目录
QuantLib 金融计算——自己动手封装 Python 接口（1）
概述
QuantLib 已经开始在 PyPi 上发布封装好的 Python 接口，安装和使用非常方便，与普通的包别无二致。并且更新及时，保持对应最新版本的 QuantLib。
官方发布的 Python 接口，其优点是广度和全面，缺点是深度不足。有时候用户需要的功能恰好没有被封装（《收益率曲线之构建曲线（3）》一文中曾经提到过），希望重新封装接口，添加自己需要的功能；亦或是用户已经在 C++ 源代码层面上扩展或修复了 QuantLib，希望包装扩展的新功能，并与官方的 Python 接口联合使用。
无论是上述哪种情况，都需要用户自己动手封装 Python 接口。
QuantLib 如何封装 Python 接口？
QuantLib 使用 swig 来封装 Python 接口（其他语言的接口也是用 swig 封装的），所以，要动手封装自己的 Python 接口需要了解一点 swig 的用法（看这里，或这里）。
swig 封装 C++ 的流程大体如下：
- 编写若干“接口文件”（文件扩展名是
.i），告知 swig 如何封装 C++ 源代码； - 在接口文件上运行 swig 命令，这会产生一个
.py文件（描述封装好的 Python 接口，包含了若干函数或类的定义），以及一个.cpp文件（接口背后的计算引擎将由该文件生成）； - 编写并运行
setup.py，这将编译.cpp文件，并将编译得到的.so文件（动态库）与.py文件绑定起来，贯通表面的 Python 接口和背后的 C++ 计算引擎； - 最终得到一个 Python 包（将包含在系统目录）。
不同版本 QuantLib 的 swig 接口文件可以在这里获得。所有接口文件可以分为三部分：
quantlib.i是最顶端的接口文件，swig 将依据此文件生成接口代码（.py和.cpp）；ql.i是中间层文件，用来汇集其他接口文件；bonds.i、date.i等等是封装具体接口的文件。
自己封装 Python 接口
了解一点 swig 的原理之后会发现，swig 在封装好的 Python 接口背后隐藏了一个个真实的 C++ 对象，实际的计算任务、类型检查和异常处理等等其实是委托给这些 C++ 对象。
因此可以猜测，将同一段 C++ 代码封装成两个不同的 Python 接口，这两个接口应该可以混用，因为这仅仅是“同一个人穿了不同的衣服”。
下面用实验验证这种想法。
封装 Array 和 Matrix 类
以 QuantLib 中的两个类 Array 和 Matrix 为例，将它们独立出来，封装成名为 QuantLibEx 的包。具体的接口文件没有必要自己写，直接沿用官方发布的版本（我的名言：学习，从模仿开始）。
在官方发布的 swig 接口文件中，Array 和 Matrix 对应的文件是 linearalgebra.i，该文件同时包含（%include）了 common.i 和 types.i 两个文件。
将上述三个文件连同 quantlib.i（重命名为 quantlibex.i）和 ql.i 独立出来，删除掉一些和封装 Python 接口无关的代码，作为构建 QuantLibEx 的接口文件。
在包含这五个接口文件的目录下创建一个 QuantLibEx 目录，然后运行 swig 命令，生成必需的 .py 和 .cpp 文件：
swig -c++ -python -outdir QuantLibEx -o QuantLibEx/qlx_wrap.cpp quantlibex.i
QuantLibEx 目录下将出现两个文件：QuantLibEx.py 和 qlx_wrap.cpp。为了使 QuantLibEx 成为一个 Python 包，需要添加一个 __init__.py 文件（内容见附录）。
QuantLibEx.py 和 qlx_wrap.cpp 准备就绪之后就可以运行事先编写好的 setup.py 文件（内容见附录），编译 .cpp 文件，并打包进 Python 的系统目录。
首先，构建（build 命令）QuantLibEx 包：
python3 setup.py build
running build
running build_py
creating build
creating build/lib.linux-x86_64-3.6
creating build/lib.linux-x86_64-3.6/QuantLibEx
copying QuantLibEx/__init__.py -> build/lib.linux-x86_64-3.6/QuantLibEx
copying QuantLibEx/QuantLibEx.py -> build/lib.linux-x86_64-3.6/QuantLibEx
running build_ext
building \'QuantLibEx._QuantLibEx\' extension
creating build/temp.linux-x86_64-3.6
creating build/temp.linux-x86_64-3.6/QuantLibEx
x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/ql -I/usr/include/python3.6m -c QuantLibEx/qlx_wrap.cpp -o build/temp.linux-x86_64-3.6/QuantLibEx/qlx_wrap.o
x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/QuantLibEx/qlx_wrap.o -L/usr/lib/ -lQuantLib -o build/lib.linux-x86_64-3.6/QuantLibEx/_QuantLibEx.cpython-36m-x86_64-linux-gnu.so
构建成功之后会出现一个 build 目录，里面包含了若干文件，包括已经构建好的 QuantLibEx 包。然后，进入安装（install 命令）环节，打包进 Python 的系统目录（需要 sudo 权限）。
sudo python3 setup.py install
running install
running build
running build_py
running build_ext
running install_lib
