(*CacheID: 234*)
(* Internal cache information:
NotebookFileLineBreakTest
NotebookFileLineBreakTest
NotebookDataPosition[         0,          0]
NotebookDataLength[   1278731,      25583]
NotebookOptionsPosition[   1246016,      24528]
NotebookOutlinePosition[   1246917,      24561]
CellTagsIndexPosition[   1246738,      24554]
WindowFrame->Normal*)

(* Beginning of Notebook Content *)
Notebook[{

Cell[CellGroupData[{
Cell["Einf\[UDoubleDot]hrung in Mathematica", "Title",
 CellChangeTimes->{{3.529736694722261*^9, 3.5297367195705547`*^9}, 
   3.529773051349444*^9}],

Cell[TextData[{
 "Dieses ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " Notebook ist dazu gedacht, Sie mit der Arbeitsweise dieses \"Systems\" \
ansich und den grundlegendsten Funktionen vertraut zu machen. Hierbei werden \
anhand einfacher Beispiele und ohne Anspruch auf Vollst\[ADoubleDot]ndigkeit \
verschiedene M\[ODoubleDot]glichkeiten ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " einzusetzen demonstriert. Versuchen Sie alle Beispiele nachzuvollziehen! \
",
 StyleBox["Mathematica ",
  FontSlant->"Italic"],
 "ist mit umfangreichen Paketen und Funktionen ausgestattet und daher f\
\[UDoubleDot]r viele verschiedene Anwendungszwecke einsetzbar. Vielleicht \
kann gerade deswegen der Einstieg in ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " recht schwer fallen. Daher sollten Sie bei Unklarheiten der Funktionsweise \
von Befehlen oder bei solchen, die hier nicht vorgestellt werden die wirklich \
hervorragende ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " Dokumentation, bzw. Hilfefunktion bem\[UDoubleDot]hen."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297367642392406`*^9, 3.529736766786724*^9}, {
   3.5297368439613132`*^9, 3.529736924831789*^9}, {3.529736960434835*^9, 
   3.529736993799666*^9}, {3.529737026431807*^9, 3.529737186522756*^9}, {
   3.529737217683305*^9, 3.529737291426849*^9}, {3.5297373417020607`*^9, 
   3.52973752316285*^9}, {3.529737565582078*^9, 3.529737613877935*^9}, {
   3.529737728488254*^9, 3.529737732753344*^9}, {3.529737847641294*^9, 
   3.529737949791535*^9}, {3.529737987304834*^9, 3.529738208312291*^9}, {
   3.529741160557745*^9, 3.529741183249587*^9}, 3.529773051349903*^9}],

Cell[CellGroupData[{

Cell["Zun\[ADoubleDot]chst Grundlegendes:", "ItemParagraph",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529738459049155*^9, 3.52973846264318*^9}, {
   3.529739016087378*^9, 3.529739018974525*^9}, {3.529762446929366*^9, 
   3.529762451756379*^9}, 3.5297730513501997`*^9},
 FontWeight->"Bold"],

Cell[TextData[{
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " Befehle werden nach Eingeben durch ",
 StyleBox["[SHIFT] + [ENTER]",
  FontWeight->"Bold"],
 " ausgef\[UDoubleDot]hrt."
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529738245520091*^9, 3.529738305128664*^9}, {
   3.529738381855735*^9, 3.52973839414126*^9}, {3.529738736308807*^9, 
   3.529738736311892*^9}, {3.529738891469797*^9, 3.5297389012423983`*^9}, 
   3.529739424142115*^9, {3.5297405222072697`*^9, 3.529740548265975*^9}, {
   3.5297483668571787`*^9, 3.529748366861474*^9}, 3.529773051350425*^9}],

Cell[TextData[{
 "Kommas werden mit einem \[OpenCurlyDoubleQuote]",
 StyleBox[".", "Input"],
 "\[OpenCurlyDoubleQuote] eingegeben!"
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297483677758207`*^9, 3.529748404529604*^9}, 
   3.529773051351486*^9}],

Cell["Es gibt verschiedene Wege die Hilfe aufzurufen:", "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529738507385913*^9, 3.5297385248173103`*^9}, {
   3.5297388040718317`*^9, 3.5297388314919157`*^9}, {3.529748412682096*^9, 
   3.529748417641966*^9}, 3.5297730513515778`*^9}],

Cell[CellGroupData[{

Cell["\<\
\[UDoubleDot]ber \[OpenCurlyDoubleQuote]Help -> Documentation Center\
\[CloseCurlyDoubleQuote],\
\>", "Subsubitem",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529738536426656*^9, 3.529738582557468*^9}, {
   3.5297386158102407`*^9, 3.529738699919004*^9}, 3.5297389989368773`*^9, {
   3.529739088442273*^9, 3.529739088444723*^9}, 3.529739428257804*^9, {
   3.5297404206883183`*^9, 3.529740427767137*^9}, 3.529773051351657*^9}],

Cell[TextData[{
 "durch Markieren eines Schl\[UDoubleDot]sselwortes und ",
 StyleBox["[F1]",
  FontWeight->"Bold"],
 ","
}], "Subsubitem",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297390897082367`*^9, 3.529739114794444*^9}, 
   3.529739428733199*^9, {3.5297405593368692`*^9, 3.529740563564867*^9}, 
   3.529773051352013*^9}],

Cell[TextData[{
 "mit den Befehlen ",
 StyleBox["?<Funktion>", "Input"],
 " (\[OpenCurlyDoubleQuote]Wildcard\[CloseCurlyDoubleQuote] ",
 StyleBox["*", "Input"],
 StyleBox[" m", "Text"],
 "\[ODoubleDot]",
 StyleBox["glich", "Text"],
 ") oder ",
 StyleBox["??<Funktion>", "Input"],
 " (zus\[ADoubleDot]tzliche Angaben \[UDoubleDot]ber Attribute und \
Optionen),"
}], "Subsubitem",
 PageWidth->PaperWidth,
 CellChangeTimes->{
  3.529739091281728*^9, {3.529739133440261*^9, 3.529739133442337*^9}, 
   3.529739429859048*^9, {3.529740450164974*^9, 3.529740478579692*^9}, {
   3.5297409355446978`*^9, 3.529740971467626*^9}, {3.529741245982085*^9, 
   3.529741245983595*^9}, {3.529746366195677*^9, 3.529746404852614*^9}, 
   3.5297730513520937`*^9}],

Cell[TextData[{
 "Benutzen der Web-Dokumentation unter ",
 ButtonBox["http://reference.wolfram.com/mathematica/guide/Mathematica.html.",
  
  BaseStyle->"Hyperlink",
  ButtonData->{
    URL["http://reference.wolfram.com/mathematica/guide/Mathematica.html"], 
    None},
  ButtonNote->
   "http://reference.wolfram.com/mathematica/guide/Mathematica.html"]
}], "Subsubitem",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297391342616673`*^9, 3.5297391651404953`*^9}, {
   3.529739318352044*^9, 3.529739355162678*^9}, 3.5297394308921413`*^9, 
   3.52977305135217*^9}]
}, Open  ]],

Cell[TextData[{
 "Die Arbeit mit ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " Notebooks wird durch Anzeigen der \[OpenCurlyDoubleQuote]open/close icons\
\[CloseCurlyDoubleQuote] wesentlich erleichtert. Dazu m\[UDoubleDot]ssen Sie \
die Option unter \[OpenCurlyDoubleQuote]Edit -> Preferences, Interface -> \
Show open/close icon for cell groups\[CloseCurlyDoubleQuote] \
ausw\[ADoubleDot]hlen."
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529739416059264*^9, 3.529739583504971*^9}, {
   3.529739615250711*^9, 3.529739692601282*^9}, {3.529739727563298*^9, 
   3.529739746107092*^9}, {3.529740292209531*^9, 3.529740320807157*^9}, 
   3.529773051352243*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"?", "Exp"}]], "Input",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529741266663995*^9, 3.529741267824898*^9}, 
   3.52977305135245*^9}],

Cell[BoxData[
 RowBox[{
  StyleBox["\<\"\!\(\*RowBox[{\\\"Exp\\\", \\\"[\\\", StyleBox[\\\"z\\\", \
\\\"TI\\\"], \\\"]\\\"}]\) gives the exponential of \!\(\*StyleBox[\\\"z\\\", \
\\\"TI\\\"]\). \"\>", "MSG"], "\[NonBreakingSpace]", 
  ButtonBox[
   StyleBox["\[RightSkeleton]", "SR"],
   Active->True,
   BaseStyle->"Link",
   ButtonData->"paclet:ref/Exp"]}]], "Print", "PrintUsage",
 CellChangeTimes->{3.530333629489489*^9},
 CellTags->"Info3530337229-1666942"]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"?", "Plot"}]], "Input",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529741266663995*^9, 3.529741294234335*^9}, 
   3.529773051353683*^9}],

Cell[BoxData[
 RowBox[{
  StyleBox["\<\"\\!\\(\\*RowBox[{\\\"Plot\\\", \\\"[\\\", RowBox[{StyleBox[\\\
\"f\\\", \\\"TI\\\"], \\\",\\\", RowBox[{\\\"{\\\", \
RowBox[{StyleBox[\\\"x\\\", \\\"TI\\\"], \\\",\\\", \
SubscriptBox[StyleBox[\\\"x\\\", \\\"TI\\\"], StyleBox[\\\"min\\\", \
\\\"TI\\\"]], \\\",\\\", SubscriptBox[StyleBox[\\\"x\\\", \\\"TI\\\"], \
StyleBox[\\\"max\\\", \\\"TI\\\"]]}], \\\"}\\\"}]}], \\\"]\\\"}]\\) generates \
a plot of \\!\\(\\*StyleBox[\\\"f\\\", \\\"TI\\\"]\\) as a function of \\!\\(\
\\*StyleBox[\\\"x\\\", \\\"TI\\\"]\\) from \
\\!\\(\\*SubscriptBox[StyleBox[\\\"x\\\", \\\"TI\\\"], StyleBox[\\\"min\\\", \
\\\"TI\\\"]]\\) to \\!\\(\\*SubscriptBox[StyleBox[\\\"x\\\", \\\"TI\\\"], \
StyleBox[\\\"max\\\", \\\"TI\\\"]]\\). \\n\\!\\(\\*RowBox[{\\\"Plot\\\", \
\\\"[\\\", RowBox[{RowBox[{\\\"{\\\", \
RowBox[{SubscriptBox[StyleBox[\\\"f\\\", \\\"TI\\\"], StyleBox[\\\"1\\\", \
\\\"TR\\\"]], \\\",\\\", SubscriptBox[StyleBox[\\\"f\\\", \\\"TI\\\"], \
StyleBox[\\\"2\\\", \\\"TR\\\"]], \\\",\\\", StyleBox[\\\"\[Ellipsis]\\\", \\\
\"TR\\\"]}], \\\"}\\\"}], \\\",\\\", RowBox[{\\\"{\\\", \
RowBox[{StyleBox[\\\"x\\\", \\\"TI\\\"], \\\",\\\", \
SubscriptBox[StyleBox[\\\"x\\\", \\\"TI\\\"], StyleBox[\\\"min\\\", \
\\\"TI\\\"]], \\\",\\\", SubscriptBox[StyleBox[\\\"x\\\", \\\"TI\\\"], \
StyleBox[\\\"max\\\", \\\"TI\\\"]]}], \\\"}\\\"}]}], \\\"]\\\"}]\\) plots \
several functions \\!\\(\\*SubscriptBox[StyleBox[\\\"f\\\", \\\"TI\\\"], \
StyleBox[\\\"i\\\", \\\"TI\\\"]]\\). \"\>", "MSG"], "\[NonBreakingSpace]", 
  ButtonBox[
   StyleBox["\[RightSkeleton]", "SR"],
   Active->True,
   BaseStyle->"Link",
   ButtonData->"paclet:ref/Plot"]}]], "Print", "PrintUsage",
 CellChangeTimes->{3.5303336306469603`*^9},
 CellTags->"Info3530337230-1666942"]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"?", "Plot*"}]], "Input",
 CellChangeTimes->{{3.52974641600181*^9, 3.5297464605730133`*^9}, 
   3.5297730513545427`*^9}],

Cell[BoxData[
 DynamicModuleBox[{Typeset`open$$ = True}, 
  PaneSelectorBox[{False->
   RowBox[{
    OpenerBox[Dynamic[Typeset`open$$],
     ImageSize->Small], 
    StyleBox["System`", "InfoHeading"]}], True->GridBox[{
     {
      RowBox[{
       OpenerBox[Dynamic[Typeset`open$$],
        ImageSize->Small], 
       StyleBox["System`", "InfoHeading"]}]},
     {GridBox[{
        {
         ButtonBox["Plot",
          BaseStyle->"InformationLink",
          ButtonData:>{"Info3530337249-1666942", {"Plot", "System`"}},
          ButtonNote->"System`"], 
         ButtonBox["Plot3Matrix",
          BaseStyle->"InformationLink",
          ButtonData:>{"Info3530337249-1666942", {"Plot3Matrix", "System`"}},
          ButtonNote->"System`"], 
         ButtonBox["PlotJoined",
          BaseStyle->"InformationLink",
          ButtonData:>{"Info3530337249-1666942", {"PlotJoined", "System`"}},
          ButtonNote->"System`"], 
         ButtonBox["PlotLayout",
          BaseStyle->"InformationLink",
          ButtonData:>{"Info3530337249-1666942", {"PlotLayout", "System`"}},
          ButtonNote->"System`"], 
         ButtonBox["PlotPoints",
          BaseStyle->"InformationLink",
          ButtonData:>{"Info3530337249-1666942", {"PlotPoints", "System`"}},
          ButtonNote->"System`"], 
         ButtonBox["PlotRangeClipping",
          BaseStyle->"InformationLink",
          
          ButtonData:>{
           "Info3530337249-1666942", {"PlotRangeClipping", "System`"}},
          ButtonNote->"System`"], 
         ButtonBox["PlotRegion",
          BaseStyle->"InformationLink",
          ButtonData:>{"Info3530337249-1666942", {"PlotRegion", "System`"}},
          ButtonNote->"System`"]},
        {
         ButtonBox["Plot3D",
          BaseStyle->"InformationLink",
          ButtonData:>{"Info3530337249-1666942", {"Plot3D", "System`"}},
          ButtonNote->"System`"], 
         ButtonBox["PlotDivision",
          BaseStyle->"InformationLink",
          ButtonData:>{"Info3530337249-1666942", {"PlotDivision", "System`"}},
          
          ButtonNote->"System`"], 
         ButtonBox["PlotLabel",
          BaseStyle->"InformationLink",
          ButtonData:>{"Info3530337249-1666942", {"PlotLabel", "System`"}},
          ButtonNote->"System`"], 
         ButtonBox["PlotMarkers",
          BaseStyle->"InformationLink",
          ButtonData:>{"Info3530337249-1666942", {"PlotMarkers", "System`"}},
          ButtonNote->"System`"], 
         ButtonBox["PlotRange",
          BaseStyle->"InformationLink",
          ButtonData:>{"Info3530337249-1666942", {"PlotRange", "System`"}},
          ButtonNote->"System`"], 
         ButtonBox["PlotRangePadding",
          BaseStyle->"InformationLink",
          
          ButtonData:>{
           "Info3530337249-1666942", {"PlotRangePadding", "System`"}},
          ButtonNote->"System`"], 
         ButtonBox["PlotStyle",
          BaseStyle->"InformationLink",
          ButtonData:>{"Info3530337249-1666942", {"PlotStyle", "System`"}},
          ButtonNote->"System`"]}
       },
       DefaultBaseStyle->"InfoGrid",
       GridBoxItemSize->{"Columns" -> {{
            Scaled[0.1357142857142857]}}}]}
    },
    GridBoxAlignment->{"Columns" -> {{Left}}, "Rows" -> {{Baseline}}}]}, 
   Dynamic[Typeset`open$$],
   ImageSize->Automatic]]], "Print", "InfoCell",
 CellChangeTimes->{3.530333650053496*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell["Ausschnitt aus dem Funktionsumfang:", "ItemParagraph",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529761863375415*^9, 3.529761876932777*^9}, {
   3.5297705023230658`*^9, 3.529770507051538*^9}, 3.529773051357847*^9},
 FontWeight->"Bold"],

Cell["numerische und symbolische Berechnungen,", "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529761884503272*^9, 3.529761902312182*^9}, 
   3.529773051357925*^9}],

Cell["Visualisierung von Daten,", "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529761885375618*^9, 3.529761910560466*^9}, 
   3.529773051358027*^9}],

Cell["Statistik und Datenmanipulation,", "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529761885565773*^9, 3.529761885567686*^9}, 
   3.52976191774016*^9, 3.529773051358102*^9}],

Cell["interaktive Oberfl\[ADoubleDot]chen,", "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297619280912*^9, 3.5297619352128277`*^9}, 
   3.5297730513581743`*^9}],

Cell["h\[ODoubleDot]here Programmiersprache,", "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297619354407988`*^9, 3.529761943716585*^9}, 
   3.529773051358247*^9, {3.529829910528288*^9, 3.529829914447157*^9}}],

Cell["\<\
Bibliotheken zu zahlreichen Gebieten der Mathematik und der \
Naturwissenschaften,\
\>", "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297619357259903`*^9, 3.5297619540985813`*^9}, 
   3.52977305135832*^9, {3.530333819676947*^9, 3.5303338520730467`*^9}}],

Cell["Netzwerk Funktionalit\[ADoubleDot]t,", "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529761960228178*^9, 3.5297619604517097`*^9}, 
   3.52977305135839*^9}],

Cell["Einbindung externer Programme,", "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529761968619728*^9, 3.5297619760323687`*^9}, 
   3.5297730513584633`*^9}],

Cell["etc.", "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529761976997225*^9, 3.529761978941066*^9}, 
   3.529773051358535*^9}]
}, Open  ]],

Cell[TextData[{
 "Notebooks (Endung \[OpenCurlyDoubleQuote]",
 StyleBox[".nb", "Input"],
 "\[CloseCurlyDoubleQuote]) sind ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " als Editor vorbehalten und k\[ODoubleDot]nnen interaktiv ausgef\
\[UDoubleDot]hrt werden. Dateien mit der Endung \[OpenCurlyDoubleQuote]",
 StyleBox[".m", "Input"],
 "\[CloseCurlyDoubleQuote] sind Pakete mit ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " Code, die entweder nachtr\[ADoubleDot]glich geladen (beispielsweise f\
\[UDoubleDot]r zus\[ADoubleDot]tzliche Funktionalit\[ADoubleDot]t) oder aus \
der Konsole direkt mit \[OpenCurlyDoubleQuote]",
 StyleBox["math < file.m", "Input"],
 "\[CloseCurlyDoubleQuote] eingesen und verarbeitet werden."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297620070758743`*^9, 3.5297622399774523`*^9}, {
   3.529762274596977*^9, 3.529762275729828*^9}, {3.5297624126452217`*^9, 
   3.5297624220513153`*^9}, 3.529773051358654*^9}],

Cell[CellGroupData[{

Cell["1. Grundlegendes", "Subtitle",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529742534520773*^9, 3.529742643999269*^9}, {
   3.529742909469145*^9, 3.5297429127422*^9}, 3.529773051358811*^9}],

Cell[TextData[{
 "1.1 ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " als Taschenrechner"
}], "Subsubtitle",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529742955903411*^9, 3.52974297357767*^9}, {
   3.529743876591792*^9, 3.52974387964113*^9}, 3.529743912614644*^9, {
   3.529758649352309*^9, 3.529758651044498*^9}, 3.529773051359024*^9}],

Cell[CellGroupData[{

Cell["Arithmetische Operationen ", "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529743909641494*^9, 3.5297439424278593`*^9}, {
   3.529745635207573*^9, 3.529745676426961*^9}, 3.529745732500554*^9, 
   3.529773051359194*^9}],

Cell[TextData[{
 "Ausdr\[UDoubleDot]cke mit \[OpenCurlyDoubleQuote]",
 StyleBox["+", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["-", "Input"],
 "\[OpenCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["*", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["/", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["^", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["(", "Input"],
 "\[OpenCurlyDoubleQuote] und \[OpenCurlyDoubleQuote]",
 StyleBox[")", "Input"],
 "\[CloseCurlyDoubleQuote] werden sofort und so weit wie m\[ODoubleDot]glich \
ausgewertet (solange kein Rundungsfehler entsteht)."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52974573449111*^9, 3.529745742916967*^9}, {
   3.529746012510673*^9, 3.529746076351515*^9}, 3.52977305135933*^9, {
   3.5303342019338017`*^9, 3.530334306390542*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"1", "+", "2"}]], "Input",
 CellChangeTimes->{{3.529745835181941*^9, 3.529745835562264*^9}, 
   3.5297730513594933`*^9}],

Cell[BoxData["3"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{3.52974583628001*^9, 3.529773051359654*^9, 
  3.530334331747777*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"45", "*", "124"}]], "Input",
 CellChangeTimes->{{3.529745841813085*^9, 3.529745849393052*^9}, 
   3.529773051360217*^9}],

Cell[BoxData["5580"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{3.52974584974263*^9, 3.529773051360368*^9, 
  3.530334334145385*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(", 
   RowBox[{"35", "-", "3"}], ")"}], "/", "6"}]], "Input",
 CellChangeTimes->{{3.529745853090706*^9, 3.529745880843112*^9}, 
   3.52977305136054*^9}],

Cell[BoxData[
 FractionBox["16", "3"]], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{{3.529745859684621*^9, 3.529745881289157*^9}, 
   3.529773051360713*^9, 3.5303343409680223`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"44", "^", "2"}]], "Input",
 CellChangeTimes->{{3.529745870696291*^9, 3.5297458729934597`*^9}, 
   3.529773051360868*^9}],

Cell[BoxData["1936"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{3.529745873276651*^9, 3.529773051361058*^9, 
  3.5303343431493893`*^9}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["Vordefinierte Konstanten", "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52974395786697*^9, 3.5297439816214237`*^9}, 
   3.529745756258812*^9, 3.529773051361264*^9}],

Cell[TextData[{
 "\[OpenCurlyDoubleQuote]",
 StyleBox["E", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["I", "Input"],
 "\[CloseCurlyDoubleQuote] und \[OpenCurlyDoubleQuote]",
 StyleBox["Pi", "Input"],
 "\[CloseCurlyDoubleQuote] sind (Beispiele f\[UDoubleDot]r) vordefinierte \
Konstanten."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529745895192103*^9, 3.529745895452142*^9}, {
   3.529745939402812*^9, 3.529746010344677*^9}, 3.529773051361403*^9, {
   3.5303343729850893`*^9, 3.5303343929667883`*^9}}],

Cell[CellGroupData[{

Cell[BoxData["E"], "Input",
 CellChangeTimes->{3.529746088488598*^9, 3.5297730513615303`*^9}],

Cell[BoxData["\[ExponentialE]"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{3.529746089156149*^9, 3.5297730513616543`*^9, 
  3.5303344062960463`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData["I"], "Input",
 CellChangeTimes->{3.5297460907030983`*^9, 3.529773051361795*^9}],

Cell[BoxData["\[ImaginaryI]"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{3.5297460910576887`*^9, 3.529773051361916*^9, 
  3.5303344101771727`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData["Pi"], "Input",
 CellChangeTimes->{{3.529746092330162*^9, 3.5297460925523653`*^9}, 
   3.529773051362064*^9}],

Cell[BoxData["\[Pi]"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{3.5297460930104227`*^9, 3.529773051362184*^9, 
  3.5303344126644077`*^9}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["Numerische Auswertung", "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529743991229147*^9, 3.52974399607226*^9}, 
   3.529773051362351*^9}],

Cell[TextData[{
 "Mit Hilfe der Funktion ",
 StyleBox["N[<Ausdruck>]", "Input"],
 " kann die numerische Auswertung erzwungen werden. (Argumente zu einer \
Funktion werden in ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " mit eckigen Klammern \[OpenCurlyDoubleQuote]",
 StyleBox["[", "Input"],
 "\[CloseCurlyDoubleQuote] und \[OpenCurlyDoubleQuote]",
 StyleBox["]", "Input"],
 "\[CloseCurlyDoubleQuote] umschlossen.)"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529746159072803*^9, 3.529746225739079*^9}, {
   3.529772880466877*^9, 3.5297729224122047`*^9}, 3.529773051362487*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"N", "[", 
  RowBox[{"1997", "/", "3"}], "]"}]], "Input",
 CellChangeTimes->{{3.529746233621257*^9, 3.529746246283658*^9}, 
   3.5297730513626347`*^9}],

Cell[BoxData["665.6666666666666`"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{{3.529746240587224*^9, 3.52974624661611*^9}, 
   3.529773051362781*^9, 3.5303344474812183`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"N", "[", "Pi", "]"}]], "Input",
 CellChangeTimes->{{3.529746252144218*^9, 3.529746253693468*^9}, 
   3.529773051362937*^9}],

Cell[BoxData["3.141592653589793`"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{3.529746254166664*^9, 3.529773051363082*^9, 
  3.530334449945612*^9}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell[TextData[StyleBox["Aufgaben",
 FontSlant->"Italic"]], "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529746534192808*^9, 3.529746548591523*^9}, 
   3.529746661107045*^9, 3.529773051363248*^9}],

Cell[CellGroupData[{

Cell[TextData[{
 "Wie findet man heraus, welche weiteren Konstanten ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " kennt?"
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529746614756171*^9, 3.529746629410859*^9}, {
   3.5297467155949717`*^9, 3.529746758185754*^9}, 3.529773051363348*^9, {
   3.53033446437993*^9, 3.5303344670554028`*^9}}],

Cell["\<\
Wie kann man bei numerischer Auswertung weitere Stellen erhalten?\
\>", "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529746614756171*^9, 3.529746629405918*^9}, {
   3.529746767040867*^9, 3.529746782341703*^9}, {3.529746856571542*^9, 
   3.529746856573999*^9}, 3.529773051363433*^9}],

Cell[TextData[{
 "Was bewirkt die Funktion ",
 StyleBox["Rationalize", "Input"],
 StyleBox["?", "Text"]
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529746857522026*^9, 3.5297468795692596`*^9}, 
   3.52977305136351*^9}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell[TextData[StyleBox["L\[ODoubleDot]sungen",
 FontSlant->"Italic"]], "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529773989883778*^9, 3.529773993519004*^9}}],

Cell[TextData[{
 "\"mathematical constants\" in der Hilfe suchen (",
 Cell[BoxData[
  FormBox[
   ButtonBox[
    RowBox[{"Mathematical", " ", "Constants"}],
    BaseStyle->"Link",
    ButtonData->"paclet:guide/MathematicalConstants"], TextForm]]],
 ")."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297745597843447`*^9, 3.529774602759284*^9}, {
  3.5303345894651127`*^9, 3.530334659039604*^9}}],

Cell[TextData[{
 "(",
 Cell[BoxData[
  FormBox[
   ButtonBox["N",
    BaseStyle->"Link",
    ButtonData->"paclet:ref/N"], TextForm]]],
 " in der Hilfe.)"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530334687437394*^9, 3.53033471736791*^9}, {
  3.530334764467004*^9, 3.530334766873786*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"N", "[", 
  RowBox[{
   RowBox[{"Exp", "[", 
    RowBox[{"1", "/", "3"}], "]"}], ",", "100"}], "]"}]], "Input",
 CellChangeTimes->{{3.529774617909692*^9, 3.5297746328161097`*^9}}],

Cell[BoxData["1.\
395612425086089528628125319602586837597906515199406982617516706031739015645951\
846969788817295830224135211184410418862096122123292780918`100."], "Output",
 CellChangeTimes->{{3.529774626717019*^9, 3.529774633222188*^9}, 
   3.530334782931691*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{"(", 
  RowBox[{
   ButtonBox["Rationalize",
    BaseStyle->"Link",
    ButtonData->"paclet:ref/Rationalize"], " ", "in", " ", "der", " ", 
   RowBox[{"Hilfe", "."}]}], ")"}]], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530334753909741*^9, 3.530334772592238*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Rationalize", "[", 
  RowBox[{"0.3333333", ",", "0.1"}], "]"}]], "Input",
 CellChangeTimes->{{3.529774640324065*^9, 3.529774677084893*^9}}],

Cell[BoxData[
 FractionBox["1", "3"]], "Output",
 CellChangeTimes->{{3.5297746470606194`*^9, 3.529774677455518*^9}, 
   3.530334784603459*^9}]
}, Open  ]],

Cell["\<\
Es bewirkt die Approximation einer Gleitkommazahl durch einen Bruch.\
\>", "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529774688296049*^9, 3.529774711206945*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell["1.2 Einige wichtige (mathematische) Funktionen", "Subsubtitle",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529743049768918*^9, 3.52974305591536*^9}, {
   3.52975717301374*^9, 3.529757215725666*^9}, {3.5297586724399*^9, 
   3.529758672865993*^9}, 3.529773051363682*^9}],

Cell[CellGroupData[{

Cell["Elementare Funtionen", "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297480950072393`*^9, 3.529748103823175*^9}, 
   3.529773051363817*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Sqrt", "[", "44", "]"}]], "Input",
 CellChangeTimes->{{3.5297471739476357`*^9, 3.529747176365367*^9}, {
   3.529748186875018*^9, 3.529748187513617*^9}, {3.529748224424876*^9, 
   3.52974822694556*^9}, 3.529773051363987*^9}],

Cell[BoxData[
 RowBox[{"2", " ", 
  SqrtBox["11"]}]], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{
  3.529748187840317*^9, {3.529748224685231*^9, 3.52974822724037*^9}, 
   3.52977305136412*^9, 3.5303362516766863`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"5", "!"}]], "Input",
 CellChangeTimes->{3.5297472921379013`*^9, 3.529748195164702*^9, 
  3.5297730513642673`*^9}],

Cell[BoxData["120"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{3.529748195461227*^9, 3.529773051364388*^9, 
  3.5303362552039337`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Exp", "[", "0.5", "]"}]], "Input",
 CellChangeTimes->{{3.529747177679175*^9, 3.5297471801940737`*^9}, {
   3.5297481996831503`*^9, 3.529748209359765*^9}, 3.529773051364541*^9}],

Cell[BoxData["1.6487212707001282`"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{{3.529748200486947*^9, 3.529748209661578*^9}, 
   3.529773051364664*^9, 3.530336257550687*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Log", "[", "1.64872", "]"}]], "Input",
 CellChangeTimes->{{3.529747181226492*^9, 3.529747181534124*^9}, {
   3.529748203343514*^9, 3.529748216041967*^9}, 3.529773051364814*^9, 
   3.530336262418645*^9}],

Cell[BoxData["0.49999922928111595`"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{{3.529748204543825*^9, 3.5297482163937073`*^9}, 
   3.529773051364936*^9, 3.530336267776441*^9}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["Numerische Funktionen", "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297481175090322`*^9, 3.529748120489772*^9}, 
   3.529773051365078*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Abs", "[", 
  RowBox[{"-", "22"}], "]"}]], "Input",
 CellChangeTimes->{{3.529747287226829*^9, 3.529747287543468*^9}, {
   3.529748297963442*^9, 3.529748300653792*^9}, 3.529773051365245*^9}],

Cell[BoxData["22"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{3.5297483009085293`*^9, 3.529773051365369*^9, 
  3.530336274225247*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Min", "[", 
  RowBox[{
   RowBox[{"-", "1"}], ",", "1"}], "]"}]], "Input",
 CellChangeTimes->{{3.529747397567958*^9, 3.529747397870934*^9}, {
   3.529748303473518*^9, 3.52974830998473*^9}, 3.52977305136553*^9}],

Cell[BoxData[
 RowBox[{"-", "1"}]], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{{3.529748304928301*^9, 3.5297483103440037`*^9}, 
   3.529773051365655*^9, 3.53033627707275*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Max", "[", 
  RowBox[{
   RowBox[{"-", "1"}], ",", "1"}], "]"}]], "Input",
 CellChangeTimes->{{3.529747399738871*^9, 3.529747400512896*^9}, {
   3.5297483122939787`*^9, 3.529748313854577*^9}, 3.5297730513658123`*^9}],

Cell[BoxData["1"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{3.529748314347176*^9, 3.5297730513659353`*^9, 
  3.5303362785372677`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Round", "[", "6.54321", "]"}]], "Input",
 CellChangeTimes->{{3.529747300892124*^9, 3.52974730410384*^9}, {
   3.5297483171042557`*^9, 3.529748330970628*^9}, {3.529748437603183*^9, 
   3.529748442485125*^9}, 3.5297730513660927`*^9}],

Cell[BoxData["7"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{{3.529748319046*^9, 3.529748331292811*^9}, 
   3.529748443033815*^9, 3.529773051366218*^9, 3.530336285556342*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Mod", "[", 
  RowBox[{"5", ",", "2"}], "]"}]], "Input",
 CellChangeTimes->{{3.52974728371511*^9, 3.529747284022032*^9}, {
   3.529748334188614*^9, 3.529748336715189*^9}, 3.529773051366372*^9}],

Cell[BoxData["1"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{3.5297483369638643`*^9, 3.529773051366494*^9, 
  3.53033628760533*^9}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["Trigonometrsiche Funktionen", "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52974749639561*^9, 3.5297475036070004`*^9}, 
   3.529773051366671*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Cos", "[", 
  RowBox[{"2", "*", "Pi"}], "]"}]], "Input",
 CellChangeTimes->{{3.529747632018252*^9, 3.5297476330144053`*^9}, {
   3.5297476966649027`*^9, 3.52974770038447*^9}, {3.529747743597982*^9, 
   3.529747750854267*^9}, 3.529773051366845*^9}],

Cell[BoxData["1"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{
  3.52974770089142*^9, {3.529747744327591*^9, 3.5297477513480577`*^9}, 
   3.5297730513669786`*^9, 3.530336298308549*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"ArcCos", "[", "1", "]"}]], "Input",
 CellChangeTimes->{{3.529747635365878*^9, 3.529747639348793*^9}, {
   3.529747705563455*^9, 3.529747753545857*^9}, 3.529773051367131*^9}],

Cell[BoxData["0"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{{3.529747710404933*^9, 3.529747753821122*^9}, 
   3.529773051367255*^9, 3.530336300359914*^9}]
}, Open  ]],

