CCBH-PLPP-ExclusionKxM.nb

(* Content-type: application/vnd.wolfram.mathematica *)

(*** Wolfram Notebook File ***)
(* http://www.wolfram.com/nb *)

(* CreatedBy='Mathematica 13.3' *)

(*CacheID: 234*)
(* Internal cache information:
NotebookFileLineBreakTest
NotebookFileLineBreakTest
NotebookDataPosition[       158,          7]
NotebookDataLength[    928569,      16897]
NotebookOptionsPosition[    903603,      16382]
NotebookOutlinePosition[    922354,      16800]
CellTagsIndexPosition[    922311,      16797]
WindowFrame->Normal*)

(* Beginning of Notebook Content *)
Notebook[{

Cell[CellGroupData[{
Cell["\<\
CCBH-PLPP: 
k x minMass exclusion plots\
\>", "Title",
 CellChangeTimes->{{3.892809052251095*^9, 3.8928090758754387`*^9}, {
   3.8928093415435677`*^9, 3.892809359178206*^9}, {3.8941835007784157`*^9, 
   3.89418350319659*^9}, {3.896430772401395*^9, 3.8964307858912153`*^9}, {
   3.897587291657257*^9, 3.8975872929931507`*^9}, {3.9055936221203012`*^9, 
   3.905593670796692*^9}, 3.905596689976119*^9, {3.90566211935399*^9, 
   3.905662124962286*^9}, {3.905777553583708*^9, 3.905777560220936*^9}, {
   3.905777820108095*^9, 3.905777834894508*^9}, {3.905871308092004*^9, 
   3.905871309187036*^9}},ExpressionUUID->"653c41f3-823d-4cf8-b781-\
a41f077bbcfc"],

Cell["Davi  C. Rodrigues (this code). October, 2023.", "Author",
 CellChangeTimes->{{3.8928090989746637`*^9, 3.892809125175556*^9}, {
  3.8941858448205843`*^9, 3.894185868361772*^9}, {3.896430794793159*^9, 
  3.896430795072702*^9}, {3.897587315909387*^9, 3.897587317675598*^9}, {
  3.904992726076982*^9, 3.9049927299908237`*^9}, {3.905593651314418*^9, 
  3.905593658488803*^9}},ExpressionUUID->"73931733-b35f-48f8-8bcc-\
eb6ec5be6ab0"],

Cell[BoxData[
 RowBox[{
  RowBox[{"ResourceFunction", "[", "\"\<DarkMode\>\"", "]"}], "[", 
  "]"}]], "Input",
 CellChangeTimes->{{3.892799813685648*^9, 3.8927998284060717`*^9}},
 CellLabel->
  "In[306]:=",ExpressionUUID->"ddd5e9c3-34d0-4b0a-b34b-8a5223c82817"],

Cell["\<\
CCBH = Cosmologically coupled black hole (general case)
DEBH = Dark energy coupled Black Hole (implies k = - 3w)
GBH = Growing BH, k is arbitrary and without direct dark energy impact.
m1 = primary (larger) mass of the BBH or NSBH pair.

Naming conventions:
All defined variables/functions start with lower case letter.
\[OpenCurlyDoubleQuote]I\[CloseCurlyDoubleQuote] at the end of a function \
name: interpolated version. 
\[OpenCurlyDoubleQuote]Raw\[CloseCurlyDoubleQuote]: a function without \
options. It is useful to store results. The version with options is based on \
the raw version.\
\>", "Text",
 CellChangeTimes->{{3.89758608446937*^9, 
  3.897586139097683*^9}},ExpressionUUID->"f18ff450-c45b-41f8-b278-\
99649fcf1000"],

Cell[CellGroupData[{

Cell["Starting...", "Section",
 CellChangeTimes->{{3.892540741919739*^9, 
  3.892540747834675*^9}},ExpressionUUID->"35ad3a7f-17be-4ab9-ad4a-\
e711b8a076ac"],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"SetDirectory", "[", 
   RowBox[{"NotebookDirectory", "[", "]"}], "]"}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"Get", "[", 
    RowBox[{"FileNameJoin", "[", 
     RowBox[{"{", 
      RowBox[{"\"\<codes\>\"", ",", " ", "\"\<Directories.wl\>\""}], "}"}], 
     "]"}], "]"}], ";"}], "\n", "\n", 
  RowBox[{"(*", "\n", "  ", 
   RowBox[{"Calling", " ", "wl", " ", 
    RowBox[{
    "files", "\n", "  ", "**", "**", "**", "**", "**", "**", "**", "**"}], 
    "*"}], " ", "\n", "*)"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{"getCode", "[", "\"\<Constants.wl\>\"", "]"}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"baseSimPoints", " ", "=", " ", 
    RowBox[{"5", " ", 
     SuperscriptBox["10", "5"]}]}], 
   StyleBox[";",
    FontColor->RGBColor[1, 0.5, 0.5]]}], " ", 
  RowBox[{"(*", 
   RowBox[{
    RowBox[{
    "The", " ", "base", " ", "number", " ", "of", " ", "points", " ", "to", 
     " ", "be", " ", "simmulated", " ", "for", " ", "each", " ", 
     "dimension"}], ",", " ", 
    RowBox[{
     RowBox[{"commonly", " ", 
      SuperscriptBox["10", "5"]}], "-", 
     SuperscriptBox["10", "7"]}], ",", " ", 
    RowBox[{"depends", " ", "on", " ", "the", " ", 
     RowBox[{"purpose", "."}]}]}], "*)"}], "\n", "\n", 
  RowBox[{"(*", 
   RowBox[{
    RowBox[{"getCode", "[", "\"\<ObsDataPreparationGWTC-3.wl\>\"", "]"}], 
    ";"}], " ", "*)"}]}], "\n", 
 RowBox[{
  RowBox[{"getCode", "[", "\"\<PowerLawPlusPeakDefinition.wl\>\"", "]"}], 
  ";"}], "\n", 
 RowBox[{
  RowBox[{"getCode", "[", "\"\<Cosmology.wl\>\"", "]"}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"getCode", "[", "\"\<MassFactorCorrection.wl\>\"", "]"}], ";"}], 
  "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"Print", "[", "\"\<End of running wl files.\>\"", "]"}], ";"}], 
  "\n", "\n", 
  RowBox[{"(*", "\n", "  ", 
   RowBox[{"GENERAL", " ", "PURPOSE", " ", 
    RowBox[{"FUNCTIONS", "\n", "  ", "**", "**", "**"}], "*", 
    RowBox[{"**", "**", "**", "**", "**", "**", "**", "**", "**"}], "*"}], 
   "\n", "*)"}], "\n", "\n", 
  RowBox[{"(*", 
   RowBox[{"Better", " ", 
    RowBox[{"names", ":", " ", 
     RowBox[{
      RowBox[{"probSigma", "[", "nSigma_", "]"}], " ", "and", " ", 
      RowBox[{"sigmaProb", "[", "prob_", "]"}]}]}]}], "*)"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"sigmaProb", "::", "usage"}], " ", "=", " ", 
   "\"\<sigmaProb[probability] yields the number of \[Sigma]'s for a given \
probability.\>\""}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"sigmaProb", "[", "prob_", "]"}], " ", ":=", " ", 
    RowBox[{"Block", "[", 
     RowBox[{
      RowBox[{"{", "sigma", "}"}], ",", " ", "\n", "  ", 
      RowBox[{"sigma", " ", "/.", " ", 
       RowBox[{"FindRoot", "[", 
        RowBox[{
         RowBox[{
          RowBox[{"NProbability", "[", 
           RowBox[{
            RowBox[{
             RowBox[{"RealAbs", "[", "x", "]"}], " ", ">", " ", "sigma"}], 
            " ", ",", " ", 
            RowBox[{"x", "\[Distributed]", 
             RowBox[{"NormalDistribution", "[", "]"}]}]}], "]"}], " ", "==", 
          " ", "prob"}], ",", " ", 
         RowBox[{"{", 
          RowBox[{"sigma", ",", " ", "0", ",", " ", "10"}], "}"}]}], 
        "]"}]}]}], "\n", "]"}]}], ";"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{"Clear", "[", "probSigma", "]"}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"probSigma", "[", "n_", "]"}], " ", ":=", " ", 
   RowBox[{
    RowBox[{"probSigma", "[", "n", "]"}], " ", "=", " ", 
    RowBox[{"NProbability", "[", 
     RowBox[{
      RowBox[{
       RowBox[{"RealAbs", "[", "x", "]"}], " ", ">", " ", "n"}], ",", " ", 
      RowBox[{"x", "\[Distributed]", 
       RowBox[{"NormalDistribution", "[", "]"}]}]}], "]"}]}]}], 
  ";"}]}], "Code",
 CellChangeTimes->{{3.890405952132571*^9, 3.890405962875386*^9}, 
   3.8912495850778008`*^9, {3.891867198632307*^9, 3.891867232380671*^9}, {
   3.891924027133012*^9, 3.8919240482809477`*^9}, {3.892540720161084*^9, 
   3.8925407207241993`*^9}, 3.892540766437785*^9, {3.892542411553705*^9, 
   3.892542431121139*^9}, {3.892542469542163*^9, 3.8925424700070343`*^9}, {
   3.892809136571782*^9, 3.89280914017656*^9}, {3.8928099459584846`*^9, 
   3.892809947109489*^9}, {3.892979682469141*^9, 3.892979718581959*^9}, {
   3.892980095932384*^9, 3.892980095971232*^9}, {3.892980384744761*^9, 
   3.8929804188129683`*^9}, 3.892980527567075*^9, {3.8929863495429173`*^9, 
   3.892986390010213*^9}, {3.892986542616708*^9, 3.8929865751055307`*^9}, 
   3.8929866538048487`*^9, {3.89332995280258*^9, 3.893329958063043*^9}, {
   3.8934953811132517`*^9, 3.8934954458421097`*^9}, {3.8934955417247133`*^9, 
   3.893495596572521*^9}, {3.893495629922421*^9, 3.893495636234009*^9}, {
   3.893496837289377*^9, 3.8934970140495243`*^9}, {3.893497113303534*^9, 
   3.8934971904258537`*^9}, {3.893497369880354*^9, 3.893497372446368*^9}, {
   3.893497424556761*^9, 3.893497428882648*^9}, {3.893497547152622*^9, 
   3.893497569068033*^9}, {3.893497846784445*^9, 3.8934978472930613`*^9}, {
   3.8934980220067253`*^9, 3.8934980474539833`*^9}, {3.893498104115862*^9, 
   3.893498191664219*^9}, {3.893498235748246*^9, 3.893498334017685*^9}, {
   3.8934983730286417`*^9, 3.893498407177032*^9}, {3.8934984499484453`*^9, 
   3.893498452097323*^9}, {3.8934985673587437`*^9, 3.8934988311063843`*^9}, {
   3.893498872725039*^9, 3.893498972458514*^9}, {3.893499021755474*^9, 
   3.8934990450277033`*^9}, {3.893499107293591*^9, 3.893499111280452*^9}, {
   3.8934994009885883`*^9, 3.8934994816660833`*^9}, {3.893499946254382*^9, 
   3.89350000984411*^9}, {3.893505695486004*^9, 3.893505703134789*^9}, {
   3.893520111454988*^9, 3.893520215830523*^9}, {3.893577043128602*^9, 
   3.8935770478313932`*^9}, {3.893588606939389*^9, 3.893588662557934*^9}, {
   3.893588726557206*^9, 3.893588794789784*^9}, {3.893595417369598*^9, 
   3.8935954177814093`*^9}, {3.893599723623033*^9, 3.893599776315145*^9}, {
   3.893603132350545*^9, 3.893603132400655*^9}, {3.893605879722896*^9, 
   3.893605881471878*^9}, {3.893829767053582*^9, 3.893829803266925*^9}, {
   3.893829958369924*^9, 3.8938299724968*^9}, {3.893830010380629*^9, 
   3.893830034568018*^9}, 3.893830086173024*^9, 3.8938301222673063`*^9, {
   3.893830158943993*^9, 3.893830166792185*^9}, 3.89383020260633*^9, {
   3.894124840796061*^9, 3.894124964792389*^9}, 3.894125095850725*^9, {
   3.894131160593029*^9, 3.894131162120569*^9}, 3.894182224699*^9, {
   3.894182543668069*^9, 3.8941825548652363`*^9}, {3.894182626409045*^9, 
   3.8941826609879847`*^9}, {3.894182692101914*^9, 3.8941827198709097`*^9}, {
   3.8941827581773033`*^9, 3.8941827778054028`*^9}, {3.8941829097976933`*^9, 
   3.894183012720541*^9}, {3.89418320482591*^9, 3.8941832266116867`*^9}, {
   3.89418331720687*^9, 3.8941833818672543`*^9}, {3.894183415333482*^9, 
   3.894183418058648*^9}, {3.894183462849697*^9, 3.894183476668674*^9}, {
   3.894183522327815*^9, 3.8941835995430593`*^9}, {3.894779952894003*^9, 
   3.894779952974799*^9}, {3.8948013964458*^9, 3.894801400052415*^9}, {
   3.894811496524934*^9, 3.894811532314274*^9}, {3.894811617531969*^9, 
   3.894811621302861*^9}, {3.8948116832998047`*^9, 3.89481170888099*^9}, {
   3.894813402722443*^9, 3.894813417079344*^9}, {3.894891408192378*^9, 
   3.894891426060767*^9}, {3.8948916473541*^9, 3.8948916814724207`*^9}, {
   3.894891716498377*^9, 3.8948917655775547`*^9}, {3.89497105718178*^9, 
   3.894971057229216*^9}, {3.8949760949123774`*^9, 3.894976131144925*^9}, {
   3.894976715997616*^9, 3.8949767342131977`*^9}, {3.895041154552971*^9, 
   3.8950411747221947`*^9}, {3.895041393713069*^9, 3.895041406982338*^9}, {
   3.895057685964912*^9, 3.895057734286571*^9}, {3.8950577652799587`*^9, 
   3.895057867104055*^9}, {3.895163995956191*^9, 3.895164010075439*^9}, {
   3.896180524374055*^9, 3.8961805244426537`*^9}, {3.8961815690969152`*^9, 
   3.896181569169095*^9}, {3.89618162929663*^9, 3.896181673745707*^9}, {
   3.896193637900317*^9, 3.896193640006021*^9}, {3.89619381906082*^9, 
   3.8961938793436117`*^9}, {3.896194230582176*^9, 3.8961942397729177`*^9}, {
   3.896244496201335*^9, 3.896244581104267*^9}, {3.896244648059657*^9, 
   3.896244658334646*^9}, {3.896250524780723*^9, 3.896250571134919*^9}, {
   3.8962507762893457`*^9, 3.896250819662874*^9}, 3.896251174682982*^9, {
   3.896264352375362*^9, 3.8962643591039743`*^9}, {3.8962644233088017`*^9, 
   3.896264423335101*^9}, {3.896266703313456*^9, 3.896266703403495*^9}, {
   3.8962668686751137`*^9, 3.8962668687995462`*^9}, {3.896345408483097*^9, 
   3.896345438260775*^9}, {3.8963455509795313`*^9, 3.8963455692560043`*^9}, {
   3.896345602767125*^9, 3.896345615861231*^9}, {3.896345716430304*^9, 
   3.8963458231550694`*^9}, {3.896345889510893*^9, 3.8963458955458603`*^9}, {
   3.896366429061225*^9, 3.896366444841134*^9}, {3.896366686621895*^9, 
   3.8963666918620234`*^9}, {3.896366822642569*^9, 3.896366827830523*^9}, {
   3.896431297194627*^9, 3.8964313432205343`*^9}, 3.896431374477769*^9, {
   3.8964314876486263`*^9, 3.896431493483041*^9}, {3.896431606785948*^9, 
   3.896431687175885*^9}, {3.896432181611611*^9, 3.8964322214195137`*^9}, {
   3.896432299653369*^9, 3.8964323015057917`*^9}, {3.896432354138777*^9, 
   3.896432401514369*^9}, 3.8964326924037027`*^9, {3.8964328964915533`*^9, 
   3.896432900146616*^9}, {3.896436473054661*^9, 3.8964365097529583`*^9}, {
   3.896458136482605*^9, 3.896458137184938*^9}, {3.896694719548595*^9, 
   3.896694738980587*^9}, {3.8966999692208147`*^9, 3.89669996923964*^9}, {
   3.896700210895443*^9, 3.896700210913096*^9}, {3.896716566511734*^9, 
   3.896716569144299*^9}, {3.896758393950205*^9, 3.896758410257683*^9}, {
   3.897639128411788*^9, 3.89763914168635*^9}, {3.905009646365121*^9, 
   3.9050096521287537`*^9}, 3.905597074281517*^9, {3.905597126333344*^9, 
   3.9055971392899933`*^9}, {3.905777841589335*^9, 3.905777846452148*^9}, {
   3.905777966385859*^9, 3.905778002036471*^9}, 3.905871145250127*^9},
 CellLabel->"In[1]:=",ExpressionUUID->"f5b666ab-d61b-4cc4-894c-abef1813a8b9"],

Cell[CellGroupData[{

Cell[BoxData[
 StyleBox["\<\"Starting Constants.wl: \"\>",
  StripOnInput->False,
  FontColor->GrayLevel[0.85]]], "Print",
 CellChangeTimes->{
  3.896364896269964*^9, 3.8963667597278223`*^9, 3.896431518999489*^9, 
   3.8964322504694633`*^9, 3.8964327230855007`*^9, 3.8964329307595253`*^9, 
   3.896436527341597*^9, 3.896438035096683*^9, 3.896455619608356*^9, 
   3.896455963510882*^9, 3.8964581475047092`*^9, 3.8964583009137278`*^9, 
   3.896675561057496*^9, 3.8966943538865232`*^9, 3.896699880333407*^9, 
   3.8966999791186953`*^9, 3.8967002228780403`*^9, 3.89670030265943*^9, 
   3.896716583472011*^9, 3.896758281931016*^9, 3.8967584176120787`*^9, 
   3.896759165282078*^9, 3.896759551293264*^9, 3.8967599255112457`*^9, 
   3.8967600588026867`*^9, 3.896760200226*^9, 3.896761149311532*^9, 
   3.9049924358951*^9, 3.905006383705678*^9, 3.9050084977816772`*^9, 
   3.905008863625617*^9, 3.90500922050238*^9, 3.9050095700675507`*^9, 
   3.905009666152536*^9, 3.905009731760088*^9, 3.905508628712727*^9, 
   3.905593683712105*^9, 3.905597178832305*^9, 3.905608824493847*^9, 
   3.9056090272691307`*^9, 3.905609611337316*^9, 3.905609821186899*^9, 
   3.905610460354281*^9, 3.905611324585765*^9, 3.905615014514592*^9, 
   3.905619295296421*^9, 3.905662589326602*^9, 3.905667426538313*^9, 
   3.90577810110223*^9, 3.905784149718334*^9, 3.905784364906673*^9, 
   3.9058439324236727`*^9, 3.905864375780452*^9, 3.9058651452068768`*^9, 
   3.9060196565347033`*^9, {3.9120048327637568`*^9, 3.912004851735503*^9}},
 CellLabel->
  "During evaluation of \
In[1]:=",ExpressionUUID->"80b542f5-f5a0-4a49-96c1-0f522a9d28a9"],

Cell[BoxData[
 StyleBox["\<\"Starting PowerLawPlusPeakDefinition.wl: \"\>",
  StripOnInput->False,
  FontColor->GrayLevel[0.85]]], "Print",
 CellChangeTimes->{
  3.896364896269964*^9, 3.8963667597278223`*^9, 3.896431518999489*^9, 
   3.8964322504694633`*^9, 3.8964327230855007`*^9, 3.8964329307595253`*^9, 
   3.896436527341597*^9, 3.896438035096683*^9, 3.896455619608356*^9, 
   3.896455963510882*^9, 3.8964581475047092`*^9, 3.8964583009137278`*^9, 
   3.896675561057496*^9, 3.8966943538865232`*^9, 3.896699880333407*^9, 
   3.8966999791186953`*^9, 3.8967002228780403`*^9, 3.89670030265943*^9, 
   3.896716583472011*^9, 3.896758281931016*^9, 3.8967584176120787`*^9, 
   3.896759165282078*^9, 3.896759551293264*^9, 3.8967599255112457`*^9, 
   3.8967600588026867`*^9, 3.896760200226*^9, 3.896761149311532*^9, 
   3.9049924358951*^9, 3.905006383705678*^9, 3.9050084977816772`*^9, 
   3.905008863625617*^9, 3.90500922050238*^9, 3.9050095700675507`*^9, 
   3.905009666152536*^9, 3.905009731760088*^9, 3.905508628712727*^9, 
   3.905593683712105*^9, 3.905597178832305*^9, 3.905608824493847*^9, 
   3.9056090272691307`*^9, 3.905609611337316*^9, 3.905609821186899*^9, 
   3.905610460354281*^9, 3.905611324585765*^9, 3.905615014514592*^9, 
   3.905619295296421*^9, 3.905662589326602*^9, 3.905667426538313*^9, 
   3.90577810110223*^9, 3.905784149718334*^9, 3.905784364906673*^9, 
   3.9058439324236727`*^9, 3.905864375780452*^9, 3.9058651452068768`*^9, 
   3.9060196565347033`*^9, {3.9120048327637568`*^9, 3.912004851742544*^9}},
 CellLabel->
  "During evaluation of \
In[1]:=",ExpressionUUID->"474faa88-1bde-4128-97f2-9261d5fecf17"],

Cell[BoxData[
 RowBox[{
  TagBox["\<\"Use plpp`pi[m, options] for the power-law-plus-peak PDF and \
plpp`\[ScriptCapitalD][options] for the distribution. Use optionsPlpp to see \
the options.\"\>",
   "EchoLabel"], "  ", "\<\"\"\>"}]], "Echo",
 CellChangeTimes->{
  3.9120048541521997`*^9},ExpressionUUID->"a2ad2a2c-7727-42aa-90fe-\
661cb6f4ba16"],

Cell[BoxData[
 StyleBox["\<\"Starting Cosmology.wl: \"\>",
  StripOnInput->False,
  FontColor->GrayLevel[0.85]]], "Print",
 CellChangeTimes->{
  3.896364896269964*^9, 3.8963667597278223`*^9, 3.896431518999489*^9, 
   3.8964322504694633`*^9, 3.8964327230855007`*^9, 3.8964329307595253`*^9, 
   3.896436527341597*^9, 3.896438035096683*^9, 3.896455619608356*^9, 
   3.896455963510882*^9, 3.8964581475047092`*^9, 3.8964583009137278`*^9, 
   3.896675561057496*^9, 3.8966943538865232`*^9, 3.896699880333407*^9, 
   3.8966999791186953`*^9, 3.8967002228780403`*^9, 3.89670030265943*^9, 
   3.896716583472011*^9, 3.896758281931016*^9, 3.8967584176120787`*^9, 
   3.896759165282078*^9, 3.896759551293264*^9, 3.8967599255112457`*^9, 
   3.8967600588026867`*^9, 3.896760200226*^9, 3.896761149311532*^9, 
   3.9049924358951*^9, 3.905006383705678*^9, 3.9050084977816772`*^9, 
   3.905008863625617*^9, 3.90500922050238*^9, 3.9050095700675507`*^9, 
   3.905009666152536*^9, 3.905009731760088*^9, 3.905508628712727*^9, 
   3.905593683712105*^9, 3.905597178832305*^9, 3.905608824493847*^9, 
   3.9056090272691307`*^9, 3.905609611337316*^9, 3.905609821186899*^9, 
   3.905610460354281*^9, 3.905611324585765*^9, 3.905615014514592*^9, 
   3.905619295296421*^9, 3.905662589326602*^9, 3.905667426538313*^9, 
   3.90577810110223*^9, 3.905784149718334*^9, 3.905784364906673*^9, 
   3.9058439324236727`*^9, 3.905864375780452*^9, 3.9058651452068768`*^9, 
   3.9060196565347033`*^9, {3.9120048327637568`*^9, 3.912004854162013*^9}},
 CellLabel->
  "During evaluation of \
In[1]:=",ExpressionUUID->"5102622f-fa44-41fa-b88e-22a89ca362c3"],

Cell[BoxData["\<\"tableZformation loaded.\"\>"], "Echo",
 CellChangeTimes->{
  3.912004854698222*^9},ExpressionUUID->"a558a1bf-2132-415d-8f21-\
f2709095b452"],

Cell[BoxData[
 StyleBox["\<\"Starting MassFactorCorrection.wl: \"\>",
  StripOnInput->False,
  FontColor->GrayLevel[0.85]]], "Print",
 CellChangeTimes->{
  3.896364896269964*^9, 3.8963667597278223`*^9, 3.896431518999489*^9, 
   3.8964322504694633`*^9, 3.8964327230855007`*^9, 3.8964329307595253`*^9, 
   3.896436527341597*^9, 3.896438035096683*^9, 3.896455619608356*^9, 
   3.896455963510882*^9, 3.8964581475047092`*^9, 3.8964583009137278`*^9, 
   3.896675561057496*^9, 3.8966943538865232`*^9, 3.896699880333407*^9, 
   3.8966999791186953`*^9, 3.8967002228780403`*^9, 3.89670030265943*^9, 
   3.896716583472011*^9, 3.896758281931016*^9, 3.8967584176120787`*^9, 
   3.896759165282078*^9, 3.896759551293264*^9, 3.8967599255112457`*^9, 
   3.8967600588026867`*^9, 3.896760200226*^9, 3.896761149311532*^9, 
   3.9049924358951*^9, 3.905006383705678*^9, 3.9050084977816772`*^9, 
   3.905008863625617*^9, 3.90500922050238*^9, 3.9050095700675507`*^9, 
   3.905009666152536*^9, 3.905009731760088*^9, 3.905508628712727*^9, 
   3.905593683712105*^9, 3.905597178832305*^9, 3.905608824493847*^9, 
   3.9056090272691307`*^9, 3.905609611337316*^9, 3.905609821186899*^9, 
   3.905610460354281*^9, 3.905611324585765*^9, 3.905615014514592*^9, 
   3.905619295296421*^9, 3.905662589326602*^9, 3.905667426538313*^9, 
   3.90577810110223*^9, 3.905784149718334*^9, 3.905784364906673*^9, 
   3.9058439324236727`*^9, 3.905864375780452*^9, 3.9058651452068768`*^9, 
   3.9060196565347033`*^9, {3.9120048327637568`*^9, 3.912004857115727*^9}},
 CellLabel->
  "During evaluation of \
In[1]:=",ExpressionUUID->"b4ed33cb-d069-4050-abe6-ea54ff64aca3"],

Cell[BoxData[
 RowBox[{
  TagBox["\<\"Base number of simmulated points per dimension (baseSimPoints): \
\"\>",
   "EchoLabel"], "  ", "500000"}]], "Echo",
 CellChangeTimes->{
  3.912004857119371*^9},ExpressionUUID->"fd6be947-31d4-4d99-a73b-\
b2aef6227ca5"],

Cell[BoxData[
 RowBox[{
  TagBox["\<\"dataM1Merger\"\>",
   "EchoLabel"], "  ", "6.177689`"}]], "EchoTiming",
 CellChangeTimes->{
  3.912004863389916*^9},ExpressionUUID->"28cece4c-3970-443e-8c7f-\
9432580066ef"],

Cell[BoxData["\<\"End of running wl files.\"\>"], "Print",
 CellChangeTimes->CompressedData["
1:eJwVz1soQwEcx/HDYqcJuTwcywPFypIXGculznJKFFnINqTNELLVsOUST+Qu
1lI2aqaZlduDW/JqhvFAxLQo13ZILZfmwf//8Ovz9qtvslIjVYcQBCGGjS2S
/l0uS0uLvy/2wPOgT3cDXoeVnaFt+0reLUiWVqegte9vj16QS6msd6Bdr8t5
AlNlWhVqFGg7nkFJvmUIDb1KtpSTLN1Yl+eWg4yT11cLyk9Uw+gL5bWjkfzL
DXSb/2FTgw/u/JBuUGDKjEVd4Q4N2qp8XUCTatY9qHlN5kMbcrmfaOyPo6kH
dNh6TRkUS78Zv9RZ4ABH3C4Co8ICc2h/3JQLrU+TBNCZ+0IiG7RJDSTq8Jis
wgSWnjrqElaABVa5rxKcPY2eVIA75uZltOS45RONDy5F1IBM1agCNR1MH6Ij
+nNjHVjU++qsBwd1K2edoFdcnm4ADcyiaBV//7aEG6CeY2HQvYlxhQfs+v2p
ugb35wXbaHFiTFoKn6U3tZR5IhV6n/wL6D+kItWk
  "],
 CellLabel->
  "During evaluation of \
In[1]:=",ExpressionUUID->"ad48af98-9d0b-4a62-bb7d-3b06c9ece02c"]
}, Open  ]]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["Exclusion plot k x MinMass using random PLPP parameters", "Section",
 CellChangeTimes->{{3.896374769619068*^9, 3.896374776494128*^9}, {
  3.896432884057825*^9, 3.896432888701438*^9}, {3.8964329400536747`*^9, 
  3.896432940700355*^9}, {3.905662036694413*^9, 3.905662060559596*^9}, {
  3.90566255266616*^9, 
  3.9056625594834423`*^9}},ExpressionUUID->"8e2d086c-3e8f-4c8e-ac60-\
0aa07484da5f"],

Cell["\<\
Modified version of the MassFactorCorrection.wl code, to allow for parameter \
variation\
\>", "Text",
 CellChangeTimes->{{3.896436669076951*^9, 3.896436712529764*^9}, 
   3.90559389428841*^9},ExpressionUUID->"76c7c0a0-be1e-4a11-a5cb-\
30de2a7dc435"],

Cell[BoxData[{
 RowBox[{
  RowBox[{
   RowBox[{"minDelayTime", " ", "=", " ", 
    RowBox[{"First", "[", "listDelayTime", "]"}]}], ";"}], " ", 
  RowBox[{"(*", 
   RowBox[{
    RowBox[{
    "min", " ", "delay", " ", "time", " ", "to", " ", "be", " ", "computed"}],
     ",", " ", 
    RowBox[{
    "it", " ", "can", " ", "be", " ", "lower", " ", "than", " ", "tdmin0"}]}],
    "*)"}]}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"maxDelayTime", "[", 
     RowBox[{"zObs_", ",", " ", 
      RowBox[{"tdmax_", "?", "NumberQ"}], ",", " ", 
      RowBox[{"zMax_", "?", "NumberQ"}], ",", " ", "w_"}], "]"}], " ", ":=", 
    " ", 
    RowBox[{
     RowBox[{"maxDelayTime", "[", 
      RowBox[{"zObs", ",", " ", "tdmax", ",", " ", "zMax", ",", " ", "w"}], 
      "]"}], " ", "=", " ", 
     RowBox[{"Min", "[", "\n", "  ", 
      RowBox[{"tdmax", ",", "\n", "  ", 
       RowBox[{"timeZ", "[", 
        RowBox[{"zObs", ",", " ", "zMax", ",", " ", "w"}], "]"}]}], "\n", 
      "]"}]}]}], ";"}], " ", "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"massFactor", "[", 
     RowBox[{"zObs_", ",", "zFormation_", ",", " ", "k_"}], "]"}], " ", "=", 
    " ", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       RowBox[{"(", 
        RowBox[{"1", " ", "+", " ", "zFormation"}], ")"}], "/", 
       RowBox[{"(", 
        RowBox[{"1", " ", "+", " ", "zObs"}], ")"}]}], ")"}], "^", "k"}]}], 
   ";"}], " ", 
  RowBox[{"(*", 
   RowBox[{
    RowBox[{
     RowBox[{
      RowBox[{"(", 
       RowBox[{"a", "/", "a_i"}], ")"}], "^", "k"}], ".", " ", "This"}], " ", 
    "is", " ", "the", " ", "factor", " ", "that", " ", "corrects", " ", "the",
     " ", "mass"}], "*)"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{"SetAttributes", "[", 
   RowBox[{"massFactorDelay", ",", " ", "Listable"}], "]"}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"massFactorDelay", "[", 
     RowBox[{
     "zObs_", ",", " ", "delayTime_", ",", " ", "k_", ",", " ", "zMax_", ",", 
      " ", "w_"}], "]"}], " ", "=", "  ", 
    RowBox[{"massFactor", "[", 
     RowBox[{"zObs", ",", " ", 
      RowBox[{"zFormationI", "[", 
       RowBox[{
       "zObs", ",", " ", "delayTime", ",", " ", "zMax", ",", " ", "w"}], 
       "]"}], ",", " ", "k"}], "]"}]}], ";"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"randomLogDelayTime", "[", 
     RowBox[{
     "zObs_", ",", " ", "tdmin_", ",", " ", "tdmax_", ",", " ", "zMax_", ",", 
      " ", "w_", ",", " ", "realizations_"}], "]"}], " ", ":=", " ", 
    RowBox[{
     RowBox[{"randomLogDelayTime", "[", 
      RowBox[{
      "zObs", ",", " ", "tdmin", ",", " ", "tdmax", ",", "  ", "zMax", ",", 
       " ", "w", ",", " ", "realizations"}], "]"}], " ", "=", " ", "\n", " ", 
     
