Group wind data in clusters based on direction
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I have an annual table with wind direction values and I want to group them per month in 16 sectors based on the degrees.
Is it possible to do it automatically either than manually?
5 个评论
Adam Danz
2023-1-8
Grouping a timetable by month is not difficult.
Grouping by a degree variable is also not difficult.
That's about as specific as I can get with the limited info. Also, it's not clear how you want to group by two different values (month and degrees, what are sectors?). Examples are worth 1000 words 🙂
Walter Roberson
2023-1-8
Grouping wind direction by strict sector is often misleading because the angle for wind just barely east of north is so different than the angle for wind just barely west of north. Calculating averages using such numbers is especially messed up unless you are careful.
Adam Danz
2023-1-9
编辑:Adam Danz
2023-1-9
Grouping angular values
This demo works with degrees but it's the same process for radians. It assumes angular data are between 0 and 360. If that's not the case in your data, wrap your data to 360 (or to 2pi).
Given the number of bins nBins this computes equispaced bin edges, with a bin centered at 0 deg, and then computes the bin number for each angular data point. The bin centered at 0 is delt with separately.
Grouping isn't too difficult. However, depending on what you plan to do with these group values, you could run into trouble that @Walter Roberson explained. Phase wrapping is a potential solution to this problem (I'm looking at you bin #1).
theta = [rand(1,30)*360]; % vector of angular data [0,360] deg
nBins = 12; % select number of bins
% Compute edges
w = 360/nBins;
edges = w/2:w:(360-w/2);
% Bin data
bin = discretize(theta, edges)+1;
bin(theta>=edges(end) | theta<edges(1)) = 1; % bin at 0
% Plot results, show theta values, bin edges, and bin ID
polaraxes('ThetaZeroLocation','top',...
'RTickLabel','', ...
'ThetaDir','ClockWise')
hold on
polarplot(theta*pi/180, 1, 'ro')
polarplot([1;1].*edges*pi/180, [0;1], 'k-')
text(theta*pi/180, ones(size(theta))-.1, string(bin), ...
'HorizontalAlignment','Center', 'VerticalAlignment', 'middle')
grid off
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1256812/image.png)
Walter Roberson
2023-1-9
See also the discussion at https://www.mathworks.com/matlabcentral/answers/128381-how-to-calculate-mean-wind-direction
采纳的回答
Star Strider
2023-1-8
编辑:Star Strider
2023-1-8
WindDir = rand(100,1)*360;
edgev = linspace(0, 360, 9);
[N,Edges,Octant] = histcounts(WindDir, edgev);
WindOctants = table(WindDir,Octant)
WindOctants = 100×2 table
WindDir Octant
_______ ______
123.39 3
272.97 7
352.43 8
10.679 1
199.56 5
205.31 5
258.28 6
329.39 8
146.07 4
171.63 4
333.69 8
328.55 8
85.531 2
331.01 8
92.321 3
232.95 6
The first output are the number of counts in each octant (bonus information), and the third is the respective octant.
EDIT — (8 Jan 2023 at 16:30)
Added table.
.
20 个评论
Ancalagon8
2023-1-9
@Star Strider thank you for the answer. I think your approach is more close to what I need. My goal is to extract a table with the frequency distribution of wind direction in 16 sectors, e.g:
0 deg-22.5 deg=x counts,
22.5 deg-45 deg=y counts,
45 deg-62.5 deg=z counts etc.
Star Strider
2023-1-9
My pleasure!
