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Finding x-intercept in a 2d plot shown below, there are multiple loops I want to find all the values of X at Y=0...Please help..
조회 수: 3 (최근 30일)
이전 댓글 표시
I have a 2D plot and I want to find x-intercept(x at y=0) for all the loops shown in the figure attached. Anyone please post relevant command and how can i use it in matlab.
If there is 2D raw data required I can share that too.
Thanks everyone.
답변 (2개)
Torsten
2022년 12월 13일
If you have the x-y values as vectors available, you can use this code to determine the x-values where y=0:
i = find(y(1:end-1).*y(2:end) <= 0)
x_root = x(i)-y(i).*(x(i+1)-x(i))./(y(i+1)-y(i))
Star Strider
2022년 12월 13일
Something like this should work —
%Finding X value with known Y value on plot
t = linspace(0, 2*pi, 1000); % Create Data
ph = -rand(10,1);
x = cos(2*pi*t*5 + zeros(size(ph)));
y = sin(2*pi*t*5 + ph);
x = reshape(x.',[],1);
y = reshape(y.',[],1);
figure
plot(x, y)
grid
axis('padded')
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1229587/image.png)
zxi = find(diff(sign(y))); % Indices Of Approximate Y-Zero-Crossings
for k = 1:size(zxi)
idxrng = max(1,zxi(k)-1) : min(numel(x),zxi(k)+1);
xv(k,:) = interp1(y(idxrng), x(idxrng), 0);
% yv(k,:) = interp1(x, ABC(k,:), xv(k,:));
end
xv
xv = 639×1
0.7099
-0.7088
0.7080
-0.7074
0.7071
-0.7072
0.7074
-0.7080
0.7088
-0.7100
% yv
figure
plot(x, y, 'DisplayName', 'Original Data')
hold on
plot(xv, zeros(size(xv)), '+r', 'DisplayName', 'X-Intersections')
hold off
grid
legend('Location','eastoutside')
axis('padded')
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1229592/image.png)
This uses synthetic data. It detects all the y-vector zero-crossings and returns the corresponding x-values in ‘xv’, and plots them.
It should work with your data without alteration, although it will require that you assign the appropriate values to ‘x’ and ‘y’ in my code.
.
댓글 수: 5
gowtham balu
2022년 12월 14일
I humbly thank you for all answers. But I have loops corresponding to cycles. I have 10,000 cycles and for each cycle I have 100 points. So at each cycle I want to find the x intercept.
I have attached the data points for first 2 cycles with this message as shown below:
dx(um) Q(N) COF P(N) Cycle
19.991 -13.604700845355397 -0.23137246335638428 58.800000000000004 1.0
19.991 -13.536100845355397 -0.23020579668971763 58.800000000000004 1.0
19.849 -13.398900845355397 -0.2278724633563843 58.800000000000004 1.0
19.706 -13.340100845355396 -0.22687246335638428 58.800000000000004 1.0
19.398 -13.340100845355396 -0.22687246335638428 58.800000000000004 1.0
19.162 -13.114700845355397 -0.22303913002305095 58.800000000000004 1.0
18.717 -12.938300845355396 -0.22003913002305095 58.800000000000004 1.0
18.233 -12.820700845355397 -0.21803913002305095 58.800000000000004 1.0
17.695 -12.507100845355398 -0.21270579668971762 58.800000000000004 1.0
17.079 -12.075900845355397 -0.2053724633563843 58.800000000000004 1.0
16.393 -11.723100845355397 -0.19937246335638428 58.800000000000004 1.0
15.728 -11.340900845355396 -0.19287246335638428 58.800000000000004 1.0
14.876 -10.713700845355397 -0.18220579668971762 58.800000000000004 1.0
14.019 -10.174700845355396 -0.17303913002305094 58.800000000000004 1.0
13.096 -9.586700845355397 -0.16303913002305095 58.800000000000004 1.0
12.085 -8.900700845355397 -0.1513724633563843 58.800000000000004 1.0
11.134 -8.146100845355397 -0.13853913002305096 58.800000000000004 1.0
10.008 -7.391500845355396 -0.12570579668971762 58.800000000000004 1.0
8.849 -6.676100845355396 -0.11353913002305095 58.800000000000004 1.0
7.8 -5.813700845355396 -0.09887246335638428 58.800000000000004 1.0
6.558 -4.902300845355396 -0.08337246335638428 58.800000000000004 1.0
5.383 -4.0693008453553965 -0.06920579668971762 58.800000000000004 1.0
4.158 -3.226500845355396 -0.05487246335638428 58.800000000000004 1.0
2.906 -2.197500845355396 -0.037372463356384285 58.800000000000004 1.0
