "ndarray/pybind11.h"

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6 changes: 3 additions & 3 deletions python/lsst/afw/geom/ellipses/quadrupole.cc
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Expand Up @@ -20,9 +20,9 @@
* see <https://www.lsstcorp.org/LegalNotices/>.
*/

#include <pybind11/pybind11.h>
//#include <pybind11/operators.h>
#include <pybind11/stl.h>
#include "pybind11/pybind11.h"
#include "pybind11/eigen.h"
#include "pybind11/stl.h"

#include "lsst/afw/geom/ellipses/BaseCore.h"
#include "lsst/afw/geom/ellipses/Quadrupole.h"
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1 change: 1 addition & 0 deletions python/lsst/afw/geom/skyWcs/skyWcs.cc
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Expand Up @@ -20,6 +20,7 @@
* see <http://www.lsstcorp.org/LegalNotices/>.
*/
#include "pybind11/pybind11.h"
#include "pybind11/eigen.h"

#include <utility>
#include <memory>
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1 change: 1 addition & 0 deletions python/lsst/afw/geom/transform/transform.cc
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Expand Up @@ -20,6 +20,7 @@
* see <http://www.lsstcorp.org/LegalNotices/>.
*/
#include "pybind11/pybind11.h"
#include "pybind11/eigen.h"

#include <memory>

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1 change: 1 addition & 0 deletions python/lsst/afw/geom/wcsUtils/wcsUtils.cc
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Expand Up @@ -20,6 +20,7 @@
* see <http://www.lsstcorp.org/LegalNotices/>.
*/
#include "pybind11/pybind11.h"
#include "pybind11/eigen.h"

#include <memory>

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1 change: 1 addition & 0 deletions python/lsst/afw/table/aggregates/aggregates.cc
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Expand Up @@ -21,6 +21,7 @@
*/

#include "pybind11/pybind11.h"
#include "pybind11/eigen.h"
#include "pybind11/stl.h"

#include "ndarray/pybind11.h"
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1 change: 1 addition & 0 deletions python/lsst/afw/table/slots.cc
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Expand Up @@ -21,6 +21,7 @@
*/

#include "pybind11/pybind11.h"
#include "pybind11/eigen.h"

#include "lsst/afw/table/slots.h"

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1 change: 1 addition & 0 deletions python/lsst/afw/table/source/source.cc
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Expand Up @@ -21,6 +21,7 @@
*/

#include "pybind11/pybind11.h"
#include "pybind11/eigen.h"

#include <memory>

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4 changes: 2 additions & 2 deletions src/math/ChebyshevBoundedField.cc
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Expand Up @@ -175,9 +175,9 @@ std::shared_ptr<ChebyshevBoundedField> ChebyshevBoundedField::fit(lsst::geom::Bo
ndarray::Array<double, 2, 2> matrix = makeMatrix(x, y, result->_toChebyshevRange, packer, ctrl);
// We want to do weighted least squares, so we multiply both the data vector 'b' and the
// matrix 'A' by the weights.
matrix.asEigen<Eigen::ArrayXpr>().colwise() *= w.asEigen<Eigen::ArrayXpr>();
ndarray::asEigenArray(matrix).colwise() *= ndarray::asEigenArray(w);
ndarray::Array<double, 1, 1> wz = ndarray::copy(z);
wz.asEigen<Eigen::ArrayXpr>() *= w.asEigen<Eigen::ArrayXpr>();
ndarray::asEigenArray(wz) *= ndarray::asEigenArray(w);
// Solve the linear least squares problem.
LeastSquares lstsq = LeastSquares::fromDesignMatrix(matrix, wz, LeastSquares::NORMAL_EIGENSYSTEM);
// Unpack the solution into a 2-d matrix, with zeros for values we didn't fit.
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4 changes: 2 additions & 2 deletions src/math/LeastSquares.cc
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Expand Up @@ -170,7 +170,7 @@ class EigensystemSolver : public LeastSquares::Impl {
ndarray::asEigenMatrix(diagnostic) = _svd.singularValues();
}
if (whichDiagnostic == LeastSquares::DIRECT_SVD) {
diagnostic.asEigen<Eigen::ArrayXpr>() = diagnostic.asEigen<Eigen::ArrayXpr>().sqrt();
ndarray::asEigenArray(diagnostic) = ndarray::asEigenArray(diagnostic).sqrt();
}
}

Expand Down Expand Up @@ -265,7 +265,7 @@ class SvdSolver : public LeastSquares::Impl {
virtual void updateDiagnostic() {
switch (whichDiagnostic) {
case LeastSquares::NORMAL_EIGENSYSTEM:
diagnostic.asEigen<Eigen::ArrayXpr>() = _svd.singularValues().array().square();
ndarray::asEigenArray(diagnostic) = _svd.singularValues().array().square();
break;
case LeastSquares::NORMAL_CHOLESKY:
throw LSST_EXCEPT(
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2 changes: 1 addition & 1 deletion tests/test_trapezoidalPacker.cc
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Expand Up @@ -14,7 +14,7 @@ typedef lsst::afw::math::ChebyshevBoundedFieldControl Control;

ndarray::Array<double, 1, 1> makeRandomArray(int n) {
ndarray::Array<double, 1, 1> result = ndarray::allocate(n);
result.asEigen<Eigen::ArrayXpr>().setRandom();
ndarray::asEigenArray(result).setRandom();
return result;
}

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