I have a problem in the annexed excel file there are two tables, first table give the graph representing geological layers I need to get the second table with NaN values

2023 2월 9
2 답변
답변 채택됨
업데이트 시간: 2023 2월 13
조회 수: 97 (30일)

0 개 추천

Dear Please I need a help to get NaN of graph of excel file (annexed file) representing gelogical layers using If-condition (the change in depths of each layer Put NaN value to made a gaps as shown in the second table) .i.e. replace first change level-values in each curve of depth .

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Voss
Voss 2023년 2월 9일
Ran in:

0 개 추천

Ran in:
t = readtable('data.xlsx');
t1 = t(:,1:12); % first table from file
t2 = t(:,end-11:end); % second table from file
disp(t1);
xc gBt z1 z2 z3 z4 z5 z6 z7 z8 z9 z10 ______ ______ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ 0 60.791 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 1.6613 60.558 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 3.3225 60.325 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 4.9838 60.098 0.3 1.2 1.7 2 2.7 2.8 3.1 3.4 3.7 4.6 6.6451 59.875 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 8.3063 59.659 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 9.9676 59.444 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 11.629 59.234 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 13.29 59.031 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 14.951 58.832 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 16.613 58.639 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 18.274 58.446 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 19.935 58.263 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 21.596 58.083 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 23.258 57.907 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 24.919 57.731 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 26.58 57.56 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 28.242 57.395 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 29.903 57.231 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 31.564 57.068 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 33.225 56.906 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 34.887 56.753 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 36.548 56.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 38.209 56.45 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 39.87 56.301 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 41.532 56.156 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 43.193 56.017 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 44.854 55.874 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 46.516 55.737 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 48.177 55.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 49.838 55.471 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 51.499 55.339 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 53.161 55.209 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 54.822 55.082 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 56.483 54.956 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 58.144 54.833 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 59.806 54.707 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 61.467 54.587 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 63.128 54.467 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 64.789 54.35 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 66.451 54.233 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 68.112 54.122 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 69.773 54.019 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 71.435 53.919 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 73.096 53.829 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 74.757 53.739 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 76.418 53.656 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 78.08 53.575 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 79.741 53.494 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 81.402 53.416 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 83.063 53.341 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 84.725 53.27 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 86.386 53.198 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 88.047 53.128 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 89.708 53.062 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 91.37 52.996 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 93.031 52.931 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 94.692 52.863 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 96.354 52.795 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 98.015 52.727 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 99.676 52.657 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 101.34 52.582 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 103 52.514 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 104.66 52.447 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 106.32 52.389 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 107.98 52.332 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 109.64 52.281 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 111.3 52.237 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 112.97 52.2 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 114.63 52.184 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 116.29 52.172 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 117.95 52.173 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 119.61 52.177 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 121.27 52.188 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 122.93 52.201 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 124.6 52.223 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 126.26 52.257 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 127.92 52.297 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 129.58 52.346 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 131.24 52.397 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 132.9 52.453 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 134.56 52.513 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 136.22 52.574 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 137.89 52.64 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 139.55 52.708 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 141.21 52.779 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 142.87 52.852 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 144.53 52.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 146.19 52.999 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 147.85 53.073 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 149.51 53.146 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 151.18 53.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 152.84 53.287 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 154.5 53.356 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 156.16 53.42 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 157.82 53.483 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 159.48 53.543 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 161.14 53.605 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 162.8 53.659 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 164.47 53.709 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 166.13 53.748 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 167.79 53.783 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 169.45 53.815 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 171.11 53.841 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 172.77 53.87 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 174.43 53.895 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 176.09 53.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 177.76 53.95 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 179.42 53.978 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 181.08 54.008 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 182.74 54.041 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 184.4 54.075 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 186.06 54.108 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 187.72 54.143 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 189.38 54.176 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 191.05 54.209 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 192.71 54.241 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 194.37 54.272 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 196.03 54.3 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 197.69 54.325 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 199.35 54.348 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 201.01 54.366 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 202.67 54.384 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 204.34 54.397 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 206 54.407 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 207.66 54.413 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 209.32 54.419 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 210.98 54.421 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 212.64 54.417 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 214.3 54.412 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 215.96 54.404 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 217.63 54.396 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 219.29 54.378 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 220.95 54.36 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 222.61 54.334 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 224.27 54.302 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 225.93 54.263 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 227.59 54.217 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 229.25 54.168 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 230.92 54.111 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 232.58 54.046 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 234.24 53.967 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 235.9 53.884 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 237.56 53.784 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 239.22 53.672 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 240.88 53.552 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 242.55 53.423 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 244.21 53.294 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 245.87 53.153 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 247.53 53.01 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 249.19 52.858 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 250.85 52.704 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 252.51 52.545 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 254.17 52.381 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 255.84 52.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 257.5 52.049 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 259.16 51.883 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 260.82 51.711 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 262.48 51.541 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 264.14 51.37 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 265.8 51.201 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 267.46 51.026 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 269.13 50.849 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 270.79 50.671 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 272.45 50.486 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 274.11 50.296 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 275.77 50.09 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 277.43 49.88 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 279.09 49.657 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 280.75 49.426 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 282.42 49.183 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 284.08 48.932 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 285.74 48.68 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 287.4 48.418 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 289.06 48.155 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 290.72 47.888 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 292.38 47.623 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 294.04 47.355 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 295.71 47.082 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 297.37 46.806 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 299.03 46.528 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 300.69 46.25 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 302.35 45.963 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 304.01 45.678 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 305.67 45.386 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 307.33 45.099 0.3 1 1.4 1.6 2.1 2.2 2.4 2.6 2.8 3.5 309 44.808 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 310.66 44.518 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 312.32 44.23 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 313.98 43.937 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 315.64 43.646 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 317.3 43.354 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 318.96 43.068 0.2 0.8 1.2 1.4 1.9 2 2.2 2.4 2.6 3.3 320.62 42.792 0.2 0.8 1.2 1.4 1.9 2 2.2 2.4 2.6 3.3 322.29 42.523 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 323.95 42.264 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 325.61 42.018 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 327.27 41.785 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 328.93 41.568 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 330.59 41.355 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1
The second table seems (more-or-less) to be the result of placing NaNs in the cells of the first table containing the last of each set of contiguous equal values in a column, e.g.:
1
1
1 % <- replace last 1 with NaN
2
2
2
However, there are a few instances where the NaNs were placed in cells containing the first of a set of contiguous equal values in a column, e.g.:
1
1
1
2 % <- replace first 2 with NaN
2
2
Your question mentions "first change level-values", which suggests the second approach, but the actual table is more like the first approach.
So here's how you can do both approaches, and you can take your pick (the functions are defined below):
t1_bottoms = t1;
t1_bottoms(:,3:end) = varfun(@place_NaNs_at_bottoms_of_layers,t1,'InputVariables',3:size(t1,2));
disp(t1_bottoms);
xc gBt z1 z2 z3 z4 z5 z6 z7 z8 z9 z10 ______ ______ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ 0 60.791 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 1.6613 60.558 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 3.3225 60.325 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 4.9838 60.098 0.3 1.2 1.7 NaN NaN NaN NaN NaN NaN NaN 6.6451 59.875 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 8.3063 59.659 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 9.9676 59.444 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 11.629 59.234 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 13.29 59.031 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 14.951 58.832 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 16.613 58.639 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 18.274 58.446 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 19.935 58.263 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 21.596 58.083 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 23.258 57.907 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 24.919 57.731 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 26.58 57.56 0.3 1.1 1.6 1.8 NaN NaN NaN NaN NaN NaN 28.242 57.395 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 29.903 57.231 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 31.564 57.068 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 33.225 56.906 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 34.887 56.753 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 36.548 56.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 38.209 56.45 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 39.87 56.301 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 41.532 56.156 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 43.193 56.017 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 NaN 44.854 55.874 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 46.516 55.737 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 48.177 55.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 49.838 55.471 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 51.499 55.339 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 53.161 55.209 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 54.822 55.082 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 56.483 54.956 0.3 1.1 NaN NaN NaN NaN NaN NaN NaN NaN 58.144 54.833 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 59.806 54.707 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 61.467 54.587 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 63.128 54.467 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 64.789 54.35 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 66.451 54.233 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 68.112 54.122 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 69.773 54.019 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 71.435 53.919 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 73.096 53.829 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 74.757 53.739 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 76.418 53.656 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 78.08 53.575 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 79.741 53.494 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 81.402 53.416 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 83.063 53.341 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 84.725 53.27 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 86.386 53.198 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 88.047 53.128 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 89.708 53.062 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 91.37 52.996 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 93.031 52.931 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 94.692 52.863 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 96.354 52.795 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 98.015 52.727 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 99.676 52.657 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 101.34 52.582 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 103 52.514 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 104.66 52.447 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 106.32 52.389 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 107.98 52.332 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 109.64 52.281 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 111.3 52.237 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 112.97 52.2 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 114.63 52.184 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 116.29 52.172 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 117.95 52.173 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 119.61 52.177 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 121.27 52.188 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 122.93 52.201 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 124.6 52.223 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 126.26 52.257 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 127.92 52.297 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 129.58 52.346 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 131.24 52.397 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 132.9 52.453 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 134.56 52.513 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 136.22 52.574 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 137.89 52.64 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 139.55 52.708 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 141.21 52.779 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 142.87 52.852 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 144.53 52.