Merge pull request #95 from lsst/tickets/DM-6056

DM-6056: replace CONST_PTR and PTR macros by std::shared

include/lsst/meas/modelfit/AdaptiveImportanceSampler.h

@@ -82,14 +82,14 @@ class AdaptiveImportanceSampler : public Sampler {
      */
     AdaptiveImportanceSampler(
         afw::table::Schema & sampleSchema,
-        PTR(afw::math::Random) rng,
+        std::shared_ptr<afw::math::Random> rng,
         std::map<int,ImportanceSamplerControl> const & ctrls,
         bool doSaveIterations=false
     );
 
     void run(
         SamplingObjective const & objective,
-        PTR(Mixture) proposal,
+        std::shared_ptr<Mixture> proposal,
         afw::table::BaseCatalog & samples
     ) const override;
 
@@ -99,7 +99,7 @@ class AdaptiveImportanceSampler : public Sampler {
 
 private:
     bool _doSaveIterations;
-    PTR(afw::math::Random)  _rng;
+    std::shared_ptr<afw::math::Random>  _rng;
     std::map<int,ImportanceSamplerControl> _ctrls;
     afw::table::Key<Scalar> _weightKey;
     afw::table::Key<Scalar> _objectiveKey;

include/lsst/meas/modelfit/CModel.h

@@ -157,9 +157,9 @@ struct CModelStageControl {
         return shapelet::RadialProfile::get(profileName);
     }
 
-    PTR(Model) getModel() const;
+    std::shared_ptr<Model> getModel() const;
 
-    PTR(Prior) getPrior() const;
+    std::shared_ptr<Prior> getPrior() const;
 
     LSST_CONTROL_FIELD(
         profileName, std::string,
@@ -308,10 +308,10 @@ struct CModelStageResult {
 
     CModelStageResult();
 
-    PTR(Model) model;    ///< Model object that defines the parametrization (defined fully by Control struct)
-    PTR(Prior) prior;    ///< Bayesian priors on the parameters (defined fully by Control struct)
-    PTR(OptimizerObjective) objfunc;  ///< Objective class used by the optimizer
-    PTR(UnitTransformedLikelihood) likelihood; ///< Object used to evaluate models and compare to data.
+    std::shared_ptr<Model> model;    ///< Model object that defines the parametrization (defined fully by Control struct)
+    std::shared_ptr<Prior> prior;    ///< Bayesian priors on the parameters (defined fully by Control struct)
+    std::shared_ptr<OptimizerObjective> objfunc;  ///< Objective class used by the optimizer
+    std::shared_ptr<UnitTransformedLikelihood> likelihood; ///< Object used to evaluate models and compare to data.
     Scalar instFlux;         ///< Flux measured from just this stage fit.
     Scalar instFluxErr;    ///< Flux uncertainty from just this stage fit.
     Scalar instFluxInner;    ///< Flux measured strictly within the fit region (no extrapolation).
@@ -583,7 +583,7 @@ class CModelAlgorithm {
     class Impl;
 
     Control _ctrl;
-    PTR(Impl) _impl;
+    std::shared_ptr<Impl> _impl;
 };
 
 }}} // namespace lsst::meas::modelfit

include/lsst/meas/modelfit/DoubleShapeletPsfApprox.h

@@ -192,7 +192,7 @@ class DoubleShapeletPsfApproxAlgorithm : public meas::base::SimpleAlgorithm {
      *                           Probably the result of a call to
      *                           Psf::computeKernelImage().
      */
-    static PTR(OptimizerObjective) makeObjective(
+    static std::shared_ptr<OptimizerObjective> makeObjective(
         afw::geom::ellipses::Ellipse const & moments,
         Control const & ctrl,
         afw::image::Image<Scalar> const & psfImage

include/lsst/meas/modelfit/GeneralPsfFitter.h

@@ -171,15 +171,15 @@ class GeneralPsfFitter {
      *  define the center of the prior; the "nonlinear" parameters are the free-to-vary ellipse
      *  parameters minus the corresponding initial values.
      */
-    PTR(Model) getModel() const { return _model; }
+    std::shared_ptr<Model> getModel() const { return _model; }
 
     /**
      *  Return the Prior object that corresponds to the configuration.
      *
      *  This Prior class only supports evaluate() and evaluateDerivatives(), reflecting the fact
      *  that we only intend to use it with a Optimizer, not a Sampler.
      */
-    PTR(Prior) getPrior() const { return _prior; }
+    std::shared_ptr<Prior> getPrior() const { return _prior; }
 
