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//Example 6-24// //Solve multiple output equation using mapping// clc //clears the window// clear //clears all existing variables// disp('f1=Sigma m(0,1,2,4,6,7,10,14,15)') //First function is displayed// disp('f2=Sigma m(3,4,5,9,10,11,14) ') //Second function is displayed// disp('f1.f2=Sigma m(4,10,14)') //Taking the common entries// disp('Mapping for f1.f2') disp(' C''D'' C''D CD CD'' ') disp('A''B'' 0 0 0 0 ') disp('AB'' 1 0 0 0 ') disp('AB 0 0 0 1 ') disp('AB'' 0 0 0 1 ') disp(' From the map, high outputs for 4,10,14') //given logic equation// a=[0 1 0 0;1 0 1 0;1 1 1 0] disp(a) for i=1: 3 if a(i,1)==1 then b(i,1)='A' else b(i,1)='A''' end if a(i,2)==1 then b(i,2)='B' else b(i,2)='B''' end if a(i,3)==1 then b(i,3)='C' else b(i,3)='C''' end if a(i,4)==1 then b(i,4)='D' else b(i,4)=' D'' ' end end disp(' evaluating expression from truth table and map ') l=strcat([ b(1,1),b(1,2),b(1,3),b(1,4)]) m=strcat([ b(2,1),b(2,2),b(2,3),b(2,4)]) n=strcat([ b(3,1),b(3,2),b(3,3),b(3,4)]) x=strcat([l"+",m"+",n]) disp(x) //Expression is displayed// disp('now reducing expression using boolean algebra') disp('ACD''+A''BC''D''')
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//chapter 5 example 4 //============================================================================= clc; clear; //Given Data Va = 40*10^3;//Anode voltage of cross field amplifier Ia = 15;//Anode current in Amp Pin = 40*10^3;//input power in watts G = 10;//gain in dB n = 40/100;//overall efficiency converted from percentage to decimal //Calculations //Gain = (1+(Pgen/Pin)) Pgen = (G-1)*Pin//Generated power ne = (Pgen/(Va*Ia))//electronic efficiency nc = n/(ne)//circuit efficiency Pout = Pin+(Pgen*nc)//output power //Output mprintf('Electronic Efficiency is %3.2f\n Output power is %g KW',ne,Pout/1000); //=============================================================================
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// Exa 4.36 clc; clear; close; // Given data V_BB = 5;// in V V_BE = 0.7;// in V R_B = 680;// in kohm R_B = 680*10^3;// in ohm I_B = (V_BB-V_BE)/R_B;// in A disp(I_B*10^6,"The base current in µA is : ") beta_dc= 150; I_C = beta_dc * I_B;// in A disp(I_C*10^3,"The collector current in mA is"); V_CC = 5;// in V R_C = 470;// in ohm V_CE = V_CC-(I_C*R_C);// in V disp(V_CE,"Voltage between collector and ground in V is ");
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function L = filternorm(b,a,varargin) // Calculates the L-2 norm or L-infinity norm of a digital filter // // Calling Sequence // L = filternorm(b,a) // L = filternorm(b,a,pnorm) // L = filternorm(b,a,2,tol) // // // Parameters // b: The filter numerator coefficients. // a: The filter denominator coefficients. // pnorm: The L-norm to be calculated. The values accepted are 2 (L2 norm) or %inf (L-infinity norm). Default value is 2. // tol: The tolerance of the L-2 norm to be calculated. If tol not specified, it defaults to 10^(-8). tol must be a positive scalar // // // Examples // // 1) L-2 norm of an IIR filter with tol = 10^(-10) // b = [-3 2]; // a = [1 -0.5]; // L = filternorm(b, a, 2, 10d-10); // // // See also // norm // zp2sos // // Authors // Ayush Baid exec('impz.sci', -1); // ** Check on number of input, output arguments [numOutArgs, numInArgs] = argn(0); if numInArgs<2 | numInArgs>4 then msg = "filternorm: Wrong number of input argument; 2-4 expected"; error(77,msg); end if numOutArgs~=1 then msg = "filternorm: Wrong number of output argument; 1 expected"; error(78,msg); end // ** Check on b and a ** if isempty(a) then a = 1; end if isempty(b) then b = 1; end b = b(:); a = a(:); // check on datatype if type(b)~=1 & type(b)~=8 then msg = "filternorm: Wrong type for argument #1 (b): Real or complex matrix expected"; error(53,msg); end if type(a)~=1 & type(a)~=8 then msg = "filternorm: Wrong type for argument #2 (a): Real or complex matrix expected"; error(53,msg); end // check on dimensions if size(b,1)==1 then b = b(:); end if size(a,1)==1 then a = a(:); end if size(b,2)~=size(a,2) then msg = "filternorm: Wrong size for arguments #1 (b) and #2(a): Same number of columns expected"; error(60,msg); end // ** Parsing the remaining arguments ** if length(varargin)==1 & ~isempty(varargin) then pnorm = varargin(1); tol = 1e-8; elseif length(varargin)==2 then pnorm = varargin(1); tol = varargin(2); if tol<=0 | length(tol)~=1 then msg = "filternorm: Wrong value for argument #4 (tol): Must be a positive real scalar"; error(116,msg); end else pnorm = 2; tol = 1e-8; end if pnorm~=2 & length(varargin)==2 then msg = "filternorm: Warning - Wrong value for argument #3 (pnorm): Must be 2 when tolerance is used"; end // ** Calculations ** if isinf(pnorm) then // We need to compute the frequency response and then get the one // with the highest magnitude h = frmag(b, a, 1024); L = max(h); else if size(a,1) == 1 then // the filter is FIR; impluse response is the filter coeffs L = norm(b,pnorm)/a; else // the filter is IIR // Checking for stability, as we wont be able to calc impulse response // within a given tolerance. pole_mag = abs(roots(a)); // stability check max_dist = max(pole_mag); if max_dist>=1 then // poles lie on the unit circle or outside it. We do not have a // decaying impulse response and hence truncation is not advisable msg = "filternorm: Non convergent impulse response. All poles should lie inside the unit circle"; error(msg); end // **** // Theory: (assuming stable filter) // Each pole will contribute a decaying exponential. The pole with // the highest magnitude will decay the slowest (i.e. will be the most // dominant). Therefore, we will work with pole(s) having the largest // magnitude to obtain a bound on the L2 norm of the tail. // **** // get the multiplicity of the largest pole mult = sum(pole_mag>(max_dist-1e-5) & pole_mag<(max_dist+1e-5)); // Using integration of a^(-x) to get a bound N = mult*log(tol)/log(max_dist); // TODO: get filter coeffs using impzlength from octave [h, temp1] = impz(b,a); L = norm(h,2); end end endfunction
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clc // initialization of variables T1=20+273 // initial temperature in kelvin P1=200 // pressure in kPa V=2 //volume in m^3 R=0.287 // gas constant for air W=-720 // negative as work is done on air in kJ //solution m=(P1*V)/(R*T1)// mass of air u1=209.1 //specific internal energy of air at 293K and 200 kPa from table E.1 s1=1.678 // by interpolation from table E.1 // change in internal energy= work done u2=-(W/m)+u1 // final internal energy T2=501.2// final temperature interpolated from table E.1 corresponding to value of u2 s2=2.222 // value of s from table E.3 by interpolating from corresponding to value of u2 P2=P1*(T2/T1) // final pressure in kPa delS=m*(s2-s1-R*log(P2/P1))// entropy change printf(" The Entropy increase is %.3f kJ/K ",delS)
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funcprot(0);clc; //Example 9.8 //Initializing the variables V = 300 ;// Volume rate w = 3; d = 65; l = 30; scaleH = 30/1000/18; scaleV = 1/60; ZmByZr = 1/60; LmByLr = 1/600; rho = 1000; mu = 1.14*10^-3; //Calculations Vr = V/(w*d); Vm =Vr*sqrt(ZmByZr); m = (w*d*scaleH*scaleV)/(d*scaleH + 2*w*scaleV); Rem = rho*Vm*m/mu; TmByTr = LmByLr*sqrt(1/ZmByZr); Tm = 12.4*60*TmByTr; disp(Tm, "Tidal Period (minutes):");
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cha8_4.sce
Lw=30;R=15;Ia=3;V=45; Tow=Lw/R t1=0.7*Tow t0=0:0.1:t1; t=0; a=integrate('45*(-3+6*%e^(-x/2))','x',t,t0) Energy=(1/2)*Lw*Ia^2 ProEnergy=(a/Energy)*100
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kirillin/manipulator_dynamics
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chis_estimater.sce
//////////////////////////////////////////////////////////////////////// //////// SCRIPT FOR ESTIMATION AND PLOTING PARAMETERS .../////////////// //////////////////////////////////////////////////////////////////////// clc(); //clear; stacksize('max'); //////////////////////////////////////////////////////////////////////// ////////// INITIALIZATION ////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////// path = get_absolute_file_path("chis_estimater.sce"); path = path + "../data_for_identification_Youbot/"; QTY_FILES = 10; QTY_JOINTS = 5; QTY_COLS = 70; TOTAL_COLS = 70; LINEAR_COLS = [2,3,4,6,7,8,9,0,1,5,17,18,20,31,10,14,32,15,16,19,21,22,23,61]+1; TITLES = ["m_{%d}","mx_{c%d}","my_{c%d}","mz_{c%d}","I_{%d,xx}","I_{%d,yy}","I_{%d,zz}","I_{%d,xy}","I_{%d,xz}","I_{%d,yz}","I_{a, %d}","f_{v,%d}","f_{c,%d}","f_{off,%d}"]; function [xi,tau]=read_measuarments(_path, _data_type, number) // !!! need global xi and tau // _type: filt or raw // number: number of file // Example for path to file "/home/data/bigs/filt/big_xi1.txt" // [xi,tau]=read_measuarments("/home/data/", "filt", 1); fn_xi = _path + sprintf("bigs_full/%s/big_xi%d.txt", _data_type, number); fn_tau = _path + sprintf("bigs_full/%s/big_tau%d.txt", _data_type, number); xi = read(fn_xi, -1, QTY_COLS); tau = read(fn_tau, -1, 1); printf("Was read: xi[%d, %d], tau[%d, %d]\n", length(xi(:,1)),length(xi(1,:)),length(tau(:,1)), length(tau(1,:))) endfunction function [xi,tau]=normalization(xi, tau) //NORMALIZING DATA sz = size(xi); m = sz(1) / QTY_JOINTS; for i = 1:QTY_JOINTS taus(:,i) = tau(i:QTY_JOINTS:sz(1),:); end for i = 1:QTY_JOINTS norma(i) = norm(taus(:, i)) end winH=waitbar('Нормировка данных...'); for i = 1:sz(1) waitbar(i/sz(1),winH); tau(i) = tau(i) / norma(pmodulo(i-1, QTY_JOINTS)+1); xi(i, :) = xi(i, :) / norma(pmodulo(i-1, QTY_JOINTS)+1); end close(winH); clear taus; endfunction function Chis=estimate_chis(_data_type, method_id) Chi = zeros(QTY_COLS, QTY_FILES); est_Chi_k_1 = zeros(QTY_COLS, 1); for i = 1:QTY_FILES [xi,tau]=read_measuarments(path, _data_type, i); // [xi,tau]=normalization(xi, tau); select method_id case 1 then Chi(:, i) = xi \ tau; case 2 then Chi(:, i) = lsq(xi, tau); case 3 then // Sigma = 0.0001 * eye(QTY_COLS, QTY_COLS); // Chi(:,l) = inv(xi' * xi + Sigma) * xi' * tau; Chi(:, i) = inv(xi' * xi) * xi' * tau; case 4 then [U,S,V] = svd([xi]); Splus = inv(S' * S) * S'; Chi(:, i) = V * Splus * U' * Tau; case 5 then [U,S,V] = svd([xi, tau]); Chi(:, i) = - V(1:$-1, $) / V($, $); case 6 then p = QTY_JOINTS; sz = size(xi); m = sz(1) / QTY_JOINTS; r = 1; xi_k = xi((r*p-p+1):(r*p), :)'; P_k_1 = eye(QTY_COLS, QTY_COLS); g_k = P_k_1 * xi_k; eps_k_1 = zeros(p, 1); for k = 2:m do xi_k = xi(r*p-p+1:r*p, :)'; y_k = tau(r*p-p+1:r*p,:); r = r + 1; eps_k = y_k - xi_k' * est_Chi_k_1; g_k = P_k_1 * xi_k * inv(1*eye(p,p) + xi_k' * P_k_1 * xi_k); P_k = P_k_1 - g_k * xi_k' * P_k_1; est_Chi_k = est_Chi_k_1 + g_k * eps_k; ///// Plot eps // plot(k-1:k, [eps_k_1, eps_k]); ///// Plot parameters //s = est_Chi_k_1; //e = est_Chi_k; //plot(k-1:k, [s,e]); //disp(k); eps_k_1 = eps_k; P_k_1 = P_k; est_Chi_k_1 = est_Chi_k; end; Chi(:,i) = est_Chi_k; end // CLEAR MEMORY clear tau; clear xi; end Chis = Chi; endfunction function ans=in(vec, el) ans = %f; n = length(vec); for i = 1:n do if el == vec(i) then ans = %t; return; end end endfunction function [mn,_sd,psd,nsd]=sd(Chis) mn = mean(Chis, 'c'); _sd = stdev(Chis, 'c'); psd = mn + _sd; nsd = mn - _sd; endfunction function plot_chis(Chis, kolor, _data_type) n = QTY_FILES; params = 14; lables = [] for l = 1:n do lables(l) = ""; end k = 1; for i = 1:TOTAL_COLS do subplot(n, TOTAL_COLS/n, i); if in(LINEAR_COLS, i) == %f then legenda = []; sz = size(_data_type); for j = 1:sz(2) do Chi = Chis(:, (j-1)*n+1:j*n); disp(size(Chi)) [mn,_sd,psd,nsd] = sd(Chi) plot2d(1:n, Chi(k, :), kolor(j)); plot2d(1:n, ones(1, n) * psd(k), kolor(j)); plot2d(1:n, ones(1, n) * nsd(k), kolor(j)); a = gca(); a.x_ticks = tlist(["ticks", "locations", "labels"],1:1:n, string(lables')); a.font_size = 0; format('e', 8); a.y_ticks = tlist(["ticks", "locations", "labels"],[nsd(j), mn(j), psd(j)], string([nsd(j), mn(j), psd(j)])); format('v'); a.margins(1) = 0.3; a.margins(2) = 0.0; l = modulo(i, params) if l == 0 then l = params; end; a.title.text = "$"+string(sprintf(TITLES(l), ceil(i / params)))+"$"; a.title.position = [3, psd(k)]; a.title.font_size = 2; legenda(j) = string(sprintf("$sd_{%s}: {%.2f}", _data_type(j), _sd(k) / abs(mn(k)) * 100)) + "\%$" end a = gca() legend(legenda(1), legenda(2)); aa = a.children(1); aa.fill_mode = "off"; k = k + 1; else plot(0,0); a = gca(); a.font_size = 0; a.x_ticks = tlist(["ticks", "locations", "labels"],1:1:n, string(lables')); a.background = 35; a.margins(1) = 0.3; a.margins(2) = 0.0; end end endfunction function plot_taus(Chis, _data_type) p = QTY_JOINTS; for i = 1:QTY_FILES do [xi,tau]=read_measuarments(path, _data_type, i); // [xi,tau]=normalization(xi, tau); sz = size(xi); m = sz(1) / QTY_JOINTS; tau_calc = xi * Chis(:,i); scf(); for j = 1:QTY_JOINTS do subplot(2, 3, j); //subplot(QTY_FILES, QTY_JOINTS, (i-1)*QTY_JOINTS+j); plot2d(1:m, tau(j:p:sz(1)), 3); plot2d(1:m, tau_calc(j:p:sz(1)), 1); legend("raw data", 'calc data') a = gca() a.title.text = 'Link ' + string(j); end xs2pdf(gcf(), path + string(i) +'.pdf'); xs2png(gcf(), path + string(i) +'.png'); end endfunction //Chis_filt = estimate_chis("filt", 1) //mean_Chi_filt = mean(Chis_filt,'c') //plot_taus(mean_Chi_filt, "filt"); //Chis_raw = estimate_chis("raw", 1) //plot_taus(Chis_raw, "raw"); plot_chis([Chis_filt, Chis_raw], [2, 5], ["filt", "raw"])
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Ex6_4.sce