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 146.19 52.999 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 147.85 53.073 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 149.51 53.146 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 151.18 53.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 152.84 53.287 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 154.5 53.356 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 156.16 53.42 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 157.82 53.483 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 159.48 53.543 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 161.14 53.605 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 162.8 53.659 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 164.47 53.709 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 166.13 53.748 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 167.79 53.783 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 169.45 53.815 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 171.11 53.841 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 172.77 53.87 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 174.43 53.895 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 176.09 53.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 177.76 53.95 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 179.42 53.978 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 181.08 54.008 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 182.74 54.041 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 184.4 54.075 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 186.06 54.108 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 187.72 54.143 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 189.38 54.176 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 191.05 54.209 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 192.71 54.241 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 194.37 54.272 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 196.03 54.3 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 197.69 54.325 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 199.35 54.348 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 201.01 54.366 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 202.67 54.384 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 204.34 54.397 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 206 54.407 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 207.66 54.413 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 209.32 54.419 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 210.98 54.421 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 212.64 54.417 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 214.3 54.412 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 215.96 54.404 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 217.63 54.396 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 219.29 54.378 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 220.95 54.36 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 222.61 54.334 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 224.27 54.302 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 225.93 54.263 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 227.59 54.217 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 229.25 54.168 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 230.92 54.111 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 232.58 54.046 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 234.24 53.967 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 235.9 53.884 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 237.56 53.784 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 239.22 53.672 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 240.88 53.552 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 242.55 53.423 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 244.21 53.294 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 245.87 53.153 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 247.53 53.01 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 249.19 52.858 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 250.85 52.704 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 252.51 52.545 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 254.17 52.381 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 255.84 52.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 257.5 52.049 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 259.16 51.883 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 260.82 51.711 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 262.48 51.541 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 264.14 51.37 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 265.8 51.201 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 267.46 51.026 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 269.13 50.849 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 270.79 50.671 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 272.45 50.486 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 274.11 50.296 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 275.77 50.09 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 277.43 49.88 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 279.09 49.657 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 280.75 49.426 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 NaN 282.42 49.183 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 284.08 48.932 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 285.74 48.68 0.3 1 1.4 1.6 NaN NaN NaN NaN NaN NaN 287.4 48.418 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 289.06 48.155 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 290.72 47.888 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 292.38 47.623 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 294.04 47.355 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 295.71 47.082 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 297.37 46.806 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 NaN NaN 299.03 46.528 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 300.69 46.25 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 302.35 45.963 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 304.01 45.678 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 305.67 45.386 0.3 1 1.4 1.6 2.1 2.2 2.4 NaN NaN NaN 307.33 45.099 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 309 44.808 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 310.66 44.518 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 312.32 44.23 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 313.98 43.937 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 315.64 43.646 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 317.3 43.354 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 318.96 43.068 0.2 0.8 1.2 1.4 1.9 2 2.2 2.4 2.6 3.3 320.62 42.792 0.2 0.8 NaN NaN NaN NaN NaN NaN NaN NaN 322.29 42.523 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 323.95 42.264 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 325.61 42.018 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 327.27 41.785 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 328.93 41.568 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 330.59 41.355 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1
t1_tops = t1;
t1_tops(:,3:end) = varfun(@place_NaNs_at_tops_of_layers,t1,'InputVariables',3:size(t1,2));
disp(t1_tops);
xc gBt z1 z2 z3 z4 z5 z6 z7 z8 z9 z10 ______ ______ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ 0 60.791 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 1.6613 60.558 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 3.3225 60.325 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 4.9838 60.098 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 6.6451 59.875 0.3 1.2 1.7 NaN NaN NaN NaN NaN NaN NaN 8.3063 59.659 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 9.9676 59.444 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 11.629 59.234 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 13.29 59.031 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 14.951 58.832 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 16.613 58.639 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 18.274 58.446 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 19.935 58.263 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 21.596 58.083 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 23.258 57.907 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 24.919 57.731 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 26.58 57.56 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 28.242 57.395 0.3 1.1 1.6 1.8 NaN NaN NaN NaN NaN NaN 29.903 57.231 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 31.564 57.068 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 33.225 56.906 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 34.887 56.753 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 36.548 56.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 38.209 56.45 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 39.87 56.301 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 41.532 56.156 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 43.193 56.017 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 44.854 55.874 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 NaN 46.516 55.737 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 48.177 55.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 49.838 55.471 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 51.499 55.339 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 53.161 55.209 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 54.822 55.082 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 56.483 54.956 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 58.144 54.833 0.3 1.1 NaN NaN NaN NaN NaN NaN NaN NaN 59.806 54.707 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 61.467 54.587 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 63.128 54.467 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 64.789 54.35 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 66.451 54.233 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 68.112 54.122 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 69.773 54.019 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 71.435 53.919 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 73.096 53.829 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 74.757 53.739 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 76.418 53.656 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 78.08 53.575 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 79.741 53.494 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 81.402 53.416 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 83.063 53.341 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 84.725 53.27 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 86.386 53.198 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 88.047 53.128 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 89.708 53.062 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 91.37 52.996 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 93.031 52.931 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 94.692 52.863 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 96.354 52.795 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 98.015 52.727 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 99.676 52.657 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 101.34 52.582 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 103 52.514 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 104.66 52.447 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 106.32 52.389 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 107.98 52.332 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 109.64 52.281 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 111.3 52.237 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 112.97 52.2 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 114.63 52.184 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 116.29 52.172 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 117.95 52.173 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 119.61 52.177 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 121.27 52.188 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 122.93 52.201 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 124.6 52.223 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 126.26 52.257 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 127.92 52.297 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 129.58 52.346 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 131.24 52.397 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 132.9 52.453 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 134.56 52.513 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 136.22 52.574 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 137.89 52.64 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 139.55 52.708 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 141.21 52.779 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 142.87 52.852 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 144.53 52.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 146.19 52.999 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 147.85 53.073 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 149.51 53.146 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 151.18 53.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 152.84 53.287 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 154.5 53.356 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 156.16 53.42 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 157.82 53.483 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 159.48 53.543 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 161.14 53.605 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 162.8 53.659 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 164.47 53.709 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 166.13 53.748 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 167.79 53.783 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 169.45 53.815 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 171.11 53.841 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 172.77 53.87 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 174.43 53.895 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 176.09 53.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 177.76 53.95 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 179.42 53.978 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 181.08 54.008 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 182.74 54.041 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 184.4 54.075 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 186.06 54.108 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 187.72 54.143 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 189.38 54.176 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 191.05 54.209 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 192.71 54.241 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 194.37 54.272 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 196.03 54.3 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 197.69 54.325 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 199.35 54.348 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 201.01 54.366 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 202.67 54.384 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 204.34 54.397 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 206 54.407 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 207.66 54.413 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 209.32 54.419 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 210.98 54.421 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 212.64 54.417 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 214.3 54.412 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 215.96 54.404 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 217.63 54.396 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 219.29 54.378 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 220.95 54.36 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 222.61 54.334 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 224.27 54.302 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 225.93 54.263 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 227.59 54.217 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 229.25 54.168 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 230.92 54.111 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 232.58 54.046 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 234.24 53.967 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 235.9 53.884 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 237.56 53.784 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 239.22 53.672 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 240.88 53.552 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 242.55 53.423 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 244.21 53.294 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 245.87 53.153 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 247.53 53.01 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 249.19 52.858 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 250.85 52.704 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 252.51 52.545 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 254.17 52.381 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 255.84 52.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 257.5 52.049 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 259.16 51.883 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 260.82 51.711 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 262.48 51.541 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 264.14 51.37 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 265.8 51.201 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 267.46 51.026 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 269.13 50.849 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 270.79 50.671 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 272.45 50.486 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 274.11 50.296 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 275.77 50.09 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 277.43 49.88 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 279.09 49.657 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 280.75 49.426 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 282.42 49.183 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 NaN 284.08 48.932 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 285.74 48.68 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 287.4 48.418 0.3 1 1.4 1.6 NaN NaN NaN NaN NaN NaN 289.06 48.155 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 290.72 47.888 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 292.38 47.623 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 294.04 47.355 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 295.71 47.082 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 297.37 46.806 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 299.03 46.528 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 NaN NaN 300.69 46.25 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 302.35 45.963 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 304.01 45.678 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 305.67 45.386 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 307.33 45.099 0.3 1 1.4 1.6 2.1 2.2 2.4 NaN NaN NaN 309 44.808 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 310.66 44.518 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 312.32 44.23 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 313.98 43.937 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 315.64 43.646 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 317.3 43.354 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 318.96 43.068 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 320.62 42.792 0.2 0.8 1.2 1.4 1.9 2 2.2 2.4 2.6 3.3 322.29 42.523 0.2 0.8 NaN NaN NaN NaN NaN NaN NaN NaN 323.95 42.264 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 325.61 42.018 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 327.27 41.785 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 328.93 41.568 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 330.59 41.355 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1
