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/******************************************************* |
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* |
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* Copyright (c) 2003-2008 by University of Queensland |
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* Earth Systems Science Computational Center (ESSCC) |
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* http://www.uq.edu.au/esscc |
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* |
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* Primary Business: Queensland, Australia |
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* Licensed under the Open Software License version 3.0 |
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* http://www.opensource.org/licenses/osl-3.0.php |
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* |
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*******************************************************/ |
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|
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|
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/** \file Data.h */ |
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|
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#ifndef DATA_H |
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#define DATA_H |
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#include "system_dep.h" |
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|
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#include "DataAbstract.h" |
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#include "DataAlgorithm.h" |
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#include "FunctionSpace.h" |
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#include "BinaryOp.h" |
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#include "UnaryOp.h" |
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#include "DataException.h" |
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#include "DataTypes.h" |
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|
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extern "C" { |
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#include "DataC.h" |
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/* #include "paso/Paso.h" doesn't belong in this file...causes trouble for BruceFactory.cpp */ |
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} |
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|
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#include "esysmpi.h" |
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#include <string> |
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#include <algorithm> |
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#include <sstream> |
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|
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|
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#include <boost/shared_ptr.hpp> |
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#include <boost/python/object.hpp> |
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#include <boost/python/tuple.hpp> |
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#include <boost/python/numeric.hpp> |
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|
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namespace escript { |
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|
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// |
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// Forward declaration for various implementations of Data. |
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class DataConstant; |
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class DataTagged; |
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class DataExpanded; |
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|
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/** |
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\brief |
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Data represents a collection of datapoints. |
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|
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Description: |
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Internally, the datapoints are actually stored by a DataAbstract object. |
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The specific instance of DataAbstract used may vary over the lifetime |
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of the Data object. |
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Some methods on this class return references (eg getShape()). |
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These references should not be used after an operation which changes the underlying DataAbstract object. |
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Doing so will lead to invalid memory access. |
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This should not affect any methods exposed via boost::python. |
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*/ |
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class Data { |
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|
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public: |
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|
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// These typedefs allow function names to be cast to pointers |
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// to functions of the appropriate type when calling unaryOp etc. |
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typedef double (*UnaryDFunPtr)(double); |
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typedef double (*BinaryDFunPtr)(double,double); |
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|
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|
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/** |
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Constructors. |
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*/ |
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|
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/** |
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\brief |
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Default constructor. |
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Creates a DataEmpty object. |
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*/ |
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ESCRIPT_DLL_API |
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Data(); |
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|
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/** |
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\brief |
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Copy constructor. |
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WARNING: Only performs a shallow copy. |
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*/ |
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ESCRIPT_DLL_API |
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Data(const Data& inData); |
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|
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/** |
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\brief |
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Constructor from another Data object. If "what" is different from the |
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function space of inData the inData are tried to be interpolated to what, |
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otherwise a shallow copy of inData is returned. |
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*/ |
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ESCRIPT_DLL_API |
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Data(const Data& inData, |
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const FunctionSpace& what); |
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|
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/** |
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\brief Copy Data from an existing vector |
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*/ |
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|
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ESCRIPT_DLL_API |
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Data(const DataTypes::ValueType& value, |
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const DataTypes::ShapeType& shape, |
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const FunctionSpace& what=FunctionSpace(), |
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bool expanded=false); |
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|
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/** |
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\brief |
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Constructor which creates a Data from a DataArrayView shape. |
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|
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\param value - Input - Single value applied to all Data. |
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\param dataPointShape - Input - The shape of each data point. |
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\param what - Input - A description of what this data represents. |
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\param expanded - Input - Flag, if true fill the entire container with |
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the given value. Otherwise a more efficient storage |
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mechanism will be used. |
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*/ |
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ESCRIPT_DLL_API |
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Data(double value, |
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const DataTypes::ShapeType& dataPointShape=DataTypes::ShapeType(), |
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const FunctionSpace& what=FunctionSpace(), |
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bool expanded=false); |
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|
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/** |
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\brief |
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Constructor which performs a deep copy of a region from another Data object. |
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|
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\param inData - Input - Input Data object. |
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\param region - Input - Region to copy. |
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*/ |
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ESCRIPT_DLL_API |
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Data(const Data& inData, |
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const DataTypes::RegionType& region); |
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|
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/** |
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\brief |
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Constructor which copies data from a python numarray. |
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|
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\param value - Input - Data value for a single point. |
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\param what - Input - A description of what this data represents. |
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\param expanded - Input - Flag, if true fill the entire container with |
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the value. Otherwise a more efficient storage |
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mechanism will be used. |
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*/ |
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ESCRIPT_DLL_API |
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Data(const boost::python::numeric::array& value, |
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const FunctionSpace& what=FunctionSpace(), |
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bool expanded=false); |
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|
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/** |
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\brief |
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Constructor which copies data from any object that can be converted into |
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a python numarray. |
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|
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\param value - Input - Input data. |
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\param what - Input - A description of what this data represents. |
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\param expanded - Input - Flag, if true fill the entire container with |
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the value. Otherwise a more efficient storage |
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mechanism will be used. |
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*/ |
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ESCRIPT_DLL_API |
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Data(const boost::python::object& value, |
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const FunctionSpace& what=FunctionSpace(), |
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bool expanded=false); |
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|
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/** |
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\brief |
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Constructor which creates a DataConstant. |
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Copies data from any object that can be converted |
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into a numarray. All other parameters are copied from other. |
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|
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\param value - Input - Input data. |
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\param other - Input - contains all other parameters. |
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*/ |
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ESCRIPT_DLL_API |
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Data(const boost::python::object& value, |
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const Data& other); |
