如何return多个值，或者如何让每个iteration的Random number 为同一个值
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下面的代码其实是错误的，但是我想问一下如何能实现 return多值。
我需要return dClass，PUr和PUz。
实在是对于编程这块了解的不够深。我尝试过分成三个class，但是问题就是分成三个class以后，每次调用的随机数就不一样了。
拜谢！
Foam::scalar Foam::distributionModels::PDF::sample() const { scalar y = rndGen_.sample01<scalar>(); //dummy Info<< "\n number1PDF = " << y << endl; return y; //dummy } Foam::scalar Foam::distributionModels::PDF::samplePDF(const PDFDataIOList& PDFsamples) const { // Generating random const scalar y = this->sample(); //scalar y = sample(); // Looking for the diameter class int classID = 0; int classIDmax = PDFsamples.size() - 1; while (y > PDFsamples[classID].prob() && classID < classIDmax) { classID++; } scalar dClassAvg = PDFsamples[classID].dclass(); scalar dClassDevP = PDFsamples[classID].devPclass(); scalar dRandon = (2.0 - ROOTVSMALL)*rndGen_.sample01<scalar>() - 1.0; scalar dClass = dClassAvg + dClassDevP*dRandon; scalar dmass = 1.0/6.0*3.141592653*dClass*dClass*dClass*1000; scalar PUrAvg = PDFsamples[classID].Ur(); scalar PUrrms = PDFsamples[classID].Urrms(); scalar PRandonur = (2.0 - ROOTVSMALL)*rndGen_.sample01<scalar>() - 1.0; scalar PUr = PUrAvg + PUrrms * PRandonur; scalar PUzAvg = PDFsamples[classID].Uz(); scalar PUzrms = PDFsamples[classID].Uzrms(); scalar PRandonuz = (2.0 - ROOTVSMALL)*rndGen_.sample01<scalar>() - 1.0; scalar PUz = PUzAvg+PUzrms*PRandonuz; Info<< "\n -------------------------------------------------------------- samplePDF"; Info<< "\n random number1 = " << y << endl; Info<< "\n classID1 = " << classID << endl; Info<< "\n classIDmax1 = " << classIDmax << endl; Info<< "\n dClassAvg1 = " << dClassAvg << " dClassDevP = " << dClassDevP << endl; Info<< "\n dRandon1 = " << dRandon << " dClass = " << dClass << " dmass = "<< dmass << endl; Info<< "\n -------------------------------------------------------------- samplePDF"; Info<< "\n -------------------------------------------------------------- samplePDFUr"; Info<< "\n random number = " << y << endl; Info<< "\n classID = " << classID << endl; Info<< "\n PUrAvg = " << PUrAvg << " PUrrms = " << PUrrms << endl; Info<< "\n PRandonur = " << PRandonur << " PUr = " << PUr << endl; Info<< "\n -------------------------------------------------------------- samplePDFUr"; Info<< "\n -------------------------------------------------------------- samplePDFUz"; Info<< "\n random number2 = " << y << endl; Info<< "\n classID2 = " << classID << endl; Info<< "\n PUzAvg2 = " << PUzAvg << " PUzrms = " << PUzrms << endl; Info<< "\n PRandonuz2 = " << PRandonuz << " PUz = " << PUz << endl; Info<< "\n -------------------------------------------------------------- samplePDFUz"; return PUr; return PUz return dClass; }Foam::scalar Foam::distributionModels::PDF::sample() const { scalar y = rndGen_.sample01<scalar>(); //dummy Info<< "\n number1PDF = " << y << endl; return y; //dummy } Foam::scalar Foam::distributionModels::PDF::samplePDF(const PDFDataIOList& PDFsamples) const { // Generating random const scalar y = this->sample(); //scalar y = sample(); // Looking for the diameter class int classID = 0; int classIDmax = PDFsamples.size() - 1; while (y > PDFsamples[classID].prob() && classID < classIDmax) { classID++; } scalar dClassAvg = PDFsamples[classID].dclass(); scalar dClassDevP = PDFsamples[classID].devPclass(); scalar dRandon = (2.0 - ROOTVSMALL)*rndGen_.sample01<scalar>() - 1.0; scalar dClass = dClassAvg + dClassDevP*dRandon; scalar dmass = 1.0/6.0*3.141592653*dClass*dClass*dClass*1000; Info<< "\n -------------------------------------------------------------- samplePDF"; Info<< "\n random number1 = " << y << endl; Info<< "\n classID1 = " << classID << endl; Info<< "\n classIDmax1 = " << classIDmax << endl; Info<< "\n dClassAvg1 = " << dClassAvg << " dClassDevP = " << dClassDevP << endl; Info<< "\n dRandon1 = " << dRandon << " dClass = " << dClass << " dmass = "<< dmass << endl; Info<< "\n -------------------------------------------------------------- samplePDF"; // Returning the class diameter return dClass; } Foam::scalar Foam::distributionModels::PDF::samplePDFUz(const PDFDataIOList& PDFsamples) const { // Generating random // scalar y = rndGen_.sample01<scalar>(); const scalar y = this->sample(); // Looking for the diameter class int classID = 0; int classIDmax = PDFsamples.size() - 1; while (y > PDFsamples[classID].prob() && classID < classIDmax) { classID++; } scalar PUzAvg = PDFsamples[classID].Uz(); scalar PUzrms = PDFsamples[classID].Uzrms(); scalar PRandonuz = (2.0 - ROOTVSMALL)*rndGen_.sample01<scalar>() - 1.0; scalar PUz = PUzAvg+PUzrms*PRandonuz; Info<< "\n -------------------------------------------------------------- samplePDFUz"; Info<< "\n random number2 = " << y << endl; Info<< "\n classID2 = " << classID << endl; Info<< "\n PUzAvg2 = " << PUzAvg << " PUzrms = " << PUzrms << endl; Info<< "\n PRandonuz2 = " << PRandonuz << " PUz = " << PUz << endl; Info<< "\n -------------------------------------------------------------- samplePDFUz"; return PUz; } Foam::scalar Foam::distributionModels::PDF::samplePDFUr(const PDFDataIOList& PDFsamples) const { // Generating random //scalar y = rndGen_.sample01<scalar>(); const scalar y = this->sample(); // Looking for the diameter class int classID = 0; int classIDmax = PDFsamples.size() - 1; while (y > PDFsamples[classID].prob() && classID < classIDmax) { classID++; } scalar PUrAvg = PDFsamples[classID].Ur(); scalar PUrrms = PDFsamples[classID].Urrms(); scalar PRandonur = (2.0 - ROOTVSMALL)*rndGen_.sample01<scalar>() - 1.0; scalar PUr = PUrAvg + PUrrms * PRandonur; Info<< "\n -------------------------------------------------------------- samplePDFUr"; Info<< "\n random number = " << y << endl; Info<< "\n classID = " << classID << endl; Info<< "\n PUrAvg = " << PUrAvg << " PUrrms = " << PUrrms << endl; Info<< "\n PRandonur = " << PRandonur << " PUr = " << PUr << endl; Info<< "\n -------------------------------------------------------------- samplePDFUr"; return PUr; } -
调用的时候是再injection model中 调用的，目前还是测试。。
只要能得到正确的值就可以使用了。。。分成3个class以后，每一次赋值，都需要进入sample()中重新获取随机数。
parcel.d() = sizeDistribution_->samplePDF(PDFsamples_); scalar uztest = sizeDistribution_->samplePDFUz(PDFsamples_); Info<< "\n---------------------in injectionmodel " << endl; Info<< "\n uztest = " << uztest << endl; scalar urtest = sizeDistribution_->samplePDFUr(PDFsamples_); Info<< "\n---------------------in injectionmodel " << endl; Info<< "\n urtest = " << urtest << endl;
没太细看哈不过