function x = place_NaNs_at_bottoms_of_layers(x)
x(logical(diff(x))) = NaN;
end
function x = place_NaNs_at_tops_of_layers(x)
x(1+find(diff(x))) = NaN;
end

댓글 수: 15
이전 댓글 13개 표시 이전 댓글 13개 숨기기

Voss
Voss 2023년 2월 9일
편집: Voss 2023년 2월 9일
Ran in:
Ran in:
And a less effficient solution, using an if condition, might look like:
t = readtable('data.xlsx');
t1 = t(:,1:12); % first table from file
t2 = t(:,end-11:end); % second table from file
disp(t1);
xc gBt z1 z2 z3 z4 z5 z6 z7 z8 z9 z10 ______ ______ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ 0 60.791 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 1.6613 60.558 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 3.3225 60.325 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 4.9838 60.098 0.3 1.2 1.7 2 2.7 2.8 3.1 3.4 3.7 4.6 6.6451 59.875 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 8.3063 59.659 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 9.9676 59.444 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 11.629 59.234 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 13.29 59.031 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 14.951 58.832 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 16.613 58.639 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 18.274 58.446 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 19.935 58.263 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 21.596 58.083 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 23.258 57.907 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 24.919 57.731 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 26.58 57.56 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 28.242 57.395 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 29.903 57.231 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 31.564 57.068 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 33.225 56.906 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 34.887 56.753 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 36.548 56.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 38.209 56.45 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 39.87 56.301 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 41.532 56.156 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 43.193 56.017 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 44.854 55.874 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 46.516 55.737 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 48.177 55.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 49.838 55.471 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 51.499 55.339 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 53.161 55.209 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 54.822 55.082 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 56.483 54.956 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 58.144 54.833 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 59.806 54.707 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 61.467 54.587 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 63.128 54.467 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 64.789 54.35 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 66.451 54.233 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 68.112 54.122 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 69.773 54.019 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 71.435 53.919 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 73.096 53.829 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 74.757 53.739 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 76.418 53.656 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 78.08 53.575 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 79.741 53.494 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 81.402 53.416 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 83.063 53.341 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 84.725 53.27 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 86.386 53.198 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 88.047 53.128 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 89.708 53.062 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 91.37 52.996 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 93.031 52.931 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 94.692 52.863 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 96.354 52.795 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 98.015 52.727 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 99.676 52.657 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 101.34 52.582 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 103 52.514 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 104.66 52.447 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 106.32 52.389 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 107.98 52.332 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 109.64 52.281 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 111.3 52.237 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 112.97 52.2 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 114.63 52.184 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 116.29 52.172 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 117.95 52.173 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 119.61 52.177 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 121.27 52.188 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 122.93 52.201 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 124.6 52.223 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 126.26 52.257 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 127.92 52.297 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 129.58 52.346 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 131.24 52.397 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 132.9 52.453 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 134.56 52.513 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 136.22 52.574 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 137.89 52.64 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 139.55 52.708 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 141.21 52.779 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 142.87 52.852 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 144.53 52.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 146.19 52.999 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 147.85 53.073 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 149.51 53.146 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 151.18 53.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 152.84 53.287 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 154.5 53.356 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 156.16 53.42 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 157.82 53.483 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 159.48 53.543 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 161.14 53.605 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 162.8 53.659 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 164.47 53.709 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 166.13 53.748 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 167.79 53.783 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 169.45 53.815 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 171.11 53.841 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 172.77 53.87 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 174.43 53.895 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 176.09 53.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 177.76 53.95 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 179.42 53.978 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 181.08 54.008 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 182.74 54.041 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 184.4 54.075 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 186.06 54.108 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 187.72 54.143 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 189.38 54.176 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 191.05 54.209 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 192.71 54.241 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 194.37 54.272 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 196.03 54.3 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 197.69 54.325 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 199.35 54.348 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 201.01 54.366 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 202.67 54.384 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 204.34 54.397 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 206 54.407 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 207.66 54.413 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 209.32 54.419 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 210.98 54.421 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 212.64 54.417 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 214.3 54.412 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 215.96 54.404 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 217.63 54.396 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 219.29 54.378 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 220.95 54.36 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 222.61 54.334 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 224.27 54.302 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 225.93 54.263 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 227.59 54.217 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 229.25 54.168 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 230.92 54.111 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 232.58 54.046 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 234.24 53.967 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 235.9 53.884 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 237.56 53.784 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 239.22 53.672 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 240.88 53.552 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 242.55 53.423 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 244.21 53.294 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 245.87 53.153 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 247.53 53.01 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 249.19 52.858 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 250.85 52.704 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 252.51 52.545 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 254.17 52.381 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 255.84 52.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 257.5 52.049 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 259.16 51.883 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 260.82 51.711 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 262.48 51.541 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 264.14 51.37 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 265.8 51.201 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 267.46 51.026 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 269.13 50.849 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 270.79 50.671 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 272.45 50.486 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 274.11 50.296 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 275.77 50.09 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 277.43 49.88 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 279.09 49.657 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 280.75 49.426 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 282.42 49.183 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 284.08 48.932 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 285.74 48.68 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 287.4 48.418 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 289.06 48.155 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 290.72 47.888 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 292.38 47.623 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 294.04 47.355 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 295.71 47.082 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 297.37 46.806 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 299.03 46.528 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 300.69 46.25 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 302.35 45.963 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 304.01 45.678 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 305.67 45.386 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 307.33 45.099 0.3 1 1.4 1.6 2.1 2.2 2.4 2.6 2.8 3.5 309 44.808 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 310.66 44.518 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 312.32 44.23 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 313.98 43.937 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 315.64 43.646 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 317.3 43.354 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 318.96 43.068 0.2 0.8 1.2 1.4 1.9 2 2.2 2.4 2.6 3.3 320.62 42.792 0.2 0.8 1.2 1.4 1.9 2 2.2 2.4 2.6 3.3 322.29 42.523 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 323.95 42.264 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 325.61 42.018 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 327.27 41.785 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 328.93 41.568 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 330.59 41.355 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1
t1_bottoms = t1;
t1_bottoms(:,3:end) = varfun(@place_NaNs_at_bottoms_of_layers,t1,'InputVariables',3:size(t1,2));
disp(t1_bottoms);
xc gBt z1 z2 z3 z4 z5 z6 z7 z8 z9 z10 ______ ______ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ 0 60.791 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 1.6613 60.558 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 3.3225 60.325 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 4.9838 60.098 0.3 1.2 1.7 NaN NaN NaN NaN NaN NaN NaN 6.6451 59.875 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 8.3063 59.659 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 9.9676 59.444 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 11.629 59.234 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 13.29 59.031 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 14.951 58.832 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 16.613 58.639 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 18.274 58.446 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 19.935 58.263 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 21.596 58.083 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 23.258 57.907 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 24.919 57.731 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 26.58 57.56 0.3 1.1 1.6 1.8 NaN NaN NaN NaN NaN NaN 28.242 57.395 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 29.903 57.231 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 31.564 57.068 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 33.225 56.906 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 34.887 56.753 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 36.548 56.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 38.209 56.45 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 39.87 56.301 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 41.532 56.156 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 43.193 56.017 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 NaN 44.854 55.874 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 46.516 55.737 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 48.177 55.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 49.838 55.471 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 51.499 55.339 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 53.161 55.209 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 54.822 55.082 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 56.483 54.956 0.3 1.1 NaN NaN NaN NaN NaN NaN NaN NaN 58.144 54.833 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 59.806 54.707 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 61.467 54.587 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 63.128 54.467 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 64.789 54.35 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 66.451 54.233 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 68.112 54.122 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 69.773 54.019 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 71.435 53.919 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 73.096 53.829 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 74.757 53.739 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 76.418 53.656 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 78.08 53.575 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 79.741 53.494 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 81.402 53.416 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 83.063 53.341 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 84.725 53.27 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 86.386 53.198 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 88.047 53.128 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 89.708 53.062 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 91.37 52.996 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 93.031 52.931 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 94.692 52.863 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 96.354 52.795 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 98.015 52.727 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 99.676 52.657 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 101.34 52.582 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 103 52.514 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 104.66 52.447 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 106.32 52.389 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 107.98 52.332 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 109.64 52.281 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 111.3 52.237 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 112.97 52.2 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 114.63 52.184 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 116.29 52.172 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 117.95 52.173 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 119.61 52.177 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 121.27 52.188 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 122.93 52.201 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 124.6 52.223 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 126.26 52.257 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 127.92 52.297 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 129.58 52.346 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 131.24 52.397 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 132.9 52.453 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 134.56 52.513 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 136.22 52.574 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 137.89 52.64 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 139.55 52.708 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 141.21 52.779 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 142.87 52.852 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 144.53 52.