// Variable Declaration E = 40.0 //Safe working stress(kV/cm) rms d = 1.5 //Conductor diameter(cm) D = 6.7 //Sheath diameter(cm) t = 0.1 //Thickness of lead tube(cm) // Calculation Section r = d/2 //Conductor radius(cm) R = D/2 //Sheath radius(cm) r_i = r+((R-r)/2)-t/2 //Internal radius of intersheath(cm) r_e = r_i + t //External radius of intersheath(cm) V_1 = E*r*log(r_i/r) //Voltage across conductor & intersheath(kV) V_2 = E*r_e*log(R/r_e) //Voltage across intersheath & earthed sheath(kV) V = V_1 + V_2 //Safe working voltage with intersheath(kV) V_no = E*r*log(R/r) //Safe working voltage without intersheath(kV) // Result Section printf('Safe working voltage with intersheath , V = %.2f kV' ,V) printf('Safe working voltage without intersheath , V = %.2f kV' ,V_no)
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r = 30; T = 600; theta = 25; val1 = cdfchi("PQ", 2*T/theta, 2*r); val2 = 1- cdfchi("PQ", 2*T/theta, 2*(r+1)); pvalue = min(val1, val2); disp(pvalue, "The pvalue is"); disp("H0 would be accepted when the significance level is 0.10");
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load Mux16.hdl, output-file Mux16.out, compare-to Mux16.cmp, output-list ip1%B1.16.1 ip2%B1.16.1 s%D2.1.2 out%B1.16.1; set ip1 0, set ip2 0, set s 0, eval, output; set s 1, eval, output; set ip1 %B0000000000000000, set ip2 %B0001001000110100, set s 0, eval, output; set s 1, eval, output; set ip1 %B1001100001110110, set ip2 %B0000000000000000, set s 0, eval, output; set s 1, eval, output; set ip1 %B1010101010101010, set ip2 %B0101010101010101, set s 0, eval, output; set s 1, eval, output;
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R=0.15//rise, in m t=0.3//tread, in m sigma_cbc=5//in MPa sigma_st=230//in MPa l1=1.8+1.5//span for flight AB, in m l2=1.2+1.5+1.5//span for flight BC, in m l3=1.8+1.5//span for flight CD, in m //assuming 50 mm slab thickness per 1 m of span D=50*l2//slab thickness, in mm W1=D/10^3*25*1.5*sqrt(R^2+t^2)/t//slab load on plan, in kN/m W2=1/2*R*t*1.5*25/t//load of step per metre, in kN/m W3=1.5*5//live load, in kN/m W=W1+W2+W3//in kN/m //bending moment //(a) flight AB and CD, refer Fig. 10.9 Rb=(W/2*1.5*(1.8+1.5/2)+W*1.8^2/2)/(1.5+1.8)//in kN Ra=W/2*1.5+W*1.8-Rb//in kN x=Ra/Rb//point of zero shear force from Ra, in m M1=Ra*x-W*x^2/2//maximum bending moment, in kN-m //(b) flight BC, refer Fig. 10.10 Rb=(W/2*1.5^2/2+W*1.2*(1.2/2+1.5)+W/2*1.5*(1.5+1.2+1.5/2))/(1.5+1.2+1.5)//in kN Rc=Rb//in kN //maximum bending moment will be at centre M2=Rb*(1.5+1.2/2)-W/2*1.5*(1.5/2+1.2/2)-W*(1.2/2)^2/2//maximum bending moment, in kN-m M=max(M1,M2)//in kN/m d=sqrt(M*10^6/0.65/1.5/10^3)//in mm //assume 10 mm dia bars dia=10//in mm D=d+dia/2+25//< 210 mm (assumed value) D=210//in mm d=D-dia/2-25//in mm //steel //flight AB and CD z=0.9*d//in mm Ast=M1*10^6/sigma_st/z//in sq mm s1=1500*0.785*dia^2/Ast//spacing of 10 mm dia bars, in mm s1=210//round-off, in mm Ads=0.12/100*D*1.5*10^3//distribution steel, in sq mm //provide 6 mm dia bars s2=1000*0.785*6^2/Ads//in mm s2=70//round-off, in mm //flight BC Ast=M2*10^6/sigma_st/z//in sq mm s3=1500*0.785*dia^2/Ast//spacing of 10 mm dia bars, in mm s3=130//round-off, in mm //distribution steel is same as flights AB and CD //let span-to-depth ratio be 'a' a=l2*10^3/D //for Fe415 grade steel and pt=.32 MF=1.2//modification factor b=20*MF//permissible span-to-depth ratio //as a < b, hence OK mprintf("Summary of design\nSlab thickness=%d mm\nCover = 25 mm\n(a)Flight AB and CD\nMain steel = 10 mm dia bars @ %d mm c/c\nDistribution steel = 6 mm dia @ %d mm c/c\n(b)Flight BC\nMain steel = 10 mm dia bars @ %d mm c/c\nDistribution steel = 6 mm dia @ %d mm c/c",D,s1,s2,s3,s2) //answer in textbook is incorrect
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clc;funcprot(0);//Example 2.38 //Initilisation of Variables t=0.001;....//Thickness of copper plate in m L=0.15;....//Height of plate in m K=60;....//thermal conductivity of wall material in W/m*degrees celcius Tb=50;....//temparature of pipe wall in degrees celcius Th=100;....//temparature reading in thermometer in degrees celcius h=25;....//heat transfer coefficient batween air and well wall in W/m^2 //calculations m=sqrt(h/(K*t));....// Tf=((50/cosh(m*L))-Th)/((1/cosh(m*L))-1);...//temparature of air in degrees celcius e=Tf-Th;....//error in reading in degrees celcius p=(e/Tf)*100;....//percentage error in % disp(Tf,"temparature of air in degrees celcius:") disp(p,"percentage error in %:")
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//Mission A4 //On récupère les deux images. pathname = "C:\Users\Jean-Guillaume P\Documents\Exia\A2\Projets\Imagerie\ExoLife\Images\Mission_A\Jupiter1.pbm"; pathname2 = "C:\Users\Jean-Guillaume P\Documents\Exia\A2\Projets\Imagerie\ExoLife\Images\Mission_A\Jupiter2.pbm"; jupiter1 = readpbm(pathname); jupiter2 = readpbm(pathname2); //On "extrait" le bruit des images. bruitJupiter = soustractionImage(jupiter1, jupiter2); //On soustrait le bruit obtenu précédemment de l'image de Jupiter. jupiterFinal1 = soustractionImage(jupiter1, bruitJupiter); //On "affine" l'image avec le filtre médian, faisant ainsi disparaître le bruit. jupiterFinal2 = filtreMedian(jupiterFinal1); // Affichage figure; display_gray(bruitJupiter); figure; display_gray(jupiterFinal1); figure; display_gray(jupiterFinal2); // Sauvegarde de l'image writepbm(jupiterFinal2, "C:\Users\Jean-Guillaume P\Documents\Exia\A2\Projets\Imagerie\ExoLife\Rendus\MissionA4.pbm");
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//******************************************************** // animation d'un pendule élastique //******************************************************** // fonction pour créer la matrice de rotation function M=rot(a) M=[cos(a),sin(a);-sin(a),cos(a)]; endfunction // quelques constantes n=40; // nombre de spires du ressort T=5; // durée de la simulation g=9.81; // g (gravitation) k=10; // k (raideur du ressort) dt=0.01; // dt (pas de temps) //******************************************************** // lancement de l'affichage //******************************************************** // titre de la fenêtre xtitle("(clic gauche pour démarrer l''animation, clic droit pour arrêter)") // page de titre (en LaTeX) titlepage(["résolution numérique d''une EDO le pendule à ressort : "; " "; "$$\Large r{d^2\over dt^2}a+2{d\over dt}r \times {d\over dt}a=g\times \sin(a)$$"; " "; "$$\Large {d^2\over dt^2}r-{k\over m}(r-r_0)=r\left({d\over dt} a\right)^2+g\times \cos(a)$$"; " "; " avec les conditions initiales : "; "$$\Large a(0)=? \;\;\;\;\;\; {d\over dt}a(0)=0 \;\;\;\;\;\; r(0)=r_0=? \;\;\;\;\;\; {d\over dt}r(0)=0 $$"]) //******************************************************** // traitement des interactions avec la fenêtre graphique //******************************************************** [c_i,c_x,c_y,c_w]=xclick(); // attente d'un clic de souris dans la fenêtre while (c_i<>2)&(c_i<>5) // tant qu'on n'a pas fait un clic droit clf() //effacer la fenêtre //******************************************************** // récupération des données initiales de l'animation //******************************************************** // titre de la fenêtre xtitle("(un click pour initialiser la position du pendule, a(0) et r(0) )") // paramétrage du handle Axes de la fenêtre plot(0,0,'.k');A=gca();A.x_location="origin";A.y_location="origin"; A.auto_scale="off";A.isoview="on";A.data_bounds=[-1 -1; 1,0];xgrid(3) //récupération des coordonnées de la position initiale du pendule [c_i,x,y,c_w]=xclick(); // calcul des données initiales a=sign(x)*abs(atan(x/y));a0=a;da=0; // calcul de l'angle a(0) l=sqrt(x^2+y^2);r=l;,dr=0; // calcul de r(0) //adapter la taille de la fenêtre à la taille maximale du pendule A.data_bounds=[-1.5,-max(4*l,4);1.5,max(l,0.5)]; //******************************************************** // boucle créant l'animation //******************************************************** for t=0:dt:T //******************************************************** // calcul des nouvelles positions //******************************************************** // résolution des équations différentielles sur a et r par la méthode d'Euler dda=-(g*sin(a)+2*dr*da)/r; ddr=r*(da)^2-k*(r-l)+g*cos(a); da=da+dt*dda; dr=dr+dt*ddr; a=a+dt*da; r=r+dt*dr; // calcul de la ligne traçant le ressort ressortr=linspace(0,r,n)'; // étirement du ressort ressorta=[0;(-1).^[0:n-3]';0]*(l/10); // coordonnées transversales à l'axe du ressort -> /\/\/\ //rotation de l'image du ressort selon l'angle a x=[x;r*sin(a)]; y=[y;-r*cos(a)]; M=-rot(-a); N=[ressortr,ressorta]*M; ressorty=N(:,1);ressortx=N(:,2); //******************************************************** // affichage du pendule //******************************************************** drawlater() // écriture dans le buffer graphique clf() // effacer la fenêtre plot(ressortx,ressorty) // affichage du ressort du pendule xstring(0,0.1,["t=" string(t)]) // temps écoulé xfarc(r*sin(a)-0.05,-r*cos(a)+0.05,0.1,0.1,0,360*64) // la boule du prendule // redimensionnement de la fenêtre graphique A=gca();A.data_bounds=[-1.5,-max(4*l,4);1.5,max(l,0.5)]; A.auto_scale="off";A.isoview="on";A.axes_visible=["off" "off" "off"]; drawnow() // afficher le buffer graphique sleep(10); // delai d'affichage end //*********************************************************** // choix d'une nouvelle animation ou d'une sortie du script //*********************************************************** xtitle("(un clic pour continuer )") // titre de la fenêtre plot(x,y,'-r') // affichage trajectoire A=gca();A.isoview="on";xgrid(3); // afficher une grille (verte) [c_i,x,y,c_w]=xclick(); // attente d'un clic de souris dans la fenêtre graphique clf(); // choix d'une nouvelle action xtitle("(clic gauche pour démarrer l''animation, clic droit pour arrêter)") plot(0,0,'.k');A=gca();A.x_location="origin";A.y_location="origin"; [c_i,x,y,c_w]=xclick(); //attente d'un clic de souris dans la fenêtre end
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// Variable declaration n = 50 Meanx = 88.34 Meany = 305.58 s1 = 7239.22 s2 = 17840.1 s3 = 66975.2 x = [] for i = 60:119 x(i) = i end // Calculation Slope1 = s2/s1 c1 = Meany - (s2/s1)*Meanx Slope2 = s2/s3 c2 = Meanx - (s2/s3)*Meany // Result printf ( "Part-A: , Height = %.2f + %.3f *width",c1,Slope1) printf ( "Part-B: Height = %.2f + %.3f *width",-c2/Slope2,1/Slope2) plot(x,c1+Slope1*x) plot(x,-c2/Slope2 + x/Slope2) legend(['height = 87.88 + 2.464*width', 'height = -26.11 + 3.759*width']) xlabel("$Width$") ylabel("$Height$")
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//% Scicos pack for FLEX and EASYLAB builder exec(SCI + '/contrib/scicos_ee/utils/palette_builder.sce'); exec(SCI + '/contrib/scicos_ee/scicos_flex/dspic/macros/man/builder.sce'); message('Please, restart ScicosLab for the changes to take effect...');
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//finding transfer function from state diagram by applying gain formula //state diagram is shown in fifure 3-21 syms s //initial conditions are sset to zero M1=s^-1*s^-1 L11=-3*s^-1 L21=-2*s^-1*s^-1 delta=1-(L11+L21) delta1=1 x=M1*delta1/delta disp(x,"Y(s)/R(s)=")
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errcatch(-1,"stop");mode(2); x=poly([0],'x'); p=x^4-2*(x^3)-21*(x^2)+22*x+40 disp("the roots of above equation are ") roots(p) exit();
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//Example No. 5.23 clc; clear; close; format('v',9); //Given Data : T1=40;//N-m N1=500;//rpm J=0.01;//N-m_sec^2/rad T2=100;//N-m N2=1000;//rpm disp("Te=J*d(omega)/dt+D*omega+TL"); d_omegaBYdt=(T2-T1)/J;// //t=omega/d_omegaBYdt+A; omega1=N1*2*%pi/60;//rad/s t=0;//s(initial time) A=t-omega1/d_omegaBYdt;// omega2=N2*2*%pi/60;//rad/s t=omega2/d_omegaBYdt+A;//s disp(t,"Time taken by the motor in sec : ");
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//example 5.11 //calculate discharge if one well discharges //percent decrease when two well discharges clc; //given d=0.2; //diameter of well r=d/2; B=100; //distance between wells b=12; //thickness of acquifer k=60; //coefficient of permeability s=3; //dispersion head R=250; //radius of influence Q=2.72*b*k*s/(24*log10(R/r)); mprintf("discharge if one well discharges=%i cubic metre/hour.",Q); //when both well are discharging Q1=2.72*k*b*s/(24*log10(R^2/(r*B))); Q1=round(Q1*10)/10; mprintf("\ndischarge if both wells discharges=%f cubic metre/hour.",Q1); PE=(Q-Q1)*100/Q; PE=round(PE*100)/100; mprintf("\npercentage decrease in discharge=%f percent.",PE);
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// Copyright INRIA files=G_make(['/tmp/ex1fi.o','/tmp/ex1f.o'],'ex1f.dll'); addinter(strcat(files,' '),'foobarf','foubaref'); a=1:10;b=a+1;c=ones(2,3)+2; [x,y,z,t]=foubaref('mul',a,b,c); // Check the result if norm(t-(a*2)) > %eps then pause,end if norm(z-(b*2) ) > %eps then pause,end if norm(y-(c*2)) > %eps then pause,end deff('[y]=f(i,j)','y=i+j'); if norm(x- ( y.* feval(1:2,1:3,f))) > %eps then pause,end [x,y,z,t]=foubaref('add',a,b,c); // Check the result if norm(t-(a+2)) > %eps then pause,end if norm(z-(b+2) ) > %eps then pause,end if norm(y-(c+2)) > %eps then pause,end deff('[y]=f(i,j)','y=i+j'); if norm(x- ( c +2 + feval(1:2,1:3,f))) > %eps then pause,end
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clear // // // //Variable declaration x=15 //distance(cm) d=0.005 //diameter(cm) lamda=6000*10**-8 //wavelength(cm) //Calculation alpha=d/x //angle(radian) beta1=lamda/(2*alpha) //fringe width(cm) //Result printf("\n fringe width is %0.3f cm",beta1)