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|
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/** |
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\brief |
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Constructor which creates a DataConstant of "shape" with constant value. |
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*/ |
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ESCRIPT_DLL_API |
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Data(double value, |
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const boost::python::tuple& shape=boost::python::make_tuple(), |
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const FunctionSpace& what=FunctionSpace(), |
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bool expanded=false); |
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|
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|
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|
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/** |
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\brief Create a Data using an existing DataAbstract. Warning: The new object assumes ownership of the pointer! |
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Once you have passed the pointer, do not delete it. |
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*/ |
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ESCRIPT_DLL_API |
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Data(DataAbstract* underlyingdata); |
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|
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|
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/** |
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\brief |
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Destructor |
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*/ |
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ESCRIPT_DLL_API |
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~Data(); |
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|
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/** |
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\brief Make this object a deep copy of "other". |
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*/ |
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ESCRIPT_DLL_API |
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void |
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copy(const Data& other); |
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|
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/** |
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\brief Return a pointer to a deep copy of this object. |
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*/ |
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ESCRIPT_DLL_API |
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Data* |
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copySelf(); |
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|
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|
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|
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|
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/** |
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Member access methods. |
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*/ |
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|
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/** |
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\brief |
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switches on update protection |
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|
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*/ |
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ESCRIPT_DLL_API |
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void |
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setProtection(); |
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|
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/** |
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\brief |
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Returns trueif the data object is protected against update |
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|
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*/ |
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ESCRIPT_DLL_API |
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bool |
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isProtected() const; |
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|
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/** |
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\brief |
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Return the values of a data point on this process |
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*/ |
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ESCRIPT_DLL_API |
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const boost::python::numeric::array |
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getValueOfDataPoint(int dataPointNo); |
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|
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/** |
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\brief |
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sets the values of a data-point from a python object on this process |
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*/ |
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ESCRIPT_DLL_API |
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void |
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setValueOfDataPointToPyObject(int dataPointNo, const boost::python::object& py_object); |
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|
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/** |
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\brief |
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sets the values of a data-point from a numarray object on this process |
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*/ |
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ESCRIPT_DLL_API |
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void |
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setValueOfDataPointToArray(int dataPointNo, const boost::python::numeric::array&); |
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|
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/** |
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\brief |
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sets the values of a data-point on this process |
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*/ |
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ESCRIPT_DLL_API |
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void |
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setValueOfDataPoint(int dataPointNo, const double); |
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|
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/** |
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\brief |
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Return the value of the specified data-point across all processors |
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*/ |
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ESCRIPT_DLL_API |
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const boost::python::numeric::array |
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getValueOfGlobalDataPoint(int procNo, int dataPointNo); |
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|
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/** |
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\brief |
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Return the tag number associated with the given data-point. |
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|
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*/ |
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ESCRIPT_DLL_API |
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int |
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getTagNumber(int dpno); |
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|
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/** |
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\brief |
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Return the C wrapper for the Data object. |
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*/ |
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ESCRIPT_DLL_API |
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escriptDataC |
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getDataC(); |
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|
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|
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|
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|
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|
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|
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// REMOVE ME |
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// ESCRIPT_DLL_API |
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// void |
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// CompareDebug(const Data& rd); |
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|
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|
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/** |
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\brief |
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Return the C wrapper for the Data object - const version. |
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*/ |
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ESCRIPT_DLL_API |
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escriptDataC |
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getDataC() const; |
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|
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/** |
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\brief |
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Write the data as a string. For large amounts of data, a summary is printed. |
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*/ |
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ESCRIPT_DLL_API |
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std::string |
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toString() const; |
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|
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|
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// /** |
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/* \brief |
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Return the DataArrayView of the point data. This essentially contains |
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the shape information for each data point although it also may be used |
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to manipulate the point data.*/ |
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// */ |
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// ESCRIPT_DLL_API |
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// inline |
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// const DataArrayView& |
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// getPointDataView() const |
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// { |
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// return m_data->getPointDataView(); |
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// } |
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|
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/** |
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\brief |
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Whatever the current Data type make this into a DataExpanded. |
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*/ |
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ESCRIPT_DLL_API |
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void |
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expand(); |
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|
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/** |
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\brief |
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If possible convert this Data to DataTagged. This will only allow |
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Constant data to be converted to tagged. An attempt to convert |
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Expanded data to tagged will throw an exception. |
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==>* |
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*/ |
368 |
ESCRIPT_DLL_API |
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void |
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tag(); |
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|
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/** |
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\brief |
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Return true if this Data is expanded. |
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*/ |
376 |
ESCRIPT_DLL_API |
377 |
bool |
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isExpanded() const; |
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|
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/** |
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\brief |
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Return true if this Data is tagged. |
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*/ |
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ESCRIPT_DLL_API |
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bool |
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isTagged() const; |
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|
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/** |
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\brief |
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Return true if this Data is constant. |
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*/ |
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ESCRIPT_DLL_API |
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bool |
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isConstant() const; |
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|
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/** |
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\brief |
398 |