     RowBox[{"RandomReal", "[", 
      RowBox[{
       RowBox[{"{", 
        RowBox[{
         RowBox[{"Log10", "[", "tdmin", "]"}], ",", " ", 
         RowBox[{"Log10", " ", "@", " ", 
          RowBox[{"maxDelayTime", "[", 
           RowBox[{
           "zObs", ",", " ", "tdmax", ",", " ", "zMax", ",", " ", "w"}], 
           "]"}]}]}], "}"}], ",", " ", "realizations"}], "]"}]}]}], ";"}], 
  " ", 
  RowBox[{"(*", 
   RowBox[{"log", "-", 
    RowBox[{"flat", " ", 
     RowBox[{"distribution", "."}]}]}], "*)"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"dataDelayTime", "[", 
     RowBox[{
     "zObs_", ",", " ", "tdmin_", ",", " ", "tdmax_", ",", " ", "zMax_", ",", 
      " ", "w_"}], "]"}], " ", ":=", " ", 
    RowBox[{
     RowBox[{"dataDelayTime", "[", 
      RowBox[{
      "zObs", ",", " ", "tdmin", ",", " ", "tdmax", ",", " ", "zMax", ",", 
       " ", "w"}], "]"}], " ", "=", " ", "\n", " ", 
     RowBox[{"10", "^", 
      RowBox[{"randomLogDelayTime", "[", 
       RowBox[{
       "zObs", ",", " ", "tdmin", ",", " ", "tdmax", ",", " ", "zMax", ",", 
        " ", "w", ",", "  ", "baseSimPoints"}], "]"}]}]}]}], ";"}], " ", 
  "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"dataMassFactor", "[", 
    RowBox[{
    "zObs_", ",", " ", "tdmin_", ",", " ", "tdmax_", ",", " ", "k_", ",", " ",
      "zMax_", ",", " ", "w_"}], "]"}], " ", ":=", " ", 
   RowBox[{
    RowBox[{"dataMassFactor", "[", 
     RowBox[{
     "zObs", ",", " ", "tdmin", ",", " ", "tdmax", ",", " ", "k", ",", " ", 
      "zMax", ",", " ", "w"}], "]"}], " ", "=", " ", "\n", " ", 
    RowBox[{"massFactorDelay", "[", 
     RowBox[{"zObs", ",", " ", 
      RowBox[{"dataDelayTime", "[", 
       RowBox[{
       "zObs", ",", " ", "tdmin", ",", " ", "tdmax", ",", " ", "zMax", ",", 
        " ", "w"}], "]"}], ",", " ", "k", ",", " ", "zMax", ",", " ", "w"}], 
     "]"}]}]}], ";"}]}], "Code",
 CellChangeTimes->{{3.905665115225278*^9, 3.90566511523236*^9}, {
  3.905866567278047*^9, 3.90586659221865*^9}},
 CellLabel->"In[13]:=",ExpressionUUID->"a3671ec2-b1f3-49f8-8d44-a13d38d87b00"],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{
   RowBox[{"Clear", "[", " ", "\n", "  ", 
    RowBox[{
    "iPS", ",", " ", "\n", "  ", "cPI", ",", "  ", "\n", "  ", 
     "probabilityMminApprox", ",", " ", "\n", "  ", 
     "probabilityMminApproxF"}], "\n", "]"}], ";"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"assoSamplesPLPPraw", " ", "=", " ", 
    RowBox[{"Import", "[", 
     RowBox[{
      RowBox[{"FileNameJoin", "[", 
       RowBox[{"{", 
        RowBox[{"pathIn", ",", " ", "\"\<all_samples_PLPP_GWTC3.h5\>\""}], 
        "}"}], "]"}], ",", " ", "\"\<Data\>\""}], "]"}]}], ";"}], " ", 
  RowBox[{"(*", 
   RowBox[{
    RowBox[{"Data", " ", "imported", " ", "as", " ", "association"}], ",", 
    " ", 
    RowBox[{"asso", " ", "for", " ", 
     RowBox[{"short", "."}]}]}], "*)"}]}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"assoSamplesPLPP", " ", "=", " ", 
    RowBox[{"KeyMap", "[", 
     RowBox[{
      RowBox[{
       RowBox[{"StringDelete", "[", 
        RowBox[{"#", ",", " ", 
         RowBox[{"{", 
          RowBox[{"\"\</\>\"", ",", " ", "\"\<_\>\""}], "}"}]}], "]"}], " ", 
       "&"}], " ", ",", " ", "assoSamplesPLPPraw"}], "]"}]}], ";"}], " ", 
  RowBox[{"(*", 
   RowBox[{
   "Removes", " ", "inconvenient", " ", "strings", " ", "from", " ", "the", 
    " ", "key", " ", 
    RowBox[{"names", "."}]}], "*)"}], " ", "\n"}], "\n", 
 RowBox[{
  RowBox[{"alpha", " ", "=", " ", 
   RowBox[{"assoSamplesPLPP", "[", "\"\<alpha\>\"", "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"beta", " ", "=", " ", 
   RowBox[{"assoSamplesPLPP", "[", "\"\<beta\>\"", "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"mmax", " ", "=", " ", 
   RowBox[{"assoSamplesPLPP", "[", "\"\<mmax\>\"", "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"mmin", " ", "=", " ", 
   RowBox[{"assoSamplesPLPP", "[", "\"\<mmin\>\"", "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"lam", " ", "=", " ", 
   RowBox[{"assoSamplesPLPP", "[", "\"\<lam\>\"", "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"mpp", " ", "=", " ", 
   RowBox[{"assoSamplesPLPP", "[", "\"\<mpp\>\"", "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"sigpp", " ", "=", " ", 
   RowBox[{"assoSamplesPLPP", "[", "\"\<sigpp\>\"", "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"deltam", " ", "=", " ", 
    RowBox[{"assoSamplesPLPP", "[", "\"\<deltam\>\"", "]"}]}], ";"}], 
  "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"lengthSample", " ", "=", " ", 
    RowBox[{"Length", " ", "@", " ", "alpha"}]}], ";"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{"Clear", "[", "\[ScriptCapitalD]plppR", "]"}], ";"}], "\n", 
 RowBox[{
  RowBox[{"listRandomSample", " ", "=", " ", 
   RowBox[{"RandomSample", "[", 
    RowBox[{"Range", " ", "@", " ", "lengthSample"}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"iPS", "[", "i_", "]"}], " ", ":=", " ", 
    RowBox[{"listRandomSample", "[", 
     RowBox[{"[", "i", "]"}], "]"}]}], ";"}], " ", 
  RowBox[{"(*", 
   RowBox[{"iPS", " ", "is", " ", "indexed", " ", "PLPP", " ", "Sample"}], 
   "*)"}]}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"cPI", " ", "=", " ", "1"}], ";"}], " ", 
  RowBox[{"(*", 
   RowBox[{"cPI", " ", "is", " ", "countPlppIndex"}], "*)"}]}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"\[ScriptCapitalD]plppR", " ", ":=", " ", 
    RowBox[{"(", "\n", "  ", 
     RowBox[{"(*", 
      RowBox[{
       RowBox[{"cPI", " ", "=", " ", 
        RowBox[{"cPI", " ", "+", " ", "1"}]}], ";"}], "*)"}], "\n", "  ", 
     RowBox[{"(*", 
      RowBox[{
       RowBox[{"If", "[", 
        RowBox[{
         RowBox[{"cPI", " ", ">", " ", 
          RowBox[{"Length", " ", "@", " ", "alpha"}]}], ",", " ", 
         RowBox[{
          RowBox[{"Echo", "[", "\"\<cPI exceeded.\>\"", "]"}], ";", " ", 
          RowBox[{"cp1", " ", "=", " ", "1"}]}]}], "]"}], ";"}], "*)"}], "\n",
      "  ", 
     RowBox[{"plpp`dist", "[", "\n", "    ", 
      RowBox[{
       RowBox[{"plpp`a", " ", "->", " ", 
        RowBox[{"alpha", "[", 
         RowBox[{"[", 
          RowBox[{"iPS", "[", "cPI", "]"}], "]"}], "]"}]}], ",", "\n", "    ", 
       RowBox[{"plpp`mMin", " ", "->", " ", 
        RowBox[{"mmin", "[", 
         RowBox[{"[", 
          RowBox[{"iPS", "[", "cPI", "]"}], "]"}], "]"}]}], ",", "\n", "    ", 
       RowBox[{"plpp`dm", " ", "->", " ", 
        RowBox[{"deltam", "[", 
         RowBox[{"[", 
          RowBox[{"iPS", "[", "cPI", "]"}], "]"}], "]"}]}], ",", "\n", "    ", 
       RowBox[{"plpp`mMax", " ", "->", " ", 
        RowBox[{"mmax", "[", 
         RowBox[{"[", 
          RowBox[{"iPS", "[", "cPI", "]"}], "]"}], "]"}]}], ",", "\n", "    ", 
       RowBox[{"plpp`mu", " ", "->", " ", 
        RowBox[{"mpp", "[", 
         RowBox[{"[", 
          RowBox[{"iPS", "[", "cPI", "]"}], "]"}], "]"}]}], ",", "\n", "    ", 
       RowBox[{"plpp`s", " ", "->", " ", 
        RowBox[{"sigpp", "[", 
         RowBox[{"[", 
          RowBox[{"iPS", "[", "cPI", "]"}], "]"}], "]"}]}], ",", "\n", "    ", 
       RowBox[{"plpp`l", " ", "->", " ", 
        RowBox[{"lam", "[", 
         RowBox[{"[", 
          RowBox[{"iPS", "[", "cPI", "]"}], "]"}], "]"}]}], ",", "\n", "    ", 
       RowBox[{"plpp`betaQ", " ", "->", " ", 
        RowBox[{"beta", "[", 
         RowBox[{"[", 
          RowBox[{"iPS", "[", "cPI", "]"}], "]"}], "]"}]}]}], "\n", "  ", 
      "]"}], "\n", ")"}]}], ";"}], " ", 
  RowBox[{"(*", "\n", "  ", 
   RowBox[{
   "\[ScriptCapitalD]plppR", " ", "picks", " ", "a", " ", "random", " ", 
    "realization", " ", "of", " ", "the", " ", "PLPP", " ", "parameters", " ", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
      "it", " ", "never", " ", "picks", " ", "a", " ", "realization", " ", 
       "more", " ", "than", " ", "once"}], ")"}], ".", " ", "\n", "  ", 
     "plpp`dist"}], " ", "is", " ", "defined", " ", "in", " ", 
    RowBox[{"PowerLawPlusPeakDefinition", ".", "wl", "."}]}], "\n", "*)"}], 
  "\n", "\n", 
  RowBox[{"(*", 
   RowBox[{
   "To", " ", "refresh", " ", "all", " ", "the", " ", "definitions", " ", 
    "related", " ", "to", " ", "the", " ", "massFactor"}], "*)"}]}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"getCode", "[", "\"\<MassFactorCorrection.wl\>\"", "]"}], ";"}], 
  " ", 
  RowBox[{"(*", 
   RowBox[{
   "It", " ", "computes", " ", "automatically", " ", "a", " ", "dataM1merger",
     " ", "but", " ", "it", " ", "will", " ", "not", " ", "be", " ", 
    RowBox[{"used", "."}]}], "*)"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"Clear", "[", "\n", "  ", 
    RowBox[{
    "dataM1Merger", ",", " ", "\n", "  ", "dataDelayTime", ",", " ", "\n", 
     "  ", "dataM1FormationRaw", ",", " ", "\n", "  ", 
     "\[ScriptCapitalD]M1FormationEmpRaw", ",", " ", "\n", "  ", 
     "\[ScriptCapitalD]M1FormationEmp"}], "\n", "]"}], ";"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"dataDelayTime", "[", 
     RowBox[{
     "zObs_", ",", " ", "tdmin_", ",", " ", "tdmax_", ",", " ", "zMax_", ",", 
      " ", "w_"}], "]"}], " ", ":=", " ", 
    RowBox[{
     RowBox[{"dataDelayTime", "[", 
      RowBox[{
      "zObs", ",", " ", "tdmin", ",", " ", "tdmax", ",", " ", "zMax", ",", 
       " ", "w"}], "]"}], " ", "=", " ", "\n", " ", 
     RowBox[{"10", "^", 
      RowBox[{"randomLogDelayTime", "[", 
       RowBox[{
       "zObs", ",", " ", "tdmin", ",", " ", "tdmax", ",", " ", "zMax", ",", 
        " ", "w", ",", "  ", "baseSimPoints"}], "]"}]}]}]}], ";"}], " ", 
  RowBox[{"(*", 
   RowBox[{"Redefined", " ", "here", " ", "to", " ", "use", " ", 
    RowBox[{"baseSimPoints", "."}]}], "*)"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"dataM1Merger", "[", "cpi_", "]"}], " ", ":=", " ", 
    RowBox[{
     RowBox[{"dataM1Merger", "[", "cpi", "]"}], " ", "=", " ", 
     RowBox[{"Block", "[", 
      RowBox[{
       RowBox[{"{", "cPI", "}"}], ",", " ", 
       RowBox[{
        RowBox[{"cPI", " ", "=", " ", "cpi"}], ";", " ", 
        RowBox[{"RandomVariate", "[", 
         RowBox[{"\[ScriptCapitalD]plppR", ",", " ", "baseSimPoints"}], 
         "]"}]}]}], "]"}]}]}], ";"}], "  ", 
  RowBox[{"(*", 
   RowBox[{
   "2", " ", "baseSimPoints", " ", "is", " ", "not", " ", "necessary", " ", 
    "here"}], "*)"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"dataM1FormationRaw", "[", 
     RowBox[{
     "zObs_", ",", " ", "tdmin_", ",", " ", "tdmax_", ",", " ", "k_", ",", 
      " ", "zMax_", ",", " ", "w_", ",", " ", "cpi_"}], "]"}], ":=", " ", 
    "\n", " ", 
    RowBox[{
     RowBox[{"dataM1Merger", "[", "cpi", "]"}], " ", "/", " ", 
     RowBox[{
      RowBox[{"dataMassFactor", "[", 
       RowBox[{
       "zObs", ",", " ", "tdmin", ",", " ", "tdmax", ",", " ", "1", ",", " ", 
        "zMax", ",", " ", "w"}], "]"}], "^", "k"}]}]}], ";"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"\[ScriptCapitalD]M1FormationEmpRaw", "[", 
     RowBox[{
     "zObs_", ",", " ", "tdmin_", ",", " ", "tdmax_", ",", " ", "k_", ",", 
      " ", "zMax_", ",", " ", "w_", ",", " ", "cpi_"}], "]"}], " ", ":=", " ",
     "\n", " ", 
    RowBox[{"EmpiricalDistribution", "[", "\n", "   ", 
     RowBox[{"dataM1FormationRaw", "[", 
      RowBox[{
      "zObs", ",", " ", "tdmin", ",", " ", "tdmax", ",", " ", "k", ",", " ", 
       "zMax", ",", " ", "w", ",", " ", "cpi"}], "]"}], "\n", " ", "]"}]}], 
   ";"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"\[ScriptCapitalD]M1FormationEmp", "[", 
     RowBox[{"zObs_", ",", " ", "cpi_", ",", " ", 
      RowBox[{"opts", ":", 
       RowBox[{"OptionsPattern", "[", "optionstkw", "]"}]}]}], "]"}], " ", ":=",
     " ", 
    RowBox[{"\[ScriptCapitalD]M1FormationEmpRaw", "[", "\n", "  ", 
     RowBox[{"zObs", ",", " ", "\n", "  ", 
      RowBox[{"OptionValue", " ", "@", " ", "tdmin"}], ",", " ", "\n", "  ", 
      RowBox[{"OptionValue", " ", "@", " ", "tdmax"}], ",", " ", "\n", "  ", 
      RowBox[{"OptionValue", " ", "@", " ", "k"}], ",", " ", "\n", "  ", 
      RowBox[{"OptionValue", " ", "@", " ", "zMax"}], ",", " ", "\n", "  ", 
      RowBox[{"OptionValue", " ", "@", " ", "w"}], ",", "\n", "  ", "cpi"}], 
     "\n", "]"}]}], ";"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"probabilityMminApprox", "[", 
    RowBox[{"mMin_", ",", " ", "cpi_", ",", " ", 
     RowBox[{"opts", ":", 
      RowBox[{"OptionsPattern", "[", "optionstkw", "]"}]}]}], "]"}], " ", ":=",
    " ", 
   SuperscriptBox[
    RowBox[{"SurvivalFunction", "[", 
     RowBox[{
      RowBox[{"\[ScriptCapitalD]M1FormationEmp", "[", 
       RowBox[{"0.4", ",", " ", "cpi", ",", " ", "opts"}], "]"}], ",", " ", 
      "mMin"}], "]"}], "72"]}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"probabilityMminApproxF", "[", 
     RowBox[{"mMin_", ",", " ", "cpi_", ",", " ", 
      RowBox[{"opts", ":", 
       RowBox[{"OptionsPattern", "[", "optionstkw", "]"}]}]}], "]"}], " ", ":=",
     " ", 
    SuperscriptBox[
     RowBox[{"SurvivalFunction", "[", 
      RowBox[{
       RowBox[{"\[ScriptCapitalD]M1FormationEmp", "[", 
        RowBox[{"0.4", ",", " ", "cpi", ",", " ", "opts"}], "]"}], ",", " ", 
       "mMin"}], "]"}], "250"]}], ";"}], " ", 
  RowBox[{"(*", "forecast", "*)"}]}]}], "Code",
 CellChangeTimes->{{3.896436389049024*^9, 3.896436391272031*^9}, {
   3.89643672229119*^9, 3.896436751018916*^9}, {3.896437261611994*^9, 
   3.896437269950083*^9}, 3.896437380248855*^9, {3.896437412361466*^9, 
   3.896437413644526*^9}, {3.8964375020437317`*^9, 3.896437547978902*^9}, {
   3.896437578555044*^9, 3.896437694101602*^9}, 3.896437868305764*^9, {
   3.896438014889433*^9, 3.896438023255764*^9}, {3.89645572243311*^9, 
   3.896455741032696*^9}, {3.8964557969151993`*^9, 3.896455818701214*^9}, {
   3.896458288887046*^9, 3.896458289242579*^9}, {3.8964984685259438`*^9, 
   3.896498477671706*^9}, {3.8966332958980293`*^9, 3.8966333752441387`*^9}, {
   3.896633406812826*^9, 3.896633457180002*^9}, {3.896633488382141*^9, 
   3.896633531197576*^9}, {3.8966997334120007`*^9, 3.896699736569056*^9}, {
   3.8966998274995127`*^9, 3.896699830881064*^9}, {3.896700186963834*^9, 
   3.896700200922678*^9}, {3.896758082685338*^9, 3.8967581487853327`*^9}, {
   3.896758196080934*^9, 3.8967582338135366`*^9}, {3.896759132738892*^9, 
   3.8967591405742817`*^9}, 3.8967595373217154`*^9, 3.89676018421768*^9, {
   3.897587405689024*^9, 3.897587406586624*^9}, {3.904992479433755*^9, 
   3.90499248150008*^9}, {3.90500881832066*^9, 3.905008828862063*^9}, {
   3.905016433312008*^9, 3.90501644772892*^9}, {3.905594233647201*^9, 
   3.9055944669690857`*^9}, {3.905594509433836*^9, 3.905594625255549*^9}, {
   3.905594770701223*^9, 3.9055947797472963`*^9}, {3.905594871947139*^9, 
   3.9055948880097837`*^9}, {3.90559492306181*^9, 3.90559496267776*^9}, {
   3.9055950746003647`*^9, 3.9055950915765333`*^9}, {3.905596736591593*^9, 
   3.905596861850874*^9}, {3.9055971599538813`*^9, 3.90559716858976*^9}, {
   3.905597266813305*^9, 3.905597272039109*^9}, {3.905597338895637*^9, 
   3.90559737790499*^9}, {3.905597423944422*^9, 3.905597464791554*^9}, 
   3.905597549871014*^9, {3.905597713053356*^9, 3.905597782719614*^9}, {
   3.905598140021439*^9, 3.905598140329239*^9}, {3.905610335620875*^9, 
   3.9056103441489143`*^9}, {3.905610405023115*^9, 3.905610438406109*^9}, {
   3.90566451597963*^9, 3.905664579061788*^9}, {3.90566473613446*^9, 
   3.9056647969234657`*^9}, {3.905664851675007*^9, 3.9056648526771507`*^9}, {
   3.905664961355101*^9, 3.905664973793868*^9}, {3.9056650337198477`*^9, 
   3.905665062295671*^9}, {3.905665277123356*^9, 3.905665558917891*^9}, {
   3.905665813355846*^9, 3.9056658184776897`*^9}, {3.9056668735100527`*^9, 
   3.9056669090926533`*^9}, {3.905667122620364*^9, 3.905667168419531*^9}, {
   3.905667200638008*^9, 3.9056672552656384`*^9}, {3.905667473308846*^9, 
   3.905667481340562*^9}},
 CellLabel->"In[21]:=",ExpressionUUID->"57415dd2-5f07-4cc7-a6bb-425e3bdb8c6b"],

Cell[CellGroupData[{

Cell[BoxData[
 StyleBox["\<\"Starting MassFactorCorrection.wl: \"\>",
  StripOnInput->False,
  FontColor->GrayLevel[0.85]]], "Print",
 CellChangeTimes->{3.905664608676261*^9, 3.905664984342538*^9, 
  3.905665593202355*^9, 3.9056658280185957`*^9, 3.9056670899179153`*^9, 
  3.9056672649410152`*^9, 3.905667442347292*^9, 3.905667483174897*^9, 
  3.906019675778345*^9, 3.912004874521337*^9},
 CellLabel->
  "During evaluation of \
In[21]:=",ExpressionUUID->"643ab74a-a539-4161-a422-6a395da5ef07"],

Cell[BoxData[
 RowBox[{
  TagBox["\<\"Base number of simmulated points per dimension (baseSimPoints): \
\"\>",
   "EchoLabel"], "  ", "500000"}]], "Echo",
 CellChangeTimes->{
  3.912004874525416*^9},ExpressionUUID->"7847530b-de8a-42ee-ba45-\
0ca94cb69f41"],

Cell[BoxData[
 RowBox[{
  TagBox["\<\"dataM1Merger\"\>",
   "EchoLabel"], "  ", "12.111689`"}]], "EchoTiming",
 CellChangeTimes->{
  3.912004886652927*^9},ExpressionUUID->"74a9a6ff-bb4c-410a-9527-\
e594de7e99c2"]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["Code for arbitrary cPI value", "Subsection",
 CellChangeTimes->{{3.905665859592971*^9, 3.905665860650352*^9}, {
  3.905666428987606*^9, 
  3.905666438658751*^9}},ExpressionUUID->"488bde6d-3234-4731-b9a2-\
fe09b24be7f0"],

Cell[BoxData[{
 RowBox[{
  RowBox[{
   RowBox[{"Clear", "[", 
    RowBox[{
    "tab", ",", " ", "sol", ",", " ", "solAll", ",", " ", "probValue"}], 
    "]"}], ";"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{"probValue", " ", "=", " ", 
   RowBox[{"probSigma", "[", "2", "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"listk1", " ", "=", " ", 
   RowBox[{"Range", "[", 
    RowBox[{"0.5", ",", " ", "3", ",", " ", "0.1"}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"listm1", " ", "=", " ", 
   RowBox[{"Range", "[", 
    RowBox[{"0.4", ",", " ", "6", ",", " ", "0.1"}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"sol", "[", 
     RowBox[{"0", ",", " ", "cpi_"}], "]"}], " ", "=", " ", 
    RowBox[{"{", 
     RowBox[{"arbitraryK", ",", " ", 
      RowBox[{"Last", " ", "@", " ", "listm1"}]}], "}"}]}], ";"}], " ", 
  RowBox[{"(*", 
   RowBox[{"Only", " ", "used", " ", "for", " ", "the", " ", "first", " ", 
    RowBox[{"step", "."}]}], "*)"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"tab", "[", 
    RowBox[{"nk1_", ",", " ", "cpi_"}], "]"}], " ", ":=", " ", 
   RowBox[{
    RowBox[{"tab", "[", 
     RowBox[{"nk1", ",", " ", "cpi"}], "]"}], " ", "=", " ", 
    RowBox[{"Block", "[", 
     RowBox[{
      RowBox[{"{", 
       RowBox[{
       "nm1Previous", ",", " ", "nm1Minimal", ",", " ", "listm1Relevant"}], 
       "}"}], ",", "\n", "  ", 
      RowBox[{
       RowBox[{"nm1Previous", " ", "=", " ", 
        RowBox[{
         RowBox[{"Position", "[", 
          RowBox[{"listm1", ",", " ", 
           RowBox[{"Last", "@", 
            RowBox[{"sol", "[", 
             RowBox[{
              RowBox[{"nk1", "-", "1"}], ",", " ", "cpi"}], "]"}]}]}], "]"}], 
         "[", 
         RowBox[{"[", 
          RowBox[{"1", ",", "1"}], "]"}], "]"}]}], ";", "\n", "  ", 
       RowBox[{"nm1Minimal", " ", "=", " ", 
        RowBox[{"If", "[", 
         RowBox[{
          RowBox[{
           RowBox[{"nm1Previous", " ", "-", " ", "10"}], " ", "<", " ", "1"}],
           ",", " ", "1", ",", " ", 
          RowBox[{"nm1Previous", " ", "-", " ", "10"}]}], "]"}]}], ";", "\n", 
       "  ", 
       RowBox[{"listm1Relevant", " ", "=", " ", 
        RowBox[{"listm1", " ", "//", " ", 
         RowBox[{
          RowBox[{"Take", "[", 
           RowBox[{"#", ",", " ", 
            RowBox[{"{", 
             RowBox[{"nm1Minimal", ",", " ", "nm1Previous"}], "}"}]}], "]"}], 
          " ", "&"}]}]}], ";", "\n", "  ", 
       RowBox[{"Table", "[", "\n", "    ", 
        RowBox[{
         RowBox[{"{", 
          RowBox[{
           RowBox[{"{", 
            RowBox[{
             RowBox[{"listk1", "[", 
              RowBox[{"[", "nk1", "]"}], "]"}], ",", " ", "m1"}], "}"}], ",", 
           " ", 
           RowBox[{"Abs", "[", 
            RowBox[{
             RowBox[{"probabilityMminApprox", "[", 
              RowBox[{"m1", ",", " ", "cpi", ",", " ", 
               RowBox[{"k", " ", "->", " ", 
                RowBox[{"listk1", "[", 
                 RowBox[{"[", "nk1", "]"}], "]"}]}]}], "]"}], " ", "-", " ", 
             "probValue"}], "]"}]}], "}"}], " ", ",", " ", "\n", "    ", 
         RowBox[{"{", 
          RowBox[{"m1", ",", " ", "listm1Relevant"}], "}"}]}], "\n", "  ", 
        "]"}]}]}], "\n", "]"}]}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"sol", "[", 
     RowBox[{"nk1_", ",", " ", "cpi_"}], "]"}], " ", ":=", " ", 
    RowBox[{
     RowBox[{"sol", "[", 
      RowBox[{"nk1", ",", " ", "cpi"}], "]"}], " ", "=", " ", 
     RowBox[{
      RowBox[{"tab", "[", 
       RowBox[{"nk1", ",", " ", "cpi"}], "]"}], " ", "//", " ", 
      RowBox[{
       RowBox[{
        RowBox[{"SortBy", "[", 
         RowBox[{"#", ",", " ", "Last"}], "]"}], "[", 
        RowBox[{"[", 
         RowBox[{"1", ",", "1"}], "]"}], "]"}], " ", "&"}]}]}]}], " ", 
   RowBox[{"(*", 
    RowBox[{"//", " ", "Echo"}], "*)"}], ";"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"solAll", "[", "cpi_", "]"}], " ", ":=", " ", 
   RowBox[{
    RowBox[{"solAll", "[", "cpi", "]"}], " ", "=", " ", 
    RowBox[{"Monitor", "[", 
     RowBox[{
      RowBox[{"Table", "[", 
       RowBox[{
        RowBox[{"sol", "[", 
         RowBox[{"nk1", ",", " ", "cpi"}], "]"}], ",", " ", 
        RowBox[{"{", 
         RowBox[{"nk1", ",", " ", 
          RowBox[{"Length", " ", "@", " ", "listk1"}]}], "}"}]}], "]"}], ",", 
      " ", 
      RowBox[{"{", 
       RowBox[{"nk1", ",", " ", 
        RowBox[{"Length", " ", "@", " ", "listk1"}]}], "}"}]}], "]"}]}]}], 
  ";"}]}], "Code",
 CellChangeTimes->{{3.905611238513006*^9, 3.905611256252783*^9}, {
   3.9056113668113403`*^9, 3.905611383832735*^9}, {3.905611456949306*^9, 
   3.905611550254397*^9}, {3.905611864429225*^9, 3.905611906148295*^9}, {
   3.9056121051412287`*^9, 3.905612151434374*^9}, {3.905612199778463*^9, 
   3.90561221489856*^9}, {3.9056122475125427`*^9, 3.9056123145857773`*^9}, {
   3.9056123662557487`*^9, 3.905612367536484*^9}, {3.905612405905558*^9, 
   3.905612429609185*^9}, {3.9056124697363577`*^9, 3.9056124868954678`*^9}, {
   3.905612891633484*^9, 3.905612896954249*^9}, {3.9056129471049*^9, 
   3.905612957544634*^9}, {3.9056129947367983`*^9, 3.9056132058302193`*^9}, {
   3.905613246293309*^9, 3.905613249975971*^9}, {3.9056133044927998`*^9, 
   3.9056133111765223`*^9}, {3.905613343452026*^9, 3.9056134197945232`*^9}, {
   3.905613450338022*^9, 3.905613452487421*^9}, {3.905613494101008*^9, 
   3.905613519051817*^9}, {3.90561354932579*^9, 3.905613549978897*^9}, {
   3.905613613303297*^9, 3.9056137342070208`*^9}, {3.905614182849924*^9, 
   3.905614196034919*^9}, {3.905614267789156*^9, 3.905614273591136*^9}, {
   3.905614313533764*^9, 3.905614329354846*^9}, {3.905614416118466*^9, 
   3.905614423756351*^9}, {3.9056146759948797`*^9, 3.9056146767918167`*^9}, {
   3.9056151340913677`*^9, 3.90561517224046*^9}, {3.9056152118177557`*^9, 
   3.905615214091358*^9}, {3.905615252759769*^9, 3.905615263352913*^9}, {
   3.905615345649466*^9, 3.905615374468997*^9}, {3.90561548267632*^9, 
   3.9056154968400993`*^9}, {3.905615751779393*^9, 3.9056157664118233`*^9}, {
   3.905615811233103*^9, 3.905616009982396*^9}, {3.90561604412062*^9, 
   3.9056160546292677`*^9}, {3.905616112659197*^9, 3.905616119555298*^9}, {
   3.905616193525331*^9, 3.905616202376616*^9}, {3.90561623434896*^9, 
   3.9056162579100447`*^9}, {3.905616318600956*^9, 3.9056163637374067`*^9}, {
   3.905616627361327*^9, 3.905616789837139*^9}, {3.905616896195166*^9, 
   3.9056168966233473`*^9}, {3.905617118811655*^9, 3.9056171914875183`*^9}, {
   3.905617255363351*^9, 3.905617304087985*^9}, {3.90561733555258*^9, 
   3.905617338820792*^9}, {3.9056173954874687`*^9, 3.905617431360471*^9}, {
   3.9056175206109447`*^9, 3.9056175773333597`*^9}, {3.9056176532804728`*^9, 
   3.905617657144596*^9}, {3.905618619745846*^9, 3.905618723006199*^9}, {
   3.905619188188505*^9, 3.905619258342877*^9}, {3.905619426500511*^9, 
   3.9056194599498367`*^9}, {3.9056621613621407`*^9, 3.90566217616637*^9}, {
   3.905662630742077*^9, 3.90566263752293*^9}, 3.905662685759055*^9, {
   3.905662865977788*^9, 3.905662868535495*^9}, {3.905662959070191*^9, 
   3.905662982684004*^9}, 3.905663468719267*^9, {3.905663618298798*^9, 
   3.905663671271834*^9}, {3.9056637288181877`*^9, 3.9056637475049667`*^9}, {
   3.905666174797846*^9, 3.9056661801370773`*^9}, {3.905666214180964*^9, 
   3.9056663117664633`*^9}, {3.905666356968383*^9, 3.9056663580875587`*^9}, {
   3.905666389377749*^9, 3.905666414478346*^9}, {3.9056673536618843`*^9, 
   3.905667382235783*^9}, {3.905667668199527*^9, 3.905667735432425*^9}, {
   3.905667822700568*^9, 3.905667830415557*^9}},
 CellLabel->
  "(Local4) In[47]:=",ExpressionUUID->"befb799c-2f21-4d29-adb2-bbe5a98dbad4"]
}, Open  ]],

Cell[CellGroupData[{

Cell["Curves for 300 PLPP realizations", "Subsection",
 CellChangeTimes->{{3.905692237939126*^9, 
  3.9056922472657127`*^9}},ExpressionUUID->"7edb88c8-2e94-49d1-bb8b-\
5828f2c27561"],

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", 
   RowBox[{
    RowBox[{"table300", " ", "=", " ", 
     RowBox[{"Table", "[", 
      RowBox[{
       RowBox[{"solAll", "[", "cpi", "]"}], ",", " ", 
       RowBox[{"{", 
        RowBox[{"cpi", ",", " ", "1", ",", " ", "300"}], "}"}]}], "]"}]}], 
    ";"}], "*)"}], "\n", 
  RowBox[{"(*", 
   RowBox[{"exportAux", "[", 
    RowBox[{"\"\<listRandomSample.csv\>\"", ",", " ", "listRandomSample"}], 
    "]"}], "*)"}], "\n", 
  RowBox[{"(*", 
   RowBox[{
    RowBox[{"exportAux", "[", 
     RowBox[{"\"\<table300.json\>\"", ",", " ", "table300"}], "]"}], "\n", 
    RowBox[{"dumpsave", "[", 
     RowBox[{"\"\<table300.mx\>\"", ",", " ", "table300"}], "]"}]}], "*)"}], 
  "\n", 
  RowBox[{"getAux", "[", "\"\<table300.mx\>\"", "]"}]}]], "Code",
 CellChangeTimes->{{3.905692257987692*^9, 3.90569231185773*^9}, {
  3.905694672100316*^9, 3.905694676039793*^9}, {3.9060196986648283`*^9, 
  3.906019727632621*^9}},
 CellLabel->"In[76]:=",ExpressionUUID->"1530ea50-817c-4365-adeb-0f5fb0dbbfe9"],

Cell[BoxData[
 RowBox[{"\n", 
  RowBox[{
   RowBox[{
    RowBox[{"dataKxM95", " ", "=", " ", 
     RowBox[{
      RowBox[{
       RowBox[{"{", 
        RowBox[{
         RowBox[{"listk1", "[", 
          RowBox[{"[", "#", "]"}], "]"}], ",", " ", 
         RowBox[{"Quantile", "[", 
          RowBox[{
           RowBox[{"table300", "[", 
            RowBox[{"[", 
             RowBox[{"All", ",", " ", "#", " ", ",", " ", "2"}], "]"}], "]"}],
            ",", " ", "0.95"}], "]"}]}], "}"}], " ", "&"}], " ", "/@", " ", 
      RowBox[{"(", 
       RowBox[{"Range", " ", "@", " ", 
        RowBox[{"Length", " ", "@", " ", "listk1"}]}], ")"}]}]}], ";"}], "\n", 
   RowBox[{
    RowBox[{"dataKxM50", " ", "=", " ", 
     RowBox[{
      RowBox[{
       RowBox[{"{", 
        RowBox[{
         RowBox[{"listk1", "[", 
          RowBox[{"[", "#", "]"}], "]"}], ",", " ", 
         RowBox[{"Quantile", "[", 
          RowBox[{
           RowBox[{"table300", "[", 
            RowBox[{"[", 
             RowBox[{"All", ",", " ", "#", " ", ",", " ", "2"}], "]"}], "]"}],
            ",", " ", "0.50"}], "]"}]}], "}"}], " ", "&"}], " ", "/@", " ", 
      RowBox[{"(", 
       RowBox[{"Range", " ", "@", " ", 
        RowBox[{"Length", " ", "@", " ", "listk1"}]}], ")"}]}]}], ";"}], "\n", 
   RowBox[{
    RowBox[{"dataKxM05", " ", "=", " ", 
     RowBox[{
      RowBox[{
       RowBox[{"{", 
        RowBox[{
         RowBox[{"listk1", "[", 
          RowBox[{"[", "#", "]"}], "]"}], ",", " ", 
         RowBox[{"Quantile", "[", 
          RowBox[{
           RowBox[{"table300", "[", 
            RowBox[{"[", 
             RowBox[{"All", ",", " ", "#", " ", ",", " ", "2"}], "]"}], "]"}],
            ",", " ", "0.05"}], "]"}]}], "}"}], " ", "&"}], " ", "/@", " ", 
      RowBox[{"(", 
       RowBox[{"Range", " ", "@", " ", 
        RowBox[{"Length", " ", "@", " ", "listk1"}]}], ")"}]}]}], ";"}], "\n",
    "\n", 
   RowBox[{
    RowBox[{"kXm95I", " ", "=", " ", 
     RowBox[{"Interpolation", "[", 
      RowBox[{"dataKxM95", ",", " ", 
       RowBox[{"InterpolationOrder", "->", "2"}], ",", " ", 
       RowBox[{"Method", "->", "\"\<Spline\>\""}]}], " ", "]"}]}], ";"}], 
   "\n", 
   RowBox[{
    RowBox[{"kXm50I", " ", "=", " ", 
     RowBox[{"Interpolation", "[", 
      RowBox[{"dataKxM50", ",", " ", 
       RowBox[{"InterpolationOrder", "->", "2"}], ",", " ", 
       RowBox[{"Method", "->", "\"\<Spline\>\""}]}], "]"}]}], ";"}], "\n", 
   RowBox[{
    RowBox[{"kXm05I", " ", "=", " ", 
     RowBox[{"Interpolation", "[", 
      RowBox[{"dataKxM05", ",", " ", 
       RowBox[{"InterpolationOrder", "->", "2"}], ",", " ", 
       RowBox[{"Method", "->", "\"\<Spline\>\""}]}], "]"}]}], 
    ";"}]}]}]], "Code",
 CellChangeTimes->{{3.905693506081048*^9, 3.905693532661688*^9}, {
   3.905693589980736*^9, 3.905693658462379*^9}, {3.905693700253523*^9, 
   3.905693717506909*^9}, {3.905693776267274*^9, 3.905693785587833*^9}, {
   3.905693822480578*^9, 3.905693824980921*^9}, 3.9056939761081333`*^9, 
   3.905694194655819*^9, {3.905694332624251*^9, 3.905694371379525*^9}, {
   3.905694444810359*^9, 3.9056945033964577`*^9}, {3.905694694681081*^9, 
   3.9056947406699266`*^9}, {3.90569484455048*^9, 3.9056949377382317`*^9}, {
   3.905695041778406*^9, 3.905695149531247*^9}, {3.90569517953335*^9, 
   3.9056952350442953`*^9}, 3.90569594019909*^9, 3.905696006311873*^9, {
   3.9056963484953003`*^9, 3.905696373720901*^9}, {3.9056965193115*^9, 
   3.905696540714879*^9}, {3.905699990969532*^9, 3.9056999968498507`*^9}, {
   3.905700076812274*^9, 3.9057000813936453`*^9}, {3.9057002131736794`*^9, 
   3.9057002144635277`*^9}, {3.9057002887391233`*^9, 3.905700288996612*^9}, {
   3.905741358292815*^9, 3.905741361039722*^9}, 3.9057775056276197`*^9},
 CellLabel->"In[77]:=",ExpressionUUID->"4becaa35-ee83-4192-b38e-1f3a0df12e37"],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     RowBox[{"kXm95I", "[", "k", "]"}], ",", " ", 
     RowBox[{"kXm50I", "[", "k", "]"}], ",", " ", 
     RowBox[{"kXm05I", "[", "k", "]"}]}], "}"}], ",", " ", 
   RowBox[{"{", 
    RowBox[{"k", ",", "0.5", ",", " ", "3"}], "}"}], ",", " ", 
   RowBox[{"PlotRange", "->", 
    RowBox[{"{", 
     RowBox[{
      RowBox[{"{", 
       RowBox[{"0.5", ",", " ", "3"}], "}"}], ",", " ", 
      RowBox[{"{", 
       RowBox[{"0", ",", "5"}], "}"}]}], "}"}]}]}], "]"}]], "Code",
 CellChangeTimes->{{3.905695251988264*^9, 3.90569525360291*^9}, {
  3.905695973025824*^9, 3.9056960508424873`*^9}, {3.905696330105577*^9, 
  3.905696332443211*^9}, {3.90570001028308*^9, 3.905700016804605*^9}, {
  3.90570022828189*^9, 3.9057002470238047`*^9}},
 CellLabel->
  "(Local4) In[63]:=",ExpressionUUID->"5761500c-fc4d-4941-9af3-4d1ed449d742"],

