Partitioning values in a sequenceOrdering the elements in a list and separate them into sublists for plottingFinding all partitions of a setPartitioning an image based on featuresPartition list into a given number of sub-listsPartitioning List Into Sublists of Length 2 With The Pairing Being RandomCluster numbers into n partitions so that each partitions sum is closest to total/nEfficient lazy weak compositionsTiming and memory use is critical:fast partitioning of binary sparse arrayVariable iterator in Do Loop (splitting a list)Non-Constant Partitioning of a List with Order AnalysisTotally orderless partition

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Partitioning values in a sequence


Ordering the elements in a list and separate them into sublists for plottingFinding all partitions of a setPartitioning an image based on featuresPartition list into a given number of sub-listsPartitioning List Into Sublists of Length 2 With The Pairing Being RandomCluster numbers into n partitions so that each partitions sum is closest to total/nEfficient lazy weak compositionsTiming and memory use is critical:fast partitioning of binary sparse arrayVariable iterator in Do Loop (splitting a list)Non-Constant Partitioning of a List with Order AnalysisTotally orderless partition













2












$begingroup$


I have a sequence that forms visible lines when plotted as a graph, what would be a good way to automatically partition the sequence to create a list of sequences, one for each line that is visible when the sequence is plotted?



Here is the start of the sequence:



list = 2,3,5,11,7,23,13,29,41,17,53,37,83,43,89,19,113,131,67,47,73,31,79,173,179,61,191,97,233,239,251,127,139,281,71,293,101,103,107,163,59,359,193,199,137,419,431,443,151,491,509,181,109,277,593,149,307,641,653,659,683,719,241,743,373,761,257,157,263,809,271,409,283,433,911,311,313,953,487,331,499,1013,1019,1031,347,1049,211,269,367,1103,577,167,397,1223,1229,619,1289,223,673,229,461,467,1409,709,1439,1451,727,739,1481,1499,503,1511,1559,1583,1601,401,557,337,853,1733,349,883,197;


Thanks.



cheers,
Jamie










share|improve this question











$endgroup$











  • $begingroup$
    Possible duplicate of ordering-the-elements-in-a-list-and-separate-them-into-sublists-for-plotting
    $endgroup$
    – MelaGo
    5 hours ago















2












$begingroup$


I have a sequence that forms visible lines when plotted as a graph, what would be a good way to automatically partition the sequence to create a list of sequences, one for each line that is visible when the sequence is plotted?



Here is the start of the sequence:



list = 2,3,5,11,7,23,13,29,41,17,53,37,83,43,89,19,113,131,67,47,73,31,79,173,179,61,191,97,233,239,251,127,139,281,71,293,101,103,107,163,59,359,193,199,137,419,431,443,151,491,509,181,109,277,593,149,307,641,653,659,683,719,241,743,373,761,257,157,263,809,271,409,283,433,911,311,313,953,487,331,499,1013,1019,1031,347,1049,211,269,367,1103,577,167,397,1223,1229,619,1289,223,673,229,461,467,1409,709,1439,1451,727,739,1481,1499,503,1511,1559,1583,1601,401,557,337,853,1733,349,883,197;


Thanks.



cheers,
Jamie










share|improve this question











$endgroup$











  • $begingroup$
    Possible duplicate of ordering-the-elements-in-a-list-and-separate-them-into-sublists-for-plotting
    $endgroup$
    – MelaGo
    5 hours ago













2












2








2





$begingroup$


I have a sequence that forms visible lines when plotted as a graph, what would be a good way to automatically partition the sequence to create a list of sequences, one for each line that is visible when the sequence is plotted?



Here is the start of the sequence:



list = 2,3,5,11,7,23,13,29,41,17,53,37,83,43,89,19,113,131,67,47,73,31,79,173,179,61,191,97,233,239,251,127,139,281,71,293,101,103,107,163,59,359,193,199,137,419,431,443,151,491,509,181,109,277,593,149,307,641,653,659,683,719,241,743,373,761,257,157,263,809,271,409,283,433,911,311,313,953,487,331,499,1013,1019,1031,347,1049,211,269,367,1103,577,167,397,1223,1229,619,1289,223,673,229,461,467,1409,709,1439,1451,727,739,1481,1499,503,1511,1559,1583,1601,401,557,337,853,1733,349,883,197;


Thanks.



cheers,
Jamie










share|improve this question











$endgroup$




I have a sequence that forms visible lines when plotted as a graph, what would be a good way to automatically partition the sequence to create a list of sequences, one for each line that is visible when the sequence is plotted?



