calculate the maximum of every 24 data in matrices

I have a series of data in .mat format, where each row determines a sensor and the columns are the data it collects every hour. The problem is that they are data that are taken every hour and I need the maximum of each day, that is, the maximum of each 24 values. taking into account that we have data from several years

Answer 1

[Star Strider]

If the times are in (or can be converted to) datetime arrays, one option would be to transpose the matrix so that the sensors are the columns (variables) and the times are the rows. Then use table2timetable and then retime. This is relatively straightforward to do, and has relevant examples in the retime documentation.

If those conditions apply and if you want specific help with it, upload/attach your data using the paperclip icon so we can work with it.

[Victoria Pilar Quesada García]

this is the lick for the date

https://uibes-my.sharepoint.com/:u:/g/personal/vqg648_id_uib_cat/EYjfB3U9ykFLpzuHJkdwUnABKzM9sIC26I5Bhx4lxYOV3w?e=QYeKDy

[Star Strider]

That file is 647 MB! Please try with a smaller file, preferably a shorter version of this one. That download keeps failing on my end.

[Victoria Pilar Quesada García]

Sorry, I had not realized how heavy the file was, these are the first 999 data of those 485 series

[Victoria Pilar Quesada García]

I think I've got a way but it can only be applied to one row.Is there a way to use it for more than one row at the same time? or another way I have to do it?

load("date 1*552262.mat")

data=sshobscorr

%total number of days of data

numDays = length(data)/24;

% temperature data so i have a column for each day, with a row for each hour in the day

Tdata = reshape(data,24,numDays)

% calculate min and max for each day

dailyMin = min(Tdata);

dailyMax = max(Tdata);

[Star Strider]

I am not certain whiat data set you want to work with, so I duplicated this for each set —

LD1 = load(websave('date%201*552262','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1331305/date%201*552262.mat'));
data1 = LD1.sshobscorr

data1 = 1×552264

NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN

LD2 = load(websave('date','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1331300/date.mat'))

LD2 = struct with fields:
    sshobscorrCopy: [485×999 double]

data2 = LD2.sshobscorrCopy

data2 = 485×999

NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN

format shortG
NrNaN1 = nnz(isnan(data1))

NrNaN1 = 
      435232

data1 = data1(~isnan(data1))

data1 = 1×117032

0.1358 0.18396 0.12512 0.041191 0.044977 -0.011474 -0.035863 -0.07526 -0.10174 -0.14825 -0.19642 -0.22789 -0.25987 -0.27876 -0.24913 -0.26042 -0.21822 -0.19 -0.12006 -0.05785 -0.028557 0.042862 0.075869 0.092993 0.11776 0.11377 0.14235 0.15074 0.1391 0.15539

numDays1 = numel(data1)/24

numDays1 = 
       4876.3

numDays1 = fix(numDays1)

numDays1 = 
        4876

data1 = data1(1:fix(numDays1)*24)

data1 = 1×117024

0.1358 0.18396 0.12512 0.041191 0.044977 -0.011474 -0.035863 -0.07526 -0.10174 -0.14825 -0.19642 -0.22789 -0.25987 -0.27876 -0.24913 -0.26042 -0.21822 -0.19 -0.12006 -0.05785 -0.028557 0.042862 0.075869 0.092993 0.11776 0.11377 0.14235 0.15074 0.1391 0.15539

Tdata1 = reshape(data1,[],24).'

