%newobject MEDCoupling::DataArrayFloat::iterator;
%newobject MEDCoupling::DataArrayFloat::__iter__;
%newobject MEDCoupling::DataArrayFloat::Meld;
+%newobject MEDCoupling::DataArrayFloat::__rmul__;
%newobject MEDCoupling::DataArrayInt::New;
%newobject MEDCoupling::DataArrayInt::__iter__;
%newobject MEDCoupling::DataArrayInt::performCopyOrIncrRef;
%newobject MEDCoupling::DataArrayInt::findIdsEqualList;
%newobject MEDCoupling::DataArrayInt::findIdsNotEqualList;
%newobject MEDCoupling::DataArrayInt::findIdsEqualTuple;
+%newobject MEDCoupling::DataArrayInt::findIdForEach;
%newobject MEDCoupling::DataArrayInt::sumPerTuple;
%newobject MEDCoupling::DataArrayInt::negate;
%newobject MEDCoupling::DataArrayInt::computeAbs;
int nbOfComp(self->getNumberOfComponents()),nbOfTuples(self->getNumberOfTuples());
return convertDblArrToPyListOfTuple<float>(vals,nbOfComp,nbOfTuples);
}
+
+ PyObject *isEqualIfNotWhy(const DataArrayFloat& other, float prec) const throw(INTERP_KERNEL::Exception)
+ {
+ std::string ret1;
+ bool ret0=self->isEqualIfNotWhy(other,prec,ret1);
+ PyObject *ret=PyTuple_New(2);
+ PyObject *ret0Py=ret0?Py_True:Py_False;
+ Py_XINCREF(ret0Py);
+ PyTuple_SetItem(ret,0,ret0Py);
+ PyTuple_SetItem(ret,1,PyString_FromString(ret1.c_str()));
+ return ret;
+ }
PyObject *__getitem__(PyObject *obj) throw(INTERP_KERNEL::Exception)
{
return DataArrayT_imul<float>(trueSelf,obj,self);
}
+ DataArrayFloat *__rmul__(PyObject *obj) throw(INTERP_KERNEL::Exception)
+ {
+ return DataArrayFPT_rmul<float>(self,obj);
+ }
+
PyObject *___idiv___(PyObject *trueSelf, PyObject *obj) throw(INTERP_KERNEL::Exception)
{
return DataArrayT_idiv<float>(trueSelf,obj,self);
return ToNumPyArray<DataArrayFloat,float>(self,NPY_FLOAT,"DataArrayFloat");
}
#endif
-
- // serialization
- static PyObject *___new___(PyObject *cls, PyObject *args) throw(INTERP_KERNEL::Exception)
- {
- return NewMethWrapCallInitOnlyIfDictWithSingleEltInInput(cls,args,"DataArrayFloat");
- }
-
- PyObject *__getnewargs__() throw(INTERP_KERNEL::Exception)
- {
-#ifdef WITH_NUMPY
- if(!self->isAllocated())
- throw INTERP_KERNEL::Exception("PyWrap of DataArrayFloat.__getnewargs__ : self is not allocated !");
- PyObject *ret(PyTuple_New(1));
- PyObject *ret0(PyDict_New());
- PyObject *numpyArryObj(MEDCoupling_DataArrayFloat_toNumPyArray(self));
- {// create a dict to discriminite in __new__ if __init__ should be called. Not beautiful but not idea ...
