Calculate the maximum and minimum values and what day these values occured

Question

Ancalagon8 am 6 Jan. 2023

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https://de.mathworks.com/matlabcentral/answers/1889732-calculate-the-maximum-and-minimum-values-and-what-day-these-values-occured

Bearbeitet: Walter Roberson am 14 Feb. 2023

Hello I have a big timetable (one year) with temperature recorded every minute. I want to calculate the maximum and minimum values of every month and what day these values occured.

x=timetable(date_time, Var);

MaxTemp = retime(x,'monthly','max'); 
MinTemp = retime(x,'monthly','min'); 

Any ideas how to proceed?

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othman warde am 14 Feb. 2023

Bearbeitet: Walter Roberson am 14 Feb. 2023

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To determine the maximum and minimum values of every month and the corresponding dates on which these values occurred, you can use the resample function in MATLAB. Here's an example of how you can use it:.

% Convert the timetable to a timetable with monthly intervals
monthlyData = retime(x, 'monthly', 'mean');
% Extract the maximum and minimum values of each month
MaxTemp = resample(x.Var, 'monthly', 'max');
MinTemp = resample(x.Var, 'monthly', 'min');
% Find the dates corresponding to the maximum and minimum values 
MaxTempDates = resample(x.date_time, 'monthly', @(x) x(find(x.Var == max(x.Var), 1))); MinTempDates = resample(x.date_time, 'monthly', @(x) x(find(x.Var == min(x.Var), 1))); 

In the code above, retime is used to convert the original timetable to a new timetable with monthly intervals. Then, resample is used to extract the maximum and minimum values of each month. Finally, resample is used again to find the dates corresponding to the maximum and minimum values. The @(x) x(find(x.Var == max(x.Var), 1)) and @(x) x(find(x.Var == min(x.Var), 1)) functions are used to find the first occurrence of the maximum and minimum values in each month, respectively. The resulting MaxTempDates and MinTempDates variables will be timetables with the date of the maximum and minimum values for each month.

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Answer 1

Star Strider am 6 Jan. 2023

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https://de.mathworks.com/matlabcentral/answers/1889732-calculate-the-maximum-and-minimum-values-and-what-day-these-values-occured#answer_1143042

I thought we covered a version of that in my Comment to your other thread.

That dealt with the hour that the daily maximum occurred. It would be straightforward to change that code to do what you want to do here.

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Star Strider am 6 Jan. 2023

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It took a bit longer than I anticipated to adapt my previous code to this problem.

Try this —

DT = datetime('01-Dec-2022 00:00:00') + days(0:365).';

Temperature = sin(2*pi*(0:numel(DT)-1)/24-0.5).'*12+5 + randn(size(DT))*1.5;

TT1 = timetable(DT, Temperature)

TT1 = 366×1 timetable

DT Temperature ___________ ___________ 01-Dec-2022 0.66504 02-Dec-2022 1.5196 03-Dec-2022 5.691 04-Dec-2022 10.741 05-Dec-2022 10.712 06-Dec-2022 11.851 07-Dec-2022 15.96 08-Dec-2022 19.993 09-Dec-2022 17.681 10-Dec-2022 16.038 11-Dec-2022 15.199 12-Dec-2022 10.901 13-Dec-2022 13.714 14-Dec-2022 10.91 15-Dec-2022 3.3633 16-Dec-2022 2.7038

figure

plot(TT1.DT, TT1.Temperature)

grid

MonthlyMax = retime(TT1, 'monthly', 'max')

MonthlyMax = 13×1 timetable

DT Temperature ___________ ___________ 01-Dec-2022 19.993 01-Jan-2023 18.335 01-Feb-2023 18.99 01-Mar-2023 17.149 01-Apr-2023 18.211 01-May-2023 20.026 01-Jun-2023 17.665 01-Jul-2023 20.068 01-Aug-2023 18.648 01-Sep-2023 17.956 01-Oct-2023 16.865 01-Nov-2023 19.498 01-Dec-2023 14.852

DailyMax = retime(TT1, 'daily', 'max')

DailyMax = 366×1 timetable

DT Temperature ___________ ___________ 01-Dec-2022 0.66504 02-Dec-2022 1.5196 03-Dec-2022 5.691 04-Dec-2022 10.741 05-Dec-2022 10.712 06-Dec-2022 11.851 07-Dec-2022 15.96 08-Dec-2022 19.993 09-Dec-2022 17.681 10-Dec-2022 16.038 11-Dec-2022 15.199 12-Dec-2022 10.901 13-Dec-2022 13.714 14-Dec-2022 10.91 15-Dec-2022 3.3633 16-Dec-2022 2.7038

MonthlyMin = retime(TT1, 'monthly', 'min');

MonthlySTD = retime(TT1, 'monthly', @std);

T2 = table(MonthlyMax.DT, MonthlyMax.Temperature, MonthlyMin.Temperature, MonthlySTD.Temperature, 'VariableNames',{'DT','Max','Min','StDv'})

T2 = 13×4 table

DT Max Min StDv ___________ ______ _______ ______ 01-Dec-2022 19.993 -7.0232 8.0264 01-Jan-2023 18.335 -8.7917 8.6537 01-Feb-2023 18.99 -8.032 8.3328 01-Mar-2023 17.149 -7.717 8.5402 01-Apr-2023 18.211 -8.5859 8.0011 01-May-2023 20.026 -9.9484 8.9743 01-Jun-2023 17.665 -7.8864 8.6088 01-Jul-2023 20.068 -8.1143 8.6465 01-Aug-2023 18.648 -6.5155 8.789 01-Sep-2023 17.956 -8.7416 8.7519 01-Oct-2023 16.865 -9.2885 9.0736 01-Nov-2023 19.498 -8.6919 8.5491 01-Dec-2023 14.852 14.852 0

Thresholdv = [16; 17; 18; 19; 20]; % Column Vector

for k = 1:numel(Thresholdv)

DaysMeetingThreshold(k,:) = nnz(T2.Max >= Thresholdv(k)); % Days Equal To Or Higher Than Thresholdv (°C)

end

ThresholdTable = table(Thresholdv, DaysMeetingThreshold)

ThresholdTable = 5×2 table

Thresholdv DaysMeetingThreshold __________ ____________________ 16 12 17 11 18 8 19 4 20 2

[yd,md,dd] = ymd(DailyMax.DT); % Year, Month, Day Of Daily Maxima

for k = 1:numel(MonthlyMax)

[ym,mm,dm] = ymd(MonthlyMax.DT(k));

Lv = ismember([yd,md], [ym,mm], 'rows');

idx = DailyMax.Temperature(Lv) == MonthlyMax.Temperature(k);

Mv = find(Lv);

Dv = find(idx);

HM = DailyMax(Mv(Dv),:);

MonthDayMax(k,:) = timetable2table(HM);

end

MonthDayMax % Table Of Day In Each Month At Which Maximum Temperature Occurred

MonthDayMax = 13×2 table

DT Temperature ___________ ___________ 08-Dec-2022 19.993 03-Jan-2023 18.335 18-Feb-2023 18.99 15-Mar-2023 17.149 08-Apr-2023 18.211 01-May-2023 20.026 18-Jun-2023 17.665 11-Jul-2023 20.068 29-Aug-2023 18.648 22-Sep-2023 17.956 18-Oct-2023 16.865 11-Nov-2023 19.498 01-Dec-2023 14.852

.

Star Strider am 6 Jan. 2023

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There were duplicate maxima, and that caused the problem.

Changing this assignment to only select the first index:

HM = DailyMax(Mv(Dv(1)),:);

solved the problem.

I initially forgot the corresponding minima, so I added a separate loop for that. It is simply a duplicate of the first loop with appropriate changes.

Bothe the maxima and minima are now calculated.

% DT = datetime('01-Dec-2022 00:00:00') + days(0:365).';

% Temperature = sin(2*pi*(0:numel(DT)-1)/24-0.5).'*12+5 + randn(size(DT))*1.5;

% TT1 = timetable(DT, Temperature)

LD = load(websave('dataset','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1255052/dataset.mat'))

LD = struct with fields:

TT1: [513077×1 timetable]

TT1 = LD.TT1

TT1 = 513077×1 timetable

date_time Temperature __________________ ___________ 01-Jan-19 00:00:00 10.14 01-Jan-19 00:03:00 10.14 01-Jan-19 00:04:00 10.14 01-Jan-19 00:05:00 10.14 01-Jan-19 00:06:00 10.139 01-Jan-19 00:07:00 10.139 01-Jan-19 00:08:00 10.139 01-Jan-19 00:09:00 10.139 01-Jan-19 00:10:00 10.139 01-Jan-19 00:11:00 10.139 01-Jan-19 00:12:00 10.139 01-Jan-19 00:13:00 10.139 01-Jan-19 00:14:00 10.139 01-Jan-19 00:15:00 10.139 01-Jan-19 00:16:00 10.139 01-Jan-19 00:17:00 10.139

figure

plot(TT1.date_time, TT1.Temperature)

grid

% return

MonthlyMax = retime(TT1, 'monthly', 'max')

MonthlyMax = 12×1 timetable

date_time Temperature __________________ ___________ 01-Jan-19 00:00:00 10.241 01-Feb-19 00:00:00 10.278 01-Mar-19 00:00:00 10.269 01-Apr-19 00:00:00 10.261 01-May-19 00:00:00 10.204 01-Jun-19 00:00:00 10.204 01-Jul-19 00:00:00 10.184 01-Aug-19 00:00:00 10.175 01-Sep-19 00:00:00 10.223 01-Oct-19 00:00:00 10.231 01-Nov-19 00:00:00 10.212 01-Dec-19 00:00:00 10.292

DailyMax = retime(TT1, 'daily', 'max')

DailyMax = 365×1 timetable

date_time Temperature __________________ ___________ 01-Jan-19 00:00:00 10.18 02-Jan-19 00:00:00 10.174 03-Jan-19 00:00:00 10.139 04-Jan-19 00:00:00 10.182 05-Jan-19 00:00:00 10.166 06-Jan-19 00:00:00 10.162 07-Jan-19 00:00:00 10.221 08-Jan-19 00:00:00 10.233 09-Jan-19 00:00:00 10.184 10-Jan-19 00:00:00 10.109 11-Jan-19 00:00:00 10.152 12-Jan-19 00:00:00 10.119 13-Jan-19 00:00:00 10.12 14-Jan-19 00:00:00 10.084 15-Jan-19 00:00:00 10.189 16-Jan-19 00:00:00 10.241

DailyMin = retime(TT1, 'daily', 'min')