Cell[TextData[{
 "Analog: ",
 StyleBox["Sin", "Input"],
 ", ",
 StyleBox["ArcSin", "Input"],
 ", ",
 StyleBox["Tan", "Input"],
 ", ",
 StyleBox["ArcTan", "Input"],
 "."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529747641527081*^9, 3.529747676512827*^9}, 
   3.529747857076947*^9, 3.529773051367374*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell["Hyperbolische Funktionen", "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529747515261776*^9, 3.529747519657186*^9}, 
   3.529773051367486*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"Cosh", "[", "0.3", "]"}], "^", "2"}]], "Input",
 CellChangeTimes->{{3.529747797684478*^9, 3.5297478375151873`*^9}, {
   3.529747904236618*^9, 3.529747926160369*^9}, 3.529773051367652*^9}],

Cell[BoxData["1.0927326091211338`"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{3.529747926911215*^9, 3.5297730513677797`*^9, 
  3.5303363239602413`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"Sinh", "[", "0.3", "]"}], "^", "2"}]], "Input",
 CellChangeTimes->{3.529773051367936*^9}],

Cell[BoxData["0.09273260912113383`"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{{3.529747802569171*^9, 3.529747837845663*^9}, {
   3.529747905225869*^9, 3.529747927602911*^9}, 3.52977305136806*^9, 
   3.5303363253279247`*^9}]
}, Open  ]],

Cell[TextData[{
 "Analog: ",
 StyleBox["Tanh", "Input"],
 ", ",
 StyleBox["ArcSinh", "Input"],
 ", ",
 StyleBox["ArcCosh", "Input"],
 ", ",
 StyleBox["ArcTanh", "Input"],
 "."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297478500989017`*^9, 3.529747885933707*^9}, 
   3.529773051368182*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell["Zufallszahlen", "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529748156320656*^9, 3.5297481610427113`*^9}, 
   3.5297730513682947`*^9}],

Cell[BoxData[
 RowBox[{"SeedRandom", "[", "]"}]], "Input",
 CellChangeTimes->{{3.529748486216157*^9, 3.529748489064375*^9}, {
   3.52974853161579*^9, 3.5297485346246443`*^9}, 3.529773051368454*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"RandomReal", "[", "]"}]], "Input",
 CellChangeTimes->{{3.529747353233625*^9, 3.529747360704709*^9}, {
   3.529748175904747*^9, 3.5297481817953987`*^9}, {3.529748459174616*^9, 
   3.5297484668938437`*^9}, 3.529773051368596*^9}],

Cell[BoxData["0.38316691828253213`"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{{3.529748461630123*^9, 3.529748492347094*^9}, {
   3.529748537910945*^9, 3.529748559059243*^9}, 3.529773051368722*^9, 
   3.5303363492614317`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"RandomInteger", "[", "100", "]"}]], "Input",
 CellChangeTimes->{{3.529748475314032*^9, 3.529748479137904*^9}, 
   3.529748548214285*^9, 3.529773051368876*^9}],

Cell[BoxData["23"], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{{3.529748476059854*^9, 3.529748493014657*^9}, {
   3.529748538677681*^9, 3.52974855498525*^9}, 3.529773051369*^9, 
   3.530336352745829*^9}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell[TextData[StyleBox["Aufgaben",
 FontSlant->"Italic"]], "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297482438277683`*^9, 3.529748244818735*^9}, 
   3.529773051369138*^9}],

Cell[CellGroupData[{

Cell["Berechnen Sie den Logarithmus von 8 in der Basis 2!", "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529748838810506*^9, 3.5297488696625757`*^9}, {
   3.529749004921398*^9, 3.529749017171417*^9}, 3.529773051369236*^9}],

Cell[TextData[{
 "Was ist der Unterschied zwischen ",
 StyleBox["Round", "Input"],
 " und ",
 StyleBox["Floor", "Input"],
 ", bzw. ",
 StyleBox["Ceiling", "Input"],
 "?"
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297488389333353`*^9, 3.5297488389376*^9}, {
   3.529748924969342*^9, 3.5297489432915287`*^9}, 3.52977305136932*^9}],

Cell[TextData[{
 "Was passiert, wenn Sie obige Befehle auf komplexe Zahlen anwenden (Siehe \
auch ",
 StyleBox["Re", "Input"],
 " und ",
 StyleBox["Im", "Input"],
 ")?"
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529749030352195*^9, 3.52974907611755*^9}, 
   3.529773051369397*^9}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell[TextData[StyleBox["L\[ODoubleDot]sungen",
 FontSlant->"Italic"]], "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529774009481127*^9, 3.529774012416782*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Log", "[", 
  RowBox[{"2", ",", "8"}], "]"}]], "Input",
 CellChangeTimes->{{3.5297740504007483`*^9, 3.529774053643053*^9}}],

Cell[BoxData["3"], "Output",
 CellChangeTimes->{3.5297740540288486`*^9, 3.530336446852662*^9}]
}, Open  ]],

Cell[TextData[{
 "Beachte die Reihenfolge der Argumente (",
 Cell[BoxData[
  FormBox[
   ButtonBox["Log",
    BaseStyle->"Link",
    ButtonData->"paclet:ref/Log"], TextForm]]],
 ")!"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{
  3.5297745252329407`*^9, {3.530336631098052*^9, 3.530336649285226*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Round", "[", "0.56", "]"}]], "Input",
 CellChangeTimes->{{3.5297740594849*^9, 3.529774065286323*^9}}],

Cell[BoxData["1"], "Output",
 CellChangeTimes->{3.529774065569175*^9, 3.530336448824046*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Floor", "[", "0.56", "]"}]], "Input",
 CellChangeTimes->{{3.5297740697243643`*^9, 3.52977407467346*^9}}],

Cell[BoxData["0"], "Output",
 CellChangeTimes->{3.52977407512906*^9, 3.530336449465901*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Ceiling", "[", "0.56", "]"}]], "Input",
 CellChangeTimes->{{3.529774078067532*^9, 3.529774084503469*^9}}],

Cell[BoxData["1"], "Output",
 CellChangeTimes->{3.529774084922832*^9, 3.530336450134788*^9}]
}, Open  ]],

Cell[TextData[{
 StyleBox["Round", "Input"],
 " (",
 Cell[BoxData[
  FormBox[
   ButtonBox["Round",
    BaseStyle->"Link",
    ButtonData->"paclet:ref/Round"], TextForm]]],
 ") bewirkt \[OpenCurlyDoubleQuote]echtes\[CloseCurlyDoubleQuote] Runden, ",
 StyleBox["Floor", "Input"],
 " (",
 Cell[BoxData[
  FormBox[
   ButtonBox["Floor",
    BaseStyle->"Link",
    ButtonData->"paclet:ref/Floor"], TextForm]]],
 ") das Abschneiden von Kommastellen und ",
 StyleBox["Ceiling", "Input"],
 " (",
 Cell[BoxData[
  FormBox[
   ButtonBox["Ceiling",
    BaseStyle->"Link",
    ButtonData->"paclet:ref/Ceiling"], TextForm]]],
 ") gibt die n\[ADoubleDot]chst gr\[ODoubleDot]\[SZ]ere ganze Zahl (",
 StyleBox["Floor[x]+1", "Input"],
 ") zur\[UDoubleDot]ck."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529774411611403*^9, 3.529774487379196*^9}, {
  3.530336462452327*^9, 3.530336462676094*^9}, {3.530336657648884*^9, 
  3.530336688567184*^9}}],

Cell[TextData[{
 "Funktionen, die f\[UDoubleDot]r komplexe Zahlen definierbar sind (",
 StyleBox["Sqrt", "Input"],
 ", ",
 StyleBox["Exp", "Input"],
 ", ",
 StyleBox["Log", "Input"],
 ", ",
 StyleBox["Sin", "Input"],
 ", ",
 StyleBox["...", "Input"],
 "), k\[ODoubleDot]nnen wie zu erwarten ausgewertet Werten, solche f\
\[UDoubleDot]r die das nicht gilt (",
 StyleBox["Min", "Input"],
 ", ",
 StyleBox["Max", "Input"],
 ", ",
 StyleBox["...", "Input"],
 ") aber nicht."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529774203854248*^9, 3.529774329588429*^9}, {
  3.529774365864402*^9, 3.529774377937664*^9}}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["1.3 Ausdr\[UDoubleDot]cke & Symbole", "Subsubtitle",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529742826018319*^9, 3.529742836434126*^9}, {
   3.5297437366473293`*^9, 3.5297437447916517`*^9}, {3.52975867492907*^9, 
   3.529758675758161*^9}, 3.5297730513696203`*^9}],

Cell[TextData[{
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " arbeitet Quellcode Ausdruck f\[UDoubleDot]r Ausdruck ab, wobei nach nach \
jeder Auswertung das Ergebnis ausgegeben wird. Ein Ausdruck wird durch einen \
Zeilenumbruch oder ein \[OpenCurlyDoubleQuote]",
 StyleBox[";", "Input"],
 "\[CloseCurlyDoubleQuote] (Semikolon/Strichpunkt) beendet, wobei letzteres \
die Ausgabe des Ergebnisses unterdr\[UDoubleDot]ckt. (Mehrere Befehle k\
\[ODoubleDot]nnen also in einer Zeile oder Zelle untergebracht werden.)"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52975063640701*^9, 3.529750827187196*^9}, {
   3.529750858328718*^9, 3.529750951298003*^9}, {3.529750996865749*^9, 
   3.529751019081653*^9}, 3.5297533287692757`*^9, {3.529753392508995*^9, 
   3.529753393832539*^9}, {3.529753436160894*^9, 3.5297534732114143`*^9}, 
   3.5297730513697577`*^9, {3.530336754125355*^9, 3.5303367733917294`*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"N", "[", 
  RowBox[{"E", "^", 
   RowBox[{"(", 
    RowBox[{"I", "*", 
     RowBox[{"(", 
      RowBox[{"Pi", "/", "3"}], ")"}]}], ")"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.529751030705175*^9, 3.529751052973456*^9}, 
   3.529773051369937*^9}],

Cell[BoxData[
 RowBox[{"0.5000000000000001`", "\[VeryThinSpace]", "+", 
  RowBox[{"0.8660254037844386`", " ", "\[ImaginaryI]"}]}]], "Output",
 GeneratedCell->False,
 CellAutoOverwrite->False,
 CellChangeTimes->{
  3.529751053307983*^9, {3.529751713085267*^9, 3.5297517440760107`*^9}, {
   3.529751793077022*^9, 3.5297517947476807`*^9}, 3.52975205866492*^9, 
   3.52977305137011*^9, 3.530336806405115*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{"N", "[", 
   RowBox[{"E", "^", 
    RowBox[{"(", 
     RowBox[{"I", "*", 
      RowBox[{"(", 
       RowBox[{"Pi", "/", "3"}], ")"}]}], ")"}]}], "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.529751030705175*^9, 3.5297510706821203`*^9}, 
   3.529773051370302*^9}],

Cell[TextData[{
 "Nicht ausgegebene Ausdr\[UDoubleDot]cke k\[ODoubleDot]nnen beispielsweise \
durch Verwendung des \[OpenCurlyDoubleQuote]History-Operators\
\[CloseCurlyDoubleQuote] \[OpenCurlyDoubleQuote]",
 StyleBox["%", "Input"],
 "\[CloseCurlyDoubleQuote] angezeigt werden. (Nicht zu verwechseln mit ",
 StyleBox["Out[<Ausgabezeile>]", "Input"],
 ", bzw. ",
 StyleBox["%<Ausgabezeile>", "Input"],
 "!) Auch ",
 StyleBox["%%", "Input"],
 ", ",
 StyleBox["%%%", "Input"],
 ", usw. sind m\[ODoubleDot]glich aber nicht zu empfehlen!"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{
  3.5297491018836737`*^9, {3.5297515137234163`*^9, 3.529751590618545*^9}, {
   3.529751656236456*^9, 3.5297516634917383`*^9}, {3.529751825729393*^9, 
   3.52975187396362*^9}, {3.529751922826226*^9, 3.5297519476000023`*^9}, 
   3.529773051370422*^9, {3.5303368215870523`*^9, 3.530336839449131*^9}, 
   3.530336893833918*^9}],

Cell[CellGroupData[{

Cell[BoxData["%"], "Input",
 CellChangeTimes->{3.529751666505785*^9, 3.529773051370544*^9}],

Cell[BoxData[
 RowBox[{"0.5000000000000001`", "\[VeryThinSpace]", "+", 
  RowBox[{"0.8660254037844386`", " ", "\[ImaginaryI]"}]}]], "Output",
 CellChangeTimes->{{3.5303369716446*^9, 3.530336998256419*^9}}]
}, Open  ]],

Cell[TextData[{
 "Mit ",
 StyleBox["Print", "Input"],
 " l\[ADoubleDot]sst sich beliebig zusammengesetzer Text ausgeben. Strings m\
\[UDoubleDot]ssen in Anf\[UDoubleDot]hrungszeichen geschrieben werden."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297519843483047`*^9, 3.5297520428770742`*^9}, {
   3.529752084176421*^9, 3.529752133242957*^9}, 3.5297730513708153`*^9, {
   3.530335333432892*^9, 3.5303353346804543`*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Print", "[", 
  RowBox[{"\"\<Ergebnis des vorletzten Ausdrucks: \>\"", ",", "%%"}], 
  "]"}]], "Input",
 CellChangeTimes->{{3.529752046105338*^9, 3.529752073224515*^9}, {
   3.529752137714521*^9, 3.529752153804515*^9}, 3.529773051371003*^9}],

Cell[BoxData[
 InterpretationBox[
  RowBox[{
   RowBox[{"\<\"Ergebnis des vorletzten Ausdrucks: \"\>", "\[InvisibleSpace]",
     "0.5000000000000001`"}], "\[VeryThinSpace]", "+", 
   RowBox[{"0.8660254037844386`", " ", "\[ImaginaryI]"}]}],
  SequenceForm["Ergebnis des vorletzten Ausdrucks: ", 
   Complex[0.5000000000000001, 0.8660254037844386]],
  Editable->False]], "Print",
 CellChangeTimes->{{3.530336991489143*^9, 3.5303370000492973`*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[TextData[StyleBox["Ausdr\[UDoubleDot]cke lassen sich auch in Variablen \
oder Symbolen speichern. Hierzu gibt es zwei M\[ODoubleDot]glichkeiten:",
 FontWeight->"Bold"]], "ItemParagraph",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529752325101363*^9, 3.52975242958362*^9}, {
   3.529752492060771*^9, 3.529752521481395*^9}, 3.529773051371277*^9}],

Cell[TextData[{
 StyleBox["Set", "Input"],
 ", bzw. \[OpenCurlyDoubleQuote]",
 StyleBox["=", "Input"],
 "\[CloseCurlyDoubleQuote] (Shortcut)"
}], "Item",
 CellChangeTimes->{{3.529752450881103*^9, 3.529752510369131*^9}, 
   3.5297730513714237`*^9}],

Cell[TextData[{
 "und ",
 StyleBox["SetDelayed", "Input"],
 ", bzw. \[OpenCurlyDoubleQuote]",
 StyleBox[":=", "Input"],
 "\[CloseCurlyDoubleQuote]."
}], "Item",
 CellChangeTimes->{{3.529752525117017*^9, 3.529752565162279*^9}, 
   3.529773051371573*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"a", "=", 
  RowBox[{"N", "[", 
   RowBox[{"Exp", "[", "44", "]"}], "]"}]}]], "Input",
 CellChangeTimes->{{3.5297526251059847`*^9, 3.5297526327432423`*^9}, 
   3.5297730513717527`*^9}],

Cell[BoxData["1.2851600114359308`*^19"], "Output",
 CellChangeTimes->{{3.530337062189139*^9, 3.530337063868556*^9}}]
}, Open  ]],

Cell[BoxData[
 RowBox[{"b", ":=", 
  RowBox[{"N", "[", 
   RowBox[{"Log", "[", "44", "]"}], "]"}]}]], "Input",
 CellChangeTimes->{{3.529752641349326*^9, 3.529752653811602*^9}, 
   3.52977305137212*^9}],

Cell[TextData[{
 "Hierbei f\[ADoubleDot]llt auf, dass f\[UDoubleDot]r \[OpenCurlyDoubleQuote]",
 StyleBox["b", "Input"],
 "\[CloseCurlyDoubleQuote] keine Ausgabe erscheint. Grund hierf\[UDoubleDot]r \
ist folgendes: Bei ",
 StyleBox["Set", "Input"],
 " wird die rechte Seite sofort ausgewertet und das Ergebnis im Symbol auf \
der linken Seite gespeichert (Wertzuweisung wie bspw. in ",
 StyleBox["C++)", "Input"],
 ". Bei ",
 StyleBox["SetDelayed", "Input"],
 " wird nicht das Ergebnis der Auswertung der rechten Seite, sondern die \
Eingabe selbst im Symbol abgelegt (Anlegen einer Definition)."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297529918497562`*^9, 3.529753266580289*^9}, 
   3.529773051372243*^9, {3.5303370973676243`*^9, 3.530337101393215*^9}, {
   3.530337133679701*^9, 3.5303371362851667`*^9}}],

Cell[TextData[{
 "Hierzu ein kleines Beispiel (Kommentare m\[UDoubleDot]ssen in \
\[OpenCurlyDoubleQuote]",
 StyleBox["(*", "Input"],
 "\[CloseCurlyDoubleQuote] und \[OpenCurlyDoubleQuote]",
 StyleBox["*)", "Input"],
 "\[CloseCurlyDoubleQuote] eingeschlossen werden):"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529753679045218*^9, 3.529753791707284*^9}, 
   3.529773051372348*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", "Wertzuweisung", " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{
    RowBox[{"a", "=", 
     RowBox[{"RandomReal", "[", "]"}]}], ";"}], "\[IndentingNewLine]", 
   RowBox[{"(*", " ", "Definitionszuweisung", " ", "*)"}], 
   "\[IndentingNewLine]", 
   RowBox[{"b", ":=", 
    RowBox[{"RandomReal", "[", "]"}]}], "\[IndentingNewLine]", 
   RowBox[{"(*", " ", 
    RowBox[{"mehrfacher", " ", "Aufruf"}], " ", "*)"}], "\[IndentingNewLine]",
    "a", "\[IndentingNewLine]", "a", "\[IndentingNewLine]", "a", 
   "\[IndentingNewLine]", 
   RowBox[{"(*", " ", 
    RowBox[{"a", " ", "konstant"}], " ", "*)"}], "\[IndentingNewLine]", "b", 
   "\[IndentingNewLine]", "b", "\[IndentingNewLine]", "b", 
   "\[IndentingNewLine]", 
   RowBox[{"(*", " ", 
    RowBox[{"b", " ", "variabel"}], " ", "*)"}]}]}]], "Input",
 CellChangeTimes->{{3.529753531377174*^9, 3.529753538814619*^9}, {
   3.5297535937727127`*^9, 3.529753654451997*^9}, {3.5297537569955673`*^9, 
   3.5297537624789057`*^9}, {3.5297538010999403`*^9, 
   3.5297538132759666`*^9}, {3.52975392708714*^9, 3.529754002194806*^9}, {
   3.5297540446943407`*^9, 3.5297540595740957`*^9}, 3.529773051372636*^9, 
   3.530426679311956*^9}],

Cell[BoxData["0.278333419659746`"], "Output",
 CellChangeTimes->{{3.530337197421713*^9, 3.530337199153*^9}}],

Cell[BoxData["0.278333419659746`"], "Output",
 CellChangeTimes->{{3.530337197421713*^9, 3.530337199158864*^9}}],

Cell[BoxData["0.278333419659746`"], "Output",
 CellChangeTimes->{{3.530337197421713*^9, 3.530337199163272*^9}}],

Cell[BoxData["0.18580333675286043`"], "Output",
 CellChangeTimes->{{3.530337197421713*^9, 3.530337199167635*^9}}],

Cell[BoxData["0.4435349656234808`"], "Output",
 CellChangeTimes->{{3.530337197421713*^9, 3.5303371991720543`*^9}}],

Cell[BoxData["0.1265123264935557`"], "Output",
 CellChangeTimes->{{3.530337197421713*^9, 3.530337199176414*^9}}]
}, Open  ]],

Cell[TextData[{
 "Bei der Auswahl von Symbolnamen kann die farbliche Syntax-Vorhebung helfen: \
Bereits vergebene/gesetzte Namen werden schwarz, alle anderen blau \
dargestellt. Eingebaute ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " Funktionen oder Konstanten beginnen in der Regel mit einem \
Gro\[SZ]buchstaben (auch zur Trennung von Wortteilen im Funktionsnamen). Man \
ist folglich auf der sicheren Seite, wenn man immer mit einem Kleinbuchstaben \
beginnt (Symbolnamen sind \[OpenCurlyDoubleQuote]Case sensitive\
\[CloseCurlyDoubleQuote])."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52975707496774*^9, 3.52975709148726*^9}, {
   3.529757262562008*^9, 3.52975741599712*^9}, {3.5297578701313677`*^9, 
   3.529757990336257*^9}, {3.529758026946002*^9, 3.52975808506255*^9}, 
   3.5297730513737507`*^9, {3.5303340645573683`*^9, 3.530334089396057*^9}, {
   3.530334129801613*^9, 3.5303341301881123`*^9}, {3.530337235264893*^9, 
   3.5303372404342403`*^9}}],

Cell[BoxData[{
 RowBox[{"a", ";", "b", ";"}], "\[IndentingNewLine]", 
 RowBox[{"c", ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"SeedRandom", "[", "]"}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"seedRandom", "[", "]"}], ";"}]}], "Input",
 CellChangeTimes->{{3.529758557868072*^9, 3.52975862104111*^9}, 
   3.529773051373962*^9}],

Cell[TextData[{
 "Die Verwendung von ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 "-internen Sonderzeichen wie ",
 StyleBox["\[Alpha]", "Input"],
 ", ",
 StyleBox["\[Beta]", "Input"],
 ", ",
 StyleBox["\[Gamma]", "Input"],
 " usw. sollte aus Gr\[UDoubleDot]nden der Lesbarkeit, Benutzung anderer \
Editoren und Portierbarkeit von Code vermieden werden."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529758133789613*^9, 3.5297584627490253`*^9}, {
   3.529770435119555*^9, 3.52977043613139*^9}, 3.529773051374085*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{"a", ",", "b", ",", "c"}], "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.53034407273593*^9, 3.5303440769222097`*^9}}],

Cell[CellGroupData[{

Cell[TextData[StyleBox["Aufgabe",
 FontSlant->"Italic"]], "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297747600942793`*^9, 3.52977476232712*^9}}],

Cell[TextData[{
 "Probieren Sie \[OpenCurlyDoubleQuote]",
 StyleBox["d", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["D", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["e", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["E", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["0D", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["d0d", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["Im", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["d_", "Input"],
 "\[CloseCurlyDoubleQuote] als Variablennamen aus. Welche davon lassen sich \
verwenden und welche nicht? Warum ist das so?"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529774779213578*^9, 3.529774922915406*^9}, {
  3.530337344825742*^9, 3.5303373515042667`*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[TextData[StyleBox["L\[ODoubleDot]sung",
 FontSlant->"Italic"]], "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297749274270687`*^9, 3.529774937606641*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"d", "=", "123"}], "\[IndentingNewLine]", 
 RowBox[{"D", "=", "123"}], "\[IndentingNewLine]", 
 RowBox[{"e", "=", "123"}], "\[IndentingNewLine]", 
 RowBox[{"E", "=", "123"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"0", "D"}], "=", "123"}], "\[IndentingNewLine]", 
 RowBox[{"d0d", "=", "123"}], "\[IndentingNewLine]", 
 RowBox[{"Im", "=", "123"}], "\[IndentingNewLine]", 
 RowBox[{"d_", "=", "123"}]}], "Input",
 CellChangeTimes->{{3.5297749423931437`*^9, 3.529774973526827*^9}}],

Cell[BoxData["123"], "Output",
 CellChangeTimes->{
  3.529774974806003*^9, {3.53033735857423*^9, 3.530337361809376*^9}}],

Cell[BoxData[
 RowBox[{
  StyleBox[
   RowBox[{"Set", "::", "wrsym"}], "MessageName"], 
  RowBox[{
  ":", " "}], "\<\"Symbol \[NoBreak]\\!\\(D\\)\[NoBreak] is Protected. \\!\\(\
\\*ButtonBox[\\\"\[RightSkeleton]\\\", ButtonStyle->\\\"Link\\\", \
ButtonFrame->None, ButtonData:>\\\"paclet:ref/Set\\\", ButtonNote -> \
\\\"Set::wrsym\\\"]\\)\"\>"}]], "Message", "MSG",
 CellChangeTimes->{
  3.5297749748094673`*^9, {3.5303373585899487`*^9, 3.530337361828886*^9}}],

Cell[BoxData["123"], "Output",
 CellChangeTimes->{
  3.529774974806003*^9, {3.53033735857423*^9, 3.530337361839182*^9}}],

Cell[BoxData["123"], "Output",
 CellChangeTimes->{
  3.529774974806003*^9, {3.53033735857423*^9, 3.530337361849704*^9}}],

Cell[BoxData[
 RowBox[{
  StyleBox[
   RowBox[{"Set", "::", "wrsym"}], "MessageName"], 
  RowBox[{
  ":", " "}], "\<\"Symbol \[NoBreak]\\!\\(\[ExponentialE]\\)\[NoBreak] is \
Protected. \\!\\(\\*ButtonBox[\\\"\[RightSkeleton]\\\", ButtonStyle->\\\"Link\
\\\", ButtonFrame->None, ButtonData:>\\\"paclet:ref/Set\\\", ButtonNote -> \\\
\"Set::wrsym\\\"]\\)\"\>"}]], "Message", "MSG",
 CellChangeTimes->{
  3.5297749748094673`*^9, {3.5303373585899487`*^9, 3.530337361860856*^9}}],

Cell[BoxData["123"], "Output",
 CellChangeTimes->{
  3.529774974806003*^9, {3.53033735857423*^9, 3.5303373618710318`*^9}}],

Cell[BoxData[
 RowBox[{
  StyleBox[
   RowBox[{"Set", "::", "write"}], "MessageName"], 
  RowBox[{
  ":", " "}], "\<\"Tag \[NoBreak]\\!\\(Times\\)\[NoBreak] in \
\[NoBreak]\\!\\(0\\\\ D\\)\[NoBreak] is Protected. \\!\\(\\*ButtonBox[\\\"\
\[RightSkeleton]\\\", ButtonStyle->\\\"Link\\\", ButtonFrame->None, \
ButtonData:>\\\"paclet:ref/Set\\\", ButtonNote -> \
\\\"Set::write\\\"]\\)\"\>"}]], "Message", "MSG",
 CellChangeTimes->{
  3.5297749748094673`*^9, {3.5303373585899487`*^9, 3.5303373618820333`*^9}}],

Cell[BoxData["123"], "Output",
 CellChangeTimes->{
  3.529774974806003*^9, {3.53033735857423*^9, 3.530337361892112*^9}}],

Cell[BoxData["123"], "Output",
 CellChangeTimes->{
  3.529774974806003*^9, {3.53033735857423*^9, 3.530337361902512*^9}}],

Cell[BoxData[
 RowBox[{
  StyleBox[
   RowBox[{"Set", "::", "wrsym"}], "MessageName"], 
  RowBox[{
  ":", " "}], "\<\"Symbol \[NoBreak]\\!\\(Im\\)\[NoBreak] is Protected. \
\\!\\(\\*ButtonBox[\\\"\[RightSkeleton]\\\", ButtonStyle->\\\"Link\\\", \
ButtonFrame->None, ButtonData:>\\\"paclet:ref/Set\\\", ButtonNote -> \
\\\"Set::wrsym\\\"]\\)\"\>"}]], "Message", "MSG",
 CellChangeTimes->{
  3.5297749748094673`*^9, {3.5303373585899487`*^9, 3.530337361913541*^9}}],

Cell[BoxData["123"], "Output",
 CellChangeTimes->{
  3.529774974806003*^9, {3.53033735857423*^9, 3.5303373619186*^9}}],

Cell[BoxData[
 RowBox[{
  StyleBox[
   RowBox[{"Set", "::", "nosym"}], "MessageName"], 
  RowBox[{
  ":", " "}], "\<\"\[NoBreak]\\!\\(d_\\)\[NoBreak] does not contain a symbol \
to attach a rule to. \\!\\(\\*ButtonBox[\\\"\[RightSkeleton]\\\", \
ButtonStyle->\\\"Link\\\", ButtonFrame->None, \
ButtonData:>\\\"paclet:ref/Set\\\", ButtonNote -> \
\\\"Set::nosym\\\"]\\)\"\>"}]], "Message", "MSG",
 CellChangeTimes->{
  3.5297749748094673`*^9, {3.5303373585899487`*^9, 3.530337361924572*^9}}],

Cell[BoxData["123"], "Output",
 CellChangeTimes->{
  3.529774974806003*^9, {3.53033735857423*^9, 3.53033736192934*^9}}]
}, Open  ]],

Cell[TextData[{
 "Zul\[ADoubleDot]ssig (oder nicht \[OpenCurlyDoubleQuote]",
 StyleBox["Protected", "Input"],
 "\[CloseCurlyDoubleQuote]) sind nur \[OpenCurlyDoubleQuote]",
 StyleBox["d", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["e", "Input"],
 "\[CloseCurlyDoubleQuote] und \[OpenCurlyDoubleQuote]",
 StyleBox["d0d", "Input"],
 "\[CloseCurlyDoubleQuote]. \[OpenCurlyDoubleQuote]",
 StyleBox["D", "Input"],
 "\[CloseCurlyDoubleQuote] ist die Ableitungsfunktion, \
\[OpenCurlyDoubleQuote]",
 StyleBox["E", "Input"],
 "\[CloseCurlyDoubleQuote] die Euler Konstante, \[OpenCurlyDoubleQuote]",
 StyleBox["0d", "Input"],
 "\[CloseCurlyDoubleQuote] beginnt mit einer Ziffer, \
\[OpenCurlyDoubleQuote]",
 StyleBox["Im", "Input"],
 "\[OpenCurlyDoubleQuote] ist die Funktion f\[UDoubleDot]r den Imagin\
\[ADoubleDot]rteil und \[OpenCurlyDoubleQuote]",
 StyleBox["d_", "Input"],
 "\[CloseCurlyDoubleQuote] ist ein Pattern (kein g\[UDoubleDot]ltiger \
Symbolname)."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529775027482527*^9, 3.529775191841564*^9}, {
  3.53033741187504*^9, 3.53033742722546*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{"d", ",", "e", ",", "d0d"}], "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.530344099428894*^9, 3.5303441107468863`*^9}}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["1.4 Der \[OpenCurlyDoubleQuote]Kernel\[CloseCurlyDoubleQuote]", \
"Subsubtitle",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297590979861727`*^9, 3.5297591021145573`*^9}, {
   3.529759440074375*^9, 3.529759442451075*^9}, 3.5297730513742743`*^9}],

Cell[TextData[{
 "Sobald Sie ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " starten, sei es durch \[CapitalODoubleDot]ffnen eines Notebooks oder durch \
Aufruf in einem Konsolenfenster, wird ein \[OpenCurlyDoubleQuote]Kernel\
\[CloseCurlyDoubleQuote] gestartet. Jeder Aufruf einer Funktion, jede \
Auswertung, das Speichern von Werten oder Definitionen usw. wird vom Kernel (\
\[OpenCurlyDoubleQuote]Backend\[CloseCurlyDoubleQuote]) \
\[UDoubleDot]bernommen. Das Interface in dem Sie sich gerade dieses Notebook \
anschaunen ist das sog. \[OpenCurlyDoubleQuote]Frontend\
\[CloseCurlyDoubleQuote], es dient lediglich zur angenehmeren Darstellung von \
Ergebnissen und der \[CapitalUDoubleDot]bergabe von Eingaben an den Kernel."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529759291695671*^9, 3.5297593918027143`*^9}, {
   3.529759464492708*^9, 3.5297594815714073`*^9}, {3.529759538418026*^9, 
   3.529759863222599*^9}, 3.529773051374401*^9}],

Cell[TextData[{
 "Wenn Sie eine Definition oder einen Wert aus dem aktuellen Zustand des \
Kernels l\[ODoubleDot]schen wollen, helfen Ihnen die Befehle ",
 StyleBox["Clear[<Liste von Symbolen>]", "Input"],
 " oder",
 StyleBox[" ClearAll", "Input"],
 "."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297599056284437`*^9, 3.529760195330166*^9}, 
   3.52976079716825*^9, {3.529770464079427*^9, 3.529770465032073*^9}, 
   3.529773051374507*^9}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"a", ":=", "11"}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"b", "=", "10"}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"c", ":=", 
   RowBox[{"a", "+", "b"}]}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"Print", "[", 
   RowBox[{"a", ",", "\"\< \>\"", ",", "b", ",", "\"\< \>\"", ",", "c"}], 
   "]"}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"Clear", "[", "b", "]"}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"Print", "[", 
   RowBox[{"a", ",", "\"\< \>\"", ",", "b", ",", "\"\< \>\"", ",", "c"}], 
   "]"}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"Clear", "[", "a", "]"}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"Print", "[", 
   RowBox[{"a", ",", "\"\< \>\"", ",", "b", ",", "\"\< \>\"", ",", "c"}], 
   "]"}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"Clear", "[", "c", "]"}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"Print", "[", 
   RowBox[{"a", ",", "\"\< \>\"", ",", "b", ",", "\"\< \>\"", ",", "c"}], 
   "]"}], ";"}]}], "Input",
 CellChangeTimes->{{3.529760226141128*^9, 3.5297604807772703`*^9}, {
   3.529760666841454*^9, 3.529760667039885*^9}, 3.529773051374908*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 InterpretationBox[
  RowBox[{
  "11", "\[InvisibleSpace]", "\<\" \"\>", "\[InvisibleSpace]", "10", 
   "\[InvisibleSpace]", "\<\" \"\>", "\[InvisibleSpace]", "21"}],
  SequenceForm[11, " ", 10, " ", 21],
  Editable->False]], "Print",
 CellChangeTimes->{{3.530337558023662*^9, 3.530337559650318*^9}}],

