annotate PyTypeConversions.h @ 71:40a01bb24209 vampyhost

Pull apart some type conversion classes for possible use in VamPy Host

/* -*- c-basic-offset: 8 indent-tabs-mode: t -*- */
/*

 * Vampy : This plugin is a wrapper around the Vamp plugin API.
 * It allows for writing Vamp plugins in Python.

 * Centre for Digital Music, Queen Mary University of London.
 * Copyright (C) 2008-2009 Gyorgy Fazekas, QMUL. (See Vamp sources 
 * for licence information.)

*/

/*
PyTypeConversions: Type safe conversion utilities between Python types 
and basic C/C++ types.
*/

#ifndef _PY_TYPE_CONVERSIONS_H_
#define _PY_TYPE_CONVERSIONS_H_
#include <Python.h>
#ifdef HAVE_NUMPY
#define PY_ARRAY_UNIQUE_SYMBOL VAMPY_ARRAY_API
#define NO_IMPORT_ARRAY
#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
#include "numpy/arrayobject.h"
#endif

#include <vector>
#include <queue>
#include <string>
#include <sstream>
#include <iostream>

using std::cerr;
using std::endl;

#ifdef HAVE_NUMPY
enum eArrayDataType {
	dtype_float32 = (int) NPY_FLOAT,
	dtype_complex64 = (int) NPY_CFLOAT 
	};
#endif 

/* C++ mapping of PyNone Type */
struct NoneType {};
	
// Data
class ValueError
{
public:
	ValueError() {}
	ValueError(std::string m, bool s) : message(m),strict(s) {}
	std::string location;
	std::string message;
	bool strict;
	std::string str() const { 
		return (location.empty()) ? message : message + "\nLocation: " + location;}
	void print() const { cerr << str() << endl; }
	template<typename V> ValueError &operator<< (const V& v)
	{
		std::ostringstream ss;
		ss << v;
		location += ss.str();
		return *this;
	}
};

class PyTypeConversions
{
public:
	PyTypeConversions();
	~PyTypeConversions();
	
	// Utilities
	void setStrictTypingFlag(bool b) {m_strict = b;}
	void setNumpyInstalled(bool b) {m_numpyInstalled = b;}
	ValueError getError() const;
	std::string PyValue_Get_TypeName(PyObject*) const;

	// Basic type conversion: Python to C++ 
	float 	PyValue_To_Float(PyObject*) const;
	size_t 	PyValue_To_Size_t(PyObject*) const;
	bool 	PyValue_To_Bool(PyObject*) const;
	std::string PyValue_To_String(PyObject*) const;
	long 	PyValue_To_Long(PyObject*) const;
	// int 	PyValue_To_Int(PyObject* pyValue) const;
	
	// C++ to Python
	PyObject *PyValue_From_CValue(const char*) const;
	PyObject *PyValue_From_CValue(const std::string& x) const { return PyValue_From_CValue(x.c_str()); }
	PyObject *PyValue_From_CValue(size_t) const;
	PyObject *PyValue_From_CValue(double) const;
	PyObject *PyValue_From_CValue(float x) const { return PyValue_From_CValue((double)x); }
	PyObject *PyValue_From_CValue(bool) const;
	
	// Sequence types
	std::vector<std::string> PyValue_To_StringVector (PyObject*) const;
	std::vector<float> PyValue_To_FloatVector (PyObject*) const;
	std::vector<float> PyList_To_FloatVector (PyObject*) const;

	// Numpy types
#ifdef HAVE_NUMPY
	std::vector<float> PyArray_To_FloatVector (PyObject *pyValue) const;
#endif

	/// Convert DTYPE type 1D NumpyArray to std::vector<RET>
	template<typename RET, typename DTYPE>
	std::vector<RET> PyArray_Convert(void* raw_data_ptr, long length, size_t strides) const
	{
		std::vector<RET> rValue;
		
		/// check if the array is continuous, if not use strides info
		if (sizeof(DTYPE)!=strides) {
#ifdef _DEBUG_VALUES
			cerr << "Warning: discontinuous numpy array. Strides: " << strides << " bytes. sizeof(dtype): " << sizeof(DTYPE) << endl;
#endif
			char* data = (char*) raw_data_ptr;
			for (long i = 0; i<length; ++i){
				rValue.push_back((RET)(*((DTYPE*)data)));
#ifdef _DEBUG_VALUES
				cerr << "value: " << (RET)(*((DTYPE*)data)) << endl;
#endif				
				data+=strides;
			}
			return rValue;
		}

		DTYPE* data = (DTYPE*) raw_data_ptr;
		for (long i = 0; i<length; ++i){
#ifdef _DEBUG_VALUES
			cerr << "value: " << (RET)data[i] << endl;
#endif
			rValue.push_back((RET)data[i]);
		}
		return rValue;
	}

	/// this is a special case. numpy.float64 has an array conversions but no array descriptor
	inline std::vector<float> PyArray0D_Convert(PyArrayInterface *ai) const
	{
		std::vector<float> rValue;
		if ((ai->typekind) == *"f") 
			rValue.push_back((float)*(double*)(ai->data));
		else { 
			setValueError("Unsupported NumPy data type.",m_strict); 
			return rValue;
		}
#ifdef _DEBUG_VALUES
		cerr << "value: " << rValue[0] << endl;
#endif
		return rValue;
	}

private:
	bool m_strict;
	mutable bool m_error;
	mutable std::queue<ValueError> m_errorQueue;
	bool m_numpyInstalled;
	
	void setValueError(std::string,bool) const;
	ValueError& lastError() const;

public:
	const bool& error;

};

#endif