Return true if this Data holds an instance of DataEmpty. This is _not_ the same as asking if the object |
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contains datapoints. |
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*/ |
401 |
ESCRIPT_DLL_API |
402 |
bool |
403 |
isEmpty() const; |
404 |
|
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/** |
406 |
\brief |
407 |
Return the function space. |
408 |
*/ |
409 |
ESCRIPT_DLL_API |
410 |
inline |
411 |
const FunctionSpace& |
412 |
getFunctionSpace() const |
413 |
{ |
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return m_data->getFunctionSpace(); |
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} |
416 |
|
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/** |
418 |
\brief |
419 |
Return a copy of the function space. |
420 |
*/ |
421 |
ESCRIPT_DLL_API |
422 |
const FunctionSpace |
423 |
getCopyOfFunctionSpace() const; |
424 |
|
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/** |
426 |
\brief |
427 |
Return the domain. |
428 |
*/ |
429 |
ESCRIPT_DLL_API |
430 |
inline |
431 |
// const AbstractDomain& |
432 |
const_Domain_ptr |
433 |
getDomain() const |
434 |
{ |
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return getFunctionSpace().getDomain(); |
436 |
} |
437 |
|
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|
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/** |
440 |
\brief |
441 |
Return the domain. |
442 |
TODO: For internal use only. This should be removed. |
443 |
*/ |
444 |
ESCRIPT_DLL_API |
445 |
inline |
446 |
// const AbstractDomain& |
447 |
Domain_ptr |
448 |
getDomainPython() const |
449 |
{ |
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return getFunctionSpace().getDomainPython(); |
451 |
} |
452 |
|
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/** |
454 |
\brief |
455 |
Return a copy of the domain. |
456 |
*/ |
457 |
ESCRIPT_DLL_API |
458 |
const AbstractDomain |
459 |
getCopyOfDomain() const; |
460 |
|
461 |
/** |
462 |
\brief |
463 |
Return the rank of the point data. |
464 |
*/ |
465 |
ESCRIPT_DLL_API |
466 |
inline |
467 |
int |
468 |
getDataPointRank() const |
469 |
{ |
470 |
// return m_data->getPointDataView().getRank(); |
471 |
return m_data->getRank(); |
472 |
} |
473 |
|
474 |
/** |
475 |
\brief |
476 |
Return the number of data points |
477 |
*/ |
478 |
ESCRIPT_DLL_API |
479 |
inline |
480 |
int |
481 |
getNumDataPoints() const |
482 |
{ |
483 |
return getNumSamples() * getNumDataPointsPerSample(); |
484 |
} |
485 |
/** |
486 |
\brief |
487 |
Return the number of samples. |
488 |
*/ |
489 |
ESCRIPT_DLL_API |
490 |
inline |
491 |
int |
492 |
getNumSamples() const |
493 |
{ |
494 |
return m_data->getNumSamples(); |
495 |
} |
496 |
|
497 |
/** |
498 |
\brief |
499 |
Return the number of data points per sample. |
500 |
*/ |
501 |
ESCRIPT_DLL_API |
502 |
inline |
503 |
int |
504 |
getNumDataPointsPerSample() const |
505 |
{ |
506 |
return m_data->getNumDPPSample(); |
507 |
} |
508 |
|
509 |
|
510 |
/** |
511 |
\brief |
512 |
Return the number of values in the shape for this object. |
513 |
*/ |
514 |
ESCRIPT_DLL_API |
515 |
int |
516 |
getNoValues() const |
517 |
{ |
518 |
return m_data->getNoValues(); |
519 |
} |
520 |
|
521 |
|
522 |
/** |
523 |
\brief |
524 |
dumps the object into a netCDF file |
525 |
*/ |
526 |
ESCRIPT_DLL_API |
527 |
void |
528 |
dump(const std::string fileName) const; |
529 |
/** |
530 |
\brief |
531 |
Return the sample data for the given sample no. This is not the |
532 |
preferred interface but is provided for use by C code. |
533 |
\param sampleNo - Input - the given sample no. |
534 |
*/ |
535 |
ESCRIPT_DLL_API |
536 |
inline |
537 |
DataAbstract::ValueType::value_type* |
538 |
getSampleData(DataAbstract::ValueType::size_type sampleNo) |
539 |
{ |
540 |
return m_data->getSampleData(sampleNo); |
541 |
} |
542 |
|
543 |
/** |
544 |
\brief |
545 |
Return the sample data for the given tag. If an attempt is made to |
546 |
access data that isn't tagged an exception will be thrown. |
547 |
\param tag - Input - the tag key. |
548 |
*/ |
549 |
ESCRIPT_DLL_API |
550 |
inline |
551 |
DataAbstract::ValueType::value_type* |
552 |
getSampleDataByTag(int tag) |
553 |
{ |
554 |
return m_data->getSampleDataByTag(tag); |
555 |
} |
556 |
|
557 |
// /** |
558 |
/* \brief |
559 |
Return a view into the data for the data point specified. |
560 |
NOTE: Construction of the DataArrayView is a relatively expensive |
561 |
operation. |
562 |
\param sampleNo - Input - |
563 |
\param dataPointNo - Input -*/ |
564 |
// */ |
565 |
// ESCRIPT_DLL_API |
566 |
// inline |
567 |
// DataArrayView |
568 |
// getDataPoint(int sampleNo, |
569 |
// int dataPointNo) |
570 |
// { |
571 |
// return m_data->getDataPoint(sampleNo,dataPointNo); |
572 |
// } |
573 |
|
574 |
|
575 |
/** |
576 |
\brief |
577 |
Return a view into the data for the data point specified. |
578 |
NOTE: Construction of the DataArrayView is a relatively expensive |
579 |
operation. |
580 |
\param sampleNo - Input - |
581 |
\param dataPointNo - Input - |
582 |
*/ |
583 |
ESCRIPT_DLL_API |
584 |
DataTypes::ValueType::const_reference |
585 |
getDataPoint(int sampleNo, int dataPointNo) const; |
586 |
|
587 |
|
588 |
ESCRIPT_DLL_API |
589 |
DataTypes::ValueType::reference |
590 |
getDataPoint(int sampleNo, int dataPointNo); |
591 |
|
592 |
|
593 |
|
594 |
/** |
595 |
\brief |
596 |
Return the offset for the given sample and point within the sample |
597 |
*/ |
598 |
ESCRIPT_DLL_API |
599 |
inline |
600 |
DataTypes::ValueType::size_type |
601 |
getDataOffset(int sampleNo, |
602 |
int dataPointNo) |
603 |
{ |
604 |
return m_data->getPointOffset(sampleNo,dataPointNo); |
605 |
} |
606 |
|
607 |
/** |
608 |
\brief |
609 |
Return a reference to the data point shape. |
610 |
*/ |
611 |
ESCRIPT_DLL_API |
612 |
inline |
613 |
const DataTypes::ShapeType& |
614 |
getDataPointShape() const |
615 |
{ |
616 |
return m_data->getShape(); |
617 |
} |
618 |
|
619 |
/** |
620 |
\brief |
621 |
Return the data point shape as a tuple of integers. |
622 |
*/ |
623 |
ESCRIPT_DLL_API |
624 |
const boost::python::tuple |
625 |
getShapeTuple() const; |
626 |
|
627 |
/** |
628 |
\brief |
629 |
Return the size of the data point. It is the product of the |
630 |
data point shape dimensions. |
631 |
*/ |
632 |
ESCRIPT_DLL_API |
633 |
int |
634 |
getDataPointSize() const; |
635 |
|
636 |
/** |
637 |
\brief |
638 |
Return the number of doubles stored for this Data. |
639 |
*/ |
640 |
ESCRIPT_DLL_API |
641 |
DataTypes::ValueType::size_type |
642 |
getLength() const; |
643 |
|
644 |
|
645 |
|
646 |
/** |
647 |
\brief |
648 |
Assign the given value to the tag assocciated with name. Implicitly converts this |
649 |
object to type DataTagged. Throws an exception if this object |
650 |
cannot be converted to a DataTagged object or name cannot be mapped onto a tag key. |
651 |
\param tagKey - Input - Integer key. |
652 |
\param value - Input - Value to associate with given key. |
653 |
==>* |
654 |
*/ |
655 |
ESCRIPT_DLL_API |
656 |
void |
657 |
setTaggedValueByName(std::string name, |
658 |
const boost::python::object& value); |
659 |
|
660 |
/** |
661 |
\brief |
662 |
Assign the given value to the tag. Implicitly converts this |
663 |
object to type DataTagged if it is constant. |
664 |
|
665 |
\param tagKey - Input - Integer key. |
666 |
\param value - Input - Value to associate with given key. |
667 |
==>* |
668 |
*/ |
669 |
ESCRIPT_DLL_API |
670 |
void |
671 |
setTaggedValue(int tagKey, |
672 |
const boost::python::object& value); |
673 |
|
674 |
|
675 |
// /** |
676 |
// \brief |
677 |
// Assign the given value to the tag. Implicitly converts this |
678 |
// object to type DataTagged if it is constant. |
679 |
// |
680 |
// \param tagKey - Input - Integer key. |
681 |
// \param value - Input - Value to associate with given key. |
682 |
// ==>* |
683 |
// */ |
684 |
// ESCRIPT_DLL_API |
685 |
// void |
686 |
// setTaggedValueFromCPP(int tagKey, |
687 |
// const DataArrayView& value); |
688 |
|
689 |
/** |
690 |
\brief |
691 |
Assign the given value to the tag. Implicitly converts this |
692 |
object to type DataTagged if it is constant. |
693 |
|
694 |
\param tagKey - Input - Integer key. |
695 |
\param pointshape - Input - The shape of the value parameter |
696 |
\param value - Input - Value to associate with given key. |
697 |
\param dataOffset - Input - Offset of the begining of the point within the value parameter |
698 |
*/ |
699 |
ESCRIPT_DLL_API |
700 |
void |
701 |
setTaggedValueFromCPP(int tagKey, |
702 |
const DataTypes::ShapeType& pointshape, |
703 |
const DataTypes::ValueType& value, |
704 |
int dataOffset=0); |
705 |
|
706 |
|
707 |
|
708 |
/** |
709 |
\brief |
710 |
Copy other Data object into this Data object where mask is positive. |
711 |
*/ |
712 |
ESCRIPT_DLL_API |
713 |
void |
714 |
copyWithMask(const Data& other, |
715 |
const Data& mask); |
716 |
|
717 |
/** |
718 |
Data object operation methods and operators. |
719 |
*/ |
720 |
|
721 |
/** |
722 |
\brief |
723 |
set all values to zero |
724 |
* |
725 |
*/ |
726 |
ESCRIPT_DLL_API |
727 |
void |
728 |
setToZero(); |
729 |
|
730 |
/** |
731 |
\brief |
732 |
Interpolates this onto the given functionspace and returns |
733 |
the result as a Data object. |
734 |
* |
735 |
*/ |
736 |
ESCRIPT_DLL_API |
737 |
Data |
738 |
interpolate(const FunctionSpace& functionspace) const; |
739 |
/** |
740 |
\brief |
741 |
Calculates the gradient of the data at the data points of functionspace. |
742 |
If functionspace is not present the function space of Function(getDomain()) is used. |
743 |
* |
744 |
*/ |
745 |
ESCRIPT_DLL_API |
746 |
Data |
747 |
gradOn(const FunctionSpace& functionspace) const; |
748 |
|
749 |
ESCRIPT_DLL_API |
750 |
Data |
751 |
grad() const; |
752 |
|
753 |
/** |
754 |
\brief |
755 |
Calculate the integral over the function space domain. |
756 |
* |
757 |
*/ |
758 |
ESCRIPT_DLL_API |
759 |
boost::python::numeric::array |
760 |
integrate() const; |
761 |
|
762 |
/** |
763 |
\brief |
764 |
Returns 1./ Data object |
765 |
* |
766 |
*/ |
767 |
ESCRIPT_DLL_API |
768 |
Data |
769 |
oneOver() const; |
770 |
/** |
771 |
\brief |
772 |
Return a Data with a 1 for +ive values and a 0 for 0 or -ive values. |
773 |
* |
774 |
*/ |
775 |
ESCRIPT_DLL_API |
776 |
Data |
777 |
wherePositive() const; |
778 |
|
779 |
/** |
780 |
\brief |
781 |
Return a Data with a 1 for -ive values and a 0 for +ive or 0 values. |
782 |
* |
783 |
*/ |
784 |
ESCRIPT_DLL_API |
785 |
Data |
786 |
whereNegative() const; |
787 |
|
788 |
/** |
789 |
\brief |
790 |
Return a Data with a 1 for +ive or 0 values and a 0 for -ive values. |
791 |
* |
792 |
*/ |
793 |
ESCRIPT_DLL_API |
794 |
Data |
795 |
whereNonNegative() const; |
796 |
|
797 |
/** |
798 |
\brief |
799 |
Return a Data with a 1 for -ive or 0 values and a 0 for +ive values. |
800 |
* |
801 |
*/ |
802 |
ESCRIPT_DLL_API |
803 |
Data |
804 |
whereNonPositive() const; |
805 |
|
806 |
/** |
807 |
\brief |
808 |
Return a Data with a 1 for 0 values and a 0 for +ive or -ive values. |
809 |
* |
810 |
*/ |
811 |
ESCRIPT_DLL_API |
812 |
Data |
813 |
whereZero(double tol=0.0) const; |
814 |
|
815 |
/** |
816 |
\brief |
817 |
Return a Data with a 0 for 0 values and a 1 for +ive or -ive values. |
818 |
* |
819 |
*/ |
820 |
ESCRIPT_DLL_API |
821 |
Data |
822 |
whereNonZero(double tol=0.0) const; |
823 |
|
824 |
/** |
825 |
\brief |
826 |
Return the maximum absolute value of this Data object. |
827 |
For Data which contain no samples (or tagged Data for which no tags in use have a value) |
828 |
zero is returned. |
829 |
* |
830 |
*/ |
831 |
ESCRIPT_DLL_API |
832 |
double |
833 |
Lsup() const; |
834 |
|
835 |
/** |
836 |
\brief |
837 |
Return the maximum value of this Data object. |
838 |
For Data which contain no samples (or tagged Data for which no tags in use have a value) |
839 |
a large negative value is returned. |
840 |
*/ |
841 |
ESCRIPT_DLL_API |
842 |
double |
843 |
sup() const; |
844 |
|
845 |
/** |
846 |
\brief |
847 |
Return the minimum value of this Data object. |
848 |
For Data which contain no samples (or tagged Data for which no tags in use have a value) |
849 |
a large positive value is returned. |
850 |
* |
851 |
*/ |
852 |
ESCRIPT_DLL_API |
853 |
double |
854 |
inf() const; |
855 |
|
856 |
/** |
857 |
\brief |
858 |
Return the absolute value of each data point of this Data object. |
859 |
* |
860 |
*/ |
861 |
ESCRIPT_DLL_API |
862 |
Data |
863 |
abs() const; |
864 |
|
865 |
/** |
866 |
\brief |
867 |
Return the maximum value of each data point of this Data object. |
868 |
* |
869 |
*/ |
870 |
ESCRIPT_DLL_API |
871 |
Data |
872 |
maxval() const; |
873 |
|
874 |
/** |
875 |
\brief |
876 |
Return the minimum value of each data point of this Data object. |
877 |
* |
878 |
*/ |
879 |
ESCRIPT_DLL_API |
880 |
Data |
881 |
minval() const; |
882 |
|
883 |
/** |
884 |
\brief |
885 |
Return the (sample number, data-point number) of the data point with |
886 |
the minimum value in this Data object. |
887 |
*/ |
888 |
ESCRIPT_DLL_API |
889 |
const boost::python::tuple |
890 |
minGlobalDataPoint() const; |
891 |
|
892 |
ESCRIPT_DLL_API |
893 |
void |
894 |
calc_minGlobalDataPoint(int& ProcNo, int& DataPointNo) const; |
895 |
/** |
896 |
\brief |
897 |
Return the sign of each data point of this Data object. |
898 |
-1 for negative values, zero for zero values, 1 for positive values. |
899 |
* |
900 |
*/ |
901 |
ESCRIPT_DLL_API |
902 |
Data |
903 |
sign() const; |
904 |
|
905 |
/** |
906 |
\brief |
907 |
Return the symmetric part of a matrix which is half the matrix plus its transpose. |
908 |
* |
909 |
*/ |
910 |
ESCRIPT_DLL_API |
911 |
Data |
912 |
symmetric() const; |
913 |
|
914 |
/** |
915 |
\brief |
916 |
Return the nonsymmetric part of a matrix which is half the matrix minus its transpose. |
917 |
* |
918 |
*/ |
919 |
ESCRIPT_DLL_API |
920 |
Data |
921 |
nonsymmetric() const; |
922 |
|
923 |
/** |
924 |
\brief |
925 |
Return the trace of a matrix |
926 |
* |
927 |
*/ |
928 |
ESCRIPT_DLL_API |
929 |
Data |
930 |
trace(int axis_offset) const; |
931 |
|
932 |
/** |
933 |
\brief |
934 |
Transpose each data point of this Data object around the given axis. |
935 |
* |
936 |
*/ |
937 |
ESCRIPT_DLL_API |
938 |
Data |
939 |
transpose(int axis_offset) const; |
940 |
|
941 |
/** |
942 |
\brief |
943 |
Return the eigenvalues of the symmetric part at each data point of this Data object in increasing values. |
944 |
Currently this function is restricted to rank 2, square shape, and dimension 3. |
945 |
* |
946 |
*/ |
947 |
ESCRIPT_DLL_API |
948 |
Data |
949 |
eigenvalues() const; |
950 |
|
951 |
/** |
952 |
\brief |
953 |
Return the eigenvalues and corresponding eigenvcetors of the symmetric part at each data point of this Data object. |
954 |
the eigenvalues are ordered in increasing size where eigenvalues with relative difference less than |
