1 | #include <iostream> |
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2 | #include <math.h> |
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3 | int linear_regression(int num, float *x, float *y, int ilow, int ihigh, float &slope, float &errSlope, float &intercept, float &errIntercept, float &r) |
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4 | { |
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5 | /** |
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6 | * int linear_regression() |
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7 | * |
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8 | * Computes the linear best fit to data - y = a*x + b, where x and y are |
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9 | * arrays of size num, a is the slope and b the y-intercept. |
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10 | * The values used in the arrays are those from ilow to ihigh. |
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11 | * (ie. if the full arrays are being used, then ilow=0 and ihigh=num-1. |
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12 | * Returns the values of slope & intercept (with errors) |
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13 | * as well as r, the regression coefficient. |
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14 | * If everything works, returns 0. |
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15 | * If slope is infinite (eg, all points have same x value), returns 1. |
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16 | */ |
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17 | |
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18 | if (ilow>ihigh) { |
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19 | std::cerr << "Error! linear_regression.cc :: ilow (" << ilow |
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20 | << ") > ihigh (" << ihigh << ")!!\n"; |
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21 | std::exit(1); |
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22 | } |
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23 | if (ihigh>num-1) { |
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24 | std::cerr << "Error! linear_regression.cc :: ihigh (" <<ihigh |
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25 | << ") out of bounds of array (>" << num-1 << ")!!\n"; |
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26 | std::exit(1); |
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27 | } |
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28 | if(ilow<0){ |
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29 | std::cerr << "Error! linear_regression.cc :: ilow (" << ilow |
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30 | << ") < 0. !!\n"; |
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31 | std::exit(1); |
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32 | } |
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33 | |
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34 | double sumx,sumy,sumxx,sumxy,sumyy; |
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35 | sumx=0.; |
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36 | sumy=0.; |
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37 | sumxx=0.; |
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38 | sumxy=0.; |
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39 | sumyy=0.; |
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40 | int count=0; |
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41 | for (int i=ilow;i<=ihigh;i++){ |
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42 | count++; |
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43 | sumx = sumx + x[i]; |
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44 | sumy = sumy + y[i]; |
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45 | sumxx = sumxx + x[i]*x[i]; |
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46 | sumxy = sumxy + x[i]*y[i]; |
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47 | sumyy = sumyy + y[i]*y[i]; |
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48 | } |
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49 | if(count!=(ihigh-ilow+1)){ |
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50 | std::cerr << "Whoops!! count (" << count <<") doesn't equal what it should (" |
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51 | << (ihigh-ilow+1) << ")!!\n"; |
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52 | std::exit(1); |
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53 | } |
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54 | |
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55 | if(fabs(count*sumxx-sumx*sumx)<1.e-6) return 1; |
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56 | else{ |
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57 | slope = (count*sumxy - sumx*sumy)/(count*sumxx - sumx*sumx); |
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58 | errSlope = count / (count*sumxx - sumx*sumx); |
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59 | intercept = (sumy*sumxx - sumxy*sumx)/(count*sumxx - sumx*sumx); |
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60 | errIntercept = sumxx / (count*sumxx - sumx*sumx); |
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61 | |
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62 | r = (count*sumxy - sumx*sumy)/(sqrt(count*sumxx-sumx*sumx)*sqrt(count*sumyy-sumy*sumy)); |
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63 | return 0; |
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64 | } |
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65 | } |
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