xydata.cpp

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/*
 * Author: Steven Ludtke, 04/10/2003 (sludtke@bcm.edu)
 * Copyright (c) 2000-2006 Baylor College of Medicine
 *
 * This software is issued under a joint BSD/GNU license. You may use the
 * source code in this file under either license. However, note that the
 * complete EMAN2 and SPARX software packages have some GPL dependencies,
 * so you are responsible for compliance with the licenses of these packages
 * if you opt to use BSD licensing. The warranty disclaimer below holds
 * in either instance.
 *
 * This complete copyright notice must be included in any revised version of the
 * source code. Additional authorship citations may be added, but existing
 * author citations must be preserved.
 *
 * 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 2 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, write to the Free Software
 * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
 *
 * */
 
#ifndef WIN32
#include <sys/param.h>
#else
#include <windows.h>
#define MAXPATHLEN (MAX_PATH*4)
#endif
#include "xydata.h"
#include <algorithm>
#include <cfloat>
#include <cmath>
#include <cstdio>
#include "log.h"
#include "exception.h"
 
using namespace EMAN;
 
XYData::XYData()
        : ymin(FLT_MAX), ymax(-FLT_MAX), mean_x_spacing(1.0)
{
}
 
void XYData::update()
{
        if (data.size()==0) return;
        
        std::sort(data.begin(), data.end());
 
        ymin = FLT_MAX;
        ymax = -FLT_MAX;
 
        typedef vector < Pair >::const_iterator Ptype;
        for (Ptype p = data.begin(); p != data.end(); p++) {
                if (p->y > ymax) {
                        ymax = p->y;
                }
                if (p->y < ymin) {
                        ymin = p->y;
                }
        }
 
        size_t n = data.size();
        mean_x_spacing = (data[n - 1].x - data[0].x) / (float) n;
}
 
 
int XYData::read_file(const string & filename)
{
        FILE *in = fopen(filename.c_str(), "rb");
        if (!in) {
                throw FileAccessException(filename.c_str());
//              LOGERR("cannot open xydata file '%s'", filename.c_str());
//              return 1;
        }
 
        char buf[MAXPATHLEN];
        char tmp_str[MAXPATHLEN];
 
        while (fgets(buf, MAXPATHLEN, in)) {
                if (buf[0] != '#') {
                        float x = 0;
                        float y = 0;
 
                        if (sscanf(buf, " %f%[^.0-9-]%f", &x, tmp_str, &y) != 3) {
                                break;
                        }
                        data.push_back(Pair(x, y));
                }
        }
 
        fclose(in);
        in = 0;
 
        update();
 
        return 0;
}
 
int XYData::write_file(const string & filename) const
{
        FILE *out = fopen(filename.c_str(), "wb");
        if (!out) {
                LOGERR("cannot open xydata file '%s' to write", filename.c_str());
                return 1;
        }
 
        typedef vector < Pair >::const_iterator Ptype;
        for (Ptype p = data.begin(); p != data.end(); p++) {
                fprintf(out, "%1.6g\t%1.6g\n", p->x, p->y);
        }
 
        fclose(out);
        out = 0;
 
        return 0;
}
 
 
float XYData::calc_correlation(XYData * xy, float minx, float maxx) const
{
        size_t n = data.size();
        float x0 = data[0].x;
        float xn = data[n - 1].x;
 
        if (maxx <= minx || minx >= xn || maxx <= x0) {
                LOGERR("incorrect minx, maxx=%f,%f for this XYData range [%f,%f]",
                           minx, maxx, x0, xn);
                return 0;
        }
 
        float scc = 0;
        float norm1 = 0;
        float norm2 = 0;
 
        xy->update();
        for (size_t i = 0; i < n; i++) {
                float x = data[i].x;
                if (x >= minx && x <= maxx && xy->is_validx(x)) {
                        float selfy = data[i].y;
                        float xyy = xy->get_yatx(x);
 
                        scc += selfy * xyy;
                        norm1 += selfy * selfy;
                        norm2 += xyy * xyy;
                }
        }
 
        float result = scc / sqrt(norm1 * norm2);
        return result;
}
 
void XYData::make_gauss(int n,float xmax, float width)
{
        set_size(n);
        for (int i=0; i<n; i++) {
                float x=i*xmax/n;
                data[i].x=x;
                data[i].y=exp(-x*x/(width*width));
        }
}
 
float XYData::get_yatx(float x,bool outzero)
{
        if (data.size()==0 || mean_x_spacing==0) return 0.0;
 
        int nx = (int) data.size();
        // Do the range checking up front before we get into trouble
        if (x<data[0].x) return outzero?0.0f:data[0].y;
        if (x>data[nx-1].x) return outzero?0.0f:data[nx-1].y;
        
        int s = (int) floor((x - data[0].x) / mean_x_spacing);
        if (s>nx-1) s=nx-1;
 