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 146.19 52.999 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 147.85 53.073 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 149.51 53.146 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 151.18 53.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 152.84 53.287 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 154.5 53.356 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 156.16 53.42 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 157.82 53.483 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 159.48 53.543 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 161.14 53.605 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 162.8 53.659 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 164.47 53.709 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 166.13 53.748 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 167.79 53.783 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 169.45 53.815 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 171.11 53.841 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 172.77 53.87 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 174.43 53.895 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 176.09 53.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 177.76 53.95 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 179.42 53.978 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 181.08 54.008 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 182.74 54.041 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 184.4 54.075 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 186.06 54.108 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 187.72 54.143 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 189.38 54.176 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 191.05 54.209 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 192.71 54.241 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 194.37 54.272 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 196.03 54.3 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 197.69 54.325 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 199.35 54.348 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 201.01 54.366 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 202.67 54.384 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 204.34 54.397 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 206 54.407 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 207.66 54.413 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 209.32 54.419 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 210.98 54.421 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 212.64 54.417 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 214.3 54.412 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 215.96 54.404 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 217.63 54.396 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 219.29 54.378 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 220.95 54.36 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 222.61 54.334 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 224.27 54.302 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 225.93 54.263 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 227.59 54.217 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 229.25 54.168 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 230.92 54.111 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 232.58 54.046 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 234.24 53.967 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 235.9 53.884 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 237.56 53.784 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 239.22 53.672 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 240.88 53.552 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 242.55 53.423 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 244.21 53.294 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 245.87 53.153 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 247.53 53.01 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 249.19 52.858 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 250.85 52.704 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 252.51 52.545 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 254.17 52.381 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 255.84 52.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 257.5 52.049 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 259.16 51.883 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 260.82 51.711 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 262.48 51.541 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 264.14 51.37 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 265.8 51.201 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 267.46 51.026 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 269.13 50.849 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 270.79 50.671 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 272.45 50.486 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 274.11 50.296 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 275.77 50.09 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 277.43 49.88 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 279.09 49.657 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 280.75 49.426 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 NaN 282.42 49.183 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 284.08 48.932 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 285.74 48.68 0.3 1 1.4 1.6 NaN NaN NaN NaN NaN NaN 287.4 48.418 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 289.06 48.155 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 290.72 47.888 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 292.38 47.623 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 294.04 47.355 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 295.71 47.082 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 297.37 46.806 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 NaN NaN 299.03 46.528 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 300.69 46.25 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 302.35 45.963 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 304.01 45.678 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 305.67 45.386 0.3 1 1.4 1.6 2.1 2.2 2.4 NaN NaN NaN 307.33 45.099 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 309 44.808 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 310.66 44.518 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 312.32 44.23 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 313.98 43.937 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 315.64 43.646 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 317.3 43.354 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 318.96 43.068 0.2 0.8 1.2 1.4 1.9 2 2.2 2.4 2.6 3.3 320.62 42.792 0.2 0.8 NaN NaN NaN NaN NaN NaN NaN NaN 322.29 42.523 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 323.95 42.264 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 325.61 42.018 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 327.27 41.785 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 328.93 41.568 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 330.59 41.355 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1
t1_tops = t1;
t1_tops(:,3:end) = varfun(@place_NaNs_at_tops_of_layers,t1,'InputVariables',3:size(t1,2));
disp(t1_tops);
xc gBt z1 z2 z3 z4 z5 z6 z7 z8 z9 z10 ______ ______ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ 0 60.791 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 1.6613 60.558 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 3.3225 60.325 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 4.9838 60.098 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 6.6451 59.875 0.3 1.2 1.7 NaN NaN NaN NaN NaN NaN NaN 8.3063 59.659 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 9.9676 59.444 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 11.629 59.234 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 13.29 59.031 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 14.951 58.832 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 16.613 58.639 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 18.274 58.446 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 19.935 58.263 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 21.596 58.083 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 23.258 57.907 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 24.919 57.731 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 26.58 57.56 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 28.242 57.395 0.3 1.1 1.6 1.8 NaN NaN NaN NaN NaN NaN 29.903 57.231 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 31.564 57.068 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 33.225 56.906 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 34.887 56.753 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 36.548 56.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 38.209 56.45 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 39.87 56.301 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 41.532 56.156 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 43.193 56.017 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 44.854 55.874 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 NaN 46.516 55.737 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 48.177 55.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 49.838 55.471 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 51.499 55.339 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 53.161 55.209 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 54.822 55.082 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 56.483 54.956 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 58.144 54.833 0.3 1.1 NaN NaN NaN NaN NaN NaN NaN NaN 59.806 54.707 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 61.467 54.587 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 63.128 54.467 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 64.789 54.35 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 66.451 54.233 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 68.112 54.122 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 69.773 54.019 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 71.435 53.919 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 73.096 53.829 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 74.757 53.739 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 76.418 53.656 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 78.08 53.575 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 79.741 53.494 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 81.402 53.416 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 83.063 53.341 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 84.725 53.27 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 86.386 53.198 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 88.047 53.128 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 89.708 53.062 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 91.37 52.996 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 93.031 52.931 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 94.692 52.863 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 96.354 52.795 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 98.015 52.727 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 99.676 52.657 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 101.34 52.582 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 103 52.514 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 104.66 52.447 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 106.32 52.389 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 107.98 52.332 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 109.64 52.281 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 111.3 52.237 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 112.97 52.2 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 114.63 52.184 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 116.29 52.172 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 117.95 52.173 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 119.61 52.177 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 121.27 52.188 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 122.93 52.201 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 124.6 52.223 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 126.26 52.257 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 127.92 52.297 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 129.58 52.346 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 131.24 52.397 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 132.9 52.453 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 134.56 52.513 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 136.22 52.574 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 137.89 52.64 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 139.55 52.708 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 141.21 52.779 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 142.87 52.852 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 144.53 52.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 146.19 52.999 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 147.85 53.073 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 149.51 53.146 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 151.18 53.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 152.84 53.287 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 154.5 53.356 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 156.16 53.42 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 157.82 53.483 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 159.48 53.543 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 161.14 53.605 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 162.8 53.659 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 164.47 53.709 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 166.13 53.748 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 167.79 53.783 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 169.45 53.815 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 171.11 53.841 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 172.77 53.87 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 174.43 53.895 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 176.09 53.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 177.76 53.95 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 179.42 53.978 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 181.08 54.008 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 182.74 54.041 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 184.4 54.075 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 186.06 54.108 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 187.72 54.143 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 189.38 54.176 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 191.05 54.209 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 192.71 54.241 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 194.37 54.272 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 196.03 54.3 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 197.69 54.325 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 199.35 54.348 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 201.01 54.366 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 202.67 54.384 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 204.34 54.397 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 206 54.407 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 207.66 54.413 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 209.32 54.419 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 210.98 54.421 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 212.64 54.417 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 214.3 54.412 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 215.96 54.404 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 217.63 54.396 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 219.29 54.378 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 220.95 54.36 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 222.61 54.334 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 224.27 54.302 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 225.93 54.263 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 227.59 54.217 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 229.25 54.168 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 230.92 54.111 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 232.58 54.046 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 234.24 53.967 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 235.9 53.884 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 237.56 53.784 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 239.22 53.672 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 240.88 53.552 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 242.55 53.423 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 244.21 53.294 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 245.87 53.153 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 247.53 53.01 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 249.19 52.858 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 250.85 52.704 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 252.51 52.545 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 254.17 52.381 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 255.84 52.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 257.5 52.049 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 259.16 51.883 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 260.82 51.711 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 262.48 51.541 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 264.14 51.37 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 265.8 51.201 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 267.46 51.026 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 269.13 50.849 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 270.79 50.671 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 272.45 50.486 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 274.11 50.296 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 275.77 50.09 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 277.43 49.88 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 279.09 49.657 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 280.75 49.426 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 282.42 49.183 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 NaN 284.08 48.932 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 285.74 48.68 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 287.4 48.418 0.3 1 1.4 1.6 NaN NaN NaN NaN NaN NaN 289.06 48.155 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 290.72 47.888 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 292.38 47.623 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 294.04 47.355 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 295.71 47.082 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 297.37 46.806 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 299.03 46.528 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 NaN NaN 300.69 46.25 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 302.35 45.963 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 304.01 45.678 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 305.67 45.386 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 307.33 45.099 0.3 1 1.4 1.6 2.1 2.2 2.4 NaN NaN NaN 309 44.808 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 310.66 44.518 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 312.32 44.23 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 313.98 43.937 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 315.64 43.646 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 317.3 43.354 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 318.96 43.068 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 320.62 42.792 0.2 0.8 1.2 1.4 1.9 2 2.2 2.4 2.6 3.3 322.29 42.523 0.2 0.8 NaN NaN NaN NaN NaN NaN NaN NaN 323.95 42.264 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 325.61 42.018 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 327.27 41.785 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 328.93 41.568 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 330.59 41.355 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1