Cell[BoxData[
 GraphicsBox[
  InterpretationBox[{
    TagBox[{{{}, {}, 
       TagBox[
        {RGBColor[0.368417, 0.506779, 0.709798], AbsoluteThickness[2], 
         Opacity[1.], LineBox[CompressedData["
1:eJwdV3k81d3z5/O57r3ZQwsSRZQHRVqUmtGishSVoqQolD30JMtTKtJiqZSl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          "]]},
        Annotation[#, "Charting`Private`Tag#1"]& ], 
       TagBox[
        {RGBColor[0.880722, 0.611041, 0.142051], AbsoluteThickness[2], 
         Opacity[1.], LineBox[CompressedData["
1:eJwdl3k81N/3x8f2ftuXkAhtypq0WKKck0SJaNPmU0gqZUkoSylbIkKlRakQ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          "]]},
        Annotation[#, "Charting`Private`Tag#2"]& ], 
       TagBox[
        {RGBColor[0.560181, 0.691569, 0.194885], AbsoluteThickness[2], 
         Opacity[1.], LineBox[CompressedData["
1:eJwVl3k81N8Xxof5zEyyllCKhCSkQrQ6hyShBVkqCqVoE4lEJSFKiJTlGxGS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          "]]},
        Annotation[#, "Charting`Private`Tag#3"]& ]}, {}},
     {"WolframDynamicHighlight", <|
      "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>}], 
    DynamicBox[(Charting`HighlightActionBox["DynamicHighlight", {}, 
      Slot["HighlightElements"], 
      Slot["LayoutOptions"], 
      Slot["Meta"], 
      Charting`HighlightActionFunction["DynamicHighlight", {{{{}, {}, 
          Annotation[{
            Directive[
             Opacity[1.], 
             RGBColor[0.368417, 0.506779, 0.709798], 
             AbsoluteThickness[2]], 
            Line[CompressedData["
1:eJwdV3k81d3z5/O57r3ZQwsSRZQHRVqUmtGishSVoqQolD30JMtTKtJiqZSl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             "]]}, "Charting`Private`Tag#1"], 
          Annotation[{
            Directive[
             Opacity[1.], 
             RGBColor[0.880722, 0.611041, 0.142051], 
             AbsoluteThickness[2]], 
            Line[CompressedData["
1:eJwdl3k81N/3x8f2ftuXkAhtypq0WKKck0SJaNPmU0gqZUkoSylbIkKlRakQ
oayVLKUQoSikjSxjT/YZzOb3/v7mn3k8HzOPe899ndc5954lzp67jvHTaLRy
Phrtf9919gcDLPl6gPb/Hzn8ZeuzorStBxyOFE3OJsjiIf86o+en+mDR8q96
C+vmYbh0xQ1P5QEY+9pA7xuUQZfkjwrlSwdA3KbV+XGfDJrrNCZJag6AqqEa
/2G6DPJvbUt9rj8Aa/bfeNzeJoMXg5mFf3cMANHw9iizUQb9RrRajl8eANdI
K0bMKxl0/XRDzrGPWs9I32ZvuAxujTx2yy5vEAZD9n0x15TBP0mxB9WLBqHW
aKDceoUMns0tWsR7MwhyHwp09y2TweRWkazs+kH468i4elZFBhlqOW+J/kFI
f6JnWCcjgynvmf1lKkOw9Wjw6VGWNHJZV4w1o4dgQ+4FM8VGaSxwz+rgc/0L
vs9FjmRclMZiZ7P8Itl/UBLWKDy/QQoPGkVoXksbATfp55fZhZJ4/PPVMvvs
Efj2dy9bIFcSfZxjbJcUjIB6qPZXIksSY6/d9H1VPgKJvQ7x7IeSWNmZ8r7z
1whc9v9x9HG0JOpcLT+gLzMKKe1rdv5xkkTez5mrfy6MAu22j42KqCR+faPv
e0d7DHQatD/lbpPABZ2CnErdMfj+5QqzdLMEOvK3hIyuHoMQwTiDyo0SOGbh
HWdhNAbNvLTpitUSKPUlJ3vKfAw8oevCFUUJtOlW77Y7PAZBYyn31AbEsZZQ
shWJH4M5me3yuZfF8b0tTyOAOQb6X/jDVDPFUGNB2+tbs2Owdam3xPUUMYzt
LN6azxmDZbQdeQL3xdDhjO+JAf5x0Diy3Ww2VgxnEoYz7KXGITjL4ba8rxjq
tf5asVZjHFz8fgrJmonhI4citeED40DQTaYWd4jipZNeiw+/GYcSqbT5V5eL
YoVPh92bd+OgX7v75ZVFoih4acdl5apxCNnsqR6tKIpXE3W6f9WNQ2TAYPgj
CVFMqBxI3fdjHJwmhrSFmCL4RMVJfefkOGiJLFV+VSOCdV936pprToBJs2PM
Kw8RFG9/dzhVZwLq0iPv2p4UwR0Dq67z602Alomy/7+jItjMkxh7ZzABB9Mj
CgwPiGCbdl3+RvMJuBxxQpIwF8GRcDN9wyMTMObu6BalJIKyxms3aN2aAFcZ
ZdMt9cI4/8Fopu2dCZhYxrvwuVoYlWjPFHyTJuDBhxrVgxXCuLhabbL88QTs
eSUTeqlYGHV3zc/amzMBaHOple+pMFq5zSpcrpmA+Ts/Pm0NF8aQe+WT32cn
oCxPgP3RXBgjuIFOXM4EbMn4vq8dhfGqo1HjUtokTOjckGduEMa4FflZ7sQk
pPe+K1ynL4zJBSlOArKTcF18OqBvuTCW1IU36upMwhG9hnXKwsI4wdqeHX54
EniN6vZfGkn8+uhu8YjTJGyru39Z4xOJeRb9NfuOTUJEzsKm8I8kuieE9Gie
noT6dYbdtu9JHNAsVmnwp9Y36n27pJDEjv0r4ubfmoQpZRW3stskfnpF882o
nwTTA5wrn11IzHbYESrdOAm+8Tl76pxIjOK/H+/fNAn3Ct0sPh0m0XKHYc72
n5NQ9JJ2t2M/iRW97v2jfZOwJD+VtdmGxNdyvw8Y8U9Bg3mxNp8hiU+8X5rW
Gk3BQFEMY4wkMe2tjP3SDVPQ2fLg8TdBElNEPdwDYQqaLZ9+LeQjMTllxf2V
FlOQverZGwc2gYlNt2fjd0+BCun1wXGEwIg1AS8OekzBvG/9N1Y3E+g6Yao1
nDoF+v9u6zBvE+himrRpS8YUxNZO7BO7SaBz1PT+5CxqP7YlqRRH4OGleVfs
8qfA17lrfFkkgfa7lvS+eDsFroZfmIPnCLQoEHh04ecU7KEll5vaE6ju/VFe
SooB7pIsazFJAvvkvd105zFAmp5bliJCYHrxwnIbeQZkSdyMXCdEoBqf54lr
CxnQ4NK/zpIjhIvj5EtFNBhQpVTSoTEkhEo5zo6Cmxjg9kTqYnuVEEoOcbJm
vRnwTD+wXcxPCD/HpM8t8GOAXy27acRLCK+ttttj5M+ADYVZap9OCaGYfyrX
L5gBeZE32nydhFBY2MpuKpoBFibxyeHWQsi/4jZjJI0Bl+6VhLcvEUKG02rs
aWXActk7L+43CmLc1tP6lr8Y4Cx4XGp9nSBqrcrQymqnuMIi4HeVIDpylOW9
ehhwO83o0poSQaxLFB5ijzNgiq/PWvOJICbXd9yQlWCC4+Ljg+uDBNFCP7bf
bDMThIf5V/XrCmLnwtq2JxZMkPf9G71FSxAD+QWbhK2Y0FnXM5O5XBDzGv3L
GuyYUNgmIhCuLIhKbsfiDx5mwpa7Kj9CRQVxJHmDibc/E5T9ToWn9QvgbeG/
sY9zmZD49tHwmXQBnLA4+76ugAniz87otKQI4I5w9uTkS2r/i8dfmDwUQIJf
/IBFGRPuN76/r3RHAH3YOsv+fmSCgebqRoUoAdw14lG0rpsJKq9YJVKeAijZ
MtFRIzcN1QbrcxgbBDD8IUtvxH8aeL/P2UZ086Plv4PTS/fOwPX9tqEr5fjx
R4UL30GdWVhsukj/gzEfvoysOryYMQt1reSD2jM0dBXy7WxoYMHrVY/zIvXn
4Kh34Evxe2wQcFh7MyqKCwZr/rzUfMCGtUcERypDuSA6ga8sHrHBmJvlxw7i
Qt4ZouhSOhv+iPjLHfPkAscr/vVUARuOHlsQsnQPFxI9M0rb6tlweLnLcgsV
LtSebn7/jMuGNbWrrunlcOC+jkFFLY0DXefl1PQyOOA1fKeiT4AD5gJWGQaP
ODD/9OHKxaIcMDW5m+CcwAHnU4NVN+dzYMbwI0f/HAc4J+dqglZxIMLlxKJ6
Mw6sOq7dYO3EAeGo/Ac5XVRcJxd5PnfhwFitm/v532y4dlpWWvIEB5g6jYd2
fGPD4Bn2zkYPDux2uHtTtZYNqUH133YGceCg41o/u3w2KCScare/zYFU7oXZ
2VA2VN88crHoHge2eQ4Whl9kg8/t3YsWJHNAQpAWo+LPhq/3TZx+pnGgJ1E3
6YwHG6IzxHoPFXCg2ylePfsAG+bKsocdP3NAIcad5rKGDTnlD2Pef+FAkF70
k/yVbHCouKG7tIUDbObuk2KabCiuCfSi/+LAzn991vRFbDjbtH3q2AClT/C8
MDVJNvT3/2W7CXDBxehSwfAwCxKHOu7XE1y4ImFnxhlggfm/5o06olyoEqof
U+hlweOJ0uB/0ly4caQi82w7Cw5xowW8VLlw8fWr6DLKB43zdMR813MhZu6l
1M1CFpi6uw8mbaDy2m95IymPBTk1OTUVwIUHls1pz5+zIDZodZi0BRcCTree
Gc9ggXWfATd7FxeSrWMLp++zoAzP/27ay4WnI3/Td99jgU5ScfHsfi70k5s1
Sm6zQMxug5/lES7QHrW3pCewoK5402j3KS7cc636xotkgbFc6GcRyldmFf+M
ciNYkOVRla3nzQXlW9JabmEsuLrM8sTF81zweGT2ai6YBVtjrLsUw7kQaLPf
L/McCz447mu2S+aCY615/J8TLFhXeif/3GMuZEo1GogdZ0Ga/K/ryWlcGBpv
kNY5xoKwOgfr4SwuOEStcrZyYoHZOucPV4q4MCPqEzC7nwUFsampOSVckFqd
XVljz4Klgz2Xv73hwuLJfZui9rCAL/m46bIqLqzePu/XX1sWvCPdi95+4YLw
dtHLSyxYoOecc6u3mQsjdiPu8ZtZ8Khs9Kz4dy40TFheZyALgs946x1sp/Ih
6uB5z4TS//e5TMYgF+Kvkk/s9VhQmhOSpCPAg8TqU313FFhAWO9Vuk3w4P7X
FZWCcizYOah+l0+UB2Z501XO0izoX/Y5sVWaB6cHfhkyhFkge1ch4ZIqD9A8
49fZ2Vk4FfossmU9D1oy98n9+D4LrxYHk7CRB99GPM1cm2eB7+3OiEzkgR+Z
fKuvYRZuzzBDL1ry4HahSfabD7NQ6b4pWGMvD/ZNB934UDALC/e3+gZ58aBG
R2H/hqhZcGU8neo7y4Oq7Gvfh8NmIT8h8OzOczxw5CkEXQ+eBcvPi8+suMiD
c6pe67J9ZuGs2anTX6J5sMxqhfOGw7NQr0M7qpbBA0/brPwPurMQyKdl96md
B59kZJb4fJiBPnOxHyu6ePBY/ZV11NsZsIscPnK5hwcBhytVbhTNgJpUrqfB
Xx6sWTU/LyhzBj4pr7v+aIYHbxwe3Mq9NgOqRqYNPrJzYDyw2uWm3QxUeOyy
Vtk2BxbeWrJ+X6ZBp2BtyznrOajetPBnwsdpSGTIOTTZzkFQ9bXrpe+m4VTQ
91NX7OcgYnT8s17+NMhFOUSPH50D9XdVcVkJ0+D6xLXuw8U5uHTomu7vfdMg
2haw1ePFHCQGpNbp/aX6/LlMietFc3C1XNp1fS8TnOb9aMotmYP1N2NdrDuY
8Hqr/n/j7+agZbg0Kr6ZCa4vR8/4fJ6DkYPtgXeoe+N9rEtSQN8cFGmZjN+J
Y8Kw5g3HpME5uHIq/41lNBMWfHi/vGx4DmQ3GP2jRTDBg62ax52Yg2PXzvkm
BFL31omfVZfm5mB0sExrzXEmlC1WP7dZnIYJd5w1XJAJuzze/myWoKHpt67l
xSZMGCjdu8FFioZpj89ELDBkguy+ML7weTTMHazwYq5kgltMV3T1AhpmGOgM
6SpT+7OSHm1bTkONKkWvBBYDcizXCvxaQcPnnMfJMUwGmN+qO+amQcOxKmO9
GxMM8NSb1YrWpmGBYHLQmyEGVLvav/y0moYLNmmXxP5mwNlm6TpbUxoGPHf8
uKycendUjHH4kIYG877UBJUyICD/y6oXm2h4+OIJXlcR9a64HndrwRYazpyW
k/max4DY7dJOXdtpiKn7P21KZUBmpdSM9wEaGvsk3HOPot41BaNayw/RsMI2
QTzqCvVuedz433cHGr5eU/qyIIwBr4KvV5o40nBIMvK5BvWuqTKRui54nIZ8
d2mY7sOAjkLJFYk+NIx72j09e4QB22+Kh7Rl0VBH+MR5MWEGbLMppOtJ8+HQ
o6RVZ2ymQLdO93jEWT5cwbiUJH55Ei6kNHFsO/jQ8LzxdHA69e73XrKhazM/
JtWN5Tj/GYevyXdi+vL40WJPwa1PguPQWlESWThfAAPvqD3hXz8GlVn5Ty4H
COBDa7v7A90joDTypaWyTwCL1c+JzKz+B7c1k55/3i6IL1NKm7bc/wsX38Xc
2V4siP6dkaEX+gbBeuHeJ3VqQlgdLDmluHkA0KPmkMxVIRw7BhqmOX3A+jFo
URUlhOkivtH/0vugcLP4mnPXhPB7hv3knYd9sEJxp3D7dSG836zylR7XB+JV
v148TRTCyoHSqm1n++CH4ogEpgmhn4jhNXvDPvD8IPfOo1wII9Q0758t6wUN
PcPsJe+FUE/hz83UF73Qfe9AYkuFEO4QhITGZ72wxyv5tHG1ELI+CyYtfNAL
xgs1FInPQtil+qgn9EIvEGdMvB/8EkLFIvn9tzb2QrKys9onhhDqvueUl5b0
gNFabV3naSEsrxErnC3ogaZtU4YzM0JoLvl05brsHiDORWxXo97BKw9FFicn
9YDH1yzvIH4CR2x8tx4P6gGImHynI0Xg6l2P5hlu6oFf98vqKqQJVPDwktEx
7gGfwvCW/fMItDt8xEp/bQ887VQYCJMnML/0rlvY8h6QNtkg1b6QwEVul1zk
xXqgczTsvxgNAt/ekjfl/0WHAGLH8WVaBN5kNv0xbqGDnIrCmWJtAou1c4uv
NNBhq1VmWK8uFc+8KpXDlXTIT/ucvVGfQKFvRx5yn9PBujTxZbMBgTY/ZGV+
PKVD39cj5SeNCBzI7SurTqWD0tx40y0TAoXbBio679Ih5MB81r9NBM6qH4kk
r9BB2atDIGwzgSWfRepDQ+jwKuKphNIWAmstmy3lLtJhqNB4icVWAr+9rhg9
40uHXZJHtibvIPBerOzsomN0GFbT2LXOjsCvrS/ETZ3oEGEyfqhuJzW3TPoc
9PqPDiUnQj2Zewi0ztyZJmNPh2WVGYk7DlFzivCFcYutdPikM5PW5kDggiOj
c/O30MEvcWuh22Hq9+GBi6xNdKg7OdgY4UTgkdwzDWwTOvg0r/8jd5RA0R7a
Q8X1dFDZGDWc4kLgHjuFTisDOnhJa4uUHyewsvFnYb8edf6AQAWbkwT2d4db
7NalQxW9fvlvNwKzVhZva9Kmg0LRabNpdwLF3V4+FlWnw9v/cgJX+RC46aLg
HRdVOpyo4V1940vggR1DOaeU6TBvte2d7dQcJmO/zyBCiQ7HBMdeHA8g8D/x
mkTGfDpIemAlI5DA8ZJaTyt5Orz+Hvc19AI1dz3eXVwgSwfx7NUjDy8ReFSO
++CNNKW3XAhnZQiBXo+V1ztK0eHIxSbRslACVVwrzedL0kF4YKmiVTiBJ53H
33WI06Fg51n1HxEE7kxMf14mRgeH0kp9V2pO/MVHF30uSgdiuZz51FUC+Z6k
/8gToUNerMuukGgCq4LH538UpsOBmReO0jEEaiZUfpgg6cDvLOSZHEugTpty
rx7Fz+r3XtCh5tBP/3F9Qgg62OunR5fEEyimcMy3X4gOtIfMu1tvEDhI7uk7
QnGWsOXTVmqOddWrq/krSIfd3rdfuSQSeDmuRjGaYs7v/qoJau411rBu20hx
+haj5kt3CUyY3iclSLFdbmSXZBKBkbyhgnYBOrAW/By9f59A1Y1CNXUUp4Vo
8rSSqfMWpm+vp9hm2F+8+CGlp1MjdlDM3FunZPmYqh+L4HSCWu9RuZLmtxQC
046+CtpEsZXmKcOjaQTueu1TeZ3iqYTSLeNPCEw2LwkYpziZI7YnOIPAKOEr
Ka7Ueba6OjhLZBIoJ/jbeJTiicZnXklZBG4wfLU5mtIjaT33ouYzAvlTFrwx
pvQyT7WJKXpO4HFz/gwuxSPiyUlbcgl0Uz3L10LpbdZp+tqpgEBb/yGylMrP
8Lbr1aOFBOqyxgrrqfzdKuxoufCSwGcFF7+MUvkdiLg0fvc1gWF1qw55U35I
GPsyp15C4B/N3bVfKL9sOLhE8lUpga3vuBlm8+hwfWWFVtNbAlNuDbxypPyW
bnRIJOQdgaSGmM4aBcrPm6f6V1cQ+FtPMVRJkdr/wIon8R+o/D6Zbl2lQukT
EbVo5ycCm5XfyruvoINT/DIerYHqB43nPw9p0OH8/bK2vEYC/UJdSuypesko
GLkr3Uzg1CIlzuQqOgh27JL78pPyx0qeqrkR1U+G/k4E/6b8RCbtVjemw1pG
2NdV7VR8D3Ro01T9OosVxV7vJPDu3Mr3h4AO/vPt3KGbwPn1D76NIR3ilgxu
H6UT+G8Xv7O3GR3KDReK2PYT+PB2Zrcx1R9azV708wYIDNwz3HrZgtLbxqY6
Z4jqt5+XbX5pSQehA31ph4cJNBGwU/9G9Rdll+BQyRGq/zK8Qru20WGd5wLn
t6NUPadG7PtlRYftAfnoMU7gX4n41PLtVHzhVotUJwlsWRd3PN6a6s9xdO7n
KSq+BWGptjZUPpKC2i4wCcwtOr2PRXFmunzpyhkqPlmr0PgddHiXn3O3fZbq
X9rK6vK2dPhRZnk+hk1gBI1uFk7xaE2n/UYugRfik1u7KCaa/fX/8Qis/7Oj
W8uODqp/5sk9oJHoPTB5zJFi/cHsCWt+Ej1zYpxCKLaeMv/KESCxSk/5WxzF
LnPtuc+ESPTyfPgumuJA0XOxDiSJvm4KamcpTpCXdhcXIbFxSdicBcVZizO3
l4mSGHardxdJ8XttM63T4iTGfDBRffG/eA1+CytLkjiWH+FkQ/HYJp/+eikS
nx6sVm6mzkfaSFQHypBYWs6y3UKx6v70NG1ZEpd1LWOnUnoYHIXQ33Ik9rzd
pDpK6Wfj8cMpej6J7P17ildQ7OJ/Bk0WkHgq99AnK0rvoDDRRX8VSVxdsW/f
ISofWfc2tFmpkFitrPttE5W/iiffSliqJN50Ef6oQOX3Z57H3azFJBaf+L7m
F+UH4ZpH9qJqJIqk7/ZS20yHRU3r9UuWk6jfQdv8jLo/DNqbZN3Uqf+3pMQs
pvx1bFLwa60WiR+mqqIaNlD9M8u8wUGHxAd2WcbqlD/3OIXVj66k9G6gD3hQ
94t5o0C1/GoSeat2Y70+VX8RmyufriGxRPbqYMdayk8bQ9+ZrKP0V5SNp6+m
g1o2f6mTIYkfo5b9LlpJ+c/Z7PWUEYknmZkXIqn6kVMMeXnFmEQiLEx1qyZV
P1f48p5vJFFdyODQTTU69DjTnsxuJlH5YdQ7R+p+aVPElGtbSIxUKtibSdVz
y5fgh4ssSfxXtHKwU466z0zn7m6xIjFt/xIxFapfpCnxYuPtSHy3mmVcy0+H
o03s85r/kVhk5m013tcNB6+a+JUdpuJv/12lSe+GXRh41taRxMJ7dzfu7OgG
sxyWu+9REm8EyGi5f++GpVGzzu9PksjXNDHyo7obujdNWx/wI/FOR6DGpZRu
+DVjYDV8jsSV99Qjnz7ohqZcP8tgf8offup95Xe6oUKFuelJEImVt5Y9KI3t
hpTZKYPxEBIvn5KY7vPvBqf8icVXr1Px+mYclLDpBreQ3RyreBLtWvxf+Fh0
g8/uF9/Fb5A4rSPbXg3dEMHwjY1LJDHh07172mu64dn6WfbtByT2VXGrmfLd
MPN+rjU9m9Lv3rzeGz+7gP+GY8GJ5/+Lb4/2069dIObyPkYrl8RDN//DjNou
UCVCzXMKSOT6VbUeK+4Ccyui4GUxic6M3hc9t7sgrkk8pqqGOk/rOYNBuy64
l+p+IqKWxJ3nNU9mWXZBqk/D5q31JArKpbjZm3bBq/lxrPoGEnPWD/z00O6C
toOyJ5q/kbjC9OPJx4JdoE5X3NxNJzFT+/sOicJO0HsRoJrWS2Ktx4x74NNO
MA7/PXusn6qX7M5DLQ86wVr9Qd7gEIkv5Ig0i8hO8D61WHV8nETTh2m9Og6d
ELTh8mzBJIlKhdyAcbtOCJfobvFhkCj/XqXj0ZZOuJObGj0zQ6J1fYHsO91O
SLkkeLyERWJUjXrPqmWdkL3zmFkQh9LvzdHQKIVOeLG0WsWUR+KBHNfxRrFO
eDu5YnZujsSOO3q6NFon/B9VeE6h
             "]]}, "Charting`Private`Tag#2"], 
          Annotation[{
            Directive[
             Opacity[1.], 
             RGBColor[0.560181, 0.691569, 0.194885], 
             AbsoluteThickness[2]], 
            Line[CompressedData["
1:eJwVl3k81N8Xxof5zEyyllCKhCSkQrQ6hyShBVkqCqVoE4lEJSFKiJTlGxGS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             "]]}, "Charting`Private`Tag#3"]}}, {}}, <|
       "HighlightElements" -> <|
         "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
        "LayoutOptions" -> <|
         "PlotRange" -> {{0.5, 3.}, {0., 5.}}, 
          "Frame" -> {{False, False}, {False, False}}, 
          "AxesOrigin" -> {0.5000000000000011, 0}, 
          "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
          "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
          "DefaultStyle" -> {
            Directive[
             Opacity[1.], 
             RGBColor[0.560181, 0.691569, 0.194885], 
             AbsoluteThickness[2]], 
            Directive[
             Opacity[1.], 
             RGBColor[0.880722, 0.611041, 0.142051], 
             AbsoluteThickness[2]], 
            Directive[
             Opacity[1.], 
             RGBColor[0.368417, 0.506779, 0.709798], 
             AbsoluteThickness[2]]}, 
          "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
              Identity[
               Part[#, 1]], 
              Identity[
               Part[#, 2]]}& ), 
            "ScalingFunctions" -> {{Identity, Identity}, {
              Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> False|>,
         "Meta" -> <|
         "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
          Plot, "GroupHighlight" -> False|>|>]]& )[<|
      "HighlightElements" -> <|
        "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
       "LayoutOptions" -> <|
        "PlotRange" -> {{0.5, 3.}, {0., 5.}}, 
         "Frame" -> {{False, False}, {False, False}}, 
         "AxesOrigin" -> {0.5000000000000011, 0}, 
         "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
         "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
         "DefaultStyle" -> {
           Directive[
            Opacity[1.], 
            RGBColor[0.560181, 0.691569, 0.194885], 
            AbsoluteThickness[2]], 
           Directive[
            Opacity[1.], 
            RGBColor[0.880722, 0.611041, 0.142051], 
            AbsoluteThickness[2]], 
           Directive[
            Opacity[1.], 
            RGBColor[0.368417, 0.506779, 0.709798], 
            AbsoluteThickness[2]]}, 
         "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
             Identity[
              Part[#, 1]], 
             Identity[
              Part[#, 2]]}& ), 
           "ScalingFunctions" -> {{Identity, Identity}, {
             Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> False|>, 
       "Meta" -> <|
        "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
         Plot, "GroupHighlight" -> False|>|>],
     ImageSizeCache->{{4.503599627370496*^15, -4.503599627370496*^15}, {
      4.503599627370496*^15, -4.503599627370496*^15}}]},
   Annotation[{{{{}, {}, 
       Annotation[{
         Directive[
          Opacity[1.], 
          RGBColor[0.368417, 0.506779, 0.709798], 
          AbsoluteThickness[2]], 
         Line[CompressedData["
1:eJwdV3k81d3z5/O57r3ZQwsSRZQHRVqUmtGishSVoqQolD30JMtTKtJiqZSl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          "]]}, "Charting`Private`Tag#1"], 
       Annotation[{
         Directive[
          Opacity[1.], 
          RGBColor[0.880722, 0.611041, 0.142051], 
          AbsoluteThickness[2]], 
         Line[CompressedData["
1:eJwdl3k81N/3x8f2ftuXkAhtypq0WKKck0SJaNPmU0gqZUkoSylbIkKlRakQ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          "]]}, "Charting`Private`Tag#2"], 
       Annotation[{
         Directive[
          Opacity[1.], 
          RGBColor[0.560181, 0.691569, 0.194885], 
          AbsoluteThickness[2]], 
         Line[CompressedData["
1:eJwVl3k81N8Xxof5zEyyllCKhCSkQrQ6hyShBVkqCqVoE4lEJSFKiJTlGxGS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          "]]}, "Charting`Private`Tag#3"]}}, {}}, <|
    "HighlightElements" -> <|
      "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
     "LayoutOptions" -> <|
      "PlotRange" -> {{0.5, 3.}, {0., 5.}}, 
       "Frame" -> {{False, False}, {False, False}}, 
       "AxesOrigin" -> {0.5000000000000011, 0}, 
       "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
       "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), "DefaultStyle" -> {
         Directive[
          Opacity[1.], 
          RGBColor[0.560181, 0.691569, 0.194885], 
          AbsoluteThickness[2]], 
         Directive[
          Opacity[1.], 
          RGBColor[0.880722, 0.611041, 0.142051], 
          AbsoluteThickness[2]], 
         Directive[
          Opacity[1.], 
          RGBColor[0.368417, 0.506779, 0.709798], 
          AbsoluteThickness[2]]}, 
       "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
           Identity[
            Part[#, 1]], 
           Identity[
            Part[#, 2]]}& ), 
         "ScalingFunctions" -> {{Identity, Identity}, {Identity, Identity}}|>,
        "Primitives" -> {}, "GCFlag" -> False|>, 
     "Meta" -> <|
      "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
       Plot, "GroupHighlight" -> False|>|>, "DynamicHighlight"]],
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->{True, True},
  AxesLabel->{None, None},
  AxesOrigin->{0.5000000000000011, 0},
  DisplayFunction->Identity,
  Frame->{{False, False}, {False, False}},
  FrameLabel->{{None, None}, {None, None}},
  FrameTicks->{{Automatic, Automatic}, {Automatic, Automatic}},
  GridLines->{None, None},
  GridLinesStyle->Directive[
    GrayLevel[0.5, 0.4]],
  ImagePadding->All,
  Method->{
   "DefaultBoundaryStyle" -> Automatic, 
    "DefaultGraphicsInteraction" -> {
     "Version" -> 1.2, "TrackMousePosition" -> {True, False}, 
      "Effects" -> {
       "Highlight" -> {"ratio" -> 2}, "HighlightPoint" -> {"ratio" -> 2}, 
        "Droplines" -> {
         "freeformCursorMode" -> True, 
          "placement" -> {"x" -> "All", "y" -> "None"}}}}, "DefaultMeshStyle" -> 
    AbsolutePointSize[6], "ScalingFunctions" -> None, 
    "CoordinatesToolOptions" -> {"DisplayFunction" -> ({
        (Identity[#]& )[
         Part[#, 1]], 
        (Identity[#]& )[
         Part[#, 2]]}& ), "CopiedValueFunction" -> ({
        (Identity[#]& )[
         Part[#, 1]], 
        (Identity[#]& )[
         Part[#, 2]]}& )}},
  PlotRange->{{0.5, 3.}, {0., 5.}},
  PlotRangeClipping->True,
  PlotRangePadding->{{0, 0}, {0, 0}},
  Ticks->{Automatic, Automatic}]], "Output",
 CellChangeTimes->{{3.905696002352214*^9, 3.905696051467525*^9}, {
   3.905696332973571*^9, 3.905696359994385*^9}, 3.905700017199814*^9, 
   3.9057000850226383`*^9, 3.905700248480451*^9, 3.90574032289703*^9, 
   3.906019745560081*^9},
 CellLabel->
  "(Local4) Out[63]=",ExpressionUUID->"f54e6261-6723-4017-a99f-e9a196274ad0"]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["Code for arbitrary cPI value - Forecast", "Subsection",
 CellChangeTimes->{{3.905665859592971*^9, 3.905665860650352*^9}, {
  3.905666428987606*^9, 3.905666438658751*^9}, {3.9057016629086847`*^9, 
  3.9057016652819443`*^9}},ExpressionUUID->"c59fee72-1d89-410f-954c-\
b21b6b245b12"],

Cell[BoxData[{
 RowBox[{
  RowBox[{
   RowBox[{"Clear", "[", 
    RowBox[{"tabF", ",", " ", "solF", ",", " ", "solAllF"}], "]"}], ";"}], 
  "\n"}], "\n", 
 RowBox[{
  RowBox[{"probValue", " ", "=", " ", 
   RowBox[{"probSigma", "[", "2", "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"listk1", " ", "=", " ", 
   RowBox[{"Range", "[", 
    RowBox[{"0.5", ",", " ", "3", ",", " ", "0.1"}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"listm1", " ", "=", " ", 
    RowBox[{"Range", "[", 
     RowBox[{"0.1", ",", " ", "5.0", ",", " ", "0.1"}], "]"}]}], ";"}], " ", 
  RowBox[{"(*", 
   RowBox[{
    RowBox[{"For", " ", "the", " ", "Forecast"}], ",", " ", 
    RowBox[{
     RowBox[{"minimmal", " ", "mass"}], " ", "=", " ", 
     RowBox[{"0.1", " ", "and", " ", "maximum", " ", 
      RowBox[{"5.0", "."}]}]}]}], "*)"}]}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"solF", "[", 
     RowBox[{"0", ",", " ", "cpi_"}], "]"}], " ", "=", " ", 
    RowBox[{"{", 
     RowBox[{"arbitraryK", ",", " ", 
      RowBox[{"Last", " ", "@", " ", "listm1"}]}], "}"}]}], ";"}], " ", 
  RowBox[{"(*", 
   RowBox[{"Only", " ", "used", " ", "for", " ", "the", " ", "first", " ", 
    RowBox[{"step", "."}]}], "*)"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"tabF", "[", 
    RowBox[{"nk1_", ",", " ", "cpi_"}], "]"}], " ", ":=", " ", 
   RowBox[{
    RowBox[{"tabF", "[", 
     RowBox[{"nk1", ",", " ", "cpi"}], "]"}], " ", "=", " ", 
    RowBox[{"Block", "[", 
     RowBox[{
      RowBox[{"{", 
       RowBox[{
       "nm1Previous", ",", " ", "nm1Minimal", ",", " ", "listm1Relevant"}], 
       "}"}], ",", "\n", "  ", 
      RowBox[{
       RowBox[{"nm1Previous", " ", "=", " ", 
        RowBox[{
         RowBox[{"Position", "[", 
          RowBox[{"listm1", ",", " ", 
           RowBox[{"Last", " ", "@", " ", 
            RowBox[{"solF", "[", 
             RowBox[{
              RowBox[{"nk1", "-", "1"}], ",", " ", "cpi"}], "]"}]}]}], "]"}], 
         "[", 
         RowBox[{"[", 
          RowBox[{"1", ",", "1"}], "]"}], "]"}]}], ";", "\n", "  ", 
       RowBox[{"nm1Minimal", " ", "=", " ", 
        RowBox[{"If", "[", 
         RowBox[{
          RowBox[{
           RowBox[{"nm1Previous", " ", "-", " ", "10"}], " ", "<", " ", "1"}],
           ",", " ", "1", ",", " ", 
          RowBox[{"nm1Previous", " ", "-", " ", "10"}]}], "]"}]}], ";", " ", 
       "\n", "  ", 
       RowBox[{"listm1Relevant", " ", "=", " ", 
        RowBox[{"listm1", " ", "//", " ", 
         RowBox[{
          RowBox[{"Take", "[", 
           RowBox[{"#", ",", " ", 
            RowBox[{"{", 
             RowBox[{"nm1Minimal", ",", " ", "nm1Previous"}], "}"}]}], "]"}], 
          " ", "&"}]}]}], ";", "\n", "  ", 
       RowBox[{"Table", "[", "\n", "    ", 
        RowBox[{
         RowBox[{"{", 
          RowBox[{
           RowBox[{"{", 
            RowBox[{
             RowBox[{"listk1", "[", 
              RowBox[{"[", "nk1", "]"}], "]"}], ",", " ", "m1"}], "}"}], ",", 
           " ", 
           RowBox[{"Abs", "[", 
            RowBox[{
             RowBox[{"probabilityMminApproxF", "[", 
              RowBox[{"m1", ",", " ", "cpi", ",", " ", 
               RowBox[{"k", " ", "->", " ", 
                RowBox[{"listk1", "[", 
                 RowBox[{"[", "nk1", "]"}], "]"}]}]}], "]"}], " ", "-", " ", 
             "probValue"}], "]"}]}], "}"}], " ", ",", " ", "\n", "    ", 
         RowBox[{"{", 
          RowBox[{"m1", ",", " ", "listm1Relevant"}], "}"}]}], "\n", "  ", 
        "]"}]}]}], "\n", "]"}]}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"solF", "[", 
     RowBox[{"nk1_", ",", " ", "cpi_"}], "]"}], " ", ":=", " ", 
    RowBox[{
     RowBox[{"solF", "[", 
      RowBox[{"nk1", ",", " ", "cpi"}], "]"}], " ", "=", " ", 
     RowBox[{
      RowBox[{"tabF", "[", 
       RowBox[{"nk1", ",", " ", "cpi"}], "]"}], " ", "//", " ", 
      RowBox[{
       RowBox[{
        RowBox[{"SortBy", "[", 
         RowBox[{"#", ",", " ", "Last"}], "]"}], "[", 
        RowBox[{"[", 
         RowBox[{"1", ",", "1"}], "]"}], "]"}], " ", "&"}]}]}]}], " ", 
   RowBox[{"(*", 
    RowBox[{"//", " ", "Echo"}], "*)"}], ";"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"solAllF", "[", "cpi_", "]"}], " ", ":=", " ", 
   RowBox[{
    RowBox[{"solAllF", "[", "cpi", "]"}], " ", "=", " ", 
    RowBox[{"Monitor", "[", 
     RowBox[{
      RowBox[{"Table", "[", 
       RowBox[{
        RowBox[{"solF", "[", 
         RowBox[{"nk1", ",", " ", "cpi"}], "]"}], ",", " ", 
        RowBox[{"{", 
         RowBox[{"nk1", ",", " ", 
          RowBox[{"Length", " ", "@", " ", "listk1"}]}], "}"}]}], "]"}], ",", 
      " ", 
      RowBox[{"{", 
       RowBox[{"nk1", ",", " ", 
        RowBox[{"Length", " ", "@", " ", "listk1"}]}], "}"}]}], "]"}]}]}], 
  ";"}]}], "Code",
 CellChangeTimes->{{3.905611238513006*^9, 3.905611256252783*^9}, {
   3.9056113668113403`*^9, 3.905611383832735*^9}, {3.905611456949306*^9, 
   3.905611550254397*^9}, {3.905611864429225*^9, 3.905611906148295*^9}, {
   3.9056121051412287`*^9, 3.905612151434374*^9}, {3.905612199778463*^9, 
   3.90561221489856*^9}, {3.9056122475125427`*^9, 3.9056123145857773`*^9}, {
   3.9056123662557487`*^9, 3.905612367536484*^9}, {3.905612405905558*^9, 
   3.905612429609185*^9}, {3.9056124697363577`*^9, 3.9056124868954678`*^9}, {
   3.905612891633484*^9, 3.905612896954249*^9}, {3.9056129471049*^9, 
   3.905612957544634*^9}, {3.9056129947367983`*^9, 3.9056132058302193`*^9}, {
   3.905613246293309*^9, 3.905613249975971*^9}, {3.9056133044927998`*^9, 
   3.9056133111765223`*^9}, {3.905613343452026*^9, 3.9056134197945232`*^9}, {
   3.905613450338022*^9, 3.905613452487421*^9}, {3.905613494101008*^9, 
   3.905613519051817*^9}, {3.90561354932579*^9, 3.905613549978897*^9}, {
   3.905613613303297*^9, 3.9056137342070208`*^9}, {3.905614182849924*^9, 
   3.905614196034919*^9}, {3.905614267789156*^9, 3.905614273591136*^9}, {
   3.905614313533764*^9, 3.905614329354846*^9}, {3.905614416118466*^9, 
   3.905614423756351*^9}, {3.9056146759948797`*^9, 3.9056146767918167`*^9}, {
   3.9056151340913677`*^9, 3.90561517224046*^9}, {3.9056152118177557`*^9, 
   3.905615214091358*^9}, {3.905615252759769*^9, 3.905615263352913*^9}, {
   3.905615345649466*^9, 3.905615374468997*^9}, {3.90561548267632*^9, 
   3.9056154968400993`*^9}, {3.905615751779393*^9, 3.9056157664118233`*^9}, {
   3.905615811233103*^9, 3.905616009982396*^9}, {3.90561604412062*^9, 
   3.9056160546292677`*^9}, {3.905616112659197*^9, 3.905616119555298*^9}, {
   3.905616193525331*^9, 3.905616202376616*^9}, {3.90561623434896*^9, 
   3.9056162579100447`*^9}, {3.905616318600956*^9, 3.9056163637374067`*^9}, {
   3.905616627361327*^9, 3.905616789837139*^9}, {3.905616896195166*^9, 
   3.9056168966233473`*^9}, {3.905617118811655*^9, 3.9056171914875183`*^9}, {
   3.905617255363351*^9, 3.905617304087985*^9}, {3.90561733555258*^9, 
   3.905617338820792*^9}, {3.9056173954874687`*^9, 3.905617431360471*^9}, {
   3.9056175206109447`*^9, 3.9056175773333597`*^9}, {3.9056176532804728`*^9, 
   3.905617657144596*^9}, {3.905618619745846*^9, 3.905618723006199*^9}, {
   3.905619188188505*^9, 3.905619258342877*^9}, {3.905619426500511*^9, 
   3.9056194599498367`*^9}, {3.9056621613621407`*^9, 3.90566217616637*^9}, {
   3.905662630742077*^9, 3.90566263752293*^9}, 3.905662685759055*^9, {
   3.905662865977788*^9, 3.905662868535495*^9}, {3.905662959070191*^9, 
   3.905662982684004*^9}, 3.905663468719267*^9, {3.905663618298798*^9, 
   3.905663671271834*^9}, {3.9056637288181877`*^9, 3.9056637475049667`*^9}, {
   3.905666174797846*^9, 3.9056661801370773`*^9}, {3.905666214180964*^9, 
   3.9056663117664633`*^9}, {3.905666356968383*^9, 3.9056663580875587`*^9}, {
   3.905666389377749*^9, 3.905666414478346*^9}, {3.9056673536618843`*^9, 
   3.905667382235783*^9}, {3.905667668199527*^9, 3.905667735432425*^9}, {
   3.905667822700568*^9, 3.905667830415557*^9}, {3.905701671077368*^9, 
   3.905701742458806*^9}, {3.9057018705504723`*^9, 3.905701911794827*^9}, {
   3.905702286669845*^9, 3.905702310205061*^9}, {3.90570236813536*^9, 
   3.905702373174576*^9}, {3.905702431490293*^9, 3.905702433037472*^9}, {
   3.90570246675418*^9, 3.905702476616034*^9}, {3.905702580300428*^9, 
   3.90570259388713*^9}, 3.905702632689417*^9},
 CellLabel->"In[54]:=",ExpressionUUID->"7a70f86a-ed7d-4a03-a47f-bfb7d2a96e20"],