Perhaps something like this —
WindDir = rand(100,1)*360;
edgev = linspace(0, 360, 17);
edgem = [edgev(1:end-1); edgev(2:end)].';
ctrs = mean(diff(edgev))/2 + edgev(1:end-1);
[N,Edges,Decihexctant] = histcounts(WindDir, edgev);
WindDecihexctants = table(WindDir,Decihexctant)
WindDecihexctants = 100×2 table
WindDir Decihexctant
_______ ____________
252.73 12
103.54 5
131.08 6
82.584 4
313.13 14
138.65 7
213.2 10
271.18 13
193.12 9
350.1 16
277.9 13
14.329 1
275.39 13
237.54 11
81.801 4
324.91 15
WindDirCounts = table(edgem(:,1),edgem(:,2),N(:), 'VariableNames',{'Start','End','Count'})
WindDirCounts = 16×3 table
Start End Count
_____ _____ _____
0 22.5 9
22.5 45 7
45 67.5 5
67.5 90 10
90 112.5 4
112.5 135 6
135 157.5 9
157.5 180 1
180 202.5 8
202.5 225 5
225 247.5 5
247.5 270 6
270 292.5 8
292.5 315 4
315 337.5 6
337.5 360 7
figure
bar(ctrs, N)
xlabel('Direction (°)')
ylabel('Counts')
xticks(ctrs)
axis('padded')
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1257267/image.png)
That only required a couple tweaks to my previous code.
.
Ancalagon8
2023-1-9
WindDir = rand(100,1)*360;
i overwrote WindDir with my anual timetable (TT). One last question is in case I want to calculate the WindDirCounts not for the year but for each month, I have to tweak the above code into a loop?
Star Strider
2023-1-9
Thank you!
Possibly something like this —
DT = datetime('01-Jan-2022') + caldays(0:365).';
WindDir = rand(size(DT))*360;
TT = timetable(DT,WindDir)
TT = 366×1 timetable
DT WindDir
___________ _______
01-Jan-2022 209.94
02-Jan-2022 347.86
03-Jan-2022 61.247
04-Jan-2022 101.24
05-Jan-2022 116.63
06-Jan-2022 100.6
07-Jan-2022 210.46
08-Jan-2022 134.27
09-Jan-2022 238.92
10-Jan-2022 315.72
11-Jan-2022 27.034
12-Jan-2022 306.89
13-Jan-2022 354.17
14-Jan-2022 291.4
15-Jan-2022 2.3855
16-Jan-2022 233.24
MM = month(TT.DT);
T = timetable2table(TT);
edgev = linspace(0, 360, 17);
edgem = [edgev(1:end-1); edgev(2:end)].';
ctrs = mean(diff(edgev))/2 + edgev(1:end-1);
[N,Edges,Decihexctant] = histcounts(WindDir, edgev);
WindDirCounts = table(edgem(:,1),edgem(:,2),'VariableNames',{'Start','End'});
for k = 1:12
Month = T(MM==k,:);
[N,Edges,Decihexctant] = histcounts(T.WindDir(MM==k,:), edgev);
Nc{k} = N;
Dch{k+2} = Decihexctant;
WindDirCounts{:,k+2} = N(:);
MMM{k} = month(Month{1,1},'shortname');
end
WindDirCounts.Properties.VariableNames = {'Start','End','Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'}
WindDirCounts = 16×14 table
Start End Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
_____ _____ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___
0 22.5 1 3 1 2 0 1 3 3 1 2 4 3
22.5 45 1 1 1 2 2 0 3 3 6 3 3 1
45 67.5 3 0 3 1 2 1 2 1 2 0 4 2
67.5 90 0 4 1 1 3 4 3 2 2 0 0 2
90 112.5 3 1 1 1 1 1 2 2 2 6 4 3
112.5 135 4 2 2 2 2 2 1 2 1 0 0 0
135 157.5 0 2 1 1 5 0 4 2 2 5 2 3
157.5 180 1 2 4 4 1 3 0 2 2 1 1 0
180 202.5 0 2 2 4 3 1 0 2 0 2 1 1
202.5 225 4 1 3 2 2 1 1 3 2 2 0 1
225 247.5 3 2 2 1 2 4 2 1 3 1 1 2
247.5 270 1 1 1 1 2 2 2 1 3 1 3 5
270 292.5 4 3 3 3 2 4 3 2 1 2 2 1
292.5 315 2 1 3 2 1 2 3 2 1 1 2 5
315 337.5 2 2 1 3 1 3 1 2 2 1 0 1
337.5 360 3 1 2 0 2 1 1 1 0 4 3 1
I thought about using splitapply or groupsummary for this, however it appears to be too complicated for those approaches.
