Wrong Callout leader colors combined with specific data

Question

Consider my data (sorry for long code but it's necessary):

data = {{{-(4963/20), 3.58534}, {-(4463/20), 3.62705}, {-(3963/20), 
   3.67089}, {-(3463/20), 3.71615}, {-(2963/20), 
   3.76244}, {-(2463/20), 3.80958}, {-(1963/20), 
   3.85741}, {-(1463/20), 3.90581}, {-(963/20), 3.95473}, {-(463/20), 
   4.00413}, {37/20, 4.05393}, {537/20, 4.10414}, {1037/20, 
   4.15465}, {1537/20, 4.20552}, {2037/20, 4.25667}, {2537/20, 
   4.30809}, {3037/20, 4.35981}, {3537/20, 4.41175}, {4037/20, 
   4.46395}, {4537/20, 4.51638}, {5037/20, 4.56903}, {5537/20, 
   4.62187}, {6037/20, 4.67495}, {6537/20, 4.72819}, {7037/20, 
   4.78165}, {7537/20, 4.83527}, {8037/20, 4.88908}, {8537/20, 
   4.94304}, {9037/20, 4.99718}, {9537/20, 5.05149}, {10037/20, 
   5.10595}, {10537/20, 5.16057}, {11037/20, 5.21533}, {11537/20, 
   5.27023}, {12037/20, 5.32528}, {12537/20, 5.38047}, {13037/20, 
   5.4358}, {13537/20, 5.49125}, {14037/20, 5.54682}, {14537/20, 
   5.60254}}, {{-(4963/20), 4.73311}, {-(4463/20), 
   4.69141}, {-(3963/20), 4.64757}, {-(3463/20), 4.6023}, {-(2963/20),
    4.55601}, {-(2463/20), 4.50887}, {-(1963/20), 
   4.46104}, {-(1463/20), 4.41264}, {-(963/20), 4.36372}, {-(463/20), 
   4.31432}, {37/20, 4.26452}, {537/20, 4.21432}, {1037/20, 
   4.1638}, {1537/20, 4.11294}, {2037/20, 4.06178}, {2537/20, 
   4.01037}, {3037/20, 3.95864}, {3537/20, 3.90671}, {4037/20, 
   3.85451}, {4537/20, 3.80207}, {5037/20, 3.74942}, {5537/20, 
   3.69658}, {6037/20, 3.64351}, {6537/20, 3.59026}, {7037/20, 
   3.53681}, {7537/20, 3.48318}, {8037/20, 3.42937}, {8537/20, 
   3.37542}, {9037/20, 3.32127}, {9537/20, 3.26696}, {10037/20, 
   3.21251}, {10537/20, 3.15789}, {11037/20, 3.10312}, {11537/20, 
   3.04822}, {12037/20, 2.99317}, {12537/20, 2.93798}, {13037/20, 
   2.88265}, {13537/20, 2.8272}, {14037/20, 2.77163}, {14537/20, 
   2.71592}}, {{-(4963/20), 2.07276}, {-(4463/20), 
   2.07276}, {-(3963/20), 2.07276}, {-(3463/20), 
   2.07276}, {-(2963/20), 2.07276}, {-(2463/20), 
   2.07276}, {-(1963/20), 2.07276}, {-(1463/20), 2.07276}, {-(963/20),
    2.07276}, {-(463/20), 2.07276}, {37/20, 2.07276}, {537/20, 
   2.07276}, {1037/20, 2.07276}, {1537/20, 2.07276}, {2037/20, 
   2.07276}, {2537/20, 2.07276}, {3037/20, 2.07276}, {3537/20, 
   2.07276}, {4037/20, 2.07276}, {4537/20, 2.07276}, {5037/20, 
   2.07276}, {5537/20, 2.07276}, {6037/20, 2.07276}, {6537/20, 
   2.07276}, {7037/20, 2.07276}, {7537/20, 2.07276}, {8037/20, 