copying build/lib.linux-x86_64-3.6/QuantLibEx/QuantLibEx.py -> /usr/local/lib/python3.6/dist-packages/QuantLibEx
copying build/lib.linux-x86_64-3.6/QuantLibEx/_QuantLibEx.cpython-36m-x86_64-linux-gnu.so -> /usr/local/lib/python3.6/dist-packages/QuantLibEx
byte-compiling /usr/local/lib/python3.6/dist-packages/QuantLibEx/QuantLibEx.py to QuantLibEx.cpython-36.pyc
running install_egg_info
Writing /usr/local/lib/python3.6/dist-packages/QuantLibEx-0.1.egg-info
运行 pip3 list 就可以看到 QuantLibEx 了。
...
QuantLib 1.17
QuantLibEx 0.1
...
QuantLibEx 和官方包混合使用
下面简单验证一下 QuantLibEx（基于 QuantLib-1.15）和官方包（基于 QuantLib-1.17）是否可以混合使用：
import QuantLib as ql
import QuantLibEx as qlx
array = ql.Array(5,0.2)
print(type(array))
print(array)
arrayX = qlx.Array(5,0.3)
print(type(arrayX))
print(arrayX)
print(array + arrayX)
<class \'QuantLib.QuantLib.Array\'>
[ 0.2; 0.2; 0.2; 0.2; 0.2 ]
<class \'QuantLibEx.QuantLibEx.Array\'>
[ 0.3; 0.3; 0.3; 0.3; 0.3 ]
[ 0.5; 0.5; 0.5; 0.5; 0.5 ]
更复杂一点的例子——二维插值：
xVec = [float(i) for i in range(10)]
yVec = [float(i) for i in range(10)]
m = ql.Matrix(len(xVec), len(yVec))
mX = qlx.Matrix(len(xVec), len(yVec))
for rowIt in range(len(xVec)):
for colIt in range(len(yVec)):
m[rowIt][colIt] = scipy.sin(xVec[rowIt]) + scipy.sin(yVec[colIt])
mX[rowIt][colIt] = scipy.sin(xVec[rowIt]) + scipy.sin(yVec[colIt])
print(type(m))
print(m)
print(type(mX))
print(mX)
bicubIntp = ql.BicubicSpline(
xVec, yVec, m)
bicubIntpX = ql.BicubicSpline(
xVec, yVec, mX)
x = 0.5
y = 4.5
print("Analytical Value: ", scipy.sin(x) + scipy.sin(y))
print("Bicubic Value(base on ql): ", bicubIntp(x, y))
print("Bicubic Value(base on qlx): ", bicubIntpX(x, y))
<class \'QuantLib.QuantLib.Matrix\'>
| 0 0.841471 0.909297 0.14112 -0.756802 -0.958924 -0.279415 0.656987 0.989358 0.412118 |
| 0.841471 1.68294 1.75077 0.982591 0.0846685 -0.117453 0.562055 1.49846 1.83083 1.25359 |
| 0.909297 1.75077 1.81859 1.05042 0.152495 -0.0496268 0.629882 1.56628 1.89866 1.32142 |
| 0.14112 0.982591 1.05042 0.28224 -0.615682 -0.817804 -0.138295 0.798107 1.13048 0.553238 |
| -0.756802 0.0846685 0.152495 -0.615682 -1.5136 -1.71573 -1.03622 -0.0998159 0.232556 -0.344684 |
| -0.958924 -0.117453 -0.0496268 -0.817804 -1.71573 -1.91785 -1.23834 -0.301938 0.030434 -0.546806 |
| -0.279415 0.562055 0.629882 -0.138295 -1.03622 -1.23834 -0.558831 0.377571 0.709943 0.132703 |
| 0.656987 1.49846 1.56628 0.798107 -0.0998159 -0.301938 0.377571 1.31397 1.64634 1.06911 |
| 0.989358 1.83083 1.89866 1.13048 0.232556 0.030434 0.709943 1.64634 1.97872 1.40148 |
| 0.412118 1.25359 1.32142 0.553238 -0.344684 -0.546806 0.132703 1.06911 1.40148 0.824237 |
<class \'QuantLibEx.QuantLibEx.Matrix\'>
| 0 0.841471 0.909297 0.14112 -0.756802 -0.958924 -0.279415 0.656987 0.989358 0.412118 |
| 0.841471 1.68294 1.75077 0.982591 0.0846685 -0.117453 0.562055 1.49846 1.83083 1.25359 |