955 |
tol are treated as equal. The eigenvectors are orthogonal, normalized and the sclaed such that the |
956 |
first non-zero entry is positive. |
957 |
Currently this function is restricted to rank 2, square shape, and dimension 3 |
958 |
* |
959 |
*/ |
960 |
ESCRIPT_DLL_API |
961 |
const boost::python::tuple |
962 |
eigenvalues_and_eigenvectors(const double tol=1.e-12) const; |
963 |
|
964 |
/** |
965 |
\brief |
966 |
swaps the components axis0 and axis1 |
967 |
* |
968 |
*/ |
969 |
ESCRIPT_DLL_API |
970 |
Data |
971 |
swapaxes(const int axis0, const int axis1) const; |
972 |
|
973 |
/** |
974 |
\brief |
975 |
Return the error function erf of each data point of this Data object. |
976 |
* |
977 |
*/ |
978 |
ESCRIPT_DLL_API |
979 |
Data |
980 |
erf() const; |
981 |
|
982 |
/** |
983 |
\brief |
984 |
Return the sin of each data point of this Data object. |
985 |
* |
986 |
*/ |
987 |
ESCRIPT_DLL_API |
988 |
Data |
989 |
sin() const; |
990 |
|
991 |
/** |
992 |
\brief |
993 |
Return the cos of each data point of this Data object. |
994 |
* |
995 |
*/ |
996 |
ESCRIPT_DLL_API |
997 |
Data |
998 |
cos() const; |
999 |
|
1000 |
/** |
1001 |
\brief |
1002 |
Return the tan of each data point of this Data object. |
1003 |
* |
1004 |
*/ |
1005 |
ESCRIPT_DLL_API |
1006 |
Data |
1007 |
tan() const; |
1008 |
|
1009 |
/** |
1010 |
\brief |
1011 |
Return the asin of each data point of this Data object. |
1012 |
* |
1013 |
*/ |
1014 |
ESCRIPT_DLL_API |
1015 |
Data |
1016 |
asin() const; |
1017 |
|
1018 |
/** |
1019 |
\brief |
1020 |
Return the acos of each data point of this Data object. |
1021 |
* |
1022 |
*/ |
1023 |
ESCRIPT_DLL_API |
1024 |
Data |
1025 |
acos() const; |
1026 |
|
1027 |
/** |
1028 |
\brief |
1029 |
Return the atan of each data point of this Data object. |
1030 |
* |
1031 |
*/ |
1032 |
ESCRIPT_DLL_API |
1033 |
Data |
1034 |
atan() const; |
1035 |
|
1036 |
/** |
1037 |
\brief |
1038 |
Return the sinh of each data point of this Data object. |
1039 |
* |
1040 |
*/ |
1041 |
ESCRIPT_DLL_API |
1042 |
Data |
1043 |
sinh() const; |
1044 |
|
1045 |
/** |
1046 |
\brief |
1047 |
Return the cosh of each data point of this Data object. |
1048 |
* |
1049 |
*/ |
1050 |
ESCRIPT_DLL_API |
1051 |
Data |
1052 |
cosh() const; |
1053 |
|
1054 |
/** |
1055 |
\brief |
1056 |
Return the tanh of each data point of this Data object. |
1057 |
* |
1058 |
*/ |
1059 |
ESCRIPT_DLL_API |
1060 |
Data |
1061 |
tanh() const; |
1062 |
|
1063 |
/** |
1064 |
\brief |
1065 |
Return the asinh of each data point of this Data object. |
1066 |
* |
1067 |
*/ |
1068 |
ESCRIPT_DLL_API |
1069 |
Data |
1070 |
asinh() const; |
1071 |
|
1072 |
/** |
1073 |
\brief |
1074 |
Return the acosh of each data point of this Data object. |
1075 |
* |
1076 |
*/ |
1077 |
ESCRIPT_DLL_API |
1078 |
Data |
1079 |
acosh() const; |
1080 |
|
1081 |
/** |
1082 |
\brief |
1083 |
Return the atanh of each data point of this Data object. |
1084 |
* |
1085 |
*/ |
1086 |
ESCRIPT_DLL_API |
1087 |
Data |
1088 |
atanh() const; |
1089 |
|
1090 |
/** |
1091 |
\brief |
1092 |
Return the log to base 10 of each data point of this Data object. |
1093 |
* |
1094 |
*/ |
1095 |
ESCRIPT_DLL_API |
1096 |
Data |
1097 |
log10() const; |
1098 |
|
1099 |
/** |
1100 |
\brief |
1101 |
Return the natural log of each data point of this Data object. |
1102 |
* |
1103 |
*/ |
1104 |
ESCRIPT_DLL_API |
1105 |
Data |
1106 |
log() const; |
1107 |
|
1108 |
/** |
1109 |
\brief |
1110 |
Return the exponential function of each data point of this Data object. |
1111 |
* |
1112 |
*/ |
1113 |
ESCRIPT_DLL_API |
1114 |
Data |
1115 |
exp() const; |
1116 |
|
1117 |
/** |
1118 |
\brief |
1119 |
Return the square root of each data point of this Data object. |
1120 |
* |
1121 |
*/ |
1122 |
ESCRIPT_DLL_API |
1123 |
Data |
1124 |
sqrt() const; |
1125 |
|
1126 |
/** |
1127 |
\brief |
1128 |
Return the negation of each data point of this Data object. |
1129 |
* |
1130 |
*/ |
1131 |
ESCRIPT_DLL_API |
1132 |
Data |
1133 |
neg() const; |
1134 |
|
1135 |
/** |
1136 |
\brief |
1137 |
Return the identity of each data point of this Data object. |
1138 |
Simply returns this object unmodified. |
1139 |
* |
1140 |
*/ |
1141 |
ESCRIPT_DLL_API |
1142 |
Data |
1143 |
pos() const; |
1144 |
|
1145 |
/** |
1146 |
\brief |
1147 |
Return the given power of each data point of this Data object. |
1148 |
|
1149 |
\param right Input - the power to raise the object to. |
1150 |
* |
1151 |
*/ |
1152 |
ESCRIPT_DLL_API |
1153 |
Data |
1154 |
powD(const Data& right) const; |
1155 |
|
1156 |
/** |
1157 |
\brief |
1158 |
Return the given power of each data point of this boost python object. |
1159 |
|
1160 |
\param right Input - the power to raise the object to. |
1161 |
* |
1162 |
*/ |
1163 |
ESCRIPT_DLL_API |
1164 |
Data |
1165 |
powO(const boost::python::object& right) const; |
1166 |
|
1167 |
/** |
1168 |
\brief |
1169 |
Return the given power of each data point of this boost python object. |
1170 |
|
1171 |
\param left Input - the bases |
1172 |
* |
1173 |
*/ |
1174 |
|
1175 |
ESCRIPT_DLL_API |
1176 |
Data |
1177 |
rpowO(const boost::python::object& left) const; |
1178 |
|
1179 |
/** |
1180 |
\brief |
1181 |
writes the object to a file in the DX file format |
1182 |
*/ |
1183 |
ESCRIPT_DLL_API |
1184 |
void |
1185 |
saveDX(std::string fileName) const; |
1186 |
|
1187 |
/** |
1188 |
\brief |
1189 |
writes the object to a file in the VTK file format |
1190 |
*/ |
1191 |
ESCRIPT_DLL_API |
1192 |
void |
1193 |
saveVTK(std::string fileName) const; |
1194 |
|
1195 |
/** |
1196 |
\brief |
1197 |
Overloaded operator += |
1198 |
\param right - Input - The right hand side. |
1199 |
* |
1200 |
*/ |
1201 |
ESCRIPT_DLL_API |
1202 |
Data& operator+=(const Data& right); |
1203 |
ESCRIPT_DLL_API |
1204 |
Data& operator+=(const boost::python::object& right); |
1205 |
|
1206 |
ESCRIPT_DLL_API |
1207 |
Data& operator=(const Data& other); |
1208 |
|
1209 |
/** |
1210 |
\brief |
1211 |
Overloaded operator -= |
1212 |
\param right - Input - The right hand side. |
1213 |
* |
1214 |
*/ |
1215 |
ESCRIPT_DLL_API |
1216 |
Data& operator-=(const Data& right); |
1217 |
ESCRIPT_DLL_API |
1218 |
Data& operator-=(const boost::python::object& right); |
1219 |
|
1220 |
/** |
1221 |
\brief |
1222 |
Overloaded operator *= |
1223 |
\param right - Input - The right hand side. |
1224 |
* |
1225 |
*/ |
1226 |
ESCRIPT_DLL_API |
1227 |
Data& operator*=(const Data& right); |
1228 |
ESCRIPT_DLL_API |
1229 |
Data& operator*=(const boost::python::object& right); |
1230 |
|
1231 |
/** |
1232 |
\brief |
1233 |
Overloaded operator /= |
1234 |
\param right - Input - The right hand side. |
1235 |
* |
1236 |
*/ |
1237 |
ESCRIPT_DLL_API |
1238 |
Data& operator/=(const Data& right); |
1239 |
ESCRIPT_DLL_API |
1240 |
Data& operator/=(const boost::python::object& right); |
1241 |
|
1242 |
/** |
1243 |
\brief |
1244 |
Returns true if this can be interpolated to functionspace. |
1245 |
*/ |
1246 |
ESCRIPT_DLL_API |
1247 |
bool |
1248 |
probeInterpolation(const FunctionSpace& functionspace) const; |
1249 |
|
1250 |
/** |
1251 |
Data object slicing methods. |
1252 |
*/ |
1253 |
|
1254 |
/** |
1255 |
\brief |
1256 |
Returns a slice from this Data object. |
1257 |
|
1258 |
/description |
1259 |
Implements the [] get operator in python. |
1260 |
Calls getSlice. |
1261 |
|
1262 |
\param key - Input - python slice tuple specifying |
1263 |
slice to return. |
1264 |
*/ |
1265 |
ESCRIPT_DLL_API |
1266 |
Data |
1267 |
getItem(const boost::python::object& key) const; |
1268 |
|
1269 |
/** |
1270 |
\brief |
1271 |
Copies slice from value into this Data object. |
1272 |
|
1273 |
Implements the [] set operator in python. |
1274 |
Calls setSlice. |
1275 |
|
1276 |
\param key - Input - python slice tuple specifying |
1277 |
slice to copy from value. |
1278 |
\param value - Input - Data object to copy from. |
1279 |
*/ |
1280 |
ESCRIPT_DLL_API |
1281 |
void |
1282 |
setItemD(const boost::python::object& key, |
1283 |
const Data& value); |
1284 |
|
1285 |
ESCRIPT_DLL_API |
1286 |
void |
1287 |
setItemO(const boost::python::object& key, |
1288 |
const boost::python::object& value); |
1289 |
|
1290 |
// These following public methods should be treated as private. |
1291 |
|
1292 |
/** |
1293 |
\brief |
1294 |
Perform the given unary operation on every element of every data point in |
1295 |
this Data object. |
1296 |
*/ |
1297 |
template <class UnaryFunction> |
1298 |
ESCRIPT_DLL_API |
1299 |
inline |
1300 |
void |
1301 |
unaryOp2(UnaryFunction operation); |
1302 |
|
1303 |
/** |
1304 |
\brief |
1305 |
Return a Data object containing the specified slice of |
1306 |
this Data object. |
1307 |
\param region - Input - Region to copy. |
1308 |
* |
1309 |
*/ |
1310 |
ESCRIPT_DLL_API |
1311 |
Data |
1312 |
getSlice(const DataTypes::RegionType& region) const; |
1313 |
|
1314 |
/** |
1315 |
\brief |
1316 |
Copy the specified slice from the given value into this |
1317 |
Data object. |
1318 |
\param value - Input - Data to copy from. |
1319 |
\param region - Input - Region to copy. |
1320 |
* |
1321 |
*/ |
1322 |
ESCRIPT_DLL_API |
1323 |
void |
1324 |
setSlice(const Data& value, |
1325 |
const DataTypes::RegionType& region); |
1326 |
|
1327 |
/** |
1328 |
\brief |
1329 |
print the data values to stdout. Used for debugging |
1330 |
*/ |
1331 |
ESCRIPT_DLL_API |
1332 |
void |
1333 |
print(void); |
1334 |
|
1335 |
/** |
1336 |
\brief |
1337 |
return the MPI rank number of the local data |
1338 |
MPI_COMM_WORLD is assumed and the result of MPI_Comm_size() |
1339 |
is returned |
1340 |
*/ |
1341 |
ESCRIPT_DLL_API |
1342 |
int |
1343 |
get_MPIRank(void) const; |
1344 |
|
1345 |
/** |
1346 |
\brief |
1347 |
return the MPI rank number of the local data |
1348 |
MPI_COMM_WORLD is assumed and the result of MPI_Comm_rank() |
1349 |
is returned |
1350 |
*/ |
1351 |
ESCRIPT_DLL_API |
1352 |
int |
1353 |
get_MPISize(void) const; |
1354 |
|
1355 |
/** |
1356 |
\brief |
1357 |
return the MPI rank number of the local data |
1358 |
MPI_COMM_WORLD is assumed and returned. |
1359 |
*/ |
1360 |
ESCRIPT_DLL_API |
1361 |
MPI_Comm |
1362 |
get_MPIComm(void) const; |
1363 |
|
1364 |
/** |
1365 |
\brief |
1366 |
return the object produced by the factory, which is a DataConstant or DataExpanded |
1367 |
TODO Ownership of this object should be explained in doco. |
1368 |
*/ |
1369 |
ESCRIPT_DLL_API |
1370 |
DataAbstract* |
1371 |
borrowData(void) const; |
1372 |
|
1373 |
|
1374 |
/** |
1375 |
\brief |
1376 |
Return a pointer to the beginning of the datapoint at the specified offset. |
1377 |
TODO Eventually these should be inlined. |
1378 |
\param i - position(offset) in the underlying datastructure |
1379 |
*/ |
1380 |
ESCRIPT_DLL_API |
1381 |
DataTypes::ValueType::const_reference |
1382 |
getDataAtOffset(DataTypes::ValueType::size_type i) const; |
1383 |
|
1384 |
|
1385 |
ESCRIPT_DLL_API |
1386 |
DataTypes::ValueType::reference |
1387 |
getDataAtOffset(DataTypes::ValueType::size_type i); |
1388 |
|
1389 |
protected: |
1390 |
|
1391 |
private: |
1392 |
|
1393 |
/** |
1394 |
\brief |
1395 |
Check *this and the right operand are compatible. Throws |
1396 |
an exception if they aren't. |
1397 |
\param right - Input - The right hand side. |
1398 |
*/ |
1399 |
inline |
1400 |
void |
1401 |
operandCheck(const Data& right) const |
1402 |
{ |
1403 |
return m_data->operandCheck(*(right.m_data.get())); |
1404 |
} |
1405 |
|
1406 |
/** |
1407 |
\brief |
1408 |
Perform the specified reduction algorithm on every element of every data point in |
1409 |
this Data object according to the given function and return the single value result. |
1410 |
*/ |
1411 |
template <class BinaryFunction> |
1412 |
inline |
1413 |
double |
1414 |
algorithm(BinaryFunction operation, |
1415 |
double initial_value) const; |
1416 |
|
1417 |
/** |
1418 |
\brief |
1419 |
Reduce each data-point in this Data object using the given operation. Return a Data |
1420 |
object with the same number of data-points, but with each data-point containing only |
1421 |
one value - the result of the reduction operation on the corresponding data-point in |
1422 |
this Data object |
1423 |
*/ |
1424 |
template <class BinaryFunction> |
1425 |
inline |
1426 |
Data |
1427 |
dp_algorithm(BinaryFunction operation, |
1428 |
double initial_value) const; |
1429 |
|
1430 |
/** |
1431 |
\brief |
1432 |
Perform the given binary operation on all of the data's elements. |
1433 |
The underlying type of the right hand side (right) determines the final |
1434 |
type of *this after the operation. For example if the right hand side |
1435 |
is expanded *this will be expanded if necessary. |
1436 |
RHS is a Data object. |
1437 |
*/ |
1438 |
template <class BinaryFunction> |
1439 |
inline |
1440 |
void |
1441 |
binaryOp(const Data& right, |
1442 |
BinaryFunction operation); |
1443 |
|
1444 |
/** |
1445 |
\brief |
1446 |
Convert the data type of the RHS to match this. |
1447 |
\param right - Input - data type to match. |
1448 |
*/ |
1449 |
void |
1450 |
typeMatchLeft(Data& right) const; |
1451 |
|
1452 |
/** |
1453 |
\brief |
1454 |
Convert the data type of this to match the RHS. |
1455 |
\param right - Input - data type to match. |
1456 |
*/ |
1457 |
void |
1458 |
typeMatchRight(const Data& right); |
1459 |
|
1460 |
/** |
1461 |
\brief |
1462 |
Construct a Data object of the appropriate type. |
1463 |
*/ |
1464 |
|
1465 |
void |
1466 |
initialise(const DataTypes::ValueType& value, |
1467 |
const DataTypes::ShapeType& shape, |
1468 |
const FunctionSpace& what, |
1469 |
bool expanded); |
1470 |
|
1471 |
void |
1472 |
initialise(const boost::python::numeric::array& value, |
1473 |
const FunctionSpace& what, |
1474 |
bool expanded); |
1475 |
|
1476 |
// |
1477 |
// flag to protect the data object against any update |
1478 |
bool m_protected; |
1479 |
|
1480 |
// |
1481 |
// pointer to the actual data object |
1482 |
// boost::shared_ptr<DataAbstract> m_data; |
1483 |
DataAbstract_ptr m_data; |
1484 |
|
1485 |
}; |
1486 |
|
1487 |
|
1488 |
|
1489 |
/** |
1490 |
Modify a filename for MPI parallel output to multiple files |
1491 |
*/ |
1492 |
char *Escript_MPI_appendRankToFileName(const char *, int, int); |
1493 |
|
1494 |
/** |
1495 |
Binary Data object operators. |
1496 |
*/ |
1497 |
inline double rpow(double x,double y) |
1498 |
{ |
1499 |
return pow(y,x); |
1500 |
} |
1501 |
|
1502 |
/** |
1503 |
\brief |
1504 |
Operator+ |
1505 |
Takes two Data objects. |
1506 |
*/ |
1507 |
ESCRIPT_DLL_API Data operator+(const Data& left, const Data& right); |
1508 |
|
1509 |
/** |
1510 |
\brief |
1511 |
Operator- |
1512 |
Takes two Data objects. |
1513 |
*/ |
1514 |
ESCRIPT_DLL_API Data operator-(const Data& left, const Data& right); |
1515 |
|
1516 |
/** |
1517 |
\brief |
1518 |
Operator* |
1519 |
Takes two Data objects. |