   2.07276}, {8537/20, 2.07276}, {9037/20, 2.07276}, {9537/20, 
   2.07276}, {10037/20, 2.07276}, {10537/20, 2.07276}, {11037/20, 
   2.07276}, {11537/20, 2.07276}, {12037/20, 2.07276}, {12537/20, 
   2.07276}, {13037/20, 2.07276}, {13537/20, 2.07276}, {14037/20, 
   2.07276}, {14537/20, 2.07276}}, {{-(4963/20), 
   1.71283}, {-(4463/20), 1.71283}, {-(3963/20), 
   1.71283}, {-(3463/20), 1.71283}, {-(2963/20), 
   1.71283}, {-(2463/20), 1.71283}, {-(1963/20), 
   1.71283}, {-(1463/20), 1.71283}, {-(963/20), 1.71283}, {-(463/20), 
   1.71283}, {37/20, 1.71283}, {537/20, 1.71283}, {1037/20, 
   1.71283}, {1537/20, 1.71283}, {2037/20, 1.71283}, {2537/20, 
   1.71283}, {3037/20, 1.71283}, {3537/20, 1.71283}, {4037/20, 
   1.71283}, {4537/20, 1.71283}, {5037/20, 1.71283}, {5537/20, 
   1.71283}, {6037/20, 1.71283}, {6537/20, 1.71283}, {7037/20, 
   1.71283}, {7537/20, 1.71283}, {8037/20, 1.71283}, {8537/20, 
   1.71283}, {9037/20, 1.71283}, {9537/20, 1.71283}, {10037/20, 
   1.71283}, {10537/20, 1.71283}, {11037/20, 1.71283}, {11537/20, 
   1.71283}, {12037/20, 1.71283}, {12537/20, 1.71283}, {13037/20, 
   1.71283}, {13537/20, 1.71283}, {14037/20, 1.71283}, {14537/20, 
   1.71283}}, {{-(4963/20), 1.67639}, {-(4463/20), 
   1.67639}, {-(3963/20), 1.67639}, {-(3463/20), 
   1.67639}, {-(2963/20), 1.67639}, {-(2463/20), 
   1.67639}, {-(1963/20), 1.67639}, {-(1463/20), 1.67639}, {-(963/20),
    1.67639}, {-(463/20), 1.67639}, {37/20, 1.67639}, {537/20, 
   1.67639}, {1037/20, 1.67639}, {1537/20, 1.67639}, {2037/20, 
   1.67639}, {2537/20, 1.67639}, {3037/20, 1.67639}, {3537/20, 
   1.67639}, {4037/20, 1.67639}, {4537/20, 1.67639}, {5037/20, 
   1.67639}, {5537/20, 1.67639}, {6037/20, 1.67639}, {6537/20, 
   1.67639}, {7037/20, 1.67639}, {7537/20, 1.67639}, {8037/20, 
   1.67639}, {8537/20, 1.67639}, {9037/20, 1.67639}, {9537/20, 
   1.67639}, {10037/20, 1.67639}, {10537/20, 1.67639}, {11037/20, 
   1.67639}, {11537/20, 1.67639}, {12037/20, 1.67639}, {12537/20, 
   1.67639}, {13037/20, 1.67639}, {13537/20, 1.67639}, {14037/20, 
   1.67639}, {14537/20, 1.67639}}, {{-(4963/20), 
   1.62463}, {-(4463/20), 1.63505}, {-(3963/20), 
   1.64601}, {-(3463/20), 1.65733}, {-(2963/20), 1.6689}, {-(2463/20),
    1.68069}, {-(1963/20), 1.69264}, {-(1463/20), 
   1.70474}, {-(963/20), 1.71698}, {-(463/20), 1.72932}, {37/20, 
   1.74177}, {537/20, 1.75433}, {1037/20, 1.76695}, {1537/20, 
   1.77967}, {2037/20, 1.79246}, {2537/20, 1.80531}, {3037/20, 
   1.81824}, {3537/20, 1.83123}, {4037/20, 1.84428}, {4537/20, 