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", 
   RowBox[{
    RowBox[{"table300F", " ", "=", " ", 
     RowBox[{"Monitor", "[", 
      RowBox[{
       RowBox[{"Table", "[", 
        RowBox[{
         RowBox[{"solAllF", "[", "cpi", "]"}], ",", " ", 
         RowBox[{"{", 
          RowBox[{"cpi", ",", " ", "1", ",", " ", "300"}], "}"}]}], "]"}], 
       ",", " ", "cpi"}], "]"}]}], ";", "\n", 
    RowBox[{
     RowBox[{"exportAux", "[", 
      RowBox[{"\"\<table300F.json\>\"", ",", " ", "table300F"}], "]"}], "\n", 
     
     RowBox[{"dumpsave", "[", 
      RowBox[{"\"\<table300F.mx\>\"", ",", " ", "table300F"}], "]"}]}]}], 
   "*)"}], "\n", 
  RowBox[{"getAux", "[", "\"\<table300F.mx\>\"", "]"}]}]], "Code",
 CellChangeTimes->{{3.905692257987692*^9, 3.90569231185773*^9}, {
  3.905694672100316*^9, 3.905694676039793*^9}, {3.905702003076253*^9, 
  3.905702038268457*^9}, {3.90570208192509*^9, 3.905702087173209*^9}, {
  3.906019759570122*^9, 3.906019778612918*^9}},
 CellLabel->"In[47]:=",ExpressionUUID->"88b75337-1af3-4710-ad45-ee511381cdaa"]
}, Open  ]],

Cell[CellGroupData[{

Cell["Plotting all the results", "Subsection",
 CellChangeTimes->{{3.905777195485314*^9, 
  3.905777204230332*^9}},ExpressionUUID->"86c21601-9b68-47a6-8220-\
134873a4c556"],

Cell[BoxData[{
 RowBox[{
  RowBox[{"dataKxM95F", " ", "=", " ", 
   RowBox[{
    RowBox[{
     RowBox[{"{", 
      RowBox[{
       RowBox[{"listk1", "[", 
        RowBox[{"[", "#", "]"}], "]"}], ",", " ", 
       RowBox[{"Quantile", "[", 
        RowBox[{
         RowBox[{"table300F", "[", 
          RowBox[{"[", 
           RowBox[{"All", ",", " ", "#", " ", ",", " ", "2"}], "]"}], "]"}], 
         ",", " ", "0.95"}], "]"}]}], "}"}], " ", "&"}], " ", "/@", " ", 
    RowBox[{"(", 
     RowBox[{"Range", " ", "@", " ", 
      RowBox[{"Length", " ", "@", " ", "listk1"}]}], ")"}]}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"dataKxM50F", " ", "=", " ", 
   RowBox[{
    RowBox[{
     RowBox[{"{", 
      RowBox[{
       RowBox[{"listk1", "[", 
        RowBox[{"[", "#", "]"}], "]"}], ",", " ", 
       RowBox[{"Quantile", "[", 
        RowBox[{
         RowBox[{"table300F", "[", 
          RowBox[{"[", 
           RowBox[{"All", ",", " ", "#", " ", ",", " ", "2"}], "]"}], "]"}], 
         ",", " ", "0.50"}], "]"}]}], "}"}], " ", "&"}], " ", "/@", " ", 
    RowBox[{"(", 
     RowBox[{"Range", " ", "@", " ", 
      RowBox[{"Length", " ", "@", " ", "listk1"}]}], ")"}]}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"dataKxM05F", " ", "=", " ", 
    RowBox[{
     RowBox[{
      RowBox[{"{", 
       RowBox[{
        RowBox[{"listk1", "[", 
         RowBox[{"[", "#", "]"}], "]"}], ",", " ", 
        RowBox[{"Quantile", "[", 
         RowBox[{
          RowBox[{"table300F", "[", 
           RowBox[{"[", 
            RowBox[{"All", ",", " ", "#", " ", ",", " ", "2"}], "]"}], "]"}], 
          ",", " ", "0.05"}], "]"}]}], "}"}], " ", "&"}], " ", "/@", " ", 
     RowBox[{"(", 
      RowBox[{"Range", " ", "@", " ", 
       RowBox[{"Length", " ", "@", " ", "listk1"}]}], ")"}]}]}], ";"}], 
  "\n"}], "\n", 
 RowBox[{
  RowBox[{"kXm95FI", " ", "=", " ", 
   RowBox[{"Interpolation", "[", 
    RowBox[{"dataKxM95F", ",", " ", 
     RowBox[{"InterpolationOrder", "->", "2"}], ",", " ", 
     RowBox[{"Method", "->", "\"\<Spline\>\""}]}], " ", "]"}]}], 
  ";"}], "\n", 
 RowBox[{
  RowBox[{"kXm50FI", " ", "=", " ", 
   RowBox[{"Interpolation", "[", 
    RowBox[{"dataKxM50F", ",", " ", 
     RowBox[{"InterpolationOrder", "->", "2"}], ",", " ", 
     RowBox[{"Method", "->", "\"\<Spline\>\""}]}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"kXm05FI", " ", "=", " ", 
   RowBox[{"Interpolation", "[", 
    RowBox[{"dataKxM05F", ",", " ", 
     RowBox[{"InterpolationOrder", "->", "2"}], ",", " ", 
     RowBox[{"Method", "->", "\"\<Spline\>\""}]}], "]"}]}], ";"}]}], "Code",
 CellChangeTimes->{{3.905693506081048*^9, 3.905693532661688*^9}, {
   3.905693589980736*^9, 3.905693658462379*^9}, {3.905693700253523*^9, 
   3.905693717506909*^9}, {3.905693776267274*^9, 3.905693785587833*^9}, {
   3.905693822480578*^9, 3.905693824980921*^9}, 3.9056939761081333`*^9, 
   3.905694194655819*^9, {3.905694332624251*^9, 3.905694371379525*^9}, {
   3.905694444810359*^9, 3.9056945033964577`*^9}, {3.905694694681081*^9, 
   3.9056947406699266`*^9}, {3.90569484455048*^9, 3.9056949377382317`*^9}, {
   3.905695041778406*^9, 3.905695149531247*^9}, {3.90569517953335*^9, 
   3.9056952350442953`*^9}, 3.90569594019909*^9, 3.905696006311873*^9, {
   3.9056963484953003`*^9, 3.905696373720901*^9}, {3.9056965193115*^9, 
   3.905696540714879*^9}, {3.905699990969532*^9, 3.9056999968498507`*^9}, {
   3.905700076812274*^9, 3.9057000813936453`*^9}, {3.9057002131736794`*^9, 
   3.9057002144635277`*^9}, {3.9057002887391233`*^9, 3.905700288996612*^9}, {
   3.905740604748106*^9, 3.905740650053679*^9}},
 CellLabel->"In[83]:=",ExpressionUUID->"ea40ec3e-5fbc-44d1-99fc-942ab1f9dd39"],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"color1i", " ", "=", " ", 
   RowBox[{"RGBColor", "[", 
    RowBox[{"0", ",", " ", 
     RowBox[{"76", "/", "255"}], ",", " ", 
     RowBox[{"153", "/", "255"}]}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"color1ii", " ", "=", " ", 
   RowBox[{"RGBColor", "[", 
    RowBox[{
     RowBox[{"51", "/", "255"}], ",", " ", 
     RowBox[{"153", "/", "255"}], ",", " ", 
     RowBox[{"255", "/", "255"}]}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"color1iii", " ", "=", " ", 
   RowBox[{"RGBColor", "[", 
    RowBox[{
     RowBox[{"153", "/", "255"}], ",", " ", "0", ",", " ", "0"}], "]"}]}], 
  ";"}], "\n", 
 RowBox[{
  RowBox[{"color1iv", " ", "=", " ", 
   RowBox[{"RGBColor", "[", 
    RowBox[{
     RowBox[{"255", "/", "255"}], ",", " ", 
     RowBox[{"102", "/", "255"}], ",", " ", 
     RowBox[{"102", "/", "255"}]}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"color3i", " ", "=", " ", 
   RowBox[{"RGBColor", "[", 
    RowBox[{"0", ",", " ", 
     RowBox[{"128", "/", "255"}], ",", " ", 
     RowBox[{"128", "/", "255"}]}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"color3ii", " ", "=", " ", 
    RowBox[{"RGBColor", "[", 
     RowBox[{"0", ",", " ", 
      RowBox[{"192", "/", "255"}], ",", " ", 
      RowBox[{"192", "/", "255"}]}], "]"}]}], ";"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"legend", " ", "=", " ", 
    RowBox[{"LineLegend", "[", "\n", "  ", 
     RowBox[{
      RowBox[{"{", "\n", "    ", 
       RowBox[{
        RowBox[{"Directive", "[", 
         RowBox[{
          RowBox[{"Thickness", "[", "0.008", "]"}], ",", " ", "color1i"}], 
         "]"}], ",", "\n", "    ", 
        RowBox[{"Directive", "[", 
         RowBox[{
          RowBox[{"Thickness", "[", "0.008", "]"}], ",", " ", "color1ii", ",",
           " ", 
          RowBox[{"Dashing", "[", "Small", "]"}]}], "]"}], ",", " ", "\n", 
        "    ", 
        RowBox[{"Directive", "[", 
         RowBox[{
          RowBox[{"Thickness", "[", "0.006", "]"}], ",", " ", "color3i", ",", 
          " ", "Dashed"}], "]"}]}], "\n", "    ", 
       RowBox[{"(*", 
        RowBox[{"Directive", "[", 
         RowBox[{
          RowBox[{"Thickness", "[", "0.006", "]"}], ",", " ", "color3ii", ",",
           " ", "DotDashed"}], "]"}], "*)"}], "\n", "  ", "}"}], ",", "\n", 
      "  ", 
      RowBox[{"{", "\n", "    ", 
       RowBox[{
        RowBox[{"Style", "[", 
         RowBox[{"\"\<Current data\>\"", ",", " ", 
          RowBox[{"FontFamily", "->", "\"\<Times\>\""}], ",", " ", 
          RowBox[{"FontSize", " ", "->", " ", "14"}]}], "]"}], ",", "\n", 
        "    ", 
        RowBox[{"Style", "[", 
         RowBox[{"\"\<Current data (IU)\>\"", ",", " ", 
          RowBox[{"FontFamily", "->", "\"\<Times\>\""}], ",", " ", 
          RowBox[{"FontSize", " ", "->", " ", "14"}]}], "]"}], ",", " ", "\n",
         "    ", 
        RowBox[{"Style", "[", 
         RowBox[{"\"\<Forecast\>\"", ",", " ", 
          RowBox[{"FontFamily", "->", "\"\<Times\>\""}], ",", " ", 
          RowBox[{"FontSize", " ", "->", " ", "14"}]}], "]"}]}], "\n", "    ", 
       RowBox[{"(*", 
        RowBox[{"Style", "[", 
         RowBox[{"\"\<Forecast (IU)\>\"", ",", " ", 
          RowBox[{"FontFamily", "->", "\"\<Times\>\""}], ",", " ", 
          RowBox[{"FontSize", " ", "->", " ", "14"}]}], "]"}], "*)"}], "\n", 
       "  ", "}"}], ",", "    ", "\n", "  ", 
      RowBox[{"LegendMarkerSize", "->", 
       RowBox[{"{", 
        RowBox[{"25", ",", " ", "5"}], "}"}]}]}], "\n", "  ", 
     RowBox[{"(*", 
      RowBox[{"Spacings", " ", "->", " ", "0.5"}], "*)"}], "\n", "]"}]}], 
   ";"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{"plotkXmPLPP", " ", "=", " ", 
   RowBox[{"Plot", "[", "\n", "  ", 
    RowBox[{
     RowBox[{"{", "\n", "    ", 
      RowBox[{
       RowBox[{"If", "[", 
        RowBox[{
         RowBox[{
          RowBox[{"kXm95FI", "[", "k", "]"}], ">=", "4.95"}], ",", " ", "200",
          ",", " ", 
         RowBox[{"kXm95FI", "[", "k", "]"}]}], "]"}], ",", " ", "\n", "    ", 
       
       RowBox[{"(*", 
        RowBox[{
         RowBox[{"If", "[", 
          RowBox[{
           RowBox[{
            RowBox[{"kXm50FI", "[", "k", "]"}], ">=", "4.95"}], ",", " ", 
           "200", ",", " ", 
           RowBox[{"kXm50FI", "[", "k", "]"}]}], "]"}], ","}], "*)"}], "\n", 
       "    ", 
       RowBox[{"If", "[", 
        RowBox[{
         RowBox[{
          RowBox[{"kXm95I", "[", "k", "]"}], ">=", "4.95"}], ",", " ", "200", 
         ",", 
         RowBox[{"kXm95I", "[", "k", "]"}]}], "]"}], ",", " ", "\n", "    ", 
       RowBox[{"If", "[", 
        RowBox[{
         RowBox[{
          RowBox[{"kXm50I", "[", "k", "]"}], ">=", "4.95"}], ",", " ", "200", 
         ",", " ", 
         RowBox[{"kXm50I", "[", "k", "]"}]}], "]"}]}], "\n", "  ", "}"}], ",",
      " ", "\n", "  ", 
     RowBox[{"{", 
      RowBox[{"k", ",", "0.5", ",", " ", "3"}], "}"}], ",", " ", "\n", "  ", 
     RowBox[{"PlotRange", "->", 
      RowBox[{"{", 
       RowBox[{
        RowBox[{"{", 
         RowBox[{"0.5", ",", " ", "3"}], "}"}], ",", " ", 
        RowBox[{"{", 
         RowBox[{"0", ",", "5"}], "}"}]}], "}"}]}], ",", "\n", "  ", 
     RowBox[{"PlotStyle", " ", "->", " ", 
      RowBox[{"{", "\n", "    ", 
       RowBox[{
        RowBox[{"{", 
         RowBox[{
          RowBox[{"Thickness", "[", "0.006", "]"}], ",", " ", "color3i", ",", 
          " ", "Dashed"}], "}"}], ",", "\n", "    ", 
        RowBox[{"(*", 
         RowBox[{
          RowBox[{"{", 
           RowBox[{
            RowBox[{"Thickness", "[", "0.006", "]"}], ",", " ", "color3ii", 
            ",", " ", "DotDashed"}], "}"}], ","}], "*)"}], "\n", "    ", 
        RowBox[{"{", 
         RowBox[{
          RowBox[{"Thickness", "[", "0.008", "]"}], ",", " ", "color1i"}], 
         "}"}], ",", " ", "\n", "    ", 
        RowBox[{"{", 
         RowBox[{
          RowBox[{"Thickness", "[", "0.008", "]"}], ",", " ", "color1ii", ",",
           " ", 
          RowBox[{"Dashing", "[", "Small", "]"}]}], "}"}]}], "\n", "  ", 
       "}"}]}], ",", "\n", "  ", 
     RowBox[{"Background", " ", "->", " ", "White"}], ",", "\n", "  ", 
     RowBox[{"Frame", " ", "->", " ", "True"}], ",", "\n", "  ", 
     RowBox[{"Axes", " ", "->", " ", "False"}], ",", "\n", "  ", 
     RowBox[{"Filling", "->", 
      RowBox[{"{", 
       RowBox[{
        RowBox[{"1", "->", " ", 
         RowBox[{"{", 
          RowBox[{"Top", ",", " ", 
           RowBox[{"Directive", "[", 
            RowBox[{
             RowBox[{"Opacity", "[", "0.5", "]"}], ",", " ", "color3i"}], 
            "]"}]}], "}"}]}], ",", " ", 
        RowBox[{"(*", 
         RowBox[{
          RowBox[{"2", "->", " ", "None"}], ","}], "*)"}], " ", 
        RowBox[{"2", "->", " ", 
         RowBox[{"{", 
          RowBox[{"Top", ",", " ", 
           RowBox[{"Directive", "[", 
            RowBox[{
             RowBox[{"Opacity", "[", "0.5", "]"}], ",", " ", "color1i"}], 
            "]"}]}], "}"}]}], ",", " ", 
        RowBox[{"3", "->", " ", "None"}]}], "}"}]}], ",", "\n", "  ", 
     RowBox[{"FrameStyle", "->", " ", 
      RowBox[{"Directive", "[", 
       RowBox[{"Black", ",", " ", 
        RowBox[{"FontSize", " ", "->", " ", "13"}], ",", " ", 
        RowBox[{"FontFamily", "->", " ", "\"\<Times\>\""}]}], "]"}]}], ",", 
     "\n", "  ", 
     RowBox[{"FrameTicksStyle", " ", "->", " ", 
      RowBox[{"Directive", "[", "Black", "]"}]}], ",", "\n", "  ", 
     RowBox[{"GridLines", "->", 
      RowBox[{"(*", 
       RowBox[{"{", 
        RowBox[{
         RowBox[{"{", 
          RowBox[{"1.65", ",", " ", "2.1"}], "}"}], ",", " ", 
         RowBox[{"{", "}"}]}], "}"}], "*)"}], "Automatic"}], ",", "\n", "  ", 
     
     RowBox[{"MaxRecursion", "->", "10"}], ",", "\n", "  ", 
     RowBox[{"Epilog", "->", 
      RowBox[{"Inset", "[", 
       RowBox[{"legend", ",", " ", 
        RowBox[{"Scaled", "[", 
         RowBox[{"{", 
          RowBox[{"0.22", ",", "0.18"}], "}"}], "]"}]}], "]"}]}]}], "\n", 
    "]"}]}], "\n"}], "\n", 
 RowBox[{"exportOut", "[", 
  RowBox[{"\"\<plotkXmPLPP.pdf\>\"", ",", " ", "plotkXmPLPP"}], 
  "]"}]}], "Code",
 CellChangeTimes->{{3.905703156005106*^9, 3.905703291733486*^9}, {
   3.905703329623831*^9, 3.905703341850874*^9}, {3.9057033728002367`*^9, 
   3.905703375341865*^9}, {3.905703409665365*^9, 3.905703410170961*^9}, {
   3.905703446139495*^9, 3.905703449197205*^9}, {3.9057035355119143`*^9, 
   3.905703539182912*^9}, {3.905703658285778*^9, 3.9057037536835833`*^9}, {
   3.905703789266073*^9, 3.905703866720512*^9}, {3.905703940790134*^9, 
   3.9057040076694393`*^9}, {3.9057041162417917`*^9, 3.905704186855021*^9}, {
   3.905740516979147*^9, 3.905740533673337*^9}, {3.9057406669497423`*^9, 
   3.905740677174673*^9}, {3.9057407540375223`*^9, 3.905740762066463*^9}, {
   3.9057410058641443`*^9, 3.9057410123419733`*^9}, {3.905741106174986*^9, 
   3.90574115829418*^9}, {3.905741413599275*^9, 3.905741522984322*^9}, {
   3.9057418604074583`*^9, 3.9057418655918503`*^9}, 3.9057419254286003`*^9, {
   3.905742028207871*^9, 3.905742089204664*^9}, {3.905742121043091*^9, 
   3.905742129793849*^9}, {3.9057421984550447`*^9, 3.9057422205930243`*^9}, {
   3.905742251280643*^9, 3.9057425011206923`*^9}, {3.905742716919977*^9, 
   3.9057427495216827`*^9}, {3.9057772837525253`*^9, 3.905777357965322*^9}, {
   3.906019789360922*^9, 3.906019953953863*^9}, {3.9060199853999434`*^9, 
   3.9060200467962427`*^9}, {3.906020095782346*^9, 3.9060201513702593`*^9}, {
   3.9060201970532093`*^9, 3.90602023222252*^9}, {3.906020264328742*^9, 
   3.906020267992305*^9}, {3.906020404633272*^9, 3.906020407161661*^9}, 
   3.912004927534137*^9, {3.912004990571951*^9, 3.9120050652159767`*^9}, {
   3.912005164173225*^9, 3.912005168459344*^9}, {3.9120052250954847`*^9, 
   3.912005271148294*^9}, {3.91200564097509*^9, 3.912005730334401*^9}, {
   3.9120057652848663`*^9, 3.912005786157963*^9}, {3.912005816192335*^9, 
   3.9120058183594103`*^9}, {3.912006145649831*^9, 3.912006190590032*^9}, {
   3.91200630447661*^9, 3.912006378049982*^9}},
 CellLabel->
  "In[321]:=",ExpressionUUID->"cb8d9aeb-a352-4322-bf6a-0dc0bde5c7de"],

Cell[BoxData[
 GraphicsBox[
  InterpretationBox[{
    TagBox[{GraphicsComplexBox[CompressedData["
1:eJx023k0lH/8P3xcs1hKQil7KMqSJAmfXu8kqWwhlSJUiEK2ylISkkp2UiFr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       "], {{
         {RGBColor[0, 
           NCache[
            Rational[128, 255], 0.5019607843137255], 
           NCache[
            Rational[128, 255], 0.5019607843137255]], Opacity[0.5], EdgeForm[
          None], GraphicsGroupBox[{PolygonBox[CompressedData["
1:eJwV0LkyQ1EcgPGD2IKx6xWW0ViDGVXUCkNBdDyAJRrLeAGVLbyE1lJYCrU9
dMETWBNGY/xSfPeee77vf+bMbZ6ZG5stDCEUYBGrKEYP0hajpSFcREKIef/5
7hSul4Qwbj1sP1EUQsoBOfu3ZpLcENfBxbk1LsNNo49v4V+5DJflurDB1eOA
X4IkRDwudSe6e0015jSf3A4mEINrhTKUI4qK/P3NXpk9NZs2V4N5s19cCpPo
R6vuTfeky2m6salrwCG/jMr8fXTXujPdg6YWC5ost4sEBtCme9c96741PdjS
NeKIX0FV/s66G9257lFTh6Qmx+1hCnFN1H/81dRgRLOv6cIdP4h2zYdzXvgf
vhfbfBOO+X+K4DjQ
             "]], PolygonBox[CompressedData["
1:eJwl2GW4FWUbhuFNiyiI0l0qSInSXZKSEkpLSEhKd5d0SHcKCAiIKCglKKJi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             "]]}]}, {}, 
         {RGBColor[0, 
           NCache[
            Rational[76, 255], 0.2980392156862745], 
           NCache[
            Rational[3, 5], 0.6]], Opacity[0.5], EdgeForm[None], 
          GraphicsGroupBox[PolygonBox[CompressedData["
1:eJwV02N4HXYYxuGTpG2S2u3q1LbtdlvXbp29dUaT2rZtr7Zt27ZtG7vPh7s5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            
            "]]]}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, \
{}}, {{}, {}, 
         TagBox[
          {RGBColor[0, 
            NCache[
             Rational[128, 255], 0.5019607843137255], 
            NCache[
             Rational[128, 255], 0.5019607843137255]], Thickness[0.006], 
           Opacity[1.], Dashing[{Small, Small}], LineBox[CompressedData["
1:eJwV0LcyRWEUQOGNK12MrFcIo5HDjIpaYSiEjgfAVQnjBVSyl9AKhVCo5dAJ
TyDey2iMT7FO+NfaZ/ac2snpoamsiEjhNjdiMD/iNBHR6f7rvZlczosY9tzv
fCwnYjM7IuP8ysws18s1cX3cEvfATaCDr+NfuAcuzbVghavELj8HSSRcznSH
uhtNKaY1H9wGRtAJa0UBCpFEEXLNnps9MntrrgwzZj+5TYyiC/W6V92jLqNp
xaquCnv8PIr/99Fd6I51d5pypDRpbgtj6EaD7k33pPvStGFNV419fgEl/zvr
LnUnuntNBWY1GW4b4+jTJP3HH00ZBjQ7mhZc8z1o1Lz7zjP/zbdjna/BAb+I
PwcoOJU=
            "]], LineBox[CompressedData["
1:eJwl2GW4FWUbhuFNiwiI0l0qSInSXUpJSigtISEp3V3SiHSngICAiIJSgiJ2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            "]]},
          Annotation[#, "Charting`Private`Tag#1"]& ], 
         TagBox[
          {RGBColor[0, 
            NCache[
             Rational[76, 255], 0.2980392156862745], 
            NCache[
             Rational[3, 5], 0.6]], Thickness[0.008], Opacity[1.], 
           LineBox[CompressedData["
1:eJwV02N4ngcYhuE3VZLa7erUtu12W9dunb11RpPatm2vtm3btm0bO/PjTL73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            "]]},
          Annotation[#, "Charting`Private`Tag#2"]& ], 
         TagBox[
          {RGBColor[
            NCache[
             Rational[1, 5], 0.2], 
            NCache[
             Rational[3, 5], 0.6], 1], Thickness[0.008], Opacity[1.], Dashing[
           Small], LineBox[{3109, 3426, 3269, 2734, 3375, 3217, 3076, 2952, 
            2844, 2490, 3327, 3169, 3028, 2904, 2796, 2703, 2626, 2563, 2393, 
            3273, 3115, 2974, 2850, 2742, 2649, 2572, 2509, 2464, 2438, 2394, 
            3450}], LineBox[CompressedData["
1:eJwNyrlVAgEUQNFv6L504FHBQBRyUjIiQ2HYCtDAIkShB3ZaYBQrcBlQSzCw
DW9wo/eOO3fXtxsRUeVtJ+KCwXbECYutiBt2yTYjRjxQ491XYOg7JfXU2GOl
j+lSJ6HBh/+Skf+MZ2+dfdb6hEeafPquGPtyvHgSDvjSpzzRIvMVmfjyLD0N
DvnWZ/Ros/KVmPrOefU0OeJHn9Pn11Mh9ZRZ6/fk+NOX/APmjSoe
            "]], LineBox[CompressedData["
1:eJwV1mW4lFUXBuChu1uk1E9CLLpblEaUMuk45KG7Q7obbLpblG4Fg+7u7q7v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            "]]},
          Annotation[#, "Charting`Private`Tag#3"]& ], 
         {RGBColor[0, 
           NCache[
            Rational[128, 255], 0.5019607843137255], 
           NCache[
            Rational[128, 255], 0.5019607843137255]], Opacity[0.5], 
          LineBox[{1892, 1891}], LineBox[{3447, 3446}], LineBox[{3452, 3451}],
           LineBox[{3453, 1896}], LineBox[{3454, 2384}], 
          LineBox[{3455, 3448}]}}}], {}},
     {"WolframDynamicHighlight", <|
      "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>}], 
    DynamicBox[(Charting`HighlightActionBox["DynamicHighlight", {}, 
      Slot["HighlightElements"], 
      Slot["LayoutOptions"], 
      Slot["Meta"], 
      Charting`HighlightActionFunction["DynamicHighlight", {
        GraphicsComplex[CompressedData["
1:eJx023k0lH/8P3xcs1hKQil7KMqSJAmfXu8kqWwhlSJUiEK2ylISkkp2UiFr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         "], {{{
            EdgeForm[], 
            Directive[
             Opacity[0.5], 
             RGBColor[0, 
              Rational[128, 255], 
              Rational[128, 255]]], 
            GraphicsGroup[{
              Polygon[CompressedData["
1:eJwV0LkyQ1EcgPGD2IKx6xWW0ViDGVXUCkNBdDyAJRrLeAGVLbyE1lJYCrU9
dMETWBNGY/xSfPeee77vf+bMbZ6ZG5stDCEUYBGrKEYP0hajpSFcREKIef/5
7hSul4Qwbj1sP1EUQsoBOfu3ZpLcENfBxbk1LsNNo49v4V+5DJflurDB1eOA
X4IkRDwudSe6e0015jSf3A4mEINrhTKUI4qK/P3NXpk9NZs2V4N5s19cCpPo
R6vuTfeky2m6salrwCG/jMr8fXTXujPdg6YWC5ost4sEBtCme9c96741PdjS
NeKIX0FV/s66G9257lFTh6Qmx+1hCnFN1H/81dRgRLOv6cIdP4h2zYdzXvgf
vhfbfBOO+X+K4DjQ
               "]], 
              Polygon[CompressedData["
1:eJwl2GW4FWUbhuFNiyiI0l0qSInSXZKSEkpLSEhKd5d0SHcKCAiIKCglKKJi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               "]]}]}, {}, {
            EdgeForm[], 
            Directive[
             Opacity[0.5], 
             RGBColor[0, 
              Rational[76, 255], 
              Rational[3, 5]]], 
            GraphicsGroup[{
              Polygon[CompressedData["
1:eJwV02N4HXYYxuGTpG2S2u3q1LbtdlvXbp29dUaT2rZtr7Zt27ZtG7vPh7s5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               
               "]]}]}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, \
{}, {}}, {{}, {}, 
           Annotation[{
             Directive[
              Opacity[1.], 
              AbsoluteThickness[2], 
              Thickness[0.006], 
              RGBColor[0, 
               Rational[128, 255], 
               Rational[128, 255]], 
              Dashing[{Small, Small}]], 
             Line[CompressedData["
1:eJwV0LcyRWEUQOGNK12MrFcIo5HDjIpaYSiEjgfAVQnjBVSyl9AKhVCo5dAJ
TyDey2iMT7FO+NfaZ/ac2snpoamsiEjhNjdiMD/iNBHR6f7rvZlczosY9tzv
fCwnYjM7IuP8ysws18s1cX3cEvfATaCDr+NfuAcuzbVghavELj8HSSRcznSH
uhtNKaY1H9wGRtAJa0UBCpFEEXLNnps9MntrrgwzZj+5TYyiC/W6V92jLqNp
xaquCnv8PIr/99Fd6I51d5pypDRpbgtj6EaD7k33pPvStGFNV419fgEl/zvr
LnUnuntNBWY1GW4b4+jTJP3HH00ZBjQ7mhZc8z1o1Lz7zjP/zbdjna/BAb+I
PwcoOJU=
              "]], 
             Line[CompressedData["
1:eJwl2GW4FWUbhuFNiwiI0l0qSInSXUpJSigtISEp3V3SiHSngICAiIJSgiJ2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              "]]}, "Charting`Private`Tag#1"], 
           Annotation[{
             Directive[
              Opacity[1.], 
              AbsoluteThickness[2], 
              Thickness[0.008], 
              RGBColor[0, 
               Rational[76, 255], 
               Rational[3, 5]]], 
             Line[CompressedData["
1:eJwV02N4ngcYhuE3VZLa7erUtu12W9dunb11RpPatm2vtm3btm0bO/PjTL73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              "]]}, "Charting`Private`Tag#2"], 
           Annotation[{
             Directive[
              Opacity[1.], 
              AbsoluteThickness[2], 
              Thickness[0.008], 
              RGBColor[
               Rational[1, 5], 
               Rational[3, 5], 1], 
              Dashing[Small]], 
             
             Line[{3109, 3426, 3269, 2734, 3375, 3217, 3076, 2952, 2844, 2490,
               3327, 3169, 3028, 2904, 2796, 2703, 2626, 2563, 2393, 3273, 
              3115, 2974, 2850, 2742, 2649, 2572, 2509, 2464, 2438, 2394, 
              3450}], 
             Line[CompressedData["
1:eJwNyrlVAgEUQNFv6L504FHBQBRyUjIiQ2HYCtDAIkShB3ZaYBQrcBlQSzCw
DW9wo/eOO3fXtxsRUeVtJ+KCwXbECYutiBt2yTYjRjxQ491XYOg7JfXU2GOl
j+lSJ6HBh/+Skf+MZ2+dfdb6hEeafPquGPtyvHgSDvjSpzzRIvMVmfjyLD0N
DvnWZ/Ros/KVmPrOefU0OeJHn9Pn11Mh9ZRZ6/fk+NOX/APmjSoe
              "]], 
             Line[CompressedData["
1:eJwV1mW4lFUXBuChu1uk1E9CLLpblEaUMuk45KG7Q7obbLpblG4Fg+7u7q7v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              "]]}, "Charting`Private`Tag#3"], {
            Directive[
             Opacity[0.5], 
             RGBColor[0, 
              Rational[128, 255], 
              Rational[128, 255]]], 
            Line[{1892, 1891}], 
            Line[{3447, 3446}], 
            Line[{3452, 3451}], 
            Line[{3453, 1896}], 
            Line[{3454, 2384}], 
            Line[{3455, 3448}]}}}], {}}, <|
       "HighlightElements" -> <|
         "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
        "LayoutOptions" -> <|
         "PlotRange" -> {{0.5, 3.}, {0., 5.}}, 
          "Frame" -> {{True, True}, {True, True}}, 
          "AxesOrigin" -> {0.5000000000000011, 0}, 
          "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {False, False}, 
          "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
          "DefaultStyle" -> {
            Directive[
             Opacity[1.], 
             AbsoluteThickness[2], 
             Thickness[0.008], 
             RGBColor[
              Rational[1, 5], 
              Rational[3, 5], 1], 
             Dashing[Small]], 
            Directive[
             Opacity[1.], 
             AbsoluteThickness[2], 
             Thickness[0.008], 
             RGBColor[0, 
              Rational[76, 255], 
              Rational[3, 5]]], 
            Directive[
             Opacity[1.], 
             AbsoluteThickness[2], 
             Thickness[0.006], 
             RGBColor[0, 
              Rational[128, 255], 
              Rational[128, 255]], 
             Dashing[{Small, Small}]]}, 
          "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
              Identity[
               Part[#, 1]], 
              Identity[
               Part[#, 2]]}& ), 
            "ScalingFunctions" -> {{Identity, Identity}, {
              Identity, Identity}}|>, "Primitives" -> {{{{
               EdgeForm[], 
               Directive[
                Opacity[0.5], 
                RGBColor[0, 
                 Rational[128, 255], 
                 Rational[128, 255]]], 
               GraphicsGroup[{{
                  Polygon[CompressedData["
1:eJxl0Xs01ekaB3Dtqd++pO3yq2QXjZQ7OSVD5HlqdmqQUg2NEVKZmgbd1NGq
7bJGqZzCRpZKhtCYGdkourDdGo0IQzcHYZq9t2z6/bbLIOm8c9Y6f513rWe9
67O+613P+76PSUjE9v0cLS2tY6T+3t2jxFdLAzXAltzuevB+Dv7PWv9d8zHZ
wiI9mFH8n0MkN09nNdG4xNSd00x8YU1ISDjxrL6uVc6sAuSHTvq6ESuyju3N
I771rcRNSNwUIEjV0yhAvOqkqOcJjRkvPxsbIL622K3oDLEk/ekK3xEF7Fqn
HbqFeN/O/b61xI/Nm/SMiFe2ppRnjiqg3tdk48NGGn9tGIryHFfAaiOTxVO/
0Th2N3fm50kFDHqe+P7YYxq3p+nwDmspod7+pNfuRzTO3a4Ujc9TgsGidpm2
nEZGR+IZIlTCaCgd+qqKxufN808/JT4r2SjMJ875YkN3vo4SGrjRa4F47frr
N/z0lFAbt4lzpJLGA/Y7lt+br4TLIrutvz+gsV4otz29WAnSNp+eixXkPU/S
kWOpBJfdI22dMtJP7B4qFCth7mCWUJVL+nG6008R26bWPSgiflh9rEFBPJvq
DIgkPuf6g4V8oxJaP+86xSE2dph+G7FJCX3mjmZLcmj0Mi2JaPNQQmcyrN2S
TeOPs4yjUn2UsGroll/+NRpDqsYuioKUEF/z7BuHNBqffZYnMzulhFu9V7rl
8TTet5r9wa1YCexEpXHqPhrjdWulEUtUEFMjdkozJOejOIkdxNFlfjOexNi/
4XtnIxWI9snqOMTTpXXHPzFWwYpJJ6/Di2g87vfoyytLVZA2lbHT04DML+ux
gXyZCnr8r22YtYBGsU3LVaGlCuYmF0u/06WRs7kr95c1JG8XCtZzyX9Fj5cO
eqvArzRnU9+oPp4Ytur4JlYF0lfm1McWfQxtks4PVqjAva4g6Xa8Pm5O2J+2
rXgAEudK/v1mWA9LwgpfzwodhBe0Iy8+SxfvhWyQldNDoDakCpzahejvdNYy
8eYwVEzvsH7xWhvbKtdEZlgzULs0W8u4ToDjt3NsnxBLl725kFkrQFGOjuID
cdWcMn0D4pCzA757bRgQhf0l0q0R4Kj3dSc7WwaG5dpCjlyAi3pnT9fZMSA8
cUTy530BBnM64t79gwHn5aYJhSUCZNyPJrk7MeCYYA62OQLUaS36aVTMQFt4
mcuCWAFu6Tfv3xbIwPG7PeERbgL8jRJt5SczELMystKrnI/DE2e5rsQL+6OC
6u/yUX9wRB5OTEUKProQ+7c023cQq11aHK3v8FF9JVb/RgoDv29RJvBL+ahr
OfDMIZUBwzif8kdFfNzlWREQfIWBSzbCda75fFRd9v22/DoDpuct1CZpfOQa
SuP3FzLwNrjvZctRPm601n5YU0d8Ya/6ji0fa7bOWJwaZ6C5Z4foWR4PN9tM
9/1E7PQ2KHkn8VPeVGY3cb/zoF7HTR521oxpr/+Lgcm86JXtuTwcXT3EcCcY
MJHd6Gr7gYcWi7oq0iYZ+E76cKb1Og8v9d7bLJtmYOzcwZDnaTwMOBJ5QMVh
odI+qeBDPA8nUtQFvjosuMXqWlaF8tD+eafZagsWxoy6eVwrHmYHlC9Xf0Vy
93yXinIumjnf6TbyZ+F021qZB/EvC0rTtxJPZHvbd9/l4v2nRbxSYpn2qAeH
uAPz1VFfs7DMwFHjVcZF7oq0Mu5uFjgT6bw3xVwMHzoqNg1m4eeBJzsNC7no
KrHb5x/KQnUi51D2NS6+vJGX+/goCx1tOZc+jeOi7h/SZXkXWSjxu12i8uZi
zMHDnwZWsuCxfSIs4x2FDv4n6VRi3qShvSOxykNCNRJbNx/80D5M4TabRPWa
KhayP0jv6RCbvCuomCdn4fNo/Ypzagprj7/eVlnNQtyciuaoAQpnx3jHLqln
ocko7+vQPyg8n27T39nIQsoZLmfPCwpT6lS5fi9ZGJlU/7NLTmGe0R5znxEW
Jv9cq6NOodBfeEB0jriBPf8xlVj4MXxeJfF7K+77dcQnek+PWIyyIF2RSCcl
U+iemyHXGmMhxqW60SGJ3N+i1a94nIUv3rb6xPyLQisHSNCZYqFwR2rt0gQK
izyMBpq1NJDzZa5dzBkKK06+KvQQamDPwn77hgMUNrb52IktNWB7sb87bD2F
ktpdJqeIhdOB0ybEq0qD5hcT78zkmz1HCjNTw6YWW5E8aCDTjfiQ3/lfR4iB
3y7QBQq1u6sDc200kN7r/ckdVwq9VSsvc+w1oHtV5ct1orB9Zh5T7agBJ7iZ
0GxHYZd1o2ydWAP+YteFvUso/A9m01L7
                   "]]}, {
                  Polygon[CompressedData["
1:eJxc12k4lO/7MHDMkChJQiISEkKyhTrv5CsVJVtRZN9DtrKmTdJG2QlZIiVL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                   "]]}}]}, {}, {
               EdgeForm[], 
               Directive[
                Opacity[0.5], 
                RGBColor[0, 
                 Rational[76, 255], 
                 Rational[3, 5]]], 
               GraphicsGroup[{{
                  Polygon[CompressedData["
1:eJxd13k4lN8bMHBmxsxkZ0h2oc3XEmmRch8qlbRHkYQsJVuorEVFK6mUJaEs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                   
                   "]]}}]}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, \
{}, {}, {}}, {{}, {}, 
              Annotation[{
                Directive[
                 Opacity[1.], 
                 AbsoluteThickness[2], 
                 Thickness[0.006], 
                 RGBColor[0, 
                  Rational[128, 255], 
                  Rational[128, 255]], 
                 Dashing[{Small, Small}]], 
                Line[CompressedData["
1:eJwV0Xs01WkXB3Cdqd+5pOPyq+SERsqdvCXjlr1rTmqQUobGCKlMTYNu8rLk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                 "]], 
                Line[CompressedData["
1:eJwc13k8VF8bAHDMkChJQiISEkJCQj03+UlFyVYU2feQraxJJWmj7IQskZIl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                 "]]}, "Charting`Private`Tag#1"], 
              Annotation[{
                Directive[
                 Opacity[1.], 
                 AbsoluteThickness[2], 
                 Thickness[0.008], 
                 RGBColor[0, 
                  Rational[76, 255], 
                  Rational[3, 5]]], 
                Line[CompressedData["
1:eJwV13k8lF8XAHBmxsxkZ5TsQpufJdIici6VStqjSEKWki1U1qKilVTKklCW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                 "]]}, "Charting`Private`Tag#2"], 
              Annotation[{
                Directive[
                 Opacity[1.], 
                 AbsoluteThickness[2], 
                 Thickness[0.008], 
                 RGBColor[
                  Rational[1, 5], 
                  Rational[3, 5], 1], 
                 Dashing[Small]], 
                Line[CompressedData["
1:eJxTTMoPSmViYGCQB2IQPSmX5/iUjCf2Cs+evZ9xRtjBTs9YVTzzib1Yz2ur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                 "]], 
                Line[CompressedData["
1:eJwVzH881Accx3FddfneL75JpVK5rPPjssqubP34fOKmqzi0SdkN0c+VrFBj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                 "]], 
                Line[CompressedData["
1:eJwV13c81W0UAHDzXqGSWUIZ2YnKCHkeI0pEeKWSrSFJijKK7ISQvZIdshtG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                 "]]}, "Charting`Private`Tag#3"], {
               Directive[
                Opacity[0.5], 
                RGBColor[0, 
                 Rational[128, 255], 
                 Rational[128, 255]]], 
               
