boost::python::str ScintillaWrapper::getWord(boost::python::object position, boost::python::object useOnlyWordChars /* = true */)
{
int pos;
if (position.is_none())
{
pos = callScintilla(SCI_GETCURRENTPOS);
}
else
{
pos = boost::python::extract<int>(position);
}
bool wordChars;
if (useOnlyWordChars.is_none())
{
wordChars = true;
}
else
{
wordChars = boost::python::extract<bool>(useOnlyWordChars);
}
int startPos = callScintilla(SCI_WORDSTARTPOSITION, pos, wordChars);
int endPos = callScintilla(SCI_WORDENDPOSITION, pos, wordChars);
Sci_TextRange tr;
tr.chrg.cpMin = startPos;
tr.chrg.cpMax = endPos;
tr.lpstrText = new char[size_t((endPos - startPos) + 1)];
callScintilla(SCI_GETTEXTRANGE, 0, reinterpret_cast<LPARAM>(&tr));
boost::python::str retVal(const_cast<const char *>(tr.lpstrText));
delete[] tr.lpstrText;
return retVal;
}
// 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;
}
inGtsSurface(py::object _surf, bool _noPad=false): pySurf(_surf), noPad(_noPad), noPadWarned(false) {
if(!pygts_surface_check(_surf.ptr())) throw std::invalid_argument("Ctor must receive a gts.Surface() instance.");
surf=PYGTS_SURFACE_AS_GTS_SURFACE(PYGTS_SURFACE(_surf.ptr()));
if(!gts_surface_is_closed(surf)) throw std::invalid_argument("Surface is not closed.");
is_open=gts_surface_volume(surf)<0.;
if((tree=gts_bb_tree_surface(surf))==NULL) throw std::runtime_error("Could not create GTree.");
}
void SequenceTypeHandler<ContainerType>::set(Kernel::IPropertyManager* alg, const std::string &name,
const boost::python::object & value) const
{
using boost::python::len;
typedef typename ContainerType::value_type DestElementType;
// Current workaround for things that still pass back wrapped vectors...
if(boost::starts_with(value.ptr()->ob_type->tp_name, "std_vector"))
{
alg->setProperty(name, StdVectorExtractor<DestElementType>::extract(value));
}
// numpy arrays requires special handling to extract their types. Hand-off to a more appropriate handler
else if( PyArray_Check(value.ptr()) )
{
alg->setProperty(name, Converters::NDArrayToVector<DestElementType>(value)());
}
else if( PySequence_Check(value.ptr()) )
{
alg->setProperty(name, Converters::PySequenceToVector<DestElementType>(value)());
}
else // assume it is a scalar and try to convert into a vector of length one
{
DestElementType scalar = boost::python::extract<DestElementType>(value.ptr());
alg->setProperty(name, std::vector<DestElementType>(1, scalar));
}
}
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);
}
}
void OutputHook::call(std::string name, boost::python::object obj)
{
Hooks::checkName(name);
auto repr_ = PyObject_Repr(obj.ptr());
if (PyErr_Occurred())
{
PyErr_Clear();
throw Hooks::Exception("Failed to get __repr__ of argument");
}
auto repr = std::string(PyUnicode_AsUTF8(repr_));
Py_DECREF(repr_);
PyObject* g = Py_BuildValue(
"{sO}", "__builtins__", PyEval_GetBuiltins());
node->parent->loadDatumHooks(g);
auto out = PyRun_String(repr.c_str(), Py_eval_input, g, g);
Py_DECREF(g);
Py_XDECREF(out);
if (PyErr_Occurred())
{
PyErr_Clear();
throw Hooks::Exception("Could not evaluate __repr__ of output");
}
const bool result = node->makeDatum(
name, obj.ptr()->ob_type, Datum::SIGIL_OUTPUT + repr, true);
if (!result)
throw Hooks::Exception("Datum was already defined in this script.");
}
TypeGeneral::EdgeData::EdgeData(const py::object& obj)
{
typedef TypeGeneral::REAL REAL;
bool isiterable = PyObject_HasAttrString(obj.ptr(), "__iter__");
if(isiterable)
{
py::stl_input_iterator<REAL> it(obj), end;
bool haslen = PyObject_HasAttrString(obj.ptr(), "__len__");
m_type = GENERAL;
if(haslen)
{
m_dataGeneral.resize(py::len(obj));
std::copy(it, end, m_dataGeneral.begin());
}
else
{
for(; it!=end; ++it)
{
m_dataGeneral.push_back(*it);
std::cout << *it << " ";
}
}
}
else
{
m_type = POTTS;
m_lambdaPotts = py::extract<REAL>(obj);
}
}
/** 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 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 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;
}
std::valarray<T> convert2valarray(boost::python::object arr)
{
import(); // ### WARNING: forgetting this will end up in segmentation fault!