Cell[BoxData[
 InterpretationBox[
  RowBox[{
  "11", "\[InvisibleSpace]", "\<\" \"\>", "\[InvisibleSpace]", "b", 
   "\[InvisibleSpace]", "\<\" \"\>", "\[InvisibleSpace]", 
   RowBox[{"11", "+", "b"}]}],
  SequenceForm[11, " ", $CellContext`b, " ", 11 + $CellContext`b],
  Editable->False]], "Print",
 CellChangeTimes->{{3.530337558023662*^9, 3.530337559668376*^9}}],

Cell[BoxData[
 InterpretationBox[
  RowBox[{
  "a", "\[InvisibleSpace]", "\<\" \"\>", "\[InvisibleSpace]", "b", 
   "\[InvisibleSpace]", "\<\" \"\>", "\[InvisibleSpace]", 
   RowBox[{"a", "+", "b"}]}],
  SequenceForm[$CellContext`a, " ", $CellContext`b, 
   " ", $CellContext`a + $CellContext`b],
  Editable->False]], "Print",
 CellChangeTimes->{{3.530337558023662*^9, 3.530337559674775*^9}}],

Cell[BoxData[
 InterpretationBox[
  RowBox[{
  "a", "\[InvisibleSpace]", "\<\" \"\>", "\[InvisibleSpace]", "b", 
   "\[InvisibleSpace]", "\<\" \"\>", "\[InvisibleSpace]", "c"}],
  SequenceForm[$CellContext`a, " ", $CellContext`b, " ", $CellContext`c],
  Editable->False]], "Print",
 CellChangeTimes->{{3.530337558023662*^9, 3.5303375596813993`*^9}}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"a", ":=", "11"}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"b", "=", "10"}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"c", ":=", 
   RowBox[{"a", "+", "b"}]}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"Print", "[", 
   RowBox[{"a", ",", "\"\< \>\"", ",", "b", ",", "\"\< \>\"", ",", "c"}], 
   "]"}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"Clear", "[", "c", "]"}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"Print", "[", 
   RowBox[{"a", ",", "\"\< \>\"", ",", "b", ",", "\"\< \>\"", ",", "c"}], 
   "]"}], ";"}]}], "Input",
 CellChangeTimes->{{3.529760226141128*^9, 3.529760547475607*^9}, {
   3.529760673489504*^9, 3.529760673680419*^9}, 3.5297730513758297`*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 InterpretationBox[
  RowBox[{
  "11", "\[InvisibleSpace]", "\<\" \"\>", "\[InvisibleSpace]", "10", 
   "\[InvisibleSpace]", "\<\" \"\>", "\[InvisibleSpace]", "21"}],
  SequenceForm[11, " ", 10, " ", 21],
  Editable->False]], "Print",
 CellChangeTimes->{{3.530337560443071*^9, 3.530337563011375*^9}}],

Cell[BoxData[
 InterpretationBox[
  RowBox[{
  "11", "\[InvisibleSpace]", "\<\" \"\>", "\[InvisibleSpace]", "10", 
   "\[InvisibleSpace]", "\<\" \"\>", "\[InvisibleSpace]", "c"}],
  SequenceForm[11, " ", 10, " ", $CellContext`c],
  Editable->False]], "Print",
 CellChangeTimes->{{3.530337560443071*^9, 3.530337563017879*^9}}]
}, Open  ]]
}, Open  ]],

Cell[TextData[{
 "Um ganz sicher zu gehen, mit einem \[OpenCurlyDoubleQuote]frischen\
\[CloseCurlyDoubleQuote] Kernel zu arbeiten, l\[ADoubleDot]sst sich dieser \
\[UDoubleDot]ber \[OpenCurlyDoubleQuote]Evaluation -> Quit Kernel -> Local\
\[CloseCurlyDoubleQuote] beenden. Alternativ kann auch der Befehl ",
 StyleBox["Quit[]", "Input"],
 " eingegeben werden. Eine neue Instanz des Kernels startet dann bei Ausf\
\[UDoubleDot]hren des n\[ADoubleDot]chsten Befehls. ",
 StyleBox["Achtung",
  FontSlant->"Italic"],
 ": alle bis dahin gespeicherten Ausdr\[UDoubleDot]cke verschwinden dadurch \
aus dem Speicher!"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297609135101767`*^9, 3.529761234871277*^9}, 
   3.529773051376254*^9, {3.530337616747136*^9, 3.530337618611779*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{"a", ",", "b", ",", "c"}], "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.53034413926096*^9, 3.530344145319668*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell["1.5 Listen", "Subsubtitle",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529770574437111*^9, 3.529770579221714*^9}, 
   3.529773051376411*^9}],

Cell[TextData[{
 "Ausdr\[UDoubleDot]cke haben in ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " keinen festen Datentyp wie in anderen Programmiersprachen, sondern sind \
Typ-frei. Variablen k\[ODoubleDot]nnen also ohne Einschr\[ADoubleDot]nkung \
Zahlen- oder Stringwerte, Definitionen oder Ausdr\[UDoubleDot]cke zugewiesen \
werden. Das wichtigste fehlende Konstrukt sind Listen, die in \
\[OpenCurlyDoubleQuote]",
 StyleBox["{", "Input"],
 "\[OpenCurlyDoubleQuote] und \[OpenCurlyDoubleQuote]",
 StyleBox["}", "Input"],
 "\[CloseCurlyDoubleQuote] eingefasst und deren Elemente durch Kommas \
\[OpenCurlyDoubleQuote]",
 StyleBox[",", "Input"],
 "\[CloseCurlyDoubleQuote] voneinander getrennt werden. Listenelemente k\
\[ODoubleDot]nnen nun wiederum beliebig kompliziert konstruiert werden. \
Insbesondere k\[ODoubleDot]nnen die einzelnen Listenelemente unterschiedlich \
aufgebaut werden, was den wichtigsten Unterschied zu einfachen Arrays \
darstellt, deren Elemente immer desselben Typs sind."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52982996966669*^9, 3.529830050661449*^9}, {
   3.5298301256976347`*^9, 3.529830179346147*^9}, {3.529830212232257*^9, 
   3.529830404898897*^9}, {3.529830445741592*^9, 3.529830503875929*^9}, {
   3.5298305378828583`*^9, 3.529830558986567*^9}, {3.52983060035525*^9, 
   3.5298307325036983`*^9}, 3.530337697223444*^9}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"liste1", "=", 
  RowBox[{"{", 
   RowBox[{"1", ",", "3", ",", "2", ",", "4"}], 
   "}"}]}], "\[IndentingNewLine]", 
 RowBox[{"liste2", "=", 
  RowBox[{"{", 
   RowBox[{"a", ",", "b", ",", "c"}], "}"}]}], "\[IndentingNewLine]", 
 RowBox[{"liste3", "=", 
  RowBox[{"{", 
   RowBox[{"1", ",", "a", ",", "\"\<strg\>\""}], 
   "}"}]}], "\[IndentingNewLine]", 
 RowBox[{"liste4", "=", 
  RowBox[{"{", 
   RowBox[{"d", ",", "liste3"}], "}"}]}]}], "Input",
 CellChangeTimes->{{3.529830760262662*^9, 3.529830859937476*^9}, {
  3.5304267333579597`*^9, 3.5304267481658773`*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"1", ",", "3", ",", "2", ",", "4"}], "}"}]], "Output",
 CellChangeTimes->{
  3.529830860504201*^9, 3.530251932578223*^9, {3.530337731296938*^9, 
   3.530337733444107*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"11", ",", "10", ",", "c"}], "}"}]], "Output",
 CellChangeTimes->{
  3.529830860504201*^9, 3.530251932578223*^9, {3.530337731296938*^9, 
   3.530337733450087*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"1", ",", "11", ",", "\<\"strg\"\>"}], "}"}]], "Output",
 CellChangeTimes->{
  3.529830860504201*^9, 3.530251932578223*^9, {3.530337731296938*^9, 
   3.530337733454672*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"123", ",", 
   RowBox[{"{", 
    RowBox[{"1", ",", "11", ",", "\<\"strg\"\>"}], "}"}]}], "}"}]], "Output",
 CellChangeTimes->{
  3.529830860504201*^9, 3.530251932578223*^9, {3.530337731296938*^9, 
   3.530337733459206*^9}}]
}, Open  ]],

Cell[TextData[{
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " bietet zahlreiche Funktionen f\[UDoubleDot]r den Umgang mit Listen, siehe ",
 Cell[BoxData[
  FormBox[
   ButtonBox[
    RowBox[{"List", " ", "Manipulation"}],
    BaseStyle->"Link",
    ButtonData->"paclet:guide/ListManipulation"], TextForm]]],
 "."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5298315427010107`*^9, 3.5298315817198553`*^9}, {
  3.529831621966662*^9, 3.52983165389819*^9}, {3.529831688110125*^9, 
  3.529831689468412*^9}, {3.5298334250117693`*^9, 3.529833440358917*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"Generierung", " ", "von", " ", "Listen"}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"Table", "[", 
    RowBox[{
     RowBox[{"10", "-", "i"}], ",", 
     RowBox[{"{", 
      RowBox[{"i", ",", "1", ",", "10"}], "}"}]}], "]"}], 
   "\[IndentingNewLine]", 
   RowBox[{"Table", "[", 
    RowBox[{
     RowBox[{"i", "*", "j"}], ",", 
     RowBox[{"{", 
      RowBox[{"i", ",", "1", ",", "3"}], "}"}], ",", 
     RowBox[{"{", 
      RowBox[{"j", ",", "1", ",", "3"}], "}"}]}], "]"}]}]}]], "Input",
 CellChangeTimes->{{3.5298316953616257`*^9, 3.529831771961241*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
  "9", ",", "8", ",", "7", ",", "6", ",", "5", ",", "4", ",", "3", ",", "2", 
   ",", "1", ",", "0"}], "}"}]], "Output",
 CellChangeTimes->{{3.529831724733609*^9, 3.5298317724187717`*^9}, 
   3.53033774282854*^9}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{"1", ",", "2", ",", "3"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"2", ",", "4", ",", "6"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"3", ",", "6", ",", "9"}], "}"}]}], "}"}]], "Output",
 CellChangeTimes->{{3.529831724733609*^9, 3.5298317724187717`*^9}, 
   3.53033774283462*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"Operationen", " ", "auf", " ", "Listen"}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{
    RowBox[{"liste1", "=", 
     RowBox[{"{", 
      RowBox[{"1", ",", "2", ",", "3"}], "}"}]}], ";"}], 
   "\[IndentingNewLine]", 
   RowBox[{
    RowBox[{"liste2", "=", 
     RowBox[{"{", 
      RowBox[{"4", ",", "5"}], "}"}]}], ";"}]}]}]], "Input",
 CellChangeTimes->{{3.529831793766492*^9, 3.529831866476795*^9}, {
  3.529831917289907*^9, 3.529831984825498*^9}, {3.529832064407311*^9, 
  3.529832090538495*^9}, {3.52983212555575*^9, 3.529832156295846*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", "Aneinanderh\[ADoubleDot]ngen", " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{"liste5", "=", 
   RowBox[{"Join", "[", 
    RowBox[{"liste1", ",", "liste2"}], "]"}]}]}]], "Input",
 CellChangeTimes->{{3.529831793766492*^9, 3.529831866476795*^9}, {
   3.529831917289907*^9, 3.529831984825498*^9}, {3.529832064407311*^9, 
   3.529832090538495*^9}, {3.52983212555575*^9, 3.529832158530424*^9}, {
   3.529832245274631*^9, 3.529832251614353*^9}, 3.529833048196052*^9}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"1", ",", "2", ",", "3", ",", "4", ",", "5"}], "}"}]], "Output",
 CellChangeTimes->{3.5298321663013573`*^9, 3.529832252819662*^9, 
  3.52983319444775*^9, 3.5303377448568983`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"Anf\[UDoubleDot]gen", " ", "eines", " ", "Elements"}], " ", 
   "*)"}], "\[IndentingNewLine]", 
  RowBox[{"Append", "[", 
   RowBox[{"liste2", ",", "6"}], "]"}]}]], "Input",
 CellChangeTimes->{{3.529831793766492*^9, 3.529831866476795*^9}, {
  3.529831917289907*^9, 3.529831984825498*^9}, {3.529832064407311*^9, 
  3.529832090538495*^9}, {3.52983212555575*^9, 3.529832160420443*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"4", ",", "5", ",", "6"}], "}"}]], "Output",
 CellChangeTimes->{3.529832167007077*^9, 3.529833195173501*^9, 
  3.530337746057729*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"Herausgreifen", " ", "eines", " ", "Bereichs"}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{"Take", "[", 
   RowBox[{"liste5", ",", "4"}], "]"}]}]], "Input",
 CellChangeTimes->{{3.5298322070372562`*^9, 3.5298322917348223`*^9}, {
   3.5298324791467037`*^9, 3.5298324802024183`*^9}, 3.529833064273987*^9}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"1", ",", "2", ",", "3", ",", "4"}], "}"}]], "Output",
 CellChangeTimes->{
  3.5298322245857363`*^9, {3.529832263086525*^9, 3.5298322672645683`*^9}, 
   3.5298331961725187`*^9, 3.530337746947976*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"L\[ADoubleDot]nge", " ", "=", " ", 
    RowBox[{"Anzahl", " ", "der", " ", "Elemente"}]}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{"Length", "[", "liste5", "]"}]}]], "Input",
 CellChangeTimes->{{3.529831793766492*^9, 3.529831866476795*^9}, {
   3.529831917289907*^9, 3.529831984825498*^9}, {3.529832064407311*^9, 
   3.529832090538495*^9}, {3.52983212555575*^9, 3.5298321614325647`*^9}, 
   3.5298323302456417`*^9, 3.529833067805296*^9}],

Cell[BoxData["5"], "Output",
 CellChangeTimes->{3.529832168169325*^9, 3.529832330829919*^9, 
  3.529833197304447*^9, 3.530337748126205*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"Zugriff", " ", "auf", " ", "Elemente"}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"First", "[", "liste5", "]"}], "\[IndentingNewLine]", 
   RowBox[{"Part", "[", 
    RowBox[{"liste5", ",", "3"}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"Last", "[", "liste5", "]"}]}]}]], "Input",
 CellChangeTimes->{{3.5298321772730503`*^9, 3.5298321839326553`*^9}, {
  3.529832299744404*^9, 3.529832328366468*^9}, {3.5298330690559673`*^9, 
  3.5298330699350147`*^9}, {3.529833556941732*^9, 3.529833563257172*^9}}],

Cell[BoxData["1"], "Output",
 CellChangeTimes->{{3.529832305028619*^9, 3.5298323315891733`*^9}, 
   3.529833197920034*^9, {3.529833563506077*^9, 3.529833577382223*^9}, 
   3.530337749294628*^9}],

Cell[BoxData["3"], "Output",
 CellChangeTimes->{{3.529832305028619*^9, 3.5298323315891733`*^9}, 
   3.529833197920034*^9, {3.529833563506077*^9, 3.529833577382223*^9}, 
   3.530337749299883*^9}],

Cell[BoxData["5"], "Output",
 CellChangeTimes->{{3.529832305028619*^9, 3.5298323315891733`*^9}, 
   3.529833197920034*^9, {3.529833563506077*^9, 3.529833577382223*^9}, 
   3.530337749303873*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"alternativer", " ", "Zugriff", " ", "auf", " ", "Elemente"}], " ",
    "*)"}], "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"liste5", "[", 
    RowBox[{"[", "1", "]"}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"liste5", "[", 
    RowBox[{"[", "3", "]"}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"liste5", "[", 
    RowBox[{"[", "5", "]"}], "]"}]}]}]], "Input",
 CellChangeTimes->{{3.529832500619175*^9, 3.529832542617009*^9}, {
   3.529833071317227*^9, 3.5298330720998507`*^9}, {3.529833565506296*^9, 
   3.52983357221712*^9}, 3.530337763743938*^9}],

Cell[BoxData["1"], "Output",
 CellChangeTimes->{{3.529832529019665*^9, 3.529832542939633*^9}, 
   3.529833198677719*^9, 3.5298335780254993`*^9, 3.5303377519949837`*^9, 
   3.5303377979819593`*^9}],

Cell[BoxData["3"], "Output",
 CellChangeTimes->{{3.529832529019665*^9, 3.529832542939633*^9}, 
   3.529833198677719*^9, 3.5298335780254993`*^9, 3.5303377519949837`*^9, 
   3.530337797987586*^9}],

Cell[BoxData["5"], "Output",
 CellChangeTimes->{{3.529832529019665*^9, 3.529832542939633*^9}, 
   3.529833198677719*^9, 3.5298335780254993`*^9, 3.5303377519949837`*^9, 
   3.530337797991968*^9}]
}, Open  ]],

Cell[TextData[{
 StyleBox["Beachte",
  FontSlant->"Italic"],
 ": Einfache eckige Klammern \[OpenCurlyDoubleQuote]",
 StyleBox["[...]", "Input"],
 "\[CloseCurlyDoubleQuote] = Parameter\[UDoubleDot]bergabe an Funktionen, \
doppelte eckige Klammern \[OpenCurlyDoubleQuote]",
 StyleBox["[[...]]", "Input"],
 "\[CloseCurlyDoubleQuote] = Elementzugriff! Im Gegensatz zu den meisten \
Programmiersprachen befindet sich bei ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " das erste zugewiesene Listenelement nicht in ",
 StyleBox["<Liste>[[0]]", "Input"],
 " (zu dessen Bedeutung sp\[ADoubleDot]ter), sondern gem\[ADoubleDot]\[SZ] \
Intuition in ",
 StyleBox["<Liste>[[1]]", "Input"],
 "!"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529832549109166*^9, 3.529832835302505*^9}, {
  3.529833134002098*^9, 3.5298331693556957`*^9}}],

Cell["\<\
Um nur einige der weiteren Listenoperationen zu demonstrieren:\
\>", "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5298328880288763`*^9, 3.529832937441543*^9}, {
  3.52983348671215*^9, 3.5298334883654127`*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{
   "erzeuge", " ", "20", " ", "Zufallszahlen", " ", "von", " ", "0", " ", 
    "bis", " ", "100"}], " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{"liste6", "=", 
   RowBox[{"Table", "[", 
    RowBox[{
     RowBox[{"RandomInteger", "[", "100", "]"}], ",", 
     RowBox[{"{", "20", "}"}]}], "]"}]}]}]], "Input",
 CellChangeTimes->{{3.52983320478946*^9, 3.52983326816718*^9}, 
   3.530337885332878*^9}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
  "2", ",", "19", ",", "21", ",", "13", ",", "46", ",", "33", ",", "14", ",", 
   "48", ",", "39", ",", "89", ",", "39", ",", "84", ",", "83", ",", "55", 
   ",", "8", ",", "1", ",", "94", ",", "77", ",", "0", ",", "29"}], 
  "}"}]], "Output",
 CellChangeTimes->{{3.529833233835994*^9, 3.529833270843252*^9}, 
   3.530251891512335*^9, {3.530337871636571*^9, 3.530337896105324*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", "Sortieren", " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{"liste6", "=", 
   RowBox[{"Sort", "[", "liste6", "]"}]}]}]], "Input",
 CellChangeTimes->{{3.529832357584099*^9, 3.529832358021253*^9}, {
   3.529832941181535*^9, 3.529832965724236*^9}, 3.529833177264016*^9, {
   3.529833274092908*^9, 3.529833291484939*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
  "20", ",", "30", ",", "37", ",", "39", ",", "45", ",", "47", ",", "49", ",",
    "49", ",", "52", ",", "58", ",", "61", ",", "62", ",", "69", ",", "73", 
   ",", "76", ",", "77", ",", "80", ",", "85", ",", "92", ",", "93"}], 
  "}"}]], "Output",
 CellChangeTimes->{{3.529833276421735*^9, 3.529833292079961*^9}, 
   3.53033787276754*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"Umkehren", " ", "der", " ", "Reihenfolge"}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{"Reverse", "[", "liste6", "]"}]}]], "Input",
 CellChangeTimes->{{3.5298323964380703`*^9, 3.529832397587166*^9}, {
  3.529833295563229*^9, 3.5298333088248034`*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
  "93", ",", "92", ",", "85", ",", "80", ",", "77", ",", "76", ",", "73", ",",
    "69", ",", "62", ",", "61", ",", "58", ",", "52", ",", "49", ",", "49", 
   ",", "47", ",", "45", ",", "39", ",", "37", ",", "30", ",", "20"}], 
  "}"}]], "Output",
 CellChangeTimes->{3.529833309092463*^9, 3.530337874004312*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{
   "Aufl\[ODoubleDot]sen", " ", "verschachtelter", " ", "Listenstrukturen"}], 
   " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{"liste4", "\[IndentingNewLine]", 
   RowBox[{"Flatten", "[", "liste4", "]"}]}]}]], "Input",
 CellChangeTimes->{{3.529832359065399*^9, 3.5298323632440987`*^9}, {
  3.5298333127707777`*^9, 3.5298333788346157`*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"123", ",", 
   RowBox[{"{", 
    RowBox[{"1", ",", "11", ",", "\<\"strg\"\>"}], "}"}]}], "}"}]], "Output",
 CellChangeTimes->{3.529833327703672*^9, 3.530337874955347*^9}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"123", ",", "1", ",", "11", ",", "\<\"strg\"\>"}], "}"}]], "Output",\

 CellChangeTimes->{3.529833327703672*^9, 3.5303378749611187`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{
   "Funktion", " ", "zur", " ", "angehmeren", " ", "Darstellung", " ", "auch",
     " ", "verschachtelter", " ", 
    RowBox[{"Listen", "/", "Tabellen"}]}], " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{"TableForm", "[", "liste6", "]"}]}]], "Input",
 CellChangeTimes->{{3.530251854394429*^9, 3.530251922400484*^9}, {
  3.530251961057269*^9, 3.5302519725917253`*^9}, {3.5303121996860027`*^9, 
  3.5303122027434072`*^9}}],

Cell[BoxData[
 TagBox[
  TagBox[GridBox[{
     {"20"},
     {"30"},
     {"37"},
     {"39"},
     {"45"},
     {"47"},
     {"49"},
     {"49"},
     {"52"},
     {"58"},
     {"61"},
     {"62"},
     {"69"},
     {"73"},
     {"76"},
     {"77"},
     {"80"},
     {"85"},
     {"92"},
     {"93"}
    },
    GridBoxAlignment->{
     "Columns" -> {{Left}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}}, 
      "RowsIndexed" -> {}},
    GridBoxSpacings->{"Columns" -> {
        Offset[0.27999999999999997`], {
         Offset[0.5599999999999999]}, 
        Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
        Offset[0.2], {
         Offset[0.4]}, 
        Offset[0.2]}, "RowsIndexed" -> {}}],
   Column],
  Function[BoxForm`e$, 
   TableForm[BoxForm`e$]]]], "Output",
 CellChangeTimes->{{3.530251902843354*^9, 3.530251973057123*^9}, 
   3.530337879341572*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{
   "liste1", ",", "liste2", ",", "liste3", ",", "liste4", ",", "liste5", ",", 
    "liste6"}], "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.530344177643702*^9, 3.530344191158703*^9}}],

Cell[CellGroupData[{

Cell[TextData[StyleBox["Aufgabe",
 FontSlant->"Italic"]], "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529833622938807*^9, 3.52983362405859*^9}}],

Cell[TextData[{
 "Generieren Sie eine Liste von beliebig vielen (",
 StyleBox["n=1000", "Input"],
 ") ganzen Zahlen von 0 bis 100 und erzeugen Sie hieraus eine Liste der \
Zahlen die gerade sind (",
 StyleBox["EvenQ", "Input"],
 ")!"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529833692596896*^9, 3.529833695202927*^9}, {
  3.52983376681222*^9, 3.529833879055909*^9}, {3.52983395179139*^9, 
  3.529833952623743*^9}, {3.529834003366561*^9, 3.529834004790514*^9}, {
  3.5298340877620287`*^9, 3.5298341212774553`*^9}, {3.5298342185913467`*^9, 
  3.529834259069395*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[TextData[StyleBox["L\[ODoubleDot]sung",
 FontSlant->"Italic"]], "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5298336268014936`*^9, 3.529833631189019*^9}}],

Cell[TextData[{
 "(Hier helfen ",
 Cell[BoxData[
  ButtonBox["Select",
   BaseStyle->"Link",
   ButtonData->"paclet:ref/Select"]]],
 " und ",
 Cell[BoxData[
  ButtonBox["EvenQ",
   BaseStyle->"Link",
   ButtonData->"paclet:ref/EvenQ"]]],
 ")"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530337967064577*^9, 3.530338013662266*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"n", "=", "100"}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{"randNrs", "=", 
    RowBox[{"Table", "[", 
     RowBox[{
      RowBox[{"RandomInteger", "[", "100", "]"}], ",", 
      RowBox[{"{", "n", "}"}]}], "]"}]}], ";"}], "\[IndentingNewLine]", 
  RowBox[{"(*", " ", "easier", " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{"(*", 
   RowBox[{
    RowBox[{"randNrs", "=", 
     RowBox[{"RandomInteger", "[", 
      RowBox[{"100", ",", "n"}], "]"}]}], ";"}], 
   "*)"}]}], "\[IndentingNewLine]", 
 RowBox[{"evenNrs", "=", 
  RowBox[{"Select", "[", 
   RowBox[{"randNrs", ",", "EvenQ"}], "]"}]}]}], "Input",
 CellChangeTimes->{{3.529833886079237*^9, 3.529834042639656*^9}, {
  3.529834234809314*^9, 3.5298343746988373`*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
  "96", ",", "38", ",", "4", ",", "74", ",", "18", ",", "34", ",", "82", ",", 
   "98", ",", "84", ",", "40", ",", "82", ",", "14", ",", "36", ",", "78", 
   ",", "56", ",", "50", ",", "90", ",", "64", ",", "32", ",", "34", ",", 
   "54", ",", "50", ",", "84", ",", "48", ",", "28", ",", "82", ",", "88", 
   ",", "44", ",", "60", ",", "88", ",", "46", ",", "46", ",", "84", ",", "8",
    ",", "22", ",", "70", ",", "98", ",", "0", ",", "24", ",", "4", ",", "38",
    ",", "40", ",", "76", ",", "80", ",", "6", ",", "30", ",", "8", ",", "44",
    ",", "32"}], "}"}]], "Output",
 CellChangeTimes->{{3.52983402245654*^9, 3.529834043132078*^9}, {
   3.529834292113098*^9, 3.529834304135796*^9}, {3.52983433737731*^9, 
   3.529834376365296*^9}, 3.530337942951064*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{"n", ",", "randNrs", ",", "evenNrs"}], "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.5303441957902603`*^9, 3.530344210331119*^9}}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["1.6 Regeln und Ersetzungen", "Subsubtitle",
 CellChangeTimes->{{3.529770581260783*^9, 3.529770583279516*^9}, 
   3.529773051376573*^9, {3.529829318092561*^9, 3.529829322314672*^9}}],

Cell[TextData[{
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " bietet analog zum \[OpenCurlyDoubleQuote]Rechnen mit Papier und Bleisift\
\[CloseCurlyDoubleQuote] die M\[ODoubleDot]glichkeit, Symbole oder sogar \
ganze Unterausdr\[UDoubleDot]cke (sp\[ADoubleDot]ter) in \
Ausdr\[UDoubleDot]cken durch andere zu ersetzen/substituieren. Formal wird \
das durch die Anwendung einer Ersetzungsregel auf einen Ausdruck erreicht. \
Ersetzungsregeln sowie nat\[UDoubleDot]rlich Ergebnisse einer Substitution k\
\[ODoubleDot]nnen in Variablen/Symbolen gespeichert werden. Folgende Syntax \
gilt es einzuhalten:"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5298346584805307`*^9, 3.529834795868228*^9}, {
  3.529835333121469*^9, 3.52983553555931*^9}, {3.5298355805755463`*^9, 
  3.529835778861347*^9}, {3.530338340013083*^9, 3.530338361977755*^9}}],

Cell[TextData[{
 StyleBox["<Ersetzungsregel> = <alter_Unterausdr.> -> <neuer_Unterausdr.>", 
  "Input"],
 "\nwobei\n",
 StyleBox["<Ausdruck> /. <Ersetzungsregel>", "Input"],
 "\noder auch direkt:\n",
 StyleBox["<Ausdruck> /. <alter_Unterausdr.> -> <neuer_Unterausdr.>", 
  "Input"]
}], "Text",
 CellChangeTimes->{{3.529835782688017*^9, 3.52983581946529*^9}, {
  3.529836278662591*^9, 3.529836394477687*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"f", "=", 
   RowBox[{"1", "+", 
    RowBox[{"x", "^", "2"}]}]}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"regel", "=", 
   RowBox[{"(", 
    RowBox[{"x", "\[Rule]", 
     RowBox[{"x", "+", "1"}]}], ")"}]}], ";"}], "\[IndentingNewLine]", 
 RowBox[{"g", "=", 
  RowBox[{"f", "/.", "regel"}]}]}], "Input",
 CellChangeTimes->{{3.5298361991331377`*^9, 3.529836253155437*^9}}],

Cell[BoxData[
 RowBox[{"1", "+", 
  SuperscriptBox[
   RowBox[{"(", 
    RowBox[{"1", "+", "x"}], ")"}], "2"]}]], "Output",
 CellChangeTimes->{3.529836254176731*^9, 3.530338129407921*^9, 
  3.530338296513526*^9}]
}, Open  ]],

Cell[TextData[{
 "Mehrere Ersetzungen k\[ODoubleDot]nnen auch gleichzeitig angewandt werden, \
indem man sie in einer Liste zusammenfasst. Durch Verwendung von \
\[OpenCurlyDoubleQuote]",
 StyleBox["//.", "Input"],
 "\[CloseCurlyDoubleQuote] erreicht man es, dass die Ersetzung(en) solange \
vorgenommen werden, bis keine der Regeln mehr greift. \[OpenCurlyDoubleQuote]",
 StyleBox[":>", "Input"],
 "\[CloseCurlyDoubleQuote] hat eine \[ADoubleDot]hnliche Wirkung wie \
\[OpenCurlyDoubleQuote]",
 StyleBox[":=", "Input"],
 "\[CloseCurlyDoubleQuote] im Vergleich von \[OpenCurlyDoubleQuote]",
 StyleBox["->", "Input"],
 "\[CloseCurlyDoubleQuote] zu \[OpenCurlyDoubleQuote]",
 StyleBox["=", "Input"],
 "\[CloseCurlyDoubleQuote]: die rechte Seite der Regel wird bei jeder tats\
\[ADoubleDot]chlichen Subsitution neu ausgwertet."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5298358579056*^9, 3.529836183049614*^9}, {
  3.5303384206630163`*^9, 3.530338421049027*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"f", "=", 
   RowBox[{
    RowBox[{"x", "^", "2"}], "+", 
    RowBox[{"y", "^", "2"}]}]}], ";"}], "\[IndentingNewLine]", 
 RowBox[{"g", "=", 
  RowBox[{"f", "/.", 
   RowBox[{"{", 
    RowBox[{
     RowBox[{"x", "\[Rule]", 
      RowBox[{"r", "*", 
       RowBox[{"Cos", "[", "phi", "]"}]}]}], ",", 
     RowBox[{"y", "\[Rule]", 
      RowBox[{"r", "*", 
       RowBox[{"Sin", "[", "phi", "]"}]}]}]}], "}"}]}]}]}], "Input",
 CellChangeTimes->{{3.5298364094730673`*^9, 3.5298364823767033`*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   SuperscriptBox["r", "2"], " ", 
   SuperscriptBox[
    RowBox[{"Cos", "[", "phi", "]"}], "2"]}], "+", 
  RowBox[{
   SuperscriptBox["r", "2"], " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "phi", "]"}], "2"]}]}]], "Output",
 CellChangeTimes->{{3.529836473090808*^9, 3.529836482794091*^9}, 
   3.5303381329188547`*^9, 3.530338303605546*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"f", "=", "x"}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"regel", "=", 
   RowBox[{"{", 
    RowBox[{
     RowBox[{"x", "\[Rule]", "y"}], ",", 
     RowBox[{"y", "\[Rule]", "z"}]}], "}"}]}], ";"}], "\[IndentingNewLine]", 
 RowBox[{"f", "/.", "regel"}], "\[IndentingNewLine]", 
 RowBox[{"f", "//.", "regel"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"f", "/.", "regel"}], "/.", "regel"}]}], "Input",
 CellChangeTimes->{{3.5298365105333*^9, 3.529836634175104*^9}}],

Cell[BoxData["y"], "Output",
 CellChangeTimes->{
  3.52983655037339*^9, {3.529836585432851*^9, 3.5298366251064577`*^9}, {
   3.53033813368248*^9, 3.530338142243094*^9}, 3.5303383119416723`*^9}],

Cell[BoxData["z"], "Output",
 CellChangeTimes->{
  3.52983655037339*^9, {3.529836585432851*^9, 3.5298366251064577`*^9}, {
   3.53033813368248*^9, 3.530338142243094*^9}, 3.5303383119569817`*^9}],

Cell[BoxData["z"], "Output",
 CellChangeTimes->{
  3.52983655037339*^9, {3.529836585432851*^9, 3.5298366251064577`*^9}, {
   3.53033813368248*^9, 3.530338142243094*^9}, 3.530338311966086*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{
   "f", ",", "x", ",", "regel", ",", "g", ",", "y", ",", "r", ",", "phi", ",",
     "z"}], "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.530344231642091*^9, 3.530344273482555*^9}, {
  3.530426556881928*^9, 3.530426588013591*^9}}],

Cell[CellGroupData[{

Cell[TextData[StyleBox["Aufgabe",
 FontSlant->"Italic"]], "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529836769624946*^9, 3.529836770461752*^9}, 
   3.529837834962648*^9, 3.529839793910857*^9}],