     /**
      *  Adapt a differently-configured previous fit to be used as an starting point for this GeneralPsfFitter.
@@ -195,7 +195,7 @@ class GeneralPsfFitter {
      */
     shapelet::MultiShapeletFunction adapt(
         shapelet::MultiShapeletFunction const & previousFit,
-        PTR(Model) previousModel
+        std::shared_ptr<Model> previousModel
     ) const;
 
     //@{
@@ -260,8 +260,8 @@ class GeneralPsfFitter {
 
 private:
     GeneralPsfFitterControl _ctrl;
-    PTR(Model) _model;
-    PTR(Prior) _prior;
+    std::shared_ptr<Model> _model;
+    std::shared_ptr<Prior> _prior;
 };
 
 class GeneralPsfFitterAlgorithm : public GeneralPsfFitter {
@@ -318,7 +318,7 @@ class MultiShapeletPsfLikelihood : public Likelihood {
     MultiShapeletPsfLikelihood(
         ndarray::Array<Pixel const,2,1> const & image,
         geom::Point2I const & xy0,
-        PTR(Model) model,
+        std::shared_ptr<Model> model,
         Scalar sigma,
         ndarray::Array<Scalar const,1,1> const & fixed
     );

include/lsst/meas/modelfit/Likelihood.h

@@ -102,7 +102,7 @@ class Likelihood
     ndarray::Array<Pixel const,1,1> getVariance() const { return _variance; }
 
     /// Return an object that defines the model and its parameters
-    PTR(Model) getModel() const { return _model; }
+    std::shared_ptr<Model> getModel() const { return _model; }
 
     /**
      *  @brief Evaluate the model for the given vector of nonlinear parameters.
@@ -135,7 +135,7 @@ class Likelihood
 
 protected:
 
-    Likelihood(PTR(Model) model, ndarray::Array<Scalar const,1,1> const & fixed) :
+    Likelihood(std::shared_ptr<Model> model, ndarray::Array<Scalar const,1,1> const & fixed) :
         _model(model), _fixed(fixed) {
         LSST_THROW_IF_NE(
             fixed.getSize<0>(), static_cast<std::size_t>(model->getFixedDim()),
@@ -144,7 +144,7 @@ class Likelihood
         );
     }
 
-    PTR(Model) _model;
+    std::shared_ptr<Model> _model;
     ndarray::Array<Scalar const,1,1> _fixed;
     ndarray::Array<Pixel,1,1> _data;
     ndarray::Array<Pixel,1,1> _unweightedData;

include/lsst/meas/modelfit/Mixture.h

@@ -160,10 +160,10 @@ class Mixture : public afw::table::io::PersistableFacade<Mixture>, public afw::t
     virtual int getComponentCount() const { return size(); }
 
     /// Project the distribution onto the given dimensions (marginalize over all others)
-    PTR(Mixture) project(int dim) const;
+    std::shared_ptr<Mixture> project(int dim) const;
 
     /// Project the distribution onto the given dimensions (marginalize over all others)
-    PTR(Mixture) project(int dim1, int dim2) const;
+    std::shared_ptr<Mixture> project(int dim1, int dim2) const;
 
     /// Return the number of dimensions
     int getDimension() const { return _dim; }
@@ -342,7 +342,7 @@ class Mixture : public afw::table::io::PersistableFacade<Mixture>, public afw::t
     );
 
     /// Polymorphic deep copy
-    virtual PTR(Mixture) clone() const;
+    virtual std::shared_ptr<Mixture> clone() const;
 
     /**
      *  @brief Construct a mixture model.

include/lsst/meas/modelfit/MixturePrior.h

@@ -35,7 +35,7 @@ namespace lsst { namespace meas { namespace modelfit {
 class MixturePrior : public Prior {
 public:
 
-    explicit MixturePrior(PTR(Mixture const) mixture, std::string const & tag="");
+    explicit MixturePrior(std::shared_ptr<Mixture const> mixture, std::string const & tag="");
 
     /// @copydoc Prior::evaluate
     Scalar evaluate(
@@ -85,10 +85,10 @@ class MixturePrior : public Prior {
      */
     static MixtureUpdateRestriction const & getUpdateRestriction();
 
-    PTR(Mixture const) getMixture() const { return _mixture; }
+    std::shared_ptr<Mixture const> getMixture() const { return _mixture; }
 
 private:
-    PTR(Mixture const) _mixture;
+    std::shared_ptr<Mixture const> _mixture;
 };
 