| 0.909297 1.75077 1.81859 1.05042 0.152495 -0.0496268 0.629882 1.56628 1.89866 1.32142 |
| 0.14112 0.982591 1.05042 0.28224 -0.615682 -0.817804 -0.138295 0.798107 1.13048 0.553238 |
| -0.756802 0.0846685 0.152495 -0.615682 -1.5136 -1.71573 -1.03622 -0.0998159 0.232556 -0.344684 |
| -0.958924 -0.117453 -0.0496268 -0.817804 -1.71573 -1.91785 -1.23834 -0.301938 0.030434 -0.546806 |
| -0.279415 0.562055 0.629882 -0.138295 -1.03622 -1.23834 -0.558831 0.377571 0.709943 0.132703 |
| 0.656987 1.49846 1.56628 0.798107 -0.0998159 -0.301938 0.377571 1.31397 1.64634 1.06911 |
| 0.989358 1.83083 1.89866 1.13048 0.232556 0.030434 0.709943 1.64634 1.97872 1.40148 |
| 0.412118 1.25359 1.32142 0.553238 -0.344684 -0.546806 0.132703 1.06911 1.40148 0.824237 |
Analytical Value: -0.498104579060894
Bicubic Value(base on ql): -0.49656170664824184
Bicubic Value(base on qlx): -0.49656170664824184
到目前为止，一切都能按照预期运行，自定义的封装确实能够和官方发布的包混合使用。不过，类型判定有些诡异：
b = array + arrayX
c = arrayX + array
print(type(b))
print(type(c))
<class \'QuantLibEx.QuantLibEx.Array\'>
<class \'QuantLibEx.QuantLibEx.Array\'>
为什么 b 和 c 都被判定为 QuantLibEx 中的 Array？
附录：接口文件、setup.py 和 __init__.py
quantlibex.i
%module QuantLibEx
%include exception.i
%exception {
try {
$action
} catch (std::out_of_range& e) {
SWIG_exception(SWIG_IndexError,const_cast<char*>(e.what()));
} catch (std::exception& e) {
SWIG_exception(SWIG_RuntimeError,const_cast<char*>(e.what()));
} catch (...) {
SWIG_exception(SWIG_UnknownError,"unknown error");
}
}
//#if defined(SWIGPYTHON)
%{
#include <ql/version.hpp>
const int __hexversion__ = QL_HEX_VERSION;
const char* __version__ = QL_VERSION;
%}
const int __hexversion__;
%immutable;
const char* __version__;
%mutable;
//#endif
%include ql.i
ql.i
//#if defined(SWIGPYTHON)
%{
#ifdef barrier
#undef barrier
#endif
%}
//#endif
%{
#include <ql/quantlib.hpp>
#if QL_HEX_VERSION < 0x011400f0
#error using an old version of QuantLib, please update
#endif
#ifdef BOOST_MSVC
#ifdef QL_ENABLE_THREAD_SAFE_OBSERVER_PATTERN
#define BOOST_LIB_NAME boost_thread
#include <boost/config/auto_link.hpp>
#undef BOOST_LIB_NAME
#define BOOST_LIB_NAME boost_system
#include <boost/config/auto_link.hpp>
#undef BOOST_LIB_NAME
#endif
#endif
// add here SWIG version check
%}
//#ifdef SWIGPYTHON
%{
#if PY_VERSION_HEX < 0x02010000
#error Python version 2.1.0 or later is required
#endif
%}
//#endif
// common name mappings
%include common.i
%include linearalgebra.i
%include types.i
types.i
#ifndef quantlib_types_i
#define quantlib_types_i
%include common.i
%include std_common.i
%{
using QuantLib::Integer;
using QuantLib::BigInteger;
using QuantLib::Natural;
using QuantLib::BigNatural;
using QuantLib::Real;
using QuantLib::Decimal;
using QuantLib::Time;
using QuantLib::Rate;
using QuantLib::Spread;
using QuantLib::DiscountFactor;
using QuantLib::Volatility;
using QuantLib::Probability;