Here is the start of the sequence:



list = 2,3,5,11,7,23,13,29,41,17,53,37,83,43,89,19,113,131,67,47,73,31,79,173,179,61,191,97,233,239,251,127,139,281,71,293,101,103,107,163,59,359,193,199,137,419,431,443,151,491,509,181,109,277,593,149,307,641,653,659,683,719,241,743,373,761,257,157,263,809,271,409,283,433,911,311,313,953,487,331,499,1013,1019,1031,347,1049,211,269,367,1103,577,167,397,1223,1229,619,1289,223,673,229,461,467,1409,709,1439,1451,727,739,1481,1499,503,1511,1559,1583,1601,401,557,337,853,1733,349,883,197;


Thanks.



cheers,
Jamie







partitions






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited 22 mins ago









user64494

3,65311122




3,65311122










asked 6 hours ago









Jamie MJamie M

475




475











  • $begingroup$
    Possible duplicate of ordering-the-elements-in-a-list-and-separate-them-into-sublists-for-plotting
    $endgroup$
    – MelaGo
    5 hours ago
















  • $begingroup$
    Possible duplicate of ordering-the-elements-in-a-list-and-separate-them-into-sublists-for-plotting
    $endgroup$
    – MelaGo
    5 hours ago















$begingroup$
Possible duplicate of ordering-the-elements-in-a-list-and-separate-them-into-sublists-for-plotting
$endgroup$
– MelaGo
5 hours ago




$begingroup$
Possible duplicate of ordering-the-elements-in-a-list-and-separate-them-into-sublists-for-plotting
$endgroup$
– MelaGo
5 hours ago










2 Answers
2






active

oldest

votes


















1












$begingroup$

You could for instance fit a mean polynomial function through the data:



fun = NonlinearModelFit[list, a x^2 + b x + c , a, b, c, x] //Normal



-48.3941 + 6.86017 x + 0.0161064 x^2




This will separarate the upper line from the lower line that you can see in the plot:



Show[
ListLinePlot[list, PlotRange -> All],
Plot[fun, x, 0, 125, PlotRange -> All, PlotStyle -> Red],
PlotRange -> All]


enter image description here



Then you can simply run through the list and separate it into two lists based on whether the value is above or below the mean fit:



upperLine = ;
lowerLine = ;
Do[
If[list[[x]] > fun,
AppendTo[upperLine, x, list[[x]]],
AppendTo[lowerLine, x, list[[x]]]];
, x, 1, Length[list]]


The upperLine and lowerLine data sets then look like:



ListLinePlot[upperLine], ListLinePlot[lowerLine]


enter image description here



Repeat the process on the lowerLine data to separate the sequences further.






share|improve this answer











$endgroup$




















    2












    $begingroup$

    list = 2, 3, 5, 11, 7, 23, 13, 29, 41, 17, 53, 37, 83, 43, 89, 19, 
    113, 131, 67, 47, 73, 31, 79, 173, 179, 61, 191, 97, 233, 239, 251,
    127, 139, 281, 71, 293, 101, 103, 107, 163, 59, 359, 193, 199,
    137, 419, 431, 443, 151, 491, 509, 181, 109, 277, 593, 149, 307,
    641, 653, 659, 683, 719, 241, 743, 373, 761, 257, 157, 263, 809,
    271, 409, 283, 433, 911, 311, 313, 953, 487, 331, 499, 1013, 1019,
    1031, 347, 1049, 211, 269, 367, 1103, 577, 167, 397, 1223, 1229,
    619, 1289, 223, 673, 229, 461, 467, 1409, 709, 1439, 1451, 727,
    739, 1481, 1499, 503, 1511, 1559, 1583, 1601, 401, 557, 337, 853,
    1733, 349, 883, 197;

    upper = FindPeaks[list];

    lower = 1, -1 # & /@ FindPeaks[-list];