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Ex7_11.txt
//Caption: Calculate Power and torque developed //Exa:7.11 clc; clear; close; p=4//Number of poles d=20//Diameter of armature(in cm) l=25//Core length(in cm) c=300//Number of conductors i_a=50//Armature current(in A) B=0.3//Average flux density(in weber/m^2) n=1000//Speedofmotor(in r.p.m) T=(B*(l/100)*(i_a/p)*c*(d/100)*(1/2)) s=(2*%pi*n)/(60) P=(T*s)/1000 disp(T,P,'Power(in KW) and Torque(in Nm) developed is=')
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// A Texbook on POWER SYSTEM ENGINEERING // A.Chakrabarti, M.L.Soni, P.V.Gupta, U.S.Bhatnagar // DHANPAT RAI & Co. // SECOND EDITION // PART IV : UTILIZATION AND TRACTION // CHAPTER 5: ELECTRIC TRACTION-SPEED TIME CURVES AND MECHANICS OF TRAIN MOVEMENT // EXAMPLE : 5.12 : // Page number 784-785 clear ; clc ; close ; // Clear the work space and console // Given data W = 200.0 // Trailing weight(tonne) G = 1.0 // Gradient(%) alpha = 1.0 // Acceleration(km phps) u = 0.2 // Co-efficient of adhesion r = 50.0 // Train resistance(N/tonne) I = 10.0 // Rotational inertia(%) // Calculations W_L = ((277.8*(100+I)/100*alpha)+98.1*G+r)*W/(u*9.81*1000-((277.8*(100+I)/100*alpha)+98.1*G+r)) // Weight of locomotive(tonnes) // Results disp("PART IV - EXAMPLE : 5.12 : SOLUTION :-") printf("\nMinimum adhesive weight of a locomotive, W_L = %.1f tonnes\n", W_L) printf("\nNOTE: ERROR: Calculation mistake in textbook solution in calculating W_L")
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ah ha ah ha and aha ah ha and aha
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example1_25.sce
// Find drift velocity,mobility,conductivity // Basic Electronics // By Debashis De // First Edition, 2010 // Dorling Kindersley Pvt. Ltd. India // Example 1-25 in page 51 clear; clc; close; // Data given A=0.835*10^-6; // Cross section of wire in m^2 J=2.4*10^6; // Current density in A/m^2 n_0=8.4*10^27; // Concentration of electrons in copper in electrons/m^3 e=1.6*10^-19; // Charge on an electron in C ohm=0.0214; // Resistance per meter E_0=2*ohm; // Electric field in V/m // Calculations v_0=(J)/(n_0*e); printf("(a)The drift velocity is %0.2e m/s\n",v_0); mu=v_0/E_0; printf("(b)The mobility of electrons is %0.2e m^2/V-s\n",mu); sigma=(n_0*10*e*mu); printf("(c)Therefore the conductivity is %0.2e /ohm-m",sigma); // Result // (a) The drift velocity is 1.78*10^-3 m/s // (b) Mobility in this case is 4.16*10^-2 m^2/V-s // (c) Conductivity is 5.61*10^8 1/ohm-m
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//stability of open loop systems s=%s sys1=syslin('c',20/((s+1)*(s+2)*(s+3))) disp(sys1,"M(s)=") printf("sys1 is stable as there are no ploes or zeroes in RHP") sys2=syslin('c',20*(s+1)/((s-1)*(s^2+2*s+2))) disp(sys2,"M(s)=") printf("sys2 is unstable due to pole at s=1") sys3=syslin('c',20*(s-1)/((s+2)*(s^2+4))) disp(sys3,"M(s)=") printf("sys3 is marginally stable or marginally unstable due to s=j2 and s=-j2") sys4=syslin('c',10/((s+10)*(s^2+4)^2)) disp(sys4,"M(s)=") printf("sys4 is unstable due to multiple order pole at s=j2 and s=-j2") sys5=syslin('c',10/(s^4+30*s^3+s^2+10*s)) disp(sys5,"M(s)=") printf("sys5 is stable if pole at s=0 is placed intentionally")
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W=20//N(weight of a flour bag) g=9.81//m/s^2(Acceleration due to gravity on the earth)
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nickgreenquist/Intro_To_Intelligent_Systems
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@relation abalone @attribute Sex{M,F,I} @attribute Length real[0.075,0.815] @attribute Diameter real[0.055,0.65] @attribute Height real[0.0,1.13] @attribute Whole_weight real[0.002,2.8255] @attribute Shucked_weight real[0.001,1.488] @attribute Viscera_weight real[5.0E-4,0.76] @attribute Shell_weight real[0.0015,1.005] @attribute Rings{15,7,9,10,8,20,16,19,14,11,12,18,13,5,4,6,21,17,22,1,3,26,23,29,2,27,25,24} @inputs Sex,Length,Diameter,Height,Whole_weight,Shucked_weight,Viscera_weight,Shell_weight @outputs Rings @data 10 8 7 7 19 11 16 10 4 7 10 8 14 9 10 10 15 9 7 9 7 6 7 6 10 10 10 10 10 9 15 9 7 8 8 8 5 6 13 10 10 9 9 9 18 9 8 7 16 11 15 9 14 11 16 10 16 10 10 9 8 8 19 10 13 8 14 9 9 9 13 9 16 9 11 9 9 7 6 6 5 6 5 4 17 9 13 9 11 10 15 10 12 9 16 9 3 7 13 8 17 10 13 10 13 9 11 8 20 9 14 9 14 8 9 9 12 10 12 8 9 6 7 6 9 8 11 8 6 6 13 9 22 9 11 8 11 9 15 9 14 9 10 8 9 9 13 9 9 8 9 8 15 9 8 9 9 9 9 9 11 10 10 10 17 11 9 10 7 8 8 8 9 9 8 9 8 9 7 9 7 9 8 9 11 10 11 10 9 10 10 10 6 10 8 11 4 7 7 6 6 8 7 8 6 8 7 8 7 9 8 8 9 9 8 9 8 9 9 9 9 9 10 10 12 11 9 9 12 11 6 7 6 9 5 9 7 8 9 8 8 8 8 8 8 8 8 8 8 9 7 8 9 9 10 9 10 10 10 9 11 9 12 9 10 10 11 10 9 10 11 11 10 10 10 11 13 11 8 8 6 8 9 9 9 9 8 9 9 9 9 10 10 10 8 10 10 11 12 10 11 10 13 11 6 7 7 7 7 9 9 8 8 8 7 8 9 9 9 9 10 9 9 9 9 9 8 9 10 10 9 9 8 9 10 9 10 9 11 10 11 10 11 10 9 9 11 10 14 10 12 10 11 11 10 11 11 11 11 11 12 11 12 12 6 8 10 10 11 11 9 11 10 11 11 11 7 9 11 9 9 10 12 10 12 10 6 6 7 7 7 7 10 8 9 9 9 9 9 9 8 9 7 9 12 11 10 11 10 9 13 10 7 9 10 9 7 7 6 6 8 8 12 8 10 8 10 8 5 6 27 11 7 8 11 11 14 10 14 10 11 8 15 9 9 9 17 11 20 11 13 11 8 8 11 9 12 8 11 8 10 6 17 9 12 9 18 8 6 6 14 9 23 9 14 9 9 9 13 9 11 8 6 8 7 8 9 10 10 10 6 8 8 8 8 9 6 9 7 9 9 10 9 10 13 11 10 11 9 9 11 10 9 10 11 10 13 11 8 8 7 9 8 9 10 9 9 9 10 9 9 9 10 9 11 10 5 6 5 7 9 9 9 9 10 9 9 9 8 9 11 11 7 8 9 9 8 9 8 9 8 9 10 10 9 9 13 10 11 10 12 10 13 10 9 10 12 11 8 8 7 8 8 9 11 10 7 9 8 7 9 8 8 8 10 9 10 9 11 11 9 9 10 9 11 9 8 10 5 6 5 9 10 10 11 9 10 9 21 10 13 10 18 11 8 9 19 11 11 9 14 8 12 8 11 9 15 9 12 9 17 10 10 8 12 8 8 7 12 9 13 8 11 8 12 8 16 8 18 10 9 6 4 7 7 9 7 8 10 9 10 10 9 10 4 6 4 6 6 6 8 8 9 8 9 9 9 9 9 9 10 9 8 9 9 10 12 10 5 9 8 8 8 9 7 9 6 8 9 9 8 9 10 9 10 9 10 10 11 11 11 10 10 11 9 9 10 11 6 9 8 8 9 9 10 11 7 7 6 9 8 8 8 8 9 9 10 9 10 9 11 9 6 6 14 9 9 9 15 10 15 10 7 9 12 9 13 9 12 9 5 6 11 11 10 11 6 6 8 9 8 10 6 6 6 7 8 10 11 10 8 8 7 9 11 9 10 9 9 9 10 10 8 9 6 9 7 9 7 8 8 9 9 10 9 10 11 10 4 6 10 9 11 10 10 10 11 10 6 8 8 8 8 6
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//Example NO.11.7 //Page No.337 clc;clear; E0 = (8.854*10^-12); x = (4.94);//Relative suceptibility. N = (10^28);//Number of dipoles per unit volume [per m^3]. a = ((E0*x)/N);//Polarizability of the material printf("\nPolarizability of the material is %3.3e F m^-2",a);
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function mdaqAOScanStart(arg1, arg2) if argn(2) == 0 then mdaqAOScan() elseif argn(2) == 1 & type(arg1) == 1 then mdaqAOScan(arg1) elseif argn(2) == 1 & type(arg1) == 10 then mdaqAOScanTrigger(arg1) mdaqAOScan() elseif argn(2) == 2 & type(arg1) == 1 & type(arg2) == 10 then mdaqAOScanTrigger(arg2) mdaqAOScan(arg1) else error("Wrong imput argument"); end endfunction
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//Example 2.1 clc;clear;close; A=1;T=2; w0=2*%pi/T; //Calculation of trignometric fourier series co-efficients a0=A/T*(integrate('-1','t',-T/2,-T/4)+integrate('+1','t',-T/4,T/4)+integrate('-1','t',T/4,T/2)); for n=1:10; a(1,n)=2*A/T*(integrate('-cos(n*w0*t)','t',-T/2,-T/4)+integrate('+cos(n*w0*t)','t',-T/4,T/4)+integrate('-cos(n*w0*t)','t',T/4,T/2)); b(1,n)=2*A/T*(integrate('-sin(n*w0*t)','t',-T/2,-T/4)+integrate('+sin(n*w0*t)','t',-T/4,T/4)+integrate('-sin(n*w0*t)','t',T/4,T/2)); end //Displaying fourier coefficients disp(T,'fundamental period T= ',A,'Assumption: Amplitude A= '); disp('Tignometric fourier series co-efficients:'); disp(a0,'a0= ');disp(a,'an= ');disp(b,'bn= '); x=[-A*ones(1,25) A*ones(1,50) -A*ones(1,25)] //Function for ploting purpose t=-T/2:0.01*T:T/2-0.01; subplot(311);plot(t,x); title('x(t)');xlabel('time t'); subplot(312);plot2d3(a); title('Coefficients an');xlabel('n'); subplot(313);plot2d3(b); title('Coefficients bn');xlabel('n');
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clc Iep=3//mA Ieh=0.01//mA Ich=0.001//mA Icp=2.99//mA gamma=Iep/(Iep+Ieh) disp(gamma,"gamma =") alphaT=Icp/Iep disp(alphaT,"alphaT =") alpha0=gamma*alphaT disp(alpha0,"alpha0 =") IE=Iep+Ieh disp(IE,"IE in mA=") IC=Icp+Ich disp(IC,"IC in mA=") ICBO=IC-alpha0*IE disp(ICBO,"ICBO in mA")
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// Test #9 : Valid case exec('./zpklp2bs.sci',-1); [z,p,k,n,d]=zpklp2bs([2 4],[8 11],7*%i,0.21,[0.54,0.8]); disp(d); disp(n); disp(k); disp(p); disp(z); // //Scilab Output //d = 1. 0.9661716 0.7419182 //n = 0.7419182 0.9661716 1. //k = 0.3853727i //p = -0.4659083 + 0.6803740i // -0.4659083 - 0.6803740i // -0.4709319 + 0.6901569i // -0.4709319 - 0.6901569i //z= -0.3839860 + 0.4869675i // -0.3839860 - 0.4869675i // -0.4448192 + 0.6372376i // - 0.4448192 - 0.6372376i // //Matlab Output //z=-0.3840 + 0.4870i // -0.3840 - 0.4870i // -0.4448 + 0.6372i // -0.4448 - 0.6372i //p=-0.4659 + 0.6804i // -0.4659 - 0.6804i // -0.4709 + 0.6902i // -0.4709 - 0.6902i //k=0.0000 + 0.3854i //n= 0.7419 0.9662 1.0000 //d= 1.0000 0.9662 0.7419
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//FOUR FUNDAMENTAL SUBSPACES //Coefficient matrix A disp('Enter the matrix A'); a11=input("Enter a11: "); a12=input("Enter a12: "); a13=input("Enter a13: "); a21=input("Enter a21: "); a22=input("Enter a22: "); a23=input("Enter a23: "); a31=input("Enter a31: "); a32=input("Enter a32: "); a33=input("Enter a33: "); A=[a11,a12,a13;a21,a22,a23;a31,a32,a33]; a=A; disp(A,"A"); //Dimensions of A [m,n]=size(A); disp(m,'m='); disp(n,'n='); //rref computes the row Echelon form of matrix A by LU transformations [v,pivot]=rref(A); disp(rref(A)); disp(v); r=length(pivot); disp(r,'rank='); ColumnSpace=A(:,pivot); disp(ColumnSpace,'Column Space='); //kernal computes the null space of the given matrix NullSpace=kernel(A); disp(NullSpace,'Null Space='); RowSpace=A(1:r,:)'; disp(RowSpace,'Row Space='); LeftNullSpace=kernel(A'); disp(LeftNullSpace,'Left Null Space=');
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//Book Name:Fundamentals of Electrical Engineering //Author:Rajendra Prasad //Publisher: PHI Learning Private Limited //Edition:Third ,2014 //Ex3_4(b).sce //case(b) clc; clear; R=1; L=0.1; C=1; I=10; s=0; //complex frequency V=(10*s)/(s^2+s+10); //voltage across the parallel circuit iG=V*R; printf("\n Current through conductance=%d A \n",iG) iC=V*C; printf("\n Current through capacitance=%d A \n",iC) iL=100/(s^2+s+10); //simplified form of V/Ls=(10s/(s^2+s+10))/(0.1s) printf("\n Current through inductance=%d A \n",iL)
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function RecPsi08() h=sumpsi08(); h.h1=Four2DBgHolo(h.h1,4,0); h.h2=Four2DBgHolo(h.h2,4,0); h.h3=Four2DBgHolo(h.h3,1,0); atsarr=MkRecArray(3,1.18/8,5*1.18); HPsi082=ReconstHoloArb(atsarr,h.h2); save('c:\mainsci\macros\psi08\recpsi08b.dat',HPsi082); HPsi083=ReconstHoloArb(atsarr,h.h3); save('c:\mainsci\macros\psi08\recpsi08b.dat',HPsi083,HPsi082); HPsi081=ReconstHoloArb(atsarr,h.h1); save('c:\mainsci\macros\psi08\recpsi08b.dat',HPsi081,HPsi082,HPsi083); endfunction
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///Chapter No 7 Fluid Mechanics ///Example 7.12 Page No 122 /// Find Intensity of pressure of water ///Input data clc; clear; Z1=1.5; //open tank contain water in m Z2=2.5; //oil of specific gravity for depth in m S=0.9; //oil of specific gravity rho1=1000; //density of water in Kg/m**3 rho2=S*10^3; //density of oil in Kg/m**3 g=9.81; //gravity ///calculation P=rho1*g*Z1+rho2*g*Z2; //Intensity of pressure in kPa ///output printf('intensity of pressure=%f N/m^2 \n',P);
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clc //initialisation of variables sw= 62.3 //lbf/ft^3 d= 288 //ft p= 1 //lbf/in^2 //CALCULATIONS P= sw*d/144 D= p*144/sw //RESULTS printf (' pressure at a depth of 288 ft= %.1f lbf/in^2',P) printf (' \n depth= %.2f ft',D)
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// Exa 7.22 clc; clear; close; // Given data R2= 834;// in Ω R3= 100;// in Ω C2= 0.124;// in µF C2= C2*10^-6;// in F C4= 0.1;// in µF C4= C4*10^-6;// in F L1= R2*R3*C4;// in H f= 2;// in kHz f= f*10^3;// in kHz disp(L1*10^3,"The value of L1 in mH is : ") R1= R3*C4/C2;// in Ω disp(R1,"The value of R1 in Ω is : ") Z= R1+%i*2*%pi*f*L1;// in Ω disp(abs(Z),"The magnitude of effective impedence in Ω is : ") disp(atand(imag(Z),real(Z)),"The angle of effective impedence in ° is : ")
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// Círculo, por Mateus de Assis /* Aqui desenha-se tão somente um arco circular (superior ou inferior) Para se utilizar a função, deve-se definir um raio (positivo ou negativo) e se o arco a ser desenhado é positivo (flag = 1) ou não(fag = -1). A chamada da função segue no exemplo: --> r = 1 -->flag = 1 -->[x,y] = circle(r,flag) -->flag = -1 Também pode-se, caso preferência, plotar o resultado obtido; -->plot(x,y) */ function [xsc,ysc] = circle(r, flag) r = abs(r); xsc = -r:.01:r; for i = 1: length(xsc) ysc(i) = sqrt(r*r-xsc(i)*xsc(i)); end if flag == -1 then ysc = -ysc elseif flag == 1 then ysc = ysc; end endfunction // Atenção! Sendo x um vetor, a chamada x*x significa multiplicação // vetorial e poderá resultar no erro de incompatibilidade dimensional // (!error 6). Assim, dado que queremos elevar cada coordenada a uma // dada potência, utilizaremos um laço for nas linhas 4~>6. Para a // manipulaçao vetorial, vale saber que o índice começa em 1 e acaba na // quantidade de termos existente.