using QuantLib::Size;
%}
typedef int Integer;
typedef long BigInteger;
typedef unsigned int Natural;
typedef unsigned long BigNatural;
typedef double Real;
typedef Real Decimal;
typedef Real Time;
typedef Real Rate;
typedef Real Spread;
typedef Real DiscountFactor;
typedef Real Volatility;
typedef Real Probability;
//#if defined(SWIGPYTHON)
// needed for those using SWIG 1.3.21 in order to compile with VC++6
%typecheck(SWIG_TYPECHECK_INTEGER) std::size_t {
$1 = (PyInt_Check($input) || PyLong_Check($input)) ? 1 : 0;
}
//#endif
typedef std::size_t Size;
#endif
common.i
#ifndef quantlib_common_i
#define quantlib_common_i
%include stl.i
%include exception.i
%define QL_TYPECHECK_BOOL 7210 %enddef
%{
// This is necessary to avoid compile failures on
// GCC 4
// see http://svn.boost.org/trac/boost/ticket/1793
#if defined(NDEBUG)
#define BOOST_DISABLE_ASSERTS 1
#endif
#include <boost/algorithm/string/case_conv.hpp>
%}
//#if defined(SWIGPYTHON)
%typemap(in) boost::optional<bool> %{
if($input == Py_None)
$1 = boost::none;
else if ($input == Py_True)
$1 = true;
else
$1 = false;
%}
%typecheck (QL_TYPECHECK_BOOL) boost::optional<bool> {
if (PyBool_Check($input) || Py_None == $input)
$1 = 1;
else
$1 = 0;
}
//#endif
%{
// generally useful classes
using QuantLib::Error;
using QuantLib::Handle;
using QuantLib::RelinkableHandle;
%}
namespace boost {
template <class T>
class shared_ptr {
public:
T* operator->();
//#if defined(SWIGPYTHON)
%extend {
bool __nonzero__() {
return !!(*self);
}
bool __bool__() {
return !!(*self);
}
}
//#endif
};
}
template <class T>
class Handle {
public:
Handle(const boost::shared_ptr<T>& = boost::shared_ptr<T>());
boost::shared_ptr<T> operator->();
//#if defined(SWIGPYTHON)
%extend {
bool __nonzero__() {
return !self->empty();
}
bool __bool__() {
return !self->empty();
}
}
//#endif
};
template <class T>
class RelinkableHandle : public Handle<T> {
public:
RelinkableHandle(const boost::shared_ptr<T>& = boost::shared_ptr<T>());
void linkTo(const boost::shared_ptr<T>&);
};
%define swigr_list_converter(ContainerRType,
ContainerCType, ElemCType)
%enddef
%define deprecate_feature(OldName, NewName)
//#if defined(SWIGPYTHON)
%pythoncode %{
def OldName(*args, **kwargs):
from warnings import warn
warn(\'%s is deprecated; use %s\' % (OldName.__name__, NewName.__name__))
return NewName(*args, **kwargs)
%}
//#endif
%enddef
#endif
linearalgebra.i
#ifndef quantlib_linear_algebra_i
#define quantlib_linear_algebra_i
%include common.i
%include types.i
%include stl.i
%{
using QuantLib::Array;
using QuantLib::Matrix;
%}
%define QL_TYPECHECK_ARRAY 4210 %enddef
%define QL_TYPECHECK_MATRIX 4220 %enddef
//#if defined(SWIGPYTHON)
%{
bool extractArray(PyObject* source, Array* target) {
if (PyTuple_Check(source) || PyList_Check(source)) {
Size size = (PyTuple_Check(source) ?
