How can i get exact data from a figure? (2024)

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open('Exercise_1.fig')

xd = get(get(gca,'children'),'xdata'); % Obtain xdata from the plot figure

yd = get(get(gca,'children'),'ydata'); % Obtain ydata from the plot figure

x = linspace(min(xd), max(xd), 200); % Resample x data

y = interp1(xd, yd, x); % Interpolate obtained data @ x resampled data

hold on

plot(x,y, 'r-.', 'LineWidth', 1)

legend('Original Figure Data', 'Obtained and Interpolated', 'Location', 'NW')

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D = [0 0

93.07876 0.224404

186.1575 0.476858

262.5298 0.729313

303.1026 0.869565

310.2625 1.290323

319.8091 1.598878

329.3556 1.486676

341.2888 1.318373

353.222 1.542777

362.7685 1.851332

372.315 2.103787

377.0883 2.412342

381.8616 2.664797

386.6348 2.889201

391.4081 3.169705

396.1814 3.45021

400.9547 3.702665

408.1146 3.98317

410.5012 4.235624

415.2745 4.460028

420.0477 4.712482

424.821 4.964937

446.3007 5.021038

467.7804 5.105189

477.327 5.329593

484.4869 5.553997

494.0334 5.778401

501.1933 5.946704

508.3532 6.143058

515.5131 6.367461

522.673 6.563815

529.8329 6.788219

536.9928 7.040673

544.1527 7.265077

548.926 7.517532

556.0859 7.798036

565.6325 8.078541

572.7924 8.387097

579.9523 8.695652

589.4988 9.004208

594.2721 9.284712

601.432 9.565217

606.2053 9.817672

613.3652 10.07013

625.2983 9.901823

637.2315 9.677419

649.1647 9.509116

663.4845 9.340813

675.4177 9.11641

684.9642 9.340813

692.1241 9.565217

696.8974 9.817672

704.0573 10.07013

706.4439 10.18233

718.3771 10.26648

720.7637 10.49088

723.1504 10.63114

725.537 10.79944

727.9236 10.96774

730.3103 11.1641

732.6969 11.41655

735.0835 11.64095

737.4702 11.86536

739.8568 12.08976

742.2434 12.37027

744.6301 12.62272

747.0167 12.84712

751.79 13.09958

756.5632 13.29593

761.3365 13.54839

766.1098 13.77279

770.8831 13.99719

775.6563 14.2216

780.4296 14.446

785.2029 14.69846

789.9761 14.89481

792.3628 15.11921

797.136 15.28752

801.9093 15.45582

806.6826 15.68022

811.4558 15.84853

813.8425 16.10098

818.6158 16.32539

828.1623 16.63394

830.5489 16.91445

835.3222 17.13885

840.0955 17.36325

844.8687 17.64376

852.0286 17.89621

875.895 17.89621

890.2148 17.89621

902.148 17.89621

918.8544 17.89621

926.0143 17.89621

933.1742 17.75596

940.3341 17.58766

947.494 17.3913

952.2673 17.223

954.6539 17.0547

964.2005 16.91445

971.3604 16.69004

978.5203 16.46564

985.6802 16.24123

995.2267 15.98878

1002.387 15.79243

1009.547 15.53997

1016.706 15.31557

1028.64 15.03506

1033.413 14.78261

1035.8 14.5582

1038.186 14.36185

1040.573 14.1655

1042.959 13.94109

1045.346 13.74474

1047.733 13.52034

1050.119 13.32398

1052.506 13.09958

1054.893 12.90323

1059.666 12.65077

1062.053 12.39832

1064.439 12.14586

1069.212 11.80926

1071.599 11.5568

1076.372 11.3324

1078.759 11.07994

1083.532 10.85554

1090.692 10.63114

1097.852 10.32258

1107.399 10.07013

1109.785 9.873773

1112.172 9.649369

1114.558 9.453015

1116.945 9.284712

1114.558 9.088359

1116.945 8.920056

1116.945 9.11641

1119.332 9.284712

1121.718 9.453015

1121.718 9.621318

1121.718 9.789621

1124.105 10.01403

1124.105 10.21038

1126.492 10.40673

1133.652 10.40673

1136.038 10.23843

1138.425 10.09818

1145.585 9.929874

1145.585 9.70547

1147.971 9.509116

1147.971 9.284712

1147.971 9.14446

1152.745 8.948107

1155.131 8.723703

1157.518 8.499299

1162.291 8.274895

1167.064 7.99439

1171.838 7.798036

1171.838 7.573633

1171.838 7.293128

1176.611 7.040673

1178.998 6.788219

1181.384 6.591865

1183.771 6.367461

1186.158 6.171108

1188.544 5.974755

1190.931 5.778401

1195.704 5.525947

1198.091 5.357644

1200.477 5.217391

1200.477 5.077139

1202.864 5.13324

1202.864 5.301543

1205.251 5.441795

1202.864 5.553997

1202.864 5.778401

1202.864 6.030856

1202.864 6.227209

1205.251 6.395512

1205.251 6.591865

1205.251 6.84432

1205.251 7.040673

1207.637 7.237027

1207.637 7.489481

1210.024 7.657784

1210.024 7.826087

1214.797 7.826087

1214.797 7.713885

1214.797 7.573633

1217.184 7.461431

1217.184 7.293128

1221.957 7.096774

1221.957 6.816269

1226.73 6.619916

1229.117 6.367461

1231.504 6.143058

1243.437 6.058906

1245.823 5.890603

1248.21 5.638149

1252.983 5.385694

1252.983 5.189341

1255.37 4.908836

1260.143 4.684432

1260.143 4.460028

1264.916 4.235624

1267.303 4.01122

1272.076 3.814867

1276.85 3.955119

1281.623 4.123422

1286.396 4.235624

1291.169 4.347826

1295.943 4.431978

1303.103 4.291725

1305.489 4.123422

1307.876 3.955119

1310.263 3.786816

1315.036 3.562412

1315.036 3.281907

1315.036 3.057504

1319.809 2.8331

1317.422 2.524544

1319.809 2.215989

1322.196 1.991585

1322.196 1.71108

1324.582 1.514727

1324.582 1.234222

1324.582 1.009818

1329.356 1.093969

1334.129 1.262272

1338.902 1.430575

1343.675 1.654979

1348.449 1.823282

1353.222 1.963534

1357.995 2.103787

1362.768 2.215989

1367.542 2.328191

1372.315 2.131837

1372.315 1.935484

1379.475 1.767181

1381.862 1.598878

1384.248 1.430575

1386.635 1.262272

1389.021 1.093969

1403.341 1.12202

1420.048 1.206171

1439.141 1.290323

1460.621 1.374474

1477.327 1.430575

1486.874 1.430575

498.807 1.234222

1510.74 1.037868

1520.286 0.785414

1529.833 0.56101

1539.379 0.392707

1548.926 0.252454

553.699 0.112202

1558.473 0 ];

[x, IDX] = sort(D(:,1));

y = D(IDX, 2);

yy = smoothdata(y, 'gaussian', 5);

plot(x,yy, 'b--', 'LineWidth', 2)

hold on

FUN = @(a, x) a(1) * exp(-((x - a(2)) / a(3)).^2); % Gaussian model

a0 = [15; 777; 333]; % Initial guess values for a

MODEL = fitnlm(x, yy, FUN, a0)

plot(x, MODEL.Fitted, 'm-', 'LineWidth', 2);

legend('Data', 'Gaussian Fit Model')

grid on

xlabel('Time, [s]')

ylabel('Depth, [m]')