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clc clear //Initalization of variables loss=80000 //Btu/lb t=560 //R //calculations ratio=t/68 power=loss/(ratio*2544) //results printf("Power = %.2f hp",power)
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// *********************************************************** // * ScicosLab Pack Installer * // * Requires: Scicoslab v4.4.1 * // * Built/Tested On: XP, Windows 7 * // * Description: Close link with the DLLs * // * Copyright (c) 2012 Evidence Srl * // * Author: Dario Di Stefano, Evidence * // *********************************************************** // This script is used to unlink DLLs unlink_err = 0; //% SMCUBE unlinking bfunc = 'smcube_block'; [test,ilib] = c_link(bfunc); if (test) ulink(ilib); if( c_link(bfunc) ) disp('Error: Unable to remove '+bfunc+' DLL link!'); unlink_err = -1; else disp('Removing DLL link...Done!'); end end //% Sources unlinking bfunc = 'rt_sinus'; [test,ilib] = c_link(bfunc); if (test) ulink(ilib); if( c_link(bfunc) ) disp('Error: Unable to remove '+bfunc+' DLL link!'); unlink_err = -1; else disp('Removing DLL link...Done!'); end end //% GW unlinking bfunc = 'serial_gateway_block'; [test,ilib] = c_link(bfunc); if (test) ulink(ilib); if( c_link(bfunc) ) disp('Error: Unable to remove '+bfunc+' DLL link!'); unlink_err = -1; else disp('Removing DLL link...Done!'); end end //% RS232 unlinking bfunc = 'rs232_config'; [test,ilib] = c_link(bfunc); if (test) ulink(ilib); if( c_link(bfunc) ) disp('Error: Unable to remove '+bfunc+' DLL link!'); unlink_err = -1; else disp('Removing DLL link...Done!'); end end //% MCP2200 unlinking bfunc = 'mcp2200_block'; [test,ilib] = c_link(bfunc); if (test) ulink(ilib); if( c_link(bfunc) ) disp('Error: Unable to remove '+bfunc+' DLL link!'); unlink_err = -1; else disp('Removing DLL link...Done!'); end end //% Rollers GUI unlinking bfunc = 'EvidenceRollers'; [test,ilib] = c_link(bfunc); if (test) ulink(ilib); if( c_link(bfunc) ) disp('Error: Unable to remove '+bfunc+' DLL link!'); unlink_err = -1; else disp('Removing DLL link...Done!'); end end //% UDP unlinking bfunc = 'udp_config'; [test,ilib] = c_link(bfunc); if (test) ulink(ilib); if( c_link(bfunc) ) disp('Error: Unable to remove '+bfunc+' DLL link!'); unlink_err = -1; else disp('Removing DLL link...Done!'); end end //% Native integer unlinking bfunc = 'nat_gainblk_i32n'; [test,ilib] = c_link(bfunc); if (test) ulink(ilib); if( c_link(bfunc) ) disp('Error: Unable to remove '+bfunc+' DLL link!'); unlink_err = -1; else disp('Removing DLL link...Done!'); end end //% iSIm unlinking bfunc = 'flex_blocks'; [test,ilib] = c_link(bfunc); if (test) ulink(ilib); if( c_link(bfunc) ) disp('Error: Unable to remove '+bfunc+' DLL link!'); unlink_err = -1; else disp('Removing DLL link...Done!'); end end //% Flex SIm unlinking bfunc = 'flex_adcin'; [test,ilib] = c_link(bfunc); if (test) ulink(ilib); if( c_link(bfunc) ) disp('Error: Unable to remove '+bfunc+' DLL link!'); unlink_err = -1; else disp('Removing DLL link...Done!'); end end
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<?php include ('knights.php'); $array=newBoard(); $array[1][0]=1; $array[2][7]=2; $array[5][5]=3; $array[5][4]=4; $array[4][0]=5; $array[5][2]=6; $array[2][3]=7; $array[0][1]=8; $array[3][4]=9; $array[2][7]=0; $array[6][5]=1; $array[7][3]=2; $array[4][0]=3; $array[1][3]=4; $array[2][2]=5; $array[4][3]=6; $array[5][1]=7; $array[4][2]=8; echo numOfMoves($array, 1,0)."\n"; echo numOfMoves($array, 2,3)."\n"; echo numOfMoves($array, 2,5)."\n"; echo numOfMoves($array, 0,2)."\n"; echo numOfMoves($array, 4,6)."\n"; echo numOfMoves($array, 3,2)."\n"; echo numOfMoves($array, 5,4)."\n"; echo numOfMoves($array, 2,6)."\n"; echo numOfMoves($array, 3,4)."\n"; ?>
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//Example 6.12 clc;clear;close; N=4; n=0:N-1; x=cos(%pi/4*n); //Calculation of DFT X=fft(x,-1); X=clean(X); disp(x,'Given Sequence is x(n): '); disp(X,'DFT of the Sequence is X(k): ');
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//start clc ; clear ; //line inputs linedata = input("Enter line data:") Yshunt=input("Enter shunt admittance:") // line data extraction from= linedata(: ,1) to= linedata(: ,2) imp= linedata(: ,3)+ linedata(: ,4)*%i half_adm= -linedata(: ,5)*%i bus_no= max(max(from,to)); Ybus= zeros(bus_no,bus_no); //Ybus building for i=1:length(from) m=from(i); n=to(i); Ybus(m,m)=Ybus(m,m) +1/imp(i)+ (half_adm(i)/2) ; Ybus(n,n)=Ybus(n,n) +1/imp(i)+ (half_adm(i)/2) ; Ybus(m,n)= -1/ imp(i); Ybus(n,m)=Ybus(m,n); end //Adding shunt to diagonal elements for i=1:bus_no Ybus(i,i)=Ybus(i,i)+Yshunt(i) end //display Ybus disp("Ybus Admittance is:") disp(Ybus) //Input and extract bus data. Taps are avoided busdata = input("Enter bus data:") bus=busdata(:,1) typ = busdata(:,2) qmin = busdata(:,9) qmax = busdata(:,10) p= busdata (:,5)-busdata(:,7) q= busdata(:,6)-busdata(:,8) v= busdata(:,3).*(cosd(busdata(:,4))+ %i*sind(busdata(:,4))); //parameter setting alpha=0.25 //default. Can take alpha as input() if needed count =0; err =1; vn(1)=v(1); vold =v(1); //gauss seidal method while abs(err)>5*10^(-5) //while count<23 //testing for i =2:bus_no sumyv =0; for j=1:bus_no //if i~=j sumyv = sumyv +Ybus(i,j)*v(j); //end end if typ(i)==2 q(i)=-imag(conj(v(i)*sumyv)); if q(i)<qmin (i) | q(n)>qmax (i) vn(i) =(1/Ybus(i,i)) *(((p(i)-%i*q(i))/(conj(v(i)))) -(sumyv-Ybus(i,i)*v(i))); vold(i)=v(i); v(i)=vn(i); typ(i)=3 if q(i)<qmin (i) q(i)= qmin (i); else q(i)= qmax (i); end else vn(i) =(1/ Ybus(i,i)) *((( p(i)-%i*q(i))/( conj (v(i)))) -(sumyv -Ybus(i,i)*v(i))); ang = atan ( imag (vn(i)),real (vn(i))); vn(i)= abs (v(i))*( cos ( ang )+%i* sin (ang)); vold (i)=v(i); v(i)=vn(i); end elseif typ (i)==3 vn(i) =(1/ Ybus(i,i)) *((( p(i)-%i*q(i))/( conj (v(i)))) -(sumyv -Ybus(i,i)*v(i))); vold (i)=v(i); v(i)=vn(i); end end err = max(abs(abs(v)-abs(vold))); count = count+1; for i=2:bus_no if (err>5*10^(-6) & typ(i)==3) v(i)= vold(i)+ alpha*(v(i)-vold(i)); end end end //disp output disp("Voltage rectangular:",v) volt=abs(v) angle=atan( imag(v),real(v))*(180/%pi); disp("Voltage:",volt) disp("Angle:",angle) printf("Gauss Seidal Load Flow converged after %i iteration.", count)
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clc //Variable declaration lamda=0.58 theta=9.5*%pi/180 n=1 d=0.5 //d200=a/sqrt(2**2+0**2+0**2)=0.5a //Calculations a=n*lamda/(2*d*sin(theta)) //2*d*sin(theta)=n*lamda //Result printf('a =%0.3f Angstorms\n',(a))
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a=200;//in mm b=150;//in mm ta=2.5;//in mm tb=2;//in mm T=1000;//in N.mm G=25000;//given in N/mm^2
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clc //initialisation of variables clear Cp= 8.21*0.0413 //lit-atm deg^-1 mole^-1 V= 8.64*28*10^-3 //lit r= 1.199 //CALCULATIONS u= V*(r-1)/Cp //RESULTS printf ('Joule-thomson coefficient = %.3f deg atm^-1',u)
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// Scilab code Ex2.2: Pg:79(2008) clc;clear; amu = 1.67e-027; // Mass of a nucleon, kg E = 8e+004; // Electric field in a Bainbridge mass spectrograph, V/m B = 0.55; // Magnetic induction, Wb per square meter M1 = 20; // Atomic mass of first isotope of neon, amu M2 = 22; // Atomic mass of second isotope of neon, amu q = 1.602e-019; // Charge of the ion, coulomb delta_x = 2*E*(M2-M1)*amu/(q*B^2); // Separation between the lines, mm printf("\nLinear separation between the lines on a photographic plates = %4.2f m", delta_x); // Result // Linear separation between the lines on a photographic plates= 0.01 m
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//ques-22.14 //To show that KBr has a FCC structure clc den=2.73;//density (in g/mL) a=654*10^-10;//edge length (in cm) Na=6.023*10^23;//(in /mol) m1=39;//molar mass of K (in g/mol) m2=80;//molar mass of Br (in g/mol) M=m1+m2; z=(den*Na*a^3)/M; printf("As z = %.0f, therefore KBr has a FCC structure.",z);
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// Scilab code Exa18.4 : : Page-764 (2011) clc;clear; p = rand(1,3); // proton pi_minus = rand(1,3); // pi minus meson pi_plus = rand(1,3); // pi plus meson pi_0 = rand(1,3); // pi zero meson n = rand(1,3); // neutron lambda_0 = rand(1,3); // lambda zero hyperon K_0 = rand(1,3); // k zero meson K_plus = rand(1,3); // k plus meson K_0_bar = rand(1,3); // anti particle of k zero sigma_plus = rand(1,3); // sigma hyperon // Now in the following steps we allocated the value of charge(Q),baryon number(B) and strangeness number (S) p(1,1) = 1; p(1,2) = 1; p(1,3) = 0; pi_minus(1,1) = -1; pi_minus(1,2) = 0; pi_minus(1,3) = 0; pi_plus(1,1) = 1; pi_plus(1,2) = 0; pi_plus(1,3) = 0; n(1,1) = 0; n(1,2) = 1; n(1,3) = 0; lambda_0(1,1) = 0; lambda_0(1,2) = 1; lambda_0(1,3) = -1; K_0(1,1) =0 ; K_0(1,2) = 0 ; K_0(1,3) = 1; K_plus(1,1) = 1; K_plus(1,2) = 0 ; K_plus(1,3) = 1; sigma_plus(1,1) = 1; sigma_plus(1,2) = 1; sigma_plus(1,3) = -1; K_0_bar(1,1) = 0; K_0_bar(1,2) = 0; K_0_bar(1,3) = -1; pi_0(1,1) = 0; pi_0(1,2) = 0; pi_0(1,3) = 0; j = 0; k = 0; printf("\n Reaction I \n pi_plus + n ......> lambda_0 + K_plus") for i = 1:3 if pi_plus(1,i)+n(1,i) == lambda_0(1,i)+K_plus(1,i) then j = j+1; else printf("\n Reaction I is forbidden") if i == 1 then printf("\n Delta Q is not zero") elseif i == 2 then printf("\n Delta B is not zero") elseif i == 3 then printf("\n Delta S is not zero") end end end if j==3 then printf("\n Reaction I is allowed "); printf("\n Delta Q is zero \n Delta B is zero \n Delta S is zero") end printf("\n Reaction II \n pi_plus + n ......> K_0 + K_plus") j = 0; for i = 1:3 if pi_plus(1,i)+n(1,i) == K_0(1,i)+K_plus(1,i) then j = j+1; else printf("\n Reaction II is forbidden") if i == 1 then printf("\n Delta Q is not zero") elseif i == 2 then printf("\n Delta B is not zero") elseif i == 3 then printf("\n Delta S is not zero") end end end if j==3 then printf("\n Reaction II is allowed "); printf("\n Delta Q is zero \n Delta B is zero \n Delta S is zero") end j = 0; printf("\n Reaction III \n pi_plus + n ......> K_0_bar + sumison_plus") for i = 1:3 if pi_plus(1,i)+n(1,i) == K_0_bar(1,i)+sigma_plus(1,i) then j = j+1; else printf("\n Reaction III is forbidden") if i == 1 then printf("\n Delta Q is not zero") elseif i == 2 then printf("\n Delta B is not zero") elseif i == 3 then printf("\n Delta S is not zero") end end end if j==3 then printf("\n Reaction III is allowed "); printf("\n Delta Q is zero \n Delta B is zero \n Delta S is zero") end j = 0; printf("\n Reaction IV \n pi_plus + n ......> pi_minus + p") for i = 1:3 if pi_plus(1,i)+n(1,i) == pi_minus(1,i)+p(1,i) then j = j+1; else printf("\n Reaction IV is forbidden") if i == 1 then printf("\n Delta Q is not zero") elseif i == 2 then printf("\n Delta B is not zero") elseif i == 3 then printf("\n Delta S is not zero") end end end if j==3 then printf("\n Reaction IV is allowed "); printf("\n Delta Q is zero \n Delta B is zero \n Delta S is zero") end j = 0; printf("\n Reaction V \n pi_minus + p ......> lambda_0 + K_0") for i = 1:3 if pi_minus(1,i)+p(1,i) == lambda_0(1,i)+K_0(1,i) then j = j+1; else printf("\n Reaction V is forbidden") if i == 1 then printf("\n Delta Q is not zero") elseif i == 2 then printf("\n Delta B is not zero") elseif i == 3 then printf("\n Delta S is not zero") end end end if j==3 then printf("\n Reaction V is allowed "); printf("\n Delta Q is zero \n Delta B is zero \n Delta S is zero") end j = 0; printf("\n Reaction VI \n pi_plus + n ......> lambda_0 + K_plus") for i = 1:3 if pi_minus(1,i)+p(1,i) == pi_0(1,i)+lambda_0(1,i) then j = j+1; else printf("\n Reaction VI is forbidden") if i == 1 then printf("\n Delta Q is not zero"); elseif i == 2 then printf("\n Delta B is not zero") elseif i == 3 then printf("\n Delta S is not zero") end end end if j==3 then printf("\n Reaction VI is allowed "); printf("\n Delta Q is zero \n Delta B is zero \n Delta S is zero"); end // Result // Reaction I // pi_plus + n ......> lambda_0 + K_plus // Reaction I is allowed // Delta Q is zero // Delta B is zero // Delta S is zero // Reaction II // pi_plus + n ......> K_0 + K_plus // Reaction II is forbidden // Delta B is not zero // Reaction II is forbidden // Delta S is not zero // Reaction III // pi_plus + n ......> K_0_bar + sumison_plus // Reaction III is forbidden // Delta S is not zero // Reaction IV // pi_plus + n ......> pi_minus + p // Reaction IV is forbidden // Delta Q is not zero // Reaction V // pi_minus + p ......> lambda_0 + K_0 // Reaction V is allowed // Delta Q is zero // Delta B is zero // Delta S is zero // Reaction VI // pi_plus + n ......> lambda_0 + K_plus // Reaction VI is forbidden // Delta S is not zero