function x = place_NaNs_at_bottoms_of_layers(x)
for ii = 1:numel(x)-1
if x(ii) ~= x(ii+1)
x(ii) = NaN;
end
end
end
function x = place_NaNs_at_tops_of_layers(x)
for ii = numel(x):-1:2
if x(ii) ~= x(ii-1)
x(ii) = NaN;
end
end
end
Voss
Voss 2023년 2월 9일
Ran in:
Ran in:
Or, replacing varfun with a for loop as well:
t = readtable('data.xlsx');
t1 = t(:,1:12); % first table from file
t2 = t(:,end-11:end); % second table from file
disp(t1);
xc gBt z1 z2 z3 z4 z5 z6 z7 z8 z9 z10 ______ ______ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ 0 60.791 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 1.6613 60.558 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 3.3225 60.325 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 4.9838 60.098 0.3 1.2 1.7 2 2.7 2.8 3.1 3.4 3.7 4.6 6.6451 59.875 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 8.3063 59.659 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 9.9676 59.444 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 11.629 59.234 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 13.29 59.031 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 14.951 58.832 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 16.613 58.639 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 18.274 58.446 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 19.935 58.263 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 21.596 58.083 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 23.258 57.907 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 24.919 57.731 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 26.58 57.56 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 28.242 57.395 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 29.903 57.231 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 31.564 57.068 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 33.225 56.906 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 34.887 56.753 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 36.548 56.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 38.209 56.45 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 39.87 56.301 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 41.532 56.156 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 43.193 56.017 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 44.854 55.874 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 46.516 55.737 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 48.177 55.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 49.838 55.471 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 51.499 55.339 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 53.161 55.209 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 54.822 55.082 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 56.483 54.956 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 58.144 54.833 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 59.806 54.707 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 61.467 54.587 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 63.128 54.467 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 64.789 54.35 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 66.451 54.233 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 68.112 54.122 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 69.773 54.019 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 71.435 53.919 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 73.096 53.829 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 74.757 53.739 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 76.418 53.656 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 78.08 53.575 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 79.741 53.494 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 81.402 53.416 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 83.063 53.341 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 84.725 53.27 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 86.386 53.198 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 88.047 53.128 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 89.708 53.062 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 91.37 52.996 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 93.031 52.931 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 94.692 52.863 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 96.354 52.795 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 98.015 52.727 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 99.676 52.657 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 101.34 52.582 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 103 52.514 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 104.66 52.447 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 106.32 52.389 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 107.98 52.332 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 109.64 52.281 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 111.3 52.237 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 112.97 52.2 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 114.63 52.184 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 116.29 52.172 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 117.95 52.173 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 119.61 52.177 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 121.27 52.188 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 122.93 52.201 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 124.6 52.223 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 126.26 52.257 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 127.92 52.297 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 129.58 52.346 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 131.24 52.397 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 132.9 52.453 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 134.56 52.513 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 136.22 52.574 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 137.89 52.64 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 139.55 52.708 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 141.21 52.779 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 142.87 52.852 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 144.53 52.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 146.19 52.999 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 147.85 53.073 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 149.51 53.146 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 151.18 53.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 152.84 53.287 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 154.5 53.356 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 156.16 53.42 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 157.82 53.483 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 159.48 53.543 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 161.14 53.605 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 162.8 53.659 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 164.47 53.709 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 166.13 53.748 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 167.79 53.783 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 169.45 53.815 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 171.11 53.841 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 172.77 53.87 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 174.43 53.895 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 176.09 53.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 177.76 53.95 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 179.42 53.978 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 181.08 54.008 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 182.74 54.041 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 184.4 54.075 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 186.06 54.108 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 187.72 54.143 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 189.38 54.176 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 191.05 54.209 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 192.71 54.241 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 194.37 54.272 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 196.03 54.3 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 197.69 54.325 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 199.35 54.348 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 201.01 54.366 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 202.67 54.384 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 204.34 54.397 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 206 54.407 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 207.66 54.413 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 209.32 54.419 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 210.98 54.421 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 212.64 54.417 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 214.3 54.412 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 215.96 54.404 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 217.63 54.396 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 219.29 54.378 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 220.95 54.36 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 222.61 54.334 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 224.27 54.302 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 225.93 54.263 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 227.59 54.217 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 229.25 54.168 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 230.92 54.111 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 232.58 54.046 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 234.24 53.967 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 235.9 53.884 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 237.56 53.784 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 239.22 53.672 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 240.88 53.552 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 242.55 53.423 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 244.21 53.294 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 245.87 53.153 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 247.53 53.01 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 249.19 52.858 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 250.85 52.704 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 252.51 52.545 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 254.17 52.381 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 255.84 52.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 257.5 52.049 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 259.16 51.883 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 260.82 51.711 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 262.48 51.541 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 264.14 51.37 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 265.8 51.201 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 267.46 51.026 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 269.13 50.849 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 270.79 50.671 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 272.45 50.486 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 274.11 50.296 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 275.77 50.09 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 277.43 49.88 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 279.09 49.657 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 280.75 49.426 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 282.42 49.183 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 284.08 48.932 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 285.74 48.68 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 287.4 48.418 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 289.06 48.155 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 290.72 47.888 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 292.38 47.623 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 294.04 47.355 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 295.71 47.082 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 297.37 46.806 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 299.03 46.528 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 300.69 46.25 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 302.35 45.963 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 304.01 45.678 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 305.67 45.386 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 307.33 45.099 0.3 1 1.4 1.6 2.1 2.2 2.4 2.6 2.8 3.5 309 44.808 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 310.66 44.518 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 312.32 44.23 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 313.98 43.937 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 315.64 43.646 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 317.3 43.354 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 318.96 43.068 0.2 0.8 1.2 1.4 1.9 2 2.2 2.4 2.6 3.3 320.62 42.792 0.2 0.8 1.2 1.4 1.9 2 2.2 2.4 2.6 3.3 322.29 42.523 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 323.95 42.264 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 325.61 42.018 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 327.27 41.785 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 328.93 41.568 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 330.59 41.355 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1
[nr,nc] = size(t1);
t1_bottoms = t1;
for jj = 3:nc
for ii = 1:nr-1
if t1_bottoms{ii,jj} ~= t1_bottoms{ii+1,jj}
t1_bottoms{ii,jj} = NaN;
end
end
end
disp(t1_bottoms);
xc gBt z1 z2 z3 z4 z5 z6 z7 z8 z9 z10 ______ ______ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ 0 60.791 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 1.6613 60.558 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 3.3225 60.325 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 4.9838 60.098 0.3 1.2 1.7 NaN NaN NaN NaN NaN NaN NaN 6.6451 59.875 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 8.3063 59.659 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 9.9676 59.444 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 11.629 59.234 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 13.29 59.031 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 14.951 58.832 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 16.613 58.639 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 18.274 58.446 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 19.935 58.263 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 21.596 58.083 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 23.258 57.907 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 24.919 57.731 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 26.58 57.56 0.3 1.1 1.6 1.8 NaN NaN NaN NaN NaN NaN 28.242 57.395 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 29.903 57.231 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 31.564 57.068 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 33.225 56.906 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 34.887 56.753 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 36.548 56.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 38.209 56.45 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 39.87 56.301 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 41.532 56.156 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 43.193 56.017 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 NaN 44.854 55.874 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 46.516 55.737 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 48.177 55.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 49.838 55.471 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 51.499 55.339 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 53.161 55.209 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 54.822 55.082 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 56.483 54.956 0.3 1.1 NaN NaN NaN NaN NaN NaN NaN NaN 58.144 54.833 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 59.806 54.707 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 61.467 54.587 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 63.128 54.467 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 64.789 54.35 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 66.451 54.233 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 68.112 54.122 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 69.773 54.019 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 71.435 53.919 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 73.096 53.829 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 74.757 53.739 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 76.418 53.656 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 78.08 53.575 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 79.741 53.494 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 81.402 53.416 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 83.063 53.341 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 84.725 53.27 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 86.386 53.198 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 88.047 53.128 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 89.708 53.062 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 91.37 52.996 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 93.031 52.931 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 94.692 52.863 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 96.354 52.795 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 98.015 52.727 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 99.676 52.657 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 101.34 52.582 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 103 52.514 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 104.66 52.447 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 106.32 52.389 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 107.98 52.332 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 109.64 52.281 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 111.3 52.237 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 112.97 52.2 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 114.63 52.184 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 116.29 52.172 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 117.95 52.173 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 119.61 52.177 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 121.27 52.188 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 122.93 52.201 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 124.6 52.223 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 126.26 52.257 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 127.92 52.297 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 129.58 52.346 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 131.24 52.397 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 132.9 52.453 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 134.56 52.513 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 136.22 52.574 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 137.89 52.64 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 139.55 52.708 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 141.21 52.779 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 142.87 52.852 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 144.53 52.