std::size_t vec_size = PyArray_Size(arr.ptr());
T * data = (T *) PyArray_DATA(arr.ptr());
std::valarray<T> vec(vec_size);
memcpy(&vec[0],data, PyArray_ITEMSIZE((PyArrayObject*) arr.ptr()) * vec_size);
return vec;
}
void send_alive(boost::python::object ad_obj=boost::python::object(), boost::python::object pid_obj=boost::python::object(), boost::python::object timeout_obj=boost::python::object())
{
std::string addr;
if (ad_obj.ptr() == Py_None)
{
char *inherit_var = getenv("CONDOR_INHERIT");
if (!inherit_var) {
THROW_EX(RuntimeError, "No location specified and $CONDOR_INHERIT not in Unix environment.");
}
std::string inherit(inherit_var);
boost::python::object inherit_obj(inherit);
boost::python::object inherit_split = inherit_obj.attr("split")();
if (py_len(inherit_split) < 2) {
THROW_EX(RuntimeError, "$CONDOR_INHERIT Unix environment variable malformed.");
}
addr = boost::python::extract<std::string>(inherit_split[1]);
}
else
{
const ClassAdWrapper ad = boost::python::extract<ClassAdWrapper>(ad_obj);
if (!ad.EvaluateAttrString(ATTR_MY_ADDRESS, addr))
{
THROW_EX(ValueError, "Address not available in location ClassAd.");
}
}
int pid = getpid();
if (pid_obj.ptr() != Py_None)
{
pid = boost::python::extract<int>(pid_obj);
}
int timeout;
if (timeout_obj.ptr() == Py_None)
{
timeout = param_integer("NOT_RESPONDING_TIMEOUT");
}
else
{
timeout = boost::python::extract<int>(timeout_obj);
}
if (timeout < 1) {
timeout = 1;
}
classy_counted_ptr<Daemon> daemon = new Daemon(DT_ANY, addr.c_str());
classy_counted_ptr<ChildAliveMsg> msg = new ChildAliveMsg(pid, timeout, 0, 0, true);
{
condor::ModuleLock ml;
daemon->sendBlockingMsg(msg.get());
}
if (msg->deliveryStatus() != DCMsg::DELIVERY_SUCCEEDED)
{
THROW_EX(RuntimeError, "Failed to deliver keepalive message.");
}
}
inline index_type sequence_len(boost::python::object const& obj){
if( !PySequence_Check( obj.ptr() ) ){
raise_error( PyExc_TypeError, "Sequence expected" );
}
index_type result = PyObject_Length( obj.ptr() );
if( PyErr_Occurred() ){
boost::python::throw_error_already_set();
}
return result;
}
// Used by multiple profile classes to ensure at most one radius is given.
static void checkRadii(const bp::object & r1, const bp::object & r2, const bp::object & r3)
{
int nRad = (r1.ptr() != Py_None) + (r2.ptr() != Py_None) + (r3.ptr() != Py_None);
if (nRad > 1) {
PyErr_SetString(PyExc_TypeError, "Multiple radius parameters given");
bp::throw_error_already_set();
}
if (nRad == 0) {
PyErr_SetString(PyExc_TypeError, "No radius parameter given");
bp::throw_error_already_set();
}
}
/** Must be called with GIL locked
* */
std::string getStrFromPy(bp::object o) {
PyObject* ptr = o.ptr();
if (PyBytes_Check(ptr)) {
return std::string(PyBytes_AsString(ptr),
PyBytes_Size(ptr));
}
bp::object bytes = o.attr("encode")("utf-8");
ptr = bytes.ptr();
return std::string(PyBytes_AsString(ptr),
PyBytes_Size(ptr));
}
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 set_errors(Tango::EventData &event_data, boost::python::object &error)
{
PyObject* error_ptr = error.ptr();
if (PyObject_IsInstance(error_ptr, PyTango_DevFailed.ptr()))
{
Tango::DevFailed df;
boost::python::object error_list = error.attr("args");
sequencePyDevError_2_DevErrorList(error_list.ptr(), event_data.errors);
}
else
{
sequencePyDevError_2_DevErrorList(error_ptr, event_data.errors);
}
}
void ScintillaWrapper::replace(boost::python::object searchStr, boost::python::object replaceStr, boost::python::object flags)
{
int start = 0;
int end = GetLength();
int iFlags = 0;
if (!flags.is_none())
{
iFlags |= boost::python::extract<int>(flags);
}
const char *replaceChars = boost::python::extract<const char*>(replaceStr.attr("__str__")());
size_t replaceLength = strlen(replaceChars);
Sci_TextToFind src;
src.lpstrText = const_cast<char*>((const char *)boost::python::extract<const char *>(searchStr.attr("__str__")()));
BeginUndoAction();
int result = 0;
while(result != -1)
{
src.chrg.cpMin = start;
src.chrg.cpMax = end;