PyTuple_Size(source) :
PyList_Size(source));
*target = Array(size);
for (Size i=0; i<size; i++) {
PyObject* o = PySequence_GetItem(source,i);
if (PyFloat_Check(o)) {
(*target)[i] = PyFloat_AsDouble(o);
Py_DECREF(o);
} else if (PyInt_Check(o)) {
(*target)[i] = Real(PyInt_AsLong(o));
Py_DECREF(o);
} else {
Py_DECREF(o);
return false;
}
}
return true;
} else {
return false;
}
}
%}
%typemap(in) Array (Array* v) {
if (extractArray($input,&$1)) {
;
} else {
SWIG_ConvertPtr($input,(void **) &v, $&1_descriptor,1);
$1 = *v;
}
};
%typemap(in) const Array& (Array temp) {
if (extractArray($input,&temp)) {
$1 = &temp;
} else {
SWIG_ConvertPtr($input,(void **) &$1,$1_descriptor,1);
}
};
%typecheck(QL_TYPECHECK_ARRAY) Array {
/* native sequence? */
if (PyTuple_Check($input) || PyList_Check($input)) {
Size size = PySequence_Size($input);
if (size == 0) {
$1 = 1;
} else {
PyObject* o = PySequence_GetItem($input,0);
if (PyNumber_Check(o))
$1 = 1;
else
$1 = 0;
Py_DECREF(o);
}
} else {
/* wrapped Array? */
Array* v;
if (SWIG_ConvertPtr($input,(void **) &v,
$&1_descriptor,0) != -1)
$1 = 1;
else
$1 = 0;
}
}
%typecheck(QL_TYPECHECK_ARRAY) const Array & {
/* native sequence? */
if (PyTuple_Check($input) || PyList_Check($input)) {
Size size = PySequence_Size($input);
if (size == 0) {
$1 = 1;
} else {
PyObject* o = PySequence_GetItem($input,0);
if (PyNumber_Check(o))
$1 = 1;
else
$1 = 0;
Py_DECREF(o);
}
} else {
/* wrapped Array? */
Array* v;
if (SWIG_ConvertPtr($input,(void **) &v,
$1_descriptor,0) != -1)
$1 = 1;
else
$1 = 0;
}
}
%typemap(in) Matrix (Matrix* m) {
if (PyTuple_Check($input) || PyList_Check($input)) {
Size rows, cols;
rows = (PyTuple_Check($input) ?
PyTuple_Size($input) :
PyList_Size($input));
if (rows > 0) {
// look ahead
PyObject* o = PySequence_GetItem($input,0);
if (PyTuple_Check(o) || PyList_Check(o)) {
cols = (PyTuple_Check(o) ?
PyTuple_Size(o) :
PyList_Size(o));
Py_DECREF(o);
} else {
PyErr_SetString(PyExc_TypeError, "Matrix expected");
Py_DECREF(o);
return NULL;
}
} else {
cols = 0;
}
$1 = Matrix(rows,cols);
for (Size i=0; i<rows; i++) {
PyObject* o = PySequence_GetItem($input,i);
if (PyTuple_Check(o) || PyList_Check(o)) {
Size items = (PyTuple_Check(o) ?