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 146.19 52.999 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 147.85 53.073 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 149.51 53.146 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 151.18 53.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 152.84 53.287 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 154.5 53.356 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 156.16 53.42 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 157.82 53.483 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 159.48 53.543 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 161.14 53.605 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 162.8 53.659 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 164.47 53.709 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 166.13 53.748 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 167.79 53.783 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 169.45 53.815 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 171.11 53.841 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 172.77 53.87 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 174.43 53.895 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 176.09 53.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 177.76 53.95 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 179.42 53.978 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 181.08 54.008 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 182.74 54.041 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 184.4 54.075 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 186.06 54.108 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 187.72 54.143 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 189.38 54.176 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 191.05 54.209 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 192.71 54.241 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 194.37 54.272 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 196.03 54.3 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 197.69 54.325 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 199.35 54.348 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 201.01 54.366 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 202.67 54.384 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 204.34 54.397 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 206 54.407 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 207.66 54.413 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 209.32 54.419 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 210.98 54.421 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 212.64 54.417 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 214.3 54.412 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 215.96 54.404 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 217.63 54.396 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 219.29 54.378 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 220.95 54.36 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 222.61 54.334 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 224.27 54.302 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 225.93 54.263 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 227.59 54.217 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 229.25 54.168 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 230.92 54.111 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 232.58 54.046 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 234.24 53.967 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 235.9 53.884 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 237.56 53.784 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 239.22 53.672 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 240.88 53.552 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 242.55 53.423 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 244.21 53.294 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 245.87 53.153 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 247.53 53.01 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 249.19 52.858 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 250.85 52.704 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 252.51 52.545 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 254.17 52.381 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 255.84 52.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 257.5 52.049 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 259.16 51.883 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 260.82 51.711 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 262.48 51.541 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 264.14 51.37 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 265.8 51.201 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 267.46 51.026 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 269.13 50.849 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 270.79 50.671 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 272.45 50.486 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 274.11 50.296 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 275.77 50.09 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 277.43 49.88 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 279.09 49.657 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 280.75 49.426 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 NaN 282.42 49.183 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 284.08 48.932 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 285.74 48.68 0.3 1 1.4 1.6 NaN NaN NaN NaN NaN NaN 287.4 48.418 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 289.06 48.155 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 290.72 47.888 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 292.38 47.623 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 294.04 47.355 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 295.71 47.082 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 297.37 46.806 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 NaN NaN 299.03 46.528 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 300.69 46.25 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 302.35 45.963 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 304.01 45.678 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 305.67 45.386 0.3 1 1.4 1.6 2.1 2.2 2.4 NaN NaN NaN 307.33 45.099 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 309 44.808 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 310.66 44.518 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 312.32 44.23 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 313.98 43.937 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 315.64 43.646 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 317.3 43.354 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 318.96 43.068 0.2 0.8 1.2 1.4 1.9 2 2.2 2.4 2.6 3.3 320.62 42.792 0.2 0.8 NaN NaN NaN NaN NaN NaN NaN NaN 322.29 42.523 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 323.95 42.264 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 325.61 42.018 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 327.27 41.785 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 328.93 41.568 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 330.59 41.355 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1
t1_tops = t1;
for jj = 3:nc
for ii = nr:-1:2
if t1_tops{ii,jj} ~= t1_tops{ii-1,jj}
t1_tops{ii,jj} = NaN;
end
end
end
disp(t1_tops);
xc gBt z1 z2 z3 z4 z5 z6 z7 z8 z9 z10 ______ ______ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ 0 60.791 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 1.6613 60.558 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 3.3225 60.325 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 4.9838 60.098 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 6.6451 59.875 0.3 1.2 1.7 NaN NaN NaN NaN NaN NaN NaN 8.3063 59.659 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 9.9676 59.444 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 11.629 59.234 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 13.29 59.031 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 14.951 58.832 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 16.613 58.639 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 18.274 58.446 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 19.935 58.263 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 21.596 58.083 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 23.258 57.907 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 24.919 57.731 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 26.58 57.56 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 28.242 57.395 0.3 1.1 1.6 1.8 NaN NaN NaN NaN NaN NaN 29.903 57.231 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 31.564 57.068 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 33.225 56.906 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 34.887 56.753 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 36.548 56.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 38.209 56.45 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 39.87 56.301 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 41.532 56.156 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 43.193 56.017 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 44.854 55.874 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 NaN 46.516 55.737 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 48.177 55.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 49.838 55.471 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 51.499 55.339 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 53.161 55.209 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 54.822 55.082 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 56.483 54.956 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 58.144 54.833 0.3 1.1 NaN NaN NaN NaN NaN NaN NaN NaN 59.806 54.707 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 61.467 54.587 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 63.128 54.467 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 64.789 54.35 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 66.451 54.233 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 68.112 54.122 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 69.773 54.019 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 71.435 53.919 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 73.096 53.829 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 74.757 53.739 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 76.418 53.656 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 78.08 53.575 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 79.741 53.494 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 81.402 53.416 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 83.063 53.341 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 84.725 53.27 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 86.386 53.198 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 88.047 53.128 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 89.708 53.062 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 91.37 52.996 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 93.031 52.931 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 94.692 52.863 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 96.354 52.795 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 98.015 52.727 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 99.676 52.657 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 101.34 52.582 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 103 52.514 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 104.66 52.447 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 106.32 52.389 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 107.98 52.332 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 109.64 52.281 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 111.3 52.237 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 112.97 52.2 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 114.63 52.184 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 116.29 52.172 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 117.95 52.173 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 119.61 52.177 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 121.27 52.188 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 122.93 52.201 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 124.6 52.223 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 126.26 52.257 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 127.92 52.297 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 129.58 52.346 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 131.24 52.397 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 132.9 52.453 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 134.56 52.513 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 136.22 52.574 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 137.89 52.64 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 139.55 52.708 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 141.21 52.779 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 142.87 52.852 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 144.53 52.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 146.19 52.999 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 147.85 53.073 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 149.51 53.146 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 151.18 53.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 152.84 53.287 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 154.5 53.356 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 156.16 53.42 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 157.82 53.483 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 159.48 53.543 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 161.14 53.605 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 162.8 53.659 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 164.47 53.709 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 166.13 53.748 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 167.79 53.783 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 169.45 53.815 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 171.11 53.841 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 172.77 53.87 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 174.43 53.895 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 176.09 53.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 177.76 53.95 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 179.42 53.978 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 181.08 54.008 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 182.74 54.041 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 184.4 54.075 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 186.06 54.108 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 187.72 54.143 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 189.38 54.176 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 191.05 54.209 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 192.71 54.241 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 194.37 54.272 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 196.03 54.3 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 197.69 54.325 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 199.35 54.348 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 201.01 54.366 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 202.67 54.384 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 204.34 54.397 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 206 54.407 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 207.66 54.413 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 209.32 54.419 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 210.98 54.421 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 212.64 54.417 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 214.3 54.412 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 215.96 54.404 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 217.63 54.396 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 219.29 54.378 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 220.95 54.36 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 222.61 54.334 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 224.27 54.302 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 225.93 54.263 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 227.59 54.217 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 229.25 54.168 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 230.92 54.111 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 232.58 54.046 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 234.24 53.967 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 235.9 53.884 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 237.56 53.784 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 239.22 53.672 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 240.88 53.552 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 242.55 53.423 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 244.21 53.294 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 245.87 53.153 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 247.53 53.01 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 249.19 52.858 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 250.85 52.704 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 252.51 52.545 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 254.17 52.381 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 255.84 52.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 257.5 52.049 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 259.16 51.883 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 260.82 51.711 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 262.48 51.541 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 264.14 51.37 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 265.8 51.201 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 267.46 51.026 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 269.13 50.849 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 270.79 50.671 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 272.45 50.486 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 274.11 50.296 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 275.77 50.09 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 277.43 49.88 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 279.09 49.657 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 280.75 49.426 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 282.42 49.183 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 NaN 284.08 48.932 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 285.74 48.68 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 287.4 48.418 0.3 1 1.4 1.6 NaN NaN NaN NaN NaN NaN 289.06 48.155 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 290.72 47.888 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 292.38 47.623 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 294.04 47.355 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 295.71 47.082 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 297.37 46.806 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 299.03 46.528 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 NaN NaN 300.69 46.25 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 302.35 45.963 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 304.01 45.678 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 305.67 45.386 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 307.33 45.099 0.3 1 1.4 1.6 2.1 2.2 2.4 NaN NaN NaN 309 44.808 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 310.66 44.518 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 312.32 44.23 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 313.98 43.937 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 315.64 43.646 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 317.3 43.354 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 318.96 43.068 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 320.62 42.792 0.2 0.8 1.2 1.4 1.9 2 2.2 2.4 2.6 3.3 322.29 42.523 0.2 0.8 NaN NaN NaN NaN NaN NaN NaN NaN 323.95 42.264 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 325.61 42.018 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 327.27 41.785 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 328.93 41.568 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 330.59 41.355 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1