- PyObject *tmp1(PyInt_FromLong(0));
- PyDict_SetItem(ret0,tmp1,numpyArryObj); Py_DECREF(tmp1); Py_DECREF(numpyArryObj);
- PyTuple_SetItem(ret,0,ret0);
- }
- return ret;
-#else
- throw INTERP_KERNEL::Exception("PyWrap of DataArrayByte.__getnewargs__ : not implemented because numpy is not active in your configuration ! No serialization/unserialization available without numpy !");
-#endif
- }
}
};
void checkNoNullValues() const throw(INTERP_KERNEL::Exception);
DataArrayDouble *computeBBoxPerTuple(double epsilon=0.0) const throw(INTERP_KERNEL::Exception);
void recenterForMaxPrecision(double eps) throw(INTERP_KERNEL::Exception);
- double getMaxValue(int& tupleId) const throw(INTERP_KERNEL::Exception);
double getMaxValueInArray() const throw(INTERP_KERNEL::Exception);
- double getMinValue(int& tupleId) const throw(INTERP_KERNEL::Exception);
+ double getMaxAbsValueInArray() const throw(INTERP_KERNEL::Exception);
double getMinValueInArray() const throw(INTERP_KERNEL::Exception);
int count(double value, double eps) const throw(INTERP_KERNEL::Exception);
double getAverageValue() const throw(INTERP_KERNEL::Exception);
}
}
+ PyObject *asArcOfCircle() const throw(INTERP_KERNEL::Exception)
+ {
+ double center[2],radius,ang;
+ self->asArcOfCircle(center,radius,ang);
+ PyObject *ret(PyTuple_New(3));
+ {
+ PyObject *ret0(PyList_New(2));
+ PyList_SetItem(ret0,0,PyFloat_FromDouble(center[0]));
+ PyList_SetItem(ret0,1,PyFloat_FromDouble(center[1]));
+ PyTuple_SetItem(ret,0,ret0);
+ }
+ PyTuple_SetItem(ret,1,PyFloat_FromDouble(radius));
+ PyTuple_SetItem(ret,2,PyFloat_FromDouble(ang));
+ return ret;
+ }
+
DataArrayDoubleIterator *__iter__() throw(INTERP_KERNEL::Exception)
{
return self->iterator();
return ret;
}
+ PyObject *getMaxAbsValue() const throw(INTERP_KERNEL::Exception)
+ {
+ std::size_t tmp;
+ double r1=self->getMaxAbsValue(tmp);
+ PyObject *ret=PyTuple_New(2);
+ PyTuple_SetItem(ret,0,PyFloat_FromDouble(r1));
+ PyTuple_SetItem(ret,1,PyInt_FromLong(tmp));
+ return ret;
+ }
+
PyObject *getMaxValue2() const throw(INTERP_KERNEL::Exception)
{
DataArrayInt *tmp;
DataArrayDouble *__rmul__(PyObject *obj) throw(INTERP_KERNEL::Exception)
{
- const char msg[]="Unexpected situation in __rmul__ !";
- double val;
- DataArrayDouble *a;
- DataArrayDoubleTuple *aa;
- std::vector<double> bb;
- int sw;
- convertDoubleStarLikePyObjToCpp_2(obj,sw,val,a,aa,bb);
- switch(sw)
- {
- case 1:
- {
- MCAuto<DataArrayDouble> ret=self->deepCopy();
- ret->applyLin(val,0.);
- return ret.retn();
- }
- case 3:
- {
- MCAuto<DataArrayDouble> aaa=aa->buildDADouble(1,self->getNumberOfComponents());
- return DataArrayDouble::Multiply(self,aaa);
- }
- case 4:
- {
- MCAuto<DataArrayDouble> aaa=DataArrayDouble::New(); aaa->useArray(&bb[0],false,CPP_DEALLOC,1,(int)bb.size());
- return DataArrayDouble::Multiply(self,aaa);
- }
- default:
- throw INTERP_KERNEL::Exception(msg);
- }
+ return DataArrayFPT_rmul<double>(self,obj);
}
PyObject *___imul___(PyObject *trueSelf, PyObject *obj) throw(INTERP_KERNEL::Exception)
PyTuple_SetItem(ret,1,SWIG_NewPointerObj(SWIG_as_voidptr(ret1),SWIGTYPE_p_MEDCoupling__DataArrayInt, SWIG_POINTER_OWN | 0 ));
return ret;
}
-
- // serialization
- static PyObject *___new___(PyObject *cls, PyObject *args) throw(INTERP_KERNEL::Exception)
- {
- return NewMethWrapCallInitOnlyIfDictWithSingleEltInInput(cls,args,"DataArrayDouble");
- }
-
- PyObject *__getnewargs__() throw(INTERP_KERNEL::Exception)
- {
-#ifdef WITH_NUMPY
- if(!self->isAllocated())
- throw INTERP_KERNEL::Exception("PyWrap of DataArrayDouble.__getnewargs__ : self is not allocated !");
- PyObject *ret(PyTuple_New(1));
- PyObject *ret0(PyDict_New());
- PyObject *numpyArryObj(MEDCoupling_DataArrayDouble_toNumPyArray(self));
- {// create a dict to discriminite in __new__ if __init__ should be called. Not beautiful but not idea ...