1520 |
*/ |
1521 |
ESCRIPT_DLL_API Data operator*(const Data& left, const Data& right); |
1522 |
|
1523 |
/** |
1524 |
\brief |
1525 |
Operator/ |
1526 |
Takes two Data objects. |
1527 |
*/ |
1528 |
ESCRIPT_DLL_API Data operator/(const Data& left, const Data& right); |
1529 |
|
1530 |
/** |
1531 |
\brief |
1532 |
Operator+ |
1533 |
Takes LHS Data object and RHS python::object. |
1534 |
python::object must be convertable to Data type. |
1535 |
*/ |
1536 |
ESCRIPT_DLL_API Data operator+(const Data& left, const boost::python::object& right); |
1537 |
|
1538 |
/** |
1539 |
\brief |
1540 |
Operator- |
1541 |
Takes LHS Data object and RHS python::object. |
1542 |
python::object must be convertable to Data type. |
1543 |
*/ |
1544 |
ESCRIPT_DLL_API Data operator-(const Data& left, const boost::python::object& right); |
1545 |
|
1546 |
/** |
1547 |
\brief |
1548 |
Operator* |
1549 |
Takes LHS Data object and RHS python::object. |
1550 |
python::object must be convertable to Data type. |
1551 |
*/ |
1552 |
ESCRIPT_DLL_API Data operator*(const Data& left, const boost::python::object& right); |
1553 |
|
1554 |
/** |
1555 |
\brief |
1556 |
Operator/ |
1557 |
Takes LHS Data object and RHS python::object. |
1558 |
python::object must be convertable to Data type. |
1559 |
*/ |
1560 |
ESCRIPT_DLL_API Data operator/(const Data& left, const boost::python::object& right); |
1561 |
|
1562 |
/** |
1563 |
\brief |
1564 |
Operator+ |
1565 |
Takes LHS python::object and RHS Data object. |
1566 |
python::object must be convertable to Data type. |
1567 |
*/ |
1568 |
ESCRIPT_DLL_API Data operator+(const boost::python::object& left, const Data& right); |
1569 |
|
1570 |
/** |
1571 |
\brief |
1572 |
Operator- |
1573 |
Takes LHS python::object and RHS Data object. |
1574 |
python::object must be convertable to Data type. |
1575 |
*/ |
1576 |
ESCRIPT_DLL_API Data operator-(const boost::python::object& left, const Data& right); |
1577 |
|
1578 |
/** |
1579 |
\brief |
1580 |
Operator* |
1581 |
Takes LHS python::object and RHS Data object. |
1582 |
python::object must be convertable to Data type. |
1583 |
*/ |
1584 |
ESCRIPT_DLL_API Data operator*(const boost::python::object& left, const Data& right); |
1585 |
|
1586 |
/** |
1587 |
\brief |
1588 |
Operator/ |
1589 |
Takes LHS python::object and RHS Data object. |
1590 |
python::object must be convertable to Data type. |
1591 |
*/ |
1592 |
ESCRIPT_DLL_API Data operator/(const boost::python::object& left, const Data& right); |
1593 |
|
1594 |
|
1595 |
|
1596 |
/** |
1597 |
\brief |
1598 |
Output operator |
1599 |
*/ |
1600 |
ESCRIPT_DLL_API std::ostream& operator<<(std::ostream& o, const Data& data); |
1601 |
|
1602 |
/** |
1603 |
\brief |
1604 |
Compute a tensor product of two Data objects |
1605 |
\param arg0 - Input - Data object |
1606 |
\param arg1 - Input - Data object |
1607 |
\param axis_offset - Input - axis offset |
1608 |
\param transpose - Input - 0: transpose neither, 1: transpose arg0, 2: transpose arg1 |
1609 |
*/ |
1610 |
ESCRIPT_DLL_API |
1611 |
Data |
1612 |
C_GeneralTensorProduct(Data& arg0, |
1613 |
Data& arg1, |
1614 |
int axis_offset=0, |
1615 |
int transpose=0); |
1616 |
|
1617 |
|
1618 |
|
1619 |
// /** |
1620 |
/* \brief |
1621 |
Return true if operands are equivalent, else return false. |
1622 |
NB: this operator does very little at this point, and isn't to |
1623 |
be relied on. Requires further implementation.*/ |
1624 |
//*/ |
1625 |
// ESCRIPT_DLL_API bool operator==(const Data& left, const Data& right); |
1626 |
|
1627 |
/** |
1628 |
\brief |
1629 |
Perform the given binary operation with this and right as operands. |
1630 |
Right is a Data object. |
1631 |
*/ |
1632 |
template <class BinaryFunction> |
1633 |
inline |
1634 |
void |
1635 |
Data::binaryOp(const Data& right, |
1636 |
BinaryFunction operation) |
1637 |
{ |
1638 |
// |
1639 |
// if this has a rank of zero promote it to the rank of the RHS |
1640 |
if (getDataPointRank()==0 && right.getDataPointRank()!=0) { |
1641 |
throw DataException("Error - attempt to update rank zero object with object with rank bigger than zero."); |
1642 |
} |
1643 |
// |
1644 |
// initially make the temporary a shallow copy |
1645 |
Data tempRight(right); |
1646 |
if (getFunctionSpace()!=right.getFunctionSpace()) { |
1647 |
if (right.probeInterpolation(getFunctionSpace())) { |
1648 |
// |
1649 |
// an interpolation is required so create a new Data |
1650 |
tempRight=Data(right,this->getFunctionSpace()); |
1651 |
} else if (probeInterpolation(right.getFunctionSpace())) { |
1652 |
// |
1653 |
// interpolate onto the RHS function space |
1654 |
Data tempLeft(*this,right.getFunctionSpace()); |
1655 |
m_data=tempLeft.m_data; |
1656 |
} |
1657 |
} |
1658 |
operandCheck(tempRight); |
1659 |
// |
1660 |
// ensure this has the right type for the RHS |
1661 |
typeMatchRight(tempRight); |
1662 |
// |
1663 |
// Need to cast to the concrete types so that the correct binaryOp |
1664 |
// is called. |
1665 |
if (isExpanded()) { |
1666 |
// |
1667 |
// Expanded data will be done in parallel, the right hand side can be |
1668 |
// of any data type |
1669 |
DataExpanded* leftC=dynamic_cast<DataExpanded*>(m_data.get()); |
1670 |
EsysAssert((leftC!=0), "Programming error - casting to DataExpanded."); |
1671 |
escript::binaryOp(*leftC,*(tempRight.m_data.get()),operation); |
1672 |
} else if (isTagged()) { |
1673 |
// |
1674 |
// Tagged data is operated on serially, the right hand side can be |
1675 |
// either DataConstant or DataTagged |
1676 |
DataTagged* leftC=dynamic_cast<DataTagged*>(m_data.get()); |
1677 |
EsysAssert((leftC!=0), "Programming error - casting to DataTagged."); |
1678 |
if (right.isTagged()) { |
1679 |
DataTagged* rightC=dynamic_cast<DataTagged*>(tempRight.m_data.get()); |
1680 |
EsysAssert((rightC!=0), "Programming error - casting to DataTagged."); |
1681 |
escript::binaryOp(*leftC,*rightC,operation); |
1682 |
} else { |
1683 |
DataConstant* rightC=dynamic_cast<DataConstant*>(tempRight.m_data.get()); |
1684 |
EsysAssert((rightC!=0), "Programming error - casting to DataConstant."); |
1685 |
escript::binaryOp(*leftC,*rightC,operation); |
1686 |
} |
1687 |
} else if (isConstant()) { |
1688 |
DataConstant* leftC=dynamic_cast<DataConstant*>(m_data.get()); |
1689 |
DataConstant* rightC=dynamic_cast<DataConstant*>(tempRight.m_data.get()); |
1690 |
EsysAssert((leftC!=0 && rightC!=0), "Programming error - casting to DataConstant."); |
1691 |
escript::binaryOp(*leftC,*rightC,operation); |
1692 |
} |
1693 |
} |
1694 |
|
1695 |
/** |
1696 |
\brief |
1697 |
Perform the given Data object reduction algorithm on this and return the result. |
1698 |
Given operation combines each element of each data point, thus argument |
1699 |
object (*this) is a rank n Data object, and returned object is a scalar. |
1700 |
Calls escript::algorithm. |
1701 |
*/ |
1702 |
template <class BinaryFunction> |
1703 |
inline |
1704 |
double |
1705 |
Data::algorithm(BinaryFunction operation, double initial_value) const |
1706 |
{ |
1707 |
if (isExpanded()) { |
1708 |
DataExpanded* leftC=dynamic_cast<DataExpanded*>(m_data.get()); |
1709 |
EsysAssert((leftC!=0), "Programming error - casting to DataExpanded."); |
1710 |
return escript::algorithm(*leftC,operation,initial_value); |
1711 |
} else if (isTagged()) { |
1712 |
DataTagged* leftC=dynamic_cast<DataTagged*>(m_data.get()); |
1713 |
EsysAssert((leftC!=0), "Programming error - casting to DataTagged."); |
1714 |
return escript::algorithm(*leftC,operation,initial_value); |
1715 |
} else if (isConstant()) { |
1716 |
DataConstant* leftC=dynamic_cast<DataConstant*>(m_data.get()); |
1717 |
EsysAssert((leftC!=0), "Programming error - casting to DataConstant."); |
1718 |
return escript::algorithm(*leftC,operation,initial_value); |
1719 |
} else if (isEmpty()) { |
1720 |
throw DataException("Error - Operations not permitted on instances of DataEmpty."); |
1721 |
} |
1722 |
return 0; |
1723 |
} |
1724 |
|
1725 |
/** |
1726 |
\brief |
1727 |
Perform the given data point reduction algorithm on data and return the result. |
1728 |
Given operation combines each element within each data point into a scalar, |
1729 |
thus argument object is a rank n Data object, and returned object is a |
1730 |
rank 0 Data object. |
1731 |
Calls escript::dp_algorithm. |
1732 |
*/ |
1733 |
template <class BinaryFunction> |
1734 |
inline |
1735 |
Data |
1736 |
Data::dp_algorithm(BinaryFunction operation, double initial_value) const |
1737 |
{ |
1738 |
if (isEmpty()) { |
1739 |
throw DataException("Error - Operations not permitted on instances of DataEmpty."); |
1740 |
} |
1741 |
else if (isExpanded()) { |
1742 |
Data result(0,DataTypes::ShapeType(),getFunctionSpace(),isExpanded()); |
1743 |
DataExpanded* dataE=dynamic_cast<DataExpanded*>(m_data.get()); |
1744 |
DataExpanded* resultE=dynamic_cast<DataExpanded*>(result.m_data.get()); |
1745 |
EsysAssert((dataE!=0), "Programming error - casting data to DataExpanded."); |
1746 |
EsysAssert((resultE!=0), "Programming error - casting result to DataExpanded."); |
1747 |
escript::dp_algorithm(*dataE,*resultE,operation,initial_value); |
1748 |
return result; |
1749 |
} |
1750 |
else if (isTagged()) { |
1751 |
DataTagged* dataT=dynamic_cast<DataTagged*>(m_data.get()); |
1752 |
EsysAssert((dataT!=0), "Programming error - casting data to DataTagged."); |
1753 |
DataTypes::ValueType defval(1); |
1754 |
defval[0]=0; |
1755 |
DataTagged* resultT=new DataTagged(getFunctionSpace(), DataTypes::scalarShape, defval, dataT); |
1756 |
escript::dp_algorithm(*dataT,*resultT,operation,initial_value); |
1757 |
return Data(resultT); // note: the Data object now owns the resultT pointer |
1758 |
} |
1759 |
else if (isConstant()) { |
1760 |
Data result(0,DataTypes::ShapeType(),getFunctionSpace(),isExpanded()); |
1761 |
DataConstant* dataC=dynamic_cast<DataConstant*>(m_data.get()); |
1762 |
DataConstant* resultC=dynamic_cast<DataConstant*>(result.m_data.get()); |
1763 |
EsysAssert((dataC!=0), "Programming error - casting data to DataConstant."); |
1764 |
EsysAssert((resultC!=0), "Programming error - casting result to DataConstant."); |
1765 |
escript::dp_algorithm(*dataC,*resultC,operation,initial_value); |
1766 |
return result; |
1767 |
} |
1768 |
Data falseRetVal; // to keep compiler quiet |
1769 |
return falseRetVal; |
1770 |
} |
1771 |
|
1772 |
/** |
1773 |
\brief |
1774 |
Compute a tensor operation with two Data objects |
1775 |
\param arg0 - Input - Data object |
1776 |
\param arg1 - Input - Data object |
1777 |
\param operation - Input - Binary op functor |
1778 |
*/ |
1779 |
template <typename BinaryFunction> |
1780 |
inline |
1781 |
Data |
1782 |
C_TensorBinaryOperation(Data const &arg_0, |
1783 |
Data const &arg_1, |
1784 |
BinaryFunction operation) |
1785 |
{ |
1786 |
if (arg_0.isEmpty() || arg_1.isEmpty()) |
1787 |
{ |
1788 |
throw DataException("Error - Operations not permitted on instances of DataEmpty."); |
1789 |
} |
1790 |
// Interpolate if necessary and find an appropriate function space |
1791 |
Data arg_0_Z, arg_1_Z; |
1792 |
if (arg_0.getFunctionSpace()!=arg_1.getFunctionSpace()) { |
1793 |
if (arg_0.probeInterpolation(arg_1.getFunctionSpace())) { |
1794 |
arg_0_Z = arg_0.interpolate(arg_1.getFunctionSpace()); |
1795 |
arg_1_Z = Data(arg_1); |
1796 |
} |
1797 |
else if (arg_1.probeInterpolation(arg_0.getFunctionSpace())) { |
1798 |
arg_1_Z=arg_1.interpolate(arg_0.getFunctionSpace()); |
1799 |
arg_0_Z =Data(arg_0); |
1800 |
} |
1801 |
else { |
1802 |
throw DataException("Error - C_TensorBinaryOperation: arguments have incompatible function spaces."); |
1803 |
} |
1804 |
} else { |
1805 |
arg_0_Z = Data(arg_0); |
1806 |
arg_1_Z = Data(arg_1); |
1807 |
} |
1808 |
// Get rank and shape of inputs |
1809 |
int rank0 = arg_0_Z.getDataPointRank(); |
1810 |
int rank1 = arg_1_Z.getDataPointRank(); |
1811 |
DataTypes::ShapeType shape0 = arg_0_Z.getDataPointShape(); |
1812 |
DataTypes::ShapeType shape1 = arg_1_Z.getDataPointShape(); |
1813 |
int size0 = arg_0_Z.getDataPointSize(); |
1814 |
int size1 = arg_1_Z.getDataPointSize(); |
1815 |
|
1816 |
// Declare output Data object |
1817 |
Data res; |
1818 |
|
1819 |
if (shape0 == shape1) { |
1820 |
|
1821 |
if (arg_0_Z.isConstant() && arg_1_Z.isConstant()) { |
1822 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace()); // DataConstant output |
1823 |
/* double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]); |
1824 |
double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[0]); |
1825 |
double *ptr_2 = &((res.getPointDataView().getData())[0]);*/ |
1826 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(0)); |
1827 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(0)); |
1828 |
double *ptr_2 = &(res.getDataAtOffset(0)); |
1829 |
|
1830 |
tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation); |
1831 |
} |
1832 |
else if (arg_0_Z.isConstant() && arg_1_Z.isTagged()) { |
1833 |
|
1834 |
// Prepare the DataConstant input |
1835 |
DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData()); |
1836 |
|
1837 |
// Borrow DataTagged input from Data object |
1838 |
DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData()); |
1839 |
|
1840 |
// Prepare a DataTagged output 2 |
1841 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace()); // DataTagged output |
1842 |
res.tag(); |
1843 |
DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData()); |
1844 |
|
1845 |
// Prepare offset into DataConstant |
1846 |
int offset_0 = tmp_0->getPointOffset(0,0); |
1847 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
1848 |
// Get the views |
1849 |
// DataArrayView view_1 = tmp_1->getDefaultValue(); |
1850 |
// DataArrayView view_2 = tmp_2->getDefaultValue(); |
1851 |
// // Get the pointers to the actual data |
1852 |
// double *ptr_1 = &((view_1.getData())[0]); |
1853 |
// double *ptr_2 = &((view_2.getData())[0]); |
1854 |
|
1855 |
// Get the pointers to the actual data |
1856 |
double *ptr_1 = &(tmp_1->getDefaultValue(0)); |
1857 |
double *ptr_2 = &(tmp_2->getDefaultValue(0)); |
1858 |
|
1859 |
// Compute a result for the default |
1860 |
tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation); |
1861 |
// Compute a result for each tag |
1862 |
const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup(); |
1863 |
DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory |
1864 |
for (i=lookup_1.begin();i!=lookup_1.end();i++) { |
1865 |
tmp_2->addTag(i->first); |
1866 |
/* DataArrayView view_1 = tmp_1->getDataPointByTag(i->first); |
1867 |
DataArrayView view_2 = tmp_2->getDataPointByTag(i->first); |
1868 |
double *ptr_1 = &view_1.getData(0); |
1869 |
double *ptr_2 = &view_2.getData(0);*/ |
1870 |
double *ptr_1 = &(tmp_1->getDataByTag(i->first,0)); |
1871 |
double *ptr_2 = &(tmp_2->getDataByTag(i->first,0)); |
1872 |
|
1873 |
tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation); |
1874 |
} |
1875 |
|
1876 |
} |
1877 |
else if (arg_0_Z.isConstant() && arg_1_Z.isExpanded()) { |
1878 |
|
1879 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output |
1880 |
DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData()); |
1881 |
DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData()); |
1882 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
1883 |
|
1884 |
int sampleNo_1,dataPointNo_1; |
1885 |
int numSamples_1 = arg_1_Z.getNumSamples(); |
1886 |
int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample(); |
1887 |
int offset_0 = tmp_0->getPointOffset(0,0); |
1888 |
#pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static) |
1889 |
for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) { |
1890 |
for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) { |
1891 |
int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1); |
1892 |
int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1); |
1893 |
// double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]); |
1894 |
// double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]); |
1895 |
// double *ptr_2 = &((res.getPointDataView().getData())[offset_2]); |
1896 |
|
1897 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
1898 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
1899 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
1900 |
tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation); |
1901 |
} |
1902 |
} |
1903 |
|
1904 |
} |
1905 |
else if (arg_0_Z.isTagged() && arg_1_Z.isConstant()) { |
1906 |
|
1907 |
// Borrow DataTagged input from Data object |
1908 |
DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData()); |
1909 |
|
1910 |
// Prepare the DataConstant input |
1911 |
DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData()); |
1912 |
|
1913 |
// Prepare a DataTagged output 2 |
1914 |
res = Data(0.0, shape0, arg_0_Z.getFunctionSpace()); // DataTagged output |
1915 |
res.tag(); |
1916 |
DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData()); |
1917 |
|
1918 |
// Prepare offset into DataConstant |
1919 |
int offset_1 = tmp_1->getPointOffset(0,0); |
1920 |
// double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]); |
1921 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
1922 |
// Get the views |
1923 |
// DataArrayView view_0 = tmp_0->getDefaultValue(); |
1924 |
// DataArrayView view_2 = tmp_2->getDefaultValue(); |
1925 |
// // Get the pointers to the actual data |
1926 |
// double *ptr_0 = &((view_0.getData())[0]); |
1927 |
// double *ptr_2 = &((view_2.getData())[0]); |
1928 |
// Get the pointers to the actual data |
1929 |
double *ptr_0 = &(tmp_0->getDefaultValue(0)); |
1930 |
double *ptr_2 = &(tmp_2->getDefaultValue(0)); |
1931 |
// Compute a result for the default |
1932 |
tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation); |
1933 |
// Compute a result for each tag |
1934 |
const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup(); |
1935 |
DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory |
1936 |
for (i=lookup_0.begin();i!=lookup_0.end();i++) { |
1937 |
tmp_2->addTag(i->first); |
1938 |
// DataArrayView view_0 = tmp_0->getDataPointByTag(i->first); |
1939 |
// DataArrayView view_2 = tmp_2->getDataPointByTag(i->first); |
1940 |
// double *ptr_0 = &view_0.getData(0); |
1941 |
// double *ptr_2 = &view_2.getData(0); |
1942 |
double *ptr_0 = &(tmp_0->getDataByTag(i->first,0)); |
1943 |
double *ptr_2 = &(tmp_2->getDataByTag(i->first,0)); |
1944 |
tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation); |
1945 |
} |
1946 |
|
1947 |
} |
1948 |
else if (arg_0_Z.isTagged() && arg_1_Z.isTagged()) { |
1949 |
|
1950 |
// Borrow DataTagged input from Data object |
1951 |
DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData()); |
1952 |
|
1953 |
// Borrow DataTagged input from Data object |
1954 |
DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData()); |
1955 |
|
1956 |
// Prepare a DataTagged output 2 |
1957 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace()); |
1958 |
res.tag(); // DataTagged output |
1959 |
DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData()); |
1960 |
|
1961 |
// // Get the views |
1962 |
// DataArrayView view_0 = tmp_0->getDefaultValue(); |
1963 |
// DataArrayView view_1 = tmp_1->getDefaultValue(); |
1964 |
// DataArrayView view_2 = tmp_2->getDefaultValue(); |
1965 |
// // Get the pointers to the actual data |
1966 |
// double *ptr_0 = &((view_0.getData())[0]); |
1967 |
// double *ptr_1 = &((view_1.getData())[0]); |
1968 |
// double *ptr_2 = &((view_2.getData())[0]); |
1969 |
|
1970 |
// Get the pointers to the actual data |
1971 |
double *ptr_0 = &(tmp_0->getDefaultValue(0)); |
1972 |
double *ptr_1 = &(tmp_1->getDefaultValue(0)); |
1973 |
double *ptr_2 = &(tmp_2->getDefaultValue(0)); |
1974 |
|
1975 |
// Compute a result for the default |
1976 |
tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation); |
1977 |
// Merge the tags |
1978 |
DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory |
1979 |
const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup(); |
1980 |
const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup(); |
1981 |
for (i=lookup_0.begin();i!=lookup_0.end();i++) { |
1982 |
tmp_2->addTag(i->first); // use tmp_2 to get correct shape |
1983 |
} |
1984 |
for (i=lookup_1.begin();i!=lookup_1.end();i++) { |
1985 |
tmp_2->addTag(i->first); |
1986 |
} |
1987 |
// Compute a result for each tag |
1988 |
const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup(); |
1989 |
for (i=lookup_2.begin();i!=lookup_2.end();i++) { |
1990 |
|
1991 |
// DataArrayView view_0 = tmp_0->getDataPointByTag(i->first); |
1992 |
// DataArrayView view_1 = tmp_1->getDataPointByTag(i->first); |
1993 |
// DataArrayView view_2 = tmp_2->getDataPointByTag(i->first); |
1994 |
// double *ptr_0 = &view_0.getData(0); |
1995 |
// double *ptr_1 = &view_1.getData(0); |
1996 |
// double *ptr_2 = &view_2.getData(0); |
1997 |
|
1998 |
double *ptr_0 = &(tmp_0->getDataByTag(i->first,0)); |
1999 |
double *ptr_1 = &(tmp_1->getDataByTag(i->first,0)); |
2000 |
double *ptr_2 = &(tmp_2->getDataByTag(i->first,0)); |
2001 |
|
2002 |
tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation); |
2003 |
} |
2004 |
|
2005 |
} |
2006 |
else if (arg_0_Z.isTagged() && arg_1_Z.isExpanded()) { |
2007 |
|
2008 |
// After finding a common function space above the two inputs have the same numSamples and num DPPS |
2009 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output |
2010 |
DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData()); |
2011 |
DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData()); |
2012 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
2013 |
|
2014 |
int sampleNo_0,dataPointNo_0; |
2015 |
int numSamples_0 = arg_0_Z.getNumSamples(); |
2016 |
int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample(); |
2017 |
#pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static) |
2018 |
for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) { |
2019 |
int offset_0 = tmp_0->getPointOffset(sampleNo_0,0); // They're all the same, so just use #0 |
2020 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2021 |
for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) { |
2022 |
int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0); |
2023 |
int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0); |
2024 |
|
2025 |
// double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]); |
2026 |
// double *ptr_2 = &((res.getPointDataView().getData())[offset_2]); |
2027 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2028 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
2029 |
|
2030 |
|
2031 |
tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation); |
2032 |
} |
2033 |
} |
2034 |
|
2035 |
} |
2036 |
else if (arg_0_Z.isExpanded() && arg_1_Z.isConstant()) { |
2037 |
|
2038 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output |
2039 |
DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData()); |
2040 |
DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData()); |
2041 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
2042 |
|
2043 |
int sampleNo_0,dataPointNo_0; |
2044 |
int numSamples_0 = arg_0_Z.getNumSamples(); |
2045 |
int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample(); |
2046 |
int offset_1 = tmp_1->getPointOffset(0,0); |
2047 |
#pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static) |
2048 |
for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) { |
2049 |
for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) { |
2050 |
int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0); |
2051 |
int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0); |
2052 |
|
2053 |
// double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]); |
2054 |
// double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]); |
2055 |
// double *ptr_2 = &((res.getPointDataView().getData())[offset_2]); |
2056 |
|
2057 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2058 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2059 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
2060 |
|
2061 |
|
2062 |
tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation); |
2063 |
} |
2064 |
} |
2065 |
|
2066 |
} |
2067 |
else if (arg_0_Z.isExpanded() && arg_1_Z.isTagged()) { |
2068 |
|
2069 |
// After finding a common function space above the two inputs have the same numSamples and num DPPS |
2070 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output |
2071 |
DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData()); |
2072 |
DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData()); |
2073 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
2074 |
|
2075 |
int sampleNo_0,dataPointNo_0; |
2076 |
int numSamples_0 = arg_0_Z.getNumSamples(); |
2077 |
int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample(); |
2078 |
#pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static) |
2079 |
for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) { |
2080 |
int offset_1 = tmp_1->getPointOffset(sampleNo_0,0); |
2081 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2082 |
for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) { |
2083 |
int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0); |
2084 |
int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0); |
2085 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2086 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
2087 |
tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation); |
2088 |
} |
2089 |
} |
2090 |
|
2091 |
} |
2092 |
else if (arg_0_Z.isExpanded() && arg_1_Z.isExpanded()) { |
2093 |
|
2094 |
// After finding a common function space above the two inputs have the same numSamples and num DPPS |
2095 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output |
2096 |
DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData()); |
2097 |
DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData()); |
2098 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
2099 |
|
2100 |
int sampleNo_0,dataPointNo_0; |
2101 |
int numSamples_0 = arg_0_Z.getNumSamples(); |
2102 |
int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample(); |
2103 |
#pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static) |
2104 |
for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) { |
2105 |
for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) { |
2106 |
int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0); |
2107 |
int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0); |
2108 |
int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0); |
2109 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2110 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2111 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
2112 |
tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation); |
2113 |
} |
2114 |
} |
2115 |
|
2116 |
} |
2117 |
else { |
2118 |
throw DataException("Error - C_TensorBinaryOperation: unknown combination of inputs"); |
2119 |
} |
2120 |
|
2121 |
} else if (0 == rank0) { |
2122 |
|
2123 |
if (arg_0_Z.isConstant() && arg_1_Z.isConstant()) { |
2124 |
res = Data(0.0, shape1, arg_1_Z.getFunctionSpace()); // DataConstant output |
2125 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(0)); |
2126 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(0)); |
2127 |
double *ptr_2 = &(res.getDataAtOffset(0)); |
2128 |
tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation); |
2129 |
} |
2130 |
else if (arg_0_Z.isConstant() && arg_1_Z.isTagged()) { |
2131 |
|
2132 |
// Prepare the DataConstant input |
2133 |
DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData()); |
2134 |
|
2135 |
// Borrow DataTagged input from Data object |
2136 |
DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData()); |
2137 |
|
2138 |
// Prepare a DataTagged output 2 |
2139 |
res = Data(0.0, shape1, arg_1_Z.getFunctionSpace()); // DataTagged output |
2140 |
res.tag(); |
2141 |
DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData()); |
2142 |
|
2143 |
// Prepare offset into DataConstant |
2144 |
int offset_0 = tmp_0->getPointOffset(0,0); |
2145 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2146 |
// Get the views |
2147 |
// DataArrayView view_1 = tmp_1->getDefaultValue(); |
2148 |
// DataArrayView view_2 = tmp_2->getDefaultValue(); |
2149 |
// // Get the pointers to the actual data |
2150 |
// double *ptr_1 = &((view_1.getData())[0]); |
2151 |
// double *ptr_2 = &((view_2.getData())[0]); |
2152 |
double *ptr_1 = &(tmp_1->getDefaultValue(0)); |
2153 |
double *ptr_2 = &(tmp_2->getDefaultValue(0)); |
2154 |
|
2155 |
// Compute a result for the default |
2156 |
tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation); |
2157 |
// Compute a result for each tag |
2158 |
const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup(); |
2159 |
DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory |
2160 |
for (i=lookup_1.begin();i!=lookup_1.end();i++) { |
2161 |
tmp_2->addTag(i->first); |
2162 |
// DataArrayView view_1 = tmp_1->getDataPointByTag(i->first); |
2163 |
// DataArrayView view_2 = tmp_2->getDataPointByTag(i->first); |
2164 |
// double *ptr_1 = &view_1.getData(0); |
2165 |
// double *ptr_2 = &view_2.getData(0); |
2166 |
double *ptr_1 = &(tmp_1->getDataByTag(i->first,0)); |
2167 |
double *ptr_2 = &(tmp_2->getDataByTag(i->first,0)); |
2168 |
tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation); |
2169 |
} |
2170 |
|
2171 |
} |
2172 |
else if (arg_0_Z.isConstant() && arg_1_Z.isExpanded()) { |
2173 |
|
2174 |
res = Data(0.0, shape1, arg_1_Z.getFunctionSpace(),true); // DataExpanded output |
2175 |
DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData()); |
2176 |
DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData()); |