DailyMin = 365×1 timetable

date_time Temperature __________________ ___________ 01-Jan-19 00:00:00 10.134 02-Jan-19 00:00:00 10.083 03-Jan-19 00:00:00 10.05 04-Jan-19 00:00:00 10.137 05-Jan-19 00:00:00 10.138 06-Jan-19 00:00:00 10.122 07-Jan-19 00:00:00 10.161 08-Jan-19 00:00:00 10.183 09-Jan-19 00:00:00 10.006 10-Jan-19 00:00:00 10.01 11-Jan-19 00:00:00 10.109 12-Jan-19 00:00:00 10.077 13-Jan-19 00:00:00 10.084 14-Jan-19 00:00:00 10.002 15-Jan-19 00:00:00 10.006 16-Jan-19 00:00:00 10.19

MonthlyMin = retime(TT1, 'monthly', 'min');

MonthlySTD = retime(TT1, 'monthly', @std);

T2 = table(MonthlyMax.date_time, MonthlyMax.Temperature, MonthlyMin.Temperature, MonthlySTD.Temperature, 'VariableNames',{'date_time','Max','Min','StDv'})

T2 = 12×4 table

date_time Max Min StDv __________________ ______ ______ ________ 01-Jan-19 00:00:00 10.241 9.8976 NaN 01-Feb-19 00:00:00 10.278 10.053 0.049242 01-Mar-19 00:00:00 10.269 10.033 0.047355 01-Apr-19 00:00:00 10.261 10.027 0.052837 01-May-19 00:00:00 10.204 10.006 0.033589 01-Jun-19 00:00:00 10.204 10.051 0.024046 01-Jul-19 00:00:00 10.184 10.035 0.033762 01-Aug-19 00:00:00 10.175 10.061 0.027458 01-Sep-19 00:00:00 10.223 10.087 0.031658 01-Oct-19 00:00:00 10.231 10.041 0.043407 01-Nov-19 00:00:00 10.212 10.047 NaN 01-Dec-19 00:00:00 10.292 9.9079 NaN

Thresholdv = [16; 17; 18; 19; 20]; % Column Vector

for k = 1:numel(Thresholdv)

DaysMeetingThreshold(k,:) = nnz(T2.Max >= Thresholdv(k)); % Days Equal To Or Higher Than Thresholdv (°C)

end

ThresholdTable = table(Thresholdv, DaysMeetingThreshold)

ThresholdTable = 5×2 table

Thresholdv DaysMeetingThreshold __________ ____________________ 16 0 17 0 18 0 19 0 20 0

[ydx,mdx,ddx] = ymd(DailyMax.date_time); % Year, Month, Day Of Daily Maxima

for k = 1:numel(MonthlyMax)

[ym,mm,dm] = ymd(MonthlyMax.date_time(k));

Lv = ismember([ydx,mdx], [ym,mm], 'rows');

idx = DailyMax.Temperature(Lv) == MonthlyMax.Temperature(k);

Mv = find(Lv);

Dv = find(idx);

HM = DailyMax(Mv(Dv(1)),:);

MonthDayMax(k,:) = timetable2table(HM);

end

[ydn,mdn,ddn] = ymd(DailyMin.date_time); % Year, Month, Day Of Daily Maxima

for k = 1:numel(MonthlyMin)

[ym,mm,dm] = ymd(MonthlyMin.date_time(k));

Lv = ismember([ydn,mdn], [ym,mm], 'rows');

idx = DailyMin.Temperature(Lv) == MonthlyMin.Temperature(k);

Mv = find(Lv);

Dv = find(idx);

HM = DailyMin(Mv(Dv(1)),:);

MonthDayMin(k,:) = timetable2table(HM);

end

MonthDayMax % Table Of Day In Each Month At Which Maximum Temperature Occurred

MonthDayMax = 12×2 table

date_time Temperature __________________ ___________ 16-Jan-19 00:00:00 10.241 17-Feb-19 00:00:00 10.278 09-Mar-19 00:00:00 10.269 21-Apr-19 00:00:00 10.261 30-May-19 00:00:00 10.204 07-Jun-19 00:00:00 10.204 01-Jul-19 00:00:00 10.184 20-Aug-19 00:00:00 10.175 15-Sep-19 00:00:00 10.223 12-Oct-19 00:00:00 10.231 16-Nov-19 00:00:00 10.212 18-Dec-19 00:00:00 10.292

MonthDayMin % Table Of Day In Each Month At Which Minimum Temperature Occurred

MonthDayMin = 12×2 table

date_time Temperature __________________ ___________ 25-Jan-19 00:00:00 9.8976 06-Feb-19 00:00:00 10.053 12-Mar-19 00:00:00 10.033 06-Apr-19 00:00:00 10.027 05-May-19 00:00:00 10.006 29-Jun-19 00:00:00 10.051 10-Jul-19 00:00:00 10.035 03-Aug-19 00:00:00 10.061 05-Sep-19 00:00:00 10.087 04-Oct-19 00:00:00 10.041 26-Nov-19 00:00:00 10.047 14-Dec-19 00:00:00 9.9079

Are those the desired results?

.

Star Strider am 7 Jan. 2023

Bearbeitet: Star Strider am 7 Jan. 2023

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I thought you only wanted the daily max and min.

This tweak gives the day and hour for the max and min each month —

% DT = datetime('01-Dec-2022 00:00:00') + days(0:365).';

% Temperature = sin(2*pi*(0:numel(DT)-1)/24-0.5).'*12+5 + randn(size(DT))*1.5;

% TT1 = timetable(DT, Temperature)

LD = load(websave('dataset','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1255052/dataset.mat'))

LD = struct with fields:

TT1: [513077×1 timetable]

TT1 = LD.TT1

TT1 = 513077×1 timetable

date_time Temperature __________________ ___________ 01-Jan-19 00:00:00 10.14 01-Jan-19 00:03:00 10.14 01-Jan-19 00:04:00 10.14 01-Jan-19 00:05:00 10.14 01-Jan-19 00:06:00 10.139 01-Jan-19 00:07:00 10.139 01-Jan-19 00:08:00 10.139 01-Jan-19 00:09:00 10.139 01-Jan-19 00:10:00 10.139 01-Jan-19 00:11:00 10.139 01-Jan-19 00:12:00 10.139 01-Jan-19 00:13:00 10.139 01-Jan-19 00:14:00 10.139 01-Jan-19 00:15:00 10.139 01-Jan-19 00:16:00 10.139 01-Jan-19 00:17:00 10.139

figure

plot(TT1.date_time, TT1.Temperature)

grid

% return

MonthlyMax = retime(TT1, 'monthly', 'max')

MonthlyMax = 12×1 timetable

date_time Temperature __________________ ___________ 01-Jan-19 00:00:00 10.241 01-Feb-19 00:00:00 10.278 01-Mar-19 00:00:00 10.269 01-Apr-19 00:00:00 10.261 01-May-19 00:00:00 10.204 01-Jun-19 00:00:00 10.204 01-Jul-19 00:00:00 10.184 01-Aug-19 00:00:00 10.175 01-Sep-19 00:00:00 10.223 01-Oct-19 00:00:00 10.231 01-Nov-19 00:00:00 10.212 01-Dec-19 00:00:00 10.292

MinutelyMax = retime(TT1, 'minutely', 'max')

MinutelyMax = 525600×1 timetable

date_time Temperature __________________ ___________ 01-Jan-19 00:00:00 10.14 01-Jan-19 00:01:00 NaN 01-Jan-19 00:02:00 NaN 01-Jan-19 00:03:00 10.14 01-Jan-19 00:04:00 10.14 01-Jan-19 00:05:00 10.14 01-Jan-19 00:06:00 10.139 01-Jan-19 00:07:00 10.139 01-Jan-19 00:08:00 10.139 01-Jan-19 00:09:00 10.139 01-Jan-19 00:10:00 10.139 01-Jan-19 00:11:00 10.139 01-Jan-19 00:12:00 10.139 01-Jan-19 00:13:00 10.139 01-Jan-19 00:14:00 10.139 01-Jan-19 00:15:00 10.139

MinutelyMin = retime(TT1, 'minutely', 'min')

MinutelyMin = 525600×1 timetable

date_time Temperature __________________ ___________ 01-Jan-19 00:00:00 10.14 01-Jan-19 00:01:00 NaN 01-Jan-19 00:02:00 NaN 01-Jan-19 00:03:00 10.14 01-Jan-19 00:04:00 10.14 01-Jan-19 00:05:00 10.14 01-Jan-19 00:06:00 10.139 01-Jan-19 00:07:00 10.139 01-Jan-19 00:08:00 10.139 01-Jan-19 00:09:00 10.139 01-Jan-19 00:10:00 10.139 01-Jan-19 00:11:00 10.139 01-Jan-19 00:12:00 10.139 01-Jan-19 00:13:00 10.139 01-Jan-19 00:14:00 10.139 01-Jan-19 00:15:00 10.139

MonthlyMin = retime(TT1, 'monthly', 'min');

MonthlySTD = retime(TT1, 'monthly', @std);

T2 = table(MonthlyMax.date_time, MonthlyMax.Temperature, MonthlyMin.Temperature, MonthlySTD.Temperature, 'VariableNames',{'date_time','Max','Min','StDv'})

T2 = 12×4 table

date_time Max Min StDv __________________ ______ ______ ________ 01-Jan-19 00:00:00 10.241 9.8976 NaN 01-Feb-19 00:00:00 10.278 10.053 0.049242 01-Mar-19 00:00:00 10.269 10.033 0.047355 01-Apr-19 00:00:00 10.261 10.027 0.052837 01-May-19 00:00:00 10.204 10.006 0.033589 01-Jun-19 00:00:00 10.204 10.051 0.024046 01-Jul-19 00:00:00 10.184 10.035 0.033762 01-Aug-19 00:00:00 10.175 10.061 0.027458 01-Sep-19 00:00:00 10.223 10.087 0.031658 01-Oct-19 00:00:00 10.231 10.041 0.043407 01-Nov-19 00:00:00 10.212 10.047 NaN 01-Dec-19 00:00:00 10.292 9.9079 NaN

Thresholdv = [16; 17; 18; 19; 20]; % Column Vector

for k = 1:numel(Thresholdv)

DaysMeetingThreshold(k,:) = nnz(T2.Max >= Thresholdv(k)); % Days Equal To Or Higher Than Thresholdv (°C)

end

ThresholdTable = table(Thresholdv, DaysMeetingThreshold)

ThresholdTable = 5×2 table

Thresholdv DaysMeetingThreshold __________ ____________________ 16 0 17 0 18 0 19 0 20 0

[yhx,mhx,dhx] = ymd(MinutelyMax.date_time); % Year, Month, Day Of Daily Maxima

for k = 1:numel(MonthlyMax)

[ym,mm,dm] = ymd(MonthlyMax.date_time(k));