               Line[{{1.1481205048690568`, 2.747916912185581}, {
                1.1481703294864039`, 2.7477972455115607`}}], 
               
               Line[{{1.1481205048690568`, 3.138339828447312}, {
                1.1481703294864039`, 3.138188760151511}}], 
               
               Line[{{0.7167432818197352, 4.631304485533731}, {
                0.7167931064388042, 4.631099082493312}}], 
               
               Line[{{0.7168429054213791, 5.}, {0.7168429310561512, 
                4.949823329486749}}], 
               
               Line[{{1.1482201284278102`, 5.}, {1.148220154103751, 
                4.949742726349324}}], 
               
               Line[{{0.6377662295106392, 5.}, {0.6377662551562244, 
                4.949802158801987}}]}}}, {}}, "GCFlag" -> True|>, 
        "Meta" -> <|
         "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
          Plot, "GroupHighlight" -> False|>|>]]& )[<|
      "HighlightElements" -> <|
        "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
       "LayoutOptions" -> <|
        "PlotRange" -> {{0.5, 3.}, {0., 5.}}, 
         "Frame" -> {{True, True}, {True, True}}, 
         "AxesOrigin" -> {0.5000000000000011, 0}, 
         "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {False, False}, 
         "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
         "DefaultStyle" -> {
           Directive[
            Opacity[1.], 
            AbsoluteThickness[2], 
            Thickness[0.008], 
            RGBColor[
             Rational[1, 5], 
             Rational[3, 5], 1], 
            Dashing[Small]], 
           Directive[
            Opacity[1.], 
            AbsoluteThickness[2], 
            Thickness[0.008], 
            RGBColor[0, 
             Rational[76, 255], 
             Rational[3, 5]]], 
           Directive[
            Opacity[1.], 
            AbsoluteThickness[2], 
            Thickness[0.006], 
            RGBColor[0, 
             Rational[128, 255], 
             Rational[128, 255]], 
            Dashing[{Small, Small}]]}, 
         "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
             Identity[
              Part[#, 1]], 
             Identity[
              Part[#, 2]]}& ), 
           "ScalingFunctions" -> {{Identity, Identity}, {
             Identity, Identity}}|>, "Primitives" -> {{{{
              EdgeForm[], 
              Directive[
               Opacity[0.5], 
               RGBColor[0, 
                Rational[128, 255], 
                Rational[128, 255]]], 
              GraphicsGroup[{{
                 Polygon[CompressedData["
1:eJxl0Xs01ekaB3Dtqd++pO3yq2QXjZQ7OSVD5HlqdmqQUg2NEVKZmgbd1NGq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                  "]]}, {
                 Polygon[CompressedData["
1:eJxc12k4lO/7MHDMkChJQiISEkKyhTrv5CsVJVtRZN9DtrKmTdJG2QlZIiVL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                  "]]}}]}, {}, {
              EdgeForm[], 
              Directive[
               Opacity[0.5], 
               RGBColor[0, 
                Rational[76, 255], 
                Rational[3, 5]]], 
              GraphicsGroup[{{
                 Polygon[CompressedData["
1:eJxd13k4lN8bMHBmxsxkZ0h2oc3XEmmRch8qlbRHkYQsJVuorEVFK6mUJaEs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                  
                  "]]}}]}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, \
{}, {}, {}}, {{}, {}, 
             Annotation[{
               Directive[
                Opacity[1.], 
                AbsoluteThickness[2], 
                Thickness[0.006], 
                RGBColor[0, 
                 Rational[128, 255], 
                 Rational[128, 255]], 
                Dashing[{Small, Small}]], 
               Line[CompressedData["
1:eJwV0Xs01WkXB3Cdqd+5pOPyq+SERsqdvCXjlr1rTmqQUobGCKlMTYNu8rLk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                "]], 
               Line[CompressedData["
1:eJwc13k8VF8bAHDMkChJQiISEkJCQj03+UlFyVYU2feQraxJJWmj7IQskZIl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                "]]}, "Charting`Private`Tag#1"], 
             Annotation[{
               Directive[
                Opacity[1.], 
                AbsoluteThickness[2], 
                Thickness[0.008], 
                RGBColor[0, 
                 Rational[76, 255], 
                 Rational[3, 5]]], 
               Line[CompressedData["
1:eJwV13k8lF8XAHBmxsxkZ5TsQpufJdIici6VStqjSEKWki1U1qKilVTKklCW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                "]]}, "Charting`Private`Tag#2"], 
             Annotation[{
               Directive[
                Opacity[1.], 
                AbsoluteThickness[2], 
                Thickness[0.008], 
                RGBColor[
                 Rational[1, 5], 
                 Rational[3, 5], 1], 
                Dashing[Small]], 
               Line[CompressedData["
1:eJxTTMoPSmViYGCQB2IQPSmX5/iUjCf2Cs+evZ9xRtjBTs9YVTzzib1Yz2ur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                "]], 
               Line[CompressedData["
1:eJwVzH881Accx3FddfneL75JpVK5rPPjssqubP34fOKmqzi0SdkN0c+VrFBj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                "]], 
               Line[CompressedData["
1:eJwV13c81W0UAHDzXqGSWUIZ2YnKCHkeI0pEeKWSrSFJijKK7ISQvZIdshtG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                "]]}, "Charting`Private`Tag#3"], {
              Directive[
               Opacity[0.5], 
               RGBColor[0, 
                Rational[128, 255], 
                Rational[128, 255]]], 
              
              Line[{{1.1481205048690568`, 2.747916912185581}, {
               1.1481703294864039`, 2.7477972455115607`}}], 
              
              Line[{{1.1481205048690568`, 3.138339828447312}, {
               1.1481703294864039`, 3.138188760151511}}], 
              
              Line[{{0.7167432818197352, 4.631304485533731}, {
               0.7167931064388042, 4.631099082493312}}], 
              
              Line[{{0.7168429054213791, 5.}, {0.7168429310561512, 
               4.949823329486749}}], 
              
              Line[{{1.1482201284278102`, 5.}, {1.148220154103751, 
               4.949742726349324}}], 
              
              Line[{{0.6377662295106392, 5.}, {0.6377662551562244, 
               4.949802158801987}}]}}}, {}}, "GCFlag" -> True|>, 
       "Meta" -> <|
        "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
         Plot, "GroupHighlight" -> False|>|>],
     ImageSizeCache->{{4.503599627370496*^15, -4.503599627370496*^15}, {
      4.503599627370496*^15, -4.503599627370496*^15}}]},
   Annotation[{
     GraphicsComplex[CompressedData["
1:eJx023k0lH/8P3xcs1hKQil7KMqSJAmfXu8kqWwhlSJUiEK2ylISkkp2UiFr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      "], {{{
         EdgeForm[], 
         Directive[
          Opacity[0.5], 
          RGBColor[0, 
           Rational[128, 255], 
           Rational[128, 255]]], 
         GraphicsGroup[{
           Polygon[CompressedData["
1:eJwV0LkyQ1EcgPGD2IKx6xWW0ViDGVXUCkNBdDyAJRrLeAGVLbyE1lJYCrU9
dMETWBNGY/xSfPeee77vf+bMbZ6ZG5stDCEUYBGrKEYP0hajpSFcREKIef/5
7hSul4Qwbj1sP1EUQsoBOfu3ZpLcENfBxbk1LsNNo49v4V+5DJflurDB1eOA
X4IkRDwudSe6e0015jSf3A4mEINrhTKUI4qK/P3NXpk9NZs2V4N5s19cCpPo
R6vuTfeky2m6salrwCG/jMr8fXTXujPdg6YWC5ost4sEBtCme9c96741PdjS
NeKIX0FV/s66G9257lFTh6Qmx+1hCnFN1H/81dRgRLOv6cIdP4h2zYdzXvgf
vhfbfBOO+X+K4DjQ
            "]], 
           Polygon[CompressedData["
1:eJwl2GW4FWUbhuFNiyiI0l0qSInSXZKSEkpLSEhKd5d0SHcKCAiIKCglKKJi
Sxq0INgCosJ3Psf34z5mnuu6Z/bea82aedfO3b5X456JExISEsnV5AkJxWyf
lGZyj/nzpAkJ+5MkJBxXekj6Kt7gFkhLKSMF9H7XO6t3S6e4zNXLKG/zwyS1
pNT7Qu+A3gmddNJP5ya3UFpJWUkj9+p+qXtQ96Reeumve4tbJK2lnDwgqXS/
0n1P95ReBhmg+ze3WNpIeXlM7w+9c3p/65SQV/QyyW5+uKSV+/S+1jukd1on
owzUuc0tkbZSQQrq/al3Xu+2TkmZp5dZ9vAj5EG5X+8bvcN6Z3QyySCdf7il
0k4qSiG9v/Qu6P2jU0rm62WRd/iR8lC8lnrH9d7X+1YnswzW+ZdbJs9LJSms
d0Pvot6/OqVlgV5WeZcfJeni9dY7ofeB3nc6WWSIzn/ccmkvlSV9vN66J3WP
6H6vl1WG6t7hVkgHqSJF9G7qXdL7T6eMLNTLJnv50ZIhXm+9U3of6v2gk02G
6dzlVkpHqSpF9W7pXda7o1NWFulll338GMkYr7feab2jemd1ssvwRP+/wFfZ
dIrz6aRK5j3TSSv1dDbzxeRLvpo8rvO38/zI3+XLyWI+h+znx0pjnazOc69e
br3WOu/yVeQ8nyneL50z/Ef8OT6HjOATyWr+hfh5Ovc5zz86D0p9nS38E/IV
X12K6dx2nit8gpTXWcLnlANQN/5J58ijU4bvz3/NPSfj+Gf4bHwqPg/fht/L
VZULfOa4FnS+5T/mz/M5ZSSfWNbwneN30bnfef7VeUga6Gzln5Sv+afkCZ1/
nOcqn0gq6Czlc8lBfrxkietJ7zu9T3Qu6OSSUTpJZC3fRWrE/UjvX72f9BJL
Rb1lOrnlPX6CZI3rSe97vWM6F3Vyy2idpLKO7xq/n05qv/9/Oumkoc7rfHH5
hq8pxXX+c55rfBKppLOczyOH+InSRCe789ynl1enrc4+vppc5LPF9ajzA/8p
f4nPI2P4ZLI+3rP4+3TSOM8dnfTSSGcbX0KO87Uku+SQnJJLckseySv54jpz
jrN+zmeOv+z4vDLW8cnlVf7F+Lt0HvBz7upkkMY62/mScoKvLSV07jjPdT6p
VNZZweeVw3Eevrhz5NUpyw/gv+FayCS+KZ+Dv5/Px7fj93PV5RL/cFxnOuf4
z/kf+Xwyjk8hG+LexT/mHJl1Htfpzn/MNZTu8XrwafkEPiP/DL+DKyVTuCZc
Na4FN4+7gZ9U78uV5wpyVbkR3Hdce1nMdeSe4bpx67jkUsdxJbm7+M94MqmC
r4zrCe/lmDZcf3xb/C34eLw+XgFvgs/Ef43nID4G74NPwg/h7zt/d7wEng8v
hw/Ej2HzsQnY0nj2Ov51bDDWBRuJ7dE7j72GLca2Yy315mFtsfpYJ+yGeZ95
i3mlY06YV5pnmtfH5xM7gL2MDcZmxmcshfuVeXfcCxL/f12ww7zK/Cj3q/23
415l/7T9o3hp+4n0JvubmtnmxMthqbn0tt+ZH3bMde5N+zWwtVwB29/NLWyf
97OO8nPMVcxj+Jy2P5qb2S6M69L2E/PTtu/ENWL7d7wPtgf8/Zsc3y9ef3MH
PovtefOQeKZyh+zvwN/0s743v2qeb97C36/7jfmw+Snnmsk/Z65lbsv/aX7X
/Jp5seO/Mi81TzWvjvPHcxobj/XDpmAf6F32mgzBq+FP4LXx8fhF/Tfw4Xh3
fCy+D++KL8e74M3xnvhG/F55JO6d3Hn8C/wK9rCMd8w9Moqr7bjSfAN+CvcT
vjGe41xBLgtXjOvBfcI1kh5xD+Af5BPxmfgm/BtcaZnKNeWqcy25+dxN/JTj
+nEVuEJcNW5kvLZcB1nCdeKacC9y67kUUtdxpbgE7hc8uVTFV8W9Ee+Nt3XM
AHx7/I34BLwBXhFvis/Cf4u1Gz4WfwmfjB/GP3DqHnjJuO7w8vgg/FNsATYR
WxbrUMdvw4ZgXbFRsV4xv2/eaX7HMRfMm81LzDv4Vo6Zj7XDGmAvYDfN+81b
zascc9K8yjwrng+uq2v2X9VLaf8L+wfw4vb/s59Y/6D+FPuVsSFcDtvL5qa2
s+I5ZPuxua7tHr6o7S1z6/g8xHvs+DfMT5lX8/ltfzM/Z7s7ntW2Z8yN4rMd
awTbxPG59zo1t83FpcEz4N/bf8QxP+O77K/D2/sZH5nnmseaF8X9UPeY+d1Y
p3tNXuP7mzuah8aa03zY/IZ5l+N/MG8wLzBv5Ws4ZhbWAquNtcOWxLoFW4ZN
w9bEeWK9ik3A+mNTsSN6P/rdh+LV8SfxOvgE/JL+TnwE3gMfh+/Hu+Er8K74
s3gvfBOeSh6NNQR3Af8SvxqfNZngmJQymqvjuDJ8Q34qdy3uN7Hm5QpxWbkn
uPhCdYxrLD35OvxD8T7zmfmm/E6ujJzm+/MV+cJ8dX5UvFZcR3maL80n4n/l
Ukg1fjX3iBzhp8izOrl1Hoh7tE4Hnff4mnKFzx9rEp2L/Ff8T/E3y0T+3njv
+F5SVyed8ySJe6deM503+bJyhq8nZXQS6/zG3yPVddbwj8qH/FR5TiePTtq4
FnU66hzia8lVvkCsa3Qu8V/z1/j8MolPJZtj7c8Xdo5sOk/q9IrPL/eM9Oaf
5tPzSfmsfHN+F1dOpnHN4vPAteIWcLfwbx03gKvEFYn7PDeaO8t1kvp8WT4J
/3t8XuUpfi2XXyZyDblKjm3GzeZ+x486ridXKj47XAVucNwHuO34ULwbPhp/
F2+NL8CfxxvinfHVeJJ43/Cp+FB8Nn4Mm+b8LfC8+IPx3MQ7xdoIewUbF8+k
uPfFa4cNwDphw7C34u/DNmILsdex2nqzsZZYHex57C/zXvPmWHfE2s683Dzd
vDbui47Zi03EBmDTYv3gHnA01gPxHc4xV/jt5pXmR7hf7L+ll9b+Kfsf4qXs
J+j9ZDPM9im8PFY81nS2P5gb29Z13G/8bnNN8wb+Mds/zC1tJ/p5n/OLzFXN
k/lctlfiuWm7Ip4rtp+a69nujeee7e14tsT91d/zpuNHmnvGNYRdsD/ecXfw
D+y/iR+Ie4p5q3mZeSefWve4+f14rjnPSr5b3G/Nvflb5gPm182vOf60eY15
jnkjfx92GJuODcfmYp9hj8VaH7+MfRPrJayATI7vYHgP/VZcX24rfh8+Bq+L
l8Ub4dPw6/iW+L7LFeGyx/OG6819xjWRPnwDKRjfLfR+1Dke9/34PeRlnftl
K/+SNJRyekmd7w+9e+MerrdOp4B8xE+Xljr5dB6K90vnhVjr8nXkGl8ovsfo
XOFP8L/wBWUKn1rGck/H+pFvzE/nfo41cHxf5opyObgSXJ+4BuJvxQfiL+DD
8bfxpvhcvHWsF/EO+HL8OLYCm4Gtw+7q7cMmYQOx6dhRvb5xv8Mz4MnwbPiz
+IfYbGw0tiA+X/HdBXsJex4bhN02v2febn4jvmuY15vnmTfH++/6+dp8KNYm
jp/ON491cTwjuHPxbNf7A3/H/ia8EP5XfIad70t8if0peB78J/ur4n5s//NY
l9juj/um7b/xe8U62c/Z47hxcf8y9+Wz216K9Znty45PsP0w7gm2b/FFbG/G
NWf7fjxzHb8t1oHx+eIftv3ZvMuxD9g/af8IXtL+XfvfOeVAx1S2XxSvofer
+e1YD5nHxPVoXmieZF7On/N77sCGYS9GB9sb62VsC7Y0XtO4rvSWYi/EOgnr
jr2qdwpbjc3GNsRrEs8ebBo2DJuDfYo18ruVx5Phf2KppCa+Pr43433wdvoD
8R3xmYjvuXijWKfhzfE5+B/4x/H85Epzj3IVuSHxu3BtZCHXPtZfXBduDZdU
ZjiuFfcwl44ryHWO9atj6sp1fjhfgy/BP81Pivchvg9L4fh/AH+VOxmvLVdI
pnJpYm0b/7fhH3d8znhfdF7iv+CaST++Pp+RTx7XA/8c/zZXQb6P/3NJBZ3k
On/FtSu1dF7lC8on/ExprfOITvq4VnW66ByJNYz8zBeJ/1vEfZ8/Ffd2vnA8
2/gH4jkZa6G4J+lkcp4UsQ7Wa6Gzm68oP8T/sqSiTgqdG/G9LZ5nOhv4QnKM
nyVtdB7VyeA8hXW6xmeXrye/8EXjfyg61/jT/O98EZnOp41rMP4HxRdzjlzx
3NLpG589rrkMiHsin5m/h8/Jt+T3cJXkLD+Ir8I/ztfkx8b3dq5z3IP5Svw9
/M14pkgdfmO8rzKZa8xVceyz3FzuT/xTx/XmynD5uUrc0HjGcG1lEdchnqFc
V24tl0xmO64tl5/LGJ9trlt85451j8zhWnF1Y73PLePu4L86bgRXkyvJ1eMm
x7Oe24WPwnvhE/CDeA98Ff4i3gLvg2/Gz2BrsbnYpnjf4rmAzcBGYK9gn2OP
x/+18OvYmbgHYkXjWsJm6Y7C5+Mz/Jy1WM+4V2L9sL/NB83bYp3jmG/N68yv
xHM4nlnuS1+aD5ofdPw4vl6sP8yZuLP2n4lrAd9jvxa2MT6Xtn/GMyM+O9xi
+9Xinsnltr0a3ylsV8Ya3fYzc33bffGdwPafuJfEesjPfMvxo80Vzb3juWJ7
MX5urGniecQfMdc274pr1/aG+T0/+zL3uv3leD78eqxRHJPG/gn7H8S9Mf7X
qfeEObe5dDxjzW+Z18frFN/7zfNirWNewn8Vz3lsENYZG4Ht1juHbcIWYdvi
+af3CtYm1lRYR2yFXoLsxyfjg/AZ+EfYQKoRngVPGeszvBX+jvNsxPvi7fHB
+E68Mj4DfzbWfHgbfBF+Gz/nXIO5qlwxrhY3Lr6fc11kGdeZa8b14DZwKWMd
4LjKXEruVrxWUhff5Jgi8hnfhy/LF3BsZX5YXK9cu/hc8O34Anwmvij/Ynwf
5hrIb/xIvhZfiq/Pv8xfje9/sprrHmtW7iVuC5c67vH4THwkPg//Ir5TYjux
NdgeLJ339Vvzx+ay9pPEc8T2f3kQczg=
            "]]}]}, {}, {
         EdgeForm[], 
         Directive[
          Opacity[0.5], 
          RGBColor[0, 
           Rational[76, 255], 
           Rational[3, 5]]], 
         GraphicsGroup[{
           Polygon[CompressedData["
1:eJwV02N4HXYYxuGTpG2S2u3q1LbtdlvXbp29dUaT2rZtr7Zt27ZtG7vPh7s5
/+f3JlevIqpeTN3o0EAgEMJlvwwMDwSC7zBqRwYCq70r+5qQ0xGBwCxaU4sM
PNTrk1a/5r2ELnxGNp5pu5jGIKKJoQENSef7rrtbSlc+JzvPtd1MZzAF3b22
72Qkf1Ga+JzX19CI9O5u2JbRjS/IwQttDzMYQiF3b+y7GMXflCEBF/S1NCaD
u5u25XTnS3LyUtvLTIbShIxub2kr6MFX5OKVto9ZDKMpmdze1lbSk6/JzWtt
P7MZTjOi3N7RVtGLb8jDG+0AcxhBYXdv7bsZzT+UJSEX9XU0J7O7u7bV9OZb
8vJWO8hcRtKCLG7vaWvow3fk4512iHmMooi7d/Y9jOFfypGIS/p6WpLV3X3b
WvryPfkJcFifz2iKuguw1z6W+pQnMZf1DbQim5sHtnX04wcKEMIRfQFjKOYu
hH32cURTgSRc0TfSmuxuHtrW058fKUgoR/WFjKW4u1D228cTQ0WSclXfRBty
uHlk28AAfqIQYRzTFzGOtrSjPR3oSCdy+v7HbjcykJ8pTCyO64sZTwl3YRyw
T6ABlUjGNX0zncnl5oltE4OoRxFic0JfQnk3cTlum0ZzapKGu/oESuqxOGj7
j4ZUJjnX9S1U0RNxxjabNnxERh7pXcitP/XezGB+oShxOKkvpYKbeJywTacF
75OWe3oNLRkXvOfTgU/IEvy96aW02BzynkgjqpCCG/pWquqJOWubQ1tqk4nH
elfy6M+8tzCEXylGOKf0ZVR0E5+Tthm05APScV+fSGk9Dodtk2hMVVJyU99G
N/K6eW7bylB+ozgRnNaXM4ky7sI5Yp9ME6qRilv6drqTz80L2zaG8TsliOSM
voJKbhJwyjaTVnxIeh7okymrR3DUNoWmVCc1t/UdVNOTcM42l3bUIYoneg/y
6y+9tzOcPyhJXM7qK5lCT3rRmz70pR/9GUABP+eV79nBCP6kFPE4p69iKuXc
RXLMPpVm1OA97ug7qa4n5bxtHu35mMw81WtqybnovYCO1CVr8N+kPQWXfF5I
Jz4N/v3bUnLZ50V0Dv6Zeqfiis+LqeVzaq4G/4/4moY6/A8nrgW8
            
            "]]}]}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, \
{}}, {{}, {}, 
        Annotation[{
          Directive[
           Opacity[1.], 
           AbsoluteThickness[2], 
           Thickness[0.006], 
           RGBColor[0, 
            Rational[128, 255], 
            Rational[128, 255]], 
           Dashing[{Small, Small}]], 
          Line[CompressedData["
1:eJwV0LcyRWEUQOGNK12MrFcIo5HDjIpaYSiEjgfAVQnjBVSyl9AKhVCo5dAJ
TyDey2iMT7FO+NfaZ/ac2snpoamsiEjhNjdiMD/iNBHR6f7rvZlczosY9tzv
fCwnYjM7IuP8ysws18s1cX3cEvfATaCDr+NfuAcuzbVghavELj8HSSRcznSH
uhtNKaY1H9wGRtAJa0UBCpFEEXLNnps9MntrrgwzZj+5TYyiC/W6V92jLqNp
xaquCnv8PIr/99Fd6I51d5pypDRpbgtj6EaD7k33pPvStGFNV419fgEl/zvr
LnUnuntNBWY1GW4b4+jTJP3HH00ZBjQ7mhZc8z1o1Lz7zjP/zbdjna/BAb+I
PwcoOJU=
           "]], 
          Line[CompressedData["
1:eJwl2GW4FWUbhuFNiwiI0l0qSInSXUpJSigtISEp3V3SiHSngICAiIJSgiJ2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           "]]}, "Charting`Private`Tag#1"], 
        Annotation[{
          Directive[
           Opacity[1.], 
           AbsoluteThickness[2], 
           Thickness[0.008], 
           RGBColor[0, 
            Rational[76, 255], 
            Rational[3, 5]]], 
          Line[CompressedData["
1:eJwV02N4ngcYhuE3VZLa7erUtu12W9dunb11RpPatm2vtm3btm0bO/PjTL73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           "]]}, "Charting`Private`Tag#2"], 
        Annotation[{
          Directive[
           Opacity[1.], 
           AbsoluteThickness[2], 
           Thickness[0.008], 
           RGBColor[
            Rational[1, 5], 
            Rational[3, 5], 1], 
           Dashing[Small]], 
          
          Line[{3109, 3426, 3269, 2734, 3375, 3217, 3076, 2952, 2844, 2490, 
           3327, 3169, 3028, 2904, 2796, 2703, 2626, 2563, 2393, 3273, 3115, 
           2974, 2850, 2742, 2649, 2572, 2509, 2464, 2438, 2394, 3450}], 
          Line[CompressedData["
1:eJwNyrlVAgEUQNFv6L504FHBQBRyUjIiQ2HYCtDAIkShB3ZaYBQrcBlQSzCw
DW9wo/eOO3fXtxsRUeVtJ+KCwXbECYutiBt2yTYjRjxQ491XYOg7JfXU2GOl
j+lSJ6HBh/+Skf+MZ2+dfdb6hEeafPquGPtyvHgSDvjSpzzRIvMVmfjyLD0N
DvnWZ/Ros/KVmPrOefU0OeJHn9Pn11Mh9ZRZ6/fk+NOX/APmjSoe
           "]], 
          Line[CompressedData["
1:eJwV1mW4lFUXBuChu1uk1E9CLLpblEaUMuk45KG7Q7obbLpblG4Fg+7u7q7v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           "]]}, "Charting`Private`Tag#3"], {
         Directive[
          Opacity[0.5], 
          RGBColor[0, 
           Rational[128, 255], 
           Rational[128, 255]]], 
         Line[{1892, 1891}], 
         Line[{3447, 3446}], 
         Line[{3452, 3451}], 
         Line[{3453, 1896}], 
         Line[{3454, 2384}], 
         Line[{3455, 3448}]}}}], {}}, <|
    "HighlightElements" -> <|
      "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
     "LayoutOptions" -> <|
      "PlotRange" -> {{0.5, 3.}, {0., 5.}}, 
       "Frame" -> {{True, True}, {True, True}}, 
       "AxesOrigin" -> {0.5000000000000011, 0}, 
       "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {False, False}, 
       "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), "DefaultStyle" -> {
         Directive[
          Opacity[1.], 
          AbsoluteThickness[2], 
          Thickness[0.008], 
          RGBColor[
           Rational[1, 5], 
           Rational[3, 5], 1], 
          Dashing[Small]], 
         Directive[
          Opacity[1.], 
          AbsoluteThickness[2], 
          Thickness[0.008], 
          RGBColor[0, 
           Rational[76, 255], 
           Rational[3, 5]]], 
         Directive[
          Opacity[1.], 
          AbsoluteThickness[2], 
          Thickness[0.006], 
          RGBColor[0, 
           Rational[128, 255], 
           Rational[128, 255]], 
          Dashing[{Small, Small}]]}, 
       "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
           Identity[
            Part[#, 1]], 
           Identity[
            Part[#, 2]]}& ), 
         "ScalingFunctions" -> {{Identity, Identity}, {Identity, Identity}}|>,
        "Primitives" -> {{{{
            EdgeForm[], 
            Directive[
             Opacity[0.5], 
             RGBColor[0, 
              Rational[128, 255], 
              Rational[128, 255]]], 
            GraphicsGroup[{{
               Polygon[CompressedData["
1:eJxl0Xs01ekaB3Dtqd++pO3yq2QXjZQ7OSVD5HlqdmqQUg2NEVKZmgbd1NGq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                "]]}, {
               Polygon[CompressedData["
1:eJxc12k4lO/7MHDMkChJQiISEkKyhTrv5CsVJVtRZN9DtrKmTdJG2QlZIiVL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                "]]}}]}, {}, {
            EdgeForm[], 
            Directive[
             Opacity[0.5], 
             RGBColor[0, 
              Rational[76, 255], 
              Rational[3, 5]]], 
            GraphicsGroup[{{
               Polygon[CompressedData["
1:eJxd13k4lN8bMHBmxsxkZ0h2oc3XEmmRch8qlbRHkYQsJVuorEVFK6mUJaEs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                
                "]]}}]}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, \
{}, {}}, {{}, {}, 
           Annotation[{
             Directive[
              Opacity[1.], 
              AbsoluteThickness[2], 
              Thickness[0.006], 
              RGBColor[0, 
               Rational[128, 255], 
               Rational[128, 255]], 
              Dashing[{Small, Small}]], 
             Line[CompressedData["
1:eJwV0Xs01WkXB3Cdqd+5pOPyq+SERsqdvCXjlr1rTmqQUobGCKlMTYNu8rLk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              "]], 
             Line[CompressedData["
1:eJwc13k8VF8bAHDMkChJQiISEkJCQj03+UlFyVYU2feQraxJJWmj7IQskZIl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              "]]}, "Charting`Private`Tag#1"], 
           Annotation[{
             Directive[
              Opacity[1.], 
              AbsoluteThickness[2], 
              Thickness[0.008], 
              RGBColor[0, 
               Rational[76, 255], 
               Rational[3, 5]]], 
             Line[CompressedData["
1:eJwV13k8lF8XAHBmxsxkZ5TsQpufJdIici6VStqjSEKWki1U1qKilVTKklCW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              "]]}, "Charting`Private`Tag#2"], 
           Annotation[{
             Directive[
              Opacity[1.], 
              AbsoluteThickness[2], 
              Thickness[0.008], 
              RGBColor[
               Rational[1, 5], 
               Rational[3, 5], 1], 
              Dashing[Small]], 
             Line[CompressedData["
1:eJxTTMoPSmViYGCQB2IQPSmX5/iUjCf2Cs+evZ9xRtjBTs9YVTzzib1Yz2ur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              "]], 
             Line[CompressedData["
1:eJwVzH881Accx3FddfneL75JpVK5rPPjssqubP34fOKmqzi0SdkN0c+VrFBj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              "]], 
             Line[CompressedData["
1:eJwV13c81W0UAHDzXqGSWUIZ2YnKCHkeI0pEeKWSrSFJijKK7ISQvZIdshtG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              "]]}, "Charting`Private`Tag#3"], {
            Directive[
             Opacity[0.5], 
             RGBColor[0, 
              Rational[128, 255], 
              Rational[128, 255]]], 
            
            Line[{{1.1481205048690568`, 2.747916912185581}, {
             1.1481703294864039`, 2.7477972455115607`}}], 
            
            Line[{{1.1481205048690568`, 3.138339828447312}, {
             1.1481703294864039`, 3.138188760151511}}], 
            
            Line[{{0.7167432818197352, 4.631304485533731}, {
             0.7167931064388042, 4.631099082493312}}], 
            
            Line[{{0.7168429054213791, 5.}, {0.7168429310561512, 
             4.949823329486749}}], 
            
            Line[{{1.1482201284278102`, 5.}, {1.148220154103751, 
             4.949742726349324}}], 
            