My initial effort was to use the ‘MMM’ cell array to define the months for ‘WindDirCounts.Properties.VariableNames’ however that wouldn’t work and I finally gave up on that (accounting for the time delay) and just typed everything out. (That should be easier!)
.
Ancalagon8
2023-1-9
Yes I tried also using splitapply with no result. So everything worked, once again @Star Strider your answer was more than helpful and detailed!
Star Strider
2023-1-10
There are two synchronize functions that may do what you want. I linked to the one here that looks most promising. (I never used either version of this function, so I have no experience with them.)
Star Strider
2023-2-7
I do not understand.
The current code uses direction, not velocity. However if you want to use velocity instead of direction, make the appropriate substitutions for velocity instead of quadrant. (It would likely not be possible to combine both in ome table.)
Star Strider
2023-2-7
Possibly something like this —
DT = datetime('01-Jan-2022') + caldays(0:365).';
WindVel = lognrnd(log(5),log(3),size(DT));
TT = timetable(DT,WindVel)
TT = 366×1 timetable
DT WindVel
___________ _______
01-Jan-2022 16.075
02-Jan-2022 2.1799
03-Jan-2022 45.175
04-Jan-2022 21.834
05-Jan-2022 1.3866
06-Jan-2022 55.71
07-Jan-2022 9.0376
08-Jan-2022 8.2512
09-Jan-2022 20.02
10-Jan-2022 19.658
11-Jan-2022 3.333
12-Jan-2022 34.172
13-Jan-2022 15.938
14-Jan-2022 2.7594
15-Jan-2022 2.9275
16-Jan-2022 5.6391
MM = month(TT.DT);
T = timetable2table(TT);
edgev = linspace(0, 100, 101);
edgem = [edgev(1:end-1); edgev(2:end)].';
ctrs = mean(diff(edgev))/2 + edgev(1:end-1);
[N,Edges,Decihexctant] = histcounts(WindVel, edgev);
figure
bar(ctrs, N)
grid
xlabel('Velocity')
ylabel('Counts')
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1287210/image.png)
WindVelCounts = table(edgem(:,1),edgem(:,2));
for k = 1:12
Month = T(MM==k,:);
[N,Edges,Decihexctant] = histcounts(T.WindVel(MM==k,:), edgev);
Nc{k} = N;
Dch{k+2} = Decihexctant;
WindVelCounts{:,k+2} = N(:);
MMM{k} = month(Month{1,1},'shortname');
end
MMMv = [MMM{:}];
WindVelCounts.Properties.VariableNames = {'Start','End', MMMv{:}}
WindVelCounts = 100×14 table
Start End Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
_____ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___
0 1 0 0 2 5 4 0 1 2 4 1 0 2
1 2 4 4 2 3 6 5 5 4 1 4 8 4
2 3 5 3 4 0 1 4 3 1 4 3 6 3
3 4 4 6 4 3 2 7 5 1 3 4 1 2
4 5 4 2 5 2 1 1 3 5 4 3 4 2
5 6 1 2 0 3 2 2 3 3 2 4 1 1
6 7 1 1 2 3 2 1 1 1 1 3 0 3
7 8 0 1 2 0 2 3 3 2 1 1 1 1
8 9 1 0 1 2 1 3 1 0 3 1 0 1
9 10 1 2 3 1 1 0 0 2 0 0 2 1
10 11 0 1 1 0 1 0 1 3 0 1 1 1
11 12 0 0 3 0 2 0 0 0 0 1 2 2
12 13 0 1 0 1 0 0 0 0 1 1 0 1
13 14 0 1 0 4 1 0 0 2 1 0 0 0
14 15 0 0 0 0 0 1 0 2 1 0 1 0
15 16 2 1 0 1 0 1 1 0 0 1 1 1
Change the second and third parameters in ‘edgeV’ to reflect the actual data, if necessary. For 1 m/s increments, the third parameter must be 1 greater than the second parameter, and both would be integers (the third must be an integer), for best results. (This uses ‘MMM’ to define the variable names in the table.)
.
Ancalagon8
2023-2-8
编辑:Ancalagon8
2023-2-8
Thanks for the detailed answer! I run the code, this part I think is not necessary for me right?