 }}} // namespace lsst::meas::modelfit

include/lsst/meas/modelfit/Model.h

@@ -38,7 +38,7 @@ class Prior;
 
 struct LocalUnitTransform;
 
-typedef std::vector<PTR(Model)> ModelVector;
+typedef std::vector<std::shared_ptr<Model>> ModelVector;
 
 /**
  *  @brief Abstract base class and concrete factories that define multi-shapelet galaxy models
@@ -63,7 +63,7 @@ class Model {
     };
 
     typedef std::vector<std::string> NameVector;
-    typedef std::vector<PTR(shapelet::MultiShapeletBasis)> BasisVector;
+    typedef std::vector<std::shared_ptr<shapelet::MultiShapeletBasis>> BasisVector;
     typedef std::vector<afw::geom::ellipses::Ellipse> EllipseVector;
     typedef std::vector<afw::geom::ellipses::Ellipse>::iterator EllipseIterator;
     typedef std::vector<afw::geom::ellipses::Ellipse>::const_iterator EllipseConstIterator;
@@ -83,7 +83,7 @@ class Model {
      *                                 fixed center (FIXED_CENTER), the same center (SINGLE_CENTER), or
      *                                 independent centers (MULTI_CENTER).
      */
-    static PTR(Model) make(BasisVector basisVector, NameVector const & prefixes, CenterEnum center);
+    static std::shared_ptr<Model> make(BasisVector basisVector, NameVector const & prefixes, CenterEnum center);
 
     /**
      *  Construct a concrete Model instance with a single ellipse and multishapelet basis
@@ -104,7 +104,7 @@ class Model {
      *  afw::geom::ellipses::SeparableConformalShearLogTraceRadius.  For the basis objects provided
      *  by lsst.shapelet.tractor, that generally means that logR=0 corresponds to the half-light radius.
      */
-    static PTR(Model) make(PTR(shapelet::MultiShapeletBasis) basis, CenterEnum center);
+    static std::shared_ptr<Model> make(std::shared_ptr<shapelet::MultiShapeletBasis> basis, CenterEnum center);
 
     /**
      *  Construct a concrete Model instance that represents a single elliptical Gaussian function.
@@ -118,7 +118,7 @@ class Model {
      *                                 (i.e. radius=1 corresponds to a model in which the radius parameter
      *                                 is ln(sigma)).
      */
-    static PTR(Model) makeGaussian(CenterEnum center, double radius=1.0);
+    static std::shared_ptr<Model> makeGaussian(CenterEnum center, double radius=1.0);
 
     /// Return the number of free nonlinear parameters
     int getNonlinearDim() const { return _nonlinearNames.size(); }
@@ -152,7 +152,7 @@ class Model {
     ) const;
 
     /// Given an arbitrary prior, return one compatible with this Model or throw LogicError
-    virtual PTR(Prior) adaptPrior(PTR(Prior) prior) const = 0;
+    virtual std::shared_ptr<Prior> adaptPrior(std::shared_ptr<Prior> prior) const = 0;
 
     /**
      *  Return an uninitialized vector of afw::geom::ellipses::Ellipse with the parametrization expected

include/lsst/meas/modelfit/MultiModel.h

@@ -47,7 +47,7 @@ class MultiModel : public Model {
     ModelVector const & getComponents() const { return _components; }
 
     /// @copydoc Model::adaptPrior
-    PTR(Prior) adaptPrior(PTR(Prior) prior) const override;
+    std::shared_ptr<Prior> adaptPrior(std::shared_ptr<Prior> prior) const override;
 
     /// @copydoc Model::makeEllipseVector
     EllipseVector makeEllipseVector() const override;

include/lsst/meas/modelfit/PixelFitRegion.h

@@ -124,7 +124,7 @@ class PixelFitRegion {
     void applyMask(afw::image::Mask<> const & mask, geom::Point2D const & center);
 
     afw::geom::ellipses::Quadrupole ellipse;
-    PTR(afw::detection::Footprint) footprint;
+    std::shared_ptr<afw::detection::Footprint> footprint;
     bool usedFootprintArea;
     bool usedPsfArea;
     bool maxArea;

include/lsst/meas/modelfit/Sampler.h

@@ -43,9 +43,9 @@ class SamplingObjective {
     virtual ~SamplingObjective() {}
 
 protected:
-    explicit SamplingObjective(PTR(Likelihood) likelihood);
+    explicit SamplingObjective(std::shared_ptr<Likelihood> likelihood);
 
