C++ object::attr方法代码示例

boost::python::object NotepadPlusWrapper::prompt(boost::python::object promptObj, boost::python::object title, boost::python::object initial)
{
	PromptDialog promptDlg(m_hInst, m_nppHandle);
	const char *cPrompt = NULL;
	const char *cTitle = NULL;
	const char *cInitial = NULL;
	if (!promptObj | !promptObj.is_none())
		cPrompt = (const char *)boost::python::extract<const char *>(promptObj.attr("__str__")());
	if (!title | !title.is_none())
		cTitle= (const char *)boost::python::extract<const char *>(title.attr("__str__")());

	if (!initial | !initial.is_none())
		cInitial = (const char *)boost::python::extract<const char *>(initial.attr("__str__")());

	PromptDialog::PROMPT_RESULT result;
	GILRelease release;
	result = promptDlg.showPrompt(cPrompt, cTitle, cInitial);

    release.reacquire();
	if (PromptDialog::RESULT_OK == result)
	{
		return boost::python::str(promptDlg.getText());
	}
	else
	{
		return boost::python::object();
	}

}

    void update(boost::python::object source)
    {
        // See if we have a dictionary-like object.
        if (py_hasattr(source, "items"))
        {
            return this->update(source.attr("items")());
        }
        if (!py_hasattr(source, "__iter__")) {
            THROW_EX(ValueError, "Must provide a dictionary-like object to update()");
        }

        object iter = source.attr("__iter__")();
        while (true) {
            PyObject *pyobj = PyIter_Next(iter.ptr());
            if (!pyobj) break;
            if (PyErr_Occurred()) {
                throw_error_already_set();
            }

            object obj = object(handle<>(pyobj));

            tuple tup = extract<tuple>(obj);
            std::string attr = extract<std::string>(tup[0]);
            std::string value = extract<std::string>(tup[1]);
            setitem(attr, value);
        }
    }

/** Converts a one-dimensional numpy vector to eigen VectorXd. */
Eigen::VectorXd fromNumpyVector(py::object vec) {
	assert(("Input numpy matrix is not one dimensional.", py::extract<int>(vec.attr("ndim"))==1));
	vec = np_mod.attr("array")(vec, "float64");
	int size = py::extract<int>(vec.attr("size"));

	double* vec_data = getPointer<double>(vec);
	return Eigen::Map<Eigen::VectorXd>(vec_data, size);
}

static Eigen::MatrixXd fromNP(py::object arr) {
  arr = np_mod.attr("array")(arr, "float64");
  int rows = py::extract<int>(arr.attr("shape")[0]);
  int cols = py::extract<int>(arr.attr("shape")[1]);
  Eigen::MatrixXd mat(rows, cols);
  double* p = getPointer<double>(arr);
  memcpy(&mat(0,0), p,  rows*cols*sizeof(double));
  return mat;
}

 static void from2dArray(PointCloudT* cloud, py::object arr) {
   arr = np_mod.attr("array")(arr, "float32");
   int npoints = py::extract<int>(arr.attr("shape")[0]);
   int floatfields = py::extract<int>(arr.attr("shape")[1]);
   FAIL_IF_FALSE(floatfields == sizeof(T)/4);
   cloud->resize(npoints);
   float* p = getPointer<float>(arr);
   memcpy(&cloud->points[0], p,  npoints*floatfields*sizeof(float));
 }

/** Converts a two-dimensional numpy matrix to eigen MatrixXd. */
Eigen::MatrixXd fromNumpy(py::object mat) {
	assert(("Input numpy matrix is not two dimensional.", py::extract<int>(mat.attr("ndim"))==2));
	mat = np_mod.attr("array")(mat, "float64");
	int rows = py::extract<int>(mat.attr("shape")[0]);
	int cols = py::extract<int>(mat.attr("shape")[1]);

	double* mat_data = getPointer<double>(mat);
	return Eigen::Map<Eigen::MatrixXd>(mat_data, rows, cols);
}

 static void from3dArray(PointCloudT* cloud, py::object arr) {
   arr = np_mod.attr("array")(arr, "float32");
   int height = py::extract<int>(arr.attr("shape")[0]);
   int width = py::extract<int>(arr.attr("shape")[1]);
   int floatfields = py::extract<int>(arr.attr("shape")[2]);
   FAIL_IF_FALSE(floatfields==sizeof(T)/4);
   cloud->resize(width*height);
   cloud->height = height;
   cloud->width = width;
   float* p = getPointer<float>(arr);
   memcpy(&cloud->points[0], p,  width*height*floatfields*sizeof(float));
 }

