#include <PolySNPimpl.hpp>
Public Member Functions | |
| void | preprocess (void) |
| _PolySNPImpl (const Sequence::PolyTable *data, bool haveOutgroup, unsigned outgroup, bool totMuts) | |
Public Attributes | |
| const PolyTable * | _data |
| unsigned | _nsites |
| unsigned | _nsam |
| unsigned | _outgroup |
| bool | _haveOutgroup |
| bool | _totMuts |
| unsigned | _totsam |
| unsigned | _DVK |
| double | _DVH |
| bool | _counted_singletons |
| bool | _know_pi |
| bool | _CalculatedDandV |
| double | _pi |
| unsigned | _singletons |
| unsigned | _walls_Bprime |
| unsigned | _NumPoly |
| double | _walls_B |
| double | _walls_Q |
| bool | _calculated_wall_stats |
|
std::vector < Sequence::stateCounter > | _counts |
|
std::vector< std::pair< bool, Sequence::stateCounter > > | _derivedCounts |
| bool | _preprocessed |
Implementation details for PolySNP. This class is visible so that it can be accessed from classes derived from PolySNP. A PolySNP object contains a pointer to an instance of this class that is storage class protected.
Definition at line 30 of file PolySNPimpl.hpp.
| void Sequence::_PolySNPImpl::preprocess | ( | void | ) |
This routine takes the data and obtains count information for each possible character state at each site. The reason for doing this is that the various summary statistics that depend on frequency spectrum information are all O(n x S) to compute, where n is the sample size and S the number of sites. However, all of these statistics depend basically on the same features of the data, so it inefficient to recalculate them every time. This function obtains the counts for each site. Note that the efficiency gain is huge (especially for large data sets) as each summary statistic is reduced from an O(n x S) to an O(S) calculation. The increase in run-time efficiency comes at the cost of allocating 2 vectors whose sizes are linear in S
Definition at line 92 of file PolySNP.cc.
1.6.1