   1.85739}, {5037/20, 1.87055}, {5537/20, 1.88376}, {6037/20, 
   1.89703}, {6537/20, 1.91034}, {7037/20, 1.9237}, {7537/20, 
   1.93711}, {8037/20, 1.95056}, {8537/20, 1.96405}, {9037/20, 
   1.97759}, {9537/20, 1.99117}, {10037/20, 2.00478}, {10537/20, 
   2.01843}, {11037/20, 2.03212}, {11537/20, 2.04585}, {12037/20, 
   2.05961}, {12537/20, 2.07341}, {13037/20, 2.08724}, {13537/20, 
   2.10111}, {14037/20, 2.115}, {14537/20, 2.12893}}, {{-(4963/20), 
   1.61898}, {-(4463/20), 1.6294}, {-(3963/20), 1.64036}, {-(3463/20),
    1.65168}, {-(2963/20), 1.66325}, {-(2463/20), 
   1.67504}, {-(1963/20), 1.687}, {-(1463/20), 1.6991}, {-(963/20), 
   1.71133}, {-(463/20), 1.72367}, {37/20, 1.73613}, {537/20, 
   1.74868}, {1037/20, 1.7613}, {1537/20, 1.77402}, {2037/20, 
   1.78681}, {2537/20, 1.79966}, {3037/20, 1.81259}, {3537/20, 
   1.82558}, {4037/20, 1.83863}, {4537/20, 1.85174}, {5037/20, 
   1.8649}, {5537/20, 1.87811}, {6037/20, 1.89138}, {6537/20, 
   1.90469}, {7037/20, 1.91805}, {7537/20, 1.93146}, {8037/20, 
   1.94491}, {8537/20, 1.9584}, {9037/20, 1.97194}, {9537/20, 
   1.98552}, {10037/20, 1.99913}, {10537/20, 2.01278}, {11037/20, 
   2.02647}, {11537/20, 2.0402}, {12037/20, 2.05396}, {12537/20, 
   2.06776}, {13037/20, 2.08159}, {13537/20, 2.09546}, {14037/20, 
   2.10935}, {14537/20, 2.12328}}, {{-(4963/20), 
   1.82555}, {-(4463/20), 1.83076}, {-(3963/20), 
   1.83624}, {-(3463/20), 1.8419}, {-(2963/20), 1.84769}, {-(2463/20),
    1.85358}, {-(1963/20), 1.85956}, {-(1463/20), 
   1.86561}, {-(963/20), 1.87172}, {-(463/20), 1.8779}, {37/20, 
   1.88412}, {537/20, 1.8904}, {1037/20, 1.89671}, {1537/20, 
   1.90307}, {2037/20, 1.90947}, {2537/20, 1.91589}, {3037/20, 
   1.92236}, {3537/20, 1.92885}, {4037/20, 1.93538}, {4537/20, 
   1.94193}, {5037/20, 1.94851}, {5537/20, 1.95512}, {6037/20, 
   1.96175}, {6537/20, 1.96841}, {7037/20, 1.97509}, {7537/20, 
   1.98179}, {8037/20, 1.98852}, {8537/20, 1.99526}, {9037/20, 
   2.00203}, {9537/20, 2.00882}, {10037/20, 2.01563}, {10537/20, 
   2.02245}, {11037/20, 2.0293}, {11537/20, 2.03616}, {12037/20, 
   2.04304}, {12537/20, 2.04994}, {13037/20, 2.05686}, {13537/20, 
   2.06379}, {14037/20, 2.07073}, {14537/20, 2.0777}}, {{-(4963/20), 
   1.74864}, {-(4463/20), 1.75386}, {-(3963/20), 
   1.75934}, {-(3463/20), 1.76499}, {-(2963/20), 
   1.77078}, {-(2463/20), 1.77667}, {-(1963/20), 
   1.78265}, {-(1463/20), 1.7887}, {-(963/20), 1.79482}, {-(463/20), 
   1.80099}, {37/20, 1.80722}, {537/20, 1.81349}, {1037/20, 