Cell[TextData[{
 "Multiplizieren Sie ein beliebiges Polynom in sin(x) und cos(x) aus und \
verwenden Sie sin(x)^2 + cos(x)^2 = 1 um alle cos(x)-Terme zu eliminieren! \
(",
 StyleBox["Hinweis",
  FontSlant->"Italic"],
 ": formulieren Sie Ihre Regel geschickt und verwenden Sie ",
 StyleBox["Expand", "Input"],
 "!)"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529836787055979*^9, 3.5298368227585907`*^9}, {
  3.5298370453687963`*^9, 3.5298370515686607`*^9}, {3.529837524132135*^9, 
  3.529837529079043*^9}, {3.5298378469193068`*^9, 3.529837863462945*^9}, {
  3.529837930026115*^9, 3.52983800457614*^9}, {3.529839380390664*^9, 
  3.5298393803934717`*^9}, {3.5298394163466597`*^9, 3.529839500442215*^9}, {
  3.529839726312224*^9, 3.529839783586006*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[TextData[StyleBox["L\[ODoubleDot]sung",
 FontSlant->"Italic"]], "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529836772224371*^9, 3.529836774852188*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{
   RowBox[{"{", 
    RowBox[{"a", ",", "b", ",", "p"}], "}"}], "=", 
   RowBox[{"{", 
    RowBox[{"2", ",", "1", ",", "7"}], "}"}]}], 
  ";"}], "\[IndentingNewLine]", 
 RowBox[{"poly", "=", 
  RowBox[{"Expand", "[", 
   RowBox[{
    RowBox[{"(", 
     RowBox[{
      RowBox[{"a", "*", 
       RowBox[{"Sin", "[", "x", "]"}]}], "+", 
      RowBox[{"b", "*", 
       RowBox[{"Cos", "[", "x", "]"}]}]}], ")"}], "^", "p"}], 
   "]"}]}], "\[IndentingNewLine]", 
 RowBox[{"%", "/.", 
  RowBox[{"{", 
   RowBox[{
    RowBox[{"Cos", "[", "x", "]"}], "\[Rule]", 
    RowBox[{"Sqrt", "[", 
     RowBox[{"1", "-", 
      RowBox[{
       RowBox[{"Sin", "[", "x", "]"}], "^", "2"}]}], "]"}]}], 
   "}"}]}]}], "Input",
 CellChangeTimes->{{3.52983951143327*^9, 3.529839707248439*^9}, 
   3.52983980919147*^9, {3.530426842879424*^9, 3.530426859359603*^9}}],

Cell[BoxData[
 RowBox[{
  SuperscriptBox[
   RowBox[{"Cos", "[", "x", "]"}], "7"], "+", 
  RowBox[{"14", " ", 
   SuperscriptBox[
    RowBox[{"Cos", "[", "x", "]"}], "6"], " ", 
   RowBox[{"Sin", "[", "x", "]"}]}], "+", 
  RowBox[{"84", " ", 
   SuperscriptBox[
    RowBox[{"Cos", "[", "x", "]"}], "5"], " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "x", "]"}], "2"]}], "+", 
  RowBox[{"280", " ", 
   SuperscriptBox[
    RowBox[{"Cos", "[", "x", "]"}], "4"], " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "x", "]"}], "3"]}], "+", 
  RowBox[{"560", " ", 
   SuperscriptBox[
    RowBox[{"Cos", "[", "x", "]"}], "3"], " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "x", "]"}], "4"]}], "+", 
  RowBox[{"672", " ", 
   SuperscriptBox[
    RowBox[{"Cos", "[", "x", "]"}], "2"], " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "x", "]"}], "5"]}], "+", 
  RowBox[{"448", " ", 
   RowBox[{"Cos", "[", "x", "]"}], " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "x", "]"}], "6"]}], "+", 
  RowBox[{"128", " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "x", "]"}], "7"]}]}]], "Output",
 CellChangeTimes->{{3.529839595469976*^9, 3.5298397076555777`*^9}, 
   3.5298398095218487`*^9, 3.530338279289781*^9, 3.530426861314899*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"128", " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "x", "]"}], "7"]}], "+", 
  RowBox[{"448", " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "x", "]"}], "6"], " ", 
   SqrtBox[
    RowBox[{"1", "-", 
     SuperscriptBox[
      RowBox[{"Sin", "[", "x", "]"}], "2"]}]]}], "+", 
  RowBox[{"672", " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "x", "]"}], "5"], " ", 
   RowBox[{"(", 
    RowBox[{"1", "-", 
     SuperscriptBox[
      RowBox[{"Sin", "[", "x", "]"}], "2"]}], ")"}]}], "+", 
  RowBox[{"560", " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "x", "]"}], "4"], " ", 
   SuperscriptBox[
    RowBox[{"(", 
     RowBox[{"1", "-", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "x", "]"}], "2"]}], ")"}], 
    RowBox[{"3", "/", "2"}]]}], "+", 
  RowBox[{"280", " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "x", "]"}], "3"], " ", 
   SuperscriptBox[
    RowBox[{"(", 
     RowBox[{"1", "-", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "x", "]"}], "2"]}], ")"}], "2"]}], "+", 
  RowBox[{"84", " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "x", "]"}], "2"], " ", 
   SuperscriptBox[
    RowBox[{"(", 
     RowBox[{"1", "-", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "x", "]"}], "2"]}], ")"}], 
    RowBox[{"5", "/", "2"}]]}], "+", 
  RowBox[{"14", " ", 
   RowBox[{"Sin", "[", "x", "]"}], " ", 
   SuperscriptBox[
    RowBox[{"(", 
     RowBox[{"1", "-", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "x", "]"}], "2"]}], ")"}], "3"]}], "+", 
  SuperscriptBox[
   RowBox[{"(", 
    RowBox[{"1", "-", 
     SuperscriptBox[
      RowBox[{"Sin", "[", "x", "]"}], "2"]}], ")"}], 
   RowBox[{"7", "/", "2"}]]}]], "Output",
 CellChangeTimes->{{3.529839595469976*^9, 3.5298397076555777`*^9}, 
   3.5298398095218487`*^9, 3.530338279289781*^9, 3.5304268613714113`*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{"a", ",", "b", ",", "p", ",", "poly"}], "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.530344283042199*^9, 3.530344291371413*^9}}]
}, Open  ]]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["2. Anwendungen", "Subtitle",
 CellChangeTimes->{{3.5297425543763027`*^9, 3.529742557910366*^9}, {
   3.5297426316137447`*^9, 3.52974264182384*^9}, 3.529742708591662*^9, {
   3.529743601950033*^9, 3.5297436189959297`*^9}, 3.529773051376731*^9}],

Cell[BoxData[""], "Input",
 CellChangeTimes->{{3.530338467707818*^9, 3.530338472040966*^9}}],

Cell[CellGroupData[{

Cell["2.1 Gleichungen", "Subsubtitle",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297414250588303`*^9, 3.529741426879901*^9}, {
   3.5297586825012903`*^9, 3.529758683048922*^9}, {3.529771218788065*^9, 
   3.529771220221965*^9}, 3.529773051376895*^9}],

Cell[TextData[{
 "Gleichungen werden mit \[OpenCurlyDoubleQuote]",
 StyleBox["==", "Input"],
 "\[CloseCurlyDoubleQuote] notiert und wieder, soweit m\[ODoubleDot]glich, \
ausgewertet. (Es existieren weitere Vergleichsoperatoren \
\[CloseCurlyDoubleQuote]",
 StyleBox["!=", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["<", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox[">", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["<=", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox[">=", "Input"],
 "\[CloseCurlyDoubleQuote].)"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529770823301293*^9, 3.529770852369877*^9}, {
   3.529771276792819*^9, 3.529771304122431*^9}, 3.529773051377132*^9, {
   3.529773417634728*^9, 3.5297735848018093`*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"1", "\[Equal]", "0"}]], "Input",
 CellChangeTimes->{{3.52977085471239*^9, 3.529770855536456*^9}, 
   3.529773051377304*^9}],

Cell[BoxData["False"], "Output",
 CellChangeTimes->{3.530339305152709*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"1", "\[Equal]", "1"}]], "Input",
 CellChangeTimes->{{3.52977123387621*^9, 3.52977123420462*^9}, 
   3.529773051381428*^9}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{3.530339305936398*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"-", "124"}], "+", 
   RowBox[{"345234", "/", "354"}]}], "\[GreaterEqual]", 
  RowBox[{"3", "^", "7"}]}]], "Input",
 CellChangeTimes->{{3.529773336579412*^9, 3.529773391753715*^9}}],

Cell[BoxData["False"], "Output",
 CellChangeTimes->{{3.530339306969564*^9, 3.530339317074177*^9}}]
}, Open  ]],

Cell["Ist das nicht der Fall ...", "Text",
 CellChangeTimes->{{3.529771314548194*^9, 3.529771329526422*^9}, 
   3.529773051386767*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"gln", "=", 
  RowBox[{"(", 
   RowBox[{"y", "\[Equal]", 
    RowBox[{
     RowBox[{"a", "*", 
      RowBox[{"x", "^", "2"}]}], "+", 
     RowBox[{"b", "*", "x"}], "+", "c"}]}], ")"}]}]], "Input",
 CellChangeTimes->{{3.5297712442769833`*^9, 3.5297712520232983`*^9}, {
   3.529771337417548*^9, 3.529771341426229*^9}, {3.529771517785946*^9, 
   3.529771537685425*^9}, 3.5297730513903837`*^9}],

Cell[BoxData[
 RowBox[{"y", "\[Equal]", 
  RowBox[{"c", "+", 
   RowBox[{"b", " ", "x"}], "+", 
   RowBox[{"a", " ", 
    SuperscriptBox["x", "2"]}]}]}]], "Output",
 CellChangeTimes->{{3.530339386343327*^9, 3.530339426258966*^9}}]
}, Open  ]],

Cell[TextData[{
 "... hilft der Befehl ",
 StyleBox["Solve[<Gleichung>,<Variable>]", "Input"],
 ". ",
 StyleBox["<Gleichung>", "Input"],
 " und ",
 StyleBox["<Variable>", "Input"],
 " k\[ODoubleDot]nnen jeweils auch Listen sein."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529771351932129*^9, 3.5297714882428493`*^9}, 
   3.5297730513930798`*^9, 3.530339349534217*^9, {3.5303394193434343`*^9, 
   3.530339420030011*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"lsg", "=", 
  RowBox[{"Solve", "[", 
   RowBox[{"gln", ",", "x"}], "]"}]}]], "Input",
 CellChangeTimes->{{3.529749680906555*^9, 3.5297496838250713`*^9}, {
   3.5297715116355247`*^9, 3.529771544270914*^9}, {3.52977158561487*^9, 
   3.529771592504961*^9}, 3.529773051393305*^9, {3.530339443127781*^9, 
   3.530339443760988*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{"x", "\[Rule]", 
     FractionBox[
      RowBox[{
       RowBox[{"-", "b"}], "+", 
       SqrtBox[
        RowBox[{
         SuperscriptBox["b", "2"], "-", 
         RowBox[{"4", " ", "a", " ", "c"}], "+", 
         RowBox[{"4", " ", "a", " ", "y"}]}]]}], 
      RowBox[{"2", " ", "a"}]]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", "\[Rule]", 
     RowBox[{"-", 
      FractionBox[
       RowBox[{"b", "+", 
        SqrtBox[
         RowBox[{
          SuperscriptBox["b", "2"], "-", 
          RowBox[{"4", " ", "a", " ", "c"}], "+", 
          RowBox[{"4", " ", "a", " ", "y"}]}]]}], 
       RowBox[{"2", " ", "a"}]]}]}], "}"}]}], "}"}]], "Output",
 CellChangeTimes->{{3.530339441597826*^9, 3.53033944422985*^9}}]
}, Open  ]],

Cell["\<\
Der Output erfolgt als Liste von Ersetzungsregeln (mehrere Listeneintr\
\[ADoubleDot]ge bedeuten mehrere m\[ODoubleDot]gliche L\[ODoubleDot]sungen).\
\>", "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529771621300481*^9, 3.529771637160696*^9}, 
   3.529773051396237*^9, {3.530191722565606*^9, 3.53019175378104*^9}, 
   3.530334920476159*^9, {3.530334981427575*^9, 3.530334982351969*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"lsg1", "=", 
  RowBox[{"x", "/.", 
   RowBox[{"lsg", "[", 
    RowBox[{"[", "1", "]"}], "]"}]}]}]], "Input",
 CellChangeTimes->{{3.529771562134741*^9, 3.529771594923847*^9}, 
   3.5297730513965*^9}],

Cell[BoxData[
 FractionBox[
  RowBox[{
   RowBox[{"-", "b"}], "+", 
   SqrtBox[
    RowBox[{
     SuperscriptBox["b", "2"], "-", 
     RowBox[{"4", " ", "a", " ", "c"}], "+", 
     RowBox[{"4", " ", "a", " ", "y"}]}]]}], 
  RowBox[{"2", " ", "a"}]]], "Output",
 CellChangeTimes->{{3.530339461796989*^9, 3.530339467722932*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"lsg2", "=", 
  RowBox[{"x", "/.", 
   RowBox[{"lsg", "[", 
    RowBox[{"[", "2", "]"}], "]"}]}]}]], "Input",
 CellChangeTimes->{{3.5297715968459997`*^9, 3.529771604098432*^9}, 
   3.52977305139935*^9}],

Cell[BoxData[
 RowBox[{"-", 
  FractionBox[
   RowBox[{"b", "+", 
    SqrtBox[
     RowBox[{
      SuperscriptBox["b", "2"], "-", 
      RowBox[{"4", " ", "a", " ", "c"}], "+", 
      RowBox[{"4", " ", "a", " ", "y"}]}]]}], 
   RowBox[{"2", " ", "a"}]]}]], "Output",
 CellChangeTimes->{{3.5303394626353493`*^9, 3.5303394685000067`*^9}}]
}, Open  ]],

Cell[TextData[{
 "Ist keine analytische L\[ODoubleDot]sung m\[ODoubleDot]glich, kann man es \
mit ",
 StyleBox["N", "Input",
  FontWeight->"Bold"],
 StyleBox["Solve", "Input"],
 " oder ",
 StyleBox["FindRoot ", "Input"],
 "versuchen."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529772051819387*^9, 3.5297720956238413`*^9}, {
   3.529772198512426*^9, 3.529772198825835*^9}, 3.529773051402281*^9, {
   3.530339491806239*^9, 3.530339497051845*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"gln", "=", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{"Cos", "[", "x", "]"}], "\[Equal]", "x"}], ")"}]}], 
  ";"}]], "Input",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297721252374153`*^9, 3.5297721572156773`*^9}, {
   3.5297722326444483`*^9, 3.529772259863913*^9}, 3.5297730514025593`*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Solve", "[", 
  RowBox[{"gln", ",", "x"}], "]"}]], "Input",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52977214311467*^9, 3.529772147461681*^9}, 
   3.529773051404071*^9}],

Cell[BoxData[
 RowBox[{
  StyleBox[
   RowBox[{"Solve", "::", "nsmet"}], "MessageName"], 
  RowBox[{
  ":", " "}], "\<\"This system cannot be solved with the methods available to \
Solve. \\!\\(\\*ButtonBox[\\\"\[RightSkeleton]\\\", \
ButtonStyle->\\\"Link\\\", ButtonFrame->None, \
ButtonData:>\\\"paclet:ref/Solve\\\", ButtonNote -> \
\\\"Solve::nsmet\\\"]\\)\"\>"}]], "Message", "MSG",
 CellChangeTimes->{{3.530339527237355*^9, 3.530339529668024*^9}}],

Cell[BoxData[
 RowBox[{"Solve", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"Cos", "[", "x", "]"}], "\[Equal]", "x"}], ",", "x"}], 
  "]"}]], "Output",
 CellChangeTimes->{{3.530339527241667*^9, 3.5303395296742907`*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"NSolve", "[", 
  RowBox[{"gln", ",", "x", ",", "Reals"}], "]"}]], "Input",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297721714623623`*^9, 3.529772254296051*^9}, 
   3.5297730514099207`*^9}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"{", 
   RowBox[{"x", "\[Rule]", "0.7390851332151607`"}], "}"}], "}"}]], "Output",
 CellChangeTimes->{{3.530339530388727*^9, 3.530339531620562*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{
   "0", " ", "ist", " ", "die", " ", "Vorgabe", " ", "f\[UDoubleDot]r", " ", 
    "einen", " ", "Startwert", " ", "bei", " ", "der", " ", "Suche", " ", 
    "anch", " ", "Nullstellen"}], " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{"FindRoot", "[", 
   RowBox[{"gln", ",", 
    RowBox[{"{", 
     RowBox[{"x", ",", "0"}], "}"}]}], "]"}]}]], "Input",
 CellChangeTimes->{{3.5297722766666803`*^9, 3.529772314394628*^9}, 
   3.529773051412561*^9, {3.5299041172433977`*^9, 3.529904145181005*^9}, {
   3.5299146795570803`*^9, 3.529914685115509*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"x", "\[Rule]", "0.7390851332151606`"}], "}"}]], "Output",
 CellChangeTimes->{{3.5303395356701193`*^9, 3.530339544720304*^9}}]
}, Open  ]],

Cell[TextData[{
 "H\[ADoubleDot]ufig haben ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " Funktionen mehrere m\[ODoubleDot]gliche Schreibweisen, das bedeutet, sie \
lassen sich mit unterschiedlicher Anzahl an Argumenten oder Optionen aufrufen \
(oder auch mit Argumenten unterschiedlicher Bedeutung!). Optionen \
unterscheiden sich von Argumenten dadurch, dass sie als Ersetzungregel \
\[UDoubleDot]bergeben werden."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52977238868574*^9, 3.529772748713258*^9}, {
   3.5297729753504*^9, 3.5297729787330437`*^9}, 3.529773051414941*^9, {
   3.530339565450218*^9, 3.530339565701507*^9}}],

Cell[TextData[StyleBox["<Funktionsname>[<Argument_1>,<Argument_2>(,<\
optionales_Argument>(,<Option> -> <Optionswert>))]", "Input"]], "Text",
 CellChangeTimes->{{3.529772750443842*^9, 3.529772832436352*^9}, 
   3.529773051415213*^9, {3.530341087010797*^9, 3.530341094438883*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{
   "gln", ",", "y", ",", "x", ",", "a", ",", "b", ",", "c", ",", "lsg", ",", 
    "lsg1", ",", "lsg2"}], "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.529771259970899*^9, 3.52977126420462*^9}, 
   3.529773051387519*^9, {3.5303393635470324`*^9, 3.530339425127902*^9}, {
   3.530344316830555*^9, 3.530344331150199*^9}, {3.530426901173951*^9, 
   3.530426927647101*^9}}],

Cell[CellGroupData[{

Cell[TextData[StyleBox["Aufgabe",
 FontSlant->"Italic"]], "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5297730514153633`*^9, 3.529773078007635*^9}, 
   3.52977391746216*^9}],

Cell["\<\
Finden nur mit einem Aufruf von NSolve alle L\[ODoubleDot]sungen der Gln. \
sin(x) = x/17, die innerhalb des Intervalls [2*Pi, 3*Pi] liegen!\
\>", "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529773108696808*^9, 3.5297731889156437`*^9}, {
  3.529773657201383*^9, 3.5297737923507967`*^9}, {3.5297738862326*^9, 
  3.5297738944497957`*^9}, {3.530341013779306*^9, 3.5303410152292852`*^9}, {
  3.530341154735632*^9, 3.530341193560316*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[TextData[StyleBox["L\[ODoubleDot]sung",
 FontSlant->"Italic"]], "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52977390989176*^9, 3.529773913572118*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"NSolve", "[", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     RowBox[{
      RowBox[{"Sin", "[", "x", "]"}], "\[Equal]", 
      RowBox[{"x", "/", "17"}]}], ",", 
     RowBox[{"x", "\[GreaterEqual]", 
      RowBox[{"2", "*", "Pi"}]}], ",", 
     RowBox[{"x", "\[LessEqual]", 
      RowBox[{"3", "*", "Pi"}]}]}], "}"}], ",", "x", ",", "Reals"}], 
  "]"}]], "Input",
 CellChangeTimes->{{3.5297732230043993`*^9, 3.5297732627644243`*^9}, {
  3.5297738039347267`*^9, 3.529773880359617*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{"x", "\[Rule]", "6.687492507719965`"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", "\[Rule]", "8.875481684397853`"}], "}"}]}], "}"}]], "Output",\

 CellChangeTimes->{{3.529773243192071*^9, 3.52977326320277*^9}, {
   3.529773814865519*^9, 3.529773880595647*^9}, 3.530341206941085*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     RowBox[{"Sin", "[", "x", "]"}], ",", 
     RowBox[{"x", "/", "17"}]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "10"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.529773837993639*^9, 3.529773869285303*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwtlnk0Vd/7xw2RKdx7DZnuvSg00Vwkz5NmaaCoJJVKypj4RGlQIiQSGSrK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     "]]}, 
   {Hue[0.9060679774997897, 0.6, 0.6], LineBox[CompressedData["
1:eJwVi2s01HkYgN23RbvUrpLLXP5OU+h6UtrifbtsEipKzqGtiBl3EbawW5JQ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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{{0, 10}, {-0.9999993680039507, 0.9999995755730018}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.5297738519496937`*^9, 3.5297738972427397`*^9}, 
   3.5303412084803123`*^9}]
}, Open  ]]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["2.2 Arbeiten mit Ausdr\[UDoubleDot]cken", "Subsubtitle",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529841488522442*^9, 3.529841509801214*^9}, {
  3.529914196108808*^9, 3.529914201191702*^9}}],

Cell[TextData[{
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " bietet eine F\[UDoubleDot]lle von M\[ODoubleDot]glichkeiten Ausdr\
\[UDoubleDot]cke umzuformen, so zun\[ADoubleDot]chst einfaches \
Ausmultiplizieren und Faktorisieren (von Polynomen):"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530019585676546*^9, 3.530019652657398*^9}, {
  3.530019710417715*^9, 3.53001971658772*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Expand", "[", 
  RowBox[{
   RowBox[{"(", 
    RowBox[{"1", "+", 
     RowBox[{"4", "*", "x"}]}], ")"}], "^", "6"}], "]"}]], "Input",
 CellChangeTimes->{{3.529914424158058*^9, 3.5299144271537857`*^9}, {
  3.530019665549429*^9, 3.530019678611504*^9}}],

Cell[BoxData[
 RowBox[{"1", "+", 
  RowBox[{"24", " ", "x"}], "+", 
  RowBox[{"240", " ", 
   SuperscriptBox["x", "2"]}], "+", 
  RowBox[{"1280", " ", 
   SuperscriptBox["x", "3"]}], "+", 
  RowBox[{"3840", " ", 
   SuperscriptBox["x", "4"]}], "+", 
  RowBox[{"6144", " ", 
   SuperscriptBox["x", "5"]}], "+", 
  RowBox[{"4096", " ", 
   SuperscriptBox["x", "6"]}]}]], "Output",
 CellChangeTimes->{{3.530019675913405*^9, 3.530019678843193*^9}, 
   3.530341369018382*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Factor", "[", 
  RowBox[{"1", "+", "x", "+", 
   RowBox[{"x", "^", "2"}], "+", 
   RowBox[{"x", "^", "3"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.530019681434188*^9, 3.5300196990105267`*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"(", 
   RowBox[{"1", "+", "x"}], ")"}], " ", 
  RowBox[{"(", 
   RowBox[{"1", "+", 
    SuperscriptBox["x", "2"]}], ")"}]}]], "Output",
 CellChangeTimes->{{3.530019689420162*^9, 3.530019699494356*^9}, 
   3.5303413699180403`*^9}]
}, Open  ]],

Cell["\<\
Rationale Ausdr\[UDoubleDot]cke lassen sich auf einen Hauptnenner bringen \
oder in ihre Partialbr\[UDoubleDot]che zerlegen:\
\>", "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530019730424399*^9, 3.5300197695317087`*^9}, {
  3.530341377660277*^9, 3.530341378930066*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Together", "[", 
  RowBox[{
   RowBox[{"x", "/", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{"1", "-", "x"}], ")"}], "^", "2"}]}], "+", 
   RowBox[{"3", "/", 
    RowBox[{"(", 
     RowBox[{"1", "+", "x"}], ")"}]}]}], "]"}]], "Input",
 CellChangeTimes->{{3.530019779030706*^9, 3.5300197988533087`*^9}}],

Cell[BoxData[
 FractionBox[
  RowBox[{"3", "-", 
   RowBox[{"5", " ", "x"}], "+", 
   RowBox[{"4", " ", 
    SuperscriptBox["x", "2"]}]}], 
  RowBox[{
   SuperscriptBox[
    RowBox[{"(", 
     RowBox[{
      RowBox[{"-", "1"}], "+", "x"}], ")"}], "2"], " ", 
   RowBox[{"(", 
    RowBox[{"1", "+", "x"}], ")"}]}]]], "Output",
 CellChangeTimes->{3.530019799228409*^9, 3.530341389590458*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Apart", "[", 
  RowBox[{"1", "/", 
   RowBox[{"(", 
    RowBox[{"1", "+", "x", "+", 
     RowBox[{"x", "^", "2"}], "+", 
     RowBox[{"x", "^", "3"}]}], ")"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.530019801846446*^9, 3.5300198217918253`*^9}}],

Cell[BoxData[
 RowBox[{
  FractionBox["1", 
   RowBox[{"2", " ", 
    RowBox[{"(", 
     RowBox[{"1", "+", "x"}], ")"}]}]], "+", 
  FractionBox[
   RowBox[{"1", "-", "x"}], 
   RowBox[{"2", " ", 
    RowBox[{"(", 
     RowBox[{"1", "+", 
      SuperscriptBox["x", "2"]}], ")"}]}]]}]], "Output",
 CellChangeTimes->{3.530019822208679*^9, 3.5303413917429733`*^9}]
}, Open  ]],

Cell[TextData[{
 "Sehr n\[UDoubleDot]tzlich sind auch die Funktionen ",
 StyleBox["Collect", "Input"],
 " zum Ausklammern bestimmter Symbole (oder sogar \
\[OpenCurlyDoubleQuote]Patterns\[CloseCurlyDoubleQuote], dazu aber sp\
\[ADoubleDot]ter) und ",
 StyleBox["Coefficient", "Input"],
 " f\[UDoubleDot]r den direkten Zugriff auf bestimmte Koeffizienten eines \
Ausdrucks."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530019855594514*^9, 3.530019965853817*^9}, {
  3.53033498624378*^9, 3.530334992178282*^9}, {3.530341401853902*^9, 
  3.530341402010911*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Collect", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"4", "*", 
     RowBox[{"a", "^", "3"}], "*", 
     RowBox[{"b", "^", "2"}]}], "+", 
    RowBox[{
     RowBox[{"a", "^", "3"}], "*", 
     RowBox[{"1", "/", "b"}]}], "-", 
    RowBox[{"3", "*", 
     RowBox[{"a", "^", "2"}], "*", 
     RowBox[{"b", "^", "2"}]}], "-", 
    RowBox[{"a", "*", "b"}], "-", 
    RowBox[{"5", "*", "a"}], "+", 
    RowBox[{"7", "*", "b"}], "+", "1"}], ",", 
   RowBox[{"{", 
    RowBox[{"a", ",", "b"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.5300199737081337`*^9, 3.530020078007506*^9}}],

Cell[BoxData[
 RowBox[{"1", "+", 
  RowBox[{"a", " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{"-", "5"}], "-", "b"}], ")"}]}], "+", 
  RowBox[{"7", " ", "b"}], "-", 
  RowBox[{"3", " ", 
   SuperscriptBox["a", "2"], " ", 
   SuperscriptBox["b", "2"]}], "+", 
  RowBox[{
   SuperscriptBox["a", "3"], " ", 
   RowBox[{"(", 
    RowBox[{
     FractionBox["1", "b"], "+", 
     RowBox[{"4", " ", 
      SuperscriptBox["b", "2"]}]}], ")"}]}]}]], "Output",
 CellChangeTimes->{{3.530020057344862*^9, 3.530020078355064*^9}, 
   3.5303414160757513`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Coefficient", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"4", "*", 
     RowBox[{"a", "^", "3"}], "*", 
     RowBox[{"b", "^", "2"}]}], "+", 
    RowBox[{
     RowBox[{"a", "^", "3"}], "*", 
     RowBox[{"1", "/", "b"}]}], "-", 
    RowBox[{"3", "*", 
     RowBox[{"a", "^", "2"}], "*", 
     RowBox[{"b", "^", "2"}]}], "-", 
    RowBox[{"a", "*", "b"}], "-", 
    RowBox[{"5", "*", "a"}], "+", 
    RowBox[{"7", "*", "b"}], "+", "1"}], ",", 
   RowBox[{"a", "*", "b"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.529914203275519*^9, 3.529914204923875*^9}, {
  3.5300200881289186`*^9, 3.5300200989835653`*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"-", "1"}], "-", 
  FractionBox["5", "b"]}]], "Output",
 CellChangeTimes->{3.530020100187439*^9, 3.530341421613055*^9}]
}, Open  ]],

Cell[TextData[{
 "Zum Vereinfachen gibt es bspw. die Kommandos ",
 StyleBox["Refine", "Input"],
 " (siehe auch ",
 StyleBox["Assuming", "Input"],
 "), ",
 StyleBox["ComplexExpand", "Input"],
 " oder ",
 StyleBox["(Full)Simplify", "Input"],
 ". Letzteres Beispiel ist zwar sehr m\[ADoubleDot]chtig, sollte jedoch mit \
Vorsicht gehandhabt werden!"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5300201483845787`*^9, 3.530020176206847*^9}, {
  3.5300202491023006`*^9, 3.53002026409332*^9}, {3.530020305008329*^9, 
  3.530020424812708*^9}, {3.530020563124483*^9, 3.530020602659186*^9}, {
  3.530341665624189*^9, 3.530341680983033*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{
   "Refine", " ", "wendet", " ", "Annahmen", " ", "auf", " ", 
    "Ausdr\[UDoubleDot]cke", " ", "an"}], " ", "*)"}], "\[IndentingNewLine]", 
  
  RowBox[{
   RowBox[{"Sqrt", "[", 
    RowBox[{"x", "^", "2"}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"Refine", "[", 
    RowBox[{
     RowBox[{"Sqrt", "[", 
      RowBox[{"x", "^", "2"}], "]"}], ",", 
     RowBox[{"x", ">", "0"}]}], "]"}]}]}]], "Input",
 CellChangeTimes->{{3.530020656630636*^9, 3.530020674847228*^9}, {
  3.530020832511344*^9, 3.53002087127374*^9}}],

Cell[BoxData[
 SqrtBox[
  SuperscriptBox["x", "2"]]], "Output",
 CellChangeTimes->{{3.530020862373698*^9, 3.5300208730606127`*^9}, 
   3.530341442043454*^9}],

Cell[BoxData["x"], "Output",
 CellChangeTimes->{{3.530020862373698*^9, 3.5300208730606127`*^9}, 
   3.530341442056984*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{
   "ComplexExpand", " ", "spaltet", " ", "einen", " ", "Ausdruck", " ", 
    "unter", " ", "der", " ", "Annahme", " ", "reeler", " ", "Variablen", " ",
     "in", " ", "Re", " ", "und", " ", "Im", " ", "auf"}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"Re", "[", 
    RowBox[{"Exp", "[", 
     RowBox[{"I", "*", "Phi"}], "]"}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"ComplexExpand", "[", 
    RowBox[{"Re", "[", 
     RowBox[{"Exp", "[", 
      RowBox[{"I", "*", "Phi"}], "]"}], "]"}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"(*", 
    RowBox[{
     RowBox[{"ComplexExpand", "[", 
      RowBox[{"Exp", "[", 
       RowBox[{"I", "*", "Phi"}], "]"}], "]"}], "/.", 
     RowBox[{"{", 
      RowBox[{"I", "\[Rule]", "0"}], "}"}]}], "*)"}]}]}]], "Input",
 CellChangeTimes->{{3.530020709276417*^9, 3.5300207698517857`*^9}, {
  3.5300208760110493`*^9, 3.530020969144085*^9}, {3.530344398963502*^9, 
  3.530344403178287*^9}}],

Cell[BoxData[
 RowBox[{"Re", "[", 
  SuperscriptBox["\[ExponentialE]", 
   RowBox[{"\[ImaginaryI]", " ", "Phi"}]], "]"}]], "Output",
 CellChangeTimes->{{3.530020899196762*^9, 3.53002096719058*^9}, 
   3.53034145083823*^9, {3.530344371858387*^9, 3.530344406120186*^9}}],

Cell[BoxData[
 RowBox[{"Cos", "[", "Phi", "]"}]], "Output",
 CellChangeTimes->{{3.530020899196762*^9, 3.53002096719058*^9}, 
   3.53034145083823*^9, {3.530344371858387*^9, 3.5303444061262608`*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{
   "Simplify", " ", "wendet", " ", "auch", " ", 
    "Funktionsidentit\[ADoubleDot]ten", " ", "und", " ", "weitere", " ", 
    "Umformungen", " ", "an"}], " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{"Simplify", "[", 
   RowBox[{
    RowBox[{"(", 
     RowBox[{
      RowBox[{"Sin", "[", "x", "]"}], "+", 
      RowBox[{"2", "*", 
       RowBox[{
        RowBox[{"Cos", "[", "x", "]"}], "^", "2"}]}]}], ")"}], "/", 
    RowBox[{"(", 
     RowBox[{"1", "+", 
      RowBox[{
       RowBox[{"Tan", "[", "x", "]"}], "^", "2"}]}], ")"}]}], 
   "]"}]}]], "Input",
 CellChangeTimes->{{3.530020974466413*^9, 3.5300210370520353`*^9}, {
  3.530341479723363*^9, 3.530341493137054*^9}}],

Cell[BoxData[
 RowBox[{
  SuperscriptBox[
   RowBox[{"Cos", "[", "x", "]"}], "2"], " ", 
  RowBox[{"(", 
   RowBox[{"1", "+", 
    RowBox[{"Cos", "[", 
     RowBox[{"2", " ", "x"}], "]"}], "+", 
    RowBox[{"Sin", "[", "x", "]"}]}], ")"}]}]], "Output",
 CellChangeTimes->{{3.530021001978389*^9, 3.530021037538423*^9}, 
   3.53034149682939*^9}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["2.3 Ableiten und Integrieren", "Subsubtitle",
 CellChangeTimes->{{3.529741375309197*^9, 3.529741390221168*^9}, 
   3.529773051415547*^9, {3.5299243597427683`*^9, 3.529924360099634*^9}}],

Cell[CellGroupData[{

Cell["Ableiten", "Subsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529907048579191*^9, 3.52990705022462*^9}}],