    ListLinePlot[list, lower, upper,
    PlotStyle -> LightGray, Blue, Red]


    enter image description here






    share|improve this answer









    $endgroup$













      Your Answer








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      2 Answers
      2






      active

      oldest

      votes








      2 Answers
      2






      active

      oldest

      votes









      active

      oldest

      votes






      active

      oldest

      votes









      1












      $begingroup$

      You could for instance fit a mean polynomial function through the data:



      fun = NonlinearModelFit[list, a x^2 + b x + c , a, b, c, x] //Normal



      -48.3941 + 6.86017 x + 0.0161064 x^2




      This will separarate the upper line from the lower line that you can see in the plot:



      Show[
      ListLinePlot[list, PlotRange -> All],
      Plot[fun, x, 0, 125, PlotRange -> All, PlotStyle -> Red],
      PlotRange -> All]


      enter image description here



      Then you can simply run through the list and separate it into two lists based on whether the value is above or below the mean fit:



      upperLine = ;
      lowerLine = ;
      Do[
      If[list[[x]] > fun,
      AppendTo[upperLine, x, list[[x]]],
      AppendTo[lowerLine, x, list[[x]]]];
      , x, 1, Length[list]]


      The upperLine and lowerLine data sets then look like:



      ListLinePlot[upperLine], ListLinePlot[lowerLine]


      enter image description here



      Repeat the process on the lowerLine data to separate the sequences further.






      share|improve this answer











      $endgroup$

















        1












        $begingroup$

        You could for instance fit a mean polynomial function through the data:



        fun = NonlinearModelFit[list, a x^2 + b x + c , a, b, c, x] //Normal



        -48.3941 + 6.86017 x + 0.0161064 x^2




        This will separarate the upper line from the lower line that you can see in the plot:



        Show[
        ListLinePlot[list, PlotRange -> All],
        Plot[fun, x, 0, 125, PlotRange -> All, PlotStyle -> Red],
        PlotRange -> All]


        enter image description here



        Then you can simply run through the list and separate it into two lists based on whether the value is above or below the mean fit:



        upperLine = ;
        lowerLine = ;
        Do[
        If[list[[x]] > fun,
        AppendTo[upperLine, x, list[[x]]],
        AppendTo[lowerLine, x, list[[x]]]];
        , x, 1, Length[list]]


        The upperLine and lowerLine data sets then look like:



        ListLinePlot[upperLine], ListLinePlot[lowerLine]


        enter image description here



        Repeat the process on the lowerLine data to separate the sequences further.






        share|improve this answer











        $endgroup$















          1












          1








          1





          $begingroup$

          You could for instance fit a mean polynomial function through the data:



          fun = NonlinearModelFit[list, a x^2 + b x + c , a, b, c, x] //Normal



          -48.3941 + 6.86017 x + 0.0161064 x^2




          This will separarate the upper line from the lower line that you can see in the plot:



          Show[
          ListLinePlot[list, PlotRange -> All],
          Plot[fun, x, 0, 125, PlotRange -> All, PlotStyle -> Red],
          PlotRange -> All]


          enter image description here



          Then you can simply run through the list and separate it into two lists based on whether the value is above or below the mean fit:



          upperLine = ;
          lowerLine = ;
          Do[
          If[list[[x]] > fun,
          AppendTo[upperLine, x, list[[x]]],
          AppendTo[lowerLine, x, list[[x]]]];
          , x, 1, Length[list]]


          The upperLine and lowerLine data sets then look like:



          ListLinePlot[upperLine], ListLinePlot[lowerLine]


          enter image description here



          Repeat the process on the lowerLine data to separate the sequences further.






          share|improve this answer











          $endgroup$



          You could for instance fit a mean polynomial function through the data:



          fun = NonlinearModelFit[list, a x^2 + b x + c , a, b, c, x] //Normal



          -48.3941 + 6.86017 x + 0.0161064 x^2




          This will separarate the upper line from the lower line that you can see in the plot:



          Show[
          ListLinePlot[list, PlotRange -> All],
          Plot[fun, x, 0, 125, PlotRange -> All, PlotStyle -> Red],
          PlotRange -> All]


          enter image description here



          Then you can simply run through the list and separate it into two lists based on whether the value is above or below the mean fit:



          upperLine = ;
          lowerLine = ;
          Do[
          If[list[[x]] > fun,
          AppendTo[upperLine, x, list[[x]]],
          AppendTo[lowerLine, x, list[[x]]]];
          , x, 1, Length[list]]