	/** Constructor. dtype_name determines type of matrices created. */
	numpy_converter( const char * dtype_name = "float64" )
	{
		PyObject* module = ::PyImport_Import( boost::python::object( "numpy" ).ptr() );
		if( ! module  )
		{
			throw std::logic_error( "Could not import numpy" );
		}
		numpy = boost::python::object( boost::python::handle<>( module ) );
		array_type = numpy.attr( "ndarray" );
		array_function = numpy.attr( "array" );
		set_dtype( dtype_name );
	}

 static
 void
 setstate(boost::python::object w_obj, boost::python::tuple state)
 {
     using namespace boost::python;
     world& w = extract<world&>(w_obj)();
     
     if (len(state) != 2)
     {
       PyErr_SetObject(PyExc_ValueError,
                       ("expected 2-item tuple in call to __setstate__; got %s"
                        % state).ptr()
           );
       throw_error_already_set();
     }
     
     // restore the object's __dict__
     dict d = extract<dict>(w_obj.attr("__dict__"))();
     d.update(state[0]);
     
     // restore the internal state of the C++ object
     long number = extract<long>(state[1]);
     if (number != 42)
         w.set_secret_number(number);
 }

// REVIEW: the poolSize can be pulled from the numeric array
RDKit::INT_VECT MaxMinPicks(MaxMinPicker *picker, python::object distMat,
                            int poolSize, int pickSize,
                            python::object firstPicks, int seed) {
  if (pickSize >= poolSize) {
    throw ValueErrorException("pickSize must be less than poolSize");
  }

  if (!PyArray_Check(distMat.ptr())) {
    throw ValueErrorException("distance mat argument must be a numpy matrix");
  }

  PyArrayObject *copy;
  copy = (PyArrayObject *)PyArray_ContiguousFromObject(distMat.ptr(),
                                                       PyArray_DOUBLE, 1, 1);
  double *dMat = (double *)copy->data;

  RDKit::INT_VECT firstPickVect;
  for (unsigned int i = 0;
       i < python::extract<unsigned int>(firstPicks.attr("__len__")()); ++i) {
    firstPickVect.push_back(python::extract<int>(firstPicks[i]));
  }
  RDKit::INT_VECT res =
      picker->pick(dMat, poolSize, pickSize, firstPickVect, seed);
  Py_DECREF(copy);
  return res;
}

T
read_or_default(const boost::python::object &o,
                const char *key,
                T default_value)
{
  // Remember AttributeError for later comparison
  //     boost::python::object attributeError =
  //     boost::python::import("AttributeError");
  try
  {
    const boost::python::object &o2 = o.attr(key);

    boost::python::extract< T > extractor(o2);
    if (extractor.check())
    {
      return extractor;
    }
    else
    {
      return default_value;
    }
  } catch (const boost::python::error_already_set &)
  {
    // https://misspent.wordpress.com/2009/10/11/
    // boost-python-and-handling-python-exceptions/
    PyObject *e, *v, *t;
    PyErr_Fetch(&e, &v, &t);