Cell[TextData[{
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " kann nahezu beliebig komplexe Ausdr\[UDoubleDot]cke aus rationalen \
Funktionen oder mathematischen Standardfunktionen ableiten, daf\[UDoubleDot]r \
gibt es die Funktion \[OpenCurlyDoubleQuote]",
 StyleBox["D", "Input"],
 "\[CloseCurlyDoubleQuote], der (partielle) Ableitungsoperator. "
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529906139483782*^9, 3.529906192967905*^9}, {
  3.529906236671418*^9, 3.529906409644198*^9}, {3.529906833991053*^9, 
  3.529906846386511*^9}}],

Cell["Verschiedene Varianten (aber nicht alle):", "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529906433680312*^9, 3.529906446579585*^9}, {
  3.529906819702467*^9, 3.5299068267023573`*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"erste", " ", "Ableitung"}], " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"D", "[", 
    RowBox[{
     RowBox[{"Sin", "[", "x", "]"}], ",", "x"}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"D", "[", 
    RowBox[{
     RowBox[{"Sin", "[", "x", "]"}], ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", "1"}], "}"}]}], "]"}]}]}]], "Input",
 CellChangeTimes->{{3.529906423060451*^9, 3.5299064875094213`*^9}}],

Cell[BoxData[
 RowBox[{"Cos", "[", "x", "]"}]], "Output",
 CellChangeTimes->{
  3.529906428748629*^9, {3.529906461015582*^9, 3.5299064881038713`*^9}, 
   3.5303418575733624`*^9}],

Cell[BoxData[
 RowBox[{"Cos", "[", "x", "]"}]], "Output",
 CellChangeTimes->{
  3.529906428748629*^9, {3.529906461015582*^9, 3.5299064881038713`*^9}, 
   3.530341857579678*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"zweite", " ", "Ableitung"}], " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{"D", "[", 
   RowBox[{
    RowBox[{"Sin", "[", "x", "]"}], ",", 
    RowBox[{"{", 
     RowBox[{"x", ",", "2"}], "}"}]}], "]"}]}]], "Input",
 CellChangeTimes->{{3.5299064960790567`*^9, 3.52990650940414*^9}}],

Cell[BoxData[
 RowBox[{"-", 
  RowBox[{"Sin", "[", "x", "]"}]}]], "Output",
 CellChangeTimes->{3.5299065121570044`*^9, 3.530341865133909*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{
   "Ableitungen", " ", "bei", " ", "mehreren", " ", 
    "Ver\[ADoubleDot]nderlichen"}], " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"D", "[", 
    RowBox[{
     RowBox[{"Cos", "[", 
      RowBox[{"x", "*", 
       RowBox[{"y", "^", "2"}]}], "]"}], ",", 
     RowBox[{"{", "x", "}"}]}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"D", "[", 
    RowBox[{
     RowBox[{"Cos", "[", 
      RowBox[{"x", "*", 
       RowBox[{"y", "^", "2"}]}], "]"}], ",", 
     RowBox[{"{", "y", "}"}]}], "]"}]}]}]], "Input",
 CellChangeTimes->{{3.529906522882757*^9, 3.529906533845436*^9}, {
  3.529906588576428*^9, 3.5299066397462*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"-", 
   SuperscriptBox["y", "2"]}], " ", 
  RowBox[{"Sin", "[", 
   RowBox[{"x", " ", 
    SuperscriptBox["y", "2"]}], "]"}]}]], "Output",
 CellChangeTimes->{{3.5299066183817387`*^9, 3.529906640437707*^9}, 
   3.5303418775176373`*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"-", "2"}], " ", "x", " ", "y", " ", 
  RowBox[{"Sin", "[", 
   RowBox[{"x", " ", 
    SuperscriptBox["y", "2"]}], "]"}]}]], "Output",
 CellChangeTimes->{{3.5299066183817387`*^9, 3.529906640437707*^9}, 
   3.530341877524168*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"rein", " ", "Symbolisch"}], " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{"D", "[", 
   RowBox[{
    RowBox[{
     RowBox[{"x", "^", "2"}], "*", 
     RowBox[{"f", "[", "x", "]"}]}], ",", 
    RowBox[{"{", 
     RowBox[{"x", ",", "3"}], "}"}]}], "]"}]}]], "Input",
 CellChangeTimes->{{3.5299067155818777`*^9, 3.529906746725811*^9}, {
  3.529906929015299*^9, 3.529906931087202*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"6", " ", 
   RowBox[{
    SuperscriptBox["f", "\[Prime]",
     MultilineFunction->None], "[", "x", "]"}]}], "+", 
  RowBox[{"6", " ", "x", " ", 
   RowBox[{
    SuperscriptBox["f", "\[Prime]\[Prime]",
     MultilineFunction->None], "[", "x", "]"}]}], "+", 
  RowBox[{
   SuperscriptBox["x", "2"], " ", 
   RowBox[{
    SuperscriptBox["f", 
     TagBox[
      RowBox[{"(", "3", ")"}],
      Derivative],
     MultilineFunction->None], "[", "x", "]"}]}]}]], "Output",
 CellChangeTimes->{
  3.5299067470661507`*^9, {3.529906925596105*^9, 3.529906931279756*^9}, 
   3.5303418832348223`*^9}]
}, Open  ]],

Cell[TextData[{
 "Mit der totalen Ableitung \[OpenCurlyDoubleQuote]",
 StyleBox["Dt", "Input"],
 "\[CloseCurlyDoubleQuote] m\[UDoubleDot]ssen Abh\[ADoubleDot]ngigkeiten \
nicht mehr explizit angegeben werden."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529906762389699*^9, 3.529906763707629*^9}, {
  3.529906950968073*^9, 3.529907028908585*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Dt", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"x", "^", "2"}], "*", "f"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "3"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.5299067662680492`*^9, 3.5299067665034313`*^9}, {
  3.529906875933326*^9, 3.5299068822226543`*^9}, {3.5299069382211637`*^9, 
  3.529906945025532*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"6", " ", 
   RowBox[{"Dt", "[", 
    RowBox[{"f", ",", "x"}], "]"}]}], "+", 
  RowBox[{"6", " ", "x", " ", 
   RowBox[{"Dt", "[", 
    RowBox[{"f", ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", "2"}], "}"}]}], "]"}]}], "+", 
  RowBox[{
   SuperscriptBox["x", "2"], " ", 
   RowBox[{"Dt", "[", 
    RowBox[{"f", ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", "3"}], "}"}]}], "]"}]}]}]], "Output",
 CellChangeTimes->{{3.529906943251525*^9, 3.529906945412806*^9}, 
   3.5303418921431932`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[TextData[StyleBox["Augabe",
 FontSlant->"Italic"]], "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529907738771572*^9, 3.5299077399677134`*^9}}],

Cell[TextData[{
 "\[CapitalUDoubleDot]berpr\[UDoubleDot]fen Sie die ",
 StyleBox["Cauchy-Riemannschen Differentialgleichungen",
  FontSlant->"Italic"],
 " explizit f\[UDoubleDot]r die Funktionen f(z) = 1 + exp(z), g(z) = z + \
1/z^2 und h(z) = z^2 + |z| (",
 StyleBox["Hinweis",
  FontSlant->"Italic"],
 ": verwenden Sie einfach ",
 StyleBox["z=x+I*y", "Input"],
 ")! Welche Eigenschaft besitzen \[LineSeparator]die Funktionen folglich \
(nicht)?"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5299077640098257`*^9, 3.529907812930545*^9}, {
   3.529907890703499*^9, 3.5299079306139727`*^9}, {3.529907981889964*^9, 
   3.529908031409422*^9}, 3.529908070377213*^9, {3.529908115370124*^9, 
   3.5299081291667747`*^9}, {3.529908193402796*^9, 3.529908200009365*^9}, {
   3.529908741240694*^9, 3.529908765952776*^9}, {3.5299088817125473`*^9, 
   3.529908917038766*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[TextData[StyleBox["L\[ODoubleDot]sung",
 FontSlant->"Italic"]], "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529907743511579*^9, 3.529907745939653*^9}}],

Cell[BoxData[{
 RowBox[{
  RowBox[{"f", "[", "z", "]"}], ":=", 
  RowBox[{"1", "+", 
   RowBox[{"Exp", "[", "z", "]"}]}]}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"g", "[", "z", "]"}], ":=", 
  RowBox[{"z", "+", 
   RowBox[{"1", "/", 
    RowBox[{"z", "^", "2"}]}]}]}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"h", "[", "z", "]"}], ":=", 
  RowBox[{
   RowBox[{"z", "^", "2"}], "+", 
   RowBox[{"Abs", "[", "z", "]"}]}]}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"subst", "=", 
   RowBox[{"{", 
    RowBox[{"z", "\[Rule]", 
     RowBox[{"x", "+", 
      RowBox[{"I", "*", "y"}]}]}], "}"}]}], ";"}]}], "Input",
 CellChangeTimes->{{3.529908079669347*^9, 3.52990810668567*^9}, {
  3.529908137024003*^9, 3.529908139366194*^9}, {3.529908219395433*^9, 
  3.529908233764974*^9}, {3.5299082865961857`*^9, 3.529908289976844*^9}, {
  3.529908649968585*^9, 3.529908663527012*^9}, {3.5299088563226833`*^9, 
  3.529908870568179*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"uf", "=", 
  RowBox[{"ComplexExpand", "[", 
   RowBox[{"Re", "[", 
    RowBox[{
     RowBox[{"f", "[", "z", "]"}], "/.", "subst"}], "]"}], 
   "]"}]}], "\[IndentingNewLine]", 
 RowBox[{"vf", "=", 
  RowBox[{"ComplexExpand", "[", 
   RowBox[{"Im", "[", 
    RowBox[{
     RowBox[{"f", "[", "z", "]"}], "/.", "subst"}], "]"}], "]"}]}]}], "Input",\

 CellChangeTimes->{{3.5299082623345957`*^9, 3.529908425081141*^9}, {
  3.529908474187285*^9, 3.529908500556288*^9}}],

Cell[BoxData[
 RowBox[{"1", "+", 
  RowBox[{
   SuperscriptBox["\[ExponentialE]", "x"], " ", 
   RowBox[{"Cos", "[", "y", "]"}]}]}]], "Output",
 CellChangeTimes->{{3.529908408299625*^9, 3.529908425721546*^9}, {
   3.529908489949898*^9, 3.5299085010184526`*^9}, {3.529908654489376*^9, 
   3.529908665791836*^9}, 3.529909028619255*^9, 3.5303419490576878`*^9}],

Cell[BoxData[
 RowBox[{
  SuperscriptBox["\[ExponentialE]", "x"], " ", 
  RowBox[{"Sin", "[", "y", "]"}]}]], "Output",
 CellChangeTimes->{{3.529908408299625*^9, 3.529908425721546*^9}, {
   3.529908489949898*^9, 3.5299085010184526`*^9}, {3.529908654489376*^9, 
   3.529908665791836*^9}, 3.529909028619255*^9, 3.530341949063286*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"D", "[", 
   RowBox[{"uf", ",", "x"}], "]"}], "\[Equal]", 
  RowBox[{"D", "[", 
   RowBox[{"vf", ",", "y"}], "]"}]}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"D", "[", 
   RowBox[{"uf", ",", "y"}], "]"}], "\[Equal]", 
  RowBox[{"-", 
   RowBox[{"D", "[", 
    RowBox[{"vf", ",", "x"}], "]"}]}]}]}], "Input",
 CellChangeTimes->{
  3.529908075299302*^9, {3.529908151822968*^9, 3.529908168423869*^9}, {
   3.529908231095337*^9, 3.5299082370641527`*^9}, {3.529908525284861*^9, 
   3.5299085881958523`*^9}, {3.529908671686946*^9, 3.529908675023391*^9}}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{
  3.52990816867117*^9, 3.5299082391826963`*^9, {3.529908536940668*^9, 
   3.529908550755142*^9}, 3.5299085885042267`*^9, {3.529908656217807*^9, 
   3.5299086760622063`*^9}, 3.5299090292460737`*^9, 3.530341949957637*^9}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{
  3.52990816867117*^9, 3.5299082391826963`*^9, {3.529908536940668*^9, 
   3.529908550755142*^9}, 3.5299085885042267`*^9, {3.529908656217807*^9, 
   3.5299086760622063`*^9}, 3.5299090292460737`*^9, 3.530341949962852*^9}]
}, Open  ]],

Cell["f ist holomorph.", "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52990877465635*^9, 3.529908779710505*^9}, {
  3.529909029871962*^9, 3.5299090305099077`*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"ug", "=", 
  RowBox[{"ComplexExpand", "[", 
   RowBox[{"Re", "[", 
    RowBox[{
     RowBox[{"g", "[", "z", "]"}], "/.", "subst"}], "]"}], 
   "]"}]}], "\[IndentingNewLine]", 
 RowBox[{"vg", "=", 
  RowBox[{"ComplexExpand", "[", 
   RowBox[{"Im", "[", 
    RowBox[{
     RowBox[{"g", "[", "z", "]"}], "/.", "subst"}], "]"}], "]"}]}]}], "Input",\

 CellChangeTimes->{{3.5299082623345957`*^9, 3.529908425081141*^9}, {
  3.529908474187285*^9, 3.529908513805558*^9}}],

Cell[BoxData[
 RowBox[{"x", "+", 
  FractionBox[
   SuperscriptBox["x", "2"], 
   SuperscriptBox[
    RowBox[{"(", 
     RowBox[{
      SuperscriptBox["x", "2"], "+", 
      SuperscriptBox["y", "2"]}], ")"}], "2"]], "-", 
  FractionBox[
   SuperscriptBox["y", "2"], 
   SuperscriptBox[
    RowBox[{"(", 
     RowBox[{
      SuperscriptBox["x", "2"], "+", 
      SuperscriptBox["y", "2"]}], ")"}], "2"]]}]], "Output",
 CellChangeTimes->{
  3.5299085144032*^9, {3.529908655286523*^9, 3.52990866640164*^9}, 
   3.529909031777132*^9, 3.530341952131407*^9}],

Cell[BoxData[
 RowBox[{"y", "-", 
  FractionBox[
   RowBox[{"2", " ", "x", " ", "y"}], 
   SuperscriptBox[
    RowBox[{"(", 
     RowBox[{
      SuperscriptBox["x", "2"], "+", 
      SuperscriptBox["y", "2"]}], ")"}], "2"]]}]], "Output",
 CellChangeTimes->{
  3.5299085144032*^9, {3.529908655286523*^9, 3.52990866640164*^9}, 
   3.529909031777132*^9, 3.53034195213864*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"D", "[", 
   RowBox[{"ug", ",", "x"}], "]"}], "\[Equal]", 
  RowBox[{"D", "[", 
   RowBox[{"vg", ",", "y"}], "]"}]}], "\[IndentingNewLine]", 
 RowBox[{"Reduce", "[", "%", "]"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"D", "[", 
   RowBox[{"ug", ",", "y"}], "]"}], "\[Equal]", 
  RowBox[{"-", 
   RowBox[{"D", "[", 
    RowBox[{"vg", ",", "x"}], "]"}]}]}], "\[IndentingNewLine]", 
 RowBox[{"Reduce", "[", "%", "]"}]}], "Input",
 CellChangeTimes->{{3.5299085521610527`*^9, 3.5299086275556707`*^9}, {
  3.53034240646506*^9, 3.53034242508773*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"1", "-", 
   FractionBox[
    RowBox[{"4", " ", 
     SuperscriptBox["x", "3"]}], 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox["x", "2"], "+", 
       SuperscriptBox["y", "2"]}], ")"}], "3"]], "+", 
   FractionBox[
    RowBox[{"4", " ", "x", " ", 
     SuperscriptBox["y", "2"]}], 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox["x", "2"], "+", 
       SuperscriptBox["y", "2"]}], ")"}], "3"]], "+", 
   FractionBox[
    RowBox[{"2", " ", "x"}], 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox["x", "2"], "+", 
       SuperscriptBox["y", "2"]}], ")"}], "2"]]}], "\[Equal]", 
  RowBox[{"1", "+", 
   FractionBox[
    RowBox[{"8", " ", "x", " ", 
     SuperscriptBox["y", "2"]}], 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox["x", "2"], "+", 
       SuperscriptBox["y", "2"]}], ")"}], "3"]], "-", 
   FractionBox[
    RowBox[{"2", " ", "x"}], 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox["x", "2"], "+", 
       SuperscriptBox["y", "2"]}], ")"}], "2"]]}]}]], "Output",
 CellChangeTimes->{{3.5299085986373568`*^9, 3.529908667588607*^9}, 
   3.52990903246275*^9, 3.530341953217854*^9, {3.530342408647932*^9, 
   3.5303424257467813`*^9}}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{{3.5299085986373568`*^9, 3.529908667588607*^9}, 
   3.52990903246275*^9, 3.530341953217854*^9, {3.530342408647932*^9, 
   3.53034242575463*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"-", 
    FractionBox[
     RowBox[{"4", " ", 
      SuperscriptBox["x", "2"], " ", "y"}], 
     SuperscriptBox[
      RowBox[{"(", 
       RowBox[{
        SuperscriptBox["x", "2"], "+", 
        SuperscriptBox["y", "2"]}], ")"}], "3"]]}], "+", 
   FractionBox[
    RowBox[{"4", " ", 
     SuperscriptBox["y", "3"]}], 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox["x", "2"], "+", 
       SuperscriptBox["y", "2"]}], ")"}], "3"]], "-", 
   FractionBox[
    RowBox[{"2", " ", "y"}], 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox["x", "2"], "+", 
       SuperscriptBox["y", "2"]}], ")"}], "2"]]}], "\[Equal]", 
  RowBox[{
   RowBox[{"-", 
    FractionBox[
     RowBox[{"8", " ", 
      SuperscriptBox["x", "2"], " ", "y"}], 
     SuperscriptBox[
      RowBox[{"(", 
       RowBox[{
        SuperscriptBox["x", "2"], "+", 
        SuperscriptBox["y", "2"]}], ")"}], "3"]]}], "+", 
   FractionBox[
    RowBox[{"2", " ", "y"}], 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox["x", "2"], "+", 
       SuperscriptBox["y", "2"]}], ")"}], "2"]]}]}]], "Output",
 CellChangeTimes->{{3.5299085986373568`*^9, 3.529908667588607*^9}, 
   3.52990903246275*^9, 3.530341953217854*^9, {3.530342408647932*^9, 
   3.5303424257613277`*^9}}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{{3.5299085986373568`*^9, 3.529908667588607*^9}, 
   3.52990903246275*^9, 3.530341953217854*^9, {3.530342408647932*^9, 
   3.530342425766053*^9}}]
}, Open  ]],

Cell["\<\
g ist holomorph bis auf (0, 0).\
\>", "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52990877465635*^9, 3.529908779710505*^9}, 
   3.529908962639677*^9, {3.5303419542257557`*^9, 3.530341955063631*^9}, {
   3.530342109583003*^9, 3.530342113634357*^9}, {3.530342414690896*^9, 
   3.530342415999711*^9}, {3.53034453538028*^9, 3.530344542111408*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"uh", "=", 
  RowBox[{"ComplexExpand", "[", 
   RowBox[{"Re", "[", 
    RowBox[{
     RowBox[{"h", "[", "z", "]"}], "/.", "subst"}], "]"}], 
   "]"}]}], "\[IndentingNewLine]", 
 RowBox[{"vh", "=", 
  RowBox[{"ComplexExpand", "[", 
   RowBox[{"Im", "[", 
    RowBox[{
     RowBox[{"h", "[", "z", "]"}], "/.", "subst"}], "]"}], "]"}]}]}], "Input",\

 CellChangeTimes->{{3.5299082623345957`*^9, 3.529908425081141*^9}, {
  3.529908474187285*^9, 3.529908513805558*^9}, {3.5299089677453327`*^9, 
  3.5299089729971027`*^9}}],

Cell[BoxData[
 RowBox[{
  SuperscriptBox["x", "2"], "-", 
  SuperscriptBox["y", "2"], "+", 
  SqrtBox[
   RowBox[{
    SuperscriptBox["x", "2"], "+", 
    SuperscriptBox["y", "2"]}]]}]], "Output",
 CellChangeTimes->{3.529908973758212*^9, 3.529909034662182*^9, 
  3.530341959475327*^9}],

Cell[BoxData[
 RowBox[{"2", " ", "x", " ", "y"}]], "Output",
 CellChangeTimes->{3.529908973758212*^9, 3.529909034662182*^9, 
  3.5303419594807796`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"D", "[", 
   RowBox[{"uh", ",", "x"}], "]"}], "\[Equal]", 
  RowBox[{"D", "[", 
   RowBox[{"vh", ",", "y"}], "]"}]}], "\[IndentingNewLine]", 
 RowBox[{"Simplify", "[", "%", "]"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"D", "[", 
   RowBox[{"uh", ",", "y"}], "]"}], "\[Equal]", 
  RowBox[{"-", 
   RowBox[{"D", "[", 
    RowBox[{"vh", ",", "x"}], "]"}]}]}], "\[IndentingNewLine]", 
 RowBox[{"Simplify", "[", "%", "]"}]}], "Input",
 CellChangeTimes->{
  3.529908075299302*^9, {3.529908151822968*^9, 3.529908168423869*^9}, {
   3.529908231095337*^9, 3.5299082370641527`*^9}, {3.529908525284861*^9, 
   3.5299085881958523`*^9}, {3.529908671686946*^9, 3.529908675023391*^9}, {
   3.529908984876453*^9, 3.5299089998759947`*^9}, {3.530342432239971*^9, 
   3.530342450218788*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"2", " ", "x"}], "+", 
   FractionBox["x", 
    SqrtBox[
     RowBox[{
      SuperscriptBox["x", "2"], "+", 
      SuperscriptBox["y", "2"]}]]]}], "\[Equal]", 
  RowBox[{"2", " ", "x"}]}]], "Output",
 CellChangeTimes->{{3.529908989204966*^9, 3.529909000249735*^9}, 
   3.529909035680114*^9, 3.5303419607245092`*^9, {3.53034243410725*^9, 
   3.530342450993126*^9}}],

Cell[BoxData[
 RowBox[{
  FractionBox["x", 
   SqrtBox[
    RowBox[{
     SuperscriptBox["x", "2"], "+", 
     SuperscriptBox["y", "2"]}]]], "\[Equal]", "0"}]], "Output",
 CellChangeTimes->{{3.529908989204966*^9, 3.529909000249735*^9}, 
   3.529909035680114*^9, 3.5303419607245092`*^9, {3.53034243410725*^9, 
   3.530342451005484*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"-", "2"}], " ", "y"}], "+", 
   FractionBox["y", 
    SqrtBox[
     RowBox[{
      SuperscriptBox["x", "2"], "+", 
      SuperscriptBox["y", "2"]}]]]}], "\[Equal]", 
  RowBox[{
   RowBox[{"-", "2"}], " ", "y"}]}]], "Output",
 CellChangeTimes->{{3.529908989204966*^9, 3.529909000249735*^9}, 
   3.529909035680114*^9, 3.5303419607245092`*^9, {3.53034243410725*^9, 
   3.530342451013153*^9}}],

Cell[BoxData[
 RowBox[{
  FractionBox["y", 
   SqrtBox[
    RowBox[{
     SuperscriptBox["x", "2"], "+", 
     SuperscriptBox["y", "2"]}]]], "\[Equal]", "0"}]], "Output",
 CellChangeTimes->{{3.529908989204966*^9, 3.529909000249735*^9}, 
   3.529909035680114*^9, 3.5303419607245092`*^9, {3.53034243410725*^9, 
   3.530342451020689*^9}}]
}, Open  ]],

Cell["g ist nicht holomorph.", "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52990877465635*^9, 3.529908779710505*^9}, 
   3.529908962639677*^9, {3.529909005979648*^9, 3.529909007241332*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{
   "f", ",", "g", ",", "h", ",", "subst", ",", "x", ",", "y", ",", "z", ",", 
    "uf", ",", "vf", ",", "ug", ",", "vg", ",", "uh", ",", "vh"}], "]"}], 
  ";"}]], "Input",
 CellChangeTimes->{{3.529908144240089*^9, 3.5299081487843018`*^9}, {
  3.529908921594626*^9, 3.529908945247057*^9}, {3.530344461419034*^9, 
  3.530344478358197*^9}, {3.530426988017282*^9, 3.530426993920163*^9}, {
  3.53042704388983*^9, 3.530427052901702*^9}}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["Integrieren", "Subsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529907058927429*^9, 3.5299070665355186`*^9}}],

Cell[TextData[{
 "Nat\[UDoubleDot]rlich stehen in ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " auch Routinen f\[UDoubleDot]r Bestimmte und Unbestimmte Integrale \
(Stammfunktionen) bereit."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529907143776333*^9, 3.529907252825013*^9}, {
  3.5299073230977*^9, 3.529907323947091*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"einfache", " ", "Polynome"}], " ", "*)"}], "\[IndentingNewLine]", 
  
  RowBox[{"Integrate", "[", 
   RowBox[{
    RowBox[{"1", "+", 
     RowBox[{"3", "*", "x"}], "-", 
     RowBox[{"x", "^", "2"}], "+", 
     RowBox[{"35", "*", 
      RowBox[{"x", "^", "7"}]}]}], ",", "x"}], "]"}]}]], "Input",
 CellChangeTimes->{{3.529907473478527*^9, 3.529907501256117*^9}}],

Cell[BoxData[
 RowBox[{"x", "+", 
  FractionBox[
   RowBox[{"3", " ", 
    SuperscriptBox["x", "2"]}], "2"], "-", 
  FractionBox[
   SuperscriptBox["x", "3"], "3"], "+", 
  FractionBox[
   RowBox[{"35", " ", 
    SuperscriptBox["x", "8"]}], "8"]}]], "Output",
 CellChangeTimes->{3.529907501891138*^9, 3.530342529649995*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"elementare", " ", "Funktionen"}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"Integrate", "[", 
    RowBox[{
     RowBox[{"1", "/", "x"}], ",", "x"}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"Integrate", "[", 
    RowBox[{
     RowBox[{
      RowBox[{"Log", "[", "x", "]"}], "^", "2"}], ",", "x"}], "]"}], 
   "\[IndentingNewLine]", 
   RowBox[{"Integrate", "[", 
    RowBox[{
     RowBox[{"Cosh", "[", "x", "]"}], ",", "x"}], "]"}], 
   "\[IndentingNewLine]", 
   RowBox[{"Integrate", "[", 
    RowBox[{
     RowBox[{"Exp", "[", 
      RowBox[{"5", "*", "x"}], "]"}], ",", "x"}], "]"}]}]}]], "Input",
 CellChangeTimes->{{3.5299073324843807`*^9, 3.5299073400835238`*^9}, {
  3.529907424953713*^9, 3.5299074672068653`*^9}, {3.529907514226787*^9, 
  3.529907563258479*^9}}],

Cell[BoxData[
 RowBox[{"Log", "[", "x", "]"}]], "Output",
 CellChangeTimes->{
  3.5299073403012*^9, {3.529907451094803*^9, 3.529907467632505*^9}, {
   3.529907521036043*^9, 3.5299075636990767`*^9}, 3.53034253196231*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"2", " ", "x"}], "-", 
  RowBox[{"2", " ", "x", " ", 
   RowBox[{"Log", "[", "x", "]"}]}], "+", 
  RowBox[{"x", " ", 
   SuperscriptBox[
    RowBox[{"Log", "[", "x", "]"}], "2"]}]}]], "Output",
 CellChangeTimes->{
  3.5299073403012*^9, {3.529907451094803*^9, 3.529907467632505*^9}, {
   3.529907521036043*^9, 3.5299075636990767`*^9}, 3.5303425319677973`*^9}],

Cell[BoxData[
 RowBox[{"Sinh", "[", "x", "]"}]], "Output",
 CellChangeTimes->{
  3.5299073403012*^9, {3.529907451094803*^9, 3.529907467632505*^9}, {
   3.529907521036043*^9, 3.5299075636990767`*^9}, 3.530342531971858*^9}],

Cell[BoxData[
 FractionBox[
  SuperscriptBox["\[ExponentialE]", 
   RowBox[{"5", " ", "x"}]], "5"]], "Output",
 CellChangeTimes->{
  3.5299073403012*^9, {3.529907451094803*^9, 3.529907467632505*^9}, {
   3.529907521036043*^9, 3.5299075636990767`*^9}, 3.53034253197605*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"komplexere", " ", "Ausdr\[UDoubleDot]cke"}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"Integrate", "[", 
    RowBox[{
     RowBox[{"1", "+", "x", "+", 
      RowBox[{"Sin", "[", 
       RowBox[{"1", "+", "x"}], "]"}]}], ",", "x"}], "]"}], 
   "\[IndentingNewLine]", 
   RowBox[{"Integrate", "[", 
    RowBox[{
     RowBox[{
      RowBox[{"(", 
       RowBox[{"1", "+", 
        RowBox[{"x", "^", "2"}]}], ")"}], "/", 
      RowBox[{"(", 
       RowBox[{"1", "-", 
        RowBox[{"x", "^", "2"}]}], ")"}]}], ",", "x"}], "]"}], 
   "\[IndentingNewLine]", 
   RowBox[{"Integrate", "[", 
    RowBox[{
     RowBox[{"x", "/", 
      RowBox[{"(", 
       RowBox[{"1", "+", 
        RowBox[{"Sin", "[", "x", "]"}]}], ")"}]}], ",", "x"}], "]"}], 
   "\[IndentingNewLine]", 
   RowBox[{"Integrate", "[", 
    RowBox[{
     RowBox[{
      RowBox[{"Sqrt", "[", 
       RowBox[{"1", "+", 
        RowBox[{"Sin", "[", "x", "]"}]}], "]"}], "/", 
      RowBox[{"(", 
       RowBox[{"1", "+", 
        RowBox[{"Cos", "[", "x", "]"}]}], ")"}]}], ",", "x"}], 
    "]"}]}]}]], "Input",
 CellChangeTimes->{{3.529907350945114*^9, 3.529907404909479*^9}, {
  3.5299075713135557`*^9, 3.529907654420292*^9}}],

Cell[BoxData[
 RowBox[{"x", "+", 
  FractionBox[
   SuperscriptBox["x", "2"], "2"], "-", 
  RowBox[{
   RowBox[{"Cos", "[", "1", "]"}], " ", 
   RowBox[{"Cos", "[", "x", "]"}]}], "+", 
  RowBox[{
   RowBox[{"Sin", "[", "1", "]"}], " ", 
   RowBox[{"Sin", "[", "x", "]"}]}]}]], "Output",
 CellChangeTimes->{{3.529907372357789*^9, 3.5299074052721024`*^9}, {
   3.529907605478191*^9, 3.529907655038382*^9}, 3.5303425393986673`*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"-", "x"}], "-", 
  RowBox[{"Log", "[", 
   RowBox[{"1", "-", "x"}], "]"}], "+", 
  RowBox[{"Log", "[", 
   RowBox[{"1", "+", "x"}], "]"}]}]], "Output",
 CellChangeTimes->{{3.529907372357789*^9, 3.5299074052721024`*^9}, {
   3.529907605478191*^9, 3.529907655038382*^9}, 3.530342539404627*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"-", "x"}], "+", 
  RowBox[{"2", " ", 
   RowBox[{"Log", "[", 
    RowBox[{
     RowBox[{"Cos", "[", 
      FractionBox["x", "2"], "]"}], "+", 
     RowBox[{"Sin", "[", 
      FractionBox["x", "2"], "]"}]}], "]"}]}], "+", 
  FractionBox[
   RowBox[{"2", " ", "x", " ", 
    RowBox[{"Sin", "[", 
     FractionBox["x", "2"], "]"}]}], 
   RowBox[{
    RowBox[{"Cos", "[", 
     FractionBox["x", "2"], "]"}], "+", 
    RowBox[{"Sin", "[", 
     FractionBox["x", "2"], "]"}]}]]}]], "Output",
 CellChangeTimes->{{3.529907372357789*^9, 3.5299074052721024`*^9}, {
   3.529907605478191*^9, 3.529907655038382*^9}, 3.5303425394758177`*^9}],

Cell[BoxData[
 RowBox[{"-", 
  RowBox[{
   RowBox[{"(", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       RowBox[{"-", "1"}], "+", 
       RowBox[{
        RowBox[{"Cos", "[", 
         FractionBox["x", "2"], "]"}], " ", 
        RowBox[{"(", 
         RowBox[{
          RowBox[{"Log", "[", 
           RowBox[{
            RowBox[{"Cos", "[", 
             FractionBox["x", "4"], "]"}], "-", 
            RowBox[{"Sin", "[", 
             FractionBox["x", "4"], "]"}]}], "]"}], "-", 
          RowBox[{"Log", "[", 
           RowBox[{
            RowBox[{"Cos", "[", 
             FractionBox["x", "4"], "]"}], "+", 
            RowBox[{"Sin", "[", 
             FractionBox["x", "4"], "]"}]}], "]"}]}], ")"}]}]}], ")"}], " ", 
     RowBox[{"Sec", "[", 
      FractionBox["x", "2"], "]"}], " ", 
     SqrtBox[
      RowBox[{"1", "+", 
       RowBox[{"Sin", "[", "x", "]"}]}]]}], ")"}], "/", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{"Cos", "[", 
      FractionBox["x", "2"], "]"}], "+", 
     RowBox[{"Sin", "[", 
      FractionBox["x", "2"], "]"}]}], ")"}]}]}]], "Output",
 CellChangeTimes->{{3.529907372357789*^9, 3.5299074052721024`*^9}, {
   3.529907605478191*^9, 3.529907655038382*^9}, 3.530342539665533*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"bestimmte", " ", "Integrale"}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"Integrate", "[", 
    RowBox[{
     RowBox[{"1", "+", 
      RowBox[{"x", "/", 
       RowBox[{"(", 
        RowBox[{"1", "-", "x"}], ")"}]}]}], ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", 
       RowBox[{"9", "/", "7"}], ",", 
       RowBox[{"33", "/", "7"}]}], "}"}]}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"Integrate", "[", 
    RowBox[{
     RowBox[{"Cos", "[", "x", "]"}], ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", "0", ",", 
       RowBox[{"Pi", "/", "2"}]}], "}"}]}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"Integrate", "[", 
    RowBox[{
     RowBox[{
      RowBox[{"Sin", "[", "x", "]"}], "/", "x"}], ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", 
       RowBox[{"-", "Infinity"}], ",", "Infinity"}], "}"}]}], "]"}], 
   "\[IndentingNewLine]", 
   RowBox[{"(*", " ", 
    RowBox[{
    "das", " ", "Symbol", " ", "Infinity", " ", "sollte", " ", 
     "selbsterkl\[ADoubleDot]rend", " ", "sein"}], " ", "*)"}], 
   "\[IndentingNewLine]", 
   RowBox[{"Integrate", "[", 
    RowBox[{
     RowBox[{"Exp", "[", 
      RowBox[{"-", 
       RowBox[{"x", "^", "2"}]}], "]"}], ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", 
       RowBox[{"-", "Infinity"}], ",", "Infinity"}], "}"}]}], 
    "]"}]}]}]], "Input",
 CellChangeTimes->{{3.529907668143649*^9, 3.5299076799627743`*^9}, {
  3.529907721263831*^9, 3.529907725892693*^9}, {3.5299090483878202`*^9, 
  3.529909188760028*^9}, {3.529909224361047*^9, 3.529909277877701*^9}, {
  3.5303425526842003`*^9, 3.530342555409752*^9}}],