- PyObject *tmp1(PyInt_FromLong(0));
- PyDict_SetItem(ret0,tmp1,numpyArryObj); Py_DECREF(tmp1); Py_DECREF(numpyArryObj);
- PyTuple_SetItem(ret,0,ret0);
- }
- return ret;
-#else
- throw INTERP_KERNEL::Exception("PyWrap of DataArrayDouble.__getnewargs__ : not implemented because numpy is not active in your configuration ! No serialization/unserialization available without numpy !");
-#endif
- }
}
};
bool presenceOfValue(const std::vector<int>& vals) const throw(INTERP_KERNEL::Exception);
int count(int value) const throw(INTERP_KERNEL::Exception);
int accumulate(int compId) const throw(INTERP_KERNEL::Exception);
- int getMaxValue(int& tupleId) const throw(INTERP_KERNEL::Exception);
int getMaxValueInArray() const throw(INTERP_KERNEL::Exception);
- int getMinValue(int& tupleId) const throw(INTERP_KERNEL::Exception);
+ int getMaxAbsValueInArray() const throw(INTERP_KERNEL::Exception);
int getMinValueInArray() const throw(INTERP_KERNEL::Exception);
void abs() throw(INTERP_KERNEL::Exception);
DataArrayInt *computeAbs() const throw(INTERP_KERNEL::Exception);
return self->findIdsEqualTuple(bg,bg+sz);
}
+ DataArrayInt *findIdForEach(PyObject *vals) const throw(INTERP_KERNEL::Exception)
+ {
+ int sw,sz,val;
+ std::vector<int> val2;
+ const int *bg(convertIntStarLikePyObjToCppIntStar(vals,sw,sz,val,val2));
+ MCAuto<DataArrayInt> ret(self->findIdForEach(bg,bg+sz));
+ return ret.retn();
+ }
+
PyObject *splitInBalancedSlices(int nbOfSlices) const throw(INTERP_KERNEL::Exception)
{
std::vector< std::pair<int,int> > slcs(self->splitInBalancedSlices(nbOfSlices));
PyTuple_SetItem(ret,1,PyInt_FromLong(tmp));
return ret;
}
+
+ PyObject *getMaxAbsValue(std::size_t& tupleId) const throw(INTERP_KERNEL::Exception)
+ {
+ std::size_t tmp;
+ int r1=self->getMaxAbsValue(tmp);
+ PyObject *ret=PyTuple_New(2);
+ PyTuple_SetItem(ret,0,PyInt_FromLong(r1));
+ PyTuple_SetItem(ret,1,PyInt_FromLong(tmp));
+ return ret;
+ }
PyObject *getMinValue() const throw(INTERP_KERNEL::Exception)
{
PyTuple_SetItem(pyRet,1,ret1Py);
return pyRet;
}
-
- // serialization
- static PyObject *___new___(PyObject *cls, PyObject *args) throw(INTERP_KERNEL::Exception)
- {
- return NewMethWrapCallInitOnlyIfDictWithSingleEltInInput(cls,args,"DataArrayInt");
- }
-
- PyObject *__getnewargs__() throw(INTERP_KERNEL::Exception)
- {
-#ifdef WITH_NUMPY
- if(!self->isAllocated())
- throw INTERP_KERNEL::Exception("PyWrap of DataArrayInt.__getnewargs__ : self is not allocated !");
- PyObject *ret(PyTuple_New(1));
- PyObject *ret0(PyDict_New());
- PyObject *numpyArryObj(MEDCoupling_DataArrayInt_toNumPyArray(self));
- {// create a dict to discriminite in __new__ if __init__ should be called. Not beautiful but not idea ...
