Databases
StackOverflow2013
Postsdbo
PO
 

Note that there are some explanatory texts on larger screens.

plurals
  1. PO
    primarykey
    data
    text
    <p>So one way of solving this would be two fit two lines to the <em>L</em> of your elbow. But since there are only a few points in one portion of the curve (as I mentioned in the comment), line fitting takes a hit unless you detect which points are spaced out and interpolate between them to manufacture a more uniform series and <strong>then</strong> use RANSAC to find two lines to fit the <em>L</em> - a little convoluted but not impossible.</p> <p>So here's a simpler solution - the graphs you've put up look the way they do thanks to MATLAB's scaling (obviously). So all I did was minimize the distance from the "origin" to your points using the scale information.</p> <p><strong>Please note:</strong> The origin estimation can be improved dramatically, but I'll leave that to you.</p> <p>Here's the code:</p> <pre><code>%% Order curve = [8.4663 8.3457 5.4507 5.3275 4.8305 4.7895 4.6889 4.6833 4.6819 4.6542 4.6501 4.6287 4.6162 4.585 4.5535 4.5134 4.474 4.4089 4.3797 4.3494 4.3268 4.3218 4.3206 4.3206 4.3203 4.2975 4.2864 4.2821 4.2544 4.2288 4.2281 4.2265 4.2226 4.2206 4.2146 4.2144 4.2114 4.1923 4.19 4.1894 4.1785 4.178 4.1694 4.1694 4.1694 4.1556 4.1498 4.1498 4.1357 4.1222 4.1222 4.1217 4.1192 4.1178 4.1139 4.1135 4.1125 4.1035 4.1025 4.1023 4.0971 4.0969 4.0915 4.0915 4.0914 4.0836 4.0804 4.0803 4.0722 4.065 4.065 4.0649 4.0644 4.0637 4.0616 4.0616 4.061 4.0572 4.0563 4.056 4.0545 4.0545 4.0522 4.0519 4.0514 4.0484 4.0467 4.0463 4.0422 4.0392 4.0388 4.0385 4.0385 4.0383 4.038 4.0379 4.0375 4.0364 4.0353 4.0344]; x_axis = 1:numel(curve); points = [x_axis ; curve ]'; %' - SO formatting %% Get the scaling info f = figure(1); plot(points(:,1),points(:,2)); ticks = get(get(f,'CurrentAxes'),'YTickLabel'); ticks = str2num(ticks); aspect = get(get(f,'CurrentAxes'),'DataAspectRatio'); aspect = [aspect(2) aspect(1)]; close(f); %% Get the "origin" O = [x_axis(1) ticks(1)]; %% Scale the data - now the scaled values look like MATLAB''s idea of % what a good plot should look like scaled_O = O.*aspect; scaled_points = bsxfun(@times,points,aspect); %% Find the closest point del = sum((bsxfun(@minus,scaled_points,scaled_O).^2),2); [val ind] = min(del); best_ROC = [ind curve(ind)]; %% Display plot(x_axis,curve,'.-'); hold on; plot(O(1),O(2),'r*'); plot(best_ROC(1),best_ROC(2),'k*'); </code></pre> <p>Results:</p> <p><img src="https://imgur.com/DFtrL.png" alt="results"></p> <p><strong>ALSO</strong> for the <code>Fit(maximize)</code> curve you'll have to change to origin to <code>[x_axis(1) ticks(end)]</code>.</p>
    singulars
    1. This table or related slice is empty.
    1. POFinding the best trade-off point on a curve
      singulars
      1. PTQuestion
    1. PTAnswer
    1. USJacob
    1. USJacob
    plurals
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. VO
      singulars
      1. PO
      1. This table or related slice is empty.
      1. VTUpMod
    2. VO
      singulars
      1. PO
      1. This table or related slice is empty.
      1. VTUpMod
    1. COan interesting idea, my only problem is the fact that you have to plot and use MATLAB's automatic scaling to find the origin.. This would not scale well especially since I have over a million of those curves to process on the fly. The xaxis is always guaranteed to start at 1, but I have no bound on the yaxis... and to answer you question, the shape is almost arbitrary although I expect a quick rise/fall in the beginning of the curve
      singulars
      1. PO
      1. USAmro
    2. COSo I suppose the problem is to figure out MATLAB's automatic scaling ... will check it out.
      singulars
      1. PO
      1. USJacob
 

Querying!

 
Guidance
A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.

SQuiL has stopped working due to an internal error.

If you are curious you may find further information in the browser console, which is accessible through the devtools (F12).

Reload