Plot line is thick in the middle on a log-log scale

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Anshuman Pal
Anshuman Pal 2021 年 7 月 2 日
コメント済み: Anshuman Pal 2021 年 7 月 3 日
I scatter() a bunch of points, on which I plot a black linear regression line calculated using polyfit() and polyeval(). On a linear scale, the line looks normal. But as soon as I turn on logscale using set(gca, 'xscale','log','yscale','log), the line becomes thick in the middle, as following:
What is going on? Could someone please help me? Closer inspection suggests that there is a smaller second line being drawn as well, which makes the main line look thick. Why?
  3 件のコメント
Scott MacKenzie
Scott MacKenzie 2021 年 7 月 2 日
I just tried to duplicate your plot and I didn't get a thick line. Perhaps provide code (and data) that can be executed to create the problem you note.



Cris LaPierre
Cris LaPierre 2021 年 7 月 2 日
編集済み: Cris LaPierre 2021 年 7 月 2 日
I can reproduce what you see in the code below. Since you haven't shared your code, I can't be certain it is the same cause, but I suspect it is.
When you use plot, it connects the points in the order they are listed. If your values are not sorted, it will bounce up and down the line plotting the points. When you switch your xscale, it highlights the subtle incontinuities in plotting the line this way.
A possible confounding issue may be if your data is in a matrix. Since each column is treated as a separate series, you would actually have multiple lines, one for each column. Of course, when you fit a line to your points, you want to fit a single line to all the points. Be sure you are not calculating a fit for each column, which results in multiple fit lines being drawn.
You do have to be mindful that, when you use polyval on all the x values are sorted to avoid the first issue mentioned above.. It may be a good idea to just create your own x vector to be sure your values are what you need.
% Create data set
x = rand(4,3);
y = x+(rand(4,3)-.5)*.1;
% Create plot where lines look normal
p = polyfit(x,y,1);
yp = polyval(p,x);
hold on
hold off
% Now looking stacked
hold on
hold off
set(gca, 'xscale','log','yscale','log')
Here's what the figure looks like if I use polyval on an x vector I create that is sorted in ascending order.
% fit a single line to all the points
p = polyfit(x(:),y(:),1);
% create a new vector of x values (ascending order)
xFit = 0:.1:1;
yp = polyval(p,xFit);
hold on
hold off
set(gca, 'xscale','log','yscale','log')
  2 件のコメント
Anshuman Pal
Anshuman Pal 2021 年 7 月 3 日
This was indeed the perfect answer. All I needed to do was sort my data before fitting. Thank you very much! I learnt something useful today.


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