Cell[BoxData[
 RowBox[{"-", 
  RowBox[{"Log", "[", "13", "]"}]}]], "Output",
 CellChangeTimes->{
  3.529909064375301*^9, {3.52990912833139*^9, 3.5299091833912277`*^9}, {
   3.529909259245553*^9, 3.529909271579859*^9}, {3.53034254731522*^9, 
   3.530342556663671*^9}}],

Cell[BoxData["1"], "Output",
 CellChangeTimes->{
  3.529909064375301*^9, {3.52990912833139*^9, 3.5299091833912277`*^9}, {
   3.529909259245553*^9, 3.529909271579859*^9}, {3.53034254731522*^9, 
   3.530342556675116*^9}}],

Cell[BoxData["\[Pi]"], "Output",
 CellChangeTimes->{
  3.529909064375301*^9, {3.52990912833139*^9, 3.5299091833912277`*^9}, {
   3.529909259245553*^9, 3.529909271579859*^9}, {3.53034254731522*^9, 
   3.5303425567509613`*^9}}],

Cell[BoxData[
 SqrtBox["\[Pi]"]], "Output",
 CellChangeTimes->{
  3.529909064375301*^9, {3.52990912833139*^9, 3.5299091833912277`*^9}, {
   3.529909259245553*^9, 3.529909271579859*^9}, {3.53034254731522*^9, 
   3.530342556827631*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell["Aufgabe", "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52990955537903*^9, 3.529909558668667*^9}}],

Cell[TextData[{
 "Integrieren Sie die Funktion sin(x)/x auf dem Intervall [0,1] (",
 StyleBox["Hinweis",
  FontSlant->"Italic"],
 ": es ist nur nach einem numerischen Ergebnis gefragt)!"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529913616434259*^9, 3.5299136255104723`*^9}, {
  3.5299136667902937`*^9, 3.52991372390784*^9}, {3.529914038372671*^9, 
  3.529914045357698*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell["L\[ODoubleDot]sung", "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5299095623625317`*^9, 3.529909564801345*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", 
   RowBox[{
    RowBox[{"alternativ", ":", " ", 
     RowBox[{"Integrate", "[", 
      RowBox[{
       RowBox[{
        RowBox[{"Sin", "[", "x", "]"}], "/", "x"}], ",", 
       RowBox[{"{", 
        RowBox[{"x", ",", "0", ",", "1"}], "}"}]}], "]"}]}], "//", "N"}], 
   "*)"}], "\[IndentingNewLine]", 
  RowBox[{"NIntegrate", "[", 
   RowBox[{
    RowBox[{
     RowBox[{"Sin", "[", "x", "]"}], "/", "x"}], ",", 
    RowBox[{"{", 
     RowBox[{"x", ",", "0", ",", "1"}], "}"}]}], "]"}]}]], "Input",
 CellChangeTimes->{{3.5299095673051043`*^9, 3.529909571493595*^9}, {
  3.529913998424891*^9, 3.5299140740279427`*^9}, {3.530342586589017*^9, 
  3.530342590947929*^9}}],

Cell[BoxData["0.9460830703671841`"], "Output",
 CellChangeTimes->{{3.529914034555222*^9, 3.529914075320381*^9}, 
   3.530342593007065*^9}]
}, Open  ]]
}, Open  ]]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["2.4 Reihenentwicklung und Grenzwerte", "Subsubtitle",
 CellChangeTimes->{{3.529740863209552*^9, 3.5297408692601748`*^9}, {
   3.529741356797666*^9, 3.529741370251501*^9}, 3.529773051415709*^9, {
   3.529924362578012*^9, 3.5299243641424713`*^9}}],

Cell[CellGroupData[{

Cell["Reihenentwicklung", "Subsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529914165966857*^9, 3.529914170425736*^9}}],

Cell["\<\
Die Taylor-, bzw. Laurentreihe eines Ausdrucks liefert die Funktion: \
\>", "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529916032947423*^9, 3.529916046840706*^9}, {
  3.529916581533374*^9, 3.529916622621828*^9}, {3.529916652814498*^9, 
  3.529916719052512*^9}, {3.529916753397909*^9, 3.5299167617013187`*^9}, {
  3.530342707601181*^9, 3.5303427124856577`*^9}}],

Cell[TextData[StyleBox["Series[<Ausdr.>,{<Var.>,<Entw.pkt>,<Entw.ordn.>}]", \
"Input"]], "Text",
 CellChangeTimes->{{3.529916762954028*^9, 3.5299167917988167`*^9}}],

Cell[TextData[{
 "Die Ausgabe dieses Befehls erfolgt in Form von ",
 StyleBox["SeriesData", "Input"],
 ", einer \[OpenCurlyDoubleQuote]Container\[CloseCurlyDoubleQuote]-Funktion. \
In der Entwicklung vernachl\[ADoubleDot]ssigte h\[ODoubleDot]here Ordnungen \
werden mit ",
 StyleBox["O[<Var.>]^(<Entw.ordn.>+1)", "Input"],
 " repr\[ADoubleDot]sentiert (Landau-Symbol). Handlicher ist aber ein \
Ausdruck, den man durch Anwenden von ",
 StyleBox["Normal", "Input"],
 " erh\[ADoubleDot]lt."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5299167964176807`*^9, 3.529916809436161*^9}, {
  3.529916853629181*^9, 3.529916952447485*^9}, {3.5299169918121433`*^9, 
  3.529917101981324*^9}, {3.5299172508932877`*^9, 3.529917256196376*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", "SeriesData", " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{"Series", "[", 
   RowBox[{
    RowBox[{"Sin", "[", "x", "]"}], ",", 
    RowBox[{"{", 
     RowBox[{"x", ",", "0", ",", "10"}], "}"}]}], "]"}]}]], "Input",
 CellChangeTimes->{{3.5299171144461193`*^9, 3.5299171384739122`*^9}, {
  3.529917187721766*^9, 3.52991719359846*^9}}],

Cell[BoxData[
 InterpretationBox[
  RowBox[{"x", "-", 
   FractionBox[
    SuperscriptBox["x", "3"], "6"], "+", 
   FractionBox[
    SuperscriptBox["x", "5"], "120"], "-", 
   FractionBox[
    SuperscriptBox["x", "7"], "5040"], "+", 
   FractionBox[
    SuperscriptBox["x", "9"], "362880"], "+", 
   InterpretationBox[
    SuperscriptBox[
     RowBox[{"O", "[", "x", "]"}], "11"],
    SeriesData[$CellContext`x, 0, {}, 1, 11, 1],
    Editable->False]}],
  SeriesData[$CellContext`x, 0, {1, 0, 
    Rational[-1, 6], 0, 
    Rational[1, 120], 0, 
    Rational[-1, 5040], 0, 
    Rational[1, 362880]}, 1, 11, 1],
  Editable->False]], "Output",
 CellChangeTimes->{{3.529917135770233*^9, 3.529917138888479*^9}, 
   3.530342734479629*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", "Ausdruck", " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{"Normal", "[", 
   RowBox[{"Series", "[", 
    RowBox[{
     RowBox[{"Cos", "[", "x", "]"}], ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", "0", ",", "10"}], "}"}]}], "]"}], "]"}]}]], "Input",
 CellChangeTimes->{{3.5299171501889963`*^9, 3.529917162874846*^9}, {
  3.529917195427215*^9, 3.5299172002757597`*^9}}],

Cell[BoxData[
 RowBox[{"1", "-", 
  FractionBox[
   SuperscriptBox["x", "2"], "2"], "+", 
  FractionBox[
   SuperscriptBox["x", "4"], "24"], "-", 
  FractionBox[
   SuperscriptBox["x", "6"], "720"], "+", 
  FractionBox[
   SuperscriptBox["x", "8"], "40320"], "-", 
  FractionBox[
   SuperscriptBox["x", "10"], "3628800"]}]], "Output",
 CellChangeTimes->{3.529917163301688*^9, 3.530342736265512*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"Landau", "-", "Symbol"}], " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"1", "+", "x", "+", 
    RowBox[{"x", "^", "2"}], "+", 
    RowBox[{"x", "^", "3"}], "+", 
    RowBox[{
     RowBox[{"O", "[", "x", "]"}], "^", "2"}]}], "\[IndentingNewLine]", 
   RowBox[{"Series", "[", 
    RowBox[{
     RowBox[{"Exp", "[", "x", "]"}], ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", "1", ",", "2"}], "}"}]}], "]"}], 
   "\[IndentingNewLine]", 
   RowBox[{
    RowBox[{"Series", "[", 
     RowBox[{
      RowBox[{"Exp", "[", "x", "]"}], ",", 
      RowBox[{"{", 
       RowBox[{"x", ",", "1", ",", "2"}], "}"}]}], "]"}], "+", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{"x", "-", "1"}], ")"}], "^", "10"}]}]}]}]], "Input",
 CellChangeTimes->{{3.529917202666946*^9, 3.529917203663568*^9}, {
  3.529917262685033*^9, 3.5299173906491413`*^9}}],

Cell[BoxData[
 InterpretationBox[
  RowBox[{"1", "+", "x", "+", 
   InterpretationBox[
    SuperscriptBox[
     RowBox[{"O", "[", "x", "]"}], "2"],
    SeriesData[$CellContext`x, 0, {}, 0, 2, 1],
    Editable->False]}],
  SeriesData[$CellContext`x, 0, {1, 1}, 0, 2, 1],
  Editable->False]], "Output",
 CellChangeTimes->{{3.5299172827990837`*^9, 3.529917343064567*^9}, 
   3.529917391216763*^9, 3.5303427428700867`*^9}],

Cell[BoxData[
 InterpretationBox[
  RowBox[{"\[ExponentialE]", "+", 
   RowBox[{"\[ExponentialE]", " ", 
    RowBox[{"(", 
     RowBox[{"x", "-", "1"}], ")"}]}], "+", 
   RowBox[{
    FractionBox["1", "2"], " ", "\[ExponentialE]", " ", 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"x", "-", "1"}], ")"}], "2"]}], "+", 
   InterpretationBox[
    SuperscriptBox[
     RowBox[{"O", "[", 
      RowBox[{"x", "-", "1"}], "]"}], "3"],
    SeriesData[$CellContext`x, 1, {}, 0, 3, 1],
    Editable->False]}],
  SeriesData[$CellContext`x, 1, {E, E, Rational[1, 2] E}, 0, 3, 1],
  Editable->False]], "Output",
 CellChangeTimes->{{3.5299172827990837`*^9, 3.529917343064567*^9}, 
   3.529917391216763*^9, 3.530342742877062*^9}],

Cell[BoxData[
 InterpretationBox[
  RowBox[{"\[ExponentialE]", "+", 
   RowBox[{"\[ExponentialE]", " ", 
    RowBox[{"(", 
     RowBox[{"x", "-", "1"}], ")"}]}], "+", 
   RowBox[{
    FractionBox["1", "2"], " ", "\[ExponentialE]", " ", 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"x", "-", "1"}], ")"}], "2"]}], "+", 
   InterpretationBox[
    SuperscriptBox[
     RowBox[{"O", "[", 
      RowBox[{"x", "-", "1"}], "]"}], "3"],
    SeriesData[$CellContext`x, 1, {}, 0, 3, 1],
    Editable->False]}],
  SeriesData[$CellContext`x, 1, {E, E, Rational[1, 2] E}, 0, 3, 1],
  Editable->False]], "Output",
 CellChangeTimes->{{3.5299172827990837`*^9, 3.529917343064567*^9}, 
   3.529917391216763*^9, 3.5303427428824263`*^9}]
}, Open  ]],

Cell[TextData[{
 "H\[ODoubleDot]here Ordnungen werden also automatisch in \
\[OpenCurlyDoubleQuote]",
 StyleBox["O", "Input"],
 "\[CloseCurlyDoubleQuote] absorbiert und somit konsistent gehandhabt. Also \
",
 StyleBox["beachte",
  FontSlant->"Italic"],
 ":"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529917395436892*^9, 3.529917467049981*^9}, {
  3.529917755991321*^9, 3.5299177729836397`*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"Normal", "[", 
   RowBox[{"Series", "[", 
    RowBox[{
     RowBox[{"Exp", "[", "x", "]"}], ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", "0", ",", "3"}], "}"}]}], "]"}], "]"}], "+", 
  RowBox[{"x", "^", "5"}]}], "\[IndentingNewLine]", 
 RowBox[{"Normal", "[", 
  RowBox[{
   RowBox[{"Series", "[", 
    RowBox[{
     RowBox[{"Exp", "[", "x", "]"}], ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", "0", ",", "3"}], "}"}]}], "]"}], "+", 
   RowBox[{"x", "^", "5"}]}], "]"}]}], "Input",
 CellChangeTimes->{{3.529917471440802*^9, 3.5299175203478527`*^9}}],

Cell[BoxData[
 RowBox[{"1", "+", "x", "+", 
  FractionBox[
   SuperscriptBox["x", "2"], "2"], "+", 
  FractionBox[
   SuperscriptBox["x", "3"], "6"], "+", 
  SuperscriptBox["x", "5"]}]], "Output",
 CellChangeTimes->{{3.529917496879396*^9, 3.52991752071581*^9}, 
   3.530342769059173*^9}],

Cell[BoxData[
 RowBox[{"1", "+", "x", "+", 
  FractionBox[
   SuperscriptBox["x", "2"], "2"], "+", 
  FractionBox[
   SuperscriptBox["x", "3"], "6"]}]], "Output",
 CellChangeTimes->{{3.529917496879396*^9, 3.52991752071581*^9}, 
   3.53034276906629*^9}]
}, Open  ]],

Cell[TextData[{
 "M\[ODoubleDot]chte man, ausgehend von einer Reihendarstellung y in der \
Variablen x, eine invertierte Reihendarstellung von x in y ermitteln, erm\
\[ODoubleDot]glicht das der Befehl ",
 StyleBox["InverseSeries", "Input"],
 "."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52991780718122*^9, 3.529917823381324*^9}, {
  3.529917855290124*^9, 3.529917962553344*^9}, {3.529918259810503*^9, 
  3.529918261921216*^9}, {3.530342790907525*^9, 3.530342794315214*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"InverseSeries", "[", 
  RowBox[{"1", "-", "x", "+", 
   RowBox[{
    RowBox[{"1", "/", "3"}], "*", 
    RowBox[{"x", "^", "2"}]}], "+", 
   RowBox[{
    RowBox[{"1", "/", "5"}], "*", 
    RowBox[{"x", "^", "3"}]}], "-", 
   RowBox[{"7", "*", 
    RowBox[{"x", "^", "4"}]}], "+", 
   RowBox[{
    RowBox[{"O", "[", "x", "]"}], "^", "5"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.52991813420723*^9, 3.5299182202973433`*^9}}],

Cell[BoxData[
 InterpretationBox[
  RowBox[{
   RowBox[{"-", 
    RowBox[{"(", 
     RowBox[{"x", "-", "1"}], ")"}]}], "+", 
   RowBox[{
    FractionBox["1", "3"], " ", 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"x", "-", "1"}], ")"}], "2"]}], "-", 
   RowBox[{
    FractionBox["19", "45"], " ", 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"x", "-", "1"}], ")"}], "3"]}], "-", 
   RowBox[{
    FractionBox["175", "27"], " ", 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"x", "-", "1"}], ")"}], "4"]}], "+", 
   InterpretationBox[
    SuperscriptBox[
     RowBox[{"O", "[", 
      RowBox[{"x", "-", "1"}], "]"}], "5"],
    SeriesData[$CellContext`x, 1, {}, 1, 5, 1],
    Editable->False]}],
  SeriesData[$CellContext`x, 1, {-1, 
    Rational[1, 3], 
    Rational[-19, 45], 
    Rational[-175, 27]}, 1, 5, 1],
  Editable->False]], "Output",
 CellChangeTimes->{{3.529918185329398*^9, 3.5299182209701157`*^9}, 
   3.53034281051871*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"y", "=", 
  RowBox[{"Series", "[", 
   RowBox[{
    RowBox[{"Exp", "[", "x", "]"}], ",", 
    RowBox[{"{", 
     RowBox[{"x", ",", "0", ",", "5"}], "}"}]}], "]"}]}]], "Input",
 CellChangeTimes->{{3.529917978587941*^9, 3.529918001044422*^9}, {
  3.529918044246811*^9, 3.529918075491157*^9}, {3.52991833292727*^9, 
  3.529918346144506*^9}}],

Cell[BoxData[
 InterpretationBox[
  RowBox[{"1", "+", "x", "+", 
   FractionBox[
    SuperscriptBox["x", "2"], "2"], "+", 
   FractionBox[
    SuperscriptBox["x", "3"], "6"], "+", 
   FractionBox[
    SuperscriptBox["x", "4"], "24"], "+", 
   FractionBox[
    SuperscriptBox["x", "5"], "120"], "+", 
   InterpretationBox[
    SuperscriptBox[
     RowBox[{"O", "[", "x", "]"}], "6"],
    SeriesData[$CellContext`x, 0, {}, 0, 6, 1],
    Editable->False]}],
  SeriesData[$CellContext`x, 0, {1, 1, 
    Rational[1, 2], 
    Rational[1, 6], 
    Rational[1, 24], 
    Rational[1, 120]}, 0, 6, 1],
  Editable->False]], "Output",
 CellChangeTimes->{
  3.5299180014317217`*^9, {3.5299180447747307`*^9, 3.529918075716444*^9}, {
   3.529918333792942*^9, 3.529918346549567*^9}, 3.5303428114984493`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"InverseSeries", "[", 
  RowBox[{"y", ",", "x"}], "]"}]], "Input",
 CellChangeTimes->{{3.529918008256968*^9, 3.529918013204115*^9}, {
  3.529918101655128*^9, 3.529918101737434*^9}}],

Cell[BoxData[
 InterpretationBox[
  RowBox[{
   RowBox[{"(", 
    RowBox[{"x", "-", "1"}], ")"}], "-", 
   RowBox[{
    FractionBox["1", "2"], " ", 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"x", "-", "1"}], ")"}], "2"]}], "+", 
   RowBox[{
    FractionBox["1", "3"], " ", 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"x", "-", "1"}], ")"}], "3"]}], "-", 
   RowBox[{
    FractionBox["1", "4"], " ", 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"x", "-", "1"}], ")"}], "4"]}], "+", 
   RowBox[{
    FractionBox["1", "5"], " ", 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"x", "-", "1"}], ")"}], "5"]}], "+", 
   InterpretationBox[
    SuperscriptBox[
     RowBox[{"O", "[", 
      RowBox[{"x", "-", "1"}], "]"}], "6"],
    SeriesData[$CellContext`x, 1, {}, 1, 6, 1],
    Editable->False]}],
  SeriesData[$CellContext`x, 1, {1, 
    Rational[-1, 2], 
    Rational[1, 3], 
    Rational[-1, 4], 
    Rational[1, 5]}, 1, 6, 1],
  Editable->False]], "Output",
 CellChangeTimes->{
  3.529918014181191*^9, {3.529918052711069*^9, 3.5299181021008673`*^9}, {
   3.529918335012516*^9, 3.5299183487633677`*^9}, 3.530342812532329*^9, 
   3.530342843152034*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Series", "[", 
  RowBox[{
   RowBox[{"Log", "[", "x", "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "1", ",", "5"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.529918090715548*^9, 3.529918119724678*^9}}],

Cell[BoxData[
 InterpretationBox[
  RowBox[{
   RowBox[{"(", 
    RowBox[{"x", "-", "1"}], ")"}], "-", 
   RowBox[{
    FractionBox["1", "2"], " ", 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"x", "-", "1"}], ")"}], "2"]}], "+", 
   RowBox[{
    FractionBox["1", "3"], " ", 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"x", "-", "1"}], ")"}], "3"]}], "-", 
   RowBox[{
    FractionBox["1", "4"], " ", 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"x", "-", "1"}], ")"}], "4"]}], "+", 
   RowBox[{
    FractionBox["1", "5"], " ", 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"x", "-", "1"}], ")"}], "5"]}], "+", 
   InterpretationBox[
    SuperscriptBox[
     RowBox[{"O", "[", 
      RowBox[{"x", "-", "1"}], "]"}], "6"],
    SeriesData[$CellContext`x, 1, {}, 1, 6, 1],
    Editable->False]}],
  SeriesData[$CellContext`x, 1, {1, 
    Rational[-1, 2], 
    Rational[1, 3], 
    Rational[-1, 4], 
    Rational[1, 5]}, 1, 6, 1],
  Editable->False]], "Output",
 CellChangeTimes->{3.529918119948433*^9, 3.530342813111849*^9, 
  3.530342843783723*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{"y", ",", "x"}], "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.5303445622358713`*^9, 3.530344577506702*^9}, {
  3.530427085779187*^9, 3.53042708725243*^9}}],

Cell[TextData[{
 "Die Reihenentwicklung der Umkehrfunktion (",
 StyleBox["InverseFunction", "Input"],
 ") entspricht wie zu erwarten der invertierten Reihenentwicklung der urspr\
\[UDoubleDot]nglichen Funktion."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5299183100341*^9, 3.529918313452434*^9}, {
  3.5299183652799387`*^9, 3.52991842480083*^9}, {3.529918529657423*^9, 
  3.5299185326783943`*^9}, {3.530342866659079*^9, 3.530342903039485*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell["Grenzwerte", "Subsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5299141719986277`*^9, 3.5299141753117867`*^9}}],

Cell[TextData[{
 "Mit ",
 StyleBox["Limit", "Input"],
 " k\[ODoubleDot]nnen Sie in ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " Grenzwerte berechnen. ",
 StyleBox["Limit", "Input"],
 " nimmt zwei Argumente entgegen, den zu betrachtenden Ausdruck und eine \
Regel zur Grenzwertbildung. Mit der Option ",
 StyleBox["Direction", "Input"],
 " kann man zwischen links- und rechtsseitigem (Std.) Grenzwert \
w\[ADoubleDot]hlen."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5299157681141157`*^9, 3.529915883976317*^9}, {
  3.5299161302696257`*^9, 3.529916133787558*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"f\[UDoubleDot]r", " ", "Folgen"}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{"Limit", "[", 
   RowBox[{
    RowBox[{
     RowBox[{"(", 
      RowBox[{"1", "-", "n"}], ")"}], "/", 
     RowBox[{"(", 
      RowBox[{"1", "+", "n"}], ")"}]}], ",", 
    RowBox[{"n", "\[Rule]", "Infinity"}]}], "]"}]}]], "Input",
 CellChangeTimes->{{3.529916315929883*^9, 3.529916350076507*^9}, {
  3.529916414447185*^9, 3.529916416967107*^9}}],

Cell[BoxData[
 RowBox[{"-", "1"}]], "Output",
 CellChangeTimes->{
  3.529916350501164*^9, {3.529916394231035*^9, 3.529916417314728*^9}, 
   3.530343014671405*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"f\[UDoubleDot]r", " ", "Reihen"}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{"Limit", "[", 
   RowBox[{
    RowBox[{"Sum", "[", 
     RowBox[{
      RowBox[{"1", "/", 
       RowBox[{"n", "^", "2"}]}], ",", 
      RowBox[{"{", 
       RowBox[{"n", ",", "1", ",", "nmax"}], "}"}]}], "]"}], ",", 
    RowBox[{"nmax", "\[Rule]", "Infinity"}]}], "]"}]}]], "Input",
 CellChangeTimes->{{3.52991615113842*^9, 3.5299162973945723`*^9}}],

Cell[BoxData[
 FractionBox[
  SuperscriptBox["\[Pi]", "2"], "6"]], "Output",
 CellChangeTimes->{{3.529916185785131*^9, 3.52991626098514*^9}, 
   3.529916422419168*^9, 3.53034301541114*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"f\[UDoubleDot]r", " ", "Funktionen"}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{"Limit", "[", 
   RowBox[{
    RowBox[{"x", "/", 
     RowBox[{"Log", "[", "x", "]"}]}], ",", 
    RowBox[{"x", "\[Rule]", "0"}]}], "]"}]}]], "Input",
 CellChangeTimes->{{3.529914149108096*^9, 3.5299141804456053`*^9}, {
  3.529915905329681*^9, 3.529915935905301*^9}, {3.5303430334903717`*^9, 
  3.5303430632541237`*^9}}],

Cell[BoxData["0"], "Output",
 CellChangeTimes->{{3.529915917770095*^9, 3.52991593641743*^9}, 
   3.529916423145879*^9, 3.530343015952183*^9, 3.5303430790944853`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"mit", " ", "der", " ", "Option", " ", "Direction"}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"Limit", "[", 
    RowBox[{
     RowBox[{"ArcTan", "[", 
      RowBox[{"1", "/", "x"}], "]"}], ",", 
     RowBox[{"x", "\[Rule]", "0"}], ",", 
     RowBox[{"Direction", "\[Rule]", 
      RowBox[{"+", "1"}]}]}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"Limit", "[", 
    RowBox[{
     RowBox[{"ArcTan", "[", 
      RowBox[{"1", "/", "x"}], "]"}], ",", 
     RowBox[{"x", "\[Rule]", "0"}], ",", 
     RowBox[{"Direction", "\[Rule]", 
      RowBox[{"-", "1"}]}]}], "]"}]}]}]], "Input",
 CellChangeTimes->{{3.529915947760686*^9, 3.529916004947847*^9}, {
  3.5299160997894373`*^9, 3.5299161122996883`*^9}, {3.530343065830159*^9, 
  3.530343076492838*^9}}],

Cell[BoxData[
 RowBox[{"-", 
  FractionBox["\[Pi]", "2"]}]], "Output",
 CellChangeTimes->{{3.529915988308173*^9, 3.5299160054650183`*^9}, {
   3.529916100341217*^9, 3.529916112809718*^9}, 3.529916423862577*^9, 
   3.5303430168884172`*^9, 3.5303430795555143`*^9}],

Cell[BoxData[
 FractionBox["\[Pi]", "2"]], "Output",
 CellChangeTimes->{{3.529915988308173*^9, 3.5299160054650183`*^9}, {
   3.529916100341217*^9, 3.529916112809718*^9}, 3.529916423862577*^9, 
   3.5303430168884172`*^9, 3.5303430795606117`*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{"n", ",", "nmax", ",", "x"}], "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.529916377470722*^9, 3.529916393145626*^9}}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["2.5 Vektoren und Matrizen", "Subsubtitle",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529741340952188*^9, 3.529741343926262*^9}, {
   3.5297415835458803`*^9, 3.5297415876813602`*^9}, 3.5297730514160223`*^9, {
   3.529924366431777*^9, 3.52992436731455*^9}}],

Cell[TextData[{
 "Vektoren und Matrizen (und bel. Tensoren) lassen sich durch \
(verschachtelte) Listen verk\[ODoubleDot]rpern. Mit ",
 StyleBox["MatrixForm", "Input"],
 " erh\[ADoubleDot]lt man auch die gewohnte Darstellung."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52992280188772*^9, 3.529922956698097*^9}, 
   3.5303433816812696`*^9}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"vektor1", "=", 
   RowBox[{"{", 
    RowBox[{"4", ",", "2", ",", "7"}], "}"}]}], ";"}], "\[IndentingNewLine]", 

 RowBox[{
  RowBox[{
   RowBox[{"matrix1", "=", 
    RowBox[{"{", "\[IndentingNewLine]", 
     RowBox[{
      RowBox[{"{", 
       RowBox[{"1", ",", "3", ",", "0"}], "}"}], ",", "\[IndentingNewLine]", 
      RowBox[{"{", 
       RowBox[{"2", ",", "1", ",", 
        RowBox[{"-", "1"}]}], "}"}], ",", "\[IndentingNewLine]", 
      RowBox[{"{", 
       RowBox[{"0", ",", "0", ",", "1"}], "}"}]}], "\[IndentingNewLine]", 
     "}"}]}], ";"}], "\[IndentingNewLine]"}], "\[IndentingNewLine]", 
 RowBox[{"MatrixForm", "[", "vektor1", "]"}], "\[IndentingNewLine]", 
 RowBox[{"MatrixForm", "[", "matrix1", "]"}]}], "Input",
 CellChangeTimes->{{3.529922962424451*^9, 3.529923025626401*^9}, {
  3.529923080636455*^9, 3.529923123487823*^9}, {3.52992366845153*^9, 
  3.52992369038737*^9}}],

Cell[BoxData[
 TagBox[
  RowBox[{"(", "\[NoBreak]", 
   TagBox[GridBox[{
      {"4"},
      {"2"},
      {"7"}
     },
     GridBoxAlignment->{
      "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}},
        "RowsIndexed" -> {}},
     GridBoxSpacings->{"Columns" -> {
         Offset[0.27999999999999997`], {
          Offset[0.5599999999999999]}, 
         Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
         Offset[0.2], {
          Offset[0.4]}, 
         Offset[0.2]}, "RowsIndexed" -> {}}],
    Column], "\[NoBreak]", ")"}],
  Function[BoxForm`e$, 
   MatrixForm[BoxForm`e$]]]], "Output",
 CellChangeTimes->{3.529923124042219*^9, 3.5299236910203943`*^9, 
  3.530343385538411*^9}],

Cell[BoxData[
 TagBox[
  RowBox[{"(", "\[NoBreak]", GridBox[{
     {"1", "3", "0"},
     {"2", "1", 
      RowBox[{"-", "1"}]},
     {"0", "0", "1"}
    },
    GridBoxAlignment->{
     "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}}, 
      "RowsIndexed" -> {}},
    GridBoxSpacings->{"Columns" -> {
        Offset[0.27999999999999997`], {
         Offset[0.7]}, 
        Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
        Offset[0.2], {
         Offset[0.4]}, 
        Offset[0.2]}, "RowsIndexed" -> {}}], "\[NoBreak]", ")"}],
  Function[BoxForm`e$, 
   MatrixForm[BoxForm`e$]]]], "Output",
 CellChangeTimes->{3.529923124042219*^9, 3.5299236910203943`*^9, 
  3.530343385545724*^9}]
}, Open  ]],

Cell[TextData[{
 "Ein \[OpenCurlyDoubleQuote]",
 StyleBox[".", "Input"],
 "\[CloseCurlyDoubleQuote] zwischen zwei Vektoren, bzw. Matrizen f\
\[UDoubleDot]hrt das entsprechende Skalar- oder Matrizenprodukt aus."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529923145905864*^9, 3.5299232409300947`*^9}, {
  3.529940658520585*^9, 3.529940658791263*^9}, {3.530343400510241*^9, 
  3.530343401244034*^9}}],

Cell[BoxData[{
 RowBox[{
  RowBox[{"vektor2", "=", 
   RowBox[{"{", 
    RowBox[{"1", ",", "1", ",", "0"}], "}"}]}], 
  ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"matrix2", "=", 
   RowBox[{"{", "\[IndentingNewLine]", 
    RowBox[{
     RowBox[{"{", 
      RowBox[{"1", ",", "0", ",", "1"}], "}"}], ",", "\[IndentingNewLine]", 
     RowBox[{"{", 
      RowBox[{"0", ",", "1", ",", "0"}], "}"}], ",", "\[IndentingNewLine]", 
     RowBox[{"{", 
      RowBox[{"1", ",", "0", ",", "1"}], "}"}]}], "\[IndentingNewLine]", 
    "}"}]}], ";"}]}], "Input",
 CellChangeTimes->{{3.529923254542617*^9, 3.529923279967482*^9}, {
  3.5299234390178423`*^9, 3.5299234468494883`*^9}, {3.5299236977687063`*^9, 
  3.5299237310676117`*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"vektor1", ".", "vektor2"}], "\[IndentingNewLine]", 
 RowBox[{"vektor1", ".", "vektor1"}], "\[IndentingNewLine]", 
 RowBox[{"MatrixForm", "[", 
  RowBox[{"matrix2", ".", "vektor1"}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"MatrixForm", "[", 
  RowBox[{"matrix1", ".", "matrix2"}], "]"}]}], "Input",
 CellChangeTimes->{{3.529923739412394*^9, 3.5299237711669903`*^9}}],

Cell[BoxData["6"], "Output",
 CellChangeTimes->{{3.529923748637658*^9, 3.52992377185126*^9}, 
   3.5303434528563557`*^9}],

Cell[BoxData["69"], "Output",
 CellChangeTimes->{{3.529923748637658*^9, 3.52992377185126*^9}, 
   3.530343452861456*^9}],

Cell[BoxData[
 TagBox[
  RowBox[{"(", "\[NoBreak]", 
   TagBox[GridBox[{
      {"11"},
      {"2"},
      {"11"}
     },
     GridBoxAlignment->{
      "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}},
        "RowsIndexed" -> {}},
     GridBoxSpacings->{"Columns" -> {
         Offset[0.27999999999999997`], {
          Offset[0.5599999999999999]}, 
         Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
         Offset[0.2], {
          Offset[0.4]}, 
         Offset[0.2]}, "RowsIndexed" -> {}}],
    Column], "\[NoBreak]", ")"}],
  Function[BoxForm`e$, 
   MatrixForm[BoxForm`e$]]]], "Output",
 CellChangeTimes->{{3.529923748637658*^9, 3.52992377185126*^9}, 
   3.53034345286628*^9}],