PyTuple_Size(o) :
PyList_Size(o));
if (items != cols) {
PyErr_SetString(PyExc_TypeError,
"Matrix must have equal-length rows");
Py_DECREF(o);
return NULL;
}
for (Size j=0; j<cols; j++) {
PyObject* d = PySequence_GetItem(o,j);
if (PyFloat_Check(d)) {
$1[i][j] = PyFloat_AsDouble(d);
Py_DECREF(d);
} else if (PyInt_Check(d)) {
$1[i][j] = Real(PyInt_AsLong(d));
Py_DECREF(d);
} else {
PyErr_SetString(PyExc_TypeError,"doubles expected");
Py_DECREF(d);
Py_DECREF(o);
return NULL;
}
}
Py_DECREF(o);
} else {
PyErr_SetString(PyExc_TypeError, "Matrix expected");
Py_DECREF(o);
return NULL;
}
}
} else {
SWIG_ConvertPtr($input,(void **) &m,$&1_descriptor,1);
$1 = *m;
}
};
%typemap(in) const Matrix & (Matrix temp) {
if (PyTuple_Check($input) || PyList_Check($input)) {
Size rows, cols;
rows = (PyTuple_Check($input) ?
PyTuple_Size($input) :
PyList_Size($input));
if (rows > 0) {
// look ahead
PyObject* o = PySequence_GetItem($input,0);
if (PyTuple_Check(o) || PyList_Check(o)) {
cols = (PyTuple_Check(o) ?
PyTuple_Size(o) :
PyList_Size(o));
Py_DECREF(o);
} else {
PyErr_SetString(PyExc_TypeError, "Matrix expected");
Py_DECREF(o);
return NULL;
}
} else {
cols = 0;
}
temp = Matrix(rows,cols);
for (Size i=0; i<rows; i++) {
PyObject* o = PySequence_GetItem($input,i);
if (PyTuple_Check(o) || PyList_Check(o)) {
Size items = (PyTuple_Check(o) ?
PyTuple_Size(o) :
PyList_Size(o));
if (items != cols) {
PyErr_SetString(PyExc_TypeError,
"Matrix must have equal-length rows");
Py_DECREF(o);
return NULL;
}
for (Size j=0; j<cols; j++) {
PyObject* d = PySequence_GetItem(o,j);
if (PyFloat_Check(d)) {
temp[i][j] = PyFloat_AsDouble(d);
Py_DECREF(d);
} else if (PyInt_Check(d)) {
temp[i][j] = Real(PyInt_AsLong(d));
Py_DECREF(d);
} else {
PyErr_SetString(PyExc_TypeError,"doubles expected");
Py_DECREF(d);
Py_DECREF(o);
return NULL;
}
}
Py_DECREF(o);
} else {
PyErr_SetString(PyExc_TypeError, "Matrix expected");
Py_DECREF(o);
return NULL;
}
}
$1 = &temp;
} else {
SWIG_ConvertPtr($input,(void **) &$1,$1_descriptor,1);
}
};
%typecheck(QL_TYPECHECK_MATRIX) Matrix {
/* native sequence? */
if (PyTuple_Check($input) || PyList_Check($input)) {
$1 = 1;
/* wrapped Matrix? */
} else {
Matrix* m;
if (SWIG_ConvertPtr($input,(void **) &m,
$&1_descriptor,0) != -1)
$1 = 1;
else
$1 = 0;
}
}
%typecheck(QL_TYPECHECK_MATRIX) const Matrix & {
/* native sequence? */
if (PyTuple_Check($input) || PyList_Check($input)) {
$1 = 1;
/* wrapped Matrix? */
} else {
Matrix* m;
if (SWIG_ConvertPtr($input,(void **) &m,
$1_descriptor,0) != -1)
$1 = 1;
else
$1 = 0;
}
}
//#endif
class Array {
//#if defined(SWIGPYTHON) || defined(SWIGRUBY)
%rename(__len__) size;
//#endif
public:
Array();
Array(Size n, Real fill = 0.0);
Array(const Array&);
Size size() const;
%extend {
std::string __str__() {
std::ostringstream out;
out << *self;
return out.str();
}
//#if defined(SWIGPYTHON) || defined(SWIGRUBY) || defined(SWIGR)
Array __add__(const Array& a) {
return Array(*self+a);