1.648 -1.2175008453553957 -0.02070579668971761 58.800000000000004 1.0
0.445 -0.37470084535539705 -0.006372463356384303 58.800000000000004 1.0
-0.906 0.6542991546446046 0.011127536643615724 58.800000000000004 1.0
-2.104 1.732299154644604 0.029460869976949047 58.800000000000004 1.0
-3.318 2.6142991546446055 0.04446086997694907 58.800000000000004 1.0
-4.515 3.5452991546446064 0.060294203310282415 58.800000000000004 1.0
-5.795 4.642899154644603 0.07896086997694902 58.800000000000004 1.0
-7.053 5.593499154644604 0.09512753664361571 58.800000000000004 1.0
-8.113 6.387299154644605 0.10862753664361573 58.800000000000004 1.0
-9.288 7.396699154644605 0.12579420331028238 58.800000000000004 1.0
-10.365 8.347299154644606 0.14196086997694907 58.800000000000004 1.0
-11.442 9.101899154644606 0.1547942033102824 58.800000000000004 1.0
-12.458 9.934899154644604 0.16896086997694904 58.800000000000004 1.0
-13.468 10.836499154644606 0.1842942033102824 58.800000000000004 1.0
-14.281 11.551899154644605 0.19646086997694906 58.800000000000004 1.0
-15.21 12.169299154644605 0.20696086997694904 58.800000000000004 1.0
-15.94 12.894499154644606 0.2192942033102824 58.800000000000004 1.0
-16.698 13.453099154644605 0.22879420331028238 58.800000000000004 1.0
-17.357 13.747099154644609 0.23379420331028244 58.800000000000004 1.0
-17.89 14.001899154644605 0.23812753664361572 58.800000000000004 1.0
-18.483 14.158699154644605 0.24079420331028237 58.800000000000004 1.0
-18.901 14.060699154644606 0.23912753664361575 58.800000000000004 1.0
-19.258 14.021499154644609 0.2384608699769491 58.800000000000004 1.0
-19.664 13.903899154644606 0.23646086997694907 58.800000000000004 1.0
-19.922 13.845099154644604 0.23546086997694904 58.800000000000004 1.0
-19.944 13.835299154644606 0.2352942033102824 58.800000000000004 1.0
-20.01 13.678499154644605 0.2326275366436157 58.800000000000004 1.0
-20.032 13.639299154644604 0.23196086997694904 58.800000000000004 1.0
-19.939 13.609899154644605 0.23146086997694906 58.800000000000004 1.0
-19.835 13.423699154644602 0.22829420331028233 58.800000000000004 1.0
-19.571 13.266899154644602 0.22562753664361565 58.800000000000004 1.0
-19.241 13.257099154644603 0.225460869976949 58.800000000000004 1.0
-18.813 13.031699154644603 0.22162753664361567 58.800000000000004 1.0
-18.313 12.649499154644605 0.21512753664361572 58.800000000000004 1.0
-17.758 12.531899154644606 0.21312753664361572 58.800000000000004 1.0
-17.171 12.218299154644605 0.20779420331028237 58.800000000000004 1.0
-16.5 11.640099154644602 0.197960869976949 58.800000000000004 1.0
-15.814 11.228499154644606 0.19096086997694905 58.800000000000004 1.0
-14.924 10.816899154644602 0.183960869976949 58.800000000000004 1.0
-14.051 10.111299154644605 0.17196086997694907 58.800000000000004 1.0
-13.139 9.444899154644606 0.16062753664361573 58.800000000000004 1.0
-12.244 8.935299154644607 0.15196086997694908 58.800000000000004 1.0
-11.096 8.161099154644603 0.13879420331028236 58.800000000000004 1.0
-10.079 7.318299154644606 0.12446086997694908 58.800000000000004 1.0
-8.97 6.593099154644605 0.11212753664361573 58.800000000000004 1.0
-7.816 5.750299154644605 0.09779420331028238 58.800000000000004 1.0
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-4.213 3.114099154644604 0.05296086997694905 58.800000000000004 1.0
-3.07 2.1634991546446045 0.03679420331028239 58.800000000000004 1.0
-1.774 1.2128991546446048 0.02062753664361573 58.800000000000004 1.0
-0.533 0.18389915464460493 0.00312753664361573 58.800000000000004 1.0
0.731 -0.7177008453553952 -0.012205796689717606 58.800000000000004 1.0
2.01 -1.6487008453553962 -0.028039130023050952 58.800000000000004 1.0
3.285 -2.746300845355396 -0.04670579668971762 58.800000000000004 1.0
4.482 -3.6479008453553963 -0.062039130023050955 58.800000000000004 1.0
5.691 -4.529900845355396 -0.07703913002305095 58.800000000000004 1.0
6.861 -5.5491008453553965 -0.09437246335638429 58.800000000000004 1.0
8.074 -6.568300845355396 -0.11170579668971761 58.800000000000004 1.0
9.211 -7.332700845355396 -0.12470579668971761 58.800000000000004 1.0
10.283 -8.273500845355397 -0.1407057966897176 58.800000000000004 1.0
11.343 -9.263300845355397 -0.15753913002305098 58.800000000000004 1.0
12.365 -9.978700845355396 -0.1697057966897176 58.800000000000004 1.0
13.376 -10.723500845355396 -0.18237246335638427 58.800000000000004 1.0
14.228 -11.576100845355397 -0.19687246335638428 58.800000000000004 1.0
15.09 -12.311100845355396 -0.20937246335638426 58.800000000000004 1.0
15.871 -12.850100845355398 -0.21853913002305098 58.800000000000004 1.0
16.662 -13.555700845355396 -0.23053913002305093 58.800000000000004 1.0
17.266 -14.104500845355396 -0.23987246335638426 58.800000000000004 1.0
17.871 -14.241700845355396 -0.24220579668971762 58.800000000000004 1.0
18.371 -14.418100845355397 -0.24520579668971762 58.800000000000004 1.0
18.865 -14.457300845355396 -0.24587246335638427 58.800000000000004 1.0
19.244 -14.339700845355397 -0.2438724633563843 58.800000000000004 1.0
19.491 -14.280900845355397 -0.2428724633563843 58.800000000000004 1.0
19.733 -14.202500845355397 -0.24153913002305094 58.800000000000004 1.0
19.937 -14.133900845355397 -0.2403724633563843 58.800000000000004 1.0
19.898 -14.084900845355397 -0.23953913002305097 58.800000000000004 1.0
19.942 -13.986900845355397 -0.2378724633563843 58.800000000000004 1.0
19.942 -13.863105360443623 -0.23576709796672826 58.800000000000004 2.0
19.876 -13.755305360443623 -0.23393376463339494 58.800000000000004 2.0
19.755 -13.765105360443624 -0.2341004313000616 58.800000000000004 2.0
19.437 -13.588705360443623 -0.23110043130006158 58.800000000000004 2.0
19.107 -13.412305360443623 -0.2281004313000616 58.800000000000004 2.0
18.744 -13.353505360443624 -0.2271004313000616 58.800000000000004 2.0
18.31 -13.118305360443623 -0.2231004313000616 58.800000000000004 2.0
17.739 -12.726305360443623 -0.21643376463339495 58.800000000000004 2.0
17.156 -12.432305360443623 -0.21143376463339494 58.800000000000004 2.0
16.437 -12.128505360443622 -0.20626709796672826 58.800000000000004 2.0
15.711 -11.530705360443623 -0.1961004313000616 58.800000000000004 2.0
14.887 -11.040705360443622 -0.18776709796672825 58.800000000000004 2.0
14.145 -10.589905360443623 -0.18010043130006162 58.800000000000004 2.0
13.123 -9.903905360443622 -0.1684337646333949 58.800000000000004 2.0
12.074 -9.168905360443622 -0.15593376463339492 58.800000000000004 2.0
11.019 -8.531905360443623 -0.14510043130006162 58.800000000000004 2.0
10.063 -7.826305360443622 -0.13310043130006158 58.800000000000004 2.0
8.827 -6.9443053604436225 -0.11810043130006159 58.800000000000004 2.0
7.8 -6.1505053604436215 -0.10460043130006158 58.800000000000004 2.0
6.536 -5.356705360443622 -0.0911004313000616 58.800000000000004 2.0
5.339 -4.4355053604436225 -0.07543376463339493 58.800000000000004 2.0
4.136 -3.4653053604436206 -0.058933764633394906 58.800000000000004 2.0
2.972 -2.553905360443622 -0.043433764633394926 58.800000000000004 2.0
1.692 -1.662105360443622 -0.028267097966728265 58.800000000000004 2.0
0.39 -0.6331053604436221 -0.010767097966728267 58.800000000000004 2.0
-0.818 0.3762946395563773 0.006399568699938389 58.800000000000004 2.0
-2.115 1.2876946395563778 0.021899568699938397 58.800000000000004 2.0
-3.329 2.267694639556378 0.03856623536660507 58.800000000000004 2.0
-4.597 3.3064946395563783 0.056232902033271734 58.800000000000004 2.0
-5.751 4.2766946395563785 0.07273290203327173 58.800000000000004 2.0
-6.954 5.1096946395563805 0.08689956869993844 58.800000000000004 2.0
-8.063 6.11909463955638 0.10406623536660509 58.800000000000004 2.0
-9.25 7.089294639556378 0.12056623536660506 58.800000000000004 2.0
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-19.988 14.155094639556381 0.24073290203327177 58.800000000000004 2.0
-20.043 14.106094639556382 0.23989956869993845 58.800000000000004 2.0
-19.95 13.929694639556377 0.23689956869993836 58.800000000000004 2.0
-19.78 13.84149463955638 0.23539956869993842 58.800000000000004 2.0
-19.533 13.80229463955638 0.23473290203327174 58.800000000000004 2.0
-19.236 13.606294639556381 0.23139956869993844 58.800000000000004 2.0
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-18.357 13.263294639556378 0.22556623536660506 58.800000000000004 2.0
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-15.808 11.734494639556381 0.19956623536660512 58.800000000000004 2.0
-14.919 11.117094639556381 0.1890662353666051 58.800000000000004 2.0
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-9.036 7.020694639556378 0.1193995686999384 58.800000000000004 2.0
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-0.456 0.7290946395563775 0.012399568699938393 58.800000000000004 2.0
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1.966 -1.3387053604436225 -0.022767097966728274 58.800000000000004 2.0
3.224 -2.1717053604436227 -0.03693376463339494 58.800000000000004 2.0
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16.607 -13.167305360443622 -0.22393376463339493 58.800000000000004 2.0
17.233 -13.647505360443622 -0.23210043130006158 58.800000000000004 2.0
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19.678 -14.421705360443623 -0.24526709796672827 58.800000000000004 2.0
19.893 -14.343305360443622 -0.24393376463339492 58.800000000000004 2.0
19.893 -14.245305360443623 -0.24226709796672827 58.800000000000004 2.0
Torsten
2022년 12월 14일
편집: Torsten
2022년 12월 14일
A = [19.991 -13.604700845355397 -0.23137246335638428 58.800000000000004 1.0
19.991 -13.536100845355397 -0.23020579668971763 58.800000000000004 1.0
19.849 -13.398900845355397 -0.2278724633563843 58.800000000000004 1.0
19.706 -13.340100845355396 -0.22687246335638428 58.800000000000004 1.0
19.398 -13.340100845355396 -0.22687246335638428 58.800000000000004 1.0
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16.393 -11.723100845355397 -0.19937246335638428 58.800000000000004 1.0
15.728 -11.340900845355396 -0.19287246335638428 58.800000000000004 1.0
14.876 -10.713700845355397 -0.18220579668971762 58.800000000000004 1.0
14.019 -10.174700845355396 -0.17303913002305094 58.800000000000004 1.0
13.096 -9.586700845355397 -0.16303913002305095 58.800000000000004 1.0
12.085 -8.900700845355397 -0.1513724633563843 58.800000000000004 1.0
11.134 -8.146100845355397 -0.13853913002305096 58.800000000000004 1.0
10.008 -7.391500845355396 -0.12570579668971762 58.800000000000004 1.0
8.849 -6.676100845355396 -0.11353913002305095 58.800000000000004 1.0
7.8 -5.813700845355396 -0.09887246335638428 58.800000000000004 1.0
6.558 -4.902300845355396 -0.08337246335638428 58.800000000000004 1.0
5.383 -4.0693008453553965 -0.06920579668971762 58.800000000000004 1.0
4.158 -3.226500845355396 -0.05487246335638428 58.800000000000004 1.0
2.906 -2.197500845355396 -0.037372463356384285 58.800000000000004 1.0
1.648 -1.2175008453553957 -0.02070579668971761 58.800000000000004 1.0
0.445 -0.37470084535539705 -0.006372463356384303 58.800000000000004 1.0
-0.906 0.6542991546446046 0.011127536643615724 58.800000000000004 1.0
-2.104 1.732299154644604 0.029460869976949047 58.800000000000004 1.0
-3.318 2.6142991546446055 0.04446086997694907 58.800000000000004 1.0
-4.515 3.5452991546446064 0.060294203310282415 58.800000000000004 1.0
-5.795 4.642899154644603 0.07896086997694902 58.800000000000004 1.0
-7.053 5.593499154644604 0.09512753664361571 58.800000000000004 1.0
-8.113 6.387299154644605 0.10862753664361573 58.800000000000004 1.0
-9.288 7.396699154644605 0.12579420331028238 58.800000000000004 1.0
-10.365 8.347299154644606 0.14196086997694907 58.800000000000004 1.0
-11.442 9.101899154644606 0.1547942033102824 58.800000000000004 1.0
-12.458 9.934899154644604 0.16896086997694904 58.800000000000004 1.0
-13.468 10.836499154644606 0.1842942033102824 58.800000000000004 1.0
-14.281 11.551899154644605 0.19646086997694906 58.800000000000004 1.0
-15.21 12.169299154644605 0.20696086997694904 58.800000000000004 1.0
-15.94 12.894499154644606 0.2192942033102824 58.800000000000004 1.0
-16.698 13.453099154644605 0.22879420331028238 58.800000000000004 1.0
-17.357 13.747099154644609 0.23379420331028244 58.800000000000004 1.0
-17.89 14.001899154644605 0.23812753664361572 58.800000000000004 1.0
-18.483 14.158699154644605 0.24079420331028237 58.800000000000004 1.0
-18.901 14.060699154644606 0.23912753664361575 58.800000000000004 1.0
-19.258 14.021499154644609 0.2384608699769491 58.800000000000004 1.0
-19.664 13.903899154644606 0.23646086997694907 58.800000000000004 1.0
-19.922 13.845099154644604 0.23546086997694904 58.800000000000004 1.0
-19.944 13.835299154644606 0.2352942033102824 58.800000000000004 1.0
-20.01 13.678499154644605 0.2326275366436157 58.800000000000004 1.0
-20.032 13.639299154644604 0.23196086997694904 58.800000000000004 1.0
-19.939 13.609899154644605 0.23146086997694906 58.800000000000004 1.0
-19.835 13.423699154644602 0.22829420331028233 58.800000000000004 1.0
-19.571 13.266899154644602 0.22562753664361565 58.800000000000004 1.0
-19.241 13.257099154644603 0.225460869976949 58.800000000000004 1.0
-18.813 13.031699154644603 0.22162753664361567 58.800000000000004 1.0
-18.313 12.649499154644605 0.21512753664361572 58.800000000000004 1.0
-17.758 12.531899154644606 0.21312753664361572 58.800000000000004 1.0
-17.171 12.218299154644605 0.20779420331028237 58.800000000000004 1.0
-16.5 11.640099154644602 0.197960869976949 58.800000000000004 1.0
-15.814 11.228499154644606 0.19096086997694905 58.800000000000004 1.0
-14.924 10.816899154644602 0.183960869976949 58.800000000000004 1.0
-14.051 10.111299154644605 0.17196086997694907 58.800000000000004 1.0
-13.139 9.444899154644606 0.16062753664361573 58.800000000000004 1.0
-12.244 8.935299154644607 0.15196086997694908 58.800000000000004 1.0
-11.096 8.161099154644603 0.13879420331028236 58.800000000000004 1.0
-10.079 7.318299154644606 0.12446086997694908 58.800000000000004 1.0
-8.97 6.593099154644605 0.11212753664361573 58.800000000000004 1.0
-7.816 5.750299154644605 0.09779420331028238 58.800000000000004 1.0
-6.657 4.868299154644603 0.08279420331028237 58.800000000000004 1.0
-5.476 3.9568991546446064 0.06729420331028242 58.800000000000004 1.0
-4.213 3.114099154644604 0.05296086997694905 58.800000000000004 1.0
-3.07 2.1634991546446045 0.03679420331028239 58.800000000000004 1.0
-1.774 1.2128991546446048 0.02062753664361573 58.800000000000004 1.0
-0.533 0.18389915464460493 0.00312753664361573 58.800000000000004 1.0
0.731 -0.7177008453553952 -0.012205796689717606 58.800000000000004 1.0
2.01 -1.6487008453553962 -0.028039130023050952 58.800000000000004 1.0
3.285 -2.746300845355396 -0.04670579668971762 58.800000000000004 1.0
4.482 -3.6479008453553963 -0.062039130023050955 58.800000000000004 1.0
5.691 -4.529900845355396 -0.07703913002305095 58.800000000000004 1.0
6.861 -5.5491008453553965 -0.09437246335638429 58.800000000000004 1.0
8.074 -6.568300845355396 -0.11170579668971761 58.800000000000004 1.0
9.211 -7.332700845355396 -0.12470579668971761 58.800000000000004 1.0
10.283 -8.273500845355397 -0.1407057966897176 58.800000000000004 1.0
11.343 -9.263300845355397 -0.15753913002305098 58.800000000000004 1.0
12.365 -9.978700845355396 -0.1697057966897176 58.800000000000004 1.0
13.376 -10.723500845355396 -0.18237246335638427 58.800000000000004 1.0
14.228 -11.576100845355397 -0.19687246335638428 58.800000000000004 1.0
15.09 -12.311100845355396 -0.20937246335638426 58.800000000000004 1.0
15.871 -12.850100845355398 -0.21853913002305098 58.800000000000004 1.0
16.662 -13.555700845355396 -0.23053913002305093 58.800000000000004 1.0
17.266 -14.104500845355396 -0.23987246335638426 58.800000000000004 1.0
17.871 -14.241700845355396 -0.24220579668971762 58.800000000000004 1.0
18.371 -14.418100845355397 -0.24520579668971762 58.800000000000004 1.0
18.865 -14.457300845355396 -0.24587246335638427 58.800000000000004 1.0
19.244 -14.339700845355397 -0.2438724633563843 58.800000000000004 1.0
19.491 -14.280900845355397 -0.2428724633563843 58.800000000000004 1.0
19.733 -14.202500845355397 -0.24153913002305094 58.800000000000004 1.0
19.937 -14.133900845355397 -0.2403724633563843 58.800000000000004 1.0
19.898 -14.084900845355397 -0.23953913002305097 58.800000000000004 1.0
19.942 -13.986900845355397 -0.2378724633563843 58.800000000000004 1.0
19.942 -13.863105360443623 -0.23576709796672826 58.800000000000004 2.0
19.876 -13.755305360443623 -0.23393376463339494 58.800000000000004 2.0
19.755 -13.765105360443624 -0.2341004313000616 58.800000000000004 2.0
19.437 -13.588705360443623 -0.23110043130006158 58.800000000000004 2.0
19.107 -13.412305360443623 -0.2281004313000616 58.800000000000004 2.0
18.744 -13.353505360443624 -0.2271004313000616 58.800000000000004 2.0
18.31 -13.118305360443623 -0.2231004313000616 58.800000000000004 2.0
17.739 -12.726305360443623 -0.21643376463339495 58.800000000000004 2.0
17.156 -12.432305360443623 -0.21143376463339494 58.800000000000004 2.0
16.437 -12.128505360443622 -0.20626709796672826 58.800000000000004 2.0
15.711 -11.530705360443623 -0.1961004313000616 58.800000000000004 2.0
14.887 -11.040705360443622 -0.18776709796672825 58.800000000000004 2.0
14.145 -10.589905360443623 -0.18010043130006162 58.800000000000004 2.0
13.123 -9.903905360443622 -0.1684337646333949 58.800000000000004 2.0
12.074 -9.168905360443622 -0.15593376463339492 58.800000000000004 2.0
11.019 -8.531905360443623 -0.14510043130006162 58.800000000000004 2.0
10.063 -7.826305360443622 -0.13310043130006158 58.800000000000004 2.0
8.827 -6.9443053604436225 -0.11810043130006159 58.800000000000004 2.0
7.8 -6.1505053604436215 -0.10460043130006158 58.800000000000004 2.0
6.536 -5.356705360443622 -0.0911004313000616 58.800000000000004 2.0
5.339 -4.4355053604436225 -0.07543376463339493 58.800000000000004 2.0
4.136 -3.4653053604436206 -0.058933764633394906 58.800000000000004 2.0
2.972 -2.553905360443622 -0.043433764633394926 58.800000000000004 2.0
1.692 -1.662105360443622 -0.028267097966728265 58.800000000000004 2.0
0.39 -0.6331053604436221 -0.010767097966728267 58.800000000000004 2.0
-0.818 0.3762946395563773 0.006399568699938389 58.800000000000004 2.0
-2.115 1.2876946395563778 0.021899568699938397 58.800000000000004 2.0
-3.329 2.267694639556378 0.03856623536660507 58.800000000000004 2.0
-4.597 3.3064946395563783 0.056232902033271734 58.800000000000004 2.0
-5.751 4.2766946395563785 0.07273290203327173 58.800000000000004 2.0
-6.954 5.1096946395563805 0.08689956869993844 58.800000000000004 2.0
-8.063 6.11909463955638 0.10406623536660509 58.800000000000004 2.0
-9.25 7.089294639556378 0.12056623536660506 58.800000000000004 2.0
-10.25 7.912494639556378 0.13456623536660506 58.800000000000004 2.0
-11.387 8.77489463955638 0.14923290203327175 58.800000000000004 2.0
-12.364 9.705894639556377 0.16506623536660503 58.800000000000004 2.0
-13.381 10.50949463955638 0.17873290203327175 58.800000000000004 2.0
-14.292 11.14649463955638 0.18956623536660508 58.800000000000004 2.0
-15.144 11.969694639556376 0.20356623536660504 58.800000000000004 2.0
-15.968 12.665494639556378 0.2153995686999384 58.800000000000004 2.0
-16.682 13.194694639556378 0.22439956869993838 58.800000000000004 2.0
-17.319 13.73369463955638 0.23356623536660506 58.800000000000004 2.0
-17.918 14.262894639556382 0.24256623536660513 58.800000000000004 2.0
-18.439 14.360894639556378 0.24423290203327172 58.800000000000004 2.0
-18.895 14.360894639556378 0.24423290203327172 58.800000000000004 2.0
-19.258 14.409894639556377 0.24506623536660505 58.800000000000004 2.0
-19.642 14.30209463955638 0.24323290203327175 58.800000000000004 2.0
-19.791 14.292294639556378 0.24306623536660504 58.800000000000004 2.0
-19.895 14.174694639556378 0.24106623536660504 58.800000000000004 2.0
-19.988 14.155094639556381 0.24073290203327177 58.800000000000004 2.0
-20.043 14.106094639556382 0.23989956869993845 58.800000000000004 2.0
-19.95 13.929694639556377 0.23689956869993836 58.800000000000004 2.0
-19.78 13.84149463955638 0.23539956869993842 58.800000000000004 2.0
-19.533 13.80229463955638 0.23473290203327174 58.800000000000004 2.0
-19.236 13.606294639556381 0.23139956869993844 58.800000000000004 2.0
-18.851 13.34169463955638 0.2268995686999384 58.800000000000004 2.0
-18.357 13.263294639556378 0.22556623536660506 58.800000000000004 2.0
-17.824 12.96929463955638 0.2205662353666051 58.800000000000004 2.0
-17.11 12.459694639556378 0.2118995686999384 58.800000000000004 2.0
-16.555 12.146094639556381 0.2065662353666051 58.800000000000004 2.0
-15.808 11.734494639556381 0.19956623536660512 58.800000000000004 2.0
-14.919 11.117094639556381 0.1890662353666051 58.800000000000004 2.0
-14.122 10.50949463955638 0.17873290203327175 58.800000000000004 2.0
-13.199 10.019494639556378 0.1703995686999384 58.800000000000004 2.0
-12.205 9.313894639556377 0.15839956869993838 58.800000000000004 2.0
-11.222 8.510294639556378 0.14473290203327172 58.800000000000004 2.0
-10.14 7.824294639556381 0.1330662353666051 58.800000000000004 2.0
-9.036 7.020694639556378 0.1193995686999384 58.800000000000004 2.0
-7.849 6.168094639556379 0.10489956869993841 58.800000000000004 2.0
-6.718 5.266494639556381 0.08956623536660512 58.800000000000004 2.0
-5.493 4.47269463955638 0.0760662353666051 58.800000000000004 2.0
-4.284 3.571094639556378 0.06073290203327173 58.800000000000004 2.0
-3.016 2.571494639556377 0.043732902033271716 58.800000000000004 2.0
-1.813 1.611094639556379 0.027399568699938415 58.800000000000004 2.0
-0.456 0.7290946395563775 0.012399568699938393 58.800000000000004 2.0
0.731 -0.26070536044362136 -0.0044337646333949205 58.800000000000004 2.0
1.966 -1.3387053604436225 -0.022767097966728274 58.800000000000004 2.0
3.224 -2.1717053604436227 -0.03693376463339494 58.800000000000004 2.0
4.482 -3.1223053604436224 -0.053100431300061604 58.800000000000004 2.0
5.685 -4.200305360443622 -0.07143376463339492 58.800000000000004 2.0
6.894 -5.150905360443622 -0.0876004313000616 58.800000000000004 2.0
8.031 -5.974105360443621 -0.10160043130006158 58.800000000000004 2.0
9.157 -6.973705360443622 -0.11860043130006159 58.800000000000004 2.0
10.239 -7.914505360443623 -0.1346004313000616 58.800000000000004 2.0
11.327 -8.649505360443623 -0.1471004313000616 58.800000000000004 2.0
12.261 -9.502105360443622 -0.16160043130006158 58.800000000000004 2.0
13.343 -10.374305360443621 -0.1764337646333949 58.800000000000004 2.0
14.261 -11.119105360443623 -0.1891004313000616 58.800000000000004 2.0
15.079 -11.795305360443622 -0.20060043130006158 58.800000000000004 2.0
15.86 -12.510705360443623 -0.21276709796672827 58.800000000000004 2.0
16.607 -13.167305360443622 -0.22393376463339493 58.800000000000004 2.0
17.233 -13.647505360443622 -0.23210043130006158 58.800000000000004 2.0
17.898 -14.137505360443622 -0.24043376463339491 58.800000000000004 2.0
18.393 -14.549105360443622 -0.24743376463339492 58.800000000000004 2.0
18.86 -14.676505360443622 -0.24960043130006157 58.800000000000004 2.0
19.211 -14.627505360443623 -0.24876709796672825 58.800000000000004 2.0
19.48 -14.529505360443622 -0.24710043130006157 58.800000000000004 2.0
19.678 -14.421705360443623 -0.24526709796672827 58.800000000000004 2.0
19.893 -14.343305360443622 -0.24393376463339492 58.800000000000004 2.0
19.893 -14.245305360443623 -0.24226709796672827 58.800000000000004 2.0];
x = A(:,1);
y = A(:,2);
i = find(y(1:end-1).*y(2:end) <= 0);
x_root = x(i)-y(i).*(x(i+1)-x(i))./(y(i+1)-y(i))
x_root = 4×1
-0.0470
-0.2752
-0.3677
0.4184
plot(x,y)
hold on
plot(x_root,zeros(size(x_root)),'o')
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1230657/image.png)
Star Strider
2022년 12월 14일
GMT-7 here, so I just saw the data.
