I don't see a file attached.
I have a problem in the annexed excel file there are two tables, first table give the graph representing geological layers I need to get the second table with Matlab Code
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I have a problem in the annexed excel file there are two tables, first table give the graph representing geological layers I need to get the second table with suitable Matlab code (I have R2014b version).
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답변 (3개)
Star Strider
2023년 3월 6일
편집: Star Strider
2023년 3월 6일
One approach —
C1 = readcell('https://www.mathworks.com/matlabcentral/answers/uploaded_files/1315950/Salt%20Dome%20Interpretation.xlsx')
nidx = find(cell2mat(cellfun(@ismissing,C1(5,:), 'Unif',0)));
Partition1 = cell2table(C1(2:end,1:nidx(1)-1), 'VariableNames',C1(1,1:nidx(1)-1))
Partition2 = cell2table(C1(2:end,nidx(2)+1:size(C1,2)), 'VariableNames',C1(1,1:nidx(1)-1))
M1 = readmatrix('https://www.mathworks.com/matlabcentral/answers/uploaded_files/1315950/Salt%20Dome%20Interpretation.xlsx')
file = websave('Salt%20Dome%20Interpretation','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1315950/Salt%20Dome%20Interpretation.xlsx')
[Data,Text] = xlsread(file);
Data
Text = Text(1,:)
nidx = find(ismissing(Text))
Data1 = Data(:,1:nidx(1)-1)
Data2 = Data(:,nidx(2)+1:numel(Text))
% Matrix1 = table2array(Partition1)
% writematrix()
.
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Star Strider
2023년 3월 6일
It is straightforward to separate these two matrices using matrix indexing, as I have demonstrated, using ismissing to determine where one sub-matrix ends and the other begins.
My code should be robust to similar Excel files that have the same general structure.
Star Strider
2023년 3월 7일
@Moustafa Abedel Fattah — With respect to your edited Comment, I already provided both tables. I call them ‘Data1’ and ‘Data2’ however you cal call them whatever you want. My code should also work in R2014b, since it uses xlsread for compatibility.
Sulaymon Eshkabilov
2023년 3월 6일
Here is the solution. readmatrix() is option 1 and xlsread() is option 2:
D = readmatrix('Salt Dome Interpretation.xlsx');
% D = xlsread('Salt Dome Interpretation.xlsx');
D(1:2,:) = []; % NaNs removed
D(:,11:12) = []; % NaNs removed
%%
D1 = D(:,3:10);
D2 = D(:, 13:20);
figure
plot(D(:,1), D1)
grid on
set(gca, 'YDir','reverse')
legend('z1', 'z2', 'z3', 'z4', 'z5', 'z6', 'z7')
figure
plot(D(:,11), D2)
grid on
set(gca, 'YDir','reverse')
legend('z1', 'z2', 'z3', 'z4', 'z5', 'z6', 'z7')
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Sulaymon Eshkabilov
2023년 3월 6일
If understood your explanations, here is how to collect the data from table to w.r.t xc range values and constant values of z1 .. to zb by computing their difference:
D = readmatrix('Salt Dome Interpretation.xlsx');
D(1:2,:) = []; % NaNs removed
D(:,11:12) = []; % NaNs removed
%
D1 = D(:,1:10);
D1(200:end,:)=[]; % NaNs removed
D2 = D(:, 11:20);
D2(200:end,:)=[]; % NaNs removed
figure(1)
plot(D1(:,1), D1(:,3:10))
grid on
set(gca, 'YDir','reverse')
legend({'z_1', 'z_2', 'z_3', 'z_4', 'z_5', 'z_6', 'z_7', 'z_b'}, 'Location','NE', 'NumColumns',2)
ylabel('z_1, z_2, ... z_b')
xlabel('x_c')
xc = D2(:,1);
INDEX =xc>=228.47935834853 & xc<= 320.84335427666;
DD2 = D2(INDEX,:);
% Find constant values of z1 ... zb using diff()
Dz1 = diff(DD2(:,3)); ind_z1 = Dz1==0;
Dz2 = diff(DD2(:,4)); ind_z2 = Dz2==0;
Dz3 = diff(DD2(:,5)); ind_z3 = Dz3==0;
Dz4 = diff(DD2(:,6)); ind_z4 = Dz4==0;
Dz5 = diff(DD2(:,7)); ind_z5 = Dz5==0;
Dz6 = diff(DD2(:,8)); ind_z6 = Dz6==0;
Dz7 = diff(DD2(:,9)); ind_z7 = Dz7==0;
Dzb = diff(DD2(:,10)); ind_zb = Dzb==0;
% Take out those values
z1=DD2(ind_z1,3);
z2=DD2(ind_z2,4);
z3=DD2(ind_z3,5);
z4=DD2(ind_z4,6);
z5=DD2(ind_z5,7);
z6=DD2(ind_z6,8);
z7=DD2(ind_z7,9);
zb=DD2(ind_zb,10);
% Take out the corresponding xc values for plateaued values of z1 to zb
xc1 = DD2(ind_z1,1);
xc2 = DD2(ind_z2,1);
xc3 = DD2(ind_z3,1);
xc4 = DD2(ind_z4,1);
xc5 = DD2(ind_z5,1);
xc6 = DD2(ind_z6,1);
xc7 = DD2(ind_z7,1);
xcb = DD2(ind_zb,1);
figure(2)
plot(xc1,z1, 'r*-'),
hold on
plot(xc2,z2, 'bd-')
plot(xc3,z3, 'gh--')
plot(xc4,z4, 'mp-.')
plot(xc5,z5, 'kd-')
plot(xc6,z6, 'm^--')
plot(xc7,z7, 'k>-.')
plot(xcb,zb, 'b-', 'linewidth', 2), grid on
grid on
ylabel('z_1, z_2, ... z_b')
xlabel('x_c')
set(gca, 'YDir','reverse')
legend({'z_1', 'z_2', 'z_3', 'z_4', 'z_5', 'z_6', 'z_7', 'z_b'}, 'Location','NE', 'NumColumns',2)
hold off
% The same figure as in Figure (2) but better scaled yy axis
figure(3)
yyaxis left
plot(xc1,z1, 'r*-'),
hold on
plot(xc2,z2, 'bd-')
plot(xc3,z3, 'gh--')
plot(xc4,z4, 'mp-.')
plot(xc5,z5, 'kd-')
plot(xc6,z6, 'm^--')
plot(xc7,z7, 'k>-.')
set(gca, 'YDir','reverse')
yyaxis right
plot(xcb,zb, 'b-', 'linewidth', 2), grid on
grid on
set(gca, 'YDir','reverse')
YC=gca;
YC.YColor='b';
legend({'z_1', 'z_2', 'z_3', 'z_4', 'z_5', 'z_6', 'z_7', 'z_b'}, 'Location','NE', 'NumColumns',2)
ylabel('z_b')
xlabel('x_c')
hold off
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