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//Chapter 11 //Example 11.6 //page 420 //To find bus voltages and currents clc;clear; v_pf=1; //prefault voltage //according to the fig.11.26 Y1dd=((%i*0.2)^-1)+((%i*0.0805)^-1); Y1fg=-(%i*0.0805)^-1; Y1de=Y1fg; Y1ff=((%i*0.0805)^-1)+((%i*0.164)^-1); Y1ee=Y1ff; Y1ef=-(%i*0.164)^-1; Y1gg=((%i*0.0805)^-1)+((%i*0.345)^-1)+((%i*0.69)^-1); Y1df=0; Y1dg=0; Y1ed=Y1de; Y1eg=0; Y1fd=0; Y1fe=Y1ef; Y1gd=0; Y1ge=0; Y1gf=Y1fg; printf('\nY-Bus and Z-Bus matrix can be written as:\n') Y1_bus=[Y1dd Y1de Y1df Y1dg;Y1ed Y1ee Y1ef Y1eg;Y1fd Y1fe Y1ff Y1fg;Y1gd Y1ge Y1gf Y1gg]; Y2_bus=Y1_bus; printf('\nY1_bus=');disp(Y1_bus); printf('\nY2_bus=');disp(Y2_bus); Y0dd=(%i*1.608)^-1;Y0de=0;Y0df=0;Y0dg=0; Y0ed=0;Y0ee=((%i*0.0805)^-1)+((%i*0.494)^-1);Y0ef=-(%i*0.494)^-1;Y0eg=0; Y0fd=0;Y0fe=Y0ef;Y0ff=Y0ee;Y0fg=0; Y0gd=0;Y0de=0;Y0gf=0;Y0gg=(%i*1.712)^-1; Y0_bus=[Y0dd Y0de Y0df Y0dg;Y0ed Y0ee Y0ef Y0eg;Y0fd Y0fe Y0ff Y0fg;Y0gd Y0de Y0gf Y0gg]; printf('\nY0_bus=');disp(Y0_bus); //finding Z-bus matrix Z1_bus=inv(Y1_bus); Z2_bus=inv(Y2_bus); Z0_bus=inv(Y0_bus); printf('\n\nZ1bus=');disp(Z1_bus); printf('\nZ2_bus=');disp(Z2_bus); printf('\nZ0_bus=');disp(Z0_bus); //to find fault current with LG fault on bus e ---case(i) If_e=(3*v_pf)/(Z1_bus(2,2)+Z2_bus(2,2)+Z0_bus(2,2)); printf('\n\n\nFault current with LG fault on bus e is If_e= -j%0.5f\n',abs(imag(If_e))); //to find fault current with LG fault on bus f ---case(ii) If_f=(3*v_pf)/(Z1_bus(3,3)+Z2_bus(3,3)+Z0_bus(3,3)); printf('Fault current with LG fault on bus f is If_f= -j%0.5f\n',abs(imag(If_f))); //to find bus voltages and line currents in case(i) printf('\n\n\nBus voltages and currents are given below:\n\n'); Vf1_d=1-(Z1_bus(1,2)*If_e/3); Vf1_e=1-(Z1_bus(2,2)*If_e/3); Vf1_f=1-(Z1_bus(3,2)*If_e/3); Vf1_g=1-(Z1_bus(4,2)*If_e/3); disp('Vf1_d=');disp(Vf1_d); disp('Vf1_e=');disp(Vf1_e); disp('Vf1_f=');disp(Vf1_f); disp('Vf1_g=');disp(Vf1_g); printf('\n\n\n'); Vf2_d=-(Z2_bus(1,2)*If_e/3); Vf2_e=-(Z2_bus(2,2)*If_e/3); Vf2_f=-(Z2_bus(3,2)*If_e/3); Vf2_g=-(Z2_bus(4,2)*If_e/3); disp('Vf2_d=');disp(Vf2_d); disp('Vf2_e=');disp(Vf2_e); disp('Vf2_f=');disp(Vf2_f); disp('Vf2_g=');disp(Vf2_g); printf('\n\n\n'); Vf0_d=-(Z0_bus(1,2)*If_e/3); Vf0_e=-(Z0_bus(2,2)*If_e/3); Vf0_f=-(Z0_bus(3,2)*If_e/3); Vf0_g=-(Z0_bus(4,2)*If_e/3); disp('Vf0_d=');disp(Vf0_d); disp('Vf0_e=');disp(Vf0_e); disp('Vf0_f=');disp(Vf0_f); disp('Vf0_g=');disp(Vf0_g); printf('\n\n\n'); If1_fe=-Y1fe*(Vf1_f-Vf1_e);disp('If1_fe=');disp(If1_fe); If1_de=-Y1de*(Vf1_d-Vf1_e);disp('If1_de=');disp(If1_de); Ia1=If1_fe+If1_de;disp('Ia1=');disp(Ia1); printf('\n\n\n'); If1_gf=-Y1gf*(Vf2_g-Vf2_f);disp('If1_gf=');disp(If1_gf); printf('\n\n\n'); If2_fe=-Y1fe*(Vf2_f-Vf2_e);disp('If2_fe=');disp(If2_fe); //Y2fe=Y1fe If0_fe=-Y0fe*(Vf2_f-Vf2_e);disp('If0_fe=');disp(If0_fe); If_fe=If1_fe+If2_fe+If0_fe;disp('If_fe=');disp(If_fe);
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//CAPTION: Current_of_a_HEMT //chapter_no.-6, page_no.-251 //Example_no.6-3-1 clc; //Calculate_the_Drain_Current q=1.60*(10^-19); n=5.21*(10^15); W=150*(10^-6); v=2*(10^5); Ids=q*n*W*v; Ids=1000*Ids; disp(Ids,'the_drain_current_is(mA)');
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//Example 1.28.b // phase shift and time clc; clear; close; //given data : Iin=30; // in celcius t1=50; // in seconds t2=10; // in seconds T1=520; // starting range variation of temerature T2=580; // range variation of temperature T=(T1+T2)/2; // mean value in celcius w=2*%pi*(1/t1); // angular frequency of oscillation rad/sec pi=atan(w*t2); L=(1/w)*pi; disp(L,"the time lag,L(seconds) = ")
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clc; clear; //assume the first cloumn values are of machine M1 and 2nd column are of M2 p=[1,1;1 3;2 2;2 4;3 3;3 1;4 4;4 2]; z=1; for i=1:length(p(:,1)) for j=i:length(p(:,1)) if(p(i,1)==p(j,1) & i~=j) q(z,:)=[p(i,:) p(j,:)]; z=z+1; end end end disp("pi(R)"); disp(q); z=1; for i=1:length(p(:,1)) for j=i:length(p(:,1)) if(p(i,2)==p(j,2) & i~=j) q(z,:)=[p(i,:) p(j,:)]; z=z+1; end end end disp("pi(S)"); disp(q);
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clc; // plot for open circuit characteristics is given in fig 4.10 IF=[ 0 11.5 23 36.5 59.5 79 110 160]; EA=[0 40 80 120 160 180 200 220 ]; subplot(221); plot(IF,EA); xlabel('field ATs'); ylabel('voltage'); title('magnetising curve'); nf=800; // field winding turns rd=0.5; // total armature resistance along d-axis ifl=0.2; // field winding current d=10; // product of (difference between mmf of compensating winding and armature mmf along d-circuit)and load current nf1=nf*ifl; // field winding turns for field current of 200mA il=nf1/d; // maximum load current printf('Maximum field current is %d A\n',il); IL=[0 2 4 6 8 10 12 14 16]; // load currents ATD=nf1-d*IL; // net d-axis ATs disp('Net d-axis ATs is'); disp(ATD); // corresponding to each ATD open circuit EMF is obtained from magnetising curve EO=[220 213 204.7 194 180.5 161.4 128 70 0 ]; // open circuit EMF VRD=rd*IL; // d-axis resistance drop VO=EO-VRD; disp('Output voltage(V) is '); disp(VO); subplot(222); plot(IL,VO); xlabel('load current(A)'); ylabel('Output voltage(v)'); title('Output voltage vs Load current');
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clear clc //Example 10.13 disp('Example 10.13') s=%s; G=4/((s+1)*(s+2)*(s+3)); G=syslin('c',G); [ki,s_i]=kpure(G); evans(G,ki*1.5); // plots for until K = 1.5*ki //disp(G,"For G=");disp(ki,"K=") disp(ki,"Max value of k for which we have closed loop stability",G,"For G=") xtitle("$G(s)=\frac{4}{(s+1)(s+2)(s+3)}$") sgrid();
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clear clc //To find rotational inertia // GIVEN:: //refer to figure 9-9 from page no. 181 //mass of first partical m1 = 2.3//in kg //mass of second partical m2 = 3.2//in kg //mass of third partical m3 = 1.5//in kg // SOLUTION: //locating center of mass x1 = 0//in m x2 = 0//in m x3 = 4.0//in m //x coordinate of center of mass x_cm = (m1*x1+m2*x2+m3*x3)/(m1+m2+m3)//in m y1 = 0//in m y2 = 3.0//in m y3 = 0//in m //y coordinate of center of mass y_cm = (m1*y1+m2*y2+m3*y3)/(m1+m2+m3)//in m //squqred distance from center of mass to each of particals //for first partical r1_square = x_cm^2 + y_cm^2//in m^2 //for second partical r2_square = x_cm^2 + (y2-y_cm)^2//in m^2 //for third partical r3_square = (x3-x_cm)^2 + y_cm^2//in m^2 //rotational inertia I_cm = (m1*r1_square+m2*r2_square+m3*r3_square)//in Kg.m^2 r2_square = nearfloat("succ",3.40) r3_square = nearfloat("pred",11.74) I_cm = ceil(I_cm) printf ("\n\n x coordinate of center of mass x_cm = \n\n %.2f m",x_cm); printf ("\n\n y coordinate of center of mass y_cm = \n\n %.2f m",y_cm); printf ("\n\n Squqred distance from center of mass for first partical r1_square = \n\n %.2f m^2",r1_square); printf ("\n\n Squqred distance from center of mass for second partical r2_square = \n\n %.2f m^2",r2_square); printf ("\n\n Squqred distance from center of mass for third partical r3_square = \n\n %2i m^2",r3_square); printf ("\n\n Rotational inertia I_cm = \n\n %.1f Kg.m^2",I_cm);
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# Cross connecter thermo test units SI $thermo = VirtualMaterials.Peng-Robinson / -> $thermo thermo + PROPANE ISOBUTANE n-BUTANE n-PENTANE WATER # lets have some streams for this test coldInlet = Stream.Stream_Material() hotInlet = Stream.Stream_Material() cd hotInlet.In T = 200 P = 150 Fraction = .01 .02 .01 0 1 MoleFlow = 500 cd / cd /coldInlet.In Fraction Fraction = .75 15 .08 .02 0 VapFrac = 0 P = 300 T = MoleFlow = 1000 cd / coldOutlet = Stream.Stream_Material() exch = Heater.HeatExchanger() exch cd exch DeltaPC = 10 DeltaPH = 50 DeltaTHO = 5 K cd / # hot side will use steam property package $thermo1 = VirtualMaterials.Steam95 exch.HotSide -> $thermo1 exch.HotSide.thermo1 + water # create hot outlet and assign the hot inlet thermo hotOutlet = Stream.Stream_Material() hotOutlet -> $thermo1 # create CrossConnector xc = CrossConnector.CrossConnector() hotInlet.Out -> xc.In xc.In xc.Out #connect things coldInlet.Out -> exch.InC exch.OutC -> coldOutlet.In xc.Out -> exch.InH exch.OutH.T exch.OutH -> hotOutlet.In # results coldInlet coldInlet.Out coldOutlet.Out hotInlet.Out hotOutlet.Out exch.ColdSide.InQ # one more stream and connector hotOut2 = Stream.Stream_Material() xc2 = CrossConnector.CrossConnector() xc2.Out -> hotOut2.In hotOut2.In copy / paste / cd /RootClone coldInlet coldInlet.Out coldOutlet.Out hotInlet.Out hotOutlet.Out exch.ColdSide.InQ
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//ex15.4 f_c=2860; R=1.8*10^3; C=1/(2*%pi*f_c*R); R2=R; R1=0.152*R2; //BUTTERWORTH RESPONSE IN FIRST STAGE R4=R; R3=1.235*R4; //BUTTERWORTH RESPONSE IN SECOND STAGE disp(C,'capacitance in farads'); disp(R1,'R1 in ohms for butterworth response in first stage') disp(R3,'R3 in ohms for butterworth response in second stage')
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// Exa 2.14 clc; clear; close; // Given data format('v',9) V_PP= 3;// in volt delta_t= 4;// in micro sec // delta_V= 90% of V_PP - 10% of V_PP = (90%-10%)*V_PP delta_V= 0.8*V_PP; SR= delta_V/delta_t;// in V/micro sec disp(SR,"Required slew rate in V/micro second")
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//Example 4_4 clc(); clear; //To calculate the number of atoms per unit cell a=2.9*10^-10 //units in meters density=7870 //units in kg/m^3 M=55.85 //units in kg/m^3 N=6.02*10^26 //units in kg/mol n=(a^3*density*N)/M printf("number of atoms %.0f",n)
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A=[3,-1,0;-2,4,-3;0,-1,1;] disp(A) printf('Eigen values are:') disp(spec(A)) printf('Display of Power Method:') U=[1,1,1]' for i=1:14 B=A*U a=abs(B(1,1)) b=abs(B(2,1)) c=abs(B(3,1)) if ((a>b)&(a>c)) then T= (B(1,1)) elseif ((b>a)&(b>c)) then T=(B(2,1)) else T=(B(3,1)) end printf('After %d iteration eigenvalue is ',i) disp(T) printf(' corresponding eigenvector is ') U=B/T disp(U) end
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#************************************************************ # Scenario of ADREAM # # date : Wed Nov 28 17:50:10 2012 #************************************************************ p3d_sel_desc_name P3D_ENV ADREAM p3d_sel_desc_name P3D_ROBOT HERAKLES_HUMAN1 p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.143000 6.521000 0.987000 0.000000 0.000000 33.732000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 79.416000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 -69.156000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 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0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT WALLE_TAPE p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT GREY_TAPE p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT PLACEMAT_RED p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT PLACEMAT_BLUE p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT PLACEMAT_GREEN p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT ACCESSKIT p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT PINK_TRASHBIN p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT PR2_GRIPPER p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_constraint p3d_lin_rel_dofs 1 3 1 2 2 1.000000 0.000000 0 p3d_sel_desc_name P3D_ROBOT PR2_GRIPPER_LEFT p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_constraint p3d_lin_rel_dofs 1 3 1 2 2 1.000000 0.000000 0 p3d_sel_desc_name P3D_ROBOT VISBALL_MIGHTABILITY p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT HUM_BAR p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT SAHandRight p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_constraint p3d_lin_rel_dofs 1 6 1 5 2 1.000000 0.000000 0 p3d_constraint p3d_lin_rel_dofs 1 10 1 9 2 1.000000 0.000000 0 p3d_constraint p3d_lin_rel_dofs 1 14 1 13 2 1.000000 0.000000 0 p3d_constraint p3d_lin_rel_dofs 1 18 1 17 2 1.000000 0.000000 0 p3d_sel_desc_name P3D_ROBOT SAHandRight2 p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_constraint p3d_lin_rel_dofs 1 6 1 5 2 1.000000 0.000000 0 p3d_constraint p3d_lin_rel_dofs 1 10 1 9 2 1.000000 0.000000 0 p3d_constraint p3d_lin_rel_dofs 1 14 1 13 2 1.000000 0.000000 0 p3d_constraint p3d_lin_rel_dofs 1 18 1 17 2 1.000000 0.000000 0 p3d_sel_desc_name P3D_ROBOT SIMPLECHAIR p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT PR_2CYLINDER p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT HUMCYLINDER p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT TABLE_1 p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT CARPET p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.580000 7.020000 0.000000 0.000000 0.000000 0.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT FAUTEUIL_1 p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.350000 5.730000 0.000000 0.000000 0.000000 -164.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT FAUTEUIL_2 p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.370000 8.150000 0.000000 0.000000 0.000000 48.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT LOW_TABLE_LARGE p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.553000 6.760000 0.000000 0.000000 0.000000 16.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT SOFA p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.100000 6.600000 0.000000 0.000000 0.000000 109.