% dx(um) Q(N) COF P(N) Cycle
A = [19.991 -13.604700845355397 -0.23137246335638428 58.800000000000004 1.0
19.991 -13.536100845355397 -0.23020579668971763 58.800000000000004 1.0
19.849 -13.398900845355397 -0.2278724633563843 58.800000000000004 1.0
19.706 -13.340100845355396 -0.22687246335638428 58.800000000000004 1.0
19.398 -13.340100845355396 -0.22687246335638428 58.800000000000004 1.0
19.162 -13.114700845355397 -0.22303913002305095 58.800000000000004 1.0
18.717 -12.938300845355396 -0.22003913002305095 58.800000000000004 1.0
18.233 -12.820700845355397 -0.21803913002305095 58.800000000000004 1.0
17.695 -12.507100845355398 -0.21270579668971762 58.800000000000004 1.0
17.079 -12.075900845355397 -0.2053724633563843 58.800000000000004 1.0
16.393 -11.723100845355397 -0.19937246335638428 58.800000000000004 1.0
15.728 -11.340900845355396 -0.19287246335638428 58.800000000000004 1.0
14.876 -10.713700845355397 -0.18220579668971762 58.800000000000004 1.0
14.019 -10.174700845355396 -0.17303913002305094 58.800000000000004 1.0
13.096 -9.586700845355397 -0.16303913002305095 58.800000000000004 1.0
12.085 -8.900700845355397 -0.1513724633563843 58.800000000000004 1.0
11.134 -8.146100845355397 -0.13853913002305096 58.800000000000004 1.0
10.008 -7.391500845355396 -0.12570579668971762 58.800000000000004 1.0
8.849 -6.676100845355396 -0.11353913002305095 58.800000000000004 1.0
7.8 -5.813700845355396 -0.09887246335638428 58.800000000000004 1.0
6.558 -4.902300845355396 -0.08337246335638428 58.800000000000004 1.0
5.383 -4.0693008453553965 -0.06920579668971762 58.800000000000004 1.0
4.158 -3.226500845355396 -0.05487246335638428 58.800000000000004 1.0
2.906 -2.197500845355396 -0.037372463356384285 58.800000000000004 1.0
1.648 -1.2175008453553957 -0.02070579668971761 58.800000000000004 1.0
0.445 -0.37470084535539705 -0.006372463356384303 58.800000000000004 1.0
-0.906 0.6542991546446046 0.011127536643615724 58.800000000000004 1.0
-2.104 1.732299154644604 0.029460869976949047 58.800000000000004 1.0
-3.318 2.6142991546446055 0.04446086997694907 58.800000000000004 1.0
-4.515 3.5452991546446064 0.060294203310282415 58.800000000000004 1.0
-5.795 4.642899154644603 0.07896086997694902 58.800000000000004 1.0
-7.053 5.593499154644604 0.09512753664361571 58.800000000000004 1.0
-8.113 6.387299154644605 0.10862753664361573 58.800000000000004 1.0
-9.288 7.396699154644605 0.12579420331028238 58.800000000000004 1.0
-10.365 8.347299154644606 0.14196086997694907 58.800000000000004 1.0
-11.442 9.101899154644606 0.1547942033102824 58.800000000000004 1.0
-12.458 9.934899154644604 0.16896086997694904 58.800000000000004 1.0
-13.468 10.836499154644606 0.1842942033102824 58.800000000000004 1.0
-14.281 11.551899154644605 0.19646086997694906 58.800000000000004 1.0
-15.21 12.169299154644605 0.20696086997694904 58.800000000000004 1.0
-15.94 12.894499154644606 0.2192942033102824 58.800000000000004 1.0
-16.698 13.453099154644605 0.22879420331028238 58.800000000000004 1.0
-17.357 13.747099154644609 0.23379420331028244 58.800000000000004 1.0
-17.89 14.001899154644605 0.23812753664361572 58.800000000000004 1.0
-18.483 14.158699154644605 0.24079420331028237 58.800000000000004 1.0
-18.901 14.060699154644606 0.23912753664361575 58.800000000000004 1.0
-19.258 14.021499154644609 0.2384608699769491 58.800000000000004 1.0
-19.664 13.903899154644606 0.23646086997694907 58.800000000000004 1.0
-19.922 13.845099154644604 0.23546086997694904 58.800000000000004 1.0
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19.893 -14.245305360443623 -0.24226709796672827 58.800000000000004 2.0];
x = A(:,1);
y = A(:,2);
zxi = find(diff(sign(y))); % Indices Of Approximate Y-Zero-Crossings
for k = 1:size(zxi)
idxrng = max(1,zxi(k)-1) : min(numel(x),zxi(k)+1);
xv(k,:) = interp1(y(idxrng), x(idxrng), 0);
% yv(k,:) = interp1(x, ABC(k,:), xv(k,:));
end
xv
xv = 4×1
-0.0470
-0.2752
-0.3677
0.4184
figure
plot(x, y, 'DisplayName', 'Original Data')
hold on
plot(xv, zeros(size(xv)), '+r', 'DisplayName', 'X-Intersections')
hold off
grid
xlabel('\delta(\mum)')
ylabel('Q(N)')
legend('Location','eastoutside')
axis('padded','equal')
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1230682/image.png)
There appear to be only four distinct intersections.
.
gowtham balu
2022년 12월 14일
I humbly Thank you for your speedy and timely response and answers........
With regards,
Gowtham
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