Moustafa Abedel Fattah
Moustafa Abedel Fattah 2023년 2월 10일
이동: Voss 2023년 2월 10일
Dear Sir;
Thanks for your the heinafter mentioned the accepted answer, and I ask you more vaor for made NaNs to be replaced with empty cells to be able to draw figure (drawing data with gaps) and if it posable to draw lines in the location of empty like the annexed figue (drawing data with lines)
Best Regards;
M. Dahab
Accepted code
t1 = readtable('data.xlsx');
[nr,nc] = size(t1);
t1_bottoms = t1;
for jj = 3:nc
for ii = 1:nr-1
if t1_bottoms{ii,jj} ~= t1_bottoms{ii+1,jj}
t1_bottoms{ii,jj} = NaN;
end
end
end
disp(t1_bottoms);
Voss
Voss 2023년 2월 10일
You're welcome!
I assume you are addressing me since you mention my code, even though you accepted the other answer.
I can work on figuring out how to generate the plot you want, and in the meantime you can accept my answer.
Thanks!
Voss
Voss 2023년 2월 11일
편집: Voss 2023년 2월 11일
Ran in:
Ran in:
How about this? Good enough?
t = readtable('data.xlsx');
t1 = t(:,1:12);
% put in the NaNs:
[nr,nc] = size(t1);
t1_bottoms = t1;
for jj = 3:nc
for ii = 1:nr-1
if t1_bottoms{ii,jj} ~= t1_bottoms{ii+1,jj}
t1_bottoms{ii,jj} = NaN;
end
end
end
disp(t1_bottoms);
xc gBt z1 z2 z3 z4 z5 z6 z7 z8 z9 z10 ______ ______ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ 0 60.791 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 1.6613 60.558 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 3.3225 60.325 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 4.9838 60.098 0.3 1.2 1.7 NaN NaN NaN NaN NaN NaN NaN 6.6451 59.875 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 8.3063 59.659 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 9.9676 59.444 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 11.629 59.234 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 13.29 59.031 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 14.951 58.832 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 16.613 58.639 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 18.274 58.446 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 19.935 58.263 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 21.596 58.083 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 23.258 57.907 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 24.919 57.731 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 26.58 57.56 0.3 1.1 1.6 1.8 NaN NaN NaN NaN NaN NaN 28.242 57.395 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 29.903 57.231 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 31.564 57.068 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 33.225 56.906 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 34.887 56.753 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 36.548 56.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 38.209 56.45 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 39.87 56.301 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 41.532 56.156 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 43.193 56.017 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 NaN 44.854 55.874 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 46.516 55.737 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 48.177 55.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 49.838 55.471 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 51.499 55.339 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 53.161 55.209 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 54.822 55.082 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 56.483 54.956 0.3 1.1 NaN NaN NaN NaN NaN NaN NaN NaN 58.144 54.833 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 59.806 54.707 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 61.467 54.587 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 63.128 54.467 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 64.789 54.35 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 66.451 54.233 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 68.112 54.122 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 69.773 54.019 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 71.435 53.919 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 73.096 53.829 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 74.757 53.739 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 76.418 53.656 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 78.08 53.575 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 79.741 53.494 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 81.402 53.416 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 83.063 53.341 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 84.725 53.27 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 86.386 53.198 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 88.047 53.128 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 89.708 53.062 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 91.37 52.996 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 93.031 52.931 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 94.692 52.863 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 96.354 52.795 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 98.015 52.727 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 99.676 52.657 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 101.34 52.582 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 103 52.514 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 104.66 52.447 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 106.32 52.389 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 107.98 52.332 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 109.64 52.281 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 111.3 52.237 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 112.97 52.2 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 114.63 52.184 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 116.29 52.172 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 117.95 52.173 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 119.61 52.177 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 121.27 52.188 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 122.93 52.201 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 124.6 52.223 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 126.26 52.257 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 127.92 52.297 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 129.58 52.346 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 131.24 52.397 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 132.9 52.453 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 134.56 52.513 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 136.22 52.574 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 137.89 52.64 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 139.55 52.708 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 141.21 52.779 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 142.87 52.852 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 144.53 52.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 146.19 52.999 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 147.85 53.073 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 149.51 53.146 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 151.18 53.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 152.84 53.287 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 154.5 53.356 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 156.16 53.42 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 157.82 53.483 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 159.48 53.543 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 161.14 53.605 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 162.8 53.659 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 164.47 53.709 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 166.13 53.748 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 167.79 53.783 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 169.45 53.815 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 171.11 53.841 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 172.77 53.87 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 174.43 53.895 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 176.09 53.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 177.76 53.95 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 179.42 53.978 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 181.08 54.008 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 182.74 54.041 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 184.4 54.075 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 186.06 54.108 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 187.72 54.143 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 189.38 54.176 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 191.05 54.209 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 192.71 54.241 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 194.37 54.272 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 196.03 54.3 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 197.69 54.325 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 199.35 54.348 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 201.01 54.366 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 202.67 54.384 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 204.34 54.397 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 206 54.407 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 207.66 54.413 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 209.32 54.419 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 210.98 54.421 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 212.64 54.417 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 214.3 54.412 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 215.96 54.404 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 217.63 54.396 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 219.29 54.378 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 220.95 54.36 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 222.61 54.334 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 224.27 54.302 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 225.93 54.263 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 227.59 54.217 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 229.25 54.168 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 230.92 54.111 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 232.58 54.046 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 234.24 53.967 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 235.9 53.884 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 237.56 53.784 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 239.22 53.672 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 240.88 53.552 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 242.55 53.423 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 244.21 53.294 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 245.87 53.153 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 247.53 53.01 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 249.19 52.858 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 250.85 52.704 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 252.51 52.545 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 254.17 52.381 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 255.84 52.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 257.5 52.049 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 259.16 51.883 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 260.82 51.711 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 262.48 51.541 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 264.14 51.37 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 265.8 51.201 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 267.46 51.026 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 269.13 50.849 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 270.79 50.671 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 272.45 50.486 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 274.11 50.296 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 275.77 50.09 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 277.43 49.88 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 279.09 49.657 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 280.75 49.426 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 NaN 282.42 49.183 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 284.08 48.932 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 285.74 48.68 0.3 1 1.4 1.6 NaN NaN NaN NaN NaN NaN 287.4 48.418 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 289.06 48.155 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 290.72 47.888 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 292.38 47.623 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 294.04 47.355 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 295.71 47.082 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 297.37 46.806 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 NaN NaN 299.03 46.528 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 300.69 46.25 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 302.35 45.963 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 304.01 45.678 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 305.67 45.386 0.3 1 1.4 1.6 2.1 2.2 2.4 NaN NaN NaN 307.33 45.099 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 309 44.808 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 310.66 44.518 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 312.32 44.23 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 313.98 43.937 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 315.64 43.646 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 317.3 43.354 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 318.96 43.068 0.2 0.8 1.2 1.4 1.9 2 2.2 2.4 2.6 3.3 320.62 42.792 0.2 0.8 NaN NaN NaN NaN NaN NaN NaN NaN 322.29 42.523 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 323.95 42.264 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 325.61 42.018 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 327.27 41.785 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 328.93 41.568 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 330.59 41.355 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1
nans = isnan(t1_bottoms{:,3:end});
nan_rows = find(any(nans,2));
xc = t1_bottoms.xc(nan_rows);
yc = zeros(numel(nan_rows),1);
for ii = 1:numel(nan_rows)
idx = find(~nans(nan_rows(ii),:),1,'last');
if isempty(idx)
yc(ii) = 0;
else
yc(ii) = t1_bottoms{nan_rows(ii),idx+2};
end
end
to_combine = diff(nan_rows) < 3;
xc_temp = (xc([to_combine; false])+xc([false; to_combine]))/2;
yc_temp = (yc([to_combine; false])+yc([false; to_combine]))/2;
to_remove = any([[to_combine; false] [false; to_combine]],2);
xc(to_remove) = [];
yc(to_remove) = [];
[xc,idx] = sort([xc; xc_temp]);
yc = [yc; yc_temp];
yc = yc(idx);
figure
hold on
plot(t1_bottoms.xc,t1_bottoms{:,3:end},'LineWidth',2)
yl = get(gca(),'YLim');
for ii = 1:numel(xc)
plot([xc(ii) xc(ii)],[yc(ii) yl(2)],'r')
end
set(gca(),'YDir','reverse')
box on
grid on
Moustafa Abedel Fattah
Moustafa Abedel Fattah 2023년 2월 11일
이동: Voss 2023년 2월 11일
Thank you sir; for your solution but excuse me there is some thing wrong belong my Matlab R2014b version...when run the code it give me the following error:
nans = isnan(t1_bottoms{:,"z"+(1:10)}) |
Error: The input character is not valid in MATLAB statements or expressions.
and when I rewrite the code in the following form it gives:
nans = isnan(t1_bottoms{:,'z'+(1:10)})
Variable index exceeds table dimensions.
can you please to modifiying the code to be suitable for my version R2014b
Best Regards;
Thanks in advance
M. Dahab
Voss
Voss 2023년 2월 11일
When posting a question, there is a place to specify which version of MATLAB you are using. This helps people who answer the question know what's going to work and what's not going to work in your version.
I've edited the code so that it should now work in R2014b.
I would appreciate if you would un-accept the answer you mistakenly accepted and accept my answer instead. Thanks!
Moustafa Abedel Fattah
Moustafa Abedel Fattah 2023년 2월 11일
Accepted Answer
Dear Sir;
Please accept my apolgize, mistake that I did not informing you about the Matalb-version. Its imortant to thank you very much and anyhow your efforts in solve the problem is succeful in either of your Matlab version (It well be helpful to another people) or my version R2014b
Best Regards;
M. Dahab
Voss
Voss 2023년 2월 11일
The code in my comment above has been edited and should now run in MATLAB R2014b. Please let me know if you have any trouble with it.
Again, please Accept my Answer and unaccept the other answer.
Moustafa Abedel Fattah
Moustafa Abedel Fattah 2023년 2월 12일
Dear Sir;
May I ask you favor please to explain the algorithm and your Matlab code, from step after (disp(t1 bottoms);. And if possible explaining the gaps not extending for line in the circled locations (see annexed figuer)?
Thanks in advance;
Best Regards;
M.Dahab
Voss
Voss 2023년 2월 12일
% find the rows that have any NaN in columns 3-end:
nans = isnan(t1_bottoms{:,3:end});
nan_rows = find(any(nans,2));
% xc is the x-coordinate of those rows:
xc = t1_bottoms.xc(nan_rows);
% yc is the y-coordinate of those rows with NaNs:
yc = zeros(numel(nan_rows),1);
for ii = 1:numel(nan_rows)
% yc will be the last non-NaN value in the row, or 0 if all are NaN:
idx = find(~nans(nan_rows(ii),:),1,'last');
if isempty(idx)
yc(ii) = 0;
else
yc(ii) = t1_bottoms{nan_rows(ii),idx+2};
end
end
% sometimes there are two consecutive rows with NaNs, and according to
% the plot with the hand-drawn red lines, these should have only one red
% line, not one red line for each row, so I find where there are multiple
% adjacent rows with NaNs:
to_combine = diff(nan_rows) < 3;
% and combine the x and y coordinates of those by taking the average
% (luckily there are never more than two consecutive rows with NaNs, or
% this would have to be modified):
xc_temp = (xc([to_combine; false])+xc([false; to_combine]))/2;
yc_temp = (yc([to_combine; false])+yc([false; to_combine]))/2;
% remove the xc and yc corresponding to rows just combined:
to_remove = any([[to_combine; false] [false; to_combine]],2);
xc(to_remove) = [];
yc(to_remove) = [];
% append the new average values found before from combining the xc and
% yc, and sort xc and yc according to xc:
[xc,idx] = sort([xc; xc_temp]);
yc = [yc; yc_temp];
yc = yc(idx);
Moustafa Abedel Fattah
Moustafa Abedel Fattah 2023년 2월 13일
Dear Sir;
It so good but what about the second part of asking; please if possible explaining the gaps not extending for line in the circled locations (see annexed figuer)?
Voss
Voss 2023년 2월 13일
편집: Voss 2023년 2월 13일
Ran in:
Ran in:
The gaps exist because I averaged the y-coordinates in cases where there is more than one adjacent row with NaNs. Gaps can be avoided by using the minimum y-coordinate among adjacent rows with NaNs, instead of the average, as shown below.