Cell[BoxData[
 TagBox[
  RowBox[{"(", "\[NoBreak]", GridBox[{
     {"1", "3", "1"},
     {"1", "1", "1"},
     {"1", "0", "1"}
    },
    GridBoxAlignment->{
     "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}}, 
      "RowsIndexed" -> {}},
    GridBoxSpacings->{"Columns" -> {
        Offset[0.27999999999999997`], {
         Offset[0.7]}, 
        Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
        Offset[0.2], {
         Offset[0.4]}, 
        Offset[0.2]}, "RowsIndexed" -> {}}], "\[NoBreak]", ")"}],
  Function[BoxForm`e$, 
   MatrixForm[BoxForm`e$]]]], "Output",
 CellChangeTimes->{{3.529923748637658*^9, 3.52992377185126*^9}, 
   3.5303434528716516`*^9}]
}, Open  ]],

Cell[TextData[{
 "Weiterhin existieren Routinen f\[UDoubleDot]r Transponierung (",
 StyleBox["Transpose", "Input"],
 "), Vektor- bzw. Kreuzprodukt (",
 StyleBox["Cross", "Input"],
 "), die Spur (",
 StyleBox["Tr", "Input"],
 "), die Determinante (",
 StyleBox["Det", "Input"],
 ") sowie die inverse Matrix (",
 StyleBox["Inverse", "Input"],
 ") oder eine n-dimensionale Diagonalmatrix (",
 StyleBox["DiagonalMatrix", "Input"],
 ")."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5299238232748737`*^9, 3.5299240614409313`*^9}, {
  3.52994068152155*^9, 3.529940695452344*^9}, {3.530343461229169*^9, 
  3.530343519961693*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"MatrixForm", "[", 
  RowBox[{"Transpose", "[", "matrix1", "]"}], "]"}]], "Input",
 CellChangeTimes->{{3.52992443125455*^9, 3.5299244369659986`*^9}, {
  3.5299246071929626`*^9, 3.529924608413844*^9}, {3.529924909204115*^9, 
  3.529924922133472*^9}}],

Cell[BoxData[
 TagBox[
  RowBox[{"(", "\[NoBreak]", GridBox[{
     {"1", "2", "0"},
     {"3", "1", "0"},
     {"0", 
      RowBox[{"-", "1"}], "1"}
    },
    GridBoxAlignment->{
     "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}}, 
      "RowsIndexed" -> {}},
    GridBoxSpacings->{"Columns" -> {
        Offset[0.27999999999999997`], {
         Offset[0.7]}, 
        Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
        Offset[0.2], {
         Offset[0.4]}, 
        Offset[0.2]}, "RowsIndexed" -> {}}], "\[NoBreak]", ")"}],
  Function[BoxForm`e$, 
   MatrixForm[BoxForm`e$]]]], "Output",
 CellChangeTimes->{
  3.529924610130175*^9, {3.529924915319812*^9, 3.529924922506332*^9}, 
   3.530343531046111*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"matrix1i", "=", 
   RowBox[{"Inverse", "[", "matrix1", "]"}]}], ";"}], "\[IndentingNewLine]", 
 RowBox[{"MatrixForm", "[", "matrix1i", "]"}]}], "Input",
 CellChangeTimes->{{3.529925158670075*^9, 3.529925208283638*^9}}],

Cell[BoxData[
 TagBox[
  RowBox[{"(", "\[NoBreak]", GridBox[{
     {
      RowBox[{"-", 
       FractionBox["1", "5"]}], 
      FractionBox["3", "5"], 
      FractionBox["3", "5"]},
     {
      FractionBox["2", "5"], 
      RowBox[{"-", 
       FractionBox["1", "5"]}], 
      RowBox[{"-", 
       FractionBox["1", "5"]}]},
     {"0", "0", "1"}
    },
    GridBoxAlignment->{
     "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}}, 
      "RowsIndexed" -> {}},
    GridBoxSpacings->{"Columns" -> {
        Offset[0.27999999999999997`], {
         Offset[0.7]}, 
        Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
        Offset[0.2], {
         Offset[0.4]}, 
        Offset[0.2]}, "RowsIndexed" -> {}}], "\[NoBreak]", ")"}],
  Function[BoxForm`e$, 
   MatrixForm[BoxForm`e$]]]], "Output",
 CellChangeTimes->{{3.529925173623992*^9, 3.529925208852076*^9}, 
   3.5303435321292973`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"MatrixForm", "[", 
  RowBox[{"matrix1", ".", "matrix1i"}], "]"}]], "Input",
 CellChangeTimes->{{3.529925288199617*^9, 3.5299252999500103`*^9}}],

Cell[BoxData[
 TagBox[
  RowBox[{"(", "\[NoBreak]", GridBox[{
     {"1", "0", "0"},
     {"0", "1", "0"},
     {"0", "0", "1"}
    },
    GridBoxAlignment->{
     "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}}, 
      "RowsIndexed" -> {}},
    GridBoxSpacings->{"Columns" -> {
        Offset[0.27999999999999997`], {
         Offset[0.7]}, 
        Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
        Offset[0.2], {
         Offset[0.4]}, 
        Offset[0.2]}, "RowsIndexed" -> {}}], "\[NoBreak]", ")"}],
  Function[BoxForm`e$, 
   MatrixForm[BoxForm`e$]]]], "Output",
 CellChangeTimes->{{3.529925293918754*^9, 3.52992530033755*^9}, 
   3.530343533480501*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"MatrixForm", "[", 
  RowBox[{"DiagonalMatrix", "[", 
   RowBox[{"{", 
    RowBox[{"a", ",", "b", ",", "c"}], "}"}], "]"}], "]"}]], "Input",
 CellChangeTimes->{{3.529925320916532*^9, 3.529925357717764*^9}}],

Cell[BoxData[
 TagBox[
  RowBox[{"(", "\[NoBreak]", GridBox[{
     {"a", "0", "0"},
     {"0", "b", "0"},
     {"0", "0", "c"}
    },
    GridBoxAlignment->{
     "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}}, 
      "RowsIndexed" -> {}},
    GridBoxSpacings->{"Columns" -> {
        Offset[0.27999999999999997`], {
         Offset[0.7]}, 
        Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
        Offset[0.2], {
         Offset[0.4]}, 
        Offset[0.2]}, "RowsIndexed" -> {}}], "\[NoBreak]", ")"}],
  Function[BoxForm`e$, 
   MatrixForm[BoxForm`e$]]]], "Output",
 CellChangeTimes->{{3.529925328469199*^9, 3.5299253580773563`*^9}, 
   3.5300187694879093`*^9, {3.5303435342611322`*^9, 3.530343552985672*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Det", "[", "matrix1", "]"}]], "Input",
 CellChangeTimes->{{3.5299407462506323`*^9, 3.5299407510644293`*^9}}],

Cell[BoxData[
 RowBox[{"-", "5"}]], "Output",
 CellChangeTimes->{3.529940752766348*^9, 3.530343554072275*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Tr", "[", "matrix1", "]"}]], "Input",
 CellChangeTimes->{{3.529940754108243*^9, 3.529940763434291*^9}}],

Cell[BoxData["3"], "Output",
 CellChangeTimes->{3.5299407637473288`*^9, 3.530343554670192*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{
   "vektor1", ",", "vektor2", ",", "matrix1", ",", "matrix2", ",", 
    "matrix1i"}], "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.530344595221383*^9, 3.530344632671605*^9}}],

Cell[CellGroupData[{

Cell[TextData[StyleBox["Aufgabe",
 FontSlant->"Italic"]], "Subsubsection",
 CellChangeTimes->{{3.529924097561617*^9, 3.529924110358605*^9}}],

Cell[TextData[{
 "Berechnen Sie die Eigenwerte und -vektoren der Matrix M! (",
 StyleBox["Hinweis",
  FontSlant->"Italic"],
 ": Sie k\[ODoubleDot]nnen mit den Ergebnissen von ",
 StyleBox["Eigenvalues", "Input"],
 " und ",
 StyleBox["Eigenvectors", "Input"],
 ", bzw. ",
 StyleBox["Eigensystem", "Input"],
 " vergleichen.)\n\nM = ",
 Cell[BoxData[
  TagBox[
   RowBox[{"(", "\[NoBreak]", GridBox[{
      {"1", 
       FractionBox["1", 
        SqrtBox["2"]], 
       RowBox[{"-", 
        FractionBox["1", 
         SqrtBox["2"]]}]},
      {
       FractionBox["1", 
        SqrtBox["2"]], 
       FractionBox["1", 
        SqrtBox["2"]], "1"},
      {"0", "1", "0"}
     },
     GridBoxAlignment->{
      "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}},
        "RowsIndexed" -> {}},
     GridBoxSpacings->{"Columns" -> {
         Offset[0.27999999999999997`], {
          Offset[0.7]}, 
         Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
         Offset[0.2], {
          Offset[0.4]}, 
         Offset[0.2]}, "RowsIndexed" -> {}}], "\[NoBreak]", ")"}],
   Function[BoxForm`e$, 
    MatrixForm[BoxForm`e$]]]], "Output",
  CellChangeTimes->{3.529940968439139*^9}],
 " "
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.529940806981792*^9, 3.529940942733818*^9}, {
  3.529941038367558*^9, 3.529941191535701*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[TextData[StyleBox["L\[ODoubleDot]sung",
 FontSlant->"Italic"]], "Subsubsection",
 CellChangeTimes->{{3.529924103003066*^9, 3.529924105066742*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"M", "=", 
   RowBox[{"{", 
    RowBox[{
     RowBox[{"{", 
      RowBox[{"1", ",", 
       RowBox[{"1", "/", 
        RowBox[{"Sqrt", "[", "2", "]"}]}], ",", 
       RowBox[{
        RowBox[{"-", "1"}], "/", 
        RowBox[{"Sqrt", "[", "2", "]"}]}]}], "}"}], ",", 
     RowBox[{"{", 
      RowBox[{
       RowBox[{"1", "/", 
        RowBox[{"Sqrt", "[", "2", "]"}]}], ",", 
       RowBox[{"1", "/", 
        RowBox[{"Sqrt", "[", "2", "]"}]}], ",", "1"}], "}"}], ",", 
     RowBox[{"{", 
      RowBox[{"0", ",", "1", ",", "0"}], "}"}]}], "}"}]}], 
  ";"}], "\[IndentingNewLine]", 
 RowBox[{"MatrixForm", "[", "M", "]"}]}], "Input",
 CellChangeTimes->{{3.529940949037599*^9, 3.529940968017819*^9}}],

Cell[BoxData[
 TagBox[
  RowBox[{"(", "\[NoBreak]", GridBox[{
     {"1", 
      FractionBox["1", 
       SqrtBox["2"]], 
      RowBox[{"-", 
       FractionBox["1", 
        SqrtBox["2"]]}]},
     {
      FractionBox["1", 
       SqrtBox["2"]], 
      FractionBox["1", 
       SqrtBox["2"]], "1"},
     {"0", "1", "0"}
    },
    GridBoxAlignment->{
     "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}}, 
      "RowsIndexed" -> {}},
    GridBoxSpacings->{"Columns" -> {
        Offset[0.27999999999999997`], {
         Offset[0.7]}, 
        Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
        Offset[0.2], {
         Offset[0.4]}, 
        Offset[0.2]}, "RowsIndexed" -> {}}], "\[NoBreak]", ")"}],
  Function[BoxForm`e$, 
   MatrixForm[BoxForm`e$]]]], "Output",
 CellChangeTimes->{3.529940968439139*^9, 3.5299431192537003`*^9, 
  3.53001788764564*^9, 3.530343667070722*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"lhs", "=", 
   RowBox[{"M", "-", 
    RowBox[{"la", "*", 
     RowBox[{"DiagonalMatrix", "[", 
      RowBox[{"{", 
       RowBox[{"1", ",", "1", ",", "1"}], "}"}], "]"}]}]}]}], 
  ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"MatrixForm", "[", "lhs", "]"}], "\[Equal]", "0"}]}], "Input",
 CellChangeTimes->{{3.529941320849429*^9, 3.529941375956663*^9}, 
   3.5299414245196447`*^9, {3.529941521705737*^9, 3.529941680521791*^9}, {
   3.5299417573061953`*^9, 3.52994176121692*^9}}],

Cell[BoxData[
 RowBox[{
  TagBox[
   RowBox[{"(", "\[NoBreak]", GridBox[{
      {
       RowBox[{"1", "-", "la"}], 
       FractionBox["1", 
        SqrtBox["2"]], 
       RowBox[{"-", 
        FractionBox["1", 
         SqrtBox["2"]]}]},
      {
       FractionBox["1", 
        SqrtBox["2"]], 
       RowBox[{
        FractionBox["1", 
         SqrtBox["2"]], "-", "la"}], "1"},
      {"0", "1", 
       RowBox[{"-", "la"}]}
     },
     GridBoxAlignment->{
      "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}},
        "RowsIndexed" -> {}},
     GridBoxSpacings->{"Columns" -> {
         Offset[0.27999999999999997`], {
          Offset[0.7]}, 
         Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
         Offset[0.2], {
          Offset[0.4]}, 
         Offset[0.2]}, "RowsIndexed" -> {}}], "\[NoBreak]", ")"}],
   Function[BoxForm`e$, 
    MatrixForm[BoxForm`e$]]], "\[Equal]", "0"}]], "Output",
 CellChangeTimes->{{3.5299416771718693`*^9, 3.5299416811089973`*^9}, 
   3.529941763198901*^9, 3.5299431199713507`*^9, 3.530017888155301*^9, 
   3.5303436680116034`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"eVal", "=", 
  RowBox[{"la", "/.", 
   RowBox[{"Solve", "[", 
    RowBox[{
     RowBox[{
      RowBox[{"Det", "[", "lhs", "]"}], "\[Equal]", "0"}], ",", "la"}], 
    "]"}]}]}]], "Input",
 CellChangeTimes->{{3.529941378207004*^9, 3.529941406704925*^9}, 
   3.529941522725939*^9, {3.529941604304945*^9, 3.529941615096375*^9}, {
   3.52994168558502*^9, 3.529941690786097*^9}, {3.5299417464274273`*^9, 
   3.529941752323112*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"1", ",", 
   RowBox[{
    FractionBox["1", "4"], " ", 
    RowBox[{"(", 
     RowBox[{
      SqrtBox["2"], "-", 
      SqrtBox["26"]}], ")"}]}], ",", 
   RowBox[{
    FractionBox["1", "4"], " ", 
    RowBox[{"(", 
     RowBox[{
      SqrtBox["2"], "+", 
      SqrtBox["26"]}], ")"}]}]}], "}"}]], "Output",
 CellChangeTimes->{{3.529941383000492*^9, 3.5299414074451847`*^9}, 
   3.52994152541329*^9, {3.529941605043667*^9, 3.5299416155985928`*^9}, 
   3.5299416928568296`*^9, 3.529941766566107*^9, 3.529943120907881*^9, 
   3.530017889019312*^9, 3.5303436688669786`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{
   RowBox[{"eVec", "=", 
    RowBox[{"{", 
     RowBox[{"v1", ",", "v2", ",", "v3"}], "}"}]}], ";"}], 
  "\[IndentingNewLine]"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"eqns1", "=", 
   RowBox[{
    RowBox[{
     RowBox[{"(", 
      RowBox[{"0", "\[Equal]", "#"}], ")"}], "&"}], "/@", 
    RowBox[{"(", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{"lhs", "/.", 
        RowBox[{"{", 
         RowBox[{"la", "\[Rule]", 
          RowBox[{"eVal", "[", 
           RowBox[{"[", "1", "]"}], "]"}]}], "}"}]}], ")"}], ".", "eVec"}], 
     ")"}]}]}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{"eVec1", "=", 
    RowBox[{"eVec", "/.", 
     RowBox[{
      RowBox[{"Solve", "[", 
       RowBox[{
        RowBox[{"Append", "[", 
         RowBox[{"eqns1", ",", 
          RowBox[{"v3", "\[Equal]", "1"}]}], "]"}], ",", "eVec"}], "]"}], "[", 
      RowBox[{"[", "1", "]"}], "]"}]}]}], ";"}], 
  "\[IndentingNewLine]"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"eqns2", "=", 
   RowBox[{
    RowBox[{
     RowBox[{"(", 
      RowBox[{"0", "\[Equal]", "#"}], ")"}], "&"}], "/@", 
    RowBox[{"(", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{"lhs", "/.", 
        RowBox[{"{", 
         RowBox[{"la", "\[Rule]", 
          RowBox[{"eVal", "[", 
           RowBox[{"[", "2", "]"}], "]"}]}], "}"}]}], ")"}], ".", "eVec"}], 
     ")"}]}]}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{"eVec2", "=", 
    RowBox[{"eVec", "/.", 
     RowBox[{
      RowBox[{"Solve", "[", 
       RowBox[{
        RowBox[{"Append", "[", 
         RowBox[{"eqns2", ",", 
          RowBox[{"v3", "\[Equal]", "1"}]}], "]"}], ",", "eVec"}], "]"}], "[", 
      RowBox[{"[", "1", "]"}], "]"}]}]}], ";"}], 
  "\[IndentingNewLine]"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"eqns3", "=", 
   RowBox[{
    RowBox[{
     RowBox[{"(", 
      RowBox[{"0", "\[Equal]", "#"}], ")"}], "&"}], "/@", 
    RowBox[{"(", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{"lhs", "/.", 
        RowBox[{"{", 
         RowBox[{"la", "\[Rule]", 
          RowBox[{"eVal", "[", 
           RowBox[{"[", "3", "]"}], "]"}]}], "}"}]}], ")"}], ".", "eVec"}], 
     ")"}]}]}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{"eVec3", "=", 
    RowBox[{"eVec", "/.", 
     RowBox[{
      RowBox[{"Solve", "[", 
       RowBox[{
        RowBox[{"Append", "[", 
         RowBox[{"eqns3", ",", 
          RowBox[{"v3", "\[Equal]", "1"}]}], "]"}], ",", "eVec"}], "]"}], "[", 
      RowBox[{"[", "1", "]"}], "]"}]}]}], ";"}], 
  "\[IndentingNewLine]"}], "\[IndentingNewLine]", 
 RowBox[{"MatrixForm", "/@", 
  RowBox[{"{", 
   RowBox[{"eVec1", ",", "eVec2", ",", "eVec3"}], "}"}]}]}], "Input",
 CellChangeTimes->{{3.52994170039684*^9, 3.52994173958657*^9}, {
   3.5299417711684647`*^9, 3.52994187527917*^9}, {3.5299419079283257`*^9, 
   3.5299419089877987`*^9}, {3.529942448669002*^9, 3.529942462167162*^9}, {
   3.529942502948172*^9, 3.5299425946179667`*^9}, {3.529943158828876*^9, 
   3.529943175226305*^9}, {3.529943280787464*^9, 3.5299432826696043`*^9}, {
   3.5299433158281393`*^9, 3.529943414368216*^9}, {3.52994344565987*^9, 
   3.529943460985446*^9}, 3.53001776834191*^9, {3.530017811348209*^9, 
   3.53001788045273*^9}, {3.530017963833618*^9, 3.530018083590289*^9}, {
   3.530018270968755*^9, 3.5300183608015947`*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   TagBox[
    RowBox[{"(", "\[NoBreak]", 
     TagBox[GridBox[{
        {
         RowBox[{"-", "1"}]},
        {"1"},
        {"1"}
       },
       GridBoxAlignment->{
        "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, 
         "Rows" -> {{Baseline}}, "RowsIndexed" -> {}},
       GridBoxSpacings->{"Columns" -> {
           Offset[0.27999999999999997`], {
            Offset[0.5599999999999999]}, 
           Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
           Offset[0.2], {
            Offset[0.4]}, 
           Offset[0.2]}, "RowsIndexed" -> {}}],
      Column], "\[NoBreak]", ")"}],
    Function[BoxForm`e$, 
     MatrixForm[BoxForm`e$]]], ",", 
   TagBox[
    RowBox[{"(", "\[NoBreak]", 
     TagBox[GridBox[{
        {
         FractionBox["1", 
          SqrtBox["2"]]},
        {
         RowBox[{
          FractionBox["1", "4"], " ", 
          RowBox[{"(", 
           RowBox[{
            SqrtBox["2"], "-", 
            SqrtBox["26"]}], ")"}]}]},
        {"1"}
       },
       GridBoxAlignment->{
        "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, 
         "Rows" -> {{Baseline}}, "RowsIndexed" -> {}},
       GridBoxSpacings->{"Columns" -> {
           Offset[0.27999999999999997`], {
            Offset[0.5599999999999999]}, 
           Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
           Offset[0.2], {
            Offset[0.4]}, 
           Offset[0.2]}, "RowsIndexed" -> {}}],
      Column], "\[NoBreak]", ")"}],
    Function[BoxForm`e$, 
     MatrixForm[BoxForm`e$]]], ",", 
   TagBox[
    RowBox[{"(", "\[NoBreak]", 
     TagBox[GridBox[{
        {
         FractionBox["1", 
          SqrtBox["2"]]},
        {
         RowBox[{
          FractionBox["1", "4"], " ", 
          RowBox[{"(", 
           RowBox[{
            SqrtBox["2"], "+", 
            SqrtBox["26"]}], ")"}]}]},
        {"1"}
       },
       GridBoxAlignment->{
        "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, 
         "Rows" -> {{Baseline}}, "RowsIndexed" -> {}},
       GridBoxSpacings->{"Columns" -> {
           Offset[0.27999999999999997`], {
            Offset[0.5599999999999999]}, 
           Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
           Offset[0.2], {
            Offset[0.4]}, 
           Offset[0.2]}, "RowsIndexed" -> {}}],
      Column], "\[NoBreak]", ")"}],
    Function[BoxForm`e$, 
     MatrixForm[BoxForm`e$]]]}], "}"}]], "Output",
 CellChangeTimes->{{3.529941710380806*^9, 3.529941718738882*^9}, 
   3.529941773839684*^9, {3.529941814052411*^9, 3.529941836432173*^9}, 
   3.529941875767912*^9, 3.529941909419869*^9, 3.529942417877187*^9, 
   3.529942493987506*^9, {3.5299425583232117`*^9, 3.5299425950432367`*^9}, 
   3.52994312148597*^9, 3.529943283159837*^9, {3.5299433163262453`*^9, 
   3.5299434150705748`*^9}, {3.529943446695179*^9, 3.529943461240211*^9}, {
   3.530017884355136*^9, 3.530017897271275*^9}, 3.530017974968226*^9, {
   3.530018038439458*^9, 3.5300180488886003`*^9}, 3.530018084135996*^9, {
   3.530018275945552*^9, 3.530018290728407*^9}, {3.530018347949839*^9, 
   3.530018361060915*^9}, {3.530343669829452*^9, 3.530343676156476*^9}}]
}, Open  ]],

Cell[TextData[{
 "(Siehe ",
 Cell[BoxData[
  ButtonBox["Function",
   BaseStyle->"Link",
   ButtonData->"paclet:ref/Function"]]],
 ", ",
 Cell[BoxData[
  ButtonBox["Map",
   BaseStyle->"Link",
   ButtonData->"paclet:ref/Map"]]],
 ".)"
}], "Text",
 CellChangeTimes->{{3.530427244125595*^9, 3.530427252283286*^9}, {
  3.530427321770133*^9, 3.530427344522046*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"Eigenvalues", "[", "M", "]"}], "\[IndentingNewLine]", 
 RowBox[{"MatrixForm", "/@", 
  RowBox[{"Eigenvectors", "[", "M", "]"}]}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{
    RowBox[{"Eigensystem", "[", "M", "]"}], " ", "macht", " ", "beides", " ", 
    "gleichzeitig"}], " ", "*)"}]}]}], "Input",
 CellChangeTimes->{{3.529940972515011*^9, 3.529941025124592*^9}, {
  3.529941216713105*^9, 3.529941229544491*^9}, {3.529942412823962*^9, 
  3.529942413405086*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   RowBox[{
    FractionBox["1", "4"], " ", 
    RowBox[{"(", 
     RowBox[{
      SqrtBox["2"], "+", 
      SqrtBox["26"]}], ")"}]}], ",", "1", ",", 
   RowBox[{
    FractionBox["1", "4"], " ", 
    RowBox[{"(", 
     RowBox[{
      SqrtBox["2"], "-", 
      SqrtBox["26"]}], ")"}]}]}], "}"}]], "Output",
 CellChangeTimes->{{3.529940981656872*^9, 3.529941025603792*^9}, 
   3.529941234089364*^9, 3.5303436828333893`*^9}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   TagBox[
    RowBox[{"(", "\[NoBreak]", 
     TagBox[GridBox[{
        {
         FractionBox["1", 
          SqrtBox["2"]]},
        {
         RowBox[{
          FractionBox["1", "4"], " ", 
          RowBox[{"(", 
           RowBox[{
            SqrtBox["2"], "+", 
            SqrtBox["26"]}], ")"}]}]},
        {"1"}
       },
       GridBoxAlignment->{
        "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, 
         "Rows" -> {{Baseline}}, "RowsIndexed" -> {}},
       GridBoxSpacings->{"Columns" -> {
           Offset[0.27999999999999997`], {
            Offset[0.5599999999999999]}, 
           Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
           Offset[0.2], {
            Offset[0.4]}, 
           Offset[0.2]}, "RowsIndexed" -> {}}],
      Column], "\[NoBreak]", ")"}],
    Function[BoxForm`e$, 
     MatrixForm[BoxForm`e$]]], ",", 
   TagBox[
    RowBox[{"(", "\[NoBreak]", 
     TagBox[GridBox[{
        {
         RowBox[{"-", "1"}]},
        {"1"},
        {"1"}
       },
       GridBoxAlignment->{
        "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, 
         "Rows" -> {{Baseline}}, "RowsIndexed" -> {}},
       GridBoxSpacings->{"Columns" -> {
           Offset[0.27999999999999997`], {
            Offset[0.5599999999999999]}, 
           Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
           Offset[0.2], {
            Offset[0.4]}, 
           Offset[0.2]}, "RowsIndexed" -> {}}],
      Column], "\[NoBreak]", ")"}],
    Function[BoxForm`e$, 
     MatrixForm[BoxForm`e$]]], ",", 
   TagBox[
    RowBox[{"(", "\[NoBreak]", 
     TagBox[GridBox[{
        {
         FractionBox["1", 
          SqrtBox["2"]]},
        {
         RowBox[{
          FractionBox["1", "4"], " ", 
          RowBox[{"(", 
           RowBox[{
            SqrtBox["2"], "-", 
            SqrtBox["26"]}], ")"}]}]},
        {"1"}
       },
       GridBoxAlignment->{
        "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, 
         "Rows" -> {{Baseline}}, "RowsIndexed" -> {}},
       GridBoxSpacings->{"Columns" -> {
           Offset[0.27999999999999997`], {
            Offset[0.5599999999999999]}, 
           Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
           Offset[0.2], {
            Offset[0.4]}, 
           Offset[0.2]}, "RowsIndexed" -> {}}],
      Column], "\[NoBreak]", ")"}],
    Function[BoxForm`e$, 
     MatrixForm[BoxForm`e$]]]}], "}"}]], "Output",
 CellChangeTimes->{{3.529940981656872*^9, 3.529941025603792*^9}, 
   3.529941234089364*^9, 3.530343682884198*^9}]
}, Open  ]],

Cell[TextData[{
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " sortiert Eigenwerte und entsprechend deren Eigenvektoren nach abnehmendem \
Absolutbetrag."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530018188027873*^9, 3.530018219123913*^9}, 
   3.530018420440619*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"SortBy", "[", 
  RowBox[{"eVal", ",", 
   RowBox[{
    RowBox[{"Abs", "[", 
     RowBox[{"N", "[", "#", "]"}], "]"}], "&"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.530018233642256*^9, 3.530018253010352*^9}, {
  3.530018388800171*^9, 3.530018405989915*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   RowBox[{
    FractionBox["1", "4"], " ", 
    RowBox[{"(", 
     RowBox[{
      SqrtBox["2"], "-", 
      SqrtBox["26"]}], ")"}]}], ",", "1", ",", 
   RowBox[{
    FractionBox["1", "4"], " ", 
    RowBox[{"(", 
     RowBox[{
      SqrtBox["2"], "+", 
      SqrtBox["26"]}], ")"}]}]}], "}"}]], "Output",
 CellChangeTimes->{{3.530018245334236*^9, 3.5300182536214733`*^9}, {
   3.530018390032814*^9, 3.5300184066801643`*^9}, 3.530343700650811*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{
   "M", ",", "lhs", ",", "la", ",", "eVal", ",", "eVec", ",", "v1", ",", "v2",
     ",", "v3", ",", "eqns1", ",", "eVec1", ",", "eqns2", ",", "eVec2", ",", 
    "eqns3", ",", "eVec3"}], "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.529941856495804*^9, 3.529941861773181*^9}, {
  3.529943084685543*^9, 3.529943099977662*^9}, {3.530344684377718*^9, 
  3.530344714720039*^9}, {3.530427213451185*^9, 3.5304272248116302`*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[TextData[{
 StyleBox["Bemerkung",
  FontSlant->"Italic"],
 " zu Listen"
}], "Subsubsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5299412747960052`*^9, 3.529941308619627*^9}}],

Cell[TextData[{
 "Man sollte beachten, dass die Operationen \[OpenCurlyDoubleQuote]",
 StyleBox["+", "Input"],
 "\[OpenCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["-", "Input"],
 "\[OpenCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["*", "Input"],
 "\[CloseCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["/", "Input"],
 "\[CloseCurlyDoubleQuote] sowie viele (\[OpenCurlyDoubleQuote]",
 StyleBox["Listable", "Input"],
 "\[CloseCurlyDoubleQuote]) Funktionen elementweise wirken (auch bei \
verschachtelten Listen)."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530018810819345*^9, 3.5300188663433867`*^9}, {
  3.530018968444167*^9, 3.530019051728306*^9}, {3.530019392325416*^9, 
  3.530019403330628*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Attributes", "[", "Plus", "]"}]], "Input",
 CellChangeTimes->{{3.5300190176242867`*^9, 3.530019024298649*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
  "Flat", ",", "Listable", ",", "NumericFunction", ",", "OneIdentity", ",", 
   "Orderless", ",", "Protected"}], "}"}]], "Output",
 CellChangeTimes->{{3.530019022100004*^9, 3.53001902476936*^9}, {
   3.5303437357461843`*^9, 3.5303437496898327`*^9}, 3.530343789627598*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Attributes", "[", "Exp", "]"}]], "Input",
 CellChangeTimes->{{3.5300190176242867`*^9, 3.530019024298649*^9}, {
  3.5300190794203997`*^9, 3.530019079790769*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
  "Listable", ",", "NumericFunction", ",", "Protected", ",", 
   "ReadProtected"}], "}"}]], "Output",
 CellChangeTimes->{3.530019080195101*^9, 3.53034375046607*^9, 
  3.530343790201406*^9}]
}, Open  ]],

Cell[BoxData[{
 RowBox[{
  RowBox[{"liste1", "=", 
   RowBox[{"{", 
    RowBox[{"a", ",", "b", ",", "c"}], "}"}]}], 
  ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"liste2", "=", 
   RowBox[{"{", 
    RowBox[{"x", ",", "y", ",", "z"}], "}"}]}], 
  ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"liste3", "=", 
   RowBox[{"{", 
    RowBox[{
     RowBox[{"{", 
      RowBox[{"i", ",", "j"}], "}"}], ",", 
     RowBox[{"{", 
      RowBox[{"k", ",", "l"}], "}"}]}], "}"}]}], ";"}]}], "Input",
 CellChangeTimes->{{3.5300191023933973`*^9, 3.530019204796969*^9}, {
  3.530019416110197*^9, 3.5300194377221537`*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"25", "*", "liste1"}]], "Input",
 CellChangeTimes->{{3.530019219790166*^9, 3.530019222838554*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   RowBox[{"25", " ", "a"}], ",", 
   RowBox[{"25", " ", "b"}], ",", 
   RowBox[{"25", " ", "c"}]}], "}"}]], "Output",
 CellChangeTimes->{3.5300192232036123`*^9, 3.530343757912806*^9, 
  3.530343791281262*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"liste1", "*", "liste2"}], "\[IndentingNewLine]", 
 RowBox[{"liste1", ".", "liste2"}]}], "Input",
 CellChangeTimes->{{3.5300191023933973`*^9, 3.5300192069779987`*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   RowBox[{"a", " ", "x"}], ",", 
   RowBox[{"b", " ", "y"}], ",", 
   RowBox[{"c", " ", "z"}]}], "}"}]], "Output",
 CellChangeTimes->{3.530019210894868*^9, 3.53034375994803*^9, 
  3.530343792002287*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"a", " ", "x"}], "+", 
  RowBox[{"b", " ", "y"}], "+", 
  RowBox[{"c", " ", "z"}]}]], "Output",
 CellChangeTimes->{3.530019210894868*^9, 3.53034375994803*^9, 
  3.530343792008658*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"liste1", "/", "liste2"}]], "Input",
 CellChangeTimes->{{3.5300191023933973`*^9, 3.530019213201497*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   FractionBox["a", "x"], ",", 
   FractionBox["b", "y"], ",", 
   FractionBox["c", "z"]}], "}"}]], "Output",
 CellChangeTimes->{{3.530019124046578*^9, 3.530019164115448*^9}, 
   3.530019213601358*^9, 3.530343796279492*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Exp", "[", "liste2", "]"}]], "Input",
 CellChangeTimes->{{3.530019244490851*^9, 3.530019258671961*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   SuperscriptBox["\[ExponentialE]", "x"], ",", 
   SuperscriptBox["\[ExponentialE]", "y"], ",", 
   SuperscriptBox["\[ExponentialE]", "z"]}], "}"}]], "Output",
 CellChangeTimes->{3.530019258904833*^9, 3.530343796862865*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"liste3", "+", "1"}]], "Input",
 CellChangeTimes->{{3.5300194417661552`*^9, 3.530019508219667*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     RowBox[{"1", "+", "i"}], ",", 
     RowBox[{"1", "+", "j"}]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{
     RowBox[{"1", "+", "k"}], ",", 
     RowBox[{"1", "+", "l"}]}], "}"}]}], "}"}]], "Output",
 CellChangeTimes->{{3.530019456397448*^9, 3.530019508560623*^9}, 
   3.530343797652006*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"{", 
   RowBox[{"u", ",", "v"}], "}"}], "*", "liste3"}]], "Input",
 CellChangeTimes->{{3.5300195125681553`*^9, 3.5300195305512257`*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     RowBox[{"i", " ", "u"}], ",", 
     RowBox[{"j", " ", "u"}]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{
     RowBox[{"k", " ", "v"}], ",", 
     RowBox[{"l", " ", "v"}]}], "}"}]}], "}"}]], "Output",
 CellChangeTimes->{{3.53001952235009*^9, 3.530019531042366*^9}, 
   3.5303437985716953`*^9}]
}, Open  ]],