            Line[{{0.6377662295106392, 5.}, {0.6377662551562244, 
             4.949802158801987}}]}}}, {}}, "GCFlag" -> True|>, 
     "Meta" -> <|
      "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
       Plot, "GroupHighlight" -> False|>|>, "DynamicHighlight"]],
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->{False, False},
  AxesLabel->{None, None},
  AxesOrigin->{0.5000000000000011, 0},
  Background->GrayLevel[1],
  DisplayFunction->Identity,
  Epilog->InsetBox[
    BoxData[
     FormBox[
      TemplateBox[{
        StyleBox[
        "\"Current data\"", FontFamily -> "Times", FontSize -> 14, 
         StripOnInput -> False], 
        StyleBox[
        "\"Current data (IU)\"", FontFamily -> "Times", FontSize -> 14, 
         StripOnInput -> False], 
        StyleBox[
        "\"Forecast\"", FontFamily -> "Times", FontSize -> 14, StripOnInput -> 
         False]}, "LineLegend", DisplayFunction -> (FormBox[
         StyleBox[
          StyleBox[
           PaneBox[
            TagBox[
             GridBox[{{
                TagBox[
                 GridBox[{{
                    GraphicsBox[{{
                    Directive[
                    EdgeForm[
                    Directive[
                    Opacity[0.3], 
                    GrayLevel[0]]], 
                    PointSize[0.5], 
                    AbsoluteThickness[1.6], 
                    Thickness[0.11520000000000001`], 
                    RGBColor[0, 
                    NCache[
                    Rational[76, 255], 0.2980392156862745], 
                    NCache[
                    Rational[3, 5], 0.6]]], {
                    LineBox[{{0, 5}, {25, 5}}]}}, {
                    Directive[
                    EdgeForm[
                    Directive[
                    Opacity[0.3], 
                    GrayLevel[0]]], 
                    PointSize[0.5], 
                    AbsoluteThickness[1.6], 
                    Thickness[0.11520000000000001`], 
                    RGBColor[0, 
                    NCache[
                    Rational[76, 255], 0.2980392156862745], 
                    NCache[
                    Rational[3, 5], 0.6]]], {}}}, AspectRatio -> Full, 
                    ImageSize -> {25, 5}, PlotRangePadding -> None, 
                    ImagePadding -> Automatic, 
                    BaselinePosition -> (Scaled[-0.21] -> Baseline)], #}, {
                    GraphicsBox[{{
                    Directive[
                    EdgeForm[
                    Directive[
                    Opacity[0.3], 
                    GrayLevel[0]]], 
                    PointSize[0.5], 
                    AbsoluteThickness[1.6], 
                    Thickness[0.11520000000000001`], 
                    RGBColor[
                    NCache[
                    Rational[1, 5], 0.2], 
                    NCache[
                    Rational[3, 5], 0.6], 1], 
                    Dashing[Small]], {
                    LineBox[{{0, 5}, {25, 5}}]}}, {
                    Directive[
                    EdgeForm[
                    Directive[
                    Opacity[0.3], 
                    GrayLevel[0]]], 
                    PointSize[0.5], 
                    AbsoluteThickness[1.6], 
                    Thickness[0.11520000000000001`], 
                    RGBColor[
                    NCache[
                    Rational[1, 5], 0.2], 
                    NCache[
                    Rational[3, 5], 0.6], 1], 
                    Dashing[Small]], {}}}, AspectRatio -> Full, 
                    ImageSize -> {25, 5}, PlotRangePadding -> None, 
                    ImagePadding -> Automatic, 
                    BaselinePosition -> (Scaled[-0.21] -> Baseline)], #2}, {
                    GraphicsBox[{{
                    Directive[
                    EdgeForm[
                    Directive[
                    Opacity[0.3], 
                    GrayLevel[0]]], 
                    PointSize[0.5], 
                    AbsoluteThickness[1.6], 
                    Thickness[0.0864], 
                    RGBColor[0, 
                    NCache[
                    Rational[128, 255], 0.5019607843137255], 
                    NCache[
                    Rational[128, 255], 0.5019607843137255]], 
                    Dashing[{Small, Small}]], {
                    LineBox[{{0, 5}, {25, 5}}]}}, {
                    Directive[
                    EdgeForm[
                    Directive[
                    Opacity[0.3], 
                    GrayLevel[0]]], 
                    PointSize[0.5], 
                    AbsoluteThickness[1.6], 
                    Thickness[0.0864], 
                    RGBColor[0, 
                    NCache[
                    Rational[128, 255], 0.5019607843137255], 
                    NCache[
                    Rational[128, 255], 0.5019607843137255]], 
                    Dashing[{Small, Small}]], {}}}, AspectRatio -> Full, 
                    ImageSize -> {25, 5}, PlotRangePadding -> None, 
                    ImagePadding -> Automatic, 
                    BaselinePosition -> (Scaled[-0.21] -> Baseline)], #3}}, 
                  GridBoxAlignment -> {
                   "Columns" -> {Center, Left}, "Rows" -> {{Baseline}}}, 
                  AutoDelete -> False, 
                  GridBoxDividers -> {
                   "Columns" -> {{False}}, "Rows" -> {{False}}}, 
                  GridBoxItemSize -> {
                   "Columns" -> {{All}}, "Rows" -> {{All}}}, 
                  GridBoxSpacings -> {
                   "Columns" -> {{0.5}}, "Rows" -> {{0.8}}}], "Grid"]}}, 
              GridBoxAlignment -> {"Columns" -> {{Left}}, "Rows" -> {{Top}}}, 
              AutoDelete -> False, 
              GridBoxItemSize -> {
               "Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, 
              GridBoxSpacings -> {"Columns" -> {{1}}, "Rows" -> {{0}}}], 
             "Grid"], Alignment -> Left, AppearanceElements -> None, 
            ImageMargins -> {{5, 5}, {5, 5}}, ImageSizeAction -> 
            "ResizeToFit"], LineIndent -> 0, StripOnInput -> False], {
          FontFamily -> "Arial"}, Background -> Automatic, StripOnInput -> 
          False], TraditionalForm]& ), 
       InterpretationFunction :> (RowBox[{"LineLegend", "[", 
          RowBox[{
            RowBox[{"{", 
              RowBox[{
                RowBox[{"Directive", "[", 
                  RowBox[{
                    RowBox[{"Thickness", "[", "0.008`", "]"}], ",", 
                    TemplateBox[<|"color" -> RGBColor[0, 
                    Rational[76, 255], 
                    Rational[3, 5]]|>, "RGBColorSwatchTemplate"]}], "]"}], 
                ",", 
                RowBox[{"Directive", "[", 
                  RowBox[{
                    RowBox[{"Thickness", "[", "0.008`", "]"}], ",", 
                    TemplateBox[<|"color" -> RGBColor[
                    Rational[1, 5], 
                    Rational[3, 5], 1]|>, "RGBColorSwatchTemplate"], ",", 
                    RowBox[{"Dashing", "[", "Small", "]"}]}], "]"}], ",", 
                RowBox[{"Directive", "[", 
                  RowBox[{
                    RowBox[{"Thickness", "[", "0.006`", "]"}], ",", 
                    TemplateBox[<|"color" -> RGBColor[0, 
                    Rational[128, 255], 
                    Rational[128, 255]]|>, "RGBColorSwatchTemplate"], ",", 
                    RowBox[{"Dashing", "[", 
                    RowBox[{"{", 
                    RowBox[{"Small", ",", "Small"}], "}"}], "]"}]}], "]"}]}], 
              "}"}], ",", 
            RowBox[{"{", 
              RowBox[{#, ",", #2, ",", #3}], "}"}], ",", 
            RowBox[{"LegendMarkerSize", "\[Rule]", 
              RowBox[{"{", 
                RowBox[{"25", ",", "5"}], "}"}]}]}], "]"}]& ), Editable -> 
       True], TraditionalForm]], 
    Scaled[{0.22, 0.18}]],
  Frame->{{True, True}, {True, True}},
  FrameLabel->{{None, None}, {None, None}},
  FrameStyle->Directive[
    GrayLevel[0], FontSize -> 13, FontFamily -> "Times"],
  FrameTicks->{{Automatic, Automatic}, {Automatic, Automatic}},
  FrameTicksStyle->Directive[
    GrayLevel[0]],
  GridLines->{Automatic, Automatic},
  GridLinesStyle->Directive[
    GrayLevel[0.5, 0.4]],
  ImagePadding->All,
  Method->{
   "DefaultBoundaryStyle" -> Automatic, 
    "DefaultGraphicsInteraction" -> {
     "Version" -> 1.2, "TrackMousePosition" -> {True, False}, 
      "Effects" -> {
       "Highlight" -> {"ratio" -> 2}, "HighlightPoint" -> {"ratio" -> 2}, 
        "Droplines" -> {
         "freeformCursorMode" -> True, 
          "placement" -> {"x" -> "All", "y" -> "None"}}}}, "DefaultMeshStyle" -> 
    AbsolutePointSize[6], "ScalingFunctions" -> None, 
    "CoordinatesToolOptions" -> {"DisplayFunction" -> ({
        (Identity[#]& )[
         Part[#, 1]], 
        (Identity[#]& )[
         Part[#, 2]]}& ), "CopiedValueFunction" -> ({
        (Identity[#]& )[
         Part[#, 1]], 
        (Identity[#]& )[
         Part[#, 2]]}& )}, "AxesInFront" -> True},
  PlotRange->{{0.5, 3.}, {0., 5.}},
  PlotRangeClipping->True,
  PlotRangePadding->{{0, 0}, {0, 0}},
  Ticks->{Automatic, Automatic}]], "Output",
 CellChangeTimes->{
  3.9120049302085733`*^9, 3.912004969945695*^9, {3.9120050015462637`*^9, 
   3.912005066392282*^9}, 3.912005169278319*^9, 3.9120052745827312`*^9, {
   3.912005662464959*^9, 3.912005731263888*^9}, {3.912005766580595*^9, 
   3.912005787252603*^9}, 3.912005819416375*^9, 3.912006191825386*^9, {
   3.912006305701858*^9, 3.91200637858432*^9}},
 CellLabel->
  "Out[328]=",ExpressionUUID->"9a654e6c-8528-4e40-b66d-7eaef8d12268"],

Cell[BoxData["\<\"pathOut/plotkXmPLPP.pdf\"\>"], "Output",
 CellChangeTimes->{
  3.9120049302085733`*^9, 3.912004969945695*^9, {3.9120050015462637`*^9, 
   3.912005066392282*^9}, 3.912005169278319*^9, 3.9120052745827312`*^9, {
   3.912005662464959*^9, 3.912005731263888*^9}, {3.912005766580595*^9, 
   3.912005787252603*^9}, 3.912005819416375*^9, 3.912006191825386*^9, {
   3.912006305701858*^9, 3.912006379311351*^9}},
 CellLabel->
  "Out[329]=",ExpressionUUID->"f9d29e1e-4ab0-40a2-a892-f76d969fe3d4"]
}, Open  ]],

Cell[BoxData["Dashing"], "Code",
 CellChangeTimes->{{3.912005129176094*^9, 
  3.912005135024765*^9}},ExpressionUUID->"7d5b627d-eaa1-4ef1-b7c1-\
464527b62225"]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["\<\
EXTRA:\[LineSeparator]Exclusion plot k x MinMass using best fit PLPP \
parameters: \[LineSeparator]This is code part is valid only as a cross check. \
It yields the same result of the median\
\>", "Section",
 CellChangeTimes->{{3.896374769619068*^9, 3.896374776494128*^9}, {
  3.896432884057825*^9, 3.896432888701438*^9}, {3.8964329400536747`*^9, 
  3.896432940700355*^9}, {3.905662036694413*^9, 3.905662060559596*^9}, {
  3.905777062300296*^9, 3.905777135050795*^9}},
 FontColor->RGBColor[
  0, 1, 1],ExpressionUUID->"e9c4dcf0-3b39-4088-b100-3f354e2459d1"],

Cell["\<\
here I have to select randomly different PLPP values and find the probability \
with reference values.\
\>", "Text",
 CellChangeTimes->{{3.896374781246215*^9, 
  3.896374809849959*^9}},ExpressionUUID->"dc6ea1b2-5259-4211-9cea-\
9874ea64dac2"],

Cell[BoxData[{
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"\[ScriptCapitalD]M1FormationEmpRaw", "[", 
     RowBox[{
     "zObs_", ",", " ", "tdmin_", ",", " ", "tdmax_", ",", " ", "k_", ",", 
      " ", "zMax_", ",", " ", "w_"}], "]"}], " ", ":=", " ", "\n", " ", 
    RowBox[{"EmpiricalDistribution", "[", "\n", "   ", 
     RowBox[{"dataM1FormationRaw", "[", 
      RowBox[{
      "zObs", ",", " ", "tdmin", ",", " ", "tdmax", ",", " ", "k", ",", " ", 
       "zMax", ",", " ", "w"}], "]"}], "\n", " ", "]"}]}], ";"}], 
  "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"\[ScriptCapitalD]M1FormationEmp", "[", 
     RowBox[{"zObs_", ",", " ", 
      RowBox[{"opts", ":", 
       RowBox[{"OptionsPattern", "[", "optionstkw", "]"}]}]}], "]"}], " ", ":=",
     " ", 
    RowBox[{"\[ScriptCapitalD]M1FormationEmpRaw", "[", "\n", "  ", 
     RowBox[{"zObs", ",", " ", "\n", "  ", 
      RowBox[{"OptionValue", " ", "@", " ", "tdmin"}], ",", " ", "\n", "  ", 
      RowBox[{"OptionValue", " ", "@", " ", "tdmax"}], ",", " ", "\n", "  ", 
      RowBox[{"OptionValue", " ", "@", " ", "k"}], ",", " ", "\n", "  ", 
      RowBox[{"OptionValue", " ", "@", " ", "zMax"}], ",", " ", "\n", "  ", 
      RowBox[{"OptionValue", " ", "@", " ", "w"}]}], "\n", "]"}]}], ";"}], 
  "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"probabilityMminApprox", "[", 
    RowBox[{"mMin_", ",", " ", 
     RowBox[{"opts", ":", 
      RowBox[{"OptionsPattern", "[", "optionstkw", "]"}]}]}], "]"}], " ", ":=",
    " ", 
   SuperscriptBox[
    RowBox[{"SurvivalFunction", "[", 
     RowBox[{
      RowBox[{"\[ScriptCapitalD]M1FormationEmp", "[", 
       RowBox[{"0.4", ",", " ", "opts"}], "]"}], ",", " ", "mMin"}], "]"}], 
    "72"]}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"probabilityMminApproxF", "[", 
     RowBox[{"mMin_", ",", " ", 
      RowBox[{"opts", ":", 
       RowBox[{"OptionsPattern", "[", "optionstkw", "]"}]}]}], "]"}], " ", ":=",
     " ", 
    SuperscriptBox[
     RowBox[{"SurvivalFunction", "[", 
      RowBox[{
       RowBox[{"\[ScriptCapitalD]M1FormationEmp", "[", 
        RowBox[{"0.4", ",", " ", "opts"}], "]"}], ",", " ", "mMin"}], "]"}], 
     "250"]}], ";"}], " ", 
  RowBox[{"(*", "forecast", "*)"}]}]}], "Code",
 CellChangeTimes->{{3.905610505837244*^9, 3.90561050649187*^9}},
 CellLabel->"In[13]:=",ExpressionUUID->"ceba595e-b4f4-47c5-bfb2-7acb69981445"],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"probabilityMminApprox", "[", "2", "]"}], " ", "//", " ", 
  "EchoTiming"}]], "Code",
 CellChangeTimes->{{3.905610474276565*^9, 3.905610474737488*^9}, {
  3.905610510853754*^9, 3.905610512721939*^9}},
 CellLabel->"In[31]:=",ExpressionUUID->"5e16e4a2-181d-4113-96b6-3974b5af7339"],

Cell[BoxData["0.167524`"], "EchoTiming",
 CellChangeTimes->{
  3.905662827049197*^9},ExpressionUUID->"edbfff56-0b3e-4c7c-8e0c-\
1c00998c6d5b"],

Cell[BoxData["0.0002366066647006493`"], "Output",
 CellChangeTimes->{
  3.9056104785388613`*^9, {3.905610523674601*^9, 3.905610540132585*^9}, 
   3.905611350572585*^9, 3.905619322264041*^9, {3.905662815465951*^9, 
   3.905662827061446*^9}},
 CellLabel->"Out[31]=",ExpressionUUID->"b77041b2-7f27-4d1c-b3b7-4d7e96359b68"]
}, Open  ]],

Cell[BoxData[{
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{
   "tab", ",", " ", "sol", ",", " ", "solAll", ",", " ", "probValue"}], "]"}],
   ";"}], "\n", 
 RowBox[{
  RowBox[{"probValue", " ", "=", " ", 
   RowBox[{"probSigma", "[", "2", "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"listk1", " ", "=", " ", 
   RowBox[{"Range", "[", 
    RowBox[{"0.5", ",", " ", "3", ",", " ", "0.025"}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"listm1", " ", "=", " ", 
   RowBox[{"Range", "[", 
    RowBox[{"0.4", ",", " ", "6", ",", " ", "0.025"}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"sol", "[", "0", "]"}], " ", "=", " ", 
    RowBox[{"{", 
     RowBox[{"arbitraryK", ",", " ", 
      RowBox[{"Last", " ", "@", " ", "listm1"}]}], "}"}]}], ";"}], " ", 
  RowBox[{"(*", 
   RowBox[{"Only", " ", "used", " ", "for", " ", "the", " ", "first", " ", 
    RowBox[{"step", "."}]}], "*)"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"tab", "[", "nk1_", "]"}], " ", ":=", " ", 
   RowBox[{
    RowBox[{"tab", "[", "nk1", "]"}], " ", "=", " ", 
    RowBox[{"Block", "[", 
     RowBox[{
      RowBox[{"{", 
       RowBox[{
       "nm1Previous", ",", " ", "nm1Minimal", ",", " ", "listm1Relevant"}], 
       "}"}], ",", "\n", "  ", 
      RowBox[{
       RowBox[{"nm1Previous", " ", "=", " ", 
        RowBox[{
         RowBox[{"Position", "[", 
          RowBox[{"listm1", ",", " ", 
           RowBox[{"Last", "@", 
            RowBox[{"sol", "[", 
             RowBox[{"nk1", "-", "1"}], "]"}]}]}], "]"}], "[", 
         RowBox[{"[", 
          RowBox[{"1", ",", "1"}], "]"}], "]"}]}], ";", "\n", "  ", 
       RowBox[{"nm1Minimal", " ", "=", " ", 
        RowBox[{"If", "[", 
         RowBox[{
          RowBox[{
           RowBox[{"nm1Previous", " ", "-", " ", "10"}], " ", "<", " ", "1"}],
           ",", " ", "1", ",", " ", 
          RowBox[{"nm1Previous", " ", "-", " ", "10"}]}], "]"}]}], ";", "\n", 
       "  ", 
       RowBox[{"listm1Relevant", " ", "=", " ", 
        RowBox[{"listm1", " ", "//", " ", 
         RowBox[{
          RowBox[{"Take", "[", 
           RowBox[{"#", ",", " ", 
            RowBox[{"{", 
             RowBox[{"nm1Minimal", ",", " ", "nm1Previous"}], "}"}]}], "]"}], 
          " ", "&"}]}]}], ";", "\n", "  ", 
       RowBox[{"Table", "[", "\n", "    ", 
        RowBox[{
         RowBox[{"{", 
          RowBox[{
           RowBox[{"{", 
            RowBox[{
             RowBox[{"listk1", "[", 
              RowBox[{"[", "nk1", "]"}], "]"}], ",", " ", "m1"}], "}"}], ",", 
           " ", 
           RowBox[{"Abs", "[", 
            RowBox[{
             RowBox[{"probabilityMminApprox", "[", 
              RowBox[{"m1", ",", " ", 
               RowBox[{"k", " ", "->", " ", 
                RowBox[{"listk1", "[", 
                 RowBox[{"[", "nk1", "]"}], "]"}]}]}], "]"}], " ", "-", " ", 
             "probValue"}], "]"}]}], "}"}], " ", ",", " ", "\n", "    ", 
         RowBox[{"{", 
          RowBox[{"m1", ",", " ", "listm1Relevant"}], "}"}]}], "\n", "  ", 
        "]"}]}]}], "\n", "]"}]}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"sol", "[", "nk1_", "]"}], " ", ":=", " ", 
    RowBox[{
     RowBox[{"sol", "[", "nk1", "]"}], " ", "=", " ", 
     RowBox[{
      RowBox[{"tab", "[", "nk1", "]"}], " ", "//", " ", 
      RowBox[{
       RowBox[{
        RowBox[{"SortBy", "[", 
         RowBox[{"#", ",", " ", "Last"}], "]"}], "[", 
        RowBox[{"[", 
         RowBox[{"1", ",", "1"}], "]"}], "]"}], " ", "&"}]}]}]}], " ", 
   RowBox[{"(*", 
    RowBox[{"//", " ", "Echo"}], "*)"}], ";"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{"solAll", " ", ":=", " ", 
   RowBox[{"solAll", " ", "=", " ", 
    RowBox[{"Monitor", "[", 
     RowBox[{
      RowBox[{"Table", "[", 
       RowBox[{
        RowBox[{"sol", "[", "nk1", "]"}], ",", " ", 
        RowBox[{"{", 
         RowBox[{"nk1", ",", " ", 
          RowBox[{"Length", " ", "@", " ", "listk1"}]}], "}"}]}], "]"}], ",", 
      " ", "nk1"}], "]"}]}]}], ";"}]}], "Code",
 CellChangeTimes->CompressedData["
1:eJwdyVtMkgEABWAiL7QmWSKjHugyHhTSiEhbhNSsh7A1oynOyphpNdOxudDR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  "],
 CellLabel->"In[60]:=",ExpressionUUID->"e8dcbb96-dd40-40e2-b9a5-9884828bfaf2"],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"sol", "[", "2", "]"}]], "Code",
 CellChangeTimes->{{3.905619319398951*^9, 3.9056193376146793`*^9}},
 CellLabel->"In[37]:=",ExpressionUUID->"bd354220-1e7e-4c63-9c02-8167f7abdd9a"],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"5.65`", ",", "0.525`"}], "}"}]], "Output",
 CellChangeTimes->{{3.9056193309600687`*^9, 3.905619347083087*^9}, 
   3.905619435463006*^9},
 CellLabel->"Out[37]=",ExpressionUUID->"a7ce2b29-7f76-4843-aa8e-914a06f94406"]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Reverse", " ", "/@", " ", "solAll", " ", 
  RowBox[{"(*", 
   RowBox[{
   "This", " ", "solAll", " ", "was", " ", "generated", " ", "with", " ", 
    "an", " ", "inversed", " ", "k", " ", "x", " ", "m", " ", 
    RowBox[{"position", "."}]}], "*)"}]}]], "Code",
 CellChangeTimes->{{3.905662083461815*^9, 3.905662086186615*^9}, {
  3.905662218352455*^9, 
  3.90566224350027*^9}},ExpressionUUID->"9e3caa9f-df25-4607-843f-\
9cf19449d947"],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{"0.5`", ",", "5.775`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.525`", ",", "5.65`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.55`", ",", "5.550000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.575`", ",", "5.425000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.6`", ",", "5.325000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.625`", ",", "5.200000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.65`", ",", "5.1000000000000005`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.675`", ",", "4.9750000000000005`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.7`", ",", "4.875000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.725`", ",", "4.775`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.75`", ",", "4.675000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.775`", ",", "4.575`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.8`", ",", "4.4750000000000005`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.825`", ",", "4.375`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.8500000000000001`", ",", "4.275`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.875`", ",", "4.175000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.9`", ",", "4.075`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.925`", ",", "4.`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.95`", ",", "3.9`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.9750000000000001`", ",", "3.8000000000000003`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.`", ",", "3.725`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.025`", ",", "3.65`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.05`", ",", "3.5500000000000003`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.0750000000000002`", ",", "3.475`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.1`", ",", "3.4`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.125`", ",", "3.325`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.15`", ",", "3.25`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.175`", ",", "3.1750000000000003`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.2000000000000002`", ",", "3.1`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.225`", ",", "3.025`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.25`", ",", "2.95`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.275`", ",", "2.875`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.3`", ",", "2.8000000000000003`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.3250000000000002`", ",", "2.75`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.35`", ",", "2.675`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.375`", ",", "2.625`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.4`", ",", "2.55`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.425`", ",", "2.5`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.4500000000000002`", ",", "2.425`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.475`", ",", "2.375`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.5`", ",", "2.325`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.5250000000000001`", ",", "2.25`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.55`", ",", "2.2`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.575`", ",", "2.15`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.6`", ",", "2.1`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.625`", ",", "2.0500000000000003`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.6500000000000001`", ",", "2.`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.675`", ",", "1.9500000000000002`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.7000000000000002`", ",", "1.9`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.725`", ",", "1.85`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.75`", ",", "1.8000000000000003`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.7750000000000001`", ",", "1.775`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.8`", ",", "1.725`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.8250000000000002`", ",", "1.6750000000000003`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.85`", ",", "1.65`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.875`", ",", "1.6`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.9000000000000001`", ",", "1.5750000000000002`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.925`", ",", "1.525`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.9500000000000002`", ",", "1.475`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.975`", ",", "1.4500000000000002`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.`", ",", "1.4250000000000003`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.0250000000000004`", ",", "1.375`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.05`", ",", "1.35`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.075`", ",", "1.3250000000000002`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.1`", ",", "1.275`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.125`", ",", "1.25`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.1500000000000004`", ",", "1.225`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.175`", ",", "1.2000000000000002`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.2`", ",", "1.15`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.225`", ",", "1.125`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.25`", ",", "1.1`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.2750000000000004`", ",", "1.0750000000000002`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.3`", ",", "1.05`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.325`", ",", "1.025`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.35`", ",", "1.`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.375`", ",", "0.9750000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.4000000000000004`", ",", "0.9500000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.425`", ",", "0.925`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.45`", ",", "0.9`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.475`", ",", "0.875`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.5`", ",", "0.8500000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.525`", ",", "0.8500000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.5500000000000003`", ",", "0.8250000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.575`", ",", "0.8`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.6`", ",", "0.775`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.625`", ",", "0.75`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.65`", ",", "0.75`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.6750000000000003`", ",", "0.7250000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.7`", ",", "0.7000000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.725`", ",", "0.675`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.75`", ",", "0.675`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.775`", ",", "0.65`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.8000000000000003`", ",", "0.625`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.825`", ",", "0.625`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.85`", ",", "0.6000000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.875`", ",", "0.6000000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.9000000000000004`", ",", "0.5750000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.9250000000000003`", ",", "0.55`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.95`", ",", "0.55`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.975`", ",", "0.525`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"3.`", ",", "0.525`"}], "}"}]}], "}"}]], "Output",
 CellChangeTimes->{{3.9056620809815397`*^9, 3.9056620901004*^9}},
 CellLabel->"Out[52]=",ExpressionUUID->"4364c2b5-5bc0-41c2-ba35-18f59ccc7591"]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Show", "[", 
  RowBox[{
   RowBox[{"ListPlot", "[", 
    RowBox[{
     RowBox[{"Reverse", " ", "/@", " ", "solAll"}], ",", " ", 
     RowBox[{"Joined", "->", "True"}], ",", " ", 
     RowBox[{"PlotRange", "->", "All"}]}], "]"}], ",", " ", 
   RowBox[{"Plot", "[", 
    RowBox[{"2", ",", " ", 
     RowBox[{"{", 
      RowBox[{"x", ",", " ", "0", ",", " ", "10"}], "}"}], ",", " ", 
     RowBox[{"PlotStyle", " ", "->", " ", "Dashed"}]}], "]"}]}], 
  "]"}]], "Code",
 CellChangeTimes->{{3.9056204361697683`*^9, 3.9056204540579042`*^9}, {
   3.905620527553697*^9, 3.9056205280481997`*^9}, 3.905662103163228*^9, {
   3.905662278634403*^9, 3.9056623385116987`*^9}},
 CellLabel->"In[57]:=",ExpressionUUID->"a5209e25-ffb2-4bef-9ac4-f8e9c04448a7"],

Cell[BoxData[
 GraphicsBox[{{{}, 
    InterpretationBox[{
      TagBox[{{}, {}, 
        TagBox[
         {RGBColor[0.368417, 0.506779, 0.709798], PointSize[
          0.009166666666666668], AbsoluteThickness[2], LineBox[CompressedData["
1:eJxdlWtSIkEMgHuGx+BzQXzU/twzyP+eA/jLI1il/NwreA28htdgPYMPZFlF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           "]]},
         Annotation[#, "Charting`Private`Tag#1"]& ]},
       {"WolframDynamicHighlight", <|
        "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>}], 
      DynamicBox[(Charting`HighlightActionBox["DynamicHighlight", {}, 
        Slot["HighlightElements"], 
        Slot["LayoutOptions"], 
        Slot["Meta"], 
        Charting`HighlightActionFunction["DynamicHighlight", {{{}, {}, 
           Annotation[{
             Hue[0.67, 0.6, 0.6], 
             Directive[
              PointSize[0.009166666666666668], 
              RGBColor[0.368417, 0.506779, 0.709798], 
              AbsoluteThickness[2]], 
             Line[CompressedData["
1:eJxdlWtSIkEMgHuGx+BzQXzU/twzyP+eA/jLI1il/NwreA28htdgPYMPZFlF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              "]]}, "Charting`Private`Tag#1"]}}, <|
         "HighlightElements" -> <|
           "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>, 
          "LayoutOptions" -> <|
           "PlotRange" -> {{0.4479166666666679, 3.}, {0, 5.775}}, 
            "Frame" -> {{False, False}, {False, False}}, 
            "AxesOrigin" -> {0.4479166666666679, 0}, 
            "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
            "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
            "DefaultStyle" -> {
              Directive[
               PointSize[0.009166666666666668], 
               RGBColor[0.368417, 0.506779, 0.709798], 
               AbsoluteThickness[2]]}, 
            "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
                Identity[
                 Part[#, 1]], 
                Identity[
                 Part[#, 2]]}& ), 
              "ScalingFunctions" -> {{Identity, Identity}, {
                Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> 
            False|>, 
          "Meta" -> <|
           "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
            ListPlot, "GroupHighlight" -> False|>|>]]& )[<|
        "HighlightElements" -> <|
          "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>, 
         "LayoutOptions" -> <|
          "PlotRange" -> {{0.4479166666666679, 3.}, {0, 5.775}}, 
           "Frame" -> {{False, False}, {False, False}}, 
           "AxesOrigin" -> {0.4479166666666679, 0}, 
           "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
           "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
           "DefaultStyle" -> {
             Directive[
              PointSize[0.009166666666666668], 
              RGBColor[0.368417, 0.506779, 0.709798], 
              AbsoluteThickness[2]]}, 
           "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
               Identity[
                Part[#, 1]], 
               Identity[
                Part[#, 2]]}& ), 
             "ScalingFunctions" -> {{Identity, Identity}, {
               Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> 
           False|>, 
         "Meta" -> <|
          "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
           ListPlot, "GroupHighlight" -> False|>|>],
       ImageSizeCache->{{4.503599627370496*^15, -4.503599627370496*^15}, {
        4.503599627370496*^15, -4.503599627370496*^15}}]},
     Annotation[{{{}, {}, 
        Annotation[{
          Hue[0.67, 0.6, 0.6], 
          Directive[
           PointSize[0.009166666666666668], 
           RGBColor[0.368417, 0.506779, 0.709798], 
           AbsoluteThickness[2]], 
          Line[CompressedData["
1:eJxdlWtSIkEMgHuGx+BzQXzU/twzyP+eA/jLI1il/NwreA28htdgPYMPZFlF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           "]]}, "Charting`Private`Tag#1"]}}, <|
      "HighlightElements" -> <|
        "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>, 
       "LayoutOptions" -> <|
        "PlotRange" -> {{0.4479166666666679, 3.}, {0, 5.775}}, 
         "Frame" -> {{False, False}, {False, False}}, 
         "AxesOrigin" -> {0.4479166666666679, 0}, 
         "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
         "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
         "DefaultStyle" -> {
           Directive[
            PointSize[0.009166666666666668], 
            RGBColor[0.368417, 0.506779, 0.709798], 
            AbsoluteThickness[2]]}, 
         "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
             Identity[
              Part[#, 1]], 
             Identity[
              Part[#, 2]]}& ), 
           "ScalingFunctions" -> {{Identity, Identity}, {
             Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> False|>, 
       "Meta" -> <|
        "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
         ListPlot, "GroupHighlight" -> False|>|>, 
      "DynamicHighlight"]], {{}, {}}}, 
   InterpretationBox[{
     TagBox[{{{}, {}, 
        TagBox[
         {RGBColor[0.368417, 0.506779, 0.709798], AbsoluteThickness[2], 
          Opacity[1.], Dashing[{Small, Small}], LineBox[CompressedData["
1:eJxTTMoPSmViYGAwAWIQPbcuic0wpduOAQIc2G8/Un8rv9Mexl94an7ha/mT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           "]]},
         Annotation[#, "Charting`Private`Tag#1"]& ]}, {}},
      {"WolframDynamicHighlight", <|
       "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>}], 
     DynamicBox[(Charting`HighlightActionBox["DynamicHighlight", {}, 
       Slot["HighlightElements"], 
       Slot["LayoutOptions"], 
       Slot["Meta"], 
       Charting`HighlightActionFunction["DynamicHighlight", {{{{}, {}, 
           Annotation[{
             Directive[
              Opacity[1.], 
              RGBColor[0.368417, 0.506779, 0.709798], 
              AbsoluteThickness[2], 
              Dashing[{Small, Small}]], 
             Line[CompressedData["
1:eJxTTMoPSmViYGAwAWIQPbcuic0wpduOAQIc2G8/Un8rv9Mexl94an7ha/mT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              "]]}, "Charting`Private`Tag#1"]}}, {}}, <|
        "HighlightElements" -> <|
          "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
         "LayoutOptions" -> <|
          "PlotRange" -> {{0, 10}, {0., 4.}}, 
           "Frame" -> {{False, False}, {False, False}}, 
           "AxesOrigin" -> {0, 0}, "ImageSize" -> {360, 360/GoldenRatio}, 
           "Axes" -> {True, True}, "LabelStyle" -> {}, "AspectRatio" -> 
           GoldenRatio^(-1), "DefaultStyle" -> {
             Directive[
              Opacity[1.], 
              RGBColor[0.368417, 0.506779, 0.709798], 
              AbsoluteThickness[2], 
              Dashing[{Small, Small}]]}, 
           "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
               Identity[
                Part[#, 1]], 
               Identity[
                Part[#, 2]]}& ), 
             "ScalingFunctions" -> {{Identity, Identity}, {
               Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> 
           False|>, 
         "Meta" -> <|
          "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
           Plot, "GroupHighlight" -> False|>|>]]& )[<|
       "HighlightElements" -> <|
         "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
        "LayoutOptions" -> <|
         "PlotRange" -> {{0, 10}, {0., 4.}}, 
          "Frame" -> {{False, False}, {False, False}}, "AxesOrigin" -> {0, 0},
           "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
          "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
          "DefaultStyle" -> {
            Directive[
             Opacity[1.], 
             RGBColor[0.368417, 0.506779, 0.709798], 
             AbsoluteThickness[2], 
             Dashing[{Small, Small}]]}, 
          "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
              Identity[
               Part[#, 1]], 
              Identity[
               Part[#, 2]]}& ), 
            "ScalingFunctions" -> {{Identity, Identity}, {
              Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> False|>,
         "Meta" -> <|
         "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
          Plot, "GroupHighlight" -> False|>|>],
      ImageSizeCache->{{4.503599627370496*^15, -4.503599627370496*^15}, {
       4.503599627370496*^15, -4.503599627370496*^15}}]},
    Annotation[{{{{}, {}, 
        Annotation[{
          Directive[
           Opacity[1.], 
           RGBColor[0.368417, 0.506779, 0.709798], 
           AbsoluteThickness[2], 
           Dashing[{Small, Small}]], 
          Line[CompressedData["
1:eJxTTMoPSmViYGAwAWIQPbcuic0wpduOAQIc2G8/Un8rv9Mexl94an7ha/mT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           "]]}, "Charting`Private`Tag#1"]}}, {}}, <|
     "HighlightElements" -> <|
       "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
      "LayoutOptions" -> <|
       "PlotRange" -> {{0, 10}, {0., 4.}}, 
        "Frame" -> {{False, False}, {False, False}}, "AxesOrigin" -> {0, 0}, 
        "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
        "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), "DefaultStyle" -> {
          Directive[
           Opacity[1.], 
           RGBColor[0.368417, 0.506779, 0.709798], 
           AbsoluteThickness[2], 
           Dashing[{Small, Small}]]}, 
        "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
            Identity[
             Part[#, 1]], 
            Identity[
             Part[#, 2]]}& ), 
          "ScalingFunctions" -> {{Identity, Identity}, {
            Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> False|>, 
      "Meta" -> <|
       "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
        Plot, "GroupHighlight" -> False|>|>, "DynamicHighlight"]]},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->{True, True},
  AxesLabel->{None, None},
  AxesOrigin->{0.4479166666666679, 0},
  DisplayFunction->Identity,
  Frame->{{False, False}, {False, False}},
  FrameLabel->{{None, None}, {None, None}},
  FrameTicks->{{Automatic, Automatic}, {Automatic, Automatic}},
  GridLines->{None, None},
  GridLinesStyle->Directive[
    GrayLevel[0.5, 0.4]],
  Method->{
   "AxisPadding" -> Scaled[0.02], "DefaultBoundaryStyle" -> Automatic, 
    "DefaultGraphicsInteraction" -> {
     "Version" -> 1.2, "TrackMousePosition" -> {True, False}, 
      "Effects" -> {
       "Highlight" -> {"ratio" -> 2}, "HighlightPoint" -> {"ratio" -> 2}, 
        "Droplines" -> {
         "freeformCursorMode" -> True, 
          "placement" -> {"x" -> "All", "y" -> "None"}}}}, "DefaultMeshStyle" -> 
    AbsolutePointSize[6], "DefaultPlotStyle" -> {
      Directive[
       RGBColor[0.368417, 0.506779, 0.709798], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.880722, 0.611041, 0.142051], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.560181, 0.691569, 0.194885], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.922526, 0.385626, 0.209179], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.528488, 0.470624, 0.701351], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.772079, 0.431554, 0.102387], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.363898, 0.618501, 0.782349], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[1, 0.75, 0], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.647624, 0.37816, 0.614037], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.571589, 0.586483, 0.], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.915, 0.3325, 0.2125], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.40082222609352647`, 0.5220066643438841, 0.85], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.9728288904374106, 0.621644452187053, 0.07336199581899142], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.736782672705901, 0.358, 0.5030266573755369], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.28026441037696703`, 0.715, 0.4292089322474965], 
       AbsoluteThickness[2]]}, "DomainPadding" -> Scaled[0.02], 
    "PointSizeFunction" -> "SmallPointSize", "RangePadding" -> Scaled[0.05], 
    "OptimizePlotMarkers" -> True, "IncludeHighlighting" -> "CurrentSet", 
    "HighlightStyle" -> Automatic, "OptimizePlotMarkers" -> True, 
    "CoordinatesToolOptions" -> {"DisplayFunction" -> ({
        Identity[
         Part[#, 1]], 
        Identity[
         Part[#, 2]]}& ), "CopiedValueFunction" -> ({
        Identity[
         Part[#, 1]], 
        Identity[
         Part[#, 2]]}& )}},
  PlotRange->{{0.4479166666666679, 3.}, {0, 5.775}},
  PlotRangeClipping->True,
  PlotRangePadding->{{
     Scaled[0.02], 
     Scaled[0.02]}, {
     Scaled[0.02], 
     Scaled[0.05]}},
  Ticks->{Automatic, Automatic}]], "Output",
 CellChangeTimes->{{3.905662318663398*^9, 3.905662338838307*^9}},
 CellLabel->"Out[57]=",ExpressionUUID->"51117444-7404-4b4a-9b62-cdfcdd788318"]
}, Open  ]],

Cell[CellGroupData[{

Cell["Faster version: larger steps and using interpolation", "Subsection",
 CellChangeTimes->{{3.905662611627655*^9, 
  3.905662658259502*^9}},ExpressionUUID->"4cbcd9b6-b66b-4642-baf3-\
a07af8433879"],

