// $Id: Vertex.cpp,v 1.5 2011/09/02 16:08:11 samn Exp $
// Vertex.cpp: implementation of the CVertex class.
//
/*
isoi - This program calculates the Isolation Information (IsoI) cluster quality measures
described in the reference below. These measures were designed for clusters
obtained from neural extracellular recordings, but are applicable to an
arbitrary dataset.
Copyright (C) 2003-2011 Sam Neymotin & BioSignal Group
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
For more information contact Sam Neymotin ( samn at neurosim dot downstate dot edu )
or Andre Fenton ( afenton at nyu dot edu ).
References:
The methods used in this program are described in an article in press
at The Journal of Neuroscience,
Measuring the quality of neuronal identification in ensemble recordings
by Neymotin SA, Lytton WW, Olypher AO, Fenton AA (2011).
*/
//////////////////////////////////////////////////////////////////////
#include "Vertex.h"
#include "Log.h"
#include "WCMath.h"
#include "Hist.h"
#include "StringUtils.h"
#include <algorithm>
#include <math.h>
#include <errno.h>
#include <fstream>
/////////////////////////////////////////////////////////////////////////////
void CVertex::AddPnt(float toStore)
{
m_Vertex.push_back(toStore);
}
/////////////////////////////////////////////////////////////////////////////
// CVertexStack
CVerxStack::CVerxStack()
{
m_NumVerx = 0;
m_iNumDim = 0;
m_bNormFloatV = true;
}
void CVerxStack::CalcDimStats()
{
MY_STACK::iterator iVerx;
m_MainMin.clear();
m_MainMax.clear();
m_MainRange = VERTEX(m_iNumDim,0.0f);
int i;
for (i=0;i<m_iNumDim;i++)
{ m_MainMin.push_back((float) 2e+20);
m_MainMax.push_back((float)-2e+20);
}
for (iVerx = m_VerxStack.begin(); iVerx != m_VerxStack.end(); iVerx++)
{ CVertex* verx = (CVertex*) *iVerx;
for (i=0;i<m_iNumDim;i++)
{ float val = verx->GetValue(i);
if ( val < m_MainMin[i] )
m_MainMin[i] = val;
if ( val > m_MainMax[i] )
m_MainMax[i] = val;
}
}
for(i=0;i<m_iNumDim;i++)
m_MainRange[i] = m_MainMax[i] - m_MainMin[i];
}
/////////////////////////////////////////////////////////////////////////////
void CVerxStack::CalcMinMax()
{
MY_STACK::iterator iVerx;
m_MainMin.clear();
m_MainMax.clear();
int i;
for (i=0;i<m_iNumDim;i++)
{
m_MainMin.push_back((float) 2e+20);
m_MainMax.push_back((float)-2e+20);
}
CVertex *verx;
for (iVerx = m_VerxStack.begin(); iVerx != m_VerxStack.end(); iVerx++)
{
verx = (CVertex*) *iVerx;
for (i=0;i<m_iNumDim;i++)
{
if ( verx->GetValue(i) < m_MainMin[i])
m_MainMin[i] = verx->GetValue(i);
if ( verx->GetValue(i) > m_MainMax[i])
m_MainMax[i] = verx->GetValue(i);
}
}
}
/////////////////////////////////////////////////////////////////////////////
float CVerxStack::GetMin(int Index)
{
if (Index<m_iNumDim)
return m_MainMin[Index];
else
return -10;
}
/////////////////////////////////////////////////////////////////////////////
float CVerxStack::GetMax(int Index)
{
if (Index<m_iNumDim)
return m_MainMax[Index];
else
return 10;
}
/////////////////////////////////////////////////////////////////////////////
void CVerxStack::AddVrx(CMyObject *toStore)
{
m_VerxStack.push_back(toStore);
}
/////////////////////////////////////////////////////////////////////////////
int CVerxStack::GetClust(int NoOfVerx)
{
if (NoOfVerx < m_NumVerx)
{
return ((CVertex*)*(m_VerxStack.begin() + NoOfVerx))->GetClust();
}
return -1;
}
void InitProbs(int iMaxNumElems);
/////////////////////////////////////////////////////////////////////////////
void CVerxStack::CalcAfterLoad()
{
//#ifdef _DEBUG
CalcMinMax();
//int i;
//for(i=0;i<m_iNumDim;i++) printf("%g %g\n",m_MainMin[i],m_MainMax[i]);
//WriteVec2Log(this->m_MainMin);
//WriteVec2Log(this->m_MainMax);
//#endif
}
bool CVerxStack::ReadAsciiData(char* path) {
try {
int i = 0, iMaxClust = 0;
char buf[2048];
vector<string> vstr;
string delim(" \t");
// do actual loading here
// line 1 is header (space-separated column names, column 0 is cluster id)
// line 2... n - vector record
//record structure : clusterID feature1 ... featuren
std::ifstream f;
f.open(path);
if(!f.is_open()) return false;
f.getline(buf,2048);
Split(buf,delim,vstr);
m_iNumDim = vstr.size() - 1; // # of dimensions (first column is cluster ID)
if(m_iNumDim < 2) {
fprintf(stderr,"Must have at least 2 dimensions!\n");
return false;
}
vector<float> v(m_iNumDim,0.0);
while(true) {
int cid;
f >> cid;
if(f.eof()) break;
for(i=0;i<m_iNumDim && !f.eof();i++) f >> v[i];
if(i<m_iNumDim && f.eof()) break; // full vector not read in
if(cid > iMaxClust) iMaxClust = cid;
CVertex* NewVerx=new CVertex();// Storing data to container
NewVerx->SetClust(cid);
NewVerx->m_Vertex.resize(m_iNumDim);
copy(v.begin(),v.end(),NewVerx->m_Vertex.begin());
m_VerxStack.push_back(NewVerx);
if(f.eof()) break;
}
f.close();
m_NumVerx = m_VerxStack.size();
if (m_NumVerx == 0) {//check if spikes were loaded
return false;
} else {
InitClust(iMaxClust);
CalcAfterLoad();
Write2Log("Imported %d spikes",m_NumVerx);
return true;
}
} catch(...) {
Write2Log("Exception in ReadData!");
return false;
}
}
void CVerxStack::InitClust(int iMaxClust)
{
m_oClusters.m_iNumClusts =iMaxClust;
}
/////////////////////////////////////////////////////////////////////////////
void CVerxStack::SetEmpty()
{
// Remove vectors
MY_STACK::iterator Index;
for (Index=m_VerxStack.begin();Index!=m_VerxStack.end();Index++)
{
CVertex* verx = (CVertex*)*Index;
delete verx;
}
m_VerxStack.clear();
m_iNumDim = 0;
m_NumVerx = 0;
}