          The upperLine and lowerLine data sets then look like:



          ListLinePlot[upperLine], ListLinePlot[lowerLine]


          enter image description here



          Repeat the process on the lowerLine data to separate the sequences further.







          share|improve this answer














          share|improve this answer



          share|improve this answer








          edited 5 hours ago

























          answered 5 hours ago









          KagaratschKagaratsch

          4,87531348




          4,87531348





















              2












              $begingroup$

              list = 2, 3, 5, 11, 7, 23, 13, 29, 41, 17, 53, 37, 83, 43, 89, 19, 
              113, 131, 67, 47, 73, 31, 79, 173, 179, 61, 191, 97, 233, 239, 251,
              127, 139, 281, 71, 293, 101, 103, 107, 163, 59, 359, 193, 199,
              137, 419, 431, 443, 151, 491, 509, 181, 109, 277, 593, 149, 307,
              641, 653, 659, 683, 719, 241, 743, 373, 761, 257, 157, 263, 809,
              271, 409, 283, 433, 911, 311, 313, 953, 487, 331, 499, 1013, 1019,
              1031, 347, 1049, 211, 269, 367, 1103, 577, 167, 397, 1223, 1229,
              619, 1289, 223, 673, 229, 461, 467, 1409, 709, 1439, 1451, 727,
              739, 1481, 1499, 503, 1511, 1559, 1583, 1601, 401, 557, 337, 853,
              1733, 349, 883, 197;

              upper = FindPeaks[list];

              lower = 1, -1 # & /@ FindPeaks[-list];

              ListLinePlot[list, lower, upper,
              PlotStyle -> LightGray, Blue, Red]


              enter image description here






              share|improve this answer









              $endgroup$

















                2












                $begingroup$

                list = 2, 3, 5, 11, 7, 23, 13, 29, 41, 17, 53, 37, 83, 43, 89, 19, 
                113, 131, 67, 47, 73, 31, 79, 173, 179, 61, 191, 97, 233, 239, 251,
                127, 139, 281, 71, 293, 101, 103, 107, 163, 59, 359, 193, 199,
                137, 419, 431, 443, 151, 491, 509, 181, 109, 277, 593, 149, 307,
                641, 653, 659, 683, 719, 241, 743, 373, 761, 257, 157, 263, 809,
                271, 409, 283, 433, 911, 311, 313, 953, 487, 331, 499, 1013, 1019,
                1031, 347, 1049, 211, 269, 367, 1103, 577, 167, 397, 1223, 1229,
                619, 1289, 223, 673, 229, 461, 467, 1409, 709, 1439, 1451, 727,
                739, 1481, 1499, 503, 1511, 1559, 1583, 1601, 401, 557, 337, 853,
                1733, 349, 883, 197;

                upper = FindPeaks[list];

                lower = 1, -1 # & /@ FindPeaks[-list];

                ListLinePlot[list, lower, upper,
                PlotStyle -> LightGray, Blue, Red]


                enter image description here






                share|improve this answer









                $endgroup$















                  2












                  2








                  2





                  $begingroup$

                  list = 2, 3, 5, 11, 7, 23, 13, 29, 41, 17, 53, 37, 83, 43, 89, 19, 
                  113, 131, 67, 47, 73, 31, 79, 173, 179, 61, 191, 97, 233, 239, 251,
                  127, 139, 281, 71, 293, 101, 103, 107, 163, 59, 359, 193, 199,
                  137, 419, 431, 443, 151, 491, 509, 181, 109, 277, 593, 149, 307,
                  641, 653, 659, 683, 719, 241, 743, 373, 761, 257, 157, 263, 809,
                  271, 409, 283, 433, 911, 311, 313, 953, 487, 331, 499, 1013, 1019,
                  1031, 347, 1049, 211, 269, 367, 1103, 577, 167, 397, 1223, 1229,
                  619, 1289, 223, 673, 229, 461, 467, 1409, 709, 1439, 1451, 727,
                  739, 1481, 1499, 503, 1511, 1559, 1583, 1601, 401, 557, 337, 853,
                  1733, 349, 883, 197;

                  upper = FindPeaks[list];

                  lower = 1, -1 # & /@ FindPeaks[-list];