Lv = ismember([yhx,mhx], [ym,mm], 'rows');

idx = MinutelyMax.Temperature(Lv) == MonthlyMax.Temperature(k);

Mv = find(Lv);

Dv = find(idx);

HM = MinutelyMax(Mv(Dv(1)),:);

MonthDayMax(k,:) = timetable2table(HM);

end

[yhn,mhn,dhn] = ymd(MinutelyMin.date_time); % Year, Month, Day Of Daily Maxima

for k = 1:numel(MonthlyMin)

[ym,mm,dm] = ymd(MonthlyMin.date_time(k));

Lv = ismember([yhn,mhn], [ym,mm], 'rows');

idx = MinutelyMin.Temperature(Lv) == MonthlyMin.Temperature(k);

Mv = find(Lv);

Dv = find(idx);

HM = MinutelyMin(Mv(Dv(1)),:);

MonthDayMin(k,:) = timetable2table(HM);

end

MonthDayMax % Table Of Day In Each Month At Which Maximum Temperature Occurred

MonthDayMax = 12×2 table

date_time Temperature __________________ ___________ 16-Jan-19 11:00:00 10.241 17-Feb-19 09:04:00 10.278 09-Mar-19 12:37:00 10.269 21-Apr-19 10:51:00 10.261 30-May-19 12:44:00 10.204 07-Jun-19 23:17:00 10.204 01-Jul-19 01:05:00 10.184 20-Aug-19 23:40:00 10.175 15-Sep-19 10:59:00 10.223 12-Oct-19 11:01:00 10.231 16-Nov-19 10:14:00 10.212 18-Dec-19 11:08:00 10.292

MonthDayMin % Table Of Day In Each Month At Which Minimum Temperature Occurred

MonthDayMin = 12×2 table

date_time Temperature __________________ ___________ 25-Jan-19 05:25:00 9.8976 06-Feb-19 03:51:00 10.053 12-Mar-19 17:53:00 10.033 06-Apr-19 04:59:00 10.027 05-May-19 06:00:00 10.006 29-Jun-19 18:16:00 10.051 10-Jul-19 19:30:00 10.035 03-Aug-19 19:13:00 10.061 05-Sep-19 16:02:00 10.087 04-Oct-19 05:41:00 10.041 26-Nov-19 01:46:00 10.047 14-Dec-19 07:12:00 9.9079

I kept the previous code intact, and copied everything to here to tweak it.

EDIT — (7 Jan 2023 at 17:20)

Changed ‘Hourly’ to ‘Minutely’ to get accuracy to the minute.

.

Star Strider am 8 Jan. 2023

In MATLAB Online öffnen

Thank you!

That depends on how ‘3 max values and the 3 min values’ are defined. For the entire year, use maxk and mink. The second output will be the indices, so to get the entire row, do something like this —

T = array2table(randn(10,2))
T = 10×2 table
      Var1         Var2   
    _________    _________

     0.034356      0.96346
      -1.3018       2.0709
     0.070568    -0.060068
      0.67504      -1.4819
      -1.0024      0.25872
     -0.86488       1.3363
      0.65376      0.51979
    -0.093837       1.6005
     -0.48581     -0.31631
      0.77923     -0.74116
[Col1,idx] = maxk(T{:,1},3);
Tx3 = T(idx,:)
Tx3 = 3×2 table
     Var1        Var2  
    _______    ________

    0.77923    -0.74116
    0.67504     -1.4819
    0.65376     0.51979

With respect to tweaking my code to do something similar, that could be possible, however not without a significant amount of recoding. The problem would be how to define the output table or timetable. That’s not immmediately obvious to me. The retime function would not work for this, however maxk and mink likely could.

With respect to using retime, one option could be:

retime(TT, 'minutely', @(x)maxk(x,3));

However that wouldn’t work in practice. The reason is that according to the documentation in the method section Aggregation Methods with respect to funciton handle methods, ‘Use the function specified by the function handle (for example, @std to calculate the standard deviation for the values in each time bin). func must return an output argument that is a scalar or a row vector, and must accept empty inputs.’ (emphasis added). So returning the 3 maxima would likely throw an error.

One way around that could be to first back up the original timetable, then run the code on a copy of it to first find the maximum for each month, save that, delete it from the timetable, run the code again, save that, delete the maxima, and repeat as long as necessary to return the desired numbers of maxima (or minima). The result would be as many output tables or timetables as required to get the required number of maxima (or minima).

.

Star Strider am 25 Jan. 2023

In MATLAB Online öffnen

That was a shile ago and I’ve forgotten what we were doing with it.

Try something like this —

LD = load(websave('dataset','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1255052/dataset.mat'));

TT1 = LD.TT1

TT1 = 513077×1 timetable

date_time Temperature __________________ ___________ 01-Jan-19 00:00:00 10.14 01-Jan-19 00:03:00 10.14 01-Jan-19 00:04:00 10.14 01-Jan-19 00:05:00 10.14 01-Jan-19 00:06:00 10.139 01-Jan-19 00:07:00 10.139 01-Jan-19 00:08:00 10.139 01-Jan-19 00:09:00 10.139 01-Jan-19 00:10:00 10.139 01-Jan-19 00:11:00 10.139 01-Jan-19 00:12:00 10.139 01-Jan-19 00:13:00 10.139 01-Jan-19 00:14:00 10.139 01-Jan-19 00:15:00 10.139 01-Jan-19 00:16:00 10.139 01-Jan-19 00:17:00 10.139

figure

plot(TT1.date_time, TT1.Temperature)

grid

Thresholdv = (9.8:0.1:10.4).'; % Column Vector

for k1 = 1:12

Lv = month(TT1.date_time) == k1; % Select Month

Month = retime(TT1(Lv,:),'daily','mean'); % Daily Mean Temperature

MMM{k1,:} = month(TT1(Lv,:).date_time(1),'shortname'); % For Row Names

for k2 = 1:numel(Thresholdv)-1 % Histogram Loop

Tempv = Month.Temperature;

DaysMeetingThreshold(k1,k2) = nnz((Tempv >= Thresholdv(k2)) & (Tempv < Thresholdv(k2+1))); % Days Equal To Or Higher Than Thresholdv (°C)

end

DaysThresholdTable = array2table(DaysMeetingThreshold, 'VariableNames',compose('%.2f',Thresholdv(1:end-1)), 'RowNames',[MMM{:}])

DaysThresholdTable = 12×6 table

9.80 9.90 10.00 10.10 10.20 10.30 ____ ____ _____ _____ _____ _____ Jan 0 3 11 14 3 0 Feb 0 0 1 14 13 0 Mar 0 0 2 21 8 0 Apr 0 0 5 20 5 0 May 0 0 3 28 0 0 Jun 0 0 0 30 0 0 Jul 0 0 11 20 0 0 Aug 0 0 6 25 0 0 Sep 0 0 0 25 5 0 Oct 0 0 3 20 8 0 Nov 0 0 5 25 0 0 Dec 0 2 6 10 13 0

This calculates a histogram of sorts without calling any histogram functions. I changed the code a bit to fit the actual data.

.

Star Strider am 1 Feb. 2023

In MATLAB Online öffnen

I’m even more impressed with the table and timetable array types than I was previously!

In order to make it easier to get the exact times of the various maxima, minima, and the rest, I created a function ‘MonthlyToMinutely’ for that. It takes the 'monthly' and 'minutely' aggretated timetable arrays as arguments, and then returns a timetable with the exact times during the year that those values occurred in each month. It also checks to be certain that the timetable arguments have the same variables. It only works with timetable arrays with one variable, however that is what we are currently dealing with.

Here is an example of it with the 'min' timetable arrays —

LD = load(websave('dataset','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1255052/dataset.mat'));
TT1 = LD.TT1
TT1 = 513077×1 timetable
date_timeTemperature_____________________________01-Jan-19 00:00:00       10.14   
    01-Jan-19 00:03:00       10.14   
    01-Jan-19 00:04:00       10.14   
    01-Jan-19 00:05:00       10.14   
    01-Jan-19 00:06:00      10.139   
    01-Jan-19 00:07:00      10.139   
    01-Jan-19 00:08:00      10.139   
    01-Jan-19 00:09:00      10.139   
    01-Jan-19 00:10:00      10.139   
    01-Jan-19 00:11:00      10.139   
    01-Jan-19 00:12:00      10.139   
    01-Jan-19 00:13:00      10.139   
    01-Jan-19 00:14:00      10.139   
    01-Jan-19 00:15:00      10.139   
    01-Jan-19 00:16:00      10.139   
    01-Jan-19 00:17:00      10.139   
MinutelyMin = retime(TT1, 'minutely', 'min');
MonthlyMin = retime(TT1, 'monthly', 'min');
MonthDayMin = MonthlyToMinutely(MonthlyMin,MinutelyMin)
MonthDayMin = 12×2 table
        date_time         Temperature
    __________________    ___________

    25-Jan-19 05:25:00      9.8976   
    06-Feb-19 03:51:00      10.053   
    12-Mar-19 17:53:00      10.033   
    06-Apr-19 04:59:00      10.027   
    05-May-19 06:00:00      10.006   
    29-Jun-19 18:16:00      10.051   
    10-Jul-19 19:30:00      10.035   
    03-Aug-19 19:13:00      10.061   
    05-Sep-19 16:02:00      10.087   
    04-Oct-19 05:41:00      10.041   
    26-Nov-19 01:46:00      10.047   
    14-Dec-19 07:12:00      9.9079   
function ExactTime = MonthlyToMinutely(MonthlyTT,MinutelyTT)
MinutelyVN = MinutelyTT.Properties.VariableNames;
MonthlyVN = MonthlyTT.Properties.VariableNames;
if ~strcmp(MinutelyVN{:}, MonthlyVN{:})
    ExactTime = timetable();
    fprintf('Variable names %s and %s in the argument timetables are not the same.',MonthlyVN{:},MinutelyVN{:})
    return
end
[yhn,mhn,dhn] = ymd(MinutelyTT.date_time);              % Year, Month, Day Of Daily Maxima
for k = 1:numel(MonthlyTT)
    [ym,mm,dm] = ymd(MonthlyTT.date_time(k));           % Year, Month, Day Of Monthily Maxima
    Lv = ismember([yhn,mhn], [ym,mm], 'rows');
    idx = MinutelyTT{:,1}(Lv) == MonthlyTT{:,1}(k);
    Mv = find(Lv);
    Dv = find(idx);
    HM = MinutelyTT(Mv(Dv(1)),:);
    MonthDayTT(k,:) = timetable2table(HM);
end
ExactTime = MonthDayTT;
end

I did not test it with the others, however it should work with them.

.