Tdata1 = 24×4876

0.1358 0.18396 0.12512 0.041191 0.044977 -0.011474 -0.035863 -0.07526 -0.10174 -0.14825 -0.19642 -0.22789 -0.25987 -0.27876 -0.24913 -0.26042 -0.21822 -0.19 -0.12006 -0.05785 -0.028557 0.042862 0.075869 0.092993 0.11776 0.11377 0.14235 0.15074 0.1391 0.15539 0.14452 0.13723 0.12455 0.10996 0.10092 0.079247 0.07611 0.087974 0.079477 0.068379 0.07165 0.074181 0.051074 0.042777 0.041157 0.038698 0.039821 0.028684 0.03321 0.046506 0.056262 0.06525 0.067504 0.084538 0.10842 0.12537 0.1243 0.137 0.14909 0.14529 0.10362 0.12894 0.15837 0.17844 0.17396 0.19869 0.20682 0.2057 0.19785 0.22796 0.2714 0.26557 0.25416 0.27252 0.2891 0.31791 0.36479 0.40764 0.45489 0.51208 0.54332 0.56781 0.58432 0.56405 0.55173 0.48655 0.44869 0.42835 0.37039 0.38935 -0.11646 -0.10988 -0.10829 -0.11861 -0.11942 -0.10706 -0.10936 -0.098284 -0.083261 -0.060146 -0.082538 -0.09234 -0.059585 -0.061251 -0.042755 -0.040799 -0.043754 -0.00236 -0.0087156 -0.015605 0.0066368 0.0046152 -0.012923 -0.0034358 0.025132 0.03125 0.023931 0.019935 0.023892 0.048275 -0.17868 -0.18342 -0.16958 -0.15358 -0.15685 -0.16677 -0.15562 -0.16205 -0.17291 -0.16663 -0.1906 -0.18738 -0.19348 -0.2006 -0.18739 -0.1938 -0.18145 -0.16909 -0.17255 -0.15634 -0.15946 -0.17631 -0.17987 -0.16758 -0.1776 -0.17209 -0.17048 -0.16351 -0.16263 -0.17524 -0.0093065 0.0057132 0.0098779 0.0044814 -0.014395 -0.01924 -0.0099304 0.012665 0.035563 0.041382 0.051966 0.06255 0.04795 0.034493 0.014188 0.011365 0.013614 0.0052942 0.011499 0.01362 0.021708 0.033427 0.037044 0.038607 0.04125 0.042373 0.028179 0.020786 0.013388 -0.0070962 -0.078911 -0.083773 -0.095854 -0.1102 -0.11643 -0.12814 -0.13237 -0.14513 -0.14621 -0.16094 -0.15157 -0.13185 -0.12836 -0.13093 -0.13938 -0.1333 -0.13858 -0.16805 -0.1567 -0.1496 -0.16208 -0.15261 -0.16681 -0.15205 -0.13031 -0.13669 -0.12592 -0.1381 -0.13605 -0.15087 0.039727 0.052571 0.046197 0.032427 0.03061 0.011015 0.019031 0.01705 -0.00062475 -0.0035273 -0.023838 -0.018832 -0.014416 -0.019046 -0.021594 -0.0065405 0.0058677 0.0017217 -0.0019562 0.0048748 -0.0066606 -0.034108 0.013164 0.037463 0.032775 0.044383 0.033484 0.056718 0.067816 0.046404 -0.14158 -0.1492 -0.1744 -0.16202 -0.15577 -0.1542 -0.14889 -0.14488 -0.14329 -0.15838 -0.15251 -0.16155 -0.18317 -0.16549 -0.17934 -0.181 -0.16091 -0.15276 -0.13753 -0.15693 -0.16771 -0.15249 -0.14442 -0.12789 -0.13841 -0.13602 -0.10903 -0.11605 -0.10774 -0.11599 0.10348 0.10462 0.12052 0.13643 0.1379 0.15332 0.10739 0.095572 0.081549 0.06506 0.062693 0.058498 0.077473 0.079918 0.056529 0.059922 0.090013 0.13258 0.14799 0.16328 0.20035 0.21319 0.20046 0.19127 0.20181 0.17847 0.16137 0.17729 0.15474 0.14306

NrDays1 = size(Tdata1,2)

NrDays1 = 
        4876

% calculate min and max for each day
dailyMin1 = min(Tdata1)

dailyMin1 = 1×4876

-0.2465 -0.277 -0.26209 -0.27948 -0.27054 -0.288 -0.2515 -0.25291 -0.26441 -0.26114 -0.27178 -0.28542 -0.2709 -0.28054 -0.27059 -0.26042 -0.27066 -0.23581 -0.22626 -0.23399 -0.22192 -0.2102 -0.18272 -0.22591 -0.2177 -0.18819 -0.19151 -0.17306 -0.18834 -0.17524

dailyMax1 = max(Tdata1)

dailyMax1 = 1×4876

0.14452 0.18396 0.15837 0.17844 0.17396 0.19869 0.20682 0.2057 0.20472 0.22796 0.2714 0.33797 0.38559 0.45053 0.461 0.40301 0.42617 0.40764 0.45489 0.51208 0.54332 0.56781 0.58432 0.56405 0.55173 0.48655 0.44869 0.42835 0.37039 0.38935

NrNaN2 = nnz(isnan(data2))

NrNaN2 = 
      448906

data2 = data2(~isnan(data2))

data2 = 35609×1

0.042969 0.0080714 0.0076017 -0.17217 0.2407 0.22599 0.24472 0.18292 0.14108 0.43792

numDays2 = numel(data2)/24

numDays2 = 
       1483.7

numDays2 = fix(numDays2)

numDays2 = 
        1483

data2 = data2(1:fix(numDays2)*24)

data2 = 35592×1

0.042969 0.0080714 0.0076017 -0.17217 0.2407 0.22599 0.24472 0.18292 0.14108 0.43792

Tdata2 = reshape(data2,[],24).'