-    PTR(Likelihood) _likelihood;
+    std::shared_ptr<Likelihood> _likelihood;
     ndarray::Array<Pixel,2,-1> _modelMatrix;
 };
 
@@ -54,7 +54,7 @@ class Sampler {
 
     virtual void run(
         SamplingObjective const & objective,
-        PTR(Mixture) proposal,
+        std::shared_ptr<Mixture> proposal,
         afw::table::BaseCatalog & samples
     ) const = 0;
 

include/lsst/meas/modelfit/SemiEmpiricalPrior.h

@@ -132,7 +132,7 @@ class SemiEmpiricalPrior : public Prior {
 
     struct Impl;
 
-    PTR(Impl) _impl;
+    std::shared_ptr<Impl> _impl;
 };
 
 }}} // namespace lsst::meas::modelfit

include/lsst/meas/modelfit/TruncatedGaussian.h

@@ -234,9 +234,9 @@ class TruncatedGaussian {
 
     class Impl;
 
-    explicit TruncatedGaussian(PTR(Impl) impl) : _impl(impl) {}
+    explicit TruncatedGaussian(std::shared_ptr<Impl> impl) : _impl(impl) {}
 
-    PTR(Impl) _impl;
+    std::shared_ptr<Impl> _impl;
 };
 
 /**
@@ -336,7 +336,7 @@ class TruncatedGaussianSampler {
     class Impl; // public so we can inherit from it in the .cc file
 
 private:
-    PTR(Impl) _impl;
+    std::shared_ptr<Impl> _impl;
 };
 
 inline TruncatedGaussian::Sampler TruncatedGaussian::sample(SampleStrategy strategy) const {

include/lsst/meas/modelfit/UnitTransformedLikelihood.h

@@ -120,11 +120,11 @@ class UnitTransformedLikelihood : public Likelihood {
      * @param[in] ctrl              Control object with various options
      */
     explicit UnitTransformedLikelihood(
-        PTR(Model) model,
+        std::shared_ptr<Model> model,
         ndarray::Array<Scalar const,1,1> const & fixed,
         UnitSystem const & fitSys,
         geom::SpherePoint const & position,
-        std::vector<PTR(EpochFootprint)> const & epochFootprintList,
+        std::vector<std::shared_ptr<EpochFootprint>> const & epochFootprintList,
         UnitTransformedLikelihoodControl const & ctrl
     );
 
@@ -141,7 +141,7 @@ class UnitTransformedLikelihood : public Likelihood {
      * @param[in] ctrl              Control object with various options
      */
     explicit UnitTransformedLikelihood(
-        PTR(Model) model,
+        std::shared_ptr<Model> model,
         ndarray::Array<Scalar const,1,1> const & fixed,
         UnitSystem const & fitSys,
         geom::SpherePoint const & position,

include/lsst/meas/modelfit/optimizer.h

@@ -56,9 +56,9 @@ class OptimizerObjective {
      *  however, so simple problems where analytic derivatives are easy to
      *  implement may merit a custom OptimizerObjective.
      */
-    static PTR(OptimizerObjective) makeFromLikelihood(
-        PTR(Likelihood) likelihood,
-        PTR(Prior) prior = PTR(Prior)()
+    static std::shared_ptr<OptimizerObjective> makeFromLikelihood(
+        std::shared_ptr<Likelihood> likelihood,
+        std::shared_ptr<Prior> prior = std::shared_ptr<Prior>()
     );
 
     /**
@@ -300,7 +300,7 @@ class OptimizerHistoryRecorder {
 
     OptimizerHistoryRecorder(
         afw::table::Schema & schema,
-        PTR(Model) model,
+        std::shared_ptr<Model> model,
         bool doRecordDerivatives
     );
 
@@ -424,12 +424,12 @@ class Optimizer {
     };
 
     Optimizer(
-        PTR(Objective const) objective,
+        std::shared_ptr<Objective const> objective,
         ndarray::Array<Scalar const,1,1> const & parameters,
         Control const & ctrl
     );
 
-    PTR(Objective const) getObjective() const { return _objective; }
+    std::shared_ptr<Objective const> getObjective() const { return _objective; }
 
     Control const & getControl() const { return _ctrl; }
 
@@ -486,7 +486,7 @@ class Optimizer {
     void _computeDerivatives();
 
     int _state;
-    PTR(Objective const) _objective;
+    std::shared_ptr<Objective const> _objective;
     Control _ctrl;
     double _trustRadius;
     IterationData _current;