The only change I made was changing this:
yc_temp = (yc([to_combine; false])+yc([false; to_combine]))/2;
to this:
yc_temp = min(yc([to_combine; false]),yc([false; to_combine]));
Complete code:
t = readtable('data.xlsx');
t1 = t(:,1:12);
% put in the NaNs:
[nr,nc] = size(t1);
t1_bottoms = t1;
for jj = 3:nc
for ii = 1:nr-1
if t1_bottoms{ii,jj} ~= t1_bottoms{ii+1,jj}
t1_bottoms{ii,jj} = NaN;
end
end
end
disp(t1_bottoms);
xc gBt z1 z2 z3 z4 z5 z6 z7 z8 z9 z10 ______ ______ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ 0 60.791 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 1.6613 60.558 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 3.3225 60.325 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 4.9838 60.098 0.3 1.2 1.7 NaN NaN NaN NaN NaN NaN NaN 6.6451 59.875 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 8.3063 59.659 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 9.9676 59.444 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 11.629 59.234 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 13.29 59.031 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 14.951 58.832 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 16.613 58.639 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 18.274 58.446 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 19.935 58.263 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 21.596 58.083 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 23.258 57.907 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 24.919 57.731 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 26.58 57.56 0.3 1.1 1.6 1.8 NaN NaN NaN NaN NaN NaN 28.242 57.395 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 29.903 57.231 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 31.564 57.068 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 33.225 56.906 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 34.887 56.753 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 36.548 56.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 38.209 56.45 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 39.87 56.301 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 41.532 56.156 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.3 43.193 56.017 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 NaN 44.854 55.874 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 46.516 55.737 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 48.177 55.602 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 49.838 55.471 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 51.499 55.339 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 53.161 55.209 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 54.822 55.082 0.3 1.1 1.6 1.8 2.4 2.5 2.8 3.1 3.4 4.2 56.483 54.956 0.3 1.1 NaN NaN NaN NaN NaN NaN NaN NaN 58.144 54.833 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 59.806 54.707 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 61.467 54.587 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 63.128 54.467 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 64.789 54.35 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 66.451 54.233 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 68.112 54.122 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 69.773 54.019 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 71.435 53.919 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 73.096 53.829 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 74.757 53.739 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 76.418 53.656 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 78.08 53.575 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 79.741 53.494 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 81.402 53.416 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 83.063 53.341 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 84.725 53.27 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 86.386 53.198 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 88.047 53.128 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 89.708 53.062 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 91.37 52.996 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 93.031 52.931 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 94.692 52.863 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 96.354 52.795 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 98.015 52.727 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 99.676 52.657 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 101.34 52.582 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 103 52.514 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 104.66 52.447 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 106.32 52.389 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 107.98 52.332 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 109.64 52.281 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 111.3 52.237 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 112.97 52.2 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 114.63 52.184 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 116.29 52.172 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 117.95 52.173 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 119.61 52.177 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 121.27 52.188 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 122.93 52.201 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 124.6 52.223 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 126.26 52.257 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 127.92 52.297 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 129.58 52.346 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 131.24 52.397 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 132.9 52.453 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 134.56 52.513 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 136.22 52.574 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 137.89 52.64 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 139.55 52.708 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 141.21 52.779 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 142.87 52.852 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 144.53 52.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 146.19 52.999 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 147.85 53.073 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 149.51 53.146 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 151.18 53.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 152.84 53.287 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 154.5 53.356 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 156.16 53.42 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 157.82 53.483 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 159.48 53.543 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 161.14 53.605 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 162.8 53.659 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 164.47 53.709 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 166.13 53.748 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 167.79 53.783 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 169.45 53.815 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 171.11 53.841 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 172.77 53.87 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 174.43 53.895 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 176.09 53.924 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 177.76 53.95 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 179.42 53.978 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 181.08 54.008 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 182.74 54.041 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 184.4 54.075 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 186.06 54.108 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 187.72 54.143 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 189.38 54.176 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 191.05 54.209 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 192.71 54.241 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 194.37 54.272 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 196.03 54.3 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 197.69 54.325 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 199.35 54.348 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 201.01 54.366 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 202.67 54.384 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 204.34 54.397 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 206 54.407 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 207.66 54.413 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 209.32 54.419 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 210.98 54.421 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 212.64 54.417 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 214.3 54.412 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 215.96 54.404 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 217.63 54.396 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 219.29 54.378 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 220.95 54.36 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 222.61 54.334 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 224.27 54.302 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 225.93 54.263 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 227.59 54.217 0.3 1.1 1.5 1.7 2.3 2.4 2.7 3 3.3 4.1 229.25 54.168 0.3 1.1 1.5 1.7 2.3 2.4 NaN NaN NaN NaN 230.92 54.111 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 232.58 54.046 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 234.24 53.967 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 235.9 53.884 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 237.56 53.784 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 239.22 53.672 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 240.88 53.552 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 242.55 53.423 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 244.21 53.294 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 245.87 53.153 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 247.53 53.01 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 249.19 52.858 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 250.85 52.704 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 252.51 52.545 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 254.17 52.381 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 255.84 52.217 0.3 1.1 1.5 1.7 2.3 2.4 2.6 2.9 3.2 4 257.5 52.049 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 259.16 51.883 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 260.82 51.711 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 262.48 51.541 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 264.14 51.37 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 265.8 51.201 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 267.46 51.026 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 269.13 50.849 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 270.79 50.671 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 272.45 50.486 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 274.11 50.296 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 275.77 50.09 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 277.43 49.88 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 279.09 49.657 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.9 280.75 49.426 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 NaN 282.42 49.183 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 284.08 48.932 0.3 1 1.4 1.6 2.2 2.3 2.5 2.8 3.1 3.8 285.74 48.68 0.3 1 1.4 1.6 NaN NaN NaN NaN NaN NaN 287.4 48.418 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 289.06 48.155 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 290.72 47.888 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 292.38 47.623 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 294.04 47.355 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 295.71 47.082 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 3 3.7 297.37 46.806 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 NaN NaN 299.03 46.528 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 300.69 46.25 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 302.35 45.963 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 304.01 45.678 0.3 1 1.4 1.6 2.1 2.2 2.4 2.7 2.9 3.6 305.67 45.386 0.3 1 1.4 1.6 2.1 2.2 2.4 NaN NaN NaN 307.33 45.099 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 309 44.808 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 310.66 44.518 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 312.32 44.23 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 313.98 43.937 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 315.64 43.646 0.3 0.9 1.3 1.5 2 2.1 2.3 2.5 2.7 3.4 317.3 43.354 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 318.96 43.068 0.2 0.8 1.2 1.4 1.9 2 2.2 2.4 2.6 3.3 320.62 42.792 0.2 0.8 NaN NaN NaN NaN NaN NaN NaN NaN 322.29 42.523 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 323.95 42.264 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 325.61 42.018 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 327.27 41.785 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 328.93 41.568 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 330.59 41.355 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1 332.25 41.159 0.2 0.8 1.1 1.3 1.8 1.9 2.1 2.3 2.5 3.1
nans = isnan(t1_bottoms{:,3:end});
nan_rows = find(any(nans,2));
xc = t1_bottoms.xc(nan_rows);
yc = zeros(numel(nan_rows),1);
for ii = 1:numel(nan_rows)
idx = find(~nans(nan_rows(ii),:),1,'last');
if isempty(idx)
yc(ii) = 0;
else
yc(ii) = t1_bottoms{nan_rows(ii),idx+2};
end
end
to_combine = diff(nan_rows) < 3;
xc_temp = (xc([to_combine; false])+xc([false; to_combine]))/2;
yc_temp = min(yc([to_combine; false]),yc([false; to_combine]));
to_remove = any([[to_combine; false] [false; to_combine]],2);
xc(to_remove) = [];
yc(to_remove) = [];
[xc,idx] = sort([xc; xc_temp]);
yc = [yc; yc_temp];
yc = yc(idx);
figure
hold on
plot(t1_bottoms.xc,t1_bottoms{:,3:end},'LineWidth',2)
yl = get(gca(),'YLim');
for ii = 1:numel(xc)
plot([xc(ii) xc(ii)],[yc(ii) yl(2)],'r')
end
set(gca(),'YDir','reverse')
box on
grid on
Moustafa Abedel Fattah
Moustafa Abedel Fattah 2023년 2월 13일
편집: Moustafa Abedel Fattah 2023년 2월 13일
Dear Sir;
Excellent efforts god blesse you. Now, please tell me how can I write your formal name as a reference when I finsh and publish my articles (It is very important for refering to your help)
Best Regards;
M.Dahab
Voss
Voss 2023년 2월 13일
You're welcome! You can refer to me as "B. Voss". Thanks!

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Cris LaPierre
Cris LaPierre 2023년 2월 9일
Ran in:

0 개 추천

Ran in:
I would use readtable with the 'Range' name-value pair to extract each table separately. readtable will automatically fill any missing data.
file = 'https://www.mathworks.com/matlabcentral/answers/uploaded_files/1290875/data.xlsx';
% A-L
tbl1 = readtable(file,'Range',"A1:L203")
tbl1 = 202×12 table
xc gBt z1 z2 z3 z4 z5 z6 z7 z8 z9 z10 ______ ______ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ 0 60.791 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 1.6613 60.558 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 3.3225 60.325 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 4.9838 60.098 0.3 1.2 1.7 2 2.7 2.8 3.1 3.4 3.7 4.6 6.6451 59.875 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 8.3063 59.659 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 9.9676 59.444 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 11.629 59.234 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 13.29 59.031 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 14.951 58.832 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 16.613 58.639 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 18.274 58.446 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 19.935 58.263 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 21.596 58.083 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 23.258 57.907 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 24.919 57.731 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4
% AG-AR
tbl2 = readtable(file,'Range',"AG1:AR203")
tbl2 = 202×12 table
xc gBt z1 z2 z3 z4 z5 z6 z7 z8 z9 z10 ______ ______ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ 0 60.791 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 1.6613 60.558 0.4 1.3 1.8 2.1 2.8 2.9 3.2 3.5 3.8 4.7 3.3225 60.325 NaN 1.3 NaN NaN NaN NaN NaN NaN NaN NaN 4.9838 60.098 0.3 NaN 1.7 NaN NaN NaN NaN NaN NaN NaN 6.6451 59.875 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 8.3063 59.659 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 9.9676 59.444 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 11.629 59.234 0.3 1.2 1.7 1.9 2.6 2.7 3 3.3 3.6 4.5 13.29 59.031 0.3 NaN NaN NaN NaN NaN NaN NaN NaN NaN 14.951 58.832 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 16.613 58.639 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 18.274 58.446 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 19.935 58.263 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 21.596 58.083 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 23.258 57.907 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4 24.919 57.731 0.3 1.1 1.6 1.8 2.5 2.6 2.9 3.2 3.5 4.4

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도움말 센터 및 File Exchange에서 2-D and 3-D Plots에 대해 자세히 알아보기

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Moustafa Abedel Fattah
Moustafa Abedel Fattah
2023년 2월 9일

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