Tdata2 = 24×1483

0.042969 0.0080714 0.0076017 -0.17217 0.2407 0.22599 0.24472 0.18292 0.14108 0.43792 0.16903 -0.096736 0.24944 0.026714 0.29188 0.34562 0.046633 -0.029092 -0.014236 -0.012677 0.0051745 0.29123 0.25167 0.070853 0.29805 0.14225 0.14928 0.14814 -0.056768 0.4183 0.40759 0.16766 0.87529 0.87734 0.38444 0.19761 0.036653 0.02588 0.095001 0.094382 -0.34344 -0.18514 -0.15477 1.3688 0.40444 -0.048043 -0.051517 -0.044927 0.28443 0.22334 -0.033382 0.23675 0.21123 0.22949 -0.090283 -0.068657 1.1169 -0.02506 0.1552 -0.12068 -0.12797 -0.096339 0.032571 0.0079394 -0.018924 -0.056825 0.41201 -0.087299 -0.022903 -0.06116 -0.063732 -0.10597 -0.10325 0.14256 0.15433 0.36148 -0.091025 -0.057225 0.01907 0.097346 0.09677 0.052912 0.2459 0.027406 -0.0041486 -0.097538 -0.094861 -0.21416 -0.090903 -0.064856 0.32447 0.20142 0.28844 0.1113 0.042889 0.048707 -0.01153 0.14548 0.16812 0.2937 0.091153 0.29312 -0.036761 -0.0086433 0.26756 0.064993 -0.042574 0.19723 0.17687 0.26203 0.035154 0.053754 0.22424 -0.047574 0.13037 0.12771 -0.10648 -0.0072317 -0.0057692 -0.11864 0.016319 -0.026082 -0.015622 0.1286 -0.061284 -0.021463 -0.15624 -0.067284 -0.055541 -0.053029 -0.2316 -0.24488 0.27277 0.045762 0.090873 0.10787 0.33128 0.334 0.040706 0.0807 0.016541 -0.032657 -0.050981 -0.049387 -0.2882 -0.14799 -0.12434 0.23611 0.092414 -0.14284 -0.12738 0.38328 -0.06186 -0.14896 -0.26218 -0.26311 -0.16655 -0.01835 0.0016429 0.03829 -0.078869 -0.069505 -0.1098 -0.1615 -0.17123 -0.16298 -0.015523 -0.092838 -0.11367 -0.14074 0.10033 0.1184 0.018203 -0.074161 -0.17304 0.00030183 -0.1192 -0.014064 -0.014385 -0.41714 0.13508 0.14591 0.50803 0.059652 0.072045 -0.011699 0.04807 0.11747 0.11963 0.31272 0.31998 0.55422 0.34655 0.38402 0.34963 0.35385 0.35366 0.27473 0.20782 0.097461 -0.08328 0.090962 0.097096 -0.14116 -0.022805 0.0038252 0.38136 -0.20596 0.032469 -0.05595 -0.043174 0.087832 0.052321 -0.0069475 0.03827 -0.01425 0.078169 0.10457 0.086145 0.099214 0.037712 0.053729 0.14658 0.071793 -0.060834 0.14612 -0.049222 0.10412 0.10267 -0.23512 -0.23825 0.055851 0.25873 0.29035 0.023673 0.063937 0.065537 0.12775 0.010922 0.10167 0.062069 -0.013435 -0.017149 0.1767 0.10487 0.27022 0.034147 0.034968 0.037019 0.2385 0.25673 0.13493 0.026021 0.31059 0.080356 0.13572 0.13397 0.25689 0.012042 0.24341 0.2245 0.21883 0.13161 0.14884 0.099209 -0.012098 0.11441 0.31337 0.00032963 0.024622 -0.053575 -0.1314 -0.14669 0.059919 0.065851 0.089178 0.21813 0.21688 0.21868 -0.045401 0.18086 0.047557 -0.0066763 -0.048877 -0.04565 -0.19126 -0.085339 -0.061679 0.043619 -0.026537 -0.1292 -0.023858 -0.11686 -0.0729 0.075209 -0.073848 0.012615 -0.0079333 0.0080566 -0.063208

NrDays2 = size(Tdata2,2)

NrDays2 = 
        1483

% calculate min and max for each day
dailyMin2 = min(Tdata2)

dailyMin2 = 1×1483

-0.32602 -0.32704 -0.53564 -0.21545 -0.26218 -0.44455 -0.26066 -0.2626 -0.39712 -0.3983 -0.57187 -0.39345 -0.38498 -0.24448 -0.35454 -0.3531 -0.28971 -0.3292 -0.38221 -0.37623 -0.34699 -0.25698 -0.18386 -0.29296 -0.58517 -0.34078 -0.2518 -0.21416 -0.4546 -0.44964

dailyMax2 = max(Tdata2)

dailyMax2 = 1×1483

0.49457 0.40117 0.87529 0.87734 0.38444 0.27022 0.41201 0.35795 0.74142 0.43792 0.31998 0.55422 0.41044 1.3688 0.40444 0.55152 0.55415 0.50979 0.46801 0.48776 0.55602 0.50783 0.50512 0.43114 0.41305 0.23216 1.1169 0.31337 0.20491 0.4183

There are no associated datetime values, so my idea will of course not work. Using reshape is the only option, however with all the NaN values, I am not certain if the usable data actually correspond to specific days or simply to sets of 24 values each. (I deleteed all the NaN values from each data set, because otherwise only the NaN values would be visible here. The non-NaN data would be in columns far off to the right.)

.

Answer 2

[CAM]

Have you considered reshaping the 2D matrix into a 3D matrix -- (number of sensors) x 24 x days? Then you could use max for each row (sensor) within each day (3rd dim).

[Victoria Pilar Quesada García]

I wouldn't really know how to do it, for now I only have a 485*552262 matrix with NaN and numbers. If, in the way you say, I would divide those 552262 into groups of 24 values ​​and then calculate the max, it would be perfect.