}
Array __sub__(const Array& a) {
return Array(*self-a);
}
Array __mul__(Real a) {
return Array(*self*a);
}
Real __mul__(const Array& a) {
return QuantLib::DotProduct(*self,a);
}
Array __mul__(const Matrix& a) {
return *self*a;
}
Array __div__(Real a) {
return Array(*self/a);
}
//#endif
//#if defined(SWIGPYTHON)
Array __rmul__(Real a) {
return Array(*self*a);
}
Array __getslice__(Integer i, Integer j) {
Integer size_ = static_cast<Integer>(self->size());
if (i<0)
i = size_+i;
if (j<0)
j = size_+j;
i = std::max(0,i);
j = std::min(size_,j);
Array tmp(j-i);
std::copy(self->begin()+i,self->begin()+j,tmp.begin());
return tmp;
}
void __setslice__(Integer i, Integer j, const Array& rhs) {
Integer size_ = static_cast<Integer>(self->size());
if (i<0)
i = size_+i;
if (j<0)
j = size_+j;
i = std::max(0,i);
j = std::min(size_,j);
QL_ENSURE(static_cast<Integer>(rhs.size()) == j-i,
"arrays are not resizable");
std::copy(rhs.begin(),rhs.end(),self->begin()+i);
}
bool __nonzero__() {
return (self->size() != 0);
}
bool __bool__() {
return (self->size() != 0);
}
//#endif
//#if defined(SWIGPYTHON) || defined(SWIGRUBY)
Real __getitem__(Integer i) {
Integer size_ = static_cast<Integer>(self->size());
if (i>=0 && i<size_) {
return (*self)[i];
} else if (i<0 && -i<=size_) {
return (*self)[size_+i];
} else {
throw std::out_of_range("array index out of range");
}
}
void __setitem__(Integer i, Real x) {
Integer size_ = static_cast<Integer>(self->size());
if (i>=0 && i<size_) {
(*self)[i] = x;
} else if (i<0 && -i<=size_) {
(*self)[size_+i] = x;
} else {
throw std::out_of_range("array index out of range");
}
}
//#endif
}
};
// 2-D view
%{
typedef QuantLib::LexicographicalView<Array::iterator> DefaultLexicographicalView;
typedef QuantLib::LexicographicalView<Array::iterator>::y_iterator DefaultLexicographicalViewColumn;
%}
//#if defined(SWIGPYTHON) || defined(SWIGRUBY) || defined(SWIGR)
class DefaultLexicographicalViewColumn {
private:
// access control - no constructor exported
DefaultLexicographicalViewColumn();
public:
%extend {
Real __getitem__(Size i) {
return (*self)[i];
}
void __setitem__(Size i, Real x) {
(*self)[i] = x;
}
}
};
//#endif
%rename(LexicographicalView) DefaultLexicographicalView;
class DefaultLexicographicalView {
public:
Size xSize() const;
Size ySize() const;
%extend {
DefaultLexicographicalView(Array& a, Size xSize) {
return new DefaultLexicographicalView(a.begin(),a.end(),xSize);
}
std::string __str__() {
std::ostringstream s;
for (Size j=0; j<self->ySize(); j++) {
s << "\\n";
for (Size i=0; i<self->xSize(); i++) {
if (i != 0)
s << ",";
Array::value_type value = (*self)[i][j];
s << value;
}
}
s << "\\n";
return s.str();
}
//#if defined(SWIGPYTHON) || defined(SWIGRUBY) || defined(SWIGR)
DefaultLexicographicalViewColumn __getitem__(Size i) {
return (*self)[i];
}
//#endif
}
};
%{
typedef QuantLib::Matrix::row_iterator MatrixRow;
using QuantLib::outerProduct;
using QuantLib::transpose;