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT IKEA_SHELF_DARK p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.733000 4.835000 0.791000 0.000000 0.000000 90.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT IKEA_SHELF_LIGHT_1 p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.733000 4.835000 0.000000 0.000000 0.000000 90.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT IKEA_SHELF_LIGHT_2 p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.523000 4.835000 0.000000 0.000000 0.000000 90.000000 p3d_set_robot_goto 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 p3d_sel_desc_name P3D_ROBOT PR2_ROBOT p3d_set_robot_steering_method Multi-Localpath p3d_set_robot_radius 1.000000 p3d_set_robot_current 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p3d_constraint p3d_lin_rel_dofs 1 25 1 24 2 1.000000 0.000000 0 p3d_constraint p3d_pr2_arm_ik 7 6 7 9 10 11 12 13 1 32 0 1 8 p3d_set_cntrt_Tatt 2 1.000000 0.000000 0.000000 -0.180000 0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 1.000000 0.000000 p3d_set_cntrt_Tatt2 2 0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 1.000000 0.000000 1.000000 0.000000 0.000000 -0.180000 p3d_constraint p3d_pr2_arm_ik 7 16 17 19 20 21 22 23 1 33 0 1 18 p3d_set_cntrt_Tatt 3 1.000000 0.000000 0.000000 -0.180000 0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 1.000000 0.000000 p3d_set_cntrt_Tatt2 3 0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 1.000000 0.000000 1.000000 0.000000 0.000000 -0.180000 p3d_set_object_base_and_arm_constraints 32 1 0 2 2 3 p3d_set_arm_data 2 3 32 p3d_set_arm_data 3 3 33 p3d_sel_desc_name P3D_ROBOT PR2_SIMUL p3d_set_robot_steering_method Linear p3d_set_robot_current 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 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// To find the scale error // Modern Electronic Instrumentation And Measurement Techniques // By Albert D. Helfrick, William D. Cooper // First Edition Second Impression, 2009 // Dorling Kindersly Pvt. Ltd. India // Example 4-7 in Page 67 clear; clc; close; // Given data R_h = 2000; //The desired scale marking for the half scale deflection E = 3; //The internal battery voltage in volt I_fsd = 1 *(10^-3); //Current for full scale deflection in ampere R_m = 50; //resistance of the basic movement in ohm //Calculations I_t = E / R_h; //Total battery current at FSD I_2 = I_t - I_fsd; // Current through zero-adjust resistor R_2 R_2 = I_fsd * R_m/I_2; R_p = R_2*R_m/(R_2 + R_m); R_1 = R_h - R_p; printf("(a) The value of R_1 and R_2 is") printf("The value of zero-adjust resistor R2 =%0.1f ohm\n",R_2); printf("The value of current-limiting resistor R1 =%0.1f ohm\n",R_1); //At a 10% drop in battery voltage E = 3- 0.3; I_t = E / R_h; //Total battery current in A I_2 = I_t - I_fsd; //Shunt current in A R_2 = ceil(I_fsd * R_m/I_2); R_p = R_2 *R_m/(R_2+R_m); R_h = R_1 + R_p; %error = (2000-2003.7)/2003.7*100; printf("\n(b) The maximum value of R2 to compensate the drop in battery voltage = %d ohm\n",R_2); printf("The true value of the half-scale mark on the meter is = %0.3f ohm\n",R_h); printf("\n(c) The percentage error = %0.3f%%\n",%error); disp('The negative sign indicates that the meter reading is low'); //Result // (a) The value of R_1 and R_2 isThe value of zero-adjust resistor R2 =100.0 ohm // The value of current-limiting resistor R1 =1966.7 ohm // (b) The maximum value of R2 to compensate the drop in battery voltage = 143 ohm // The true value of the half-scale mark on the meter is = 2003.713 ohm // (c) The percentage error = -0.185% // The negative sign indicates that the meter reading is low
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//CHAPTER 8 _ TEMPERATURE MEASUREMENT //Caption : Thermocouple // Example 1 // Page 500 t1 = 100 //('entering the temperature(in deg cent) =:') e1= 5 // ('entering the emf (in mv)at temperature t1 =:') t2=445 //('entering the second temperature(in deg cent)= :') e2=25 //('entering the emf(in mv) at temperature t2 =:') // TO CALCULATE CONSTANTS a AND b //e1=a*(t1)+b*(t1^2); //e2=a*(t2)+b*(t2^2); A=[t1 t1^2;t2 t2^2]; B=[e1 0 ;e2 0] Y=lsq(A,B); //computes the minimum norm least square solution of the equation A*Y=B, disp(Y) printf('value of constants a and b are %fd V/deg cent and %fd V/deg cent respectively',Y(1,1),Y(2,1)) //PART B //Let e(0-40) be represented by E1 , e(40-t) by E2 and e(0-t) by E3 E1=(Y(1,1)*40)+(Y(2,1)*40^2); disp(E1); E2=2; // given E3=E1+E2; D=sqrt((Y(1,1)^2)+(4*Y(2,1)*E3)); t=(-Y(1,1)+D)/(2*Y(2,1)); disp(t) printf('Hot junction temperature is %1.1f deg cent ',t); // PART C // Let e(0-500) be represented by E4 and e(40-500) by E5 E4=Y(1,1)*500+Y(2,1)*500^2; E5=E4-E1; disp (E5) printf('emf when the hot junction is at 500 and cold at 40 is %1.1f mV ',E5);
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clc // Given that m = 6 // mass of object in kg a= 5 // acceleration of object in m/s^2 g = 9.8 // acceleration due to gravity in m/s^2 // Sample problem 1 on page no. 10 printf("\n # Problem 1 \n") F_down = m*(g+a) // force acting on a particle going downwards in N F_up = m*(g-a)//force acting on a particle going upwards in N printf("\n Force acting on a particle while going upward is %f N \n Force acting on a particle while going downward is %f N",F_up,F_down)
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function y=f(x) y=-2*sin(x)+4*cos(x) endfunction n=1000000 tol=0.00001 //dispay the following: //1. result (at least 9 decimal places or scientific notation)
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chain 8, fact 1 [[-2,-2,0,1],[1,0,2,2],[0,1,-2,-2],[2,2,1,0]] [39,17,-36,-26] => [-138,-85,141,76] => [522,296,-519,-305] => [-1941,-1126,1944,1117] => [7251,4181,-7248,-4190] => [-27054,-15625,27057,15616] => [100974,58292,-100971,-58301] => [-376833,-217570,376836,217561] => [1406367,811961,-1406364,-811970] chain 8, fact 1 [[-2,1,0,-2],[1,2,2,0],[0,-2,-2,1],[2,0,1,2]] [39,17,-36,-26] => [-9,1,12,-10] => [39,17,-36,-26] => [-9,1,12,-10] => [39,17,-36,-26] => [-9,1,12,-10] => [39,17,-36,-26] => [-9,1,12,-10] => [39,17,-36,-26] chain 8, fact 1 [[-2,-2,0,1],[2,2,1,0],[0,1,-2,-2],[1,0,2,2]] [39,17,-36,-26] => [-138,76,141,-85] => [39,17,-36,-26] => [-138,76,141,-85] => [39,17,-36,-26] => [-138,76,141,-85] => [39,17,-36,-26] => [-138,76,141,-85] => [39,17,-36,-26] chain 5, fact 1 [[-2,1,0,-2],[2,0,1,2],[0,-2,-2,1],[1,2,2,0]] [39,17,-36,-26] => [-9,-10,12,1] => [6,-4,-3,-5] => [-6,-1,9,-8] => [27,-19,-24,10] => [-93,50,96,-59] ?? [354,-208,-351,199] chain 5, fact 1 [[0,-2,-2,1],[1,2,2,0],[-2,1,0,-2],[2,0,1,2]] [39,17,-36,-26] => [12,1,-9,-10] => [6,-4,-3,-5] => [9,-8,-6,-1] => [27,-19,-24,10] => [96,-59,-93,50] ?? [354,-208,-351,199] chain 8, fact 1 [[0,1,-2,-2],[1,0,2,2],[-2,-2,0,1],[2,2,1,0]] [39,17,-36,-26] => [141,-85,-138,76] => [39,17,-36,-26] => [141,-85,-138,76] => [39,17,-36,-26] => [141,-85,-138,76] => [39,17,-36,-26] => [141,-85,-138,76] => [39,17,-36,-26] chain 2, fact 1 [[0,-2,-2,1],[1,2,2,0],[0,0,1,-1],[0,1,0,1]] [39,17,-36,-26] => [12,1,-10,-9] => [9,-6,-1,-8] ?? [6,-5,7,-14] chain 8, fact 1 [[0,-2,-2,1],[2,0,1,2],[-2,1,0,-2],[1,2,2,0]] [39,17,-36,-26] => [12,-10,-9,1] => [39,17,-36,-26] => [12,-10,-9,1] => [39,17,-36,-26] => [12,-10,-9,1] => [39,17,-36,-26] => [12,-10,-9,1] => [39,17,-36,-26] chain 8, fact 1 [[0,1,-2,-2],[2,2,1,0],[-2,-2,0,1],[1,0,2,2]] [39,17,-36,-26] => [141,76,-138,-85] => [522,296,-519,-305] => [1944,1117,-1941,-1126] => [7251,4181,-7248,-4190] => [27057,15616,-27054,-15625] => [100974,58292,-100971,-58301] => [376836,217561,-376833,-217570] => [1406367,811961,-1406364,-811970] elapsed time: nn s
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compound_residuals.sci
function y=compound_residuals(x, Ainput,Ncomp ) //****************************************************************************** // Data Reconciliation Benchmark Problems From Literature Review // Author: Edson Cordeiro do Valle // Contact - edsoncv@{gmail.com}{vrtech.com.br} // Skype: edson.cv //********************************************************************* // This function is prepared to use the automatic derivatives toolbox of // Scilab. This toolbox can be instaled using the ATOMS installer (package diffcode). // This function evaluates the residuals of the compound balances for each stream: // the 'A' matrix, and then concatenates with the normalization equations: // x_{j,i}, where i= stream and j = compounds // Example for a 3 stream system with 3 compounds // for a simple splitter where the incidence matrix is Ainput = [a11 a12 a13] // the resulting system is: // eq1 = a11.F1.x11 + a12.F2.x12 +a13.F3.x13 // eq2 = a12.F1.x21 + a12.F2.x22 +a13.F3.x23 // eq3 = a12.F1.x31 + a12.F2.x32 +a13.F3.x33 // for each stream, we have \sum_{xi}^n x_{i,j} -1 = 0, , resulting in 3 equaitons // eq4 = x11 + x21 + x31 = 1 // eq5 = x12 + x22 + x32 = 1 // eq6 = x13 + x23 + x33 = 1 // Notice that the x is a column vector and must pe previoulsy organized // Outputs: // y,: the constraints residuals // Inputs: // x: the column vector of the variables, after the x = [flow, compounds] // and x = x(:) operation // Ainput: the incidence matrix of the total flow // Ncomp: number of compounds // // get the sizes // [Aeqp, Astreams] =size(Ainput); // resize the x vector xx=matrix(x,Astreams,Ncomp+1) // organize the variables appropriately TotalFlowMeasured = xx(:,1)'; compoundMeasured = xx(:, 2:$); // Build the functions for the constraints residuals for i = 0:Aeqp - 1 // pause A(i*(Ncomp) + 1:(i + 1)*Ncomp ) = sum((ones(Ncomp,1)*Ainput(i+1,:)).*(ones(Ncomp,1)*TotalFlowMeasured.*compoundMeasured'),'c') end // next we'll build the derivatives of the normalization equations: // for each stream, we have \sum_{j}^streams x_{j,i} -1 = 0, , resulting in "Astreams" equations //pause Asum = sum (compoundMeasured','r')' ; y=[A;Asum]; endfunction
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clc Tk = 360 // time taken by tool to cut before sharpening in min. Tc = 20 // time taken to change the tool in min. T = 4320 // time taken before it is discarded in min. t = (Tc*Tk)/T // tool change time per cycle in min. printf("\n Unit tool change time per cycle = %0.2f min" , t )
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//Ex9.3.5.1.;Calculate Energy generated R=12;//unit=m; R is the range r=3;//unit=m; the head below turbine stops operating time=(44700/2); A=30*10^6; g=9.80; p=1025; //The total theoretical work W=integrate('1','w',R,r); W=(g*p*A*((R^2)-(r^2)))/2; printf(" W=%f ",W); //The average power generated Pav=W/time;//unit=watts printf("\n The average power generated=%f watts",Pav); pav=(Pav/1000)*3600;//unit=kWh printf("\n The average power generated=%f kWh",pav) //the energy generated Energy_generated=pav*0.73 printf("\n Energy generated=%f kWh",Energy_generated);
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Ra = 37/2; Rb = 4; Rc = 12; Rc = 7/2; Wa
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clc; clear; h=6.63*10^-34 //Plancks constant in J-s c=3*10^8 //velocity of light in m/s E0=6.20*10^3 //energy of photon in keV freq_s=0.5/100 //frequency shift m=9.1*10^-31 //mass in kg //CALCULATION lambda0=(h*c)/(E0*1.6*10^-19) //wavelength in m delta_E=(freq_s*E0)/10^3 //Loss in energy of photon in keV E=(E0/10^3)-delta_E //energy of scattered photon on keV lambda=(h*c)/(E*10^3*1.6*10^-19) //wavelength of scattered photon in m delta_lambda=lambda-lambda0 //compton shift phi=acosd(1-(m*c*delta_lambda)/h) mprintf("The angle through which Xray is scattered is = %2.1f degree",phi) //The answer varies due to round off error.
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//Book Name:Fundamentals of Electrical Engineering //Author:Rajendra Prasad //Publisher: PHI Learning Private Limited //Edition:Third ,2014 //EX3_16.sce clc; clear; //from the mesh equations coefficient of I1,I2,and source is given below a1=complex(4,-2); b1=-complex(3,-2); c1=complex(12,0); a2=-complex(3,4); b2=complex(5,3); c2=complex(0); del1=det([c1 b1;c2 b2]); del2=det([a1 c1;a2 c2]); del=det([a1 b1;a2 b2]); I2=del2/del; I1=del1/del; V2=(2*I2)+((3*(-2*%i))*(I1-I2)); V2_mag=sqrt(real(V2)^2+imag(V2)^2); V2_ang=atand(imag(V2)/real(V2)); printf("\n V2=%1.2f angle:%2.2f degree \n",V2_mag,V2_ang) //Anawer vary dueto round off error //Result:v2(t)=4.87*sqrt(2) sin(2t-66.04)
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//”CˆÓ‹É”z’u A=[1 0;0 2]; b=[1;1]; poles=[-2,-3]; k_=ppol(A,b,poles); k=-k_ spec(A+b*k)
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opeGaAs = 36; //optical phonon energies in GaAs in meV opeGaN = 90; //optical phonon energies in GaN in meV disp(opeGaAs,"The optical phonon energies in GaAs (in meV)") disp(opeGaN,"The optical phonon energies in GaN (in meV)") disp ("If the electron energies are below these values, there is no phonon emission.The phonon occupation number in GaAs at 300 K is 0.33 and in GaN is 0.032. Thus above threshold, the emission to absorption ratios are approximately 4:1 and 32:1 respectively.")