   1.81981}, {1537/20, 1.82617}, {2037/20, 1.83256}, {2537/20, 
   1.83899}, {3037/20, 1.84545}, {3537/20, 1.85194}, {4037/20, 
   1.85847}, {4537/20, 1.86502}, {5037/20, 1.8716}, {5537/20, 
   1.87821}, {6037/20, 1.88484}, {6537/20, 1.8915}, {7037/20, 
   1.89818}, {7537/20, 1.90488}, {8037/20, 1.91161}, {8537/20, 
   1.91836}, {9037/20, 1.92512}, {9537/20, 1.93191}, {10037/20, 
   1.93872}, {10537/20, 1.94555}, {11037/20, 1.95239}, {11537/20, 
   1.95926}, {12037/20, 1.96614}, {12537/20, 1.97303}, {13037/20, 
   1.97995}, {13537/20, 1.98688}, {14037/20, 1.99383}, {14537/20, 
   2.00079}}, {{-(4963/20), 1.73374}, {-(4463/20), 
   1.73896}, {-(3963/20), 1.74444}, {-(3463/20), 1.7501}, {-(2963/20),
    1.75588}, {-(2463/20), 1.76177}, {-(1963/20), 
   1.76775}, {-(1463/20), 1.7738}, {-(963/20), 1.77992}, {-(463/20), 
   1.78609}, {37/20, 1.79232}, {537/20, 1.79859}, {1037/20, 
   1.80491}, {1537/20, 1.81127}, {2037/20, 1.81766}, {2537/20, 
   1.82409}, {3037/20, 1.83055}, {3537/20, 1.83705}, {4037/20, 
   1.84357}, {4537/20, 1.85012}, {5037/20, 1.85671}, {5537/20, 
   1.86331}, {6037/20, 1.86995}, {6537/20, 1.8766}, {7037/20, 
   1.88328}, {7537/20, 1.88999}, {8037/20, 1.89671}, {8537/20, 
   1.90346}, {9037/20, 1.91022}, {9537/20, 1.91701}, {10037/20, 
   1.92382}, {10537/20, 1.93065}, {11037/20, 1.93749}, {11537/20, 
   1.94436}, {12037/20, 1.95124}, {12537/20, 1.95814}, {13037/20, 
   1.96505}, {13537/20, 1.97198}, {14037/20, 1.97893}, {14537/20, 
   1.98589}}, {{-(4963/20), 1.75651}, {-(4463/20), 
   1.76172}, {-(3963/20), 1.7672}, {-(3463/20), 1.77286}, {-(2963/20),
    1.77864}, {-(2463/20), 1.78454}, {-(1963/20), 
   1.79052}, {-(1463/20), 1.79656}, {-(963/20), 1.80268}, {-(463/20), 
   1.80885}, {37/20, 1.81508}, {537/20, 1.82136}, {1037/20, 
   1.82767}, {1537/20, 1.83403}, {2037/20, 1.84042}, {2537/20, 
   1.84685}, {3037/20, 1.85331}, {3537/20, 1.85981}, {4037/20, 
   1.86633}, {4537/20, 1.87289}, {5037/20, 1.87947}, {5537/20, 
   1.88607}, {6037/20, 1.89271}, {6537/20, 1.89936}, {7037/20, 
   1.90604}, {7537/20, 1.91275}, {8037/20, 1.91947}, {8537/20, 
   1.92622}, {9037/20, 1.93299}, {9537/20, 1.93978}, {10037/20, 
   1.94658}, {10537/20, 1.95341}, {11037/20, 1.96025}, {11537/20, 
   1.96712}, {12037/20, 1.974}, {12537/20, 1.9809}, {13037/20, 
   1.98781}, {13537/20, 1.99475}, {14037/20, 2.00169}, {14537/20, 
   2.00866}}, {{-(4963/20), 1.91449}, {-(4463/20), 
   1.90928}, {-(3963/20), 1.90379}, {-(3463/20), 
   1.89814}, {-(2963/20), 1.89235}, {-(2463/20), 