using QuantLib::SVD;
%}
//#if defined(SWIGPYTHON) || defined(SWIGRUBY)
class MatrixRow {
private:
MatrixRow();
public:
%extend {
Real __getitem__(Size i) {
return (*self)[i];
}
void __setitem__(Size i, Real x) {
(*self)[i] = x;
}
}
};
//#endif
class Matrix {
public:
Matrix();
Matrix(Size rows, Size columns, Real fill = 0.0);
Matrix(const Matrix&);
Size rows() const;
Size columns() const;
%extend {
std::string __str__() {
std::ostringstream out;
out << *self;
return out.str();
}
//#if defined(SWIGPYTHON) || defined(SWIGRUBY)
Matrix __add__(const Matrix& m) {
return *self+m;
}
Matrix __sub__(const Matrix& m) {
return *self-m;
}
Matrix __mul__(Real x) {
return *self*x;
}
Array __mul__(const Array& x) {
return *self*x;
}
Matrix __mul__(const Matrix& x) {
return *self*x;
}
Matrix __div__(Real x) {
return *self/x;
}
//#endif
//#if defined(SWIGPYTHON) || defined(SWIGRUBY)
MatrixRow __getitem__(Size i) {
return (*self)[i];
}
//#endif
//#if defined(SWIGPYTHON)
Matrix __rmul__(Real x) {
return x*(*self);
}
Array __rmul__(const Array& x) {
return x*(*self);
}
Matrix __rmul__(const Matrix& x) {
return x*(*self);
}
//#endif
}
};
// functions
%{
using QuantLib::pseudoSqrt;
using QuantLib::SalvagingAlgorithm;
%}
struct SalvagingAlgorithm {
//#if defined(SWIGPYTHON)
%rename(NoAlgorithm) None;
//#endif
enum Type { None, Spectral };
};
Matrix transpose(const Matrix& m);
Matrix outerProduct(const Array& v1, const Array& v2);
Matrix pseudoSqrt(const Matrix& m, SalvagingAlgorithm::Type a);
class SVD {
public:
SVD(const Matrix&);
const Matrix& U() const;
const Matrix& V() const;
Matrix S() const;
const Array& singularValues() const;
};
#endif
setup.py
"""
setup.py file for QuantLibEx
"""
from distutils.core import setup, Extension
qlx_module = Extension(
name=\'QuantLibEx._QuantLibEx\',
sources=[\'QuantLibEx/qlx_wrap.cpp\'],
include_dirs=[\'/usr/include/ql\'], # QuantLib 头文件所在的目录
library_dirs=[\'/usr/lib/\'], # QuantLib 库所在的目录
libraries=[\'QuantLib\'] # QuantLib 库的名字
)
setup(
name = \'QuantLibEx\',
version = \'0.1\',
author = "xrl",
description = "Python bindings for the QuantLibEx library",
ext_modules = [qlx_module],
py_modules = [\'QuantLibEx.__init__\',\'QuantLibEx.QuantLibEx\'])
__init__.py
import sys
if sys.version_info.major >= 3:
from .QuantLibEx import *
from .QuantLibEx import _QuantLibEx
else:
from QuantLibEx import *
from QuantLibEx import _QuantLibEx
del sys
__author__ = \'xrl\'
if hasattr(_QuantLibEx,\'__version__\'):
__version__ = _QuantLibEx.__version__
elif hasattr(_QuantLibEx.cvar,\'__version__\'):
__version__ = _QuantLibEx.cvar.__version__
else:
print(\'Could not find __version__ attribute\')
if hasattr(_QuantLibEx,\'__hexversion__\'):
__hexversion__ = _QuantLibEx.__hexversion__
elif hasattr(_QuantLibEx.cvar,\'__hexversion__\'):
__hexversion__ = _QuantLibEx.cvar.__hexversion__
else:
print(\'Could not find __hexversion__ attribute\')
__license__ = """
QuantLibEx ...
"""