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//Introduction to Fiber Optics by A. Ghatak and K. Thyagarajan, Cambridge, New Delhi, 1999 //Example 13.2 //OS=Windows XP sp3 //Scilab version 5.5.2 clc; clear; //given //Vc(t)=V0*(1-exp(-t/(R*C))) is the voltage across capacitance in an RC circuit //Hence, the time t=R*C*(-log(1-Vc/V0)) //The Rise time is the time taken by a system to rise from 10% to 90% of maximum value //So, it is given as Tr=T90-T10 where T90 is time when Vc is 90% of maximum value and T10 is time when Vc is 10% of maximum value //i.e. Tr=R*C*(-log(1-0.9))-R*C*(-log(1-0.1)) //Let Tr=R*C*k; where k=log(1-0.1))-log(1-0.9) k=log(1-0.1)-log(1-0.9); mprintf("\n The Rise Time Tr=%.2fRC",k); //Now, The 3dB bandwidth is given as Deltaf=1/(2*%pi*R*C); //Let Deltaf=m/(R*C); where m=1/(2*%pi) m=1/(2*%pi); mprintf("\n The 3dB bandwidth Deltaf=%.2f/RC",m); //By multiplying expressions of Tr and Deltaf, we eliminate RC from the expressions //Rearranging te terms, we get Tr in terms of Deltaf mprintf("\n Rise time in terms of Bandwidth is given as:"); mprintf("\n Tr=%.2f/Deltaf",k*m);
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clc //Intitalisation of variables clear n1= 2 //moles n2= 2 //moles n3= 1 //mole h1= 54.6 //cal h2= 7.8 //cal h3= -69.6 //cal R= 1.987 //cal T= 25 //C //CALCULATIONS dF= -n1*h1-(-n2*h2+n3*h3) Kp= 10^(-dF*1000/(2.303*R*(273.2+T))) //RESULTS printf ('dF = %.f kcal ',dF) printf ('\n equillibrium constant = %.1e ',Kp)
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2;er;0 5;r 4;- p1;-;-;-;3;1;2 -;p2;-;-;0;1;1 usePlayerItem 1 r 2 status
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clc disp("Example 14.10") printf("\n") s=%s; //Applying KVL equation to the two loops we get //V1=3*I1+3*(I1+I2) //V2=7*I1+3*(I1+I2)+2*I2 //On solving we get disp("6*I1+3*I2=V1 (1)"); disp("10*I1+5*I2=V2 (2)"); //The equations which contain Z parameters are //V1=Z11*I1+Z12*I2 //V2=Z21*I1+Z22*I2 //On comparing (1) and (2) with above equations Z11=6; Z12=3; Z21=10; Z22=5; disp(Z11,"Z11=") disp(Z12,"Z12=") disp(Z21,"Z21=") disp(Z22,"Z22=") disp("As DZZ results in zero(0) therefore Y parameters are not defined ")
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// Scilab code Ex5.28: Pg 185-186 (2008) clc; clear; L_1 = 25e-03; // Self-inductance of first coil, H L_2 = 40e-03; // Self-inductance of second coil, H I = 0.25; // Electric current in coils, A k =0.8; // Coupling coefficient // Part (a) W_1 = (L_1*(I^2))/2; // Energy stored in first coil, J W_2 = (L_2*(I^2))/2; // Energy stored in second coil, J M = k*sqrt(L_1*L_2); // Mutual inductance of coils // Part (b) W_M = M*(I)*(I); // Energy stored due to mutual inductance of coils, J W_sa = W_1 + W_2 + W_M; // Energy stored by two inductors when connected in series aiding, J W_so = W_1 + W_2 - W_M; // Energy stored by two inductors when connected in series opposition, J printf("\nEnergy stored in first coil = %4.2f mJ", W_1/1e-03) printf("\nEnergy stored in second coil = %4.2f mJ", W_2/1e-03) printf("\nEnergy stored by two inductors when connected in series aiding = %3.1f mJ", W_sa/1e-03) printf("\nEnergy stored by two inductors when connected in series opposition = %4.2f mJ", W_so/1e-03) // Result // Energy stored in first coil = 0.78 mJ // Energy stored in second coil = 1.25 mJ // Energy stored by two inductors when connected in series aiding = 3.6 mJ // Energy stored by two inductors when connected in series opposition = 0.45 mJ
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clear; clc; close; clf; x=linspace(-3,4,8); y=(x-1)^2; plot2d(x,y,3); xtitle("Curve of y=(x-1)^2","x axis","y axis"); legend("y=(x-1)^2"); xgrid();
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// exa 8.7 Pg 232 clc;clear;close; // Given Data dv=30;// mm Wv=10;// N Wl=25;// N lf=100;// mm del1=20;// mm p=3.5;// N/mm.sq. valve_lift=2;// mm C=6;// spring index tau=500;// N/mm.sq. G=0.84*10**5;// N/mm.sq. W=(%pi/4)*dv**2*p;// N (load on the valve at operating condition) W1=W-Wv;//N (Net load on the valve at operating condition) //W1*100=Wl*150+S1*200+P*300 // taking momens about the fulcrum //S1*200+P*300=W1*100-Wl*150 ...eqn(1) valve_lift=20*100/200;// mm //from figure (when spring is extended by 20 mm) spring_extension=2*200/100;// mm // from figure (when valve is lifted 2 mm) valve_load=W*12/10;// N // (when valve is lifted 2 mm) W2=valve_load-Wv;// N // (when valve is lifted 2 mm) del2=del1+4;// mm (when valve is lifted) //S2=S1*del2/del1;// spring force when valve is lifted //S1*del2/del1-s2=0 ... eqn(1) //W2*100=Wl*150+S2*200+P*300 // taking momens about the fulcrum //S2*200+P*300 =W2*100-Wl*150 ... eqn(2) //S1*200+P*300=W1*100-Wl*150 ...eqn(3) // solving above 3 eqn. by matrix method A=[del2/del1 -1 0;200 0 300;0 200 300]; B=[0;W1*100-Wl*150;W2*100-Wl*150]; X=A**-1*B;// solution matrix S1=X(1);// N S2=X(2);// N printf('\n Spring force when valve is lifted = %.1f N',S2) printf('\n\n Design of spring - ') k=(S2-S1)/(del2-del1);// N/mm (Spring stiffness) printf('\n Spring stiffness = %.2f N/mm',k) Kw=(4*C-1)/(4*C-4)+0.615/C;// Wahl's correction factor printf('\n Wahl''s correction factor = %.4f',Kw) // tau=Kw*8*S2*C/%pi/d**2 max. shear stress d=sqrt(Kw*8*S2*C/%pi/tau);// mm (spring diameter) printf('\n spring diameter = %.2f mm or %.f mm',d,d) d=ceil(d);// mm // k=G*d/(8*C**3*n) (Spring stiffness) n=G*d/(8*C**3*k);// no. of active coils printf('\n no. of active coils = %.2f. Use n=7',n) n=ceil(n);// rounding nt=n+1;// total no. of active coils printf('\n total no. of active coils = %.f',nt) p=lf/(n-1);// mm (pitch of coils) printf('\n pitch of coils = %.2f mm',p)
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function[So,N]=fn_op_wave(n,S,O,varargin) select O case 1 then N = [n+varargin(1)] ; So = [S]; case 2 then N=[(-1)*(n)]; So=[S]; case 3 then N=[n/varargin(1)]; So=[S]; end endfunction
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//Chapter-2,Example2_21_6,pg 2-49 c=5*10^28 //concentration of Si atoms e=1.6*10^-19 //charge on electron u=0.048 //mobility of hole s=4.4*10^-4 //conductivity of Si //since millionth Si atom is replaced by an indium atom n=c*10^-6 sp=u*e*n //conductivity of resultant printf("conductivity =") disp(sp) printf("mho/m")
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// **** Purpose **** // finds the surrounding sites of a unitcell up to Nth order // **** Variables **** // [primitive]: 3x3 / 2x2 / 1x1, real // <= the primitive vectros in row // [sublatt]: nx3 / nx2 / nx1, real // <= the (x,y,z) cartisian coordinate of sublattices in the unitcell // [vec_order]: 1x1, integer // <= c1*a1+c2*a2+c3*a3, if vec_order=2, then it lists all neighbors // within -2 <= [c1,c2,c3] <= +2, must larger than 1 // [NN_criterion]: 1x1, real // <= criterion of labeling the NN order. if the difference between // is small than this valus, they are consider as the same NN order. // [NN_order]:1x1, int // <= neighbor order higer than this will be ignored in surr_site. // [surr_site]: list(total_sublatt) -> total_nb x 9 x , real // => the surrounding sites of that sublattice up to N-th vec_order // [nn_order,distant, sublattice label, n1, n2, n3, x, y, z] // r=n1*a1+n2*a2+n3*a3+(sublatt(n,:))=[x,y,z] // **** Version **** // 05/01/2014 first built // 05/20/2014 full rewrite, performance improved, accept low dimension // ba_ratio, ca_ratio inputs removed. // 05/29/2014 fix bug, distant equal set to 10^(-6); // 06/03/2014 fix bug, surr_site may have different for each sublatt, // so surr_site has been modified to list-type! // 01/07/2016 add vec_order and NN_criterion. So the degree of search // is defined by user. Performance and readability have // also much improved. // **** Comment **** // 1. This function accepts low dimension input. e.g , if your premitive // cell and sublatt are two dimenstion vectors, the code will // generate surr_site table with n3 and z as zero. Use it carefully. // 2. One should tune vec_order to make sure the nn_order is correct // for high order NNs. // 3. NN: n-th neighbors // 4. Don't put too regious value to NN_criterion, it should be around // 0.1 to get reasonable results function [surr_site]=PIL_uc_nb(primitive,sublatt,vec_order,NN_criterion,NN_order); // variable check if length(primitive(1,:))~=length(sublatt(1,:)) then disp('Error: PIL_uc_nb, dimeisnion inconsistent!'); abort; end if vec_order <1 then disp('Error: PIL_uc_nb, vec_order must be greater than 1') abort end // generate unit cell index dim=length(primitive(1,:)); tot_sublat=length(sublatt(:,1)); select dim case 3 loop_index=PIL_nest_loop([-vec_order,vec_order;-vec_order,vec_order;-vec_order,vec_order]) case 2 loop_index=PIL_nest_loop([-vec_order,vec_order;-vec_order,vec_order]) case 1 loop_index=PIL_nest_loop([-vec_order,vec_order]) end // search all sites reside in the super cell count=0; site_pos=zeros(tot_sublat*(2*vec_order+1)^dim,7); for n=1:length(loop_index(:,1)) rc=loop_index(n,:)*primitive; for m=1:tot_sublat count=count+1; site_pos(count,1:4)=[m,loop_index(n,:)]; site_pos(count,5:7)=PIL_vec_3d(rc+sublatt(m,:)); end end // construct surr_site tot_site=length(site_pos(:,1)); surr_site=list(); for n=1:tot_sublat surr_site(n)=zeros(tot_site,9) //[nn_order,distant, sublattice label, n1, n2, n3, x, y, z] for m=1:tot_site d=norm(site_pos(m,5:7)-sublatt(n,:)); surr_site(n)(m,:)=[0,d,site_pos(m,:)] end surr_site(n)=PIL_lsort(surr_site(n),'c',[2:9,1],'i') // label order order=0; for m=2:tot_site if ((surr_site(n)(m,2)-surr_site(n)(m-1,2))) >= NN_criterion then order=order+1; end if order > NN_order then // quit for higher order neighbors surr_site(n)=surr_site(n)(1:m-1,:); break; else // label neighbor order surr_site(n)(m,1)=order; end end // reorder based based on sublatt label surr_site(n)=PIL_lsort(surr_site(n),'c',[1,3:9,2],'i') end endfunction // examples of this function: (TaAs structure) //primitive=.. // data from ab initio //[ 6.305100000 0.000000000 0.000000000;.. // 4.439200000 4.477400000 0.000000000;.. // -5.372100000 -2.238700000 2.425300000 ] //sublatt=.. //[0.00000 0.00000 0.00000;.. // 3.15258 0.00000 1.21265;.. // 4.48037 1.86708 0.00000;.. // 1.32785 1.86708 1.21265] // //vec_order=1 //NN_criterion=0.1
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//Example 5 //given m=9.1*(10^-31)//in kg v=300//in m/s h=6.6*(10^-34)// in j-s p=m*v disp("The electrom momentum in kg-m/s=") disp(p) delta_p=(0.0001)*p disp("delta_p in kg-m/s=") disp(delta_p) delta_x=(h/delta_p) disp("Minimum uncertainaity in m=") disp(delta_x)
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FLMLEChiSqUdt-NZ-01.tst
-- Fuzzy Logix, LLC: Functional Testing Script for DB Lytix functions on Netezza -- -- Copyright (c): 2014 Fuzzy Logix, LLC -- -- NOTICE: All information contained herein is, and remains the property of Fuzzy Logix, LLC. -- The intellectual and technical concepts contained herein are proprietary to Fuzzy Logix, LLC. -- and may be covered by U.S. and Foreign Patents, patents in process, and are protected by trade -- secret or copyright law. Dissemination of this information or reproduction of this material is -- strictly forbidden unless prior written permission is obtained from Fuzzy Logix, LLC. -- Functional Test Specifications: -- -- Test Category: Basic Statistics -- -- Test Unit Number: FLMLEChiSqUdt-NZ-01.tst -- -- Name(s): FLMLEChiSqUdt -- -- Description: Fit a ChiSq distribution -- -- Applications: -- -- Signature: -- -- Parameters: See Documentation -- -- Return value: Table -- -- Last Updated: 07-06-2017 -- -- Author: Positive test cases: <Zhi.Wang@fuzzyl.com> -- Negative test cases: <Joe.Fan@fuzzyl.com> -- Netezza test cases: <Anurag.Reddy@fuzzyl.com> -- Kamlesh Meena -- -- BEGIN: TEST SCRIPT \time --.RUN file=../PulsarLogOn.sql --.SET WIDTH 1000 --SET ROLE ALL; -- BEGIN: NEGATIVE TEST(s) ---- Initialize Fit Distribution test -- Initialize tblSimDistMap DROP TABLE tblSimDistMap IF EXISTS; CREATE TABLE tblSimDistMap ( NewGroupID BIGINT, Distribution VARCHAR(100), GroupID BIGINT ) DISTRIBUTE ON(NewGroupID); INSERT INTO tblSimDistMap (Distribution, GroupID, NewGroupID) SELECT a.Distribution, a.GroupID, ROW_NUMBER() OVER (ORDER BY a.tbl, a.Distribution, a.GroupID) AS NewGroupID FROM ( SELECT DISTINCT 1 AS tbl, a.Distribution, GroupID FROM tblMLETest1 a Union ALL SELECT DISTINCT 2 AS tbl, a.Distribution, GroupID FROM tblMLETest2 a ) a; -- Initialize tblSimDistFloat DROP TABLE tblSimDistFloat IF EXISTS; CREATE TABLE tblSimDistFloat ( NewGroupID BIGINT, Distribution VARCHAR(100), GroupID BIGINT, Num_Val DOUBLE PRECISION ) DISTRIBUTE ON (NewGroupID); INSERT INTO tblSimDistFloat (NewGroupID, Distribution, GroupID, Num_Val) SELECT b.NewGroupID, a.Distribution, a.GroupID, a.Num_Val FROM tblMLETest1 a, tblSimDistMap b WHERE a.Distribution = b.Distribution And a.GroupID = b.GroupID Union ALL SELECT b.NewGroupID, a.Distribution, a.GroupID, CAST(a.Num_Val AS DOUBLE PRECISION) FROM tblMLETest2 a, tblSimDistMap b WHERE a.Distribution = b.Distribution AND a.GroupID = b.GroupID; -- Initialize tblSimDistInt DROP TABLE tblSimDistInt IF EXISTS; CREATE TABLE tblSimDistInt ( NewGroupID BIGINT, Distribution VARCHAR(100), GroupID BIGINT, Num_Val INTEGER ) DISTRIBUTE ON(NewGroupID); INSERT INTO tblSimDistInt (NewGroupID, Distribution, GroupID, Num_Val) SELECT b.NewGroupID, a.Distribution, a.GroupID, CAST(a.Num_Val AS INTEGER) FROM tblMLETest1 a, tblSimDistMap b WHERE a.Distribution = b.Distribution And a.GroupID = b.GroupID Union ALL SELECT b.NewGroupID, a.Distribution, a.GroupID, a.Num_Val FROM tblMLETest2 a, tblSimDistMap b WHERE a.Distribution = b.Distribution AND a.GroupID = b.GroupID; ---- Case 1: Stress test with different distributions (Num_Val is DOUBLE PRECISION) -- Case 1a: Fit FLMLEChiSqUdt onto Beta distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Beta')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1b: Fit FLMLEChiSqUdt onto Bradford distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Bradford')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1c: Fit FLMLEChiSqUdt onto Burr distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Burr')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1d: Fit FLMLEChiSqUdt onto Cauchy distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Cauchy')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1e: Fit FLMLEChiSqUdt onto Chi distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Chi')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1f: Fit FLMLEChiSqUdt onto ChiSq distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('ChiSq')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1g: Fit FLMLEChiSqUdt onto Cosine distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Cosine')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1h: Fit FLMLEChiSqUdt onto DoubleGamma distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('DoubleGamma')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1i: Fit FLMLEChiSqUdt onto DoubleWeibull distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('DoubleWeibull')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1j: Fit FLMLEChiSqUdt onto Erlang distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Erlang')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1k: Fit FLMLEChiSqUdt onto Exponential distribution WITH z (GroupID, Num_Val) AS ( SELECT a.NewGroupID, a.Num_Val FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Exponential') ) SELECT b.Distribution (FORMAT 'XXXXXXXXXXXXXXX'), b.GroupID, a.* FROM TABLE (FLMLEChiSqUdt(z.GroupID, z.Num_Val) HASH BY z.GroupID LOCAL ORDER BY z.GroupID,z.Num_Val) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1l: Fit FLMLEChiSqUdt onto ExtremeLB distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('ExtremeLB')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1m: Fit FLMLEChiSqUdt onto Fisk distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Fisk')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1n: Fit FLMLEChiSqUdt onto FoldedNormal distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('FoldedNormal')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1o: Fit FLMLEChiSqUdt onto Gamma distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Gamma')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1p: Fit FLMLEChiSqUdt onto GenLogistic distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('GenLogistic')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1q: Fit FLMLEChiSqUdt onto Gumbel distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Gumbel')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1r: Fit FLMLEChiSqUdt onto HalfNormal distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('HalfNormal')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1s: Fit FLMLEChiSqUdt onto HypSecant distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('HypSecant')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1t: Fit FLMLEChiSqUdt onto InvGamma distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('InvGamma')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1u: Fit FLMLEChiSqUdt onto InvNormal distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('InvNormal')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1v: Fit FLMLEChiSqUdt onto Laplace distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Laplace')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1w: Fit FLMLEChiSqUdt onto Logistic distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Logistic')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1x: Fit FLMLEChiSqUdt onto LogNormal distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('LogNormal')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1y: Fit FLMLEChiSqUdt onto Maxwell distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Maxwell')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1z: Fit FLMLEChiSqUdt onto Normal distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Normal')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1aa: Fit FLMLEChiSqUdt onto Pareto distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Pareto')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1ab: Fit FLMLEChiSqUdt onto Power distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Power')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1ac: Fit FLMLEChiSqUdt onto Rayleigh distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Rayleigh')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1ad: Fit FLMLEChiSqUdt onto Reciprocal distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Reciprocal')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1ae: Fit FLMLEChiSqUdt onto Semicircular distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Semicircular')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1af: Fit FLMLEChiSqUdt onto StudentsT distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('StudentsT')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1ag: Fit FLMLEChiSqUdt onto TransBeta distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('TransBeta')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1ah: Fit FLMLEChiSqUdt onto Triangular distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Triangular')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1ai: Fit FLMLEChiSqUdt onto Uniform distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Uniform')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1aj: Fit FLMLEChiSqUdt onto Weibull distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Weibull')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1ak: Fit FLMLEChiSqUdt onto Binomial distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Binomial')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1al: Fit FLMLEChiSqUdt onto Geometric distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Geometric')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1am: Fit FLMLEChiSqUdt onto Logarithmic distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Logarithmic')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1an: Fit FLMLEChiSqUdt onto NegBinomial distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('NegBinomial')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 1ao: Fit FLMLEChiSqUdt onto Poisson distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistFloat a WHERE UPPER(a.Distribution) = UPPER('Poisson')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; ---- Case 2: Stress test with different distributions (Num_Val is INTEGER) -- Case 2a: Fit FLMLEChiSqUdt onto Beta distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Beta')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2b: Fit FLMLEChiSqUdt onto Bradford distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Bradford')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2c: Fit FLMLEChiSqUdt onto Burr distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Burr')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2d: Fit FLMLEChiSqUdt onto Cauchy distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Cauchy')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2e: Fit FLMLEChiSqUdt onto Chi distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Chi')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2f: Fit FLMLEChiSqUdt onto ChiSq distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('ChiSq')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2g: Fit FLMLEChiSqUdt onto Cosine distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Cosine')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2h: Fit FLMLEChiSqUdt onto DoubleGamma distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('DoubleGamma')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2i: Fit FLMLEChiSqUdt onto DoubleWeibull distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('DoubleWeibull')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2j: Fit FLMLEChiSqUdt onto Erlang distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Erlang')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2k: Fit FLMLEChiSqUdt onto Exponential distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Exponential')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2l: Fit FLMLEChiSqUdt onto ExtremeLB distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('ExtremeLB')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2m: Fit FLMLEChiSqUdt onto Fisk distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Fisk')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2n: Fit FLMLEChiSqUdt onto FoldedNormal distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('FoldedNormal')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2o: Fit FLMLEChiSqUdt onto Gamma distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Gamma')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2p: Fit FLMLEChiSqUdt onto GenLogistic distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('GenLogistic')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2q: Fit FLMLEChiSqUdt onto Gumbel distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Gumbel')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2r: Fit FLMLEChiSqUdt onto HalfNormal distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('HalfNormal')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2s: Fit FLMLEChiSqUdt onto HypSecant distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('HypSecant')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2t: Fit FLMLEChiSqUdt onto InvGamma distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('InvGamma')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2u: Fit FLMLEChiSqUdt onto InvNormal distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('InvNormal')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2v: Fit FLMLEChiSqUdt onto Laplace distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Laplace')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2w: Fit FLMLEChiSqUdt onto Logistic distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Logistic')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2x: Fit FLMLEChiSqUdt onto LogNormal distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('LogNormal')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2y: Fit FLMLEChiSqUdt onto Maxwell distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Maxwell')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2z: Fit FLMLEChiSqUdt onto Normal distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Normal')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2aa: Fit FLMLEChiSqUdt onto Pareto distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Pareto')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2ab: Fit FLMLEChiSqUdt onto Power distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Power')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2ac: Fit FLMLEChiSqUdt onto Rayleigh distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Rayleigh')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2ad: Fit FLMLEChiSqUdt onto Reciprocal distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Reciprocal')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2ae: Fit FLMLEChiSqUdt onto Semicircular distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('SemiCircular')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2af: Fit FLMLEChiSqUdt onto StudentsT distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('StudentsT')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2ag: Fit FLMLEChiSqUdt onto TransBeta distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('TransBeta')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2ah: Fit FLMLEChiSqUdt onto Triangular distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Triangular')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2ai: Fit FLMLEChiSqUdt onto Uniform distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Uniform')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2aj: Fit FLMLEChiSqUdt onto Weibull distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Weibull')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2ak: Fit FLMLEChiSqUdt onto Binomial distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Binomial')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2al: Fit FLMLEChiSqUdt onto Geometric distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Geometric')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2am: Fit FLMLEChiSqUdt onto Logarithmic distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Logarithmic')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2an: Fit FLMLEChiSqUdt onto NegBinomial distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('NegBinomial')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 2ao: Fit FLMLEChiSqUdt onto Poisson distribution SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistInt a WHERE UPPER(a.Distribution) = UPPER('Poisson')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; ---- Case 3: Num_Val is constant (zero, one, 2^30) -- Case 3a: Num_Val is constant (zero) CREATE OR REPLACE VIEW vwSimDist AS SELECT a.NewGroupID, a.Distribution, a.GroupID, 0 AS Num_Val FROM tblSimDistFloat a WHERE a.Distribution = 'ChiSq'; SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM vwSimDist a WHERE UPPER(a.Distribution) = UPPER('ChiSq')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 3b: Num_Val is constant (one) CREATE OR REPLACE VIEW vwSimDist AS SELECT a.NewGroupID, a.Distribution, a.GroupID, 1 AS Num_Val FROM tblSimDistFloat a WHERE a.Distribution = 'ChiSq'; SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM vwSimDist a WHERE UPPER(a.Distribution) = UPPER('ChiSq')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 3c: Num_Val is constant (2^30) CREATE OR REPLACE VIEW vwSimDist AS SELECT a.NewGroupID, a.Distribution, a.GroupID, 2**30 AS Num_Val FROM tblSimDistFloat a WHERE a.Distribution = 'ChiSq'; SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM vwSimDist a WHERE UPPER(a.Distribution) = UPPER('ChiSq')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; ---- Case 4: Num_Val is very large -- Case 4a: Num_Val is very large (100% of array) CREATE OR REPLACE VIEW vwSimDist AS SELECT a.NewGroupID, a.Distribution, a.GroupID, 1000000 * a.Num_Val AS Num_Val FROM tblSimDistFloat a WHERE a.Distribution = 'ChiSq'; SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM vwSimDist a WHERE UPPER(a.Distribution) = UPPER('ChiSq')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 4b: Num_Val is very large (50% of array) CREATE OR REPLACE VIEW vwSimDist AS SELECT a.NewGroupID, a.Distribution, a.GroupID, CASE WHEN CAST(RANDOM() AS INT) = 1 THEN 1000000 ELSE 1 END * a.Num_Val AS Num_Val FROM tblSimDistFloat a WHERE a.Distribution = 'ChiSq'; SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM vwSimDist a WHERE UPPER(a.Distribution) = UPPER('ChiSq')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 4c: Num_Val is very large (10% of array) CREATE OR REPLACE VIEW vwSimDist AS SELECT a.NewGroupID, a.Distribution, a.GroupID, CASE WHEN CAST((RANDOM()*9 + 1) AS INT) = 1 THEN 1000000 ELSE 1 END * a.Num_Val AS Num_Val FROM tblSimDistFloat a WHERE a.Distribution = 'ChiSq'; SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM vwSimDist a WHERE UPPER(a.Distribution) = UPPER('ChiSq')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; ---- Case 5: Num_Val contains NULL -- Case 5a: 10% of values are NULL CREATE OR REPLACE VIEW vwSimDist AS SELECT a.NewGroupID, a.Distribution, a.GroupID, CASE WHEN CAST((RANDOM()*9 + 1) AS INT) = 1 THEN NULL ELSE a.Num_Val END AS Num_Val FROM tblSimDistFloat a WHERE a.Distribution = 'ChiSq'; SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM vwSimDist a WHERE UPPER(a.Distribution) = UPPER('ChiSq')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; -- Case 5b: 100% of values are NULL CREATE OR REPLACE VIEW vwSimDist AS SELECT a.NewGroupID, a.Distribution, a.GroupID, NULL AS Num_Val FROM tblSimDistFloat a WHERE a.Distribution = 'ChiSq'; SELECT b.Distribution, b.GroupID, a.* FROM ( SELECT a.NewGroupID, a.Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM vwSimDist a WHERE UPPER(a.Distribution) = UPPER('ChiSq')) AS z, TABLE (FLMLEChiSqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistMap b WHERE a.GroupID = b.NewGroupID ORDER BY 1,2; --case 6 ---Test case without local order by numval --NA for NZ ---- Drop tables after Pulsar test for fit distribution function DROP TABLE tblSimDistFloat; DROP TABLE tblSimDistInt; DROP TABLE tblSimDistMap; DROP VIEW vwSimDist; -- END: NEGATIVE TEST(s) -- BEGIN: POSITIVE TEST(s) ---- Positive Test 1 SELECT b.Nobs AS Nobs, a.DegreeOfFreedom AS Est_Df, b.Param1 AS Df, CASE WHEN ABS(a.DegreeOfFreedom - b.Param1)/b.Param1 < 0.5 THEN 'Passed' ELSE 'Check' END AS Hint FROM ( SELECT a.GroupID, a.Num_Val, a.Distribution, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM tblSimDistR a, tblSimDistRParams b WHERE UPPER(a.Distribution) = UPPER('ChiSq') AND UPPER(b.Distribution) = UPPER('ChiSq') AND a.GroupID = b.GroupID) AS z, TABLE (FLMLEChiSqUdt(z.GroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a, tblSimDistRParams AS b WHERE a.GroupID = b.GroupID AND b.Distribution='ChiSq' ORDER BY 3, 1; ---- Positive Test 2 TD-85 Teradata mistake CREATE VIEW view_chisq_100 AS SELECT 1 AS GroupID,a.SerialVal AS ObsID, FLSimChiSq(RANDOM()*10e9,6) AS NumVal FROM fzzlSerial a WHERE a.SerialVal <= 100; CREATE VIEW view_chisq_1000 AS SELECT 1 AS GroupID,a.SerialVal AS ObsID, FLSimChiSq(RANDOM()*10e9,6) AS NumVal FROM fzzlSerial a WHERE a.SerialVal <= 1000; CREATE VIEW view_chisq_10000 AS SELECT 1 AS GroupID,a.SerialVal AS ObsID, FLSimChiSq(RANDOM()*10e9,6) AS NumVal FROM fzzlSerial a WHERE a.SerialVal <= 10000; ---- Positive Test 2a SELECT a.* FROM ( SELECT a.GroupID AS NewGroupID, a.NumVal AS Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM view_chisq_100 a) AS z, TABLE (FLMLEchisqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a; ---- Positive Test 2b SELECT a.* FROM ( SELECT a.GroupID AS NewGroupID, a.NumVal AS Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM view_chisq_1000 a) AS z, TABLE (FLMLEchisqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a; ---- Positive Test 2c SELECT a.* FROM ( SELECT a.GroupID AS NewGroupID, a.NumVal AS Num_Val, NVL(LAG(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS begin_flag, NVL(LEAD(0) OVER (PARTITION BY a.GroupID ORDER BY a.GroupID), 1) AS end_flag FROM view_chisq_10000 a) AS z, TABLE (FLMLEchisqUdt(z.NewGroupID, z.Num_Val, z.begin_flag, z.end_flag)) AS a; DROP VIEW view_chisq_100; DROP VIEW view_chisq_1000; DROP VIEW view_chisq_10000; -- END: POSITIVE TEST(s) \time --END SCRIPT
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//Obtain path of solution file path = get_absolute_file_path('solution2_1.sce') //Obtain path of data file datapath = path + filesep() + 'data2_1.sci' //Clear all clc //Execute the data file exec(datapath) //Calculate weightage points for all materials //U - Ultimate tensile strength, H - Hardenability index, C - Cost //Store the summations of each category in Uweigh, Hweigh and Cweigh respectively Uweigh = 0 Hweigh = 0 Cweigh = 0 for i = 1:1:4 Uweigh = Uweigh + U(i) Hweigh = Hweigh + H(i) Cweigh = Cweigh + (C(i)^(-1)) end //Store percent strength for each material in Uper, Hper and Cper arrays according to respective categories //Store points for each material in Up, Hp and Cp arrays according to respective categories for i = 1:1:4 Uper(i) = U(i)/Uweigh Up(i) = Uper(i) * Uw Hper(i) = H(i)/Hweigh Hp(i) = Hper(i) * Hw Cper(i) = (C(i)^(-1))/Cweigh Cp(i) = Cper(i) * Cw end //Store total points for each material in t array for i = 1:1:4 t(i) = Up(i) + Hp(i) + Cp(i) end //Print result table. Refer Table 2.14 on page 53 printf('\n\t|Material Property\t|Low alloy steel\t|Plain carbon steel\t|Stainless steel\t|Chromium steel\n') printf('\na)\tTensile Strength') printf('\n\tPer cent') for i = 1:1:4 printf('\t\t%0.3f\t',Uper(i)) end printf('\n\tPoints') for i = 1:1:4 printf('\t\t\t%0.3f',Up(i)) end printf('\n\nb)\tHardenability') printf('\n\tPer cent') for i = 1:1:4 printf('\t\t%0.3f\t',Hper(i)) end printf('\n\tPoints') for i = 1:1:4 printf('\t\t\t%0.3f',Hp(i)) end printf('\n\nc)\tCost') printf('\n\tPer cent') for i = 1:1:4 printf('\t\t%0.3f\t',Cper(i)) end printf('\n\tPoints') for i = 1:1:4 printf('\t\t\t%0.3f',Cp(i)) end printf('\n\n\tTotal Points') for i = 1:1:4 printf('\t\t%0.3f\t',t(i)) end //Store all values of t in s array for i = 1:1:4 s(i) = t(i) end //Find the material with largest value of total points using s array for i = 1:1:3 if (s(i)>s(i+1)) then s(i+1) = s(i) end end //Largest value is obtained when i becomes 3 and the value is stored in s(i+1) //Display the best material choice = s(i+1) if(choice == t(1)) printf('\n\nLow alloy steel is the best material for the component\n') else if (choice == t(2)) printf('\n\nPlain carbon steel is the best material for the component\n') else if (choice == t(3)) printf('\n\nStainless steel is the best material for the component\n') else printf('\n\nChromium steel is the best material for the component\n') end
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clc clear //Input data Vm=100//Maximum voltage in V R=50//resitance in ohms //Calculations Vrms=(Vm/sqrt(2))//rms voltage in V Irms=(Vrms/R)//rms current in A Im=(Vm/R)//Maximum current in A //Output printf('rms current is %3.2f A and maximum current is %i A',Irms,Im)
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// Exa 1.1 clc; clear; close; format('v',5) // Given data R1=4;// in ohm R2= 6;// in ohm R3= 2;// in ohm V1= 24;// in V V2= 12;// in V // Applying KVL in Mesh ABEFA, V1 = (R1+R3)*I1 - R3*I2 (i) // Applying KVL in Mesh BCDEB, V2 = R3*I1 - (R2+R3)*I2 (ii) A= [(R1+R3) R3;-R3 -(R2+R3)];// assumed B= [V1 V2];// assumed I= B*A^-1;// Solving equations by matrix multiplication I1= I(1);// in A I2= I(2);// in A disp(I1,"The current through 4 ohm resistor in A is"); // current through 2 ohm resistor I= I1-I2;// in A disp(I,"The current through 2 ohm resistor in A is"); disp(I2,"The current through 6 ohm resistor in A is"); disp("That is "+string(abs(I2))+" A current flows in 6 ohm resistor from C to B")
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2023-05-31T04:06:22.931111
2022-09-13T14:41:51
2022-09-13T14:41:51
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Scilab
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bigM.sci
function [x,Z,z,ul,iters]=bigM(F,blck_szs,c,x0,M,nu,abstol,reltol,tv,maxiters); // [x,Z,z,ul,iters]=bigM(F,blck_szs,c,x0,M,nu,abstol,reltol,tv,maxiters); // // minimize c^T x // subject to F(x) = F0 + x1*F1 + ... + xm*Fm >= 0 // Tr F(x) <= M // // maximize -Tr F0*(Z-zI) - Mz // subject to Tr Fi*(Z-zI) = c_i // Z >= 0, z>= 0 // // Convergence criteria: // (1) maxiters is exceeded // (2) duality gap is less than abstol // (3) primal and dual objective are both positive and // duality gap is less than (reltol * dual objective) // or primal and dual objective are both negative and // duality gap is less than (reltol * minus the primal objective) // (4) reltol is negative and // primal objective is less than tv or dual objective is greater // than tv // // Input arguments: // F: (sum_i n_i^2) times (m+1) matrix // [ F_0^1(:) F_1^1(:) ... F_m^1(:) ] // [ F_0^2(:) F_1^2(:) ... F_m^2(:) ] // ... ... ... // [ F_0^L(:) F_1^L(:) ... F_m^L(:) ] // F_i^j: jth block of F_i, size n_i times n_i. // blck_szs: L-vector [n_1 ... n_L], dimensions of diagonal blocks. // c: m-vector. Specifies primal objective. // x0: m-vector. The primal starting point. F(x0) > 0. // M: scalar. M > Tr F(x0). // nu: >= 1.0. Controls the rate of convergence. // abstol: absolute tolerance. // reltol: relative tolerance. Has a special meaning when negative. // tv: target value. // maxiters: maximum number of iterations. // // Output arguments: // x: m-vector; last primal iterate. // Z: last dual iterate; block-diagonal matrix stored as // [ Z^1(:); Z^2(:); ... ; Z^L(:) ]. // z: scalar part of last dual iterate. // ul: ul(1): primal objective, ul(1): dual objective. // iters: number of iterations taken. [rowf,colf]=size(F); m = colf-1; if (rowf ~= sum(blck_szs.*blck_szs)) error('Dimensions of F do not match blck_szs.'); end; [rowx0,colx0]=size(x0); if (rowx0 ~= m) | (colx0 ~= 1) error('x0 must be an m-vector.'); end; if (prod(size(x0)) ~= m), error('c must be an m-vector.'); end; // I is the identity I = zeros(rowf,1); blck_szs=matrix(blck_szs,1,prod(size(blck_szs))); k=0; for n=blck_szs, I(k+[1:n*n]) = matrix(eye(n,n),n*n,1); // identity k = k+n*n; // k = sum n_i*n_i end; // Z0 = projection of I on dual feasible space Z0 = I-F(:,2:m+1) * ... ( (F(:,2:m+1)'*F(:,2:m+1)) \ ( F(:,2:m+1)'*I - c ) ); // mineigZ is the smallest eigenvalue of Z0 mineigZ = 0.0; k=0; for n=blck_szs, mineigZ = min(mineigZ, min(real(spec(matrix(Z0(k+[1:n*n]),n,n))))); k=k+n*n; end; // z = max( 1e-5, -1.1*mineigZ ) Z0(k+1) = max( 1e-5, -1.1*mineigZ); Z0(1:k) = Z0(1:k) + Z0(k+1)*I; if (M < I'*F*[1;x0] + 1e-5), error('M must be strictly greater than trace of F(x0).'); end; // add scalar block Tr F(x) <= M F = [F; M-I'*F(:,1),-I'*F(:,2:m+1)]; blck_szs = [blck_szs,1]; [x,Z,ul,info]=... semidef(x0,pack(Z0),pack(F),blck_szs,c,[nu,abstol,reltol,tv,maxiters]); iters = info(2); nz=prod(size(Z)) z=Z(nz) Z=unpack(Z(1:nz-1),blck_szs(1:prod(size(blck_szs))-1)) Z = Z(1:k);