    return default_value;
  }

  return default_value;
}

void SystemMatrix::setToSolution(escript::Data& out, escript::Data& in,
                                 boost::python::object& options) const
{
    if (in.isComplex() || out.isComplex())
    {
        throw PasoException("SystemMatrix::setToSolution: complex arguments not supported.");
    }
    options.attr("resetDiagnostics")();
    Options paso_options(options);
    if (out.getDataPointSize() != getColumnBlockSize()) {
        throw PasoException("solve: column block size does not match the number of components of solution.");
    } else if (in.getDataPointSize() != getRowBlockSize()) {
        throw PasoException("solve: row block size does not match the number of components of  right hand side.");
    } else if (out.getFunctionSpace() != getColumnFunctionSpace()) {
        throw PasoException("solve: column function space and function space of solution don't match.");
    } else if (in.getFunctionSpace() != getRowFunctionSpace()) {
        throw PasoException("solve: row function space and function space of right hand side don't match.");
    }
    out.expand();
    in.expand();
    out.requireWrite();
    in.requireWrite();
    double* out_dp = out.getExpandedVectorReference(static_cast<escript::DataTypes::real_t>(0)).data();        
    double* in_dp = in.getExpandedVectorReference(static_cast<escript::DataTypes::real_t>(0)).data();                
    solve(out_dp, in_dp, &paso_options);
    paso_options.updateEscriptDiagnostics(options);
}

void fill_alpha3D_complex(bp::object points, bp::object complex)
{
    typedef     std::map<AlphaSimplex3D::Vertex, unsigned>      ASPointMap;

    Delaunay3D  Dt;
    ASPointMap  point_map;
    unsigned i = 0;
    for (bp::stl_input_iterator<bp::list> pt = points; pt != bp::stl_input_iterator<bp::list>(); ++pt)
    {
        double x = bp::extract<double>((*pt)[0]);
        double y = bp::extract<double>((*pt)[1]);
        double z = bp::extract<double>((*pt)[2]);
        point_map[Dt.insert(Point(x,y,z))] = i++;
    }

    AlphaSimplex3D::SimplexSet simplices;
    fill_simplex_set(Dt, simplices);

    for (AlphaSimplex3D::SimplexSet::const_iterator cur = simplices.begin(); cur != simplices.end(); ++cur)
    {
        
        dp::SimplexVD s;
        for (AlphaSimplex3D::VertexContainer::const_iterator vcur  = cur->vertices().begin(); 
                                                             vcur != cur->vertices().end(); ++vcur)
            s.add(point_map[*vcur]);
        
        s.data() = bp::object(std::make_pair(cur->value(), !cur->attached()));      // regular/critical rather than attached
        complex.attr("append")(s);
    }
}

 boost::python::object call_(const char* name,Args... args){
     using namespace boost::python;
     try {
         return context_.attr(name)(args...);
     }
     catch(error_already_set const &){
         PyObject *type,*value,*traceback;
         PyErr_Fetch(&type,&value,&traceback);
         // Construct a message
         std::string message;
         if(value){
             extract<std::string> value_string(value);
             // Check a string can be extracted from the PyObject
             if(value_string.check()){
                 message += value_string() +":\n";
             }
         }
         // There may not be a traceback (e.g. if a syntax error)
         if(value and traceback){
             handle<> type_handle(type);
             handle<> value_handle(allow_null(value));
             handle<> traceback_handle(allow_null(traceback));
             object formatted_list = import("traceback").attr("format_exception")(type_handle,value_handle,traceback_handle);
             for(int i=0;i<len(formatted_list);i++){
                 extract<std::string> line_string(formatted_list[i]);
                 // Check a string can be extracted from the PyObject
                 if(line_string.check()){
                     message += line_string();
                 }
             }
         }
         throw PythonException(message);
     }
 }

		static void	toCPP(boost::python::object o, ImmutableTreeMap<T1, T2>& outT)
			{
			outT = ImmutableTreeMap<T1, T2>();

			boost::python::object it = o.attr("__iter__")();

			while(1)
				{
				T1 t1;
				T2 t2;
				
				boost::python::object key;
				try {
					key = it.attr("next")();
					}
				catch(...)
					{
					PyErr_Clear();
					return;
					}

				Converter<T1>::toCPP(key, t1);
				Converter<T2>::toCPP(o[key], t2);
				
				outT = outT + make_pair(t1, t2);
				}
			}