Cell[BoxData[{
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{
   "liste1", ",", "liste2", ",", "liste3", ",", "a", ",", "b", ",", "c", ",", 
    "x", ",", "y", ",", "z", ",", "i", ",", "j", ",", "k", ",", "l"}], "]"}], 
  ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{
    RowBox[{"verwendete", " ", "Symbole"}], ",", " ", 
    RowBox[{"die", " ", "nicht", " ", "gesetzt", " ", "wurden", " ", 
     RowBox[{"(", 
      RowBox[{"a", ",", "b", ",", "..."}], ")"}], " ", "eigentlich", " ", 
     "unn\[ODoubleDot]tig"}]}], " ", "*)"}]}]}], "Input",
 CellChangeTimes->{{3.5303437634803047`*^9, 3.530343785693927*^9}, {
  3.530427369270153*^9, 3.530427418110138*^9}}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["2.6 Plotten in 2D und 3D", "Subsubtitle",
 CellChangeTimes->{{3.5297413490390368`*^9, 3.529741351366197*^9}, {
   3.529741591432526*^9, 3.529741601382472*^9}, 3.529773051416176*^9, {
   3.529924376296419*^9, 3.529924378680689*^9}, {3.530191463543275*^9, 
   3.530191466883074*^9}}],

Cell[TextData[{
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " ist \[ADoubleDot]u",
 "\[SZ]",
 "erst m\[ADoubleDot]chtig, was die Visualisierung von Daten angeht. Das \
betrifft hier vorwiegend das einfache Plotten von Funktionen, parametrischen \
Darstellungen oder diskreten Datenpunkten in 2 oder 3 Dimensionen."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530249139332801*^9, 3.5302493287651243`*^9}, {
   3.530334930039832*^9, 3.530334931024352*^9}, 3.530335144757416*^9}],

Cell[CellGroupData[{

Cell["\<\
2-dimensionales Plotten von Funktionen\
\>", "Subsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.53024937228185*^9, 3.530249374468267*^9}, {
  3.530249468561273*^9, 3.5302494811926203`*^9}, {3.530265768353744*^9, 
  3.530265773832037*^9}}],

Cell[TextData[{
 "Zun",
 "\[ADoubleDot]",
 "chst ein Blick auf die Syntax des ",
 StyleBox["Plot", "Input"],
 "-Befehls:"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5302505650638638`*^9, 3.530250586938047*^9}, 
   3.530334932267405*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"?", "Plot"}]], "Input",
 CellChangeTimes->{{3.530250529928145*^9, 3.530250531439773*^9}}],

Cell[BoxData[
 RowBox[{
  StyleBox["\<\"\!\(\*RowBox[{\\\"Plot\\\", \\\"[\\\", RowBox[{StyleBox[\\\"f\
\\\", \\\"TI\\\"], \\\",\\\", RowBox[{\\\"{\\\", RowBox[{StyleBox[\\\"x\\\", \
\\\"TI\\\"], \\\",\\\", SubscriptBox[StyleBox[\\\"x\\\", \\\"TI\\\"], \
StyleBox[\\\"min\\\", \\\"TI\\\"]], \\\",\\\", \
SubscriptBox[StyleBox[\\\"x\\\", \\\"TI\\\"], StyleBox[\\\"max\\\", \
\\\"TI\\\"]]}], \\\"}\\\"}]}], \\\"]\\\"}]\) generates a plot of \
\!\(\*StyleBox[\\\"f\\\", \\\"TI\\\"]\) as a function of \!\(\*StyleBox[\\\"x\
\\\", \\\"TI\\\"]\) from \!\(\*SubscriptBox[StyleBox[\\\"x\\\", \\\"TI\\\"], \
StyleBox[\\\"min\\\", \\\"TI\\\"]]\) to \
\!\(\*SubscriptBox[StyleBox[\\\"x\\\", \\\"TI\\\"], StyleBox[\\\"max\\\", \
\\\"TI\\\"]]\). \\n\!\(\*RowBox[{\\\"Plot\\\", \\\"[\\\", \
RowBox[{RowBox[{\\\"{\\\", RowBox[{SubscriptBox[StyleBox[\\\"f\\\", \
\\\"TI\\\"], StyleBox[\\\"1\\\", \\\"TR\\\"]], \\\",\\\", \
SubscriptBox[StyleBox[\\\"f\\\", \\\"TI\\\"], StyleBox[\\\"2\\\", \
\\\"TR\\\"]], \\\",\\\", StyleBox[\\\"\[Ellipsis]\\\", \\\"TR\\\"]}], \\\"}\\\
\"}], \\\",\\\", RowBox[{\\\"{\\\", RowBox[{StyleBox[\\\"x\\\", \\\"TI\\\"], \
\\\",\\\", SubscriptBox[StyleBox[\\\"x\\\", \\\"TI\\\"], \
StyleBox[\\\"min\\\", \\\"TI\\\"]], \\\",\\\", \
SubscriptBox[StyleBox[\\\"x\\\", \\\"TI\\\"], StyleBox[\\\"max\\\", \
\\\"TI\\\"]]}], \\\"}\\\"}]}], \\\"]\\\"}]\) plots several functions \
\!\(\*SubscriptBox[StyleBox[\\\"f\\\", \\\"TI\\\"], StyleBox[\\\"i\\\", \
\\\"TI\\\"]]\). \"\>", "MSG"], "\[NonBreakingSpace]", 
  ButtonBox[
   StyleBox["\[RightSkeleton]", "SR"],
   Active->True,
   BaseStyle->"Link",
   ButtonData->"paclet:ref/Plot"]}]], "Print", "PrintUsage",
 CellChangeTimes->{3.5303388777462597`*^9},
 CellTags->"Info3530342477-3033539"]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"1.", " ", 
    RowBox[{"Variante", ":", " ", 
     RowBox[{"einzelne", " ", "Funktion"}]}]}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{"Plot", "[", 
   RowBox[{
    RowBox[{"Sin", "[", 
     RowBox[{"Pi", "*", "x"}], "]"}], ",", 
    RowBox[{"{", 
     RowBox[{"x", ",", "0", ",", "5"}], "}"}]}], "]"}]}]], "Input",
 CellChangeTimes->{{3.53025059793933*^9, 3.530250634276848*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwVm3k8VO8XxzEIM5YZpZKtSIWIUH1T50lRSipFthItiOztlEIhRVosbbKU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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{{0, 5}, {-0.9999995444593152, 0.9999994330066376}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{3.530249528261158*^9, 3.5303388824329977`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"2.", " ", 
    RowBox[{"Variante", ":", " ", 
     RowBox[{
      RowBox[{
      "mehrere", " ", "zu", " ", "plottende", " ", "Funktionen", " ", 
       "werden", " ", "Mathematica"}], "-", 
      RowBox[{
      "typisch", " ", "als", " ", "Liste", " ", 
       "\[UDoubleDot]bergeben"}]}]}]}], " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{"Plot", "[", 
   RowBox[{
    RowBox[{"{", 
     RowBox[{
      RowBox[{"Sin", "[", 
       RowBox[{"Pi", "*", "x"}], "]"}], ",", 
      RowBox[{"Sin", "[", 
       RowBox[{"2", "*", "Pi", "*", "x"}], "]"}], ",", 
      RowBox[{
       RowBox[{"Sin", "[", 
        RowBox[{"Pi", "*", "x"}], "]"}], "/", 
       RowBox[{"(", 
        RowBox[{"Pi", "*", "x"}], ")"}]}]}], "}"}], ",", 
    RowBox[{"{", 
     RowBox[{"x", ",", "0", ",", "5"}], "}"}]}], "]"}]}]], "Input",
 CellChangeTimes->{{3.530249591581849*^9, 3.530249681928047*^9}, {
   3.530250636149786*^9, 3.5302506400373583`*^9}, 3.5303350388354607`*^9}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwVm3k8VO8XxzEIM5YZpZKtSIWIUH1T50lRSipFthItiOztlEIhRVosbbKU
bCGUpR5kKbJFyL6vM3PtBuF3f3/N6/N65s75nHPez3Pn3NfMWlsX4/M8XFxc
qhQurv+/vrply69+7uZuK+eHhVa+z3YX18kZnpQzB6W713pZeR6wVPrNV07O
AXQEEls+5fnCq4KHsnxy1+F+ecFR27wn4LTr8qUZ2UBwGth8xS43Furm7Z+O
ykbCee4DnLfZn2BZS/cGluwHYPGGy8S+/w5vy9+4jcjmgMIPY9cpxzqYjMhS
6gjOgR2BJaKXvtaBvl1Fz+/ZHJDIP3q+UKQemJQZk9y6XBhGZ1gLafWwfZfR
f4H382HDS9eo7Ik/UPPxH88GAoOjyXxoglsT3C5XOahu/R02LWV6fzzUBgnp
nxWTnn2HbgW5Zx/C2+B3hC5l/a/vwHmfVuLc0wYKdmb5q3YUg//N2hNmN9qh
nOKnyiVeAtW8ku6R8R0gsauFUV1aCtISKU8+cjoh9WNgi5NqObB1dbi1NvfA
MGM4+KBNOYj6ptutPdwDG64c3L3xaTkIw8gXwqkHonWob3tmywHNh5qoJ/dA
2M/gCxYlFbDp1cGVezf1wpWekLH9VpXQphNmdkW6D95QK3zpejUgYm/OXcfs
h927blr5nK6BxS2TLtECA9DqrKxFXK2B4BcrOQYKA7Dq94P+X4k1kH0vL2GL
5QA8jjA0CBCrhWXFG7v3lw2A7/oqkaWWWnAxVNxwPWIQ7KA2kuleB0XvmsKr
pIeBK2Y6t+VBHazW/jNqpTkMEbxSreVxdVA4biFQfHAYfvy8IPOhoQ4a1y0x
11wdho0n/sWc/68eVuUEEuzKYRi035Dczv0HDuzqyeTzHAGfCsPKSsk/cHQy
5qtYwAisUnVn52/9A63ZywLGX4zAgYn8LS/O/4H9B1qGd3wfgQ/exlknf/6B
SqvFrHpRJlwM8/5WE9oA9PVXo9a+ZQLPVEwH/tAAz4s3HX2QwYSokz+4PhY1
wPnHpwXKvzOhXEp878PJBmg5tWN1aR8TlN8nlBmYNcKKHL3ZrA0sYObV1RTJ
NsGEgcwl61gW+MnMjqVvbwLh+HVfhTNYIHVHRvztsSb4sLwvNKSABYb6Dia3
fZugdZrjJNzGgpSaxb87B5qgU/Poe0KcDc59m3oyU/9Cgpb0HZ3rbOg8/Veg
8OdfSO02/rrqHhuONwWoVvb+hSWmljIOY8P2ioHrfZLNsL1vy96LSWygpMeL
SdxvhocWvNRtzWy4omSivS6mGXrGV1637WPDYCyvlerXZogp63Q9OcqGqudn
3+tPNIOuU1raKz4CIrzW7r5q3QLlF5ScIjcTIDRdc9b3Rgt0eyjLiW4jwNvF
JzDkWQt8Hx+sPIwIsLXtqH9f0QLb+8v/rDcmQOXAK8emba3wnF7ev9uDgNeF
ho97jVthX+37rLkbBNB3/ssevdQKFxfv89++S8D0ZksewbhWWKGUPtsZSkCh
+OrIHWJt8MGmsFwgiQDNhz++6Sm3gd2EnOGydALe8V/rPabfBlWXdUYrswkI
nm1Qu+jVBq9YR659KiRg0f2eyRVyHya9ZRj8LiXAjal1825GGwT1KUrkVBBg
2vG0NGqwDVYfWunbXk/AD7N9zHeUduil1zOk/xKw8/cE/ZNMOyhUx96SbyMg
9VDsNryjHcTWOeOxTgLkSoxPVZxoh4fJ3lX3ewkI283j2+jSDgsyPvF9AwTw
fUlP6AlqB9u993ZTRwgYThSbnC9oB9OAmuiUUQKsFApWC7S2Q+1KxTNKEwRU
v3KB5TPt8OJATKXzFAG6K2XPyzE6QG5Sr+/GDAGZoVVBKps7YGbP5VijWQI2
CN1K236gA7alzvAOzxEQ5bu5Yd/ZDlAR5fAf/kcAbaF1/uitDjgcxfv+6gIB
t68Erz0V2QFPB0V6HBYJGCd27nfI7IAVc4458ksEnHMYcbpc3QHT2+s3xpO6
sTsq7M5wB6TcPLuFTer1qutbS3k64TF/ZPUiqduH/7ENxTqhMPgkfyOpI97X
c9dJd8KJLX31V0h97FzycnPlTui4M7KznYwntNZvQ8f2TjC4fVVHmNQ/dB6r
3dLrhFuiD46sJP3dM3u9Tdq4E6jbk/VG5wnY55kE+ac7QXbyjVwEmR9P6Jf9
lo6d8Cv2SrcImX9BUsmRuaud0CYQ/PAEWZ9bZb9PRvp1wra99xUcyPrp9HRY
b3/cCcW/LBINyfrOLTLtGl91wrjnvnVLZP2/SM65XEnshAzLyhAfNgFXtJdd
W/G5E+jMn9M1ZL/GL60NOF7TCS8EBwvb+whIC1QNHW/thM0pSmovuwlwjt8Z
8XioExRXyyds7CBgpNUkoZqnC8JdM36nNhKQyLFNcxbtgp0530MS6giwX+76
RViqCyget13cqgnoPRT045BWF+ReUUh3JfmMsQuvGd7TBUkHO+Xek/ye8Y1r
CjTqAr9HI1XJ+QS05n4bLLPrAoZ2Ja9iBtnvhorRC55dILLw62VkMgFm400c
vjtdkNnl/KT1HQH1myYE9kV1ganb2oKaKAJ+RWzYVPCrC57hQ3IePgQEZWqq
W//tAsLdMtP2OgEHavbsWOzrAlybOrXWnYDiZVYGOktdEB08lSx6loD8K6EO
X9S7IWBCYPsHXQJuhL1yO7m7G8ykNG+t/I+A7amJ16cPdsNejZrfJuokr33F
gZrnumHtdcc2XVkCUk7Mfkh73g2KKek8nRw2OLnyZxyJ7QabsJ59NWw2KAWL
57I/dkOGiKTg4142vPu+uVzlZzdczKkw9atmw2sN2+GE+W6Y70+s3RrLhkdi
FUpvz/TAVf+t90r2sCFnm3SWkXMPzO2v35qylQ29p13g380eCLEcdjy9ng07
U8RPnAzvgW6OUI+0AHn+GVh5C1f1gJvm00bxChbs9WVVX9/ZCxdirjpN6rPA
OREsNhj0wqPPF1LvaLEgqvZxb71pL1gIrdFrlmfBqKz2rJp7Lwjq3h9lLTHh
df6tdf0J5PVTfL9jspjAmRK9bCzRB4kfqQFnVjJBXtp2aUm+D07kd1Vn8DDB
aF9mYIp6H4Qd+/zsN2sE4sPMXgsc7oPb64w0bpL3K2O1t2XffPsgk+PR4+k0
Ain2GpLKY33AM7SWrZI1DLYtJzDlVz8Uf29iN64bAqEXXZfc/vZD3rqhZ+8E
hiDDwlmqo78fzqnk5hqwB4HSfP96LvcAaCeoaYnkDEJcU+5Wt20D8CLvJ88z
w0Ho/yOX0B4zAO8KfV5/dxyAizXM0Jzrg3BLqO0eV3AfuJX42bpsGIa3+0Q8
Mq27QKZXn3966zDwPlG88WJ3F1TwCCZ6oWG4ucn4kr10F6xHD8cCzYfhU1hr
Z2ZzJ/zNfeYT92AYBtRE/aRPdMKetHev/xLDsEzvVk+mXzvQX/xo3vtlBLbm
7+TrXNMM6a6046sMWNDWvhy+NNfA25uOw1tOjoK7SdBtlzXp+O6bf8cmmWNg
r3b745roRnx0yxc35YkxmL1efi16sBHLFHo8tp0dg/0BAe+41ZtwbvdwTQ3f
OMiYnvU5WdiEx9f/PZIiMw4rrKNd9Tr/YtvkrMMXjo6D9PC+5ZUSrXhPjrNB
06dxkFjxZW2jeicWOajkIJo7DjHrLJ9cP96JW5v7AvQLxkH4rHMm5XInvvbP
6kfmr3EIltPZVfW5E6fBof2P+8ah3a5jXlunC8uVbtA7uHICvHUtdFRQN+aq
60T5NyYg4Am2MN3ai/2Gvr29cWcC0rw8D6490YsFuV7x7AiYgDthHc9+ePZi
xmbz4qxnE1B2VcIyKasXr79fu/9j2gRo/XjsmKfVhw/uLDKK6Z+AgtL81nrV
fvwkNtYqwHgS0vdwPD0pg3hV7p2v+uaToLGf3X9GdhC/rLGW4TszCYkC+cLy
Owfxu4U1nXcuTYLwgtfnDe6D+MvJp2dvBkzCCFV/5+b2QdxK9b/o/G0Sbjg6
zC2lDGFFzwvXTihNwc+5/KUHyiN4838dx99smYLnHx5stUAjWJPLTG1Yewoe
OQlVLZ4YwbrBBv23905BnoVhTrn3CD4dp3IiyWoK4mb281+sHMHP68fVeEKm
YP569fbkc0z8KsqRevjZFDiP97z+fYWJ48709oe/mIJzCbmPKwOYOIP559Xm
hClQYW5IQ8lMXMWbQzUvnIJkhf6OVWNMzKd1e+DjxBSccnC5cMOdhWnzM0Vz
s1OAtN4ebrvDwoxC19d6XNMg6D2+SfwxC8sdtjVpoU0D46PZ+ZlUFtY5r/ed
X3EatOLozm8GWXiv8rfXx1SmwXBMxzd8moUPjmnfeKlB6hGzFhteNjbz3qiu
AdNg8M2T65IsG3s+o745ZTYNxc9p3RbH2fimpd+NhNPTMLf8XU23NRvfXbtg
MnFuGgaPX7bRcWLj0BQ2LdBtGg69fCJzzo+Nk0tqb2QGTcMf+iUBvww27p0K
N6V+nQbmrvDH03wEjtmz1aPt+zT4sdhvrMQIbP2wKuRj+TR86OKeCZIkcLMC
38/jTdMg0JihjVQJXHvcfefLiWmonnixgnqcwI/eCJs5z03DMQFnn3RLAhuO
JHgi7hlo1WlPlj1H4B93O1J6RWYg1OeuyHFPAn9LN5TbrDQDqZHmF5aHEdhr
YUBnacsMWB5tNpyJIPAOA1/z2m0zMKcvfv/tGwJnduaEXdabAc0o3bJDyQR2
VzH5uN9wBtgZd7IPZRBY7dpoxerjMxCeLPSL8YXAiaIb+L6dIeP/ZqLpIgLb
WxatDbWbgaPu34IZPwi8/v2p3bbOM+A4X9449YvA0bufXuX3moHK9qED9AYC
nw5Se9p0dwaWP3l32qCZwFIN5WmJgTNgyDNhfKCdwOGXuIeNwmcgPXg6N6qP
wCdyXvKvfT0DhV8frGUPEpjBt11+Im4G1rCcDAWYBK45WgclSTPwPV1Qe4hN
1uuls1V4Bunv+Pa/oWNkvQYFrzvkzMDQHy31pQkCC2rGP9tZMAMmC/E7NKcJ
XHobZQiXzYCBxRO2GofAfhUtVR2VZDwjF8PxWQLrrrw6kl4/AxPLGUdvzhN4
yZYh4NcyA+PFudPl/wicn5qiYNo9A7Hmoru7Fgh8Y+7Ano1D5HqmlMK3RQJv
1+89NUfMwPFY0/c2SwSeenz7xq/pGfBvDy+tIHVGm2T464UZeCe67s4/Urtu
yv7kyssB35pXDROkVr18rEaXyoFtyZJl6aQeKWAylzM4ICYrelyb1Am0AMGB
VRzIeWZ28w4Z74KZvGKOLAeSHXfueUL6UYj7pvtAkQPEoO07R9JvN2FufWoz
B8ShK1mIzCd659RNNU0O+PirnXQl8z11PzSCeycHKFmbE17OEFiyTjmrbg8H
4mPWxYZMEbhJpqw2/gAHKmfzDhmQ9Xx+0ZZ99QiHnH9E3v0cJfuVvSB00JQD
dZFPs8XIfjB4IjdIneLASSX1uzIjBK4+rLmPfZYD3TEqIhMDBD7Yd9E7zI0D
HuHnbo12EljfWz553zUOPGe4MJXbyPqvaG2evsWBRRtB/S1/Cfyf3uHtlsEc
mO9raHxSQ2DtNj474SccMExiykxUEFjj8rdnOJIDUYYnXdaUEVgpXm1C/j0H
8Dc+o7J8AivuGlzbkMIBtEWBffAzgdf9iT4akMmBHdGGeeHpZL58jFRmIQe4
Y3x5H8YTmHp+0j6rlQNeUdneA0EEFlhIDrfr4QDjRk5qli+BeZ+dL109zAHT
ltHzh70I/K+4Qf7WDAfaG8Ki/joRmKmQ067PmIU1tENRFw4ReDDfTXh21SyY
e/Bdu6tL4N4TSjpJsrNwNj3B0H4HgVv9XkSKbibXP0yvDlMk8K9e7xNN+2dB
aGDz8jOLbPzDS9s3yGgW3D5JX6mcYOPi5US6jsksDJVTTvINsXH+vjOib21n
YWX+i8763+T5FKdb7uA9CwPF/lunYtn44bllaD5jFsJC6gQP67Bx0D/snJIz
C0YJWZ2Oqmx87+m1V9YFs6Cuhh+YyrHxreKhue+VsyCpTCkIobCxs8KvrODB
WRicEbN5WsbCRr2hyjIyc6CnYJqwoMfCv5R7660U5sDckdteRJuFD3lsu/VC
aQ5UXbN1Jtaz8AGe9ppV2+bgbLLlvR18LKwrp3xF/OgctBmWHs0rZGItq5IC
gbtzwDrSZZCowcRS9bMmE31zEGR2ZOfM5DCOWnN4SZ05B076C5e+dQzj1Wej
E1zH5+DA2O4dp8qHscS4/jxrcQ78qYcl170ZxmJiT6MHV86DX/rlyF/6w5hi
qDrSZjAPpodFBgofDeHh77Y+P1LmQUtpd7gCzyCWfdx08VHmPCSa5T5l9g3g
E6eNTE7kzcO5DyOHg34O4G+cHUqdP+bBTN8/f3/oAA7bTK+f6ZkH9MlJsmbN
AN4ZjjdskPwHQwUS+/cp9+Pgi1LV/vf+wYcImrHm5l6sSm+Q3mu9AOzGZJz1
pAP3P+y/++z8AmybvzLga9SBXwnNDAw4LoCJlNvvtYIdmMa7KiP42gK8yWp/
VeXdjoenzfUbHi+AQNVc5cy5Nhzf2ubsULwAaZL9zweUWrBUQh8O2bQI0Yj1
RjeiAQvBlE3rxCIYbspxSJQvx/tZFjPrTLjQikaHMf2kAmgqOsdtocKNhs6a
Fjt4tsLonmZJbzVu1JcnHDCR2wrLCo9oRmuQ69et049xt4E2/s+ufzs3qk3p
Dwx82AZP88Qq3fW4EVavz2yJbYcjmfkRD05zo5ZT+pMNZzuhNH75lq+h3GhO
rwe99OyGdoUgg84n3GjZaqncoqfdMBW7ZEsJ50bZ2uu4KjO7QSFm+JnBK250
dxG2BE92w93XBfN/PnCjutPdfz+698DucKcydhE3KhtakWLr0AtZAcWn5aa4
0esLj55pQD8kHKxYdZ/DjXq1b+HGU/0QRfv9mzXPjdZfMOMx8eoHn9AO/Twe
HmQo4zPb8KUfDCPmVE3FeFCp/f5f42oD0P1+C/k9iQf5BHANWUoMwh+HbTnj
qjxoj6t/oYPGIPxQ3u1hrsGDVs/yuBgaDULKx0MDijt4UPAP7bsh/oNw7fOF
6kJ9HiSQn6C8bHwQRMpevpmx4UHz+MrrsKIh4A6MNT99ngfZD5rINbYMweTB
RPESex4UQGz1YU0Owd+qz/fDXHhQk+n2DSGKwxDX8NtlszcP0rON2PP2/jD8
1y+AzkbwoOdXkzRb0Ahc4LvcWVVF+hkRFw1+xARJ2Z+N87U8iFNxufBqNBOq
tktXb/xDfn5XEls7gwnaTiVf77bwIBcBz0Nqf5jAX7fihfYgD2ovLpPkW82C
+Ohsk9fcFFRylmGuGsECs1yhwxW8FJS6Md9G7z0LaPWn93GWUZB0kJ+hajYL
PJct22osQkH9TRzHy3Us2Od8Uox/DQWlveizaKCS891OTvklTQrq+rpRqcaD
DREmhkVR2ygouMt6+fxtNhi6ROeU/UdBj9Q+hkw/YENmzIGEtXsoaKWEKXGa
nB/9BCP9/xymoLUKWy0nyPlyuzzLi+cYBcULPq+PbmYDU2ePp9oJCjqbvdJY
po8NJ1yHbAMtKEj2qM+qwFk2KDTuQLvsKMiq4a6UlBwBTaMPt128SEGW950X
928iIFioWzX8EgU5Tyte3KtBwOSuIOkxDwpqMHd4n7CXnK/jmufifCgoXfXD
PuVzBFz7pjpe60vmm3dmsdaRAJWmu0OL9yjoRJ9D834PAp5SlZvMHlJQ7vET
FdF3CDjrfjOLFkX6Y9if5n9JgLZGe9amVxT0myqRzB9DgNA4ytaPpiC21KP0
xvcEpLnxf/Z5R0EZr60KRzII8FV3+PzqAwV5zsjnqX4hwHSs4nNuMgXVHQ0/
pPuVgH+uj79MZlBQr6ALo6WUgOotk1/o2RT0YtfN/85UEBAzapqjmkNBF9V8
W7OqCTBwlcq1xxQ0Ruvx/N1IgNSW27n+RRQUK7rGOrKFgFGiKzemhIKCxEST
tnQQ8NzlfV5rBckDc9a4po8ABzWh/NkqCuLbJxTfNEiADuGUL/GbgiSiBfXS
RwgQ+1idv/UPBV0fyVa1YBPQ46zx9WgTBT22WXW6bpSAbNVnXy+1UNDzpzer
pSYICGLPfA1qJ/vtcfm29hQBp1Itvr3voqDVh7svys0QsMX567fiXgoqb+p7
1MwhgKIqh7sGSD/aI4Pn5ghoYN3Fi8MUxJqKu4LnCfiQ0ofXsCmoU0JYe/gf
AV6XDhRsH6OgJZHz6/sWCDiyOanAZJKCKBVae9MWCVjHEi50n6EgzfQjjw4t
ETCd7FoYMkdBqrHlfJ9J/dOprjB5gYK2L/F9GCf1SxXtop9cvGj724Sr/3++
5sqMKOqn8CLtnmi3ZlLvTZ4voizjRddeKYTfI7WE0+nvckK8aIti+iAPqYeU
C7/vEuZF349S7Y6Q8fNH5IstxHjRGycQdyL9hSTdK74qzotS9r5lm5H+bR2H
ip9K8CLTVb/mVpD5aSkblqSv5kUrY2N2xM4SIDCSWlIlxYs+ix5J4SLr05pI
Lx2R5UW8c7pmqtMEfLzoWSogz4vULm7bpTJJwF2lxtL1irwor0bFem6M5Gl4
R5nuJl60wO1YGEGQPDkslXmp8aKjI3om+sMkT5tsf0Rq8KJZscZHJgMkT0PF
P7K1eFFSTeQqrV6SJ4egn6M7eVGqZora+TaSp02sn8LAi/S9Vcqy/pI8DR4p
V9LlRZqR/31v+EPyZL+i4twBXlT1wIUrqJLkaeO1ijuHeNGAweJhqZ8kT4PN
Fa+NeNH78JFVt4sJ6LaL/tV0ghf9kcK62bkEqNkpVxna8KJ1j5q/jMQR0O4g
65JyjhcpzWzU9HlN7mcncTERe14kXr5ZrC2crLfb/LFqZ15U7+W6ejSQgFiv
ij/HvHjRMk5NtRe5f41v4ysZt3mRD2dNislZArjuflop7suLqqU0js9YkDze
f2FeH8iLvB5StJ4ZELAyzLHNNJzMT8CAskuBgNKn1rc+R/Gi3LPGTackCfAM
Py676jUvMtroO71fjIDalztt/sbxolX3M0yuzbPhwXtqn2UGLxphpbw/RJ5n
S/lJzDOVvGjcsVuiyokNqfjNw8IaXlSjmx8dbM0Gq6InquvqedEtkzP5K4zZ
kFN207WnmcxnvbxAgDYbPH4fmjw/yItaDOrfEP9YMDAwMn+RwoeCVNw8um6z
4Plwx8sKfj7kKQdcJi7k+cyq26UixIeebb5Y8vQ0C96O591mifGhkHQxl+s6
LLBceEBxleFDHG2+kOYpJlQzVKiXd/Chl1O0uJXWTNh96dLQCx0+JHHnzs40
QyaklqWWFQEf8nt37Zr0f0x45KXuJ6bPh16oc5tcWc4Ew37thSRjPmRxzbVE
oWwEynP2EN2OfIiuc77okcIIlJw5WXf0NR8K82WeuFIwBJp5EelX3/Kh9r/Z
7zsShiBuRXPI6zg+NMJ/Imnt4yHwK7cyZCbyIfsH2HSLzRDoatqW3P9M+ou4
ud9raRAKll36/K2GD3VTTr0gNAchL/XuCxUKP8q8n6ll5tcP/IYmkuH8/Cj1
Nz31+/l+ODa0IZJbiB9VDF5v4t/fDwPylc8bxPiRw9dxuRWC/SAeuTLMR4Yf
tTeNvz75oA8cfZMD6nfwIwZ/9aZ3Ab2wxqzhspcrP5IQEEX89t1wk1vp6K82
fnT9+EgELaQFhFpvHHDOXIZyXa4UCb38Cn3v1j594yWAZj+6VykZ/8BMv65Z
io8Ayr9xZY/X7A88bvvW2t5XAOmiXWffRv/EXLJrldWDBBChtSRmyy7HkuFy
RUXhAqhxTceXl/cr8dH7sqN9GQKI68Knr3Mna3G+nbShypAA8kszbZe2b8BP
N67mzTERRFzer2J1eDux1WnF9z1mgsjfyFslVrETKzzdelDEShAdH+TKHz3Q
iTOXDoeetRVEYwRbEj3sxPXkfVPERRA5C7UtT1zehcX9mZpnAwRRQEPzGW+Z
bhzWhc8L5wmiuIY2+CrViy1WVgps/yaIlpl8mo7e2YvXHW5Osi0URM++Hzl3
3qIXZ3yZHPtcJoge0ArjQ8J78e+QTbds6wWRcolH5DmxPkzf/eT5Z5YgevxX
4f3AfB8OjbpQZiMnhApvP1+2KmcAX71y18NLXgipWv47rlk3gE8bv5YNVxRC
W7KFdmxmDWAVoYarv1SE0HXhKY1MuUH887rexm07hNDPI/a5jHuDmMdcIZBm
LISId86OYwZDeEgTaW0wEULsW0rRJTZDuEbMqmuPmRCqjz4o7Xl9CL/58WTH
1dNC6HCXyjnrhCGss50y3HVRCHWG85s78g7jyyu7D372FUIxH6t278waxlYT
C9O194TQ0xGHmVhyHtlXvTqWGSiEbFyUOnvJeYVx/9j82lAhpLiRp5gtOIJT
pwuSgl8KoZBPNi6yViN48M8bmm2WEDLhyWf+5Yxgi6enqmgDQmh/kW0Fk8HC
Up+E1jgOCyEn4oHUXQUW7qj9bPeTJYQe7j3i2qvFwudEGdz3JoVQiufxd6Jm
LOwcVLp1iZuK8t5niyxEsvCWDx4+p/ioSO/JO82ZDyw8USZXmSdARS8VPnp8
zWHha3w3L1wTpSL73sWqlCYWvuujFjkmRUWd3Ttpa5az8b43rX1H5Kjo4ePV
Qh7r2HjZt0CNVHkquue9x+j5FjYOnu+puKhERRVuzfq7Ddn4+ZWIxZ5tVDRq
bWFJv8PGH5y4zzUYU5HuXfMTaZ1s7PQgNU3TlIrO6FUNpY+wsWqi5UKYORVN
ubue955m44yBrOdHzlDRkKJosRuVwPm2F3/+uERFzIJt66s0CHzrzkqJDW5U
hBopo1I6BN4TXWzr70lFZqwDy7X0CFzaJvNvz00q+jg2s6nQlMA1ZnWqeQFU
5Do32aN/lcBhV31urg4m4y/O1LbfIrDJ880/roZQUanjuzi4R+Dmuvs2ms+p
qLGsqNjyKYFfjmumhkVS0bpPPrMSLwhsTe+eG31JxlMJ6op6S87zRjpPU2Kp
SNJn/+t/KQR+d2mok/qeiqysj51q/kRgh+Dnmy8mUlHzvHGcTw6B2T9HSxXT
qSg7YHmsYjGB0wZfiftnUtGxXo0Dij8J7LHs0Jmez1S0a5LvKLuSwJx98bNv
vlHR4mzmhcYGAnvlvfEtLqSiuu0XTD81E5hLI0p4qJiKLnHuF55uJ7BfwtNw
4R9UVHDGN+ZvF4GXyYas1aigIq0A6qR8H4GDngUmmVaR+d6UTