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Borrar filtros

Conditionally select rows and add to new table

6 visualizaciones (últimos 30 días)
Jonathan Cheong
Jonathan Cheong el 25 de Nov. de 2020
Respondida: Mathieu NOE el 30 de Nov. de 2020
For example, I have a 2000 x 3 table: Column_1: Datetime Column_2: Rain Column_3: Soil Moisture
The actual table has more variables but I plan to get to it once I know how to undergo the coding.
The idea is to append the rows to a new table if they meet these conditions:
1) While rain > 3 and ends when rain < 2 for 2 subsequent days
2) The 1st condition cannot be less than 4 days
I've been trying to code this out but have gone nowhere:
for i = 1:height(ddtable)
ii = 0;
finaldd(:,:) = [];
while ddtable.RAIN > 3
ii = ii + 1;
if ii < 4
break
elseif ii > 4
finaldd(ddtable);
end
end
end
  5 comentarios
Jonathan Cheong
Jonathan Cheong el 30 de Nov. de 2020
Editada: Jonathan Cheong el 30 de Nov. de 2020
Wow, this is superb work. I've taken a look at it and understand most parts, thank you very much!
I've done a few changes to it because my goal is: Plot datetime against SM value with the index found.
Would you like to submit your comment as an answer so that I can mark it as accepted?
Jonathan Cheong
Jonathan Cheong el 30 de Nov. de 2020
takerow = ddtable2(time_index,:);
figure(2)
y2 = takerow.SM_12h;
x = linspace(datetime('2011-07-14 00:00:00'),datetime('2020-01-01 00:00:00'),length (y2));
plot(x,y2)
This is the new code I've done for the plot. Once again, thanks!

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Mathieu NOE
Mathieu NOE el 30 de Nov. de 2020
hello
so official answer below (modified original code)
good luck for the future !
load('ddtable2.mat'); % ddtable2
date_ymd = ddtable2.DT;
date_days = datenum(date_ymd);
rain = ddtable2.RAIN;
SM = ddtable2.SM_12h;
samples = length(rain);
% first loop
k = 0;
q = 0;
% let's analyse the data by buffer data slection and analysis
for ci = 1:length(rain)-3
% cond1 : % 4 days and all with rain > 3
buffer1 = rain(ci:ci+3); % 4 days buffer
cond1 = all(buffer1>3); % will be 1 if buffer is contiguous and all values are > 3
if cond1 == 1
k = k+1;
ind_start1(k) = ci;
ind_stop1(k) = ci+3;
end
% cond2 : % 2 days contiguous with rain < 2
buffer2 = rain(ci:ci+1); % 2 days buffer
cond2 = all(buffer2<2); % contiguous and all < 2
if cond2 == 1
q = q+1;
ind_start2(q) = ci;
ind_stop2(q) = ci+1;
end
end
% now let's check when we have a ind_start2 just after one value of
m = 0;
for ck = 1:length(ind_start1)
ind = find(ind_start2>ind_start1(ck));
if ~isempty(ind)
m = m+1;
ind_start22(m) = ind_start2(ind(1));
ind_start11(m) = ind_start1(ck);
end
end
% keep only unique values
[c2,ia2,ic2] = unique(ind_start22);
ind_start222 = ind_start22(ia2);
ind_start111 = ind_start11(ia2);
% finally , stack (concatenate) data that fullfills the condition
time_index = [];
data_rain = [];
for cc = 1:length(ia2)
time_index = [time_index (ind_start111(cc):ind_start222(cc))]; % concatenation
data_rain = [data_rain; rain(ind_start111(cc):ind_start222(cc))]; % concatenation
end
figure(1),plot((1:samples),rain,'b',time_index,data_rain,'-*r');
legend('all data','selected data');

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