2177 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
2178 |
|
2179 |
int sampleNo_1,dataPointNo_1; |
2180 |
int numSamples_1 = arg_1_Z.getNumSamples(); |
2181 |
int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample(); |
2182 |
int offset_0 = tmp_0->getPointOffset(0,0); |
2183 |
#pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static) |
2184 |
for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) { |
2185 |
for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) { |
2186 |
int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1); |
2187 |
int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1); |
2188 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2189 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2190 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
2191 |
tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation); |
2192 |
|
2193 |
} |
2194 |
} |
2195 |
|
2196 |
} |
2197 |
else if (arg_0_Z.isTagged() && arg_1_Z.isConstant()) { |
2198 |
|
2199 |
// Borrow DataTagged input from Data object |
2200 |
DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData()); |
2201 |
|
2202 |
// Prepare the DataConstant input |
2203 |
DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData()); |
2204 |
|
2205 |
// Prepare a DataTagged output 2 |
2206 |
res = Data(0.0, shape1, arg_0_Z.getFunctionSpace()); // DataTagged output |
2207 |
res.tag(); |
2208 |
DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData()); |
2209 |
|
2210 |
// Prepare offset into DataConstant |
2211 |
int offset_1 = tmp_1->getPointOffset(0,0); |
2212 |
// double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]); |
2213 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2214 |
// Get the views |
2215 |
/* DataArrayView view_0 = tmp_0->getDefaultValue(); |
2216 |
DataArrayView view_2 = tmp_2->getDefaultValue(); |
2217 |
// Get the pointers to the actual data |
2218 |
double *ptr_0 = &((view_0.getData())[0]); |
2219 |
double *ptr_2 = &((view_2.getData())[0]);*/ |
2220 |
|
2221 |
// Get the pointers to the actual data |
2222 |
double *ptr_0 = &(tmp_0->getDefaultValue(0)); |
2223 |
double *ptr_2 = &(tmp_2->getDefaultValue(0)); |
2224 |
|
2225 |
|
2226 |
// Compute a result for the default |
2227 |
tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation); |
2228 |
// Compute a result for each tag |
2229 |
const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup(); |
2230 |
DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory |
2231 |
for (i=lookup_0.begin();i!=lookup_0.end();i++) { |
2232 |
tmp_2->addTag(i->first); |
2233 |
/* DataArrayView view_0 = tmp_0->getDataPointByTag(i->first); |
2234 |
DataArrayView view_2 = tmp_2->getDataPointByTag(i->first); |
2235 |
double *ptr_0 = &view_0.getData(0); |
2236 |
double *ptr_2 = &view_2.getData(0);*/ |
2237 |
double *ptr_0 = &(tmp_0->getDataByTag(i->first,0)); |
2238 |
double *ptr_2 = &(tmp_2->getDataByTag(i->first,0)); |
2239 |
|
2240 |
tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation); |
2241 |
} |
2242 |
|
2243 |
} |
2244 |
else if (arg_0_Z.isTagged() && arg_1_Z.isTagged()) { |
2245 |
|
2246 |
// Borrow DataTagged input from Data object |
2247 |
DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData()); |
2248 |
|
2249 |
// Borrow DataTagged input from Data object |
2250 |
DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData()); |
2251 |
|
2252 |
// Prepare a DataTagged output 2 |
2253 |
res = Data(0.0, shape1, arg_1_Z.getFunctionSpace()); |
2254 |
res.tag(); // DataTagged output |
2255 |
DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData()); |
2256 |
|
2257 |
// Get the views |
2258 |
/* DataArrayView view_0 = tmp_0->getDefaultValue(); |
2259 |
DataArrayView view_1 = tmp_1->getDefaultValue(); |
2260 |
DataArrayView view_2 = tmp_2->getDefaultValue(); |
2261 |
// Get the pointers to the actual data |
2262 |
double *ptr_0 = &((view_0.getData())[0]); |
2263 |
double *ptr_1 = &((view_1.getData())[0]); |
2264 |
double *ptr_2 = &((view_2.getData())[0]);*/ |
2265 |
|
2266 |
// Get the pointers to the actual data |
2267 |
double *ptr_0 = &(tmp_0->getDefaultValue(0)); |
2268 |
double *ptr_1 = &(tmp_1->getDefaultValue(0)); |
2269 |
double *ptr_2 = &(tmp_2->getDefaultValue(0)); |
2270 |
|
2271 |
|
2272 |
// Compute a result for the default |
2273 |
tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation); |
2274 |
// Merge the tags |
2275 |
DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory |
2276 |
const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup(); |
2277 |
const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup(); |
2278 |
for (i=lookup_0.begin();i!=lookup_0.end();i++) { |
2279 |
tmp_2->addTag(i->first); // use tmp_2 to get correct shape |
2280 |
} |
2281 |
for (i=lookup_1.begin();i!=lookup_1.end();i++) { |
2282 |
tmp_2->addTag(i->first); |
2283 |
} |
2284 |
// Compute a result for each tag |
2285 |
const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup(); |
2286 |
for (i=lookup_2.begin();i!=lookup_2.end();i++) { |
2287 |
|
2288 |
/* DataArrayView view_0 = tmp_0->getDataPointByTag(i->first); |
2289 |
DataArrayView view_1 = tmp_1->getDataPointByTag(i->first); |
2290 |
DataArrayView view_2 = tmp_2->getDataPointByTag(i->first); |
2291 |
double *ptr_0 = &view_0.getData(0); |
2292 |
double *ptr_1 = &view_1.getData(0); |
2293 |
double *ptr_2 = &view_2.getData(0);*/ |
2294 |
|
2295 |
double *ptr_0 = &(tmp_0->getDataByTag(i->first,0)); |
2296 |
double *ptr_1 = &(tmp_1->getDataByTag(i->first,0)); |
2297 |
double *ptr_2 = &(tmp_2->getDataByTag(i->first,0)); |
2298 |
|
2299 |
tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation); |
2300 |
} |
2301 |
|
2302 |
} |
2303 |
else if (arg_0_Z.isTagged() && arg_1_Z.isExpanded()) { |
2304 |
|
2305 |
// After finding a common function space above the two inputs have the same numSamples and num DPPS |
2306 |
res = Data(0.0, shape1, arg_1_Z.getFunctionSpace(),true); // DataExpanded output |
2307 |
DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData()); |
2308 |
DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData()); |
2309 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
2310 |
|
2311 |
int sampleNo_0,dataPointNo_0; |
2312 |
int numSamples_0 = arg_0_Z.getNumSamples(); |
2313 |
int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample(); |
2314 |
#pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static) |
2315 |
for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) { |
2316 |
int offset_0 = tmp_0->getPointOffset(sampleNo_0,0); // They're all the same, so just use #0 |
2317 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2318 |
for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) { |
2319 |
int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0); |
2320 |
int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0); |
2321 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2322 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
2323 |
tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation); |
2324 |
} |
2325 |
} |
2326 |
|
2327 |
} |
2328 |
else if (arg_0_Z.isExpanded() && arg_1_Z.isConstant()) { |
2329 |
|
2330 |
res = Data(0.0, shape1, arg_1_Z.getFunctionSpace(),true); // DataExpanded output |
2331 |
DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData()); |
2332 |
DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData()); |
2333 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
2334 |
|
2335 |
int sampleNo_0,dataPointNo_0; |
2336 |
int numSamples_0 = arg_0_Z.getNumSamples(); |
2337 |
int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample(); |
2338 |
int offset_1 = tmp_1->getPointOffset(0,0); |
2339 |
#pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static) |
2340 |
for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) { |
2341 |
for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) { |
2342 |
int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0); |
2343 |
int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0); |
2344 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2345 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2346 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
2347 |
tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation); |
2348 |
} |
2349 |
} |
2350 |
|
2351 |
|
2352 |
} |
2353 |
else if (arg_0_Z.isExpanded() && arg_1_Z.isTagged()) { |
2354 |
|
2355 |
// After finding a common function space above the two inputs have the same numSamples and num DPPS |
2356 |
res = Data(0.0, shape1, arg_1_Z.getFunctionSpace(),true); // DataExpanded output |
2357 |
DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData()); |
2358 |
DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData()); |
2359 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
2360 |
|
2361 |
int sampleNo_0,dataPointNo_0; |
2362 |
int numSamples_0 = arg_0_Z.getNumSamples(); |
2363 |
int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample(); |
2364 |
#pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static) |
2365 |
for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) { |
2366 |
int offset_1 = tmp_1->getPointOffset(sampleNo_0,0); |
2367 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2368 |
for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) { |
2369 |
int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0); |
2370 |
int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0); |
2371 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2372 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
2373 |
tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation); |
2374 |
} |
2375 |
} |
2376 |
|
2377 |
} |
2378 |
else if (arg_0_Z.isExpanded() && arg_1_Z.isExpanded()) { |
2379 |
|
2380 |
// After finding a common function space above the two inputs have the same numSamples and num DPPS |
2381 |
res = Data(0.0, shape1, arg_1_Z.getFunctionSpace(),true); // DataExpanded output |
2382 |
DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData()); |
2383 |
DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData()); |
2384 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
2385 |
|
2386 |
int sampleNo_0,dataPointNo_0; |
2387 |
int numSamples_0 = arg_0_Z.getNumSamples(); |
2388 |
int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample(); |
2389 |
#pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static) |
2390 |
for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) { |
2391 |
for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) { |
2392 |
int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0); |
2393 |
int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0); |
2394 |
int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0); |
2395 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2396 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2397 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
2398 |
tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation); |
2399 |
} |
2400 |
} |
2401 |
|
2402 |
} |
2403 |
else { |
2404 |
throw DataException("Error - C_TensorBinaryOperation: unknown combination of inputs"); |
2405 |
} |
2406 |
|
2407 |
} else if (0 == rank1) { |
2408 |
|
2409 |
if (arg_0_Z.isConstant() && arg_1_Z.isConstant()) { |
2410 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace()); // DataConstant output |
2411 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(0)); |
2412 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(0)); |
2413 |
double *ptr_2 = &(res.getDataAtOffset(0)); |
2414 |
tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation); |
2415 |
} |
2416 |
else if (arg_0_Z.isConstant() && arg_1_Z.isTagged()) { |
2417 |
|
2418 |
// Prepare the DataConstant input |
2419 |
DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData()); |
2420 |
|
2421 |
// Borrow DataTagged input from Data object |
2422 |
DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData()); |
2423 |
|
2424 |
// Prepare a DataTagged output 2 |
2425 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace()); // DataTagged output |
2426 |
res.tag(); |
2427 |
DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData()); |
2428 |
|
2429 |
// Prepare offset into DataConstant |
2430 |
int offset_0 = tmp_0->getPointOffset(0,0); |
2431 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2432 |
// Get the views |
2433 |
/* DataArrayView view_1 = tmp_1->getDefaultValue(); |
2434 |
DataArrayView view_2 = tmp_2->getDefaultValue(); |
2435 |
// Get the pointers to the actual data |
2436 |
double *ptr_1 = &((view_1.getData())[0]); |
2437 |
double *ptr_2 = &((view_2.getData())[0]);*/ |
2438 |
//Get the pointers to the actual data |
2439 |
double *ptr_1 = &(tmp_1->getDefaultValue(0)); |
2440 |
double *ptr_2 = &(tmp_2->getDefaultValue(0)); |
2441 |
|
2442 |
// Compute a result for the default |
2443 |
tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation); |
2444 |
// Compute a result for each tag |
2445 |
const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup(); |
2446 |
DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory |
2447 |
for (i=lookup_1.begin();i!=lookup_1.end();i++) { |
2448 |
tmp_2->addTag(i->first); |
2449 |
// DataArrayView view_1 = tmp_1->getDataPointByTag(i->first); |
2450 |
// DataArrayView view_2 = tmp_2->getDataPointByTag(i->first); |
2451 |
// double *ptr_1 = &view_1.getData(0); |
2452 |
// double *ptr_2 = &view_2.getData(0); |
2453 |
double *ptr_1 = &(tmp_1->getDataByTag(i->first,0)); |
2454 |
double *ptr_2 = &(tmp_2->getDataByTag(i->first,0)); |
2455 |
|
2456 |
|
2457 |
tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation); |
2458 |
} |
2459 |
|
2460 |
} |
2461 |
else if (arg_0_Z.isConstant() && arg_1_Z.isExpanded()) { |
2462 |
|
2463 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output |
2464 |
DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData()); |
2465 |
DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData()); |
2466 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
2467 |
|
2468 |
int sampleNo_1,dataPointNo_1; |
2469 |
int numSamples_1 = arg_1_Z.getNumSamples(); |
2470 |
int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample(); |
2471 |
int offset_0 = tmp_0->getPointOffset(0,0); |
2472 |
#pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static) |
2473 |
for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) { |
2474 |
for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) { |
2475 |
int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1); |
2476 |
int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1); |
2477 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2478 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2479 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
2480 |
tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation); |
2481 |
} |
2482 |
} |
2483 |
|
2484 |
} |
2485 |
else if (arg_0_Z.isTagged() && arg_1_Z.isConstant()) { |
2486 |
|
2487 |
// Borrow DataTagged input from Data object |
2488 |
DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData()); |
2489 |
|
2490 |
// Prepare the DataConstant input |
2491 |
DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData()); |
2492 |
|
2493 |
// Prepare a DataTagged output 2 |
2494 |
res = Data(0.0, shape0, arg_0_Z.getFunctionSpace()); // DataTagged output |
2495 |
res.tag(); |
2496 |
DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData()); |
2497 |
|
2498 |
// Prepare offset into DataConstant |
2499 |
int offset_1 = tmp_1->getPointOffset(0,0); |
2500 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2501 |
// Get the views |
2502 |
// DataArrayView view_0 = tmp_0->getDefaultValue(); |
2503 |
// DataArrayView view_2 = tmp_2->getDefaultValue(); |
2504 |
// // Get the pointers to the actual data |
2505 |
// double *ptr_0 = &((view_0.getData())[0]); |
2506 |
// double *ptr_2 = &((view_2.getData())[0]); |
2507 |
// Get the pointers to the actual data |
2508 |
double *ptr_0 = &(tmp_0->getDefaultValue(0)); |
2509 |
double *ptr_2 = &(tmp_2->getDefaultValue(0)); |
2510 |
// Compute a result for the default |
2511 |
tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation); |
2512 |
// Compute a result for each tag |
2513 |
const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup(); |
2514 |
DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory |
2515 |
for (i=lookup_0.begin();i!=lookup_0.end();i++) { |
2516 |
tmp_2->addTag(i->first); |
2517 |
/* DataArrayView view_0 = tmp_0->getDataPointByTag(i->first); |
2518 |
DataArrayView view_2 = tmp_2->getDataPointByTag(i->first); |
2519 |
double *ptr_0 = &view_0.getData(0); |
2520 |
double *ptr_2 = &view_2.getData(0);*/ |
2521 |
double *ptr_0 = &(tmp_0->getDataByTag(i->first,0)); |
2522 |
double *ptr_2 = &(tmp_2->getDataByTag(i->first,0)); |
2523 |
tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation); |
2524 |
} |
2525 |
|
2526 |
} |
2527 |
else if (arg_0_Z.isTagged() && arg_1_Z.isTagged()) { |
2528 |
|
2529 |
// Borrow DataTagged input from Data object |
2530 |
DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData()); |
2531 |
|
2532 |
// Borrow DataTagged input from Data object |
2533 |
DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData()); |
2534 |
|
2535 |
// Prepare a DataTagged output 2 |
2536 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace()); |
2537 |
res.tag(); // DataTagged output |
2538 |
DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData()); |
2539 |
|
2540 |
// Get the views |
2541 |
// DataArrayView view_0 = tmp_0->getDefaultValue(); |
2542 |
// DataArrayView view_1 = tmp_1->getDefaultValue(); |
2543 |
// DataArrayView view_2 = tmp_2->getDefaultValue(); |
2544 |
// // Get the pointers to the actual data |
2545 |
// double *ptr_0 = &((view_0.getData())[0]); |
2546 |
// double *ptr_1 = &((view_1.getData())[0]); |
2547 |
// double *ptr_2 = &((view_2.getData())[0]); |
2548 |
|
2549 |
// Get the pointers to the actual data |
2550 |
double *ptr_0 = &(tmp_0->getDefaultValue(0)); |
2551 |
double *ptr_1 = &(tmp_1->getDefaultValue(0)); |
2552 |
double *ptr_2 = &(tmp_2->getDefaultValue(0)); |
2553 |
|
2554 |
// Compute a result for the default |
2555 |
tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation); |
2556 |
// Merge the tags |
2557 |
DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory |
2558 |
const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup(); |
2559 |
const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup(); |
2560 |
for (i=lookup_0.begin();i!=lookup_0.end();i++) { |
2561 |
tmp_2->addTag(i->first); // use tmp_2 to get correct shape |
2562 |
} |
2563 |
for (i=lookup_1.begin();i!=lookup_1.end();i++) { |
2564 |
tmp_2->addTag(i->first); |
2565 |
} |
2566 |
// Compute a result for each tag |
2567 |
const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup(); |
2568 |
for (i=lookup_2.begin();i!=lookup_2.end();i++) { |
2569 |
// DataArrayView view_0 = tmp_0->getDataPointByTag(i->first); |
2570 |
// DataArrayView view_1 = tmp_1->getDataPointByTag(i->first); |
2571 |
// DataArrayView view_2 = tmp_2->getDataPointByTag(i->first); |
2572 |
// double *ptr_0 = &view_0.getData(0); |
2573 |
// double *ptr_1 = &view_1.getData(0); |
2574 |
// double *ptr_2 = &view_2.getData(0); |
2575 |
|
2576 |
double *ptr_0 = &(tmp_0->getDataByTag(i->first,0)); |
2577 |
double *ptr_1 = &(tmp_1->getDataByTag(i->first,0)); |
2578 |
double *ptr_2 = &(tmp_2->getDataByTag(i->first,0)); |
2579 |
tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation); |
2580 |
} |
2581 |
|
2582 |
} |
2583 |
else if (arg_0_Z.isTagged() && arg_1_Z.isExpanded()) { |
2584 |
|
2585 |
// After finding a common function space above the two inputs have the same numSamples and num DPPS |
2586 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output |
2587 |
DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData()); |
2588 |
DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData()); |
2589 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
2590 |
|
2591 |
int sampleNo_0,dataPointNo_0; |
2592 |
int numSamples_0 = arg_0_Z.getNumSamples(); |
2593 |
int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample(); |
2594 |
#pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static) |
2595 |
for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) { |
2596 |
int offset_0 = tmp_0->getPointOffset(sampleNo_0,0); // They're all the same, so just use #0 |
2597 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2598 |
for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) { |
2599 |
int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0); |
2600 |
int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0); |
2601 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2602 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
2603 |
tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation); |
2604 |
} |
2605 |
} |
2606 |
|
2607 |
} |
2608 |
else if (arg_0_Z.isExpanded() && arg_1_Z.isConstant()) { |
2609 |
|
2610 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output |
2611 |
DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData()); |
2612 |
DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData()); |
2613 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
2614 |
|
2615 |
int sampleNo_0,dataPointNo_0; |
2616 |
int numSamples_0 = arg_0_Z.getNumSamples(); |
2617 |
int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample(); |
2618 |
int offset_1 = tmp_1->getPointOffset(0,0); |
2619 |
#pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static) |
2620 |
for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) { |
2621 |
for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) { |
2622 |
int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0); |
2623 |
int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0); |
2624 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2625 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2626 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
2627 |
tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation); |
2628 |
} |
2629 |
} |
2630 |
|
2631 |
|
2632 |
} |
2633 |
else if (arg_0_Z.isExpanded() && arg_1_Z.isTagged()) { |
2634 |
|
2635 |
// After finding a common function space above the two inputs have the same numSamples and num DPPS |
2636 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output |
2637 |
DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData()); |
2638 |
DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData()); |
2639 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
2640 |
|
2641 |
int sampleNo_0,dataPointNo_0; |
2642 |
int numSamples_0 = arg_0_Z.getNumSamples(); |
2643 |
int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample(); |
2644 |
#pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static) |
2645 |
for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) { |
2646 |
int offset_1 = tmp_1->getPointOffset(sampleNo_0,0); |
2647 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2648 |
for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) { |
2649 |
int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0); |
2650 |
int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0); |
2651 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2652 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
2653 |
tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation); |
2654 |
} |
2655 |
} |
2656 |
|
2657 |
} |
2658 |
else if (arg_0_Z.isExpanded() && arg_1_Z.isExpanded()) { |
2659 |
|
2660 |
// After finding a common function space above the two inputs have the same numSamples and num DPPS |
2661 |
res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output |
2662 |
DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData()); |
2663 |
DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData()); |
2664 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
2665 |
|
2666 |
int sampleNo_0,dataPointNo_0; |
2667 |
int numSamples_0 = arg_0_Z.getNumSamples(); |
2668 |
int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample(); |
2669 |
#pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static) |
2670 |
for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) { |
2671 |
for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) { |
2672 |
int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0); |
2673 |
int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0); |
2674 |
int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0); |
2675 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2676 |
double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1)); |
2677 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
2678 |
tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation); |
2679 |
} |
2680 |
} |
2681 |
|
2682 |
} |
2683 |
else { |
2684 |
throw DataException("Error - C_TensorBinaryOperation: unknown combination of inputs"); |
2685 |
} |
2686 |
|
2687 |
} else { |
2688 |
throw DataException("Error - C_TensorBinaryOperation: arguments have incompatible shapes"); |
2689 |
} |
2690 |
|
2691 |
return res; |
2692 |
} |
2693 |
|
2694 |
template <typename UnaryFunction> |
2695 |
Data |
2696 |
C_TensorUnaryOperation(Data const &arg_0, |
2697 |
UnaryFunction operation) |
2698 |
{ |
2699 |
if (arg_0.isEmpty()) // do this before we attempt to interpolate |
2700 |
{ |
2701 |
throw DataException("Error - Operations not permitted on instances of DataEmpty."); |
2702 |
} |
2703 |
|
2704 |
// Interpolate if necessary and find an appropriate function space |
2705 |
Data arg_0_Z = Data(arg_0); |
2706 |
|
2707 |
// Get rank and shape of inputs |
2708 |
// int rank0 = arg_0_Z.getDataPointRank(); |
2709 |
const DataTypes::ShapeType& shape0 = arg_0_Z.getDataPointShape(); |
2710 |
int size0 = arg_0_Z.getDataPointSize(); |
2711 |
|
2712 |
// Declare output Data object |
2713 |
Data res; |
2714 |
|
2715 |
if (arg_0_Z.isConstant()) { |
2716 |
res = Data(0.0, shape0, arg_0_Z.getFunctionSpace()); // DataConstant output |
2717 |
// double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]); |
2718 |
// double *ptr_2 = &((res.getPointDataView().getData())[0]); |
2719 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(0)); |
2720 |
double *ptr_2 = &(res.getDataAtOffset(0)); |
2721 |
tensor_unary_operation(size0, ptr_0, ptr_2, operation); |
2722 |
} |
2723 |
else if (arg_0_Z.isTagged()) { |
2724 |
|
2725 |
// Borrow DataTagged input from Data object |
2726 |
DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData()); |
2727 |
|
2728 |
// Prepare a DataTagged output 2 |
2729 |
res = Data(0.0, shape0, arg_0_Z.getFunctionSpace()); // DataTagged output |
2730 |
res.tag(); |
2731 |
DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData()); |
2732 |
|
2733 |
// // Get the views |
2734 |
// DataArrayView view_0 = tmp_0->getDefaultValue(); |
2735 |
// DataArrayView view_2 = tmp_2->getDefaultValue(); |
2736 |
// // Get the pointers to the actual data |
2737 |
// double *ptr_0 = &((view_0.getData())[0]); |
2738 |
// double *ptr_2 = &((view_2.getData())[0]); |
2739 |
// Get the pointers to the actual data |
2740 |
double *ptr_0 = &(tmp_0->getDefaultValue(0)); |
2741 |
double *ptr_2 = &(tmp_2->getDefaultValue(0)); |
2742 |
// Compute a result for the default |
2743 |
tensor_unary_operation(size0, ptr_0, ptr_2, operation); |
2744 |
// Compute a result for each tag |
2745 |
const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup(); |
2746 |
DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory |
2747 |
for (i=lookup_0.begin();i!=lookup_0.end();i++) { |
2748 |
tmp_2->addTag(i->first); |
2749 |
// DataArrayView view_0 = tmp_0->getDataPointByTag(i->first); |
2750 |
// DataArrayView view_2 = tmp_2->getDataPointByTag(i->first); |
2751 |
// double *ptr_0 = &view_0.getData(0); |
2752 |
// double *ptr_2 = &view_2.getData(0); |
2753 |
double *ptr_0 = &(tmp_0->getDataByTag(i->first,0)); |
2754 |
double *ptr_2 = &(tmp_2->getDataByTag(i->first,0)); |
2755 |
tensor_unary_operation(size0, ptr_0, ptr_2, operation); |
2756 |
} |
2757 |
|
2758 |
} |
2759 |
else if (arg_0_Z.isExpanded()) { |
2760 |
|
2761 |
res = Data(0.0, shape0, arg_0_Z.getFunctionSpace(),true); // DataExpanded output |
2762 |
DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData()); |
2763 |
DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData()); |
2764 |
|
2765 |
int sampleNo_0,dataPointNo_0; |
2766 |
int numSamples_0 = arg_0_Z.getNumSamples(); |
2767 |
int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample(); |
2768 |
#pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static) |
2769 |
for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) { |
2770 |
for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) { |
2771 |
// int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0); |
2772 |
// int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0); |
2773 |
// double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]); |
2774 |
// double *ptr_2 = &((res.getPointDataView().getData())[offset_2]); |
2775 |
int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0); |
2776 |
int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0); |
2777 |
double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0)); |
2778 |
double *ptr_2 = &(res.getDataAtOffset(offset_2)); |
2779 |
tensor_unary_operation(size0, ptr_0, ptr_2, operation); |
2780 |
} |
2781 |
} |
2782 |
} |
2783 |
else { |
2784 |
throw DataException("Error - C_TensorUnaryOperation: unknown combination of inputs"); |
2785 |
} |
2786 |
|
2787 |
return res; |
2788 |
} |
2789 |
|
2790 |
} |
2791 |
#endif |