   1.88646}, {-(1963/20), 1.88048}, {-(1463/20), 1.87443}, {-(963/20),
    1.86831}, {-(463/20), 1.86214}, {37/20, 1.85591}, {537/20, 
   1.84964}, {1037/20, 1.84332}, {1537/20, 1.83697}, {2037/20, 
   1.83057}, {2537/20, 1.82414}, {3037/20, 1.81768}, {3537/20, 
   1.81119}, {4037/20, 1.80466}, {4537/20, 1.79811}, {5037/20, 
   1.79153}, {5537/20, 1.78492}, {6037/20, 1.77829}, {6537/20, 
   1.77163}, {7037/20, 1.76495}, {7537/20, 1.75825}, {8037/20, 
   1.75152}, {8537/20, 1.74478}, {9037/20, 1.73801}, {9537/20, 
   1.73122}, {10037/20, 1.72441}, {10537/20, 1.71758}, {11037/20, 
   1.71074}, {11537/20, 1.70388}, {12037/20, 1.697}, {12537/20, 
   1.6901}, {13037/20, 1.68318}, {13537/20, 1.67625}, {14037/20, 
   1.6693}, {14537/20, 1.66234}}, {{-(4963/20), 1.92372}, {-(4463/20),
    1.91851}, {-(3963/20), 1.91303}, {-(3463/20), 
   1.90737}, {-(2963/20), 1.90158}, {-(2463/20), 
   1.89569}, {-(1963/20), 1.88971}, {-(1463/20), 1.88366}, {-(963/20),
    1.87755}, {-(463/20), 1.87137}, {37/20, 1.86515}, {537/20, 
   1.85887}, {1037/20, 1.85256}, {1537/20, 1.8462}, {2037/20, 
   1.83981}, {2537/20, 1.83338}, {3037/20, 1.82691}, {3537/20, 
   1.82042}, {4037/20, 1.8139}, {4537/20, 1.80734}, {5037/20, 
   1.80076}, {5537/20, 1.79416}, {6037/20, 1.78752}, {6537/20, 
   1.78087}, {7037/20, 1.77418}, {7537/20, 1.76748}, {8037/20, 
   1.76075}, {8537/20, 1.75401}, {9037/20, 1.74724}, {9537/20, 
   1.74045}, {10037/20, 1.73365}, {10537/20, 1.72682}, {11037/20, 
   1.71997}, {11537/20, 1.71311}, {12037/20, 1.70623}, {12537/20, 
   1.69933}, {13037/20, 1.69241}, {13537/20, 1.68548}, {14037/20, 
   1.67854}, {14537/20, 1.67157}}, {{-(4963/20), 
   1.78417}, {-(4463/20), 1.77895}, {-(3963/20), 
   1.77347}, {-(3463/20), 1.76781}, {-(2963/20), 
   1.76203}, {-(2463/20), 1.75614}, {-(1963/20), 
   1.75016}, {-(1463/20), 1.74411}, {-(963/20), 1.73799}, {-(463/20), 
   1.73182}, {37/20, 1.72559}, {537/20, 1.71932}, {1037/20, 
   1.713}, {1537/20, 1.70664}, {2037/20, 1.70025}, {2537/20, 
   1.69382}, {3037/20, 1.68736}, {3537/20, 1.68086}, {4037/20, 
   1.67434}, {4537/20, 1.66779}, {5037/20, 1.6612}, {5537/20, 
   1.6546}, {6037/20, 1.64796}, {6537/20, 1.64131}, {7037/20, 
   1.63463}, {7537/20, 1.62792}, {8037/20, 1.6212}, {8537/20, 
   1.61445}, {9037/20, 1.60769}, {9537/20, 1.6009}, {10037/20, 
   1.59409}, {10537/20, 1.58726}, {11037/20, 1.58042}, {11537/20, 
   1.57355}, {12037/20, 1.56667}, {12537/20, 1.55977}, {13037/20, 
   1.55286}, {13537/20, 1.54593}, {14037/20, 1.53898}, {14537/20, 
   1.53202}}}