Star Strider am 2 Feb. 2023

Either save the function to a file called ‘MonthlyToMinutely.m’ (that is likely the best approach, and save it to a subdirectory on your MATLAB search path), or put it at the end of the script you are using it with, similar to what I did here. Saving it to a file is likely the easiest solution.

The code you would save to the ‘MonthlyToMinutely.m’ file is:

function ExactTime = MonthlyToMinutely(MonthlyTT,MinutelyTT)

MinutelyVN = MinutelyTT.Properties.VariableNames;

MonthlyVN = MonthlyTT.Properties.VariableNames;

if ~strcmp(MinutelyVN{:}, MonthlyVN{:})

ExactTime = timetable();

fprintf('Variable names %s and %s in the argument timetables are not the same.',MonthlyVN{:},MinutelyVN{:})

return

end

[yhn,mhn,dhn] = ymd(MinutelyTT.date_time); % Year, Month, Day Of Daily Maxima

for k = 1:numel(MonthlyTT)

[ym,mm,dm] = ymd(MonthlyTT.date_time(k)); % Year, Month, Day Of Monthily Maxima

Lv = ismember([yhn,mhn], [ym,mm], 'rows');

idx = MinutelyTT{:,1}(Lv) == MonthlyTT{:,1}(k);

Mv = find(Lv);

Dv = find(idx);

HM = MinutelyTT(Mv(Dv(1)),:);

MonthDayTT(k,:) = timetable2table(HM);

end

ExactTime = MonthDayTT;

end

.

Star Strider am 2 Feb. 2023

In MATLAB Online öffnen

I checked with the result in my earlier Comment.

They are not the same when I run it —

LD = load(websave('dataset','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1255052/dataset.mat'));
TT1 = LD.TT1
TT1 = 513077×1 timetable
date_timeTemperature_____________________________01-Jan-19 00:00:00       10.14   
    01-Jan-19 00:03:00       10.14   
    01-Jan-19 00:04:00       10.14   
    01-Jan-19 00:05:00       10.14   
    01-Jan-19 00:06:00      10.139   
    01-Jan-19 00:07:00      10.139   
    01-Jan-19 00:08:00      10.139   
    01-Jan-19 00:09:00      10.139   
    01-Jan-19 00:10:00      10.139   
    01-Jan-19 00:11:00      10.139   
    01-Jan-19 00:12:00      10.139   
    01-Jan-19 00:13:00      10.139   
    01-Jan-19 00:14:00      10.139   
    01-Jan-19 00:15:00      10.139   
    01-Jan-19 00:16:00      10.139   
    01-Jan-19 00:17:00      10.139   
MinutelyMax = retime(TT1, 'minutely', 'max');
MonthlyMax = retime(TT1, 'monthly', 'max');
MonthDayMax = MonthlyToMinutely(MonthlyMax,MinutelyMax)
MonthDayMax = 12×2 table
        date_time         Temperature
    __________________    ___________

    16-Jan-19 11:00:00      10.241   
    17-Feb-19 09:04:00      10.278   
    09-Mar-19 12:37:00      10.269   
    21-Apr-19 10:51:00      10.261   
    30-May-19 12:44:00      10.204   
    07-Jun-19 23:17:00      10.204   
    01-Jul-19 01:05:00      10.184   
    20-Aug-19 23:40:00      10.175   
    15-Sep-19 10:59:00      10.223   
    12-Oct-19 11:01:00      10.231   
    16-Nov-19 10:14:00      10.212   
    18-Dec-19 11:08:00      10.292   
MinutelyMin = retime(TT1, 'minutely', 'min');
MonthlyMin = retime(TT1, 'monthly', 'min');
MonthDayMin = MonthlyToMinutely(MonthlyMin,MinutelyMin)
MonthDayMin = 12×2 table
        date_time         Temperature
    __________________    ___________

    25-Jan-19 05:25:00      9.8976   
    06-Feb-19 03:51:00      10.053   
    12-Mar-19 17:53:00      10.033   
    06-Apr-19 04:59:00      10.027   
    05-May-19 06:00:00      10.006   
    29-Jun-19 18:16:00      10.051   
    10-Jul-19 19:30:00      10.035   
    03-Aug-19 19:13:00      10.061   
    05-Sep-19 16:02:00      10.087   
    04-Oct-19 05:41:00      10.041   
    26-Nov-19 01:46:00      10.047   
    14-Dec-19 07:12:00      9.9079   
MinutelyMax = retime(TT1, 'minutely', 'max');
MonthlyMax = retime(TT1, 'monthly', 'max');
MonthDayMax = MonthlyToMinutely(MonthlyMax,MinutelyMax)
MonthDayMax = 12×2 table
        date_time         Temperature
    __________________    ___________

    16-Jan-19 11:00:00      10.241   
    17-Feb-19 09:04:00      10.278   
    09-Mar-19 12:37:00      10.269   
    21-Apr-19 10:51:00      10.261   
    30-May-19 12:44:00      10.204   
    07-Jun-19 23:17:00      10.204   
    01-Jul-19 01:05:00      10.184   
    20-Aug-19 23:40:00      10.175   
    15-Sep-19 10:59:00      10.223   
    12-Oct-19 11:01:00      10.231   
    16-Nov-19 10:14:00      10.212   
    18-Dec-19 11:08:00      10.292   
MinutelyMin = retime(TT1, 'minutely', 'min');
MonthlyMin = retime(TT1, 'monthly', 'min');
MonthDayMin = MonthlyToMinutely(MonthlyMin,MinutelyMin)
MonthDayMin = 12×2 table
        date_time         Temperature
    __________________    ___________

    25-Jan-19 05:25:00      9.8976   
    06-Feb-19 03:51:00      10.053   
    12-Mar-19 17:53:00      10.033   
    06-Apr-19 04:59:00      10.027   
    05-May-19 06:00:00      10.006   
    29-Jun-19 18:16:00      10.051   
    10-Jul-19 19:30:00      10.035   
    03-Aug-19 19:13:00      10.061   
    05-Sep-19 16:02:00      10.087   
    04-Oct-19 05:41:00      10.041   
    26-Nov-19 01:46:00      10.047   
    14-Dec-19 07:12:00      9.9079   
function ExactTime = MonthlyToMinutely(MonthlyTT,MinutelyTT)
MinutelyVN = MinutelyTT.Properties.VariableNames;
MonthlyVN = MonthlyTT.Properties.VariableNames;
if ~strcmp(MinutelyVN{:}, MonthlyVN{:})
    ExactTime = timetable();
    fprintf('Variable names %s and %s in the argument timetables are not the same.',MonthlyVN{:},MinutelyVN{:})
    return
end
[yhn,mhn,dhn] = ymd(MinutelyTT.date_time);              % Year, Month, Day Of Daily Maxima
for k = 1:numel(MonthlyTT)
    [ym,mm,dm] = ymd(MonthlyTT.date_time(k));           % Year, Month, Day Of Monthily Maxima
    Lv = ismember([yhn,mhn], [ym,mm], 'rows');
    idx = MinutelyTT{:,1}(Lv) == MonthlyTT{:,1}(k);
    Mv = find(Lv);
    Dv = find(idx);
    HM = MinutelyTT(Mv(Dv(1)),:);
    MonthDayTT(k,:) = timetable2table(HM);
end
ExactTime = MonthDayTT;
end

The function appears to work correctly.

.

Ancalagon8 am 2 Feb. 2023

Bearbeitet: Ancalagon8 am 2 Feb. 2023

In MATLAB Online öffnen

Indeed works. As the results that I want were the RangeMax, RangeMin and RangeMean, I had to replace MonthlyMin/Max:

MinutelyMax = retime(TT1, 'minutely', 'max');
MonthlyMax = retime(TT1, 'monthly', 'max');
MonthDayMax = MonthlyToMinutely(MonthlyMax,MinutelyMax)
MinutelyMin = retime(TT1, 'minutely', 'min');
MonthlyMin = retime(TT1, 'monthly', 'min');
MonthDayMin = MonthlyToMinutely(MonthlyMin,MinutelyMin)

with DailyMin/Μax:

MinutelyMax = retime(TT1, 'minutely', 'max');
DailyMax = retime(TT1, 'monthly', 'max');
MonthDayMax = MonthlyToMinutely(DailyMax,MinutelyMax)
MinutelyMin = retime(TT1, 'minutely', 'min');
DailyMin = retime(TT1, 'monthly', 'min');
MonthDayMin = MonthlyToMinutely(DailyMin,MinutelyMin)

in order to retrieve MonthDayMax (365X2 table) MonthDayMin (365X2 table).

So now I continued like this:

DailyRange = MonthDayMax.Temperature - MonthDayMin.Temperature;
DailyRange = timetable(MonthDayMin.date_time, DailyRange);
RangeMean = retime(DailyRange, 'monthly', 'mean')
RangeMax = retime(DailyRange, 'monthly', 'max')
RangeMin = retime(DailyRange, 'monthly', 'min')

The thing is that the retrieved MonthDayMax (365X2) and MonthDayMin (365X2) tables are wrong, as there is not a unique daily max or min value:

MonthDayMin =
365×2 table
date_time         Temperature
__________________    ___________
01-Jan-19 23:44:00       8.093   
02-Jan-19 08:02:00       3.485   
03-Jan-19 23:41:00       5.057   
04-Jan-19 09:42:00       2.584   
05-Jan-19 00:49:00       2.325   
06-Jan-19 07:31:00       0.578   
05-Jan-19 00:33:00       2.546   
08-Jan-19 08:20:00      -0.452   
04-Jan-19 02:38:00       4.652   
01-Jan-19 10:17:00      10.299   
02-Jan-19 00:03:00       7.933   
02-Jan-19 10:33:00       8.475   
02-Jan-19 08:26:00       3.927   
02-Jan-19 07:02:00       5.179   
02-Jan-19 03:16:00       6.674   
08-Jan-19 03:37:00        2.21   
04-Jan-19 05:44:00       3.393   
02-Jan-19 00:07:00       7.941   
01-Jan-19 03:32:00        10.1   
02-Jan-19 00:25:00       8.002   
03-Jan-19 04:47:00       6.445   
01-Jan-19 21:03:00       9.032   
01-Jan-19 00:17:00       9.826   
02-Jan-19 09:37:00        7.62   
01-Jan-19 22:08:00       8.567   
02-Jan-19 02:47:00       7.109   
03-Jan-19 05:44:00       6.064   
01-Jan-19 18:19:00       9.284   
01-Jan-19 03:08:00      10.108   
02-Jan-19 13:03:00       9.482   
02-Jan-19 13:06:00       9.513   
01-Feb-19 02:21:00        8.01   
01-Feb-19 20:46:00      14.091   
02-Feb-19 11:07:00      16.502   
01-Feb-19 11:19:00      14.434   
05-Feb-19 01:19:00      13.572   
01-Feb-19 09:29:00      11.878   
07-Feb-19 05:00:00       9.932   
08-Feb-19 06:29:00       6.369   
09-Feb-19 06:03:00        6.72   
10-Feb-19 07:10:00       6.682   
01-Feb-19 00:55:00       9.291   
01-Feb-19 01:11:00        9.07   
08-Feb-19 08:47:00       8.193   
01-Feb-19 03:59:00       8.452   
15-Feb-19 07:44:00       5.804   
16-Feb-19 02:28:00        5.27   
17-Feb-19 06:42:00       3.943   
18-Feb-19 07:52:00       5.781   
08-Feb-19 03:50:00        7.33   
08-Feb-19 01:42:00        7.88   
08-Feb-19 06:06:00       7.399   
09-Feb-19 07:15:00       7.056   
15-Feb-19 07:41:00        6.01   
24-Feb-19 07:02:00       3.828   
17-Feb-19 05:47:00       5.072   
15-Feb-19 07:02:00       6.636   
09-Feb-19 02:35:00       7.933   
16-Feb-19 02:26:00        5.53   
    .......
    .......
01-Nov-19 07:17:00       14.61   
01-Nov-19 01:33:00       16.09   
01-Nov-19 08:22:00      17.364   
01-Nov-19 00:33:00      16.632   
01-Nov-19 00:36:00      16.494   
01-Nov-19 00:00:00      16.899   
01-Nov-19 06:47:00      15.083   
01-Nov-19 00:46:00      16.365   
01-Nov-19 06:59:00      14.892   
10-Nov-19 23:59:00       14.48   
11-Nov-19 07:18:00      13.114   
01-Nov-19 05:57:00      14.961   
09-Nov-19 02:47:00      15.052   
11-Nov-19 05:44:00      13.732   
11-Nov-19 05:33:00      13.809   
01-Nov-19 06:36:00      15.419   
01-Nov-19 01:18:00      16.357   
11-Nov-19 05:33:00      13.809   
11-Nov-19 05:36:00      13.694   
10-Nov-19 22:01:00      14.846   
21-Nov-19 07:23:00       12.42   
21-Nov-19 06:20:00      12.717   
21-Nov-19 07:31:00      12.511   
14-Nov-19 21:19:00      14.144   
22-Nov-19 04:53:00      13.541   
21-Nov-19 07:35:00      12.557   
27-Nov-19 04:21:00      11.184   
01-Nov-19 05:40:00      15.014   
11-Nov-19 00:27:00      14.869   
10-Nov-19 22:38:00      15.037   
01-Dec-19 17:15:00       13.61   
02-Dec-19 05:19:00        8.46   
03-Dec-19 01:37:00      11.733   
02-Dec-19 18:17:00      13.778   
05-Dec-19 00:55:00       9.978   
02-Dec-19 22:17:00      12.191   
01-Dec-19 00:14:00      15.411   
08-Dec-19 08:04:00      10.802   
02-Dec-19 01:40:00       9.421   
02-Dec-19 09:13:00      11.802   
08-Dec-19 06:44:00      11.512   
08-Dec-19 08:04:00      10.802   
02-Dec-19 00:14:00      10.947   
09-Dec-19 01:48:00      10.672   
02-Dec-19 00:45:00       9.635   
02-Dec-19 00:27:00      10.299   
02-Dec-19 04:16:00       9.749   
09-Dec-19 00:49:00      10.848   
08-Dec-19 06:34:00      11.382   
02-Dec-19 09:56:00      13.488   
02-Dec-19 09:32:00      12.733   
02-Dec-19 16:40:00      15.823   
05-Dec-19 01:11:00      12.809   
03-Dec-19 03:49:00      13.572   
02-Dec-19 01:33:00       9.826   
26-Dec-19 06:43:00        6.88   
27-Dec-19 06:25:00        6.27   
27-Dec-19 04:07:00       6.674   
27-Dec-19 06:06:00       6.621   
30-Dec-19 07:47:00         5.4   
31-Dec-19 23:44:00       5.606   

Star Strider am 2 Feb. 2023

In MATLAB Online öffnen

To calculate the ranges, it would likely be better to calculate something other than the the minutely ranges and then the maximum and minimum ranges from that. A range will not work for the ‘minutely’ values, since there is only one temperature recorded each minute.

There is simply no possible way to calculate a range from single values, since there is no variation in them.

A fix for that is to aggregate over small intervals, and for this I chose:

'Timestep',minutes(2)

in ‘MinutelyMin’ and ‘MinutelyMax’ and from those I calculated the ranges. Other intervals are of course possible. The ‘Monthly’ range values were calcualted from the ‘Minutely’ values, since it is higholy unlikely that a monthly range is going to be in any way equivalent to a range over 2 minutes (or whatever aggregation interval is used). The reason of course is that the ranges are unique values, and do not exist in the original data. They first must be calculated.

With those changes, it works for the ranges —

LD = load(websave('dataset','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1255052/dataset.mat'));
TT1 = LD.TT1
TT1 = 513077×1 timetable
date_timeTemperature_____________________________01-Jan-19 00:00:00       10.14   
    01-Jan-19 00:03:00       10.14   
    01-Jan-19 00:04:00       10.14   
    01-Jan-19 00:05:00       10.14   
    01-Jan-19 00:06:00      10.139   
    01-Jan-19 00:07:00      10.139   
    01-Jan-19 00:08:00      10.139   
    01-Jan-19 00:09:00      10.139   
    01-Jan-19 00:10:00      10.139   
    01-Jan-19 00:11:00      10.139   
    01-Jan-19 00:12:00      10.139   
    01-Jan-19 00:13:00      10.139   
    01-Jan-19 00:14:00      10.139   
    01-Jan-19 00:15:00      10.139   
    01-Jan-19 00:16:00      10.139   
    01-Jan-19 00:17:00      10.139   
MinutelyMin = retime(TT1, 'regular',  'min', 'Timestep',minutes(2))
MinutelyMin = 262800×1 timetable
date_timeTemperature_____________________________01-Jan-19 00:00:00       10.14   
    01-Jan-19 00:02:00       10.14   
    01-Jan-19 00:04:00       10.14   
    01-Jan-19 00:06:00      10.139   
    01-Jan-19 00:08:00      10.139   
    01-Jan-19 00:10:00      10.139   
    01-Jan-19 00:12:00      10.139   
    01-Jan-19 00:14:00      10.139   
    01-Jan-19 00:16:00      10.139   
    01-Jan-19 00:18:00      10.139   
    01-Jan-19 00:20:00      10.138   
    01-Jan-19 00:22:00      10.138   
    01-Jan-19 00:24:00      10.138   
    01-Jan-19 00:26:00      10.137   
    01-Jan-19 00:28:00      10.137   
    01-Jan-19 00:30:00      10.138   
MinutelyMax = retime(TT1, 'regular', 'max', 'Timestep',minutes(2))
MinutelyMax = 262800×1 timetable
date_timeTemperature_____________________________01-Jan-19 00:00:00       10.14   
    01-Jan-19 00:02:00       10.14   
    01-Jan-19 00:04:00       10.14   
    01-Jan-19 00:06:00      10.139   
    01-Jan-19 00:08:00      10.139   
    01-Jan-19 00:10:00      10.139   
    01-Jan-19 00:12:00      10.139   
    01-Jan-19 00:14:00      10.139   
    01-Jan-19 00:16:00      10.139   
    01-Jan-19 00:18:00      10.139   
    01-Jan-19 00:20:00      10.139   
    01-Jan-19 00:22:00      10.138   
    01-Jan-19 00:24:00      10.138   
    01-Jan-19 00:26:00      10.137   
    01-Jan-19 00:28:00      10.137   
    01-Jan-19 00:30:00      10.138   
MinutelyRange = table(MinutelyMax.Temperature - MinutelyMin.Temperature, 'VariableNames',{'Temperature'});
MinutelyRange = addvars(MinutelyRange, MinutelyMin.date_time, 'Before','Temperature');
MinutelyRange.Properties.VariableNames = {'date_time','Temperature'};
MinutelyRange = table2timetable(MinutelyRange)
MinutelyRange = 262800×1 timetable
date_timeTemperature_____________________________01-Jan-19 00:00:00            0  
    01-Jan-19 00:02:00            0  
    01-Jan-19 00:04:00      0.00018  
    01-Jan-19 00:06:00      0.00018  
    01-Jan-19 00:08:00      0.00036  
    01-Jan-19 00:10:00      0.00018  
    01-Jan-19 00:12:00      0.00037  
    01-Jan-19 00:14:00      0.00018  
    01-Jan-19 00:16:00      0.00018  
    01-Jan-19 00:18:00      0.00019  
    01-Jan-19 00:20:00      0.00055  
    01-Jan-19 00:22:00      0.00018  
    01-Jan-19 00:24:00      0.00037  
    01-Jan-19 00:26:00      0.00036  
    01-Jan-19 00:28:00            0  
    01-Jan-19 00:30:00      0.00018  
MonthlyRangeMin = retime(MinutelyRange, 'monthly', 'min')
MonthlyRangeMin = 12×1 timetable
        date_time         Temperature
    __________________    ___________

    01-Jan-19 00:00:00         0     
    01-Feb-19 00:00:00         0     
    01-Mar-19 00:00:00         0     
    01-Apr-19 00:00:00         0     
    01-May-19 00:00:00         0     
    01-Jun-19 00:00:00         0     
    01-Jul-19 00:00:00         0     
    01-Aug-19 00:00:00         0     
    01-Sep-19 00:00:00         0     
    01-Oct-19 00:00:00         0     
    01-Nov-19 00:00:00         0     
    01-Dec-19 00:00:00         0     
MonthlyRangeMax = retime(MinutelyRange, 'monthly', 'max')
MonthlyRangeMax = 12×1 timetable
        date_time         Temperature
    __________________    ___________

    01-Jan-19 00:00:00      0.00549  
    01-Feb-19 00:00:00      0.01117  
    01-Mar-19 00:00:00      0.03645  
    01-Apr-19 00:00:00      0.08332  
    01-May-19 00:00:00      0.00787  
    01-Jun-19 00:00:00      0.06977  
    01-Jul-19 00:00:00      0.00531  
    01-Aug-19 00:00:00      0.00385  
    01-Sep-19 00:00:00      0.04743  
    01-Oct-19 00:00:00      0.00933  
    01-Nov-19 00:00:00      0.01026  
    01-Dec-19 00:00:00      0.00751  
MonthlyRange = table(MonthlyRangeMax.Temperature - MonthlyRangeMin.Temperature, 'VariableNames',{'Temperature'});
MonthlyRange = addvars(MonthlyRange, MonthlyRangeMin.date_time, 'Before','Temperature');
MonthlyRange.Properties.VariableNames = {'date_time','Temperature'};
MonthlyRange = table2timetable(MonthlyRange);
MonthDayRange = MonthlyToMinutely(MonthlyRange,MinutelyRange)
MonthDayRange = 12×2 table
        date_time         Temperature
    __________________    ___________

    25-Jan-19 04:20:00      0.00549  
    03-Feb-19 21:26:00      0.01117  
    22-Mar-19 09:36:00      0.03645  
    19-Apr-19 16:10:00      0.08332  
    25-May-19 06:56:00      0.00787  
    29-Jun-19 18:16:00      0.06977  
    18-Jul-19 13:52:00      0.00531  
    22-Aug-19 08:36:00      0.00385  
    14-Sep-19 11:48:00      0.04743  
    04-Oct-19 04:10:00      0.00933  
    07-Nov-19 18:44:00      0.01026  
    04-Dec-19 03:38:00      0.00751  
function ExactTime = MonthlyToMinutely(MonthlyTT,MinutelyTT)
MinutelyVN = MinutelyTT.Properties.VariableNames;
MonthlyVN = MonthlyTT.Properties.VariableNames;
if ~strcmp(MinutelyVN{:}, MonthlyVN{:})
    ExactTime = timetable();
    fprintf('Variable names %s and %s in the argument timetables are not the same.',MonthlyVN{:},MinutelyVN{:})
    return
end
[yhn,mhn,dhn] = ymd(MinutelyTT.date_time);              % Year, Month, Day Of Daily Maxima
for k = 1:numel(MonthlyTT)
    [ym,mm,dm] = ymd(MonthlyTT.date_time(k));           % Year, Month, Day Of Monthily Maxima
    Lv = ismember([yhn,mhn], [ym,mm], 'rows');
    idx = MinutelyTT{:,1}(Lv) == MonthlyTT{:,1}(k);
    Mv = find(Lv);
    Dv = find(idx);
    HM = MinutelyTT(Mv(Dv(1)),:);
    MonthDayTT(k,:) = timetable2table(HM);
end
ExactTime = MonthDayTT;
end

This is the only possible way to calculate the ranges in order to conform to the other calculations.

.

Star Strider am 3 Feb. 2023

In MATLAB Online öffnen

My pleasure!

The ‘MonthlyRangeMin’ and ‘MonthlyRangeMax’ default to midnight on the first of the month for the monthly values. That is simply how retime works. Similarly, the ‘Minutely’ values would default to zero seconds of the appropriate minute if seconds were reported.

The ‘MonthlyDayRange’ (or whatever you choose to call it, if different from my code) reports the dates and times —

MonthDayRange = 12×2 table
        date_time         Temperature
    __________________    ___________
    25-Jan-19 04:20:00      0.00549  
    03-Feb-19 21:26:00      0.01117  
    22-Mar-19 09:36:00      0.03645  
    19-Apr-19 16:10:00      0.08332  
    25-May-19 06:56:00      0.00787  
    29-Jun-19 18:16:00      0.06977  
    18-Jul-19 13:52:00      0.00531  
    22-Aug-19 08:36:00      0.00385  
    14-Sep-19 11:48:00      0.04743  
    04-Oct-19 04:10:00      0.00933  

My ‘MonthlyToMinutely’ function turns out to be reasonably robust, so experiment with it with different arguments to get the result you want.

We used it earlier to get the hourly maxima and minima. The range values must be calculated from the 2-minute ranges (or whatever interval you choose) because the ranges are not an inherent part of the original data, that report single values only. The ranges must be calculated from them, although the accumulation interval for the ranges can be anything you want. I chose 2 minutes here because it is the shortest interval these data permit.

.

Star Strider am 3 Feb. 2023

In MATLAB Online öffnen

To the best of my knowledge, the aggregation time of the values for the range was not previously defined. For the daily range, this is straightforward.

Try this —

LD = load(websave('dataset','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1255052/dataset.mat'));
TT1 = LD.TT1
TT1 = 513077×1 timetable
date_timeTemperature_____________________________01-Jan-19 00:00:00       10.14   
    01-Jan-19 00:03:00       10.14   
    01-Jan-19 00:04:00       10.14   
    01-Jan-19 00:05:00       10.14   
    01-Jan-19 00:06:00      10.139   
    01-Jan-19 00:07:00      10.139   
    01-Jan-19 00:08:00      10.139   
    01-Jan-19 00:09:00      10.139   
    01-Jan-19 00:10:00      10.139   
    01-Jan-19 00:11:00      10.139   
    01-Jan-19 00:12:00      10.139   
    01-Jan-19 00:13:00      10.139   
    01-Jan-19 00:14:00      10.139   
    01-Jan-19 00:15:00      10.139   
    01-Jan-19 00:16:00      10.139   
    01-Jan-19 00:17:00      10.139   
% MinutelyMin = retime(TT1, 'regular',  'min', 'Timestep',minutes(2))
% 
% MinutelyMax = retime(TT1, 'regular', 'max', 'Timestep',minutes(2))
% 
% MinutelyRange = table(MinutelyMax.Temperature - MinutelyMin.Temperature, 'VariableNames',{'Temperature'});
% MinutelyRange = addvars(MinutelyRange, MinutelyMin.date_time, 'Before','Temperature');
% MinutelyRange.Properties.VariableNames = {'date_time','Temperature'};
% MinutelyRange = table2timetable(MinutelyRange)
DailyMin = retime(TT1, 'daily', 'min')
DailyMin = 365×1 timetable
date_timeTemperature_____________________________01-Jan-19 00:00:00      10.134   
    02-Jan-19 00:00:00      10.083   
    03-Jan-19 00:00:00       10.05   
    04-Jan-19 00:00:00      10.137   
    05-Jan-19 00:00:00      10.138   
    06-Jan-19 00:00:00      10.122   
    07-Jan-19 00:00:00      10.161   
    08-Jan-19 00:00:00      10.183   
    09-Jan-19 00:00:00      10.006   
    10-Jan-19 00:00:00       10.01   
    11-Jan-19 00:00:00      10.109   
    12-Jan-19 00:00:00      10.077   
    13-Jan-19 00:00:00      10.084   
    14-Jan-19 00:00:00      10.002   
    15-Jan-19 00:00:00      10.006   
    16-Jan-19 00:00:00       10.19   
DailyMax = retime(TT1, 'daily', 'max')
DailyMax = 365×1 timetable
date_timeTemperature_____________________________01-Jan-19 00:00:00       10.18   
    02-Jan-19 00:00:00      10.174   
    03-Jan-19 00:00:00      10.139   
    04-Jan-19 00:00:00      10.182   
    05-Jan-19 00:00:00      10.166   
    06-Jan-19 00:00:00      10.162   
    07-Jan-19 00:00:00      10.221   
    08-Jan-19 00:00:00      10.233   
    09-Jan-19 00:00:00      10.184   
    10-Jan-19 00:00:00      10.109   
    11-Jan-19 00:00:00      10.152   
    12-Jan-19 00:00:00      10.119   
    13-Jan-19 00:00:00       10.12   
    14-Jan-19 00:00:00      10.084   
    15-Jan-19 00:00:00      10.189   
    16-Jan-19 00:00:00      10.241   
DailyRange = table2timetable(table(DailyMin.date_time, DailyMax.Temperature - DailyMin.Temperature, 'VariableNames',{'date_time','Temperature'}))
DailyRange = 365×1 timetable
date_timeTemperature_____________________________01-Jan-19 00:00:00      0.04597  
    02-Jan-19 00:00:00      0.09137  
    03-Jan-19 00:00:00        0.089  
    04-Jan-19 00:00:00      0.04504  
    05-Jan-19 00:00:00      0.02765  
    06-Jan-19 00:00:00      0.04029  
    07-Jan-19 00:00:00      0.06061  
    08-Jan-19 00:00:00      0.05054  
    09-Jan-19 00:00:00      0.17799  
    10-Jan-19 00:00:00      0.09925  
    11-Jan-19 00:00:00      0.04321  
    12-Jan-19 00:00:00      0.04194  
    13-Jan-19 00:00:00      0.03571  
    14-Jan-19 00:00:00      0.08241  
    15-Jan-19 00:00:00      0.18275  
    16-Jan-19 00:00:00     0.051641  
MonthlyRangeMin = retime(DailyRange, 'monthly', 'min')
MonthlyRangeMin = 12×1 timetable
        date_time         Temperature
    __________________    ___________

    01-Jan-19 00:00:00      0.01758  
    01-Feb-19 00:00:00      0.01977  
    01-Mar-19 00:00:00      0.02014  
    01-Apr-19 00:00:00      0.01721  
    01-May-19 00:00:00      0.01703  
    01-Jun-19 00:00:00      0.01629  
    01-Jul-19 00:00:00      0.01703  
    01-Aug-19 00:00:00      0.01135  
    01-Sep-19 00:00:00      0.01373  
    01-Oct-19 00:00:00      0.01593  
    01-Nov-19 00:00:00      0.00751  
    01-Dec-19 00:00:00      0.01722  
MonthlyRangeMax = retime(DailyRange, 'monthly', 'max')
MonthlyRangeMax = 12×1 timetable
        date_time         Temperature
    __________________    ___________

    01-Jan-19 00:00:00      0.18275  
    01-Feb-19 00:00:00      0.11226  
    01-Mar-19 00:00:00      0.09815  
    01-Apr-19 00:00:00      0.09944  
    01-May-19 00:00:00      0.10896  
    01-Jun-19 00:00:00      0.09028  
    01-Jul-19 00:00:00      0.08588  
    01-Aug-19 00:00:00        0.052  
    01-Sep-19 00:00:00      0.06117  
    01-Oct-19 00:00:00       0.1335  
    01-Nov-19 00:00:00      0.11464  
    01-Dec-19 00:00:00      0.17781  
% MonthlyRange = table(MonthlyRangeMax.Temperature - MonthlyRangeMin.Temperature, 'VariableNames',{'Temperature'});
% MonthlyRange = addvars(MonthlyRange, MonthlyRangeMin.date_time, 'Before','Temperature');
% MonthlyRange.Properties.VariableNames = {'date_time','Temperature'};
% MonthlyRange = table2timetable(MonthlyRange)
MonthDayRangeMax = MonthlyToMinutely(MonthlyRangeMax,DailyRange)        % Output: Day In Month With Maximum Range
MonthDayRangeMax = 12×2 table
        date_time         Temperature
    __________________    ___________

    15-Jan-19 00:00:00      0.18275  
    11-Feb-19 00:00:00      0.11226  
    11-Mar-19 00:00:00      0.09815  
    19-Apr-19 00:00:00      0.09944  
    04-May-19 00:00:00      0.10896  
    29-Jun-19 00:00:00      0.09028  
    10-Jul-19 00:00:00      0.08588  
    03-Aug-19 00:00:00        0.052  
    24-Sep-19 00:00:00      0.06117  
    08-Oct-19 00:00:00       0.1335  
    24-Nov-19 00:00:00      0.11464  
    14-Dec-19 00:00:00      0.17781  
MonthDayRangeMin = MonthlyToMinutely(MonthlyRangeMin,DailyRange)        % Output: Day In Month With Mionimum Range
MonthDayRangeMin = 12×2 table
        date_time         Temperature
    __________________    ___________

    21-Jan-19 00:00:00      0.01758  
    19-Feb-19 00:00:00      0.01977  
    07-Mar-19 00:00:00      0.02014  
    11-Apr-19 00:00:00      0.01721  
    01-May-19 00:00:00      0.01703  
    03-Jun-19 00:00:00      0.01629  
    21-Jul-19 00:00:00      0.01703  
    19-Aug-19 00:00:00      0.01135  
    08-Sep-19 00:00:00      0.01373  
    30-Oct-19 00:00:00      0.01593  
    25-Nov-19 00:00:00      0.00751  
    17-Dec-19 00:00:00      0.01722  
function ExactTime = MonthlyToMinutely(MonthlyTT,MinutelyTT)            % FUNCTION: 'MonthlyToMinutely'
MinutelyVN = MinutelyTT.Properties.VariableNames;
MonthlyVN = MonthlyTT.Properties.VariableNames;
if ~strcmp(MinutelyVN{:}, MonthlyVN{:})
    ExactTime = timetable();
    fprintf('Variable names %s and %s in the argument timetables are not the same.',MonthlyVN{:},MinutelyVN{:})
    return
end
[yhn,mhn,dhn] = ymd(MinutelyTT.date_time);              % Year, Month, Day Of Daily Maxima
for k = 1:numel(MonthlyTT)
    [ym,mm,dm] = ymd(MonthlyTT.date_time(k));           % Year, Month, Day Of Monthily Maxima
    Lv = ismember([yhn,mhn], [ym,mm], 'rows');
    idx = MinutelyTT{:,1}(Lv) == MonthlyTT{:,1}(k);
    Mv = find(Lv);
    Dv = find(idx);
    HM = MinutelyTT(Mv(Dv(1)),:);
    MonthDayTT(k,:) = timetable2table(HM);
end
ExactTime = MonthDayTT;
end

The times are all at midnight (00:00:00) because the ranges are now daily. The retime function defaults to midnight for daily aggregation.

And again, ‘MonthlyToMinuitely’ works here and gives the correct result!

.

Star Strider am 8 Feb. 2023

In MATLAB Online öffnen

I am slightly lost. I have no idea where we are with this data set.

My guess is that we’re doing this —

LD = load(websave('T','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1289405/T.mat'));
TT1 = LD.T
TT1 = 513077×1 timetable
date_timeWind________________________01-Jan-19 00:00:00    -5.624
    01-Jan-19 00:03:00    -5.624
    01-Jan-19 00:04:00    -5.818
    01-Jan-19 00:05:00    -5.818
    01-Jan-19 00:06:00    -6.012
    01-Jan-19 00:07:00    -6.206
    01-Jan-19 00:08:00    -6.788
    01-Jan-19 00:09:00    -5.818
    01-Jan-19 00:10:00     -5.43
    01-Jan-19 00:11:00    -5.818
    01-Jan-19 00:12:00    -6.012
    01-Jan-19 00:13:00     -5.43
    01-Jan-19 00:14:00    -6.012
    01-Jan-19 00:15:00    -5.236
    01-Jan-19 00:16:00    -5.818
    01-Jan-19 00:17:00    -6.206
% return
% LD = load(websave('dataset','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1255052/dataset.mat'));
% TT1 = LD.TT1
MinutelyMax = retime(TT1, 'minutely', 'max');
MonthlyMax = retime(TT1, 'monthly', 'max');
MonthDayMax = MonthlyToMinutely(MonthlyMax,MinutelyMax)
MonthDayMax = 12×2 table
        date_time          Wind 
    __________________    ______

    28-Jan-19 12:48:00    783.79
    13-Feb-19 13:23:00    894.92
    29-Mar-19 12:24:00    1023.9
    11-Apr-19 13:17:00      1214
    30-May-19 13:29:00    1280.9
    29-Jun-19 14:46:00    1123.2
    14-Jul-19 13:46:00    1132.7
    04-Aug-19 13:57:00    966.11
    03-Sep-19 12:45:00    1053.8
    02-Oct-19 13:54:00    946.32
    08-Nov-19 11:50:00       777
    13-Dec-19 12:18:00     738.4
MinutelyMin = retime(TT1, 'minutely', 'min');
MonthlyMin = retime(TT1, 'monthly', 'min');
MonthDayMin = MonthlyToMinutely(MonthlyMin,MinutelyMin)
MonthDayMin = 12×2 table
        date_time          Wind  
    __________________    _______

    11-Jan-19 22:59:00    -15.904
    23-Feb-19 22:45:00    -13.189
    27-Mar-19 23:36:00    -12.413
    23-Apr-19 19:17:00    -18.232
    04-May-19 21:30:00    -18.813
    29-Jun-19 01:59:00     -16.68
    10-Jul-19 21:13:00    -18.426
    29-Aug-19 04:04:00     -7.952
    14-Sep-19 06:08:00     -9.697
    06-Oct-19 00:50:00    -19.589
    17-Nov-19 21:04:00     -17.65
    26-Dec-19 17:52:00     -18.62
MinutelyMax = retime(TT1, 'minutely', 'max');
MonthlyMax = retime(TT1, 'monthly', 'max');
MonthDayMax = MonthlyToMinutely(MonthlyMax,MinutelyMax)
MonthDayMax = 12×2 table
        date_time          Wind 
    __________________    ______

    28-Jan-19 12:48:00    783.79
    13-Feb-19 13:23:00    894.92
    29-Mar-19 12:24:00    1023.9
    11-Apr-19 13:17:00      1214
    30-May-19 13:29:00    1280.9
    29-Jun-19 14:46:00    1123.2
    14-Jul-19 13:46:00    1132.7
    04-Aug-19 13:57:00    966.11
    03-Sep-19 12:45:00    1053.8
    02-Oct-19 13:54:00    946.32
    08-Nov-19 11:50:00       777
    13-Dec-19 12:18:00     738.4
MinutelyMin = retime(TT1, 'minutely', 'min');
MonthlyMin = retime(TT1, 'monthly', 'min');
MonthDayMin = MonthlyToMinutely(MonthlyMin,MinutelyMin)
MonthDayMin = 12×2 table
        date_time          Wind  
    __________________    _______

    11-Jan-19 22:59:00    -15.904
    23-Feb-19 22:45:00    -13.189
    27-Mar-19 23:36:00    -12.413
    23-Apr-19 19:17:00    -18.232
    04-May-19 21:30:00    -18.813
    29-Jun-19 01:59:00     -16.68
    10-Jul-19 21:13:00    -18.426
    29-Aug-19 04:04:00     -7.952
    14-Sep-19 06:08:00     -9.697
    06-Oct-19 00:50:00    -19.589
    17-Nov-19 21:04:00     -17.65
    26-Dec-19 17:52:00     -18.62
function ExactTime = MonthlyToMinutely(MonthlyTT,MinutelyTT)
MinutelyVN = MinutelyTT.Properties.VariableNames;
MonthlyVN = MonthlyTT.Properties.VariableNames;
if ~strcmp(MinutelyVN{:}, MonthlyVN{:})
    ExactTime = timetable();
    fprintf('Variable names %s and %s in the argument timetables are not the same.',MonthlyVN{:},MinutelyVN{:})
    return
end
[yhn,mhn,dhn] = ymd(MinutelyTT.date_time);              % Year, Month, Day Of Daily Maxima
for k = 1:numel(MonthlyTT)
    [ym,mm,dm] = ymd(MonthlyTT.date_time(k));           % Year, Month, Day Of Monthily Maxima
    Lv = ismember([yhn,mhn], [ym,mm], 'rows');
    idx = MinutelyTT{:,1}(Lv) == MonthlyTT{:,1}(k);
    Mv = find(Lv);
    Dv = find(idx);
    HM = MinutelyTT(Mv(Dv(1)),:);
    MonthDayTT(k,:) = timetable2table(HM);
end
ExactTime = MonthDayTT;
end

I have no idea what the units are here, however it seems to work when I run it.

There may not be unique values in each daily data set for the maxima and minima. My code defaults to whatever retime does in those situations. In my ‘MonthlyToMinutely’ function, the ‘idx’ vector is a logical vector, and could return multiple results. I solve that problem by returning the first result (the ‘HM’ assignment in the loop) rather than all of them, because returning all of them would disrupt the table result. It allows for only one result per row. Returning all of them causes problems with the table format.

.

Star Strider am 9 Feb. 2023

Bearbeitet: Star Strider am 9 Feb. 2023

In MATLAB Online öffnen

It seems to me that would simply be this —

LD = load(websave('T','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1289405/T.mat'));
TT1 = LD.T
TT1 = 513077×1 timetable
date_timeWind________________________01-Jan-19 00:00:00    -5.624
    01-Jan-19 00:03:00    -5.624
    01-Jan-19 00:04:00    -5.818
    01-Jan-19 00:05:00    -5.818
    01-Jan-19 00:06:00    -6.012
    01-Jan-19 00:07:00    -6.206
    01-Jan-19 00:08:00    -6.788
    01-Jan-19 00:09:00    -5.818
    01-Jan-19 00:10:00     -5.43
    01-Jan-19 00:11:00    -5.818
    01-Jan-19 00:12:00    -6.012
    01-Jan-19 00:13:00     -5.43
    01-Jan-19 00:14:00    -6.012
    01-Jan-19 00:15:00    -5.236
    01-Jan-19 00:16:00    -5.818
    01-Jan-19 00:17:00    -6.206
% return
% LD = load(websave('dataset','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1255052/dataset.mat'));
% TT1 = LD.TT1
MinutelyMax = retime(TT1, 'minutely', 'max');
DailyMax = retime(TT1, 'daily', 'max');
DayMinuteMax = MonthlyToMinutely(DailyMax,MinutelyMax);
DayMinuteMax
DayMinuteMax = 365×2 table
date_timeWind________________________

    01-Jan-19 12:48:00     549.1
    02-Jan-19 10:56:00    495.95
    03-Jan-19 15:36:00    284.34
    04-Jan-19 13:11:00    667.41
    05-Jan-19 12:43:00    504.87
    06-Jan-19 14:11:00    534.16
    07-Jan-19 12:42:00    675.17
    01-Jan-19 12:52:00    542.11
    05-Jan-19 09:19:00    103.96
    10-Jan-19 12:26:00    702.32
    01-Jan-19 12:47:00     548.9
    01-Jan-19 11:00:00    350.87
    13-Jan-19 12:27:00    543.28
    06-Jan-19 10:59:00    417.79
    15-Jan-19 12:46:00    537.46
    15-Jan-19 13:21:00    529.51
MinutelyMin = retime(TT1, 'minutely', 'min');
DailyMin = retime(TT1, 'daily', 'min');
DayMinuteMin = MonthlyToMinutely(DailyMin,MinutelyMin);
DayMinuteMin
DayMinuteMin = 365×2 table
date_timeWind_________________________

    01-Jan-19 22:10:00    -11.637
    02-Jan-19 07:24:00    -12.413
    01-Jan-19 18:53:00    -10.667
    04-Jan-19 01:28:00    -12.801
    05-Jan-19 22:35:00    -12.995
    04-Jan-19 01:28:00    -12.801
    07-Jan-19 02:06:00    -13.383
    08-Jan-19 05:34:00     -14.74
    02-Jan-19 00:36:00    -11.831
    01-Jan-19 21:49:00    -10.861
    11-Jan-19 22:59:00    -15.904
    01-Jan-19 22:53:00    -11.443
    04-Jan-19 01:28:00    -12.801
    02-Jan-19 01:22:00    -12.219
    02-Jan-19 00:36:00    -11.831
    08-Jan-19 06:14:00    -13.577
% G = findgroups(day(AllMin.date_time),month(AllMin.date_time),hour(AllMin.date_time),minute(AllMin.date_time),AllMin{:,1});
% MinutelyMax = retime(TT1, 'minutely', 'max');
% DailyMax = retime(TT1, 'daily', 'max');
% DayMinujteMax = MonthlyToMinutely(DailyMax,MinutelyMax)
% 
% MinutelyMin = retime(TT1, 'minutely', 'min');
% DailyMin = retime(TT1, 'daily', 'min');
% DayMinuteMin = MonthlyToMinutely(DailyMin,MinutelyMin)
function [ExactTime,AllMatches] = MonthlyToMinutely(MonthlyTT,MinutelyTT)
MinutelyVN = MinutelyTT.Properties.VariableNames;
MonthlyVN = MonthlyTT.Properties.VariableNames;
if ~strcmp(MinutelyVN{:}, MonthlyVN{:})
    ExactTime = timetable();
    fprintf('Variable names %s and %s in the argument timetables are not the same.',MonthlyVN{:},MinutelyVN{:})
    return
end
[yhn,mhn,dhn] = ymd(MinutelyTT.date_time);              % Year, Month, Day Of Daily Maxima
for k = 1:numel(MonthlyTT)
    [ym,mm,dm] = ymd(MonthlyTT.date_time(k));           % Year, Month, Day Of Monthily Maxima
    Lv = ismember([yhn,mhn], [ym,mm], 'rows');
    idx = MinutelyTT{:,1}(Lv) == MonthlyTT{:,1}(k);
    Mv = find(Lv);
    Dv = find(idx);
    HM = MinutelyTT(Mv(Dv(1)),:);
    MonthDayTT(k,:) = timetable2table(HM);
end
ExactTime = MonthDayTT;
end

As I mentioned, my ‘MonthlyToMinutely’ function returns the first instance of the match that it finds, if there are more than one. This preserves the integrity of the ‘ExactTime’ output table.

I changed it to return multiple times for the same values as the second output, if the variable values are not unique. That works for the minimum values, however it’s returning anomalous results for the maximum values. I’ll work on it offlline and include it when I understand what the problem is.

EDIT — Forgot to run the code before I submitted it.

.

Ancalagon8 am 9 Feb. 2023

Ok @Star Strider, the code runs fine, the only thing is how to eliminate the appearance of multiple max values per day. Thanks you in advance!

Star Strider am 9 Feb. 2023

In MATLAB Online öffnen

Only one max value per day appears in the ‘ExactTime’ result, although there can be more than one detected. My ‘MonthlyToMinutely’ function returns the first one it finds.

The problem was the resolution in the two arrays. For the time being, I’m using two different functions. I’ll work on the function to add an option (extra arguments) to make it more flexible. It will likely take some time to get that working properly. In the interim, the differences are explained by the code in the different functions, specifically in the ‘Lv’ and ‘idx’ assignments.

Try this —

LD = load(websave('T','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1289405/T.mat'));
TT1 = LD.T
TT1 = 513077×1 timetable
date_timeWind________________________01-Jan-19 00:00:00    -5.624
    01-Jan-19 00:03:00    -5.624
    01-Jan-19 00:04:00    -5.818
    01-Jan-19 00:05:00    -5.818
    01-Jan-19 00:06:00    -6.012
    01-Jan-19 00:07:00    -6.206
    01-Jan-19 00:08:00    -6.788
    01-Jan-19 00:09:00    -5.818
    01-Jan-19 00:10:00     -5.43
    01-Jan-19 00:11:00    -5.818
    01-Jan-19 00:12:00    -6.012
    01-Jan-19 00:13:00     -5.43
    01-Jan-19 00:14:00    -6.012
    01-Jan-19 00:15:00    -5.236
    01-Jan-19 00:16:00    -5.818
    01-Jan-19 00:17:00    -6.206
MinutelyMax = retime(TT1, 'minutely', 'max');
DailyMax = retime(TT1, 'daily', 'max');
[DayMinuteMax,AllMax] = DailyToMinutely(DailyMax,MinutelyMax);
DayMinuteMax
DayMinuteMax = 365×2 table
date_timeWind________________________

    01-Jan-19 12:48:00     549.1
    02-Jan-19 10:56:00    495.95
    03-Jan-19 15:36:00    284.34
    04-Jan-19 13:11:00    667.41
    05-Jan-19 12:43:00    504.87
    06-Jan-19 14:11:00    534.16
    07-Jan-19 12:42:00    675.17
    08-Jan-19 12:42:00    542.11
    09-Jan-19 14:14:00    103.96
    10-Jan-19 12:26:00    702.32
    11-Jan-19 12:29:00     548.9
    12-Jan-19 13:48:00    350.87
    13-Jan-19 12:27:00    543.28
    14-Jan-19 11:07:00    417.79
    15-Jan-19 12:46:00    537.46
    16-Jan-19 13:00:00    529.51
AllMax = cat(1,AllMax{:})
AllMax = 397×1 timetable
date_timeWind________________________01-Jan-19 12:48:00     549.1
    02-Jan-19 10:56:00    495.95
    03-Jan-19 15:36:00    284.34
    04-Jan-19 13:11:00    667.41
    05-Jan-19 12:43:00    504.87
    06-Jan-19 14:11:00    534.16
    07-Jan-19 12:42:00    675.17
    08-Jan-19 12:42:00    542.11
    09-Jan-19 14:14:00    103.96
    10-Jan-19 12:26:00    702.32
    11-Jan-19 12:29:00     548.9
    11-Jan-19 12:30:00     548.9
    12-Jan-19 13:48:00    350.87
    13-Jan-19 12:27:00    543.28
    14-Jan-19 11:07:00    417.79
    15-Jan-19 12:46:00    537.46
MinutelyMin = retime(TT1, 'minutely', 'min');
DailyMin = retime(TT1, 'daily', 'min');
[DayMinuteMin,AllMin] = DailyToMinutely(DailyMin,MinutelyMin);
DayMinuteMin
DayMinuteMin = 365×2 table
date_timeWind_________________________

    01-Jan-19 22:10:00    -11.637
    02-Jan-19 07:24:00    -12.413
    03-Jan-19 23:47:00    -10.667
    04-Jan-19 01:28:00    -12.801
    05-Jan-19 22:35:00    -12.995
    06-Jan-19 00:03:00    -12.801
    07-Jan-19 02:06:00    -13.383
    08-Jan-19 05:34:00     -14.74
    09-Jan-19 03:50:00    -11.831
    10-Jan-19 17:52:00    -10.861
    11-Jan-19 22:59:00    -15.904
    12-Jan-19 22:23:00    -11.443
    13-Jan-19 04:33:00    -12.801
    14-Jan-19 02:24:00    -12.219
    15-Jan-19 23:30:00    -11.831
    16-Jan-19 06:17:00    -13.577
AllMin = cat(1,AllMin{:})
AllMin = 570×1 timetable
date_timeWind_________________________01-Jan-19 22:10:00    -11.637
    01-Jan-19 22:11:00    -11.637
    02-Jan-19 07:24:00    -12.413
    03-Jan-19 23:47:00    -10.667
    04-Jan-19 01:28:00    -12.801
    05-Jan-19 22:35:00    -12.995
    05-Jan-19 23:20:00    -12.995
    06-Jan-19 00:03:00    -12.801
    06-Jan-19 20:50:00    -12.801
    06-Jan-19 20:56:00    -12.801
    06-Jan-19 23:02:00    -12.801
    07-Jan-19 02:06:00    -13.383
    07-Jan-19 02:29:00    -13.383
    08-Jan-19 05:34:00     -14.74
    09-Jan-19 03:50:00    -11.831
    09-Jan-19 03:51:00    -11.831
function [ExactTime,AllMatches] = DailyToMinutely(MonthlyTT,MinutelyTT)
MinutelyVN = MinutelyTT.Properties.VariableNames;
MonthlyVN = MonthlyTT.Properties.VariableNames;
if ~strcmp(MinutelyVN{:}, MonthlyVN{:})
    ExactTime = timetable();
    fprintf('Variable names %s and %s in the argument timetables are not the same.',MonthlyVN{:},MinutelyVN{:})
    return
end
[yhn,mhn,dhn] = ymd(MinutelyTT.date_time);              % Year, Month, Day Of Daily Maxima
for k = 1:numel(MonthlyTT)
    [ym,mm,dm] = ymd(MonthlyTT.date_time(k));           % Year, Month, Day Of Monthily Maxima
%     YrMoDa = [ym mm dm]
    Lv = ismember([yhn,mhn,dhn], [ym,mm,dm], 'rows');
    idx = MinutelyTT{:,1}(Lv) == MonthlyTT{:,1}(k);
%     LvSize = nnz(Lv)
    Mv = find(Lv);
    Dv = find(idx);
    HM = MinutelyTT(Mv(Dv(1)),:);
    AllHM{k,:} = MinutelyTT(Mv(Dv),:);
    MonthDayTT(k,:) = timetable2table(HM);
end
ExactTime = MonthDayTT;
AllMatches = AllHM;
end

.

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Calculate the maximum and minimum values and what day these values occured

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