I am trying to plot three different equations onto one figure, and each equation with a smooth curve. Because I need to set the values of the independent variable, I cannot figure out how to make them into smooth curves; instead the graphs are segmented, from point to point. Any tips ar...
Open in MATLAB Online This question concerns only the way a curve is displayed on the screen with plot(x,y), not the data. For example: x=linspace(0,50,1000000); plot(x,sin(x)) Displays the following plot: And I would like to have something like this: ...
Tags Color Contour plot Matlab Plot Smooth In summary, the conversation was about representing data with 2 variables in a 2D format using the contourf function in MATLAB. The speaker was experiencing coarse-granularity in their current plot and wanted to know if there was a way to make the co...
i need to do a boxcar smoothing of this data (need to apply a 100meter boxcar smoothing). how i will do it in matlab ? 댓글 수: 0 댓글을 달려면 로그인하십시오. 이 질문에 답변하려면 로그인하십시오....
in the screen view of Word looks rough, the lines are smooth when printed to paper or to a ...
Open in MATLAB Online Hello, There is an option that you can refer, ThemeCopy a1 = smooth(a); plot(x,a1) There are many types of smooth function, you may read links below for more options. https://it.mathworks.com/help/curvefit/smooth.html https://it.mathworks.com/...
Edge preserving filter will smooth the contours while keeping the density (high at the edge) unmodified. That is exactly what it needs, I think. Sign in to comment.Sign in to answer this question.See Also MATLAB Answers How to smooth a contour plot using the low pass filter 1 Answer ...
The 3rd plot is a comparison: when data's not noisy, Matlab produces a flat background part (the blue part) too. I wonder if there's anyway I can get do the same as in Origin using Matlab. Or do I have to smooth the data myself?
In this step-by-step tutorial, you'll learn about MATLAB vs Python, why you should switch from MATLAB to Python, the packages you'll need to make a smooth transition, and the bumps you'll most likely encounter along the way.
The calculation is straightforward; we remove a measurement, smooth the series, and calculate the squared residual between our smoothed curve and the removed measurement. Repeat this for every measurement in the data, take an average and voila,we’ve calculated theleave-one-out cross validation err...