        // These deal with possibly nonuniform x values. A btree would be better, but this is simple
        while (s>0 && data[s].x > x) s--;
        while (s<(nx-1) && data[s + 1].x < x ) s++;
        if (s>nx-2) return outzero?0.0f:data[nx-1].y;
        
        float f = (x - data[s].x) / (data[s + 1].x - data[s].x);
        float y = data[s].y * (1 - f) + data[s + 1].y * f;
        return y;
}
 
float XYData::get_yatx_smooth(float x,int smoothing)
{
        if (data.size()==0) return 0.0;
        if (data.size()==1) return data[0].y;
        if (smoothing!=1) throw InvalidParameterException("Only smoothing==1 (linear) currently supported");
        
        int nx = (int) data.size();
        
        int s = nx/2; 
        if (mean_x_spacing>0) s=(int) floor((x - data[0].x) / mean_x_spacing);
        if (s>nx-2) s=nx-2;
        else if (s<0) s=0;
        else {
                // These deal with possibly nonuniform x values. A btree would be better, but this is simple, and there usually won't be THAT many points
                while (s>0 && data[s].x > x) s--;
                while (s<(nx-2) && data[s + 1].x < x ) s++;
        }
        
        float f = 0,y=0;
        if (data[s + 1].x != data[s].x) {
                f= (x - data[s].x) / (data[s + 1].x - data[s].x);
                y = data[s].y * (1 - f) + data[s + 1].y * f;
        }
        else {
                int s2=s;
                while (data[s2].x==data[s].x) {
                        if (s2<nx-1) s2++;
                        if (s>0) s--;
                        if (s==0 &&s2==nx-1) return data[nx/2].y;
                }
                f= (x - data[s].x) / (data[s2].x - data[s].x);
                y = data[s].y * (1 - f) + data[s2].y * f;
                
        }
//      printf("%d %1.2f x %1.2f %1.2f %1.2f y %1.2f %1.2f\n",s,f,x,data[s].x,data[s+1].x,data[s].y,data[s+1].y);
        return y;
}
 
// FIXME: clearly a slow way to do this
void XYData::insort(float x, float y) {
        data.push_back(Pair(x,y));
        update();
        
        
        //      int nx = (int) data.size();
//      if (nx==0) { data.push_back(Pair(x,y)); return; }
//      
//      int s = (int) floor((x - data[0].x) / mean_x_spacing);
//      if (s>nx) s=nx;
//      else if (s<0) s=0;
//      else {
//      // These deal with possibly nonuniform x values. A btree would be better, but this is simple, and there usually won't be THAT many points
//              while (s>0 && data[s-1].x > x) s--;
//              while (s<nx && data[s].x <= x ) s++;
//      }
//      data.insert(data.begin()+s,Pair(x,y));
}       
 
// data must be sorted before this will work
void XYData::dedupx() {
        float acnt=1.0;
        for (std::vector<Pair>::iterator it = data.begin() ; it+1 < data.end(); ++it) {
                while (it+1<data.end() && it->x==(it+1)->x) {
//                      printf("%d\t%d\t%1.0f\t%f\t%f\n",it-data.begin(),data.end()-it,acnt,it->x,(it+1)->x);
                        it->y+=(it+1)->y;
                        acnt+=1.0;
                        data.erase(it+1);
                }
                if (acnt>1.0) {
                        it->y/=acnt;
                        acnt=1.0;
                }
        }
}
 
void XYData::set_xy_list(const vector<float>& xlist, const vector<float>& ylist)
{
        if(xlist.size() != ylist.size()) {
                throw InvalidParameterException("xlist and ylist size does not match!");
        }
 
        for(unsigned int i=0; i<xlist.size(); ++i) {
                data.push_back(Pair(xlist[i], ylist[i]));
        }
}
 
void XYData::set_size(size_t n)
{
        data.resize(n, Pair(0.0f, 0.0f));
}
 
vector<float>  XYData::get_state() const {
        vector<float> list;
        vector<Pair>::const_iterator cit;
        for(cit=data.begin(); cit!=data.end(); ++cit) {
                list.push_back( (*cit).x);
                list.push_back( (*cit).y);
        }
 
        return list;
        
}
 
void  XYData::set_state(vector<float> list) {
        if(list.size()%2==1) {
                throw InvalidParameterException("Invalid pickled data");
        }
 
        data.clear();
        for(unsigned int i=0; i<list.size(); i+=2) {
                data.push_back(Pair(list[i], list[i+1]));
        }
 
        update();
}
 
vector<float> XYData::get_xlist() const
{
        vector<float> xlist;
        vector<Pair>::const_iterator cit;
        for(cit=data.begin(); cit!=data.end(); ++cit) {
                xlist.push_back( (*cit).x);
        }
 
        return xlist;
}
 
vector<float> XYData::get_ylist() const
{
        vector<float> ylist;
        vector<Pair>::const_iterator cit;
        for(cit=data.begin(); cit!=data.end(); ++cit) {
                ylist.push_back( (*cit).y);
        }
 
        return ylist;
}