Cell[BoxData[{
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{
   "tab", ",", " ", "sol", ",", " ", "solAll", ",", " ", "probValue"}], "]"}],
   ";"}], "\n", 
 RowBox[{
  RowBox[{"probValue", " ", "=", " ", 
   RowBox[{"probSigma", "[", "2", "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"listk1", " ", "=", " ", 
   RowBox[{"Range", "[", 
    RowBox[{"0.5", ",", " ", "3", ",", " ", "0.1"}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{"listm1", " ", "=", " ", 
   RowBox[{"Range", "[", 
    RowBox[{"0.4", ",", " ", "6", ",", " ", "0.1"}], "]"}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"sol", "[", "0", "]"}], " ", "=", " ", 
    RowBox[{"{", 
     RowBox[{"arbitraryK", ",", " ", 
      RowBox[{"Last", " ", "@", " ", "listm1"}]}], "}"}]}], ";"}], " ", 
  RowBox[{"(*", 
   RowBox[{"Only", " ", "used", " ", "for", " ", "the", " ", "first", " ", 
    RowBox[{"step", "."}]}], "*)"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{"tab", "[", "nk1_", "]"}], " ", ":=", " ", 
   RowBox[{
    RowBox[{"tab", "[", "nk1", "]"}], " ", "=", " ", 
    RowBox[{"Block", "[", 
     RowBox[{
      RowBox[{"{", 
       RowBox[{
       "nm1Previous", ",", " ", "nm1Minimal", ",", " ", "listm1Relevant"}], 
       "}"}], ",", "\n", "  ", 
      RowBox[{
       RowBox[{"nm1Previous", " ", "=", " ", 
        RowBox[{
         RowBox[{"Position", "[", 
          RowBox[{"listm1", ",", " ", 
           RowBox[{"Last", "@", 
            RowBox[{"sol", "[", 
             RowBox[{"nk1", "-", "1"}], "]"}]}]}], "]"}], "[", 
         RowBox[{"[", 
          RowBox[{"1", ",", "1"}], "]"}], "]"}]}], ";", "\n", "  ", 
       RowBox[{"nm1Minimal", " ", "=", " ", 
        RowBox[{"If", "[", 
         RowBox[{
          RowBox[{
           RowBox[{"nm1Previous", " ", "-", " ", "10"}], " ", "<", " ", "1"}],
           ",", " ", "1", ",", " ", 
          RowBox[{"nm1Previous", " ", "-", " ", "10"}]}], "]"}]}], ";", "\n", 
       "  ", 
       RowBox[{"listm1Relevant", " ", "=", " ", 
        RowBox[{"listm1", " ", "//", " ", 
         RowBox[{
          RowBox[{"Take", "[", 
           RowBox[{"#", ",", " ", 
            RowBox[{"{", 
             RowBox[{"nm1Minimal", ",", " ", "nm1Previous"}], "}"}]}], "]"}], 
          " ", "&"}]}]}], ";", "\n", "  ", 
       RowBox[{"Table", "[", "\n", "    ", 
        RowBox[{
         RowBox[{"{", 
          RowBox[{
           RowBox[{"{", 
            RowBox[{
             RowBox[{"listk1", "[", 
              RowBox[{"[", "nk1", "]"}], "]"}], ",", " ", "m1"}], "}"}], ",", 
           " ", 
           RowBox[{"Abs", "[", 
            RowBox[{
             RowBox[{"probabilityMminApprox", "[", 
              RowBox[{"m1", ",", " ", 
               RowBox[{"k", " ", "->", " ", 
                RowBox[{"listk1", "[", 
                 RowBox[{"[", "nk1", "]"}], "]"}]}]}], "]"}], " ", "-", " ", 
             "probValue"}], "]"}]}], "}"}], " ", ",", " ", "\n", "    ", 
         RowBox[{"{", 
          RowBox[{"m1", ",", " ", "listm1Relevant"}], "}"}]}], "\n", "  ", 
        "]"}]}]}], "\n", "]"}]}]}], ";"}], "\n", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"sol", "[", "nk1_", "]"}], " ", ":=", " ", 
    RowBox[{
     RowBox[{"sol", "[", "nk1", "]"}], " ", "=", " ", 
     RowBox[{
      RowBox[{"tab", "[", "nk1", "]"}], " ", "//", " ", 
      RowBox[{
       RowBox[{
        RowBox[{"SortBy", "[", 
         RowBox[{"#", ",", " ", "Last"}], "]"}], "[", 
        RowBox[{"[", 
         RowBox[{"1", ",", "1"}], "]"}], "]"}], " ", "&"}]}]}]}], " ", 
   RowBox[{"(*", 
    RowBox[{"//", " ", "Echo"}], "*)"}], ";"}], "\n"}], "\n", 
 RowBox[{
  RowBox[{"solAll", " ", ":=", " ", 
   RowBox[{"solAll", " ", "=", " ", 
    RowBox[{"Monitor", "[", 
     RowBox[{
      RowBox[{"Table", "[", 
       RowBox[{
        RowBox[{"sol", "[", "nk1", "]"}], ",", " ", 
        RowBox[{"{", 
         RowBox[{"nk1", ",", " ", 
          RowBox[{"Length", " ", "@", " ", "listk1"}]}], "}"}]}], "]"}], ",", 
      " ", "nk1"}], "]"}]}]}], ";"}]}], "Code",
 CellChangeTimes->{{3.905611238513006*^9, 3.905611256252783*^9}, {
   3.9056113668113403`*^9, 3.905611383832735*^9}, {3.905611456949306*^9, 
   3.905611550254397*^9}, {3.905611864429225*^9, 3.905611906148295*^9}, {
   3.9056121051412287`*^9, 3.905612151434374*^9}, {3.905612199778463*^9, 
   3.90561221489856*^9}, {3.9056122475125427`*^9, 3.9056123145857773`*^9}, {
   3.9056123662557487`*^9, 3.905612367536484*^9}, {3.905612405905558*^9, 
   3.905612429609185*^9}, {3.9056124697363577`*^9, 3.9056124868954678`*^9}, {
   3.905612891633484*^9, 3.905612896954249*^9}, {3.9056129471049*^9, 
   3.905612957544634*^9}, {3.9056129947367983`*^9, 3.9056132058302193`*^9}, {
   3.905613246293309*^9, 3.905613249975971*^9}, {3.9056133044927998`*^9, 
   3.9056133111765223`*^9}, {3.905613343452026*^9, 3.9056134197945232`*^9}, {
   3.905613450338022*^9, 3.905613452487421*^9}, {3.905613494101008*^9, 
   3.905613519051817*^9}, {3.90561354932579*^9, 3.905613549978897*^9}, {
   3.905613613303297*^9, 3.9056137342070208`*^9}, {3.905614182849924*^9, 
   3.905614196034919*^9}, {3.905614267789156*^9, 3.905614273591136*^9}, {
   3.905614313533764*^9, 3.905614329354846*^9}, {3.905614416118466*^9, 
   3.905614423756351*^9}, {3.9056146759948797`*^9, 3.9056146767918167`*^9}, {
   3.9056151340913677`*^9, 3.90561517224046*^9}, {3.9056152118177557`*^9, 
   3.905615214091358*^9}, {3.905615252759769*^9, 3.905615263352913*^9}, {
   3.905615345649466*^9, 3.905615374468997*^9}, {3.90561548267632*^9, 
   3.9056154968400993`*^9}, {3.905615751779393*^9, 3.9056157664118233`*^9}, {
   3.905615811233103*^9, 3.905616009982396*^9}, {3.90561604412062*^9, 
   3.9056160546292677`*^9}, {3.905616112659197*^9, 3.905616119555298*^9}, {
   3.905616193525331*^9, 3.905616202376616*^9}, {3.90561623434896*^9, 
   3.9056162579100447`*^9}, {3.905616318600956*^9, 3.9056163637374067`*^9}, {
   3.905616627361327*^9, 3.905616789837139*^9}, {3.905616896195166*^9, 
   3.9056168966233473`*^9}, {3.905617118811655*^9, 3.9056171914875183`*^9}, {
   3.905617255363351*^9, 3.905617304087985*^9}, {3.90561733555258*^9, 
   3.905617338820792*^9}, {3.9056173954874687`*^9, 3.905617431360471*^9}, {
   3.9056175206109447`*^9, 3.9056175773333597`*^9}, {3.9056176532804728`*^9, 
   3.905617657144596*^9}, {3.905618619745846*^9, 3.905618723006199*^9}, {
   3.905619188188505*^9, 3.905619258342877*^9}, {3.905619426500511*^9, 
   3.9056194599498367`*^9}, {3.9056621613621407`*^9, 3.90566217616637*^9}, {
   3.905662630742077*^9, 3.90566263752293*^9}, 3.905662685759055*^9, {
   3.905662865977788*^9, 3.905662868535495*^9}, {3.905662959070191*^9, 
   3.905662982684004*^9}, 3.905663468719267*^9, {3.905663618298798*^9, 
   3.905663671271834*^9}, {3.9056637288181877`*^9, 3.9056637475049667`*^9}},
 CellLabel->
  "In[109]:=",ExpressionUUID->"a300557d-0576-4d1e-ac07-4182474e49fa"],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"solAll", " ", "//", " ", "EchoTiming"}]], "Code",
 CellChangeTimes->{{3.90566301908002*^9, 3.905663019932776*^9}, {
  3.905663848863998*^9, 3.905663850487421*^9}},
 CellLabel->
  "In[118]:=",ExpressionUUID->"3b98ed33-caa7-4931-8e5b-a66921090c62"],

Cell[BoxData["91.848281`"], "EchoTiming",
 CellChangeTimes->{
  3.905663942690344*^9},ExpressionUUID->"37790c5d-3af7-4c82-be1f-\
ae1bdc2a8d30"],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{"0.5`", ",", "5.800000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.6`", ",", "5.300000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.7`", ",", "4.9`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.8`", ",", "4.4`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"0.9`", ",", "4.1000000000000005`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.`", ",", "3.7`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.1`", ",", "3.4`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.2000000000000002`", ",", "3.1`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.3`", ",", "2.8000000000000003`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.4`", ",", "2.5`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.5`", ",", "2.3000000000000003`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.6`", ",", "2.1`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.7000000000000002`", ",", "1.9`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.8`", ",", "1.7000000000000002`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"1.9000000000000001`", ",", "1.5`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.`", ",", "1.4`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.1`", ",", "1.3`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.2`", ",", "1.1`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.3`", ",", "1.`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.4000000000000004`", ",", "0.9`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.5`", ",", "0.8`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.6`", ",", "0.8`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.7`", ",", "0.7000000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.8000000000000003`", ",", "0.6000000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2.9000000000000004`", ",", "0.6000000000000001`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"3.`", ",", "0.5`"}], "}"}]}], "}"}]], "Output",
 CellChangeTimes->{3.905663089577956*^9, 3.905663942701581*^9},
 CellLabel->
  "Out[118]=",ExpressionUUID->"dc454fae-fb30-42ed-8c2d-593efad7d540"]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"solAllI", " ", "=", " ", 
   RowBox[{"Interpolation", "[", 
    RowBox[{"solAll", ",", " ", 
     RowBox[{"InterpolationOrder", "->", "2"}]}], "]"}]}], ";"}], "\n", 
 RowBox[{"Show", "[", 
  RowBox[{
   RowBox[{"ListPlot", "[", "solAll", "]"}], ",", " ", 
   RowBox[{"Plot", "[", 
    RowBox[{
     RowBox[{"solAllI", "[", "k", "]"}], ",", " ", 
     RowBox[{"{", 
      RowBox[{"k", ",", " ", "0.5", ",", " ", "3"}], "}"}], ",", " ", 
     RowBox[{"PlotStyle", "->", "Red"}]}], "]"}], ",", " ", 
   GraphicsBox[{{{}, 
      InterpretationBox[{
        TagBox[{{}, {}, 
          TagBox[
           {RGBColor[0.368417, 0.506779, 0.709798], PointSize[
            0.009166666666666668], AbsoluteThickness[2], 
            LineBox[CompressedData["
1:eJxdlWtSIkEMgHuGx+BzQXzU/twzyP+eA/jLI1il/NwreA28htdgPYMPZFlF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             "]]},
           Annotation[#, "Charting`Private`Tag#1"]& ]},
         {
         "WolframDynamicHighlight", <|
          "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>}], 
        DynamicBox[(Charting`HighlightActionBox["DynamicHighlight", {}, 
          Slot["HighlightElements"], 
          Slot["LayoutOptions"], 
          Slot["Meta"], 
          Charting`HighlightActionFunction["DynamicHighlight", {{{}, {}, 
             Annotation[{
               Hue[0.67, 0.6, 0.6], 
               Directive[
                PointSize[0.009166666666666668], 
                RGBColor[0.368417, 0.506779, 0.709798], 
                AbsoluteThickness[2]], 
               Line[CompressedData["
1:eJxdlWtSIkEMgHuGx+BzQXzU/twzyP+eA/jLI1il/NwreA28htdgPYMPZFlF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                "]]}, "Charting`Private`Tag#1"]}}, <|
           "HighlightElements" -> <|
             "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>, 
            "LayoutOptions" -> <|
             "PlotRange" -> {{0.4479166666666679, 3.}, {0, 5.775}}, 
              "Frame" -> {{False, False}, {False, False}}, 
              "AxesOrigin" -> {0.4479166666666679, 0}, 
              "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
              "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
              "DefaultStyle" -> {
                Directive[
                 PointSize[0.009166666666666668], 
                 RGBColor[0.368417, 0.506779, 0.709798], 
                 AbsoluteThickness[2]]}, 
              "HighlightLabelingFunctions" -> <|
               "CoordinatesToolOptions" -> ({
                  Identity[
                   Part[#, 1]], 
                  Identity[
                   Part[#, 2]]}& ), 
                "ScalingFunctions" -> {{Identity, Identity}, {
                  Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> 
              False|>, 
            "Meta" -> <|
             "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, 
              "Function" -> ListPlot, "GroupHighlight" -> False|>|>]]& )[<|
          "HighlightElements" -> <|
            "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>, 
           "LayoutOptions" -> <|
            "PlotRange" -> {{0.4479166666666679, 3.}, {0, 5.775}}, 
             "Frame" -> {{False, False}, {False, False}}, 
             "AxesOrigin" -> {0.4479166666666679, 0}, 
             "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
             "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
             "DefaultStyle" -> {
               Directive[
                PointSize[0.009166666666666668], 
                RGBColor[0.368417, 0.506779, 0.709798], 
                AbsoluteThickness[2]]}, 
             "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
                 Identity[
                  Part[#, 1]], 
                 Identity[
                  Part[#, 2]]}& ), 
               "ScalingFunctions" -> {{Identity, Identity}, {
                 Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> 
             False|>, 
           "Meta" -> <|
            "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, 
             "Function" -> ListPlot, "GroupHighlight" -> False|>|>],
         ImageSizeCache->{{4.503599627370496*^15, -4.503599627370496*^15}, {
          4.503599627370496*^15, -4.503599627370496*^15}}]},
       Annotation[{{{}, {}, 
          Annotation[{
            Hue[0.67, 0.6, 0.6], 
            Directive[
             PointSize[0.009166666666666668], 
             RGBColor[0.368417, 0.506779, 0.709798], 
             AbsoluteThickness[2]], 
            Line[CompressedData["
1:eJxdlWtSIkEMgHuGx+BzQXzU/twzyP+eA/jLI1il/NwreA28htdgPYMPZFlF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             "]]}, "Charting`Private`Tag#1"]}}, <|
        "HighlightElements" -> <|
          "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>, 
         "LayoutOptions" -> <|
          "PlotRange" -> {{0.4479166666666679, 3.}, {0, 5.775}}, 
           "Frame" -> {{False, False}, {False, False}}, 
           "AxesOrigin" -> {0.4479166666666679, 0}, 
           "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
           "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
           "DefaultStyle" -> {
             Directive[
              PointSize[0.009166666666666668], 
              RGBColor[0.368417, 0.506779, 0.709798], 
              AbsoluteThickness[2]]}, 
           "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
               Identity[
                Part[#, 1]], 
               Identity[
                Part[#, 2]]}& ), 
             "ScalingFunctions" -> {{Identity, Identity}, {
               Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> 
           False|>, 
         "Meta" -> <|
          "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
           ListPlot, "GroupHighlight" -> False|>|>, 
        "DynamicHighlight"]], {{}, {}}}, 
     InterpretationBox[{
       TagBox[{{{}, {}, 
          TagBox[
           {RGBColor[0.368417, 0.506779, 0.709798], AbsoluteThickness[2], 
            Opacity[1.], Dashing[{Small, Small}], LineBox[CompressedData["
1:eJxTTMoPSmViYGAwAWIQPbcuic0wpduOAQIc2G8/Un8rv9Mexl94an7ha/mT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             "]]},
           Annotation[#, "Charting`Private`Tag#1"]& ]}, {}},
        {"WolframDynamicHighlight", <|
         "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>}], 
       DynamicBox[(Charting`HighlightActionBox["DynamicHighlight", {}, 
         Slot["HighlightElements"], 
         Slot["LayoutOptions"], 
         Slot["Meta"], 
         Charting`HighlightActionFunction["DynamicHighlight", {{{{}, {}, 
             Annotation[{
               Directive[
                Opacity[1.], 
                RGBColor[0.368417, 0.506779, 0.709798], 
                AbsoluteThickness[2], 
                Dashing[{Small, Small}]], 
               Line[CompressedData["
1:eJxTTMoPSmViYGAwAWIQPbcuic0wpduOAQIc2G8/Un8rv9Mexl94an7ha/mT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                "]]}, "Charting`Private`Tag#1"]}}, {}}, <|
          "HighlightElements" -> <|
            "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
           "LayoutOptions" -> <|
            "PlotRange" -> {{0, 10}, {0., 4.}}, 
             "Frame" -> {{False, False}, {False, False}}, 
             "AxesOrigin" -> {0, 0}, "ImageSize" -> {360, 360/GoldenRatio}, 
             "Axes" -> {True, True}, "LabelStyle" -> {}, "AspectRatio" -> 
             GoldenRatio^(-1), "DefaultStyle" -> {
               Directive[
                Opacity[1.], 
                RGBColor[0.368417, 0.506779, 0.709798], 
                AbsoluteThickness[2], 
                Dashing[{Small, Small}]]}, 
             "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
                 Identity[
                  Part[#, 1]], 
                 Identity[
                  Part[#, 2]]}& ), 
               "ScalingFunctions" -> {{Identity, Identity}, {
                 Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> 
             False|>, 
           "Meta" -> <|
            "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, 
             "Function" -> Plot, "GroupHighlight" -> False|>|>]]& )[<|
         "HighlightElements" -> <|
           "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
          "LayoutOptions" -> <|
           "PlotRange" -> {{0, 10}, {0., 4.}}, 
            "Frame" -> {{False, False}, {False, False}}, 
            "AxesOrigin" -> {0, 0}, "ImageSize" -> {360, 360/GoldenRatio}, 
            "Axes" -> {True, True}, "LabelStyle" -> {}, "AspectRatio" -> 
            GoldenRatio^(-1), "DefaultStyle" -> {
              Directive[
               Opacity[1.], 
               RGBColor[0.368417, 0.506779, 0.709798], 
               AbsoluteThickness[2], 
               Dashing[{Small, Small}]]}, 
            "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
                Identity[
                 Part[#, 1]], 
                Identity[
                 Part[#, 2]]}& ), 
              "ScalingFunctions" -> {{Identity, Identity}, {
                Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> 
            False|>, 
          "Meta" -> <|
           "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
            Plot, "GroupHighlight" -> False|>|>],
        ImageSizeCache->{{4.503599627370496*^15, -4.503599627370496*^15}, {
         4.503599627370496*^15, -4.503599627370496*^15}}]},
      Annotation[{{{{}, {}, 
          Annotation[{
            Directive[
             Opacity[1.], 
             RGBColor[0.368417, 0.506779, 0.709798], 
             AbsoluteThickness[2], 
             Dashing[{Small, Small}]], 
            Line[CompressedData["
1:eJxTTMoPSmViYGAwAWIQPbcuic0wpduOAQIc2G8/Un8rv9Mexl94an7ha/mT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             "]]}, "Charting`Private`Tag#1"]}}, {}}, <|
       "HighlightElements" -> <|
         "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
        "LayoutOptions" -> <|
         "PlotRange" -> {{0, 10}, {0., 4.}}, 
          "Frame" -> {{False, False}, {False, False}}, "AxesOrigin" -> {0, 0},
           "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
          "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
          "DefaultStyle" -> {
            Directive[
             Opacity[1.], 
             RGBColor[0.368417, 0.506779, 0.709798], 
             AbsoluteThickness[2], 
             Dashing[{Small, Small}]]}, 
          "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
              Identity[
               Part[#, 1]], 
              Identity[
               Part[#, 2]]}& ), 
            "ScalingFunctions" -> {{Identity, Identity}, {
              Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> False|>,
         "Meta" -> <|
         "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
          Plot, "GroupHighlight" -> False|>|>, "DynamicHighlight"]]},
    AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
    Axes->{True, True},
    AxesLabel->{None, None},
    AxesOrigin->{0.4479166666666679, 0},
    DisplayFunction->Identity,
    Frame->{{False, False}, {False, False}},
    FrameLabel->{{None, None}, {None, None}},
    FrameTicks->{{Automatic, Automatic}, {Automatic, Automatic}},
    GridLines->{None, None},
    GridLinesStyle->Directive[
      GrayLevel[0.5, 0.4]],
    Method->{
     "AxisPadding" -> Scaled[0.02], "DefaultBoundaryStyle" -> Automatic, 
      "DefaultGraphicsInteraction" -> {
       "Version" -> 1.2, "TrackMousePosition" -> {True, False}, 
        "Effects" -> {
         "Highlight" -> {"ratio" -> 2}, "HighlightPoint" -> {"ratio" -> 2}, 
          "Droplines" -> {
           "freeformCursorMode" -> True, 
            "placement" -> {"x" -> "All", "y" -> "None"}}}}, 
      "DefaultMeshStyle" -> AbsolutePointSize[6], "DefaultPlotStyle" -> {
        Directive[
         RGBColor[0.368417, 0.506779, 0.709798], 
         AbsoluteThickness[2]], 
        Directive[
         RGBColor[0.880722, 0.611041, 0.142051], 
         AbsoluteThickness[2]], 
        Directive[
         RGBColor[0.560181, 0.691569, 0.194885], 
         AbsoluteThickness[2]], 
        Directive[
         RGBColor[0.922526, 0.385626, 0.209179], 
         AbsoluteThickness[2]], 
        Directive[
         RGBColor[0.528488, 0.470624, 0.701351], 
         AbsoluteThickness[2]], 
        Directive[
         RGBColor[0.772079, 0.431554, 0.102387], 
         AbsoluteThickness[2]], 
        Directive[
         RGBColor[0.363898, 0.618501, 0.782349], 
         AbsoluteThickness[2]], 
        Directive[
         RGBColor[1, 0.75, 0], 
         AbsoluteThickness[2]], 
        Directive[
         RGBColor[0.647624, 0.37816, 0.614037], 
         AbsoluteThickness[2]], 
        Directive[
         RGBColor[0.571589, 0.586483, 0.], 
         AbsoluteThickness[2]], 
        Directive[
         RGBColor[0.915, 0.3325, 0.2125], 
         AbsoluteThickness[2]], 
        Directive[
         RGBColor[0.40082222609352647`, 0.5220066643438841, 0.85], 
         AbsoluteThickness[2]], 
        Directive[
         RGBColor[0.9728288904374106, 0.621644452187053, 0.07336199581899142], 
         AbsoluteThickness[2]], 
        Directive[
         RGBColor[0.736782672705901, 0.358, 0.5030266573755369], 
         AbsoluteThickness[2]], 
        Directive[
         RGBColor[0.28026441037696703`, 0.715, 0.4292089322474965], 
         AbsoluteThickness[2]]}, "DomainPadding" -> Scaled[0.02], 
      "PointSizeFunction" -> "SmallPointSize", "RangePadding" -> Scaled[0.05],
       "OptimizePlotMarkers" -> True, "IncludeHighlighting" -> "CurrentSet", 
      "HighlightStyle" -> Automatic, "OptimizePlotMarkers" -> True, 
      "CoordinatesToolOptions" -> {"DisplayFunction" -> ({
          Identity[
           Part[#, 1]], 
          Identity[
           Part[#, 2]]}& ), "CopiedValueFunction" -> ({
          Identity[
           Part[#, 1]], 
          Identity[
           Part[#, 2]]}& )}},
    PlotRange->{{0.4479166666666679, 3.}, {0, 5.775}},
    PlotRangeClipping->True,
    PlotRangePadding->{{
       Scaled[0.02], 
       Scaled[0.02]}, {
       Scaled[0.02], 
       Scaled[0.05]}},
    Ticks->{Automatic, Automatic}]}], " ", "]"}]}], "Code",
 CellChangeTimes->{{3.905664016322147*^9, 
  3.905664017063108*^9}},ExpressionUUID->"337a4a2e-f53c-423a-b841-\
887c41d71752"],