When I try to plot that with Callout, the colors of the leaders are wrong:

labelNames = Table["abcdef", Length@data];
SeedRandom[1234];
colors = RandomSample[ColorData["Atoms", "ColorList"], 
   Length@labelNames];
ListLinePlot[
 MapThread[
  Callout[#1, #2, CalloutStyle -> #3, 
    LabelStyle -> Directive[Bold, Medium, #3]] &, {data, labelNames, 
   colors}], PlotStyle -> colors, ImageSize -> Large]

But, when I use another similarly constructed data, the results are satisfying:

anotherData = Table[{x, a*x}, {a, -7, 6, 1}, {x, -5, 5}];
ListLinePlot[
 MapThread[
  Callout[#1, #2, CalloutStyle -> #3, 
    LabelStyle -> Directive[Bold, Medium, #3]] &, {anotherData, 
   labelNames, colors}], PlotStyle -> colors, ImageSize -> Large]

What's wrong?

Try adding PlotRange->All - Looks like ListPlot is getting confused if some of the curves are not displayed at all, leading to the callouts being assigned to the wrong curves. — Lukas Lang, Apr 27 at 17:36
Unfortunately I don't want these 2 remaining plots to be visible by default — Lechuu, Apr 28 at 12:35

kglr · Accepted Answer · 2023-04-28 01:26:54Z

A work-around: Rotate the data two steps to the left (using RotateLeft[data,2]) so that the two datasets excluded from plot under the default setting for PlotRange are the last two datasets. (Alternatively, you can sort the input datasets by the vertical value of the last points to move the first two data sets to the end of the list.)

labelNames = Table["abc" <> ToString[i], {i, Length@data}];

SeedRandom[1234];
colors = RandomSample[ColorData["Atoms", "ColorList"], Length @ labelNames];


dataWcallouts = MapThread[
  Callout[#, #2, CalloutStyle -> #3, 
    LabelStyle -> Directive[Bold, Medium, #3]] &, 
  {RotateLeft[data, 2], RotateLeft[labelNames,2], RotateLeft[colors,2]}];


ListLinePlot[dataWcallouts, PlotStyle ->  RotateLeft[colors,2], 
 ImageSize -> Large]

ListLinePlot[dataWcallouts, PlotStyle ->  RotateLeft[colors,2], 
 ImageSize -> Large, PlotRange -> {1.5,.2.2}]

With PlotRange -> All we get

Thank You for Your answer! Rotating is not really useful since I'm not sure which of the plots will have the highest value, so I would prefer sorting. In order to do that I have to join in list the name of the labels with data (so the labels will be sorted with data as well) and then sort by last y element in all sublists: SortBy[ Thread@{labelNames, data}, #[[-1, -1, -1]] &] — Lechuu, Apr 28 at 10:15

Stack Exchange Network

Wrong Callout leader colors combined with specific data

1 Answer 1

Your Answer

Not the answer you're looking for? Browse other questions tagged
plotting
labeling
or ask your own question.

Hot Network Questions

Wrong Callout leader colors combined with specific data

1 Answer 1

Your Answer

Sign up or log in

Post as a guest

Not the answer you're looking for? Browse other questions tagged plottinglabeling or ask your own question.

Related

Hot Network Questions

Not the answer you're looking for? Browse other questions tagged
plotting
labeling
or ask your own question.