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lab_2/12/chain-random-walk.cpp
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lab_2/12/chain-random-walk.cpp
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#include <cstdlib>
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#include <iomanip>
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#include <iostream>
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#include "chain-random-walk.h"
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using namespace crw;
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namespace {
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// set each element forward or backward by 1, at random
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void stochastic_unit_step(long size, float config[])
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{
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for(long i = 0; i < size; i++)
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if(std::rand() % 2 == 0) config[i]++;
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else config[i]--;
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}
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void shift_centre_to_origin(long size, float config[])
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{
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double sum = 0.0;
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for(long i = 0; i < size; i++) sum += config[i];
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for(long i = 0; i < size; i++) config[i] -= sum/size;
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}
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const int el_out_max = 9; // show at most the first nine elements
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}
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float crw::elongation(long size, float config[])
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{
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float min = config[0];
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float max = config[0];
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for(long i = 1; i < size; i++)
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if(config[i] > max) max = config[i];
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else if(config[i] < min) min = config[i];
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return max - min;
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}
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float* crw::step(long size, float previous[])
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{
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// allocate the next configuration
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float* config = new float[size]();
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// first, let the chain contract: each element is attracted by its neighbours
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for(long i = 0; i < size; i++)
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config[i] = 0.5*previous[i] + 0.25*previous[(i-1) % size]
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+ 0.25*previous[(i+1) % size];
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stochastic_unit_step(size, config); // actual random walk step
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shift_centre_to_origin(size, config); // shift such that the average remains zero
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return config;
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}
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void crw::output(long no, long size, float present[], float extreme[], double avg_el)
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{
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/* output statistics over the run so far
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*/
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std::cout << std::setw(12) << no << "\t" << std::setprecision(3) << std::fixed
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<< std::setw(6) << elongation(size, present) << " "
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<< std::setprecision(7) << std::setw(10) << avg_el << " " << std::setprecision(5)
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<< std::setw(9) << elongation(size, extreme) << std::setprecision(3) << "\t\t";
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/* display the present configuration, showing up to <el_out_max> element coordinates */
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for(long i = 0; (i < size) && (i < el_out_max); i++)
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std::cout << std::setw(7) << present[i] << " ";
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if(size > el_out_max) std::cout << "...";
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std::cout << "\t\t";
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/* display the most extreme configuration so far,
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* showing up to <el_out_max> element coordinates
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*/
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for(long i = 0; (i < size) && (i < el_out_max); i++)
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std::cout << std::setw(7) << extreme[i] << " ";
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if(size > el_out_max) std::cout << "...";
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std::cout << "\n";
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}
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lab_2/12/chain-random-walk.h
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lab_2/12/chain-random-walk.h
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#ifndef CHAIN_RANDOM_WALK_H
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#define CHAIN_RANDOM_WALK_H
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namespace crw
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{
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float elongation(long size, float config[]);
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float* step(long size, float previous[]);
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void output(long no, long size, float present[], float extreme[], double avg_el);
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}
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#endif
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lab_2/12/memleak.cpp
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lab_2/12/memleak.cpp
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#include <cassert>
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#include <cstdlib>
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#include <ctime>
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#include "chain-random-walk.h"
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namespace {
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constexpr int default_size = 7;
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constexpr int default_steps = 100000000;
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constexpr int outlines = 25;
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}
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/* first argument: array size
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* second argument: number of steps
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*/
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int main(int argc, char** argv)
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{
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long size = default_size;
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if(argc > 1) size = std::atol(argv[1]);
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assert(size > 0);
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long steps = default_steps;
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if(argc > 2) steps = std::atol(argv[2]);
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assert(steps > 0);
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long outfreq = steps / outlines;
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if(outfreq < 1) outfreq = 1;
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/* the configuration is given by an array of float numbers */
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float* present_configuration = new float[size]();
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/* store the one with greatest deviation between min and max element */
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float* extreme_configuration = present_configuration;
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float extreme_elongation = 0.0;
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double el_sum = 0.0;
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double el_avg = 0.0;
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std::srand(std::time(nullptr)); // initialize the random number generator
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for(long i = 0; i < steps; i++)
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{
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if(i % outfreq == 0)
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crw::output(i, size, present_configuration, extreme_configuration, el_avg);
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/* here we are calling the random walk step;
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* this returns a new configuration (float array) on the heap
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*/
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present_configuration = crw::step(size, present_configuration);
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float present_elongation = crw::elongation(size, present_configuration);
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if(present_elongation > extreme_elongation)
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{
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extreme_configuration = present_configuration;
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extreme_elongation = present_elongation;
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}
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el_sum += present_elongation;
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el_avg = el_sum / (i + 1.0);
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}
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crw::output(steps, size, present_configuration, extreme_configuration, el_avg);
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delete[] present_configuration;
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}
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