result = callScintilla(SCI_FINDTEXT, iFlags, reinterpret_cast<LPARAM>(&src));
// If nothing found, then just finish
if (-1 == result)
{
return;
}
else
{
// Replace the location found with the replacement text
SetTargetStart(src.chrgText.cpMin);
SetTargetEnd(src.chrgText.cpMax);
callScintilla(SCI_REPLACETARGET, replaceLength, reinterpret_cast<LPARAM>(replaceChars));
start = src.chrgText.cpMin + (int)replaceLength;
end = end + ((int)replaceLength - (src.chrgText.cpMax - src.chrgText.cpMin));
}
}
EndUndoAction();
}
void sgs_lvm_simulation(
boost::python::tuple output_array,
const py_grid_t & grid,
const py_sgs_params_t & param,
boost::python::object mean_data,
PyObject * cdf_property,
boost::python::object mask_data)
{
using namespace boost::python;
sp_double_property_array_t out_prop = cont_prop_from_tuple(output_array);
boost::python::extract<tuple> ext(cdf_property);
unsigned char * mask =
mask_data.ptr() == Py_None ? NULL
: get_buffer_from_ndarray<unsigned char,'u'>(mask_data, out_prop->size(), "sgs_lvm_simulation");
sp_double_property_array_t cdf_prop;
if (ext.check())
{
cdf_prop = cont_prop_from_tuple(ext);
}
else
{
cdf_prop = out_prop;
}
mean_t * lvm_data = get_buffer_from_ndarray<mean_t, 'f'>(mean_data, out_prop->size(), "sgs_lvm_simulation");
hpgl::sequential_gaussian_simulation_lvm(*grid.m_sugarbox_geometry, param.m_sgs_params, lvm_data, *out_prop, *cdf_prop, mask);
}
static py::object unpack( py::object bytes )
{
auto p = bytes.ptr();
if( !p )
{
throw std::runtime_error( "can't unpack: no object" );
}
const void * data = nullptr;
Py_ssize_t size = 0;
if( PyObject_AsReadBuffer( p, &data, &size ) )
{
py::throw_error_already_set();
}
if( !data || !size )
{
throw std::runtime_error( "can't unpack: no data" );
}
Unpacker unpacker( reinterpret_cast< char const * >( data ), size );
return unpacker.unpack();
}
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);
}
}
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);
}
}
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);
}
boost::python::object test2( boost::python::object M, range const & R1, range const & R2) {
cerr<<" entring test2 "<<endl;
array_view<long,2> A (M.ptr());
array_view<long,2> V(A(R1,R2));
cerr<<" array python "<<A<<endl<<R1<<" return view "<<V<<endl;
return boost::python::object(V);
}
boost::python::object test4( boost::python::object M, range const & R1, int j) {
cerr<<" entring test4 "<<endl;
array_view<long,2> A(M.ptr());
array_view<long,1> V(A(R1,j));
cerr<<" array python "<<A<<endl<<" return view "<<V<<endl;
return boost::python::object(V);
}
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);
}
bool doTriangleSmoothing(python::object boundsMatArg,double tol){
PyObject *boundsMatObj = boundsMatArg.ptr();
if(!PyArray_Check(boundsMatObj))
throw_value_error("Argument isn't an array");
PyArrayObject *boundsMat=reinterpret_cast<PyArrayObject *>(boundsMatObj);
// get the dimensions of the array
int nrows = boundsMat->dimensions[0];
int ncols = boundsMat->dimensions[1];
if(nrows!=ncols)
throw_value_error("The array has to be square");
if(nrows<=0)
throw_value_error("The array has to have a nonzero size");
if (boundsMat->descr->type_num != PyArray_DOUBLE)
throw_value_error("Only double arrays are currently supported");
unsigned int dSize = nrows*nrows;
double *cData = new double[dSize];
double *inData = reinterpret_cast<double *>(boundsMat->data);
memcpy(static_cast<void *>(cData),
static_cast<const void *>(inData),
dSize*sizeof(double));
DistGeom::BoundsMatrix::DATA_SPTR sdata(cData);
DistGeom::BoundsMatrix bm(nrows,sdata);
bool res=DistGeom::triangleSmoothBounds(&bm,tol);
memcpy(static_cast<void *>(inData),
static_cast<const void *>(cData),
dSize*sizeof(double));
return res;
}
static void set_errors(Tango::DataReadyEventData &event_data,
boost::python::object &dev_failed)
{
Tango::DevFailed df;
boost::python::object errors = dev_failed.attr("args");
sequencePyDevError_2_DevErrorList(errors.ptr(), event_data.errors);
}