Cell[BoxData[
 GraphicsBox[{{{}, 
    InterpretationBox[{
      TagBox[
       TagBox[
        {RGBColor[0.368417, 0.506779, 0.709798], PointSize[
         0.012833333333333334`], AbsoluteThickness[2], 
         PointBox[CompressedData["
1:eJxTTMoPSmViYGCQAmIQDQEP7E2MQUDcAUwZP4byRR3SwOCZ/ayZICDsAKFf
QvmCDmfPgMAb+3SwOgEHiHkfoPK8UPUf7SHmcjtAzP1sD9HHAdX/BaqfDWrf
N3uIOSxQ835A5Zmg5v2E6meAmvfbHqLvH1T8jz1MPB0qDjMH6mG4PTBzYO6A
mM8Id3ca1F6YvyDmMsP9DXMnLFwg4ixo4cTqkA4NR5g/TVDCmR3Oh5jH4QCL
FwALE6SW
          "]]},
        Annotation[#, "Charting`Private`Tag#1"]& ],
       {"WolframDynamicHighlight", <|
        "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>}], 
      DynamicBox[(Charting`HighlightActionBox["DynamicHighlight", {}, 
        Slot["HighlightElements"], 
        Slot["LayoutOptions"], 
        Slot["Meta"], 
        Charting`HighlightActionFunction["DynamicHighlight", {{
           Annotation[{
             Directive[
              PointSize[0.012833333333333334`], 
              RGBColor[0.368417, 0.506779, 0.709798], 
              AbsoluteThickness[2]], 
             Point[CompressedData["
1:eJxTTMoPSmViYGCQAmIQDQEP7E2MQUDcAUwZP4byRR3SwOCZ/ayZICDsAKFf
QvmCDmfPgMAb+3SwOgEHiHkfoPK8UPUf7SHmcjtAzP1sD9HHAdX/BaqfDWrf
N3uIOSxQ835A5Zmg5v2E6meAmvfbHqLvH1T8jz1MPB0qDjMH6mG4PTBzYO6A
mM8Id3ca1F6YvyDmMsP9DXMnLFwg4ixo4cTqkA4NR5g/TVDCmR3Oh5jH4QCL
FwALE6SW
              "]]}, "Charting`Private`Tag#1"]}}, <|
         "HighlightElements" -> <|
           "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>, 
          "LayoutOptions" -> <|
           "PlotRange" -> {{0, 3.}, {0, 5.800000000000001}}, 
            "Frame" -> {{False, False}, {False, False}}, 
            "AxesOrigin" -> {0, 0}, "ImageSize" -> {360, 360/GoldenRatio}, 
            "Axes" -> {True, True}, "LabelStyle" -> {}, "AspectRatio" -> 
            GoldenRatio^(-1), "DefaultStyle" -> {
              Directive[
               PointSize[0.012833333333333334`], 
               RGBColor[0.368417, 0.506779, 0.709798], 
               AbsoluteThickness[2]]}, 
            "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
                Identity[
                 Part[#, 1]], 
                Identity[
                 Part[#, 2]]}& ), 
              "ScalingFunctions" -> {{Identity, Identity}, {
                Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> 
            False|>, 
          "Meta" -> <|
           "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
            ListPlot, "GroupHighlight" -> False|>|>]]& )[<|
        "HighlightElements" -> <|
          "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>, 
         "LayoutOptions" -> <|
          "PlotRange" -> {{0, 3.}, {0, 5.800000000000001}}, 
           "Frame" -> {{False, False}, {False, False}}, 
           "AxesOrigin" -> {0, 0}, "ImageSize" -> {360, 360/GoldenRatio}, 
           "Axes" -> {True, True}, "LabelStyle" -> {}, "AspectRatio" -> 
           GoldenRatio^(-1), "DefaultStyle" -> {
             Directive[
              PointSize[0.012833333333333334`], 
              RGBColor[0.368417, 0.506779, 0.709798], 
              AbsoluteThickness[2]]}, 
           "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
               Identity[
                Part[#, 1]], 
               Identity[
                Part[#, 2]]}& ), 
             "ScalingFunctions" -> {{Identity, Identity}, {
               Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> 
           False|>, 
         "Meta" -> <|
          "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
           ListPlot, "GroupHighlight" -> False|>|>],
       ImageSizeCache->{{4.503599627370496*^15, -4.503599627370496*^15}, {
        4.503599627370496*^15, -4.503599627370496*^15}}]},
     Annotation[{{
        Annotation[{
          Directive[
           PointSize[0.012833333333333334`], 
           RGBColor[0.368417, 0.506779, 0.709798], 
           AbsoluteThickness[2]], 
          Point[CompressedData["
1:eJxTTMoPSmViYGCQAmIQDQEP7E2MQUDcAUwZP4byRR3SwOCZ/ayZICDsAKFf
QvmCDmfPgMAb+3SwOgEHiHkfoPK8UPUf7SHmcjtAzP1sD9HHAdX/BaqfDWrf
N3uIOSxQ835A5Zmg5v2E6meAmvfbHqLvH1T8jz1MPB0qDjMH6mG4PTBzYO6A
mM8Id3ca1F6YvyDmMsP9DXMnLFwg4ixo4cTqkA4NR5g/TVDCmR3Oh5jH4QCL
FwALE6SW
           "]]}, "Charting`Private`Tag#1"]}}, <|
      "HighlightElements" -> <|
        "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>, 
       "LayoutOptions" -> <|
        "PlotRange" -> {{0, 3.}, {0, 5.800000000000001}}, 
         "Frame" -> {{False, False}, {False, False}}, "AxesOrigin" -> {0, 0}, 
         "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
         "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
         "DefaultStyle" -> {
           Directive[
            PointSize[0.012833333333333334`], 
            RGBColor[0.368417, 0.506779, 0.709798], 
            AbsoluteThickness[2]]}, 
         "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
             Identity[
              Part[#, 1]], 
             Identity[
              Part[#, 2]]}& ), 
           "ScalingFunctions" -> {{Identity, Identity}, {
             Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> False|>, 
       "Meta" -> <|
        "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
         ListPlot, "GroupHighlight" -> False|>|>, 
      "DynamicHighlight"]], {{}, {}}}, 
   InterpretationBox[{
     TagBox[{{{}, {}, 
        TagBox[
         {RGBColor[1, 0, 0], AbsoluteThickness[2], Opacity[1.], 
          LineBox[CompressedData["
1:eJwVmnk8VO8Xx2fMnTsl2ZeSRFS2lD0q55CkkCVFkpAQRdYk7aLNkkqWoqRV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           "]]},
         Annotation[#, "Charting`Private`Tag#1"]& ]}, {}},
      {"WolframDynamicHighlight", <|
       "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>}], 
     DynamicBox[(Charting`HighlightActionBox["DynamicHighlight", {}, 
       Slot["HighlightElements"], 
       Slot["LayoutOptions"], 
       Slot["Meta"], 
       Charting`HighlightActionFunction["DynamicHighlight", {{{{}, {}, 
           Annotation[{
             Directive[
              Opacity[1.], 
              AbsoluteThickness[2], 
              RGBColor[1, 0, 0]], 
             Line[CompressedData["
1:eJwVmnk8VO8Xx2fMnTsl2ZeSRFS2lD0q55CkkCVFkpAQRdYk7aLNkkqWoqRV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              "]]}, "Charting`Private`Tag#1"]}}, {}}, <|
        "HighlightElements" -> <|
          "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
         "LayoutOptions" -> <|
          "PlotRange" -> {{0.5, 3}, {0., 5.799999719387769}}, 
           "Frame" -> {{False, False}, {False, False}}, 
           "AxesOrigin" -> {0.5000000000000011, 0}, 
           "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
           "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
           "DefaultStyle" -> {
             Directive[
              Opacity[1.], 
              AbsoluteThickness[2], 
              RGBColor[1, 0, 0]]}, 
           "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
               Identity[
                Part[#, 1]], 
               Identity[
                Part[#, 2]]}& ), 
             "ScalingFunctions" -> {{Identity, Identity}, {
               Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> 
           False|>, 
         "Meta" -> <|
          "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
           Plot, "GroupHighlight" -> False|>|>]]& )[<|
       "HighlightElements" -> <|
         "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
        "LayoutOptions" -> <|
         "PlotRange" -> {{0.5, 3}, {0., 5.799999719387769}}, 
          "Frame" -> {{False, False}, {False, False}}, 
          "AxesOrigin" -> {0.5000000000000011, 0}, 
          "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
          "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
          "DefaultStyle" -> {
            Directive[
             Opacity[1.], 
             AbsoluteThickness[2], 
             RGBColor[1, 0, 0]]}, 
          "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
              Identity[
               Part[#, 1]], 
              Identity[
               Part[#, 2]]}& ), 
            "ScalingFunctions" -> {{Identity, Identity}, {
              Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> False|>,
         "Meta" -> <|
         "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
          Plot, "GroupHighlight" -> False|>|>],
      ImageSizeCache->{{4.503599627370496*^15, -4.503599627370496*^15}, {
       4.503599627370496*^15, -4.503599627370496*^15}}]},
    Annotation[{{{{}, {}, 
        Annotation[{
          Directive[
           Opacity[1.], 
           AbsoluteThickness[2], 
           RGBColor[1, 0, 0]], 
          Line[CompressedData["
1:eJwVmnk8VO8Xx2fMnTsl2ZeSRFS2lD0q55CkkCVFkpAQRdYk7aLNkkqWoqRV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           "]]}, "Charting`Private`Tag#1"]}}, {}}, <|
     "HighlightElements" -> <|
       "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
      "LayoutOptions" -> <|
       "PlotRange" -> {{0.5, 3}, {0., 5.799999719387769}}, 
        "Frame" -> {{False, False}, {False, False}}, 
        "AxesOrigin" -> {0.5000000000000011, 0}, 
        "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
        "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), "DefaultStyle" -> {
          Directive[
           Opacity[1.], 
           AbsoluteThickness[2], 
           RGBColor[1, 0, 0]]}, 
        "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
            Identity[
             Part[#, 1]], 
            Identity[
             Part[#, 2]]}& ), 
          "ScalingFunctions" -> {{Identity, Identity}, {
            Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> False|>, 
      "Meta" -> <|
       "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
        Plot, "GroupHighlight" -> False|>|>, "DynamicHighlight"]], {{{}, 
     InterpretationBox[{
       TagBox[{{}, {}, 
         TagBox[
          {RGBColor[0.368417, 0.506779, 0.709798], PointSize[
           0.009166666666666668], AbsoluteThickness[2], 
           LineBox[CompressedData["
1:eJxdlWtSIkEMgHuGx+BzQXzU/twzyP+eA/jLI1il/NwreA28htdgPYMPZFlF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            "]]},
          Annotation[#, "Charting`Private`Tag#1"]& ]},
        {"WolframDynamicHighlight", <|
         "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>}], 
       DynamicBox[(Charting`HighlightActionBox["DynamicHighlight", {}, 
         Slot["HighlightElements"], 
         Slot["LayoutOptions"], 
         Slot["Meta"], 
         Charting`HighlightActionFunction["DynamicHighlight", {{{}, {}, 
            Annotation[{
              Hue[0.67, 0.6, 0.6], 
              Directive[
               PointSize[0.009166666666666668], 
               RGBColor[0.368417, 0.506779, 0.709798], 
               AbsoluteThickness[2]], 
              Line[CompressedData["
1:eJxdlWtSIkEMgHuGx+BzQXzU/twzyP+eA/jLI1il/NwreA28htdgPYMPZFlF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               "]]}, "Charting`Private`Tag#1"]}}, <|
          "HighlightElements" -> <|
            "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>, 
           "LayoutOptions" -> <|
            "PlotRange" -> {{0.4479166666666679, 3.}, {0, 5.775}}, 
             "Frame" -> {{False, False}, {False, False}}, 
             "AxesOrigin" -> {0.4479166666666679, 0}, 
             "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
             "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
             "DefaultStyle" -> {
               Directive[
                PointSize[0.009166666666666668], 
                RGBColor[0.368417, 0.506779, 0.709798], 
                AbsoluteThickness[2]]}, 
             "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
                 Identity[
                  Part[#, 1]], 
                 Identity[
                  Part[#, 2]]}& ), 
               "ScalingFunctions" -> {{Identity, Identity}, {
                 Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> 
             False|>, 
           "Meta" -> <|
            "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, 
             "Function" -> ListPlot, "GroupHighlight" -> False|>|>]]& )[<|
         "HighlightElements" -> <|
           "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>, 
          "LayoutOptions" -> <|
           "PlotRange" -> {{0.4479166666666679, 3.}, {0, 5.775}}, 
            "Frame" -> {{False, False}, {False, False}}, 
            "AxesOrigin" -> {0.4479166666666679, 0}, 
            "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
            "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
            "DefaultStyle" -> {
              Directive[
               PointSize[0.009166666666666668], 
               RGBColor[0.368417, 0.506779, 0.709798], 
               AbsoluteThickness[2]]}, 
            "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
                Identity[
                 Part[#, 1]], 
                Identity[
                 Part[#, 2]]}& ), 
              "ScalingFunctions" -> {{Identity, Identity}, {
                Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> 
            False|>, 
          "Meta" -> <|
           "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
            ListPlot, "GroupHighlight" -> False|>|>],
        ImageSizeCache->{{4.503599627370496*^15, -4.503599627370496*^15}, {
         4.503599627370496*^15, -4.503599627370496*^15}}]},
      Annotation[{{{}, {}, 
         Annotation[{
           Hue[0.67, 0.6, 0.6], 
           Directive[
            PointSize[0.009166666666666668], 
            RGBColor[0.368417, 0.506779, 0.709798], 
            AbsoluteThickness[2]], 
           Line[CompressedData["
1:eJxdlWtSIkEMgHuGx+BzQXzU/twzyP+eA/jLI1il/NwreA28htdgPYMPZFlF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            "]]}, "Charting`Private`Tag#1"]}}, <|
       "HighlightElements" -> <|
         "Label" -> {"XYLabel"}, "Ball" -> {"IndicatedBall"}|>, 
        "LayoutOptions" -> <|
         "PlotRange" -> {{0.4479166666666679, 3.}, {0, 5.775}}, 
          "Frame" -> {{False, False}, {False, False}}, 
          "AxesOrigin" -> {0.4479166666666679, 0}, 
          "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
          "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
          "DefaultStyle" -> {
            Directive[
             PointSize[0.009166666666666668], 
             RGBColor[0.368417, 0.506779, 0.709798], 
             AbsoluteThickness[2]]}, 
          "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
              Identity[
               Part[#, 1]], 
              Identity[
               Part[#, 2]]}& ), 
            "ScalingFunctions" -> {{Identity, Identity}, {
              Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> False|>,
         "Meta" -> <|
         "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
          ListPlot, "GroupHighlight" -> False|>|>, 
       "DynamicHighlight"]], {{}, {}}}, 
    InterpretationBox[{
      TagBox[{{{}, {}, 
         TagBox[
          {RGBColor[0.368417, 0.506779, 0.709798], AbsoluteThickness[2], 
           Opacity[1.], Dashing[{Small, Small}], LineBox[CompressedData["
1:eJxTTMoPSmViYGAwAWIQPbcuic0wpduOAQIc2G8/Un8rv9Mexl94an7ha/mT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            "]]},
          Annotation[#, "Charting`Private`Tag#1"]& ]}, {}},
       {"WolframDynamicHighlight", <|
        "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>}], 
      DynamicBox[(Charting`HighlightActionBox["DynamicHighlight", {}, 
        Slot["HighlightElements"], 
        Slot["LayoutOptions"], 
        Slot["Meta"], 
        Charting`HighlightActionFunction["DynamicHighlight", {{{{}, {}, 
            Annotation[{
              Directive[
               Opacity[1.], 
               RGBColor[0.368417, 0.506779, 0.709798], 
               AbsoluteThickness[2], 
               Dashing[{Small, Small}]], 
              Line[CompressedData["
1:eJxTTMoPSmViYGAwAWIQPbcuic0wpduOAQIc2G8/Un8rv9Mexl94an7ha/mT
cP669Z23c/Ruwfnp9hdnvil6DOfnPdV8vGXdSzifS7FF/b7FBzi/T+C01sKE
z3B+0u2Q/cxnvsH5hUdbkvLVf8H5Gwt4giU8/yLcU539yiCcwQHGb5r/J/DL
G0Y4n+HyA4c9VcxwvlpJWkWIFiuc/+Tr9DDuvWxwvtfTrNpJhRxwvt+TCdpy
clxw/qvDSQ0n1nLD+XqC12Sd43nhfC77r4l3PvPB+e5vo74rhQrA+TcOpTBG
6QjC+Vs7jsQpfEXw01hLH5w7JwTnJxdVb+WZJQzn66drn/NJFIHzzwvpcJda
isL5u9c1zdZhFoPzqxm1As7cRfC57lR55G0Rh/OfLlOcMr9GAs6foiHJsjNU
Es6fMCvteKKCFJwfNSX2HM9zBP+Hy9Kf8/dJw/mPnzpVHGqXgfMX2RpKn02U
hfPXtpYKpuvKwfntocnezF8RfNM7C1e2n5WH82dozl571lsBzq8/0DvDeyeC
7ysduvSUiiKc75h3PFqwE8GfL5OkcuYrgq9yePk0v2glhP90D2ld2ofgp31m
uXhSSxnOT9r4SaGzH8GfcImn98hxBH/fZ7Wf//8j+AAJ58LO
               "]]}, "Charting`Private`Tag#1"]}}, {}}, <|
         "HighlightElements" -> <|
           "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
          "LayoutOptions" -> <|
           "PlotRange" -> {{0, 10}, {0., 4.}}, 
            "Frame" -> {{False, False}, {False, False}}, 
            "AxesOrigin" -> {0, 0}, "ImageSize" -> {360, 360/GoldenRatio}, 
            "Axes" -> {True, True}, "LabelStyle" -> {}, "AspectRatio" -> 
            GoldenRatio^(-1), "DefaultStyle" -> {
              Directive[
               Opacity[1.], 
               RGBColor[0.368417, 0.506779, 0.709798], 
               AbsoluteThickness[2], 
               Dashing[{Small, Small}]]}, 
            "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
                Identity[
                 Part[#, 1]], 
                Identity[
                 Part[#, 2]]}& ), 
              "ScalingFunctions" -> {{Identity, Identity}, {
                Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> 
            False|>, 
          "Meta" -> <|
           "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
            Plot, "GroupHighlight" -> False|>|>]]& )[<|
        "HighlightElements" -> <|
          "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
         "LayoutOptions" -> <|
          "PlotRange" -> {{0, 10}, {0., 4.}}, 
           "Frame" -> {{False, False}, {False, False}}, 
           "AxesOrigin" -> {0, 0}, "ImageSize" -> {360, 360/GoldenRatio}, 
           "Axes" -> {True, True}, "LabelStyle" -> {}, "AspectRatio" -> 
           GoldenRatio^(-1), "DefaultStyle" -> {
             Directive[
              Opacity[1.], 
              RGBColor[0.368417, 0.506779, 0.709798], 
              AbsoluteThickness[2], 
              Dashing[{Small, Small}]]}, 
           "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
               Identity[
                Part[#, 1]], 
               Identity[
                Part[#, 2]]}& ), 
             "ScalingFunctions" -> {{Identity, Identity}, {
               Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> 
           False|>, 
         "Meta" -> <|
          "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
           Plot, "GroupHighlight" -> False|>|>],
       ImageSizeCache->{{4.503599627370496*^15, -4.503599627370496*^15}, {
        4.503599627370496*^15, -4.503599627370496*^15}}]},
     Annotation[{{{{}, {}, 
         Annotation[{
           Directive[
            Opacity[1.], 
            RGBColor[0.368417, 0.506779, 0.709798], 
            AbsoluteThickness[2], 
            Dashing[{Small, Small}]], 
           Line[CompressedData["
1:eJxTTMoPSmViYGAwAWIQPbcuic0wpduOAQIc2G8/Un8rv9Mexl94an7ha/mT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            "]]}, "Charting`Private`Tag#1"]}}, {}}, <|
      "HighlightElements" -> <|
        "Label" -> {"XYLabel"}, "Ball" -> {"InterpolatedBall"}|>, 
       "LayoutOptions" -> <|
        "PlotRange" -> {{0, 10}, {0., 4.}}, 
         "Frame" -> {{False, False}, {False, False}}, "AxesOrigin" -> {0, 0}, 
         "ImageSize" -> {360, 360/GoldenRatio}, "Axes" -> {True, True}, 
         "LabelStyle" -> {}, "AspectRatio" -> GoldenRatio^(-1), 
         "DefaultStyle" -> {
           Directive[
            Opacity[1.], 
            RGBColor[0.368417, 0.506779, 0.709798], 
            AbsoluteThickness[2], 
            Dashing[{Small, Small}]]}, 
         "HighlightLabelingFunctions" -> <|"CoordinatesToolOptions" -> ({
             Identity[
              Part[#, 1]], 
             Identity[
              Part[#, 2]]}& ), 
           "ScalingFunctions" -> {{Identity, Identity}, {
             Identity, Identity}}|>, "Primitives" -> {}, "GCFlag" -> False|>, 
       "Meta" -> <|
        "DefaultHighlight" -> {"Dynamic", None}, "Index" -> {}, "Function" -> 
         Plot, "GroupHighlight" -> False|>|>, "DynamicHighlight"]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->{True, True},
  AxesLabel->{None, None},
  AxesOrigin->{0, 0},
  DisplayFunction->Identity,
  Frame->{{False, False}, {False, False}},
  FrameLabel->{{None, None}, {None, None}},
  FrameTicks->{{Automatic, Automatic}, {Automatic, Automatic}},
  GridLines->{None, None},
  GridLinesStyle->Directive[
    GrayLevel[0.5, 0.4]],
  ImageSize->{407.9084065755201, Automatic},
  Method->{
   "AxisPadding" -> Scaled[0.02], "DefaultBoundaryStyle" -> Automatic, 
    "DefaultGraphicsInteraction" -> {
     "Version" -> 1.2, "TrackMousePosition" -> {True, False}, 
      "Effects" -> {
       "Highlight" -> {"ratio" -> 2}, "HighlightPoint" -> {"ratio" -> 2}, 
        "Droplines" -> {
         "freeformCursorMode" -> True, 
          "placement" -> {"x" -> "All", "y" -> "None"}}}}, "DefaultMeshStyle" -> 
    AbsolutePointSize[6], "DefaultPlotStyle" -> {
      Directive[
       RGBColor[0.368417, 0.506779, 0.709798], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.880722, 0.611041, 0.142051], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.560181, 0.691569, 0.194885], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.922526, 0.385626, 0.209179], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.528488, 0.470624, 0.701351], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.772079, 0.431554, 0.102387], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.363898, 0.618501, 0.782349], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[1, 0.75, 0], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.647624, 0.37816, 0.614037], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.571589, 0.586483, 0.], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.915, 0.3325, 0.2125], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.40082222609352647`, 0.5220066643438841, 0.85], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.9728288904374106, 0.621644452187053, 0.07336199581899142], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.736782672705901, 0.358, 0.5030266573755369], 
       AbsoluteThickness[2]], 
      Directive[
       RGBColor[0.28026441037696703`, 0.715, 0.4292089322474965], 
       AbsoluteThickness[2]]}, "DomainPadding" -> Scaled[0.02], 
    "PointSizeFunction" -> "SmallPointSize", "RangePadding" -> Scaled[0.05], 
    "OptimizePlotMarkers" -> True, "IncludeHighlighting" -> "CurrentPoint", 
    "HighlightStyle" -> Automatic, "OptimizePlotMarkers" -> True, 
    "CoordinatesToolOptions" -> {"DisplayFunction" -> ({
        Identity[
         Part[#, 1]], 
        Identity[
         Part[#, 2]]}& ), "CopiedValueFunction" -> ({
        Identity[
         Part[#, 1]], 
        Identity[
         Part[#, 2]]}& )}},
  PlotRange->{{0, 3.}, {0, 5.800000000000001}},
  PlotRangeClipping->True,
  PlotRangePadding->{{
     Scaled[0.02], 
     Scaled[0.02]}, {
     Scaled[0.02], 
     Scaled[0.05]}},
  Ticks->{Automatic, Automatic}]], "Output",
 CellChangeTimes->{3.905663946779726*^9},
 CellLabel->
  "Out[120]=",ExpressionUUID->"998d7ec3-12dd-427c-8a56-284c69557b34"]
}, Open  ]]
}, Open  ]]
}, Closed]]
}, Open  ]]
},
AutoGeneratedPackage->None,
WindowToolbars->"MultipurposeBar",
WindowSize->{1440, 847},
WindowMargins->{{Automatic, -75}, {-903, Automatic}},
Magnification:>1.25 Inherited,
FrontEndVersion->"13.3 for Mac OS X x86 (64-bit) (July 24, 2023)",
StyleDefinitions->Notebook[{
   Cell[
    CellGroupData[{
      Cell["DarkStyle for Notebooks", "Title"], 
      Cell[
       StyleData[StyleDefinitions -> "Default.nb"]], 
      Cell[
       CellGroupData[{
         Cell["Styles for Tongue menu cells", "Section"], 
         Cell[
          StyleData[
          "WolframAlphaShort", StyleDefinitions -> StyleData["Input"]], 
          StyleKeyMapping -> {
           "=" -> "WolframAlphaLong", "Backspace" -> "Input"}, EvaluationMode -> 
          "WolframAlphaShort", 
          CellEventActions -> {"ReturnKeyDown" :> FrontEndTokenExecute[
              EvaluationNotebook[], "HandleShiftReturn"]}, 
          CellFrameLabels -> {{
             Cell[
              BoxData[
               StyleBox[
               "\[FreeformPrompt]", FontColor -> RGBColor[0, 0.7, 1]]]], 
             None}, {None, None}}, DefaultFormatType -> TextForm, 
          ShowCodeAssist -> False, FormatType -> TextForm, FontFamily -> 
          "Helvetica"], 
         Cell[
          StyleData[
          "WolframAlphaShortInput", StyleDefinitions -> StyleData["Input"]], 
          EvaluationMode -> "WolframAlphaShort", 
          CellEventActions -> {"ReturnKeyDown" :> FrontEndTokenExecute[
              EvaluationNotebook[], "HandleShiftReturn"]}, 
          CellFrameLabels -> {{
             Cell[
              BoxData[
               StyleBox[
               "\[FreeformPrompt]", FontColor -> RGBColor[0, 0.7, 1]]], 
              CellBaseline -> Baseline], None}, {None, None}}, ShowCodeAssist -> 
          False, FormatType -> TextForm, FontFamily -> "Helvetica"], 
         Cell[
          StyleData[
          "WolframAlphaLong", StyleDefinitions -> StyleData["Input"]], 
          StyleKeyMapping -> {
           "=" -> "Input", "Backspace" -> "WolframAlphaShort"}, 
          EvaluationMode -> "WolframAlphaLong", 
          CellEventActions -> {"ReturnKeyDown" :> FrontEndTokenExecute[
              EvaluationNotebook[], "HandleShiftReturn"]}, 
          CellFrameLabels -> {{
             Cell[
              BoxData[
               StyleBox[
               "\[WolframAlphaPrompt]", FontColor -> RGBColor[0, 0.7, 1]]]], 
             None}, {None, None}}, DefaultFormatType -> TextForm, 
          ShowCodeAssist -> False, FormatType -> TextForm, FontFamily -> 
          "Helvetica"], 
         Cell[
          StyleData["WolframAlphaFullOutput"], 
          CellMargins -> {{20, 10}, {Inherited, Inherited}}], 
         Cell[
          CellGroupData[{
            Cell[
             StyleData["ExternalLanguage"], CellFrame -> 1, 
             CellMargins -> {{66, 10}, {8, 8}}, 
             StyleKeyMapping -> {"Backspace" -> "Input"}, Evaluatable -> True,
              EvaluationMode -> "ExternalLanguage", CellGroupingRules -> 
             "InputGrouping", StripStyleOnPaste -> True, 
             CellEvaluationLanguage -> "Python", 
             CellFrameMargins -> {{4, 8}, {8, 8}}, CellFrameColor -> 
             RGBColor[0.2549, 0.23137, 0.42549], CellFrameLabels -> {{
                Cell[
                 BoxData[
                  DynamicBox[
                   ToBoxes[
                   ExternalEvaluate`FE`$ExternalLanguageMenuDataChanged; 
                    FrontEnd`Private`MakeExternalLanguageMenu[
                    ExternalEvaluate`FE`GetDefaultCellEvaluationLanguage[], 
                    ExternalEvaluate`FE`GetExternalLanguageMenuData[]], 
                    StandardForm], 
                   TrackedSymbols :> {
                    ExternalEvaluate`FE`$ExternalLanguageMenuDataChanged}, 
                   ImageSizeCache -> {
                    35., {10.64208984375, 17.35791015625}}]], "Output", 
                 Background -> None, CellFrame -> 0], None}, {None, None}}, 
             CellFrameLabelMargins -> 0, AllowInlineCells -> False, 
             Hyphenation -> False, AutoQuoteCharacters -> {}, 
             PasteAutoQuoteCharacters -> {}, LanguageCategory -> "Formula", 
             ScriptLevel -> 1, MenuSortingValue -> 1800, FontFamily -> Dynamic[
               CurrentValue[{StyleHints, "CodeFont"}]], FontSize -> 12, 
             FontColor -> GrayLevel[0.97], Background -> 
             RGBColor[0.18, 0.172, 0.22]], 
            Cell[
             StyleData["ExternalLanguage", "Presentation"], 
             CellMargins -> {{101, 10}, {8, 15}}, FontSize -> 18], 
            Cell[
             StyleData["ExternalLanguage", "SlideShow"], ShowGroupOpener -> 
             False, CellMargins -> {{110, 10}, {8, 15}}, FontSize -> 18], 
            Cell[
             StyleData["ExternalLanguage", "Printout"], 
             CellMargins -> {{48, 10}, {8, 8}}, 
             CellFrameMargins -> {{2, 8}, {8, 8}}]}, Open]]}, Open]], 
      Cell[
       CellGroupData[{
         Cell["Notebook options settings", "Section"], 
         Cell[
          StyleData[All, "Working"], InitializationCellEvaluation -> False, 
          DockedCells -> None, DefaultNewCellStyle -> "Code", 
          ShowPredictiveInterface -> False], 
         Cell[
          StyleData["Notebook"], 
          CellBracketOptions -> {
           "Color" -> RGBColor[0., 0.8, 1], "HoverColor" -> 
            RGBColor[0.78, 0.64, 1], "Thickness" -> 1.3, "Widths" -> {2, 8}}, 
          StyleKeyMapping -> {
           "==" -> "WolframAlphaLong", "Backspace" -> "WolframAlphaShort", 
            "=" -> "WolframAlphaShort", "*" -> "Item", ">" -> 
            "ExternalLanguage", "Backspace" -> "Code"}, 
          AutoStyleOptions -> {
           "CommentStyle" -> {
             FontColor -> RGBColor[0.89, 0.56, 1., 0.95], ShowAutoStyles -> 
              False, ShowSyntaxStyles -> False, AutoNumberFormatting -> 
              False}, "ExcessArgumentStyle" -> {
             FontColor -> 
              RGBColor[
               0.8627450980392157, 0.19607843137254902`, 0.1843137254901961]},
             "FunctionLocalVariableStyle" -> {
             FontColor -> RGBColor[0.52549, 0.843137, 1.]}, 
            "GraphicsCompatibilityProblemStyle" -> {
             FontColor -> 
              RGBColor[
               0.8627450980392157, 0.19607843137254902`, 0.1843137254901961]},
             "LocalScopeConflictStyle" -> {
             FontColor -> 
              RGBColor[
               0.8274509803921568, 0.21176470588235294`, 0.5098039215686274]},
             "LocalVariableStyle" -> {
             FontColor -> RGBColor[0., 0.8200000000000001, 0.32]}, 
            "MissingArgumentStyle" -> {
             FontColor -> 
              RGBColor[
               0.8627450980392157, 0.19607843137254902`, 0.1843137254901961]},
             "MisspelledWordStyle" -> {
             FontColor -> 
              RGBColor[
               0.8274509803921568, 0.21176470588235294`, 0.5098039215686274]},
             "NoKernelPresentStyle" -> {
             FontColor -> 
              RGBColor[
               0.16470588235294117`, 0.6313725490196078, 0.596078431372549]}, 
            "PatternVariableStyle" -> {
             FontColor -> RGBColor[0.11, 1., 0.08], FontSlant -> "Italic"}, 
            "StringStyle" -> {
             FontColor -> RGBColor[0.98, 0.71, 0.], ShowAutoStyles -> False, 
              ShowSyntaxStyles -> False, AutoNumberFormatting -> False}, 
            "UndefinedSymbolStyle" -> {FontColor -> RGBColor[0.42, 0.94, 1]}, 
            "UnknownOptionStyle" -> {
             FontColor -> 
              RGBColor[
               0.8627450980392157, 0.19607843137254902`, 0.1843137254901961]},
             "UnwantedAssignmentStyle" -> {
             FontColor -> 
              RGBColor[
               0.8627450980392157, 0.19607843137254902`, 
                0.1843137254901961]}}, 
          CodeAssistOptions -> {
           "AutoConvertEnable" -> False, 
            "HeadHighlightStyle" -> {
             Background -> None, FontColor -> RGBColor[1, 1, 0], FontWeight -> 
              Bold}, "MatchHighlightStyle" -> {
             Background -> None, FontColor -> RGBColor[1, 1, 0], FontWeight -> 
              Bold}}, TranslationOptions -> {"Language" -> None}, FontColor -> 
          RGBColor[0, 0.7, 1], Background -> GrayLevel[0.15]], 
         Cell[
          StyleData["DialogStyle"], FontColor -> RGBColor[0, 0.7, 1]], 
         Cell[
          StyleData["NotebookObject"], FontColor -> RGBColor[0, 0.7, 1]], 
         Cell[
          StyleData["LinguisticAssistant"], FontColor -> 
          RGBColor[0, 0.7, 1]]}, Open]], 
      Cell[
       CellGroupData[{
         Cell["Styles for Title and Section Cells", "Section"], 
         Cell[
          StyleData["Title"], FontColor -> GrayLevel[1]], 
         Cell[
          StyleData["Chapter"], FontColor -> RGBColor[0.8, 0.8, 0.8]], 
         Cell[
          StyleData["Subchapter"], FontColor -> RGBColor[0.65, 0.05, 0.65]], 
         Cell[
          StyleData["Subtitle"], FontColor -> 
          RGBColor[0.196078, 0.694118, 0.862745]], 
         Cell[
          StyleData["Subsubtitle"], FontColor -> 
          RGBColor[0.196078, 0.394118, 0.562745]], 
         Cell[
          StyleData["Subsubtitle"]], 
         Cell[
          StyleData["Section"], FontColor -> 
          RGBColor[
           0.1399099717708095, 0.5224231326771954, 0.6501869230182346]], 
         Cell[
          StyleData["Subsection"], FontColor -> GrayLevel[0.749996]], 
         Cell[
          StyleData["Subsubsection"], FontColor -> 
          RGBColor[0.823529, 0.490654, 0.202274]], 
         Cell[
          StyleData["Subsubsubsection"], FontColor -> 
          RGBColor[0.954147, 0.694224, 0.124651]], 
         Cell[
          StyleData["Subsubsubsubsection"], FontColor -> 
          RGBColor[0.913237, 0.365469, 0.0854353]], 
         Cell[
          StyleData["Text"], FontFamily -> "Gill Sans Light", FontSize -> 14, 
          FontWeight -> "Plain", FontSlant -> "Plain", FontColor -> 
          GrayLevel[0.683803]], 
         Cell[
          StyleData["Item"], CellDingbat -> 
          StyleBox["\[FilledSmallSquare]", Alignment -> Baseline, 
            RGBColor[0, 0.7, 1]], CellMargins -> {{81, 10}, {4, 8}}, 
          ReturnCreatesNewCell -> True, 
          StyleKeyMapping -> {"Tab" -> "Subitem", "*" -> "Subitem"}, 
          CellGroupingRules -> {"GroupTogetherNestedGrouping", 15000}, 
          CellFrameLabelMargins -> 4, CounterIncrements -> "Item", 
          CounterAssignments -> {{"Subitem", 0}, {"Subsubitem", 0}}, 
          MenuSortingValue -> 1600, FontFamily -> "Source Sans Pro", FontSize -> 
          15], 
         Cell[
          StyleData["ItemParagraph"], FontColor -> GrayLevel[0.6]], 
         Cell[
          StyleData["SubitemParagraph"], FontColor -> GrayLevel[0.6]], 
         Cell[
          StyleData["SubsubitemParagraph"], FontColor -> GrayLevel[0.6]], 
         Cell[
          CellGroupData[{
            Cell["Chapter", "Subsection"], 
            Cell[
             StyleData["Chapter"], CounterIncrements -> "Chapter", 
             CounterAssignments -> {{"Subchapter", 0}, {"Section", 0}, {
               "Equation", 0}, {"Figure", 0}, {"Subsubtitle", 0}, {
               "Item", 0}, {"Subitem", 0}, {"Subsubitem", 0}, {
               "ItemNumbered", 0}, {"SubitemNumbered", 0}, {
               "SubsubitemNumbered", 0}}, MenuSortingValue -> 1150, 
             MenuCommandKey :> "2"], 
            Cell[
             StyleData["Subchapter"], CellDingbat -> 
             StyleBox["\[MathematicaIcon]", Alignment -> Baseline, 
               RGBColor[0., 0.043, 0.9]], CounterIncrements -> "Subchapter", 
             CounterAssignments -> {{"Section", 0}, {"Equation", 0}, {
               "Figure", 0}, {"Item", 0}, {"Subitem", 0}, {"Subsubitem", 0}, {
               "ItemNumbered", 0}, {"SubitemNumbered", 0}, {
               "SubsubitemNumbered", 0}}, MenuSortingValue -> 1200, 
             MenuCommandKey :> "3"]}, Open]]}, Open]], 
      Cell[
       CellGroupData[{
         Cell["Input and Output cells", "Section"], 
         Cell[
          StyleData["Code"], 
          CellMargins -> {{66, Inherited}, {Inherited, Inherited}}, 
          CellFrameLabelMargins -> {{17, Inherited}, {Inherited, Inherited}}, 
          FontSize -> 13, FontWeight -> Plain, FontColor -> GrayLevel[1], 
          Background -> GrayLevel[0.1]], 
         Cell[
          StyleData["InitializationCell"], 
          CellMargins -> {{55, Inherited}, {Inherited, Inherited}}, 
          CellFrameMargins -> {{10, 10}, {5, 5}}, CellFrameLabelMargins -> -5,
           FontColor -> GrayLevel[1], Background -> GrayLevel[0.25]], 
         Cell[
          StyleData["Input"], 
          CellMargins -> {{66, Inherited}, {Inherited, Inherited}}, 
          CellFrameLabelMargins -> {{17, Inherited}, {Inherited, Inherited}}, 
          FontSize -> 13, FontColor -> GrayLevel[0.7]], 
         Cell[
          StyleData["Output"], CellFrame -> True, 
          CellMargins -> {{55, Inherited}, {Inherited, Inherited}}, 
          CellLabelStyle -> {"CellLabel", FontColor -> GrayLevel[0.78]}, 
          CellFrameMargins -> {{10, 0}, {0, 0}}, CellFrameStyle -> {
            Directive[
             GrayLevel[1, 0]], 
            Directive[
             GrayLevel[1, 0]], 
            Directive[
             GrayLevel[1, 0]], 
            Directive[
             RGBColor[0.45, 0.45, 0.95], 
             Thickness[1], 
             Dashing[{4, 6}]]}, CellFrameLabelMargins -> -5, FontSize -> 13], 
         
         Cell[
          StyleData["Message"], CellFrame -> True, 
          CellMargins -> {{55, Inherited}, {Inherited, Inherited}}, 
          CellLabelStyle -> {"CellLabel", FontColor -> GrayLevel[0.78]}, 
          CellFrameMargins -> {{10, 0}, {0, 0}}, CellFrameStyle -> {
            Directive[
             GrayLevel[1, 0]], 
            Directive[
             GrayLevel[1, 0]], 
            Directive[
             GrayLevel[1, 0]], 
            Directive[
             RGBColor[0.45, 0.45, 0.95], 
             Thickness[1], 
             Dashing[{4, 6}]]}, CellFrameLabelMargins -> -5, FontColor -> 
          RGBColor[
           0.704600595101854, 0.24277103837644007`, 0.22278171969176777`]], 
         Cell[
          StyleData["Print"], CellFrame -> True, 
          CellMargins -> {{55, Inherited}, {Inherited, Inherited}}, 
          CellLabelStyle -> {"CellLabel", FontColor -> GrayLevel[0.78]}, 
          CellFrameMargins -> {{10, 0}, {0, 0}}, CellFrameStyle -> {
            Directive[
             GrayLevel[1, 0]], 
            Directive[
             GrayLevel[1, 0]], 
            Directive[
             GrayLevel[1, 0]], 
            Directive[
             RGBColor[0.45, 0.45, 0.95], 
             Thickness[1], 
             Dashing[{4, 6}]]}, CellFrameLabelMargins -> -5, FontColor -> 
          GrayLevel[0.3]]}, Open]], 
      Cell[
       CellGroupData[{
         Cell["misc", "Section"], 
         Cell[
          StyleData["InformationCell"], 
          CellBracketOptions -> {
           "Color" -> RGBColor[0.760174, 0.600641, 0.675288]}, FontColor -> 
          GrayLevel[0.3]], 
         Cell[
          StyleData["InformationLink"], FontColor -> 
          RGBColor[0.4525, 0.48138, 0.7]], 
         Cell[
          StyleData["InformationLinkLF"], FontColor -> 
          RGBColor[0.4525, 0.48138, 0.7]], 
         Cell[
          StyleData["CellLabel"], 
          CellLabelMargins -> {{12, Inherited}, {Inherited, Inherited}}, 
          LanguageCategory -> None, StyleMenuListing -> None, FontFamily -> 
          "Helvetica", FontSize -> 9]}, Open]], 
      Cell[
       CellGroupData[{
         Cell["Styles for Formulas and Programming", "Section"], 
         Cell[
          StyleData["DisplayFormula"], FontColor -> GrayLevel[0.85]], 
         Cell[
          StyleData["DisplayFormulaNumbered"], FontColor -> GrayLevel[0.85]], 
         
         Cell[
          StyleData["Program"], CellFrameColor -> GrayLevel[0.4]]}, Open]], 
      Cell[
       CellGroupData[{
         Cell[
          TextData[{"Styles for ", 
            StyleBox["Mathematica", FontSlant -> "Italic"], 
            " System\[Hyphen]specific Elements"}], "Section", 
          CellChangeTimes -> {{3.601920784160323*^9, 3.60192078489342*^9}, 
            3.60356525124664*^9, {3.6037117681643677`*^9, 
            3.6037117683195887`*^9}}], 
         Cell[
          CellGroupData[{
            Cell["FormatType Styles", "Subsection"], 
            Cell[
             StyleData["StandardForm"]], 
            Cell[
             StyleData["CellExpression"], FontColor -> GrayLevel[0], 
             Background -> GrayLevel[0.75]], 
            Cell[
             StyleData["CellLabel"], FontSize -> 9, FontColor -> 
             RGBColor[0.603861, 0.615915, 0.607843]]}, Open]], 
         Cell[
          CellGroupData[{
            Cell[
            "Graphics Styles", "Subsection", 
             CellChangeTimes -> {{3.603565272271762*^9, 
              3.603565284491351*^9}}], 
            Cell[
             StyleData["GraphicsAxes"], LineColor -> 
             RGBColor[
              0.5764705882352941, 0.6313725490196078, 0.6313725490196078], 
             FontFamily -> "Avenir", FontSize -> 9, FontWeight -> "Plain", 
             FontSlant -> "Plain", FontColor -> 
             RGBColor[
              0.5764705882352941, 0.6313725490196078, 0.6313725490196078]], 
            Cell[
             StyleData["GraphicsFrame"], LineColor -> 
             RGBColor[
              0.5764705882352941, 0.6313725490196078, 0.6313725490196078], 
             FontFamily -> "Avenir", FontSize -> 9, FontWeight -> "Plain", 
             FontSlant -> "Plain", FontColor -> 
             RGBColor[
              0.5764705882352941, 0.6313725490196078, 0.6313725490196078]], 
            Cell[
             StyleData["Graphics3DAxes"], LineColor -> 
             RGBColor[
              0.5764705882352941, 0.6313725490196078, 0.6313725490196078], 
             FontFamily -> "Arial", FontSize -> 9, FontWeight -> "Plain", 
             FontSlant -> "Plain", FontColor -> 
             RGBColor[
              0.5764705882352941, 0.6313725490196078, 0.6313725490196078]]}, 
           Open]]}, Open]]}, Open]]}, Visible -> False, FrontEndVersion -> 
  "13.3 for Mac OS X x86 (64-bit) (July 24, 2023)", StyleDefinitions -> 
  "Default.nb"],
ExpressionUUID->"96cc0f0e-eba9-4f89-a4b8-a0f3b95f15a9"
]
(* End of Notebook Content *)

(* Internal cache information *)
(*CellTagsOutline
CellTagsIndex->{}
*)
(*CellTagsIndex
CellTagsIndex->{}
*)
(*NotebookFileOutline
Notebook[{
Cell[CellGroupData[{
Cell[580, 22, 661, 12, 200, "Title",ExpressionUUID->"653c41f3-823d-4cf8-b781-a41f077bbcfc"],
Cell[1244, 36, 435, 6, 41, "Author",ExpressionUUID->"73931733-b35f-48f8-8bcc-eb6ec5be6ab0"],
Cell[1682, 44, 261, 6, 31, "Input",ExpressionUUID->"ddd5e9c3-34d0-4b0a-b34b-8a5223c82817"],
Cell[1946, 52, 742, 16, 238, "Text",ExpressionUUID->"f18ff450-c45b-41f8-b278-99649fcf1000"],
Cell[CellGroupData[{
Cell[2713, 72, 156, 3, 84, "Section",ExpressionUUID->"35ad3a7f-17be-4ab9-ad4a-e711b8a076ac"],
Cell[CellGroupData[{
Cell[2894, 79, 9977, 189, 850, "Code",ExpressionUUID->"f5b666ab-d61b-4cc4-894c-abef1813a8b9"],
Cell[CellGroupData[{
Cell[12896, 272, 1607, 26, 31, "Print",ExpressionUUID->"80b542f5-f5a0-4a49-96c1-0f522a9d28a9"],
Cell[14506, 300, 1624, 26, 31, "Print",ExpressionUUID->"474faa88-1bde-4128-97f2-9261d5fecf17"],
Cell[16133, 328, 347, 8, 30, "Echo",ExpressionUUID->"a2ad2a2c-7727-42aa-90fe-661cb6f4ba16"],
Cell[16483, 338, 1607, 26, 31, "Print",ExpressionUUID->"5102622f-fa44-41fa-b88e-22a89ca362c3"],
Cell[18093, 366, 158, 3, 30, "Echo",ExpressionUUID->"a558a1bf-2132-415d-8f21-f2709095b452"],
Cell[18254, 371, 1618, 26, 31, "Print",ExpressionUUID->"b4ed33cb-d069-4050-abe6-ea54ff64aca3"],
Cell[19875, 399, 256, 7, 30, "Echo",ExpressionUUID->"fd6be947-31d4-4d99-a73b-b2aef6227ca5"],
Cell[20134, 408, 211, 6, 30, "EchoTiming",ExpressionUUID->"28cece4c-3970-443e-8c7f-9432580066ef"],
Cell[20348, 416, 734, 14, 31, "Print",ExpressionUUID->"ad48af98-9d0b-4a62-bb7d-3b06c9ece02c"]
}, Open  ]]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[21143, 437, 396, 6, 84, "Section",ExpressionUUID->"8e2d086c-3e8f-4c8e-ac60-0aa07484da5f"],
Cell[21542, 445, 260, 6, 40, "Text",ExpressionUUID->"76c7c0a0-be1e-4a11-a5cb-30de2a7dc435"],
Cell[21805, 453, 4828, 134, 512, "Code",ExpressionUUID->"a3671ec2-b1f3-49f8-8d44-a13d38d87b00"],
Cell[CellGroupData[{
Cell[26658, 591, 13750, 322, 2072, "Code",ExpressionUUID->"57415dd2-5f07-4cc7-a6bb-425e3bdb8c6b"],
Cell[CellGroupData[{
Cell[40433, 917, 493, 10, 31, "Print",ExpressionUUID->"643ab74a-a539-4161-a422-6a395da5ef07"],
Cell[40929, 929, 256, 7, 30, "Echo",ExpressionUUID->"7847530b-de8a-42ee-ba45-0ca94cb69f41"],
Cell[41188, 938, 212, 6, 30, "EchoTiming",ExpressionUUID->"74a9a6ff-bb4c-410a-9527-e594de7e99c2"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[41449, 950, 225, 4, 67, "Subsection",ExpressionUUID->"488bde6d-3234-4731-b9a2-fe09b24be7f0"],
Cell[41677, 956, 7702, 171, 530, "Code",ExpressionUUID->"befb799c-2f21-4d29-adb2-bbe5a98dbad4"]
}, Open  ]],
Cell[CellGroupData[{
Cell[49416, 1132, 182, 3, 67, "Subsection",ExpressionUUID->"7edb88c8-2e94-49d1-bb8b-5828f2c27561"],
Cell[49601, 1137, 1026, 26, 148, "Code",ExpressionUUID->"1530ea50-817c-4365-adeb-0f5fb0dbbfe9"],
Cell[50630, 1165, 3818, 89, 226, "Code",ExpressionUUID->"4becaa35-ee83-4192-b38e-1f3a0df12e37"],
Cell[CellGroupData[{
Cell[54473, 1258, 899, 22, 61, "Code",ExpressionUUID->"5761500c-fc4d-4941-9af3-4d1ed449d742"],
Cell[55375, 1282, 89902, 1547, 325, "Output",ExpressionUUID->"f54e6261-6723-4017-a99f-e9a196274ad0"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[145326, 2835, 286, 4, 67, "Subsection",ExpressionUUID->"c59fee72-1d89-410f-954c-b21b6b245b12"],
Cell[145615, 2841, 8331, 182, 512, "Code",ExpressionUUID->"7a70f86a-ed7d-4a03-a47f-bfb7d2a96e20"],
Cell[153949, 3025, 1046, 25, 122, "Code",ExpressionUUID->"88b75337-1af3-4710-ad45-ee511381cdaa"]
}, Open  ]],
Cell[CellGroupData[{
Cell[155032, 3055, 172, 3, 67, "Subsection",ExpressionUUID->"86c21601-9b68-47a6-8220-134873a4c556"],
Cell[155207, 3060, 3661, 87, 200, "Code",ExpressionUUID->"ea40ec3e-5fbc-44d1-99fc-942ab1f9dd39"],
Cell[CellGroupData[{
Cell[158893, 3151, 10129, 240, 1344, "Code",ExpressionUUID->"cb8d9aeb-a352-4322-bf6a-0dc0bde5c7de"],
Cell[169025, 3393, 602971, 10223, 306, "Output",ExpressionUUID->"9a654e6c-8528-4e40-b66d-7eaef8d12268"],
Cell[771999, 13618, 502, 8, 33, "Output",ExpressionUUID->"f9d29e1e-4ab0-40a2-a892-f76d969fe3d4"]
}, Open  ]],
Cell[772516, 13629, 158, 3, 43, "Code",ExpressionUUID->"7d5b627d-eaa1-4ef1-b7c1-464527b62225"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[772723, 13638, 567, 10, 179, "Section",ExpressionUUID->"e9c4dcf0-3b39-4088-b100-3f354e2459d1"],
Cell[773293, 13650, 252, 6, 40, "Text",ExpressionUUID->"dc6ea1b2-5259-4211-9cea-9874ea64dac2"],
Cell[773548, 13658, 2391, 59, 433, "Code",ExpressionUUID->"ceba595e-b4f4-47c5-bfb2-7acb69981445"],
Cell[CellGroupData[{
Cell[775964, 13721, 313, 6, 45, "Code",ExpressionUUID->"5e16e4a2-181d-4113-96b6-3974b5af7339"],
Cell[776280, 13729, 142, 3, 30, "EchoTiming",ExpressionUUID->"edbfff56-0b3e-4c7c-8e0c-1c00998c6d5b"],
Cell[776425, 13734, 319, 5, 33, "Output",ExpressionUUID->"b77041b2-7f27-4d1c-b3b7-4d7e96359b68"]
}, Open  ]],
Cell[776759, 13742, 4906, 127, 485, "Code",ExpressionUUID->"e8dcbb96-dd40-40e2-b9a5-9884828bfaf2"],
Cell[CellGroupData[{
Cell[781690, 13873, 202, 3, 45, "Code",ExpressionUUID->"bd354220-1e7e-4c63-9c02-8167f7abdd9a"],
Cell[781895, 13878, 255, 5, 33, "Output",ExpressionUUID->"a7ce2b29-7f76-4843-aa8e-914a06f94406"]
}, Open  ]],
Cell[CellGroupData[{
Cell[782187, 13888, 458, 10, 45, "Code",ExpressionUUID->"9e3caa9f-df25-4607-843f-9cf19449d947"],
Cell[782648, 13900, 7776, 206, 292, "Output",ExpressionUUID->"4364c2b5-5bc0-41c2-ba35-18f59ccc7591"]
}, Open  ]],
Cell[CellGroupData[{
Cell[790461, 14111, 764, 17, 45, "Code",ExpressionUUID->"a5209e25-ffb2-4bef-9ac4-f8e9c04448a7"],
Cell[791228, 14130, 16887, 365, 306, "Output",ExpressionUUID->"51117444-7404-4b4a-9b62-cdfcdd788318"]
}, Open  ]],
Cell[CellGroupData[{
Cell[808152, 14500, 200, 3, 67, "Subsection",ExpressionUUID->"4cbcd9b6-b66b-4642-baf3-a07af8433879"],
Cell[808355, 14505, 6835, 150, 485, "Code",ExpressionUUID->"a300557d-0576-4d1e-ac07-4182474e49fa"],
Cell[CellGroupData[{
Cell[815215, 14659, 270, 5, 45, "Code",ExpressionUUID->"3b98ed33-caa7-4931-8e5b-a66921090c62"],
Cell[815488, 14666, 143, 3, 30, "EchoTiming",ExpressionUUID->"37790c5d-3af7-4c82-be1f-ae1bdc2a8d30"],
Cell[815634, 14671, 2109, 57, 60, "Output",ExpressionUUID->"dc454fae-fb30-42ed-8c2d-593efad7d540"]
}, Open  ]],
Cell[CellGroupData[{
Cell[817780, 14733, 18063, 386, 145, "Code",ExpressionUUID->"337a4a2e-f53c-423a-b841-887c41d71752"],
Cell[835846, 15121, 67705, 1255, 341, "Output",ExpressionUUID->"998d7ec3-12dd-427c-8a56-284c69557b34"]
}, Open  ]]
}, Open  ]]
}, Closed]]
}, Open  ]]
}
]
*)