                  ListLinePlot[list, lower, upper,
                  PlotStyle -> LightGray, Blue, Red]


                  enter image description here






                  share|improve this answer









                  $endgroup$



                  list = 2, 3, 5, 11, 7, 23, 13, 29, 41, 17, 53, 37, 83, 43, 89, 19, 
                  113, 131, 67, 47, 73, 31, 79, 173, 179, 61, 191, 97, 233, 239, 251,
                  127, 139, 281, 71, 293, 101, 103, 107, 163, 59, 359, 193, 199,
                  137, 419, 431, 443, 151, 491, 509, 181, 109, 277, 593, 149, 307,
                  641, 653, 659, 683, 719, 241, 743, 373, 761, 257, 157, 263, 809,
                  271, 409, 283, 433, 911, 311, 313, 953, 487, 331, 499, 1013, 1019,
                  1031, 347, 1049, 211, 269, 367, 1103, 577, 167, 397, 1223, 1229,
                  619, 1289, 223, 673, 229, 461, 467, 1409, 709, 1439, 1451, 727,
                  739, 1481, 1499, 503, 1511, 1559, 1583, 1601, 401, 557, 337, 853,
                  1733, 349, 883, 197;

                  upper = FindPeaks[list];

                  lower = 1, -1 # & /@ FindPeaks[-list];

                  ListLinePlot[list, lower, upper,
                  PlotStyle -> LightGray, Blue, Red]


                  enter image description here







                  share|improve this answer












                  share|improve this answer



                  share|improve this answer










                  answered 1 hour ago









                  Bob HanlonBob Hanlon

                  61.9k33598




                  61.9k33598



























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                      Францішак Багушэвіч Змест Сям'я | Біяграфія | Творчасць | Мова Багушэвіча | Ацэнкі дзейнасці | Цікавыя факты | Спадчына | Выбраная бібліяграфія | Ушанаванне памяці | У філатэліі | Зноскі | Літаратура | Спасылкі | НавігацыяЛяхоўскі У. Рупіўся дзеля Бога і людзей: Жыццёвы шлях Лявона Вітан-Дубейкаўскага // Вольскі і Памідораў з песняй пра немца Адвакат, паэт, народны заступнік Ашмянскі веснікВ Минске появится площадь Богушевича и улица Сырокомли, Белорусская деловая газета, 19 июля 2001 г.Айцец беларускай нацыянальнай ідэі паўстаў у бронзе Сяргей Аляксандравіч Адашкевіч (1918, Мінск). 80-я гады. Бюст «Францішак Багушэвіч».Яўген Мікалаевіч Ціхановіч. «Партрэт Францішка Багушэвіча»Мікола Мікалаевіч Купава. «Партрэт зачынальніка новай беларускай літаратуры Францішка Багушэвіча»Уладзімір Іванавіч Мелехаў. На помніку «Змагарам за родную мову» Барэльеф «Францішак Багушэвіч»Памяць пра Багушэвіча на Віленшчыне Страчаная сталіца. Беларускія шыльды на вуліцах Вільні«Krynica». Ideologia i przywódcy białoruskiego katolicyzmuФранцішак БагушэвічТворы на knihi.comТворы Францішка Багушэвіча на bellib.byСодаль Уладзімір. Францішак Багушэвіч на Лідчыне;Луцкевіч Антон. Жыцьцё і творчасьць Фр. Багушэвіча ў успамінах ягоных сучасьнікаў // Запісы Беларускага Навуковага таварыства. Вільня, 1938. Сшытак 1. С. 16-34.Большая российская1188761710000 0000 5537 633Xn9209310021619551927869394п

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                      ValueError: Expected n_neighbors <= n_samples, but n_samples = 1, n_neighbors = 6 (SMOTE) The 2019 Stack Overflow Developer Survey Results Are InCan SMOTE be applied over sequence of words (sentences)?ValueError when doing validation with random forestsSMOTE and multi class oversamplingLogic behind SMOTE-NC?ValueError: Error when checking target: expected dense_1 to have shape (7,) but got array with shape (1,)SmoteBoost: Should SMOTE be ran individually for each iteration/tree in the boosting?solving multi-class imbalance classification using smote and OSSUsing SMOTE for Synthetic Data generation to improve performance on unbalanced dataproblem of entry format for a simple model in KerasSVM SMOTE fit_resample() function runs forever with no result