- PyObject *tmp1(PyInt_FromLong(0));
- PyDict_SetItem(ret0,tmp1,numpyArryObj); Py_DECREF(tmp1); Py_DECREF(numpyArryObj);
- PyTuple_SetItem(ret,0,ret0);
- }
- return ret;
-#else
- throw INTERP_KERNEL::Exception("PyWrap of DataArrayInt.__getnewargs__ : not implemented because numpy is not active in your configuration ! No serialization/unserialization available without numpy !");
-#endif
- }
}
};
}
#endif
- // serialization
- static PyObject *___new___(PyObject *cls, PyObject *args) throw(INTERP_KERNEL::Exception)
- {
- return NewMethWrapCallInitOnlyIfDictWithSingleEltInInput(cls,args,"DataArrayByte");
- }
-
- PyObject *__getnewargs__() throw(INTERP_KERNEL::Exception)
- {
-#ifdef WITH_NUMPY
- if(!self->isAllocated())
- throw INTERP_KERNEL::Exception("PyWrap of DataArrayByte.__getnewargs__ : self is not allocated !");
- PyObject *ret(PyTuple_New(1));
- PyObject *ret0(PyDict_New());
- PyObject *numpyArryObj(MEDCoupling_DataArrayByte_toNumPyArray(self));
- {// create a dict to discriminite in __new__ if __init__ should be called. Not beautiful but not idea ...
- PyObject *tmp1(PyInt_FromLong(0));
- PyDict_SetItem(ret0,tmp1,numpyArryObj); Py_DECREF(tmp1); Py_DECREF(numpyArryObj);
- PyTuple_SetItem(ret,0,ret0);
- }
- return ret;
-#else
- throw INTERP_KERNEL::Exception("PyWrap of DataArrayByte.__getnewargs__ : not implemented because numpy is not active in your configuration ! No serialization/unserialization available without numpy !");
-#endif
- }
-
DataArrayByte *__setitem__(PyObject *obj, PyObject *value) throw(INTERP_KERNEL::Exception)
{
self->checkAllocated();
}
};
}
+
+%pythoncode %{
+def MEDCouplingStdReduceFunct(cls,params):
+ a,b=params
+ ret=object.__new__(cls)
+ ret.__init__(*a)
+ ret.__setstate__(b)
+ return ret
+
+def MEDCouplingDataArrayDoubleReduce(self):
+ if not MEDCouplingHasNumPyBindings():
+ raise InterpKernelException("PyWrap of DataArrayDouble.__reduce__ : not implemented because numpy is not active in your configuration ! No serialization/unserialization available without numpy !")
+ return MEDCouplingStdReduceFunct,(DataArrayDouble,((self.toNumPyArray(),),(self.__getstate__()),))
+
+def MEDCouplingDataArrayIntReduce(self):
+ if not MEDCouplingHasNumPyBindings():
+ raise InterpKernelException("PyWrap of DataArrayInt.__reduce__ : not implemented because numpy is not active in your configuration ! No serialization/unserialization available without numpy !")
+ return MEDCouplingStdReduceFunct,(DataArrayInt,((self.toNumPyArray(),),(self.__getstate__()),))
+
+def MEDCouplingDataArrayByteReduce(self):
+ if not MEDCouplingHasNumPyBindings():
+ raise InterpKernelException("PyWrap of DataArrayByte.__reduce__ : not implemented because numpy is not active in your configuration ! No serialization/unserialization available without numpy !")
+ return MEDCouplingStdReduceFunct,(DataArrayByte,((self.toNumPyArray(),),(self.__getstate__()),))
+
+def MEDCouplingDataArrayFloatReduce(self):
+ if not MEDCouplingHasNumPyBindings():
+ raise InterpKernelException("PyWrap of DataArrayFloat.__reduce__ : not implemented because numpy is not active in your configuration ! No serialization/unserialization available without numpy !")
+ return MEDCouplingStdReduceFunct,(DataArrayFloat,((self.toNumPyArray(),),(self.__getstate__()),))
+%}
