本文整理汇总了C++中Genome::readFasta方法的典型用法代码示例。如果您正苦于以下问题：C++ Genome::readFasta方法的具体用法？C++ Genome::readFasta怎么用？C++ Genome::readFasta使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Genome的用法示例。
在下文中一共展示了Genome::readFasta方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: main
int main()
{
std::string pathBegin = "/home/nax/Work/biolab/TestingIn/";
unsigned numMixtures = 1;
std::vector<double> sphi_init(numMixtures, 2);
std::vector<std::vector<unsigned> > mixtureDefinitionMatrix;
// SIMULATE GENOME: RFP
Genome genome;
//if(testEqualityGenome(genome, genome)){
// my_print("So far so good\n");
//}
//exit(1);
genome.readRFPData(pathBegin + "rfp_file_20positions_20genes.csv", false);
exit(0);
/*genome.readFasta(pathBegin + "RibModelDev/data/singleMixture/genome_2000.fasta", false);
std::vector<unsigned> geneAssignment(genome.getGenomeSize());
for (unsigned i = 0u; i < genome.getGenomeSize(); i++)
{
geneAssignment[i] = 0u;
}
PAParameter parameter(sphi_init, numMixtures, geneAssignment, mixtureDefinitionMatrix, true, "allUnique");
PAModel model;
//ROCParameter parameter(sphi_init, numMixtures, geneAssignment, mixtureDefinitionMatrix, true, "allUnique");
//ROCModel model;
model.setParameter(parameter);
model.simulateGenome(genome);
genome.writeRFPData(pathBegin + "labbooks/Denizhan.Pak/Log_Files/sim_genomes/PASim.csv", true);
genome.writeRFPData(pathBegin + "labbooks/Denizhan.Pak/Log_Files/sim_genomes/PANotSim.csv", false);
exit(1);*/
// UNIT TESTING
//testUtility();
//testSequenceSummary();
//testGene();
//testGenome(pathBegin + "RibModelFramework/tests/testthat/UnitTestingData");
//testCovarianceMatrix();
//testParameter();
//testParameterWithFile(pathBegin + "HollisFile.txt");
//testPAParameter();
//testMCMCAlgorithm();
//exit(0);
std::string modelToRun = "PANSE"; //can be RFP, ROC or FONSE
bool withPhi = false;
bool fromRestart = false;
my_print("Initializing MCMCAlgorithm object---------------\n");
unsigned samples = 100;
unsigned thinning = 100;
int useSamples = 1000;
my_print("\t# Samples: %\n", samples);
my_print("\tThinning: %\n", thinning);
my_print("\t # Samples used: %\n", useSamples);
MCMCAlgorithm mcmc = MCMCAlgorithm(samples, thinning, 10, true, true, true);
mcmc.setRestartFileSettings(pathBegin + "RestartFile.txt", 20, true);
my_print("Done!-------------------------------\n\n\n");
if (modelToRun == "ROC")
{
my_print("Initializing Genome object--------------------------\n");
Genome genome;
genome.readFasta(pathBegin + "RibModelDev/data/twoMixtures/simulatedAllUniqueR.fasta");
if (withPhi)
{
genome.readObservedPhiValues(pathBegin + "RibModelFramework/ribModel/data/simulatedAllUniqueR_phi.csv", false);
}
my_print("Done!-------------------------------\n\n\n");
my_print("Initializing shared parameter variables---------------\n");
std::vector<unsigned> geneAssignment(genome.getGenomeSize());
std::vector<double> sphi_init(numMixtures, 1);
if (numMixtures == 1)
{
for (unsigned i = 0u; i < genome.getGenomeSize(); i++)
{
geneAssignment[i] = 0u;
}
}
else if (numMixtures == 3)
{
for (unsigned i = 0u; i < genome.getGenomeSize(); i++)
{
if (i < 961) geneAssignment[i] = 0u;
else if (i < 1418) geneAssignment[i] = 1u;
else geneAssignment[i] = 0u;
}
//.........这里部分代码省略.........
示例2: main
int main()
{
std::cout << "Initializing MCMCAlgorithm object---------------" << std::endl;
int samples = 200;
int thinning = 10;
int useSamples = 100;
std::cout << "\t# Samples: " << samples << "\n";
std::cout << "\tThinning: " << thinning << "\n";
std::cout << "\t# Samples used: " << useSamples << "\n";
MCMCAlgorithm mcmc = MCMCAlgorithm(samples, thinning, 100, false, true, true);
mcmc.setRestartFileSettings(std::string("test"), 100, true);
//mcmc.setRestartFileSettings("RestartFile.txt", 20, true);
std::cout << "Done!-------------------------------\n\n\n";
std::cout << "initialize Genome object--------------------------" << std::endl;
bool withPhi = false;
Genome genome;
genome.readFasta("/home/clandere/CodonUsageBias/RibosomeModel/RibModelDev/data/twoMixtures/simulatedMutationSharedR.fasta");
//genome.readFasta("F:/GitHub/RibModelDev/data/twoMixtures/simulatedAllUniqueR.fasta");
//genome.readFasta("E:/RibosomeModel/RibModelDev/data/twoMixtures/simulatedAllUniqueR_unevenMixtures.fasta");
if(withPhi)
{
genome.readObservedPhiValues("F:/GitHub/RibModelDev/data/twoMixtures/simulatedAllUniqueR_phi_withPhiSet.csv", false);
//genome.readObservedPhiValues("E:/RibosomeModel/RibModelDev/data/twoMixtures/simulatedAllUniqueR_phi_unevenMixtures.csv", false);
}
std::cout << "Done!-------------------------------\n\n\n";
std::cout << "Initializing shared parameter variables---------------\n";
std::cout << "Done!-------------------------------\n\n\n";
std::cout << "Initializing shared parameter variables---------------\n";
std::vector<unsigned> geneAssignment(genome.getGenomeSize());
unsigned numMixtures = 2;
std::vector<double> sphi_init(numMixtures, 1);
/* For 2 mixture */
for (unsigned i = 0u; i < genome.getGenomeSize(); i++)
{
geneAssignment[i] = ( ((double)rand() / (double)RAND_MAX) < 0.5 ? 0u : 1u );
}
std::vector<std::vector<unsigned>> mixtureDefinitionMatrix;
std::cout << "Done!------------------------\n\n\n";
std::cout << "initialize ROCParameter object" << std::endl;
std::string mixDef = ROCParameter::mutationShared;
ROCParameter parameter(sphi_init, numMixtures, geneAssignment, mixtureDefinitionMatrix, true, mixDef);
for (unsigned i = 0u; i < numMixtures; i++)
{
unsigned selectionCategry = parameter.getSelectionCategory(i);
std::cout << "Sphi_init for selection category " << selectionCategry << ": " << sphi_init[selectionCategry] << std::endl;
}
std::cout << "\t# mixtures: " << numMixtures << "\n";
std::cout << "\tmixture definition: " << mixDef << "\n";
std::vector<std::string> files(1);
//files[0] = std::string("F:/GitHub/RibModelDev/data/twoMixtures/simulated_mutation0.csv");
//files[1] = std::string("F:/GitHub/RibModelDev/data/twoMixtures/simulated_mutation1.csv");
files[0] = std::string("/home/clandere/CodonUsageBias/RibosomeModel/RibModelDev/data/twoMixtures/simulated_mutation0.csv");
//files[1] = std::string("/home/clandere/CodonUsageBias/RibosomeModel/RibModelDev/data/twoMixtures/simulated_mutation1.csv");
parameter.initMutationCategories(files, parameter.getNumMutationCategories());
files.resize(2);
//files[0] = std::string("F:/GitHub/RibModelDev/data/twoMixtures/simulated_selection0.csv");
//files[1] = std::string("F:/GitHub/RibModelDev/data/twoMixtures/simulated_selection1.csv");
files[0] = std::string("/home/clandere/CodonUsageBias/RibosomeModel/RibModelDev/data/twoMixtures/simulated_selection0.csv");
files[1] = std::string("/home/clandere/CodonUsageBias/RibosomeModel/RibModelDev/data/twoMixtures/simulated_selection1.csv");
parameter.initSelectionCategories(files, parameter.getNumSelectionCategories());
parameter.InitializeSynthesisRate(genome, sphi_init[0]);
//std::vector<double> phiVals = parameter.readPhiValues("/home/clandere/CodonUsageBias/RibosomeModel/RibModelFramework/ribModel/data/Skluyveri_ChrA_ChrCleft_phi_est.csv");
//parameter.InitializeSynthesisRate(phiVals);
std::cout << "done initialize ROCParameter object" << std::endl;
std::cout << "Initializing ROCModel object\n";
ROCModel model(withPhi);
model.setParameter(parameter);
std::cout << "starting MCMC for ROC" << std::endl;
mcmc.run(genome, model, 1, 0);
std::cout << std::endl << "Finished MCMC for ROC" << std::endl;
double temp[] = { 0.025, 0.5, 0.975 };
std::vector<double> probs(temp, temp + sizeof(temp) / sizeof(double));
//std::vector<double> quants = parameter.getCodonSpecificQuantile(1, 100, std::string("GCA"), 0, probs, true);
std::string codon = std::string("TTT");
double a = parameter.getCodonSpecificPosteriorMean(0u, 50u, codon, 0u, true);
double b = parameter.getCodonSpecificPosteriorMean(0u, 50u, codon, 1u, true);
double c = parameter.getCodonSpecificPosteriorMean(1u, 50u, codon, 0u, true);
double d = parameter.getCodonSpecificPosteriorMean(1u, 50u, codon, 1u, true);
std::cout << std::endl << "Exiting" << std::endl;
}