DT = datetime('01-Jan-2022') + caldays(0:365).';
WindVel = lognrnd(log(5),log(3),size(DT));
TT = timetable(DT,WindVel)
I replaced T with my timetable(timestamp in first column and WindVelocity in the second one). I wonder how to proceed because
WindVel = lognrnd(log(5),log(3),size(DT));
appears also later in code. Also I need to set xlim and WindVelCounts to 40 m/s , instead of 100.
Thank you in advance!
EDIT
uploaded T.mat
Star Strider
2023-2-8
编辑:Star Strider
2023-2-8
As always, my pleasure!
I create the data with those lines. I do not remember any data files being posted with wind velocity (or direction), and I need data to test my code. Use the actual data instead of my synthetic data. (The only actual data I have seen thus far as been what I assume to be air temperature.)
If you post the data (with wind velocity, wind direction, temperature, and anything else necessary), I will update my code to import the files and process those data.
EDIT — (8 Feb 2023 at )
LD = load(websave('T','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1289030/T.mat'))
LD = struct with fields:
T: [513077×1 timetable]
% DT = datetime('01-Jan-2022') + caldays(0:365).';
% WindVel = lognrnd(log(5),log(3),size(DT));
TT = LD.T
TT = 513077×1 timetable
date_time Vel_avg
__________________ _______
01-Jan-19 00:00:00 1.337
01-Jan-19 00:03:00 1.609
01-Jan-19 00:04:00 1.389
01-Jan-19 00:05:00 1.466
01-Jan-19 00:06:00 2.345
01-Jan-19 00:07:00 2.074
01-Jan-19 00:08:00 1.505
01-Jan-19 00:09:00 1.253
01-Jan-19 00:10:00 1.15
01-Jan-19 00:11:00 1.958
01-Jan-19 00:12:00 2.339
01-Jan-19 00:13:00 1.641
01-Jan-19 00:14:00 1.557
01-Jan-19 00:15:00 1.053
01-Jan-19 00:16:00 1.486
01-Jan-19 00:17:00 2.436
% return
MM = month(TT.date_time);
T = timetable2table(TT);
Vmax = ceil(max(TT.Vel_avg)) % Maximum Velocity In File
Vmax = 21
edgev = linspace(0, Vmax, Vmax+1); % Edge Vector
edgem = [edgev(1:end-1); edgev(2:end)].'; % Bin Limits (For Output Table)
ctrs = mean(diff(edgev))/2 + edgev(1:end-1); % Bin Centers
[N,Edges,mps] = histcounts(TT.Vel_avg, edgev); % Call 'histcounts'
figure
bar(ctrs, N)
grid
xlabel('Velocity')
ylabel('Counts')
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1289060/image.png)
WindVelCounts = table(edgem(:,1),edgem(:,2)); % Initialise Table
for k = 1:12
Month = T(MM==k,:);
[N,Edges,mps] = histcounts(T.Vel_avg(MM==k,:), edgev); % Call 'histcounts¹
Nc{k} = N;
Dch{k+2} = mps;
WindVelCounts{:,k+2} = N(:);
MMM{k} = month(Month{1,1},'shortname');
end
MMMv = [MMM{:}];
WindVelCounts.Properties.VariableNames = {'Start','End', MMMv{:}}
WindVelCounts = 21×14 table
Start End Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
_____ ___ _____ ____ _____ _____ _____ ____ ____ _____ _____ _____ _____ _____
0 1 7795 5600 7057 6124 6305 7404 7028 7613 7985 11406 6710 8092
1 2 10956 8951 14743 11734 11255 9244 8714 10383 12751 15673 13858 11413
2 3 6025 4791 5595 6726 6466 4887 6072 4637 5098 5946 7968 5106
3 4 4810 3813 4157 5829 5610 4540 5179 3997 3517 3420 5417 3886
4 5 3538 3597 3318 4266 5170 4518 4086 3874 3756 3175 3212 2486
5 6 2797 2717 2628 2841 3850 3537 3915 3844 3360 2199 1838 1675
6 7 2193 2305 2013 1998 2550 2837 3858 3938 2932 1038 1002 1527
7 8 1645 1942 1538 1558 1641 2534 3239 3269 1953 611 372 1657
8 9 1171 1355 1066 1016 666 1538 1474 2109 1027 334 169 1549
9 10 787 1040 779 617 494 652 342 529 269 205 79 1248
10 11 609 1066 664 278 350 152 65 39 33 92 27 762
11 12 359 957 506 113 145 27 11 1 7 58 7 427
12 13 194 780 249 14 38 3 5 0 0 15 7 287
13 14 42 461 98 0 2 0 0 0 0 1 2 154
14 15 0 253 31 0 0 0 0 0 0 0 0 77
15 16 0 177 7 0 0 0 0 0 0 0 0 31
figure
TL = tiledlayout(4,3);
for k = 1:12
nexttile
bar(ctrs,WindVelCounts{:,k+2})
grid
ylim([0 1.8E+4])
title(MMM{k})
end
title(TL,year(TT.date_time(1,1)))
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1289065/image.png)
.
Ancalagon8
2023-2-8
Works perfect, the only thing that I changed was:
Vmax = 40
instead of
Vmax = ceil(max(TT.Vel_avg))
thank you!
Ancalagon8
2023-2-23
编辑:Ancalagon8
2023-2-23
- Is it possible to transpose WindVelCounts? I am trying to merge Start and End, in order to have the twelve months vertically and then something like (0-1],(1-2]..(59-60], similar to Frequencies from our previous thread: https://www.mathworks.com/matlabcentral/answers/1896925-calculate-number-appearance-within-a-range
Star Strider
2023-2-23
I thought I could do this with one of the table functions, however extracting and transposing proved to be easiest —
LD = load(websave('T','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1289030/T.mat'))
LD = struct with fields:
T: [513077×1 timetable]
% DT = datetime('01-Jan-2022') + caldays(0:365).';
% WindVel = lognrnd(log(5),log(3),size(DT));
TT = LD.T
TT = 513077×1 timetable
date_time Vel_avg
__________________ _______
01-Jan-19 00:00:00 1.337
01-Jan-19 00:03:00 1.609
01-Jan-19 00:04:00 1.389
01-Jan-19 00:05:00 1.466
01-Jan-19 00:06:00 2.345
01-Jan-19 00:07:00 2.074
01-Jan-19 00:08:00 1.505
01-Jan-19 00:09:00 1.253
01-Jan-19 00:10:00 1.15
01-Jan-19 00:11:00 1.958
01-Jan-19 00:12:00 2.339
01-Jan-19 00:13:00 1.641
01-Jan-19 00:14:00 1.557
01-Jan-19 00:15:00 1.053
01-Jan-19 00:16:00 1.486
01-Jan-19 00:17:00 2.436
% return
MM = month(TT.date_time);
T = timetable2table(TT);
Vmax = ceil(max(TT.Vel_avg)) % Maximum Velocity In File
Vmax = 21
edgev = linspace(0, Vmax, Vmax+1); % Edge Vector
edgem = [edgev(1:end-1); edgev(2:end)].'; % Bin Limits (For Output Table)
ctrs = mean(diff(edgev))/2 + edgev(1:end-1); % Bin Centers
[N,Edges,mps] = histcounts(TT.Vel_avg, edgev); % Call 'histcounts'
figure
bar(ctrs, N)
grid
xlabel('Velocity')
ylabel('Counts')
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1304610/image.png)
WindVelCounts = table(edgem(:,1),edgem(:,2)); % Initialise Table
for k = 1:12
Month = T(MM==k,:);
[N,Edges,mps] = histcounts(T.Vel_avg(MM==k,:), edgev); % Call 'histcounts¹
Nc{k} = N;
Dch{k+2} = mps;
WindVelCounts{:,k+2} = N(:);
MMM{k} = month(Month{1,1},'shortname');
end
MMMv = [MMM{:}];
WindVelCounts.Properties.VariableNames = {'Start','End', MMMv{:}}
WindVelCounts = 21×14 table
Start End Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
_____ ___ _____ ____ _____ _____ _____ ____ ____ _____ _____ _____ _____ _____
0 1 7795 5600 7057 6124 6305 7404 7028 7613 7985 11406 6710 8092
1 2 10956 8951 14743 11734 11255 9244 8714 10383 12751 15673 13858 11413
2 3 6025 4791 5595 6726 6466 4887 6072 4637 5098 5946 7968 5106
3 4 4810 3813 4157 5829 5610 4540 5179 3997 3517 3420 5417 3886
4 5 3538 3597 3318 4266 5170 4518 4086 3874 3756 3175 3212 2486
5 6 2797 2717 2628 2841 3850 3537 3915 3844 3360 2199 1838 1675
6 7 2193 2305 2013 1998 2550 2837 3858 3938 2932 1038 1002 1527
7 8 1645 1942 1538 1558 1641 2534 3239 3269 1953 611 372 1657
8 9 1171 1355 1066 1016 666 1538 1474 2109 1027 334 169 1549
9 10 787 1040 779 617 494 652 342 529 269 205 79 1248
10 11 609 1066 664 278 350 152 65 39 33 92 27 762
11 12 359 957 506 113 145 27 11 1 7 58 7 427
12 13 194 780 249 14 38 3 5 0 0 15 7 287
13 14 42 461 98 0 2 0 0 0 0 1 2 154
14 15 0 253 31 0 0 0 0 0 0 0 0 77
15 16 0 177 7 0 0 0 0 0 0 0 0 31
VN = WindVelCounts.Properties.VariableNames;
WindVelCountsTransposed = array2table(table2array(WindVelCounts(:,3:end)).', 'RowNames',VN(3:end));
WindVelCountsTransposed.Properties.VariableNames = compose('[%d-%d]',edgem)
WindVelCountsTransposed = 12×21 table
[0-1] [1-2] [2-3] [3-4] [4-5] [5-6] [6-7] [7-8] [8-9] [9-10] [10-11] [11-12] [12-13] [13-14] [14-15] [15-16] [16-17] [17-18] [18-19] [19-20] [20-21]
_____ _____ _____ _____ _____ _____ _____ _____ _____ ______ _______ _______ _______ _______ _______ _______ _______ _______ _______ _______ _______
Jan 7795 10956 6025 4810 3538 2797 2193 1645 1171 787 609 359 194 42 0 0 0 0 0 0 0
Feb 5600 8951 4791 3813 3597 2717 2305 1942 1355 1040 1066 957 780 461 253 177 108 68 33 12 1
Mar 7057 14743 5595 4157 3318 2628 2013 1538 1066 779 664 506 249 98 31 7 0 0 0 0 0
Apr 6124 11734 6726 5829 4266 2841 1998 1558 1016 617 278 113 14 0 0 0 0 0 0 0 0
May 6305 11255 6466 5610 5170 3850 2550 1641 666 494 350 145 38 2 0 0 0 0 0 0 0
Jun 7404 9244 4887 4540 4518 3537 2837 2534 1538 652 152 27 3 0 0 0 0 0 0 0 0
Jul 7028 8714 6072 5179 4086 3915 3858 3239 1474 342 65 11 5 0 0 0 0 0 0 0 0
Aug 7613 10383 4637 3997 3874 3844 3938 3269 2109 529 39 1 0 0 0 0 0 0 0 0 0
Sep 7985 12751 5098 3517 3756 3360 2932 1953 1027 269 33 7 0 0 0 0 0 0 0 0 0
Oct 11406 15673 5946 3420 3175 2199 1038 611 334 205 92 58 15 1 0 0 0 0 0 0 0
Nov 6710 13858 7968 5417 3212 1838 1002 372 169 79 27 7 7 2 0 0 1 1 1 0 0
Dec 8092 11413 5106 3886 2486 1675 1527 1657 1549 1248 762 427 287 154 77 31 6 3 3 1 0
% figure
% TL = tiledlayout(4,3);
% for k = 1:12
% nexttile
% bar(ctrs,WindVelCounts{:,k+2})
% grid
% ylim([0 1.8E+4])
% title(MMM{k})
% end
% title(TL,year(TT.date_time(1,1)))
All the original information is still there in case you need it. Plotting it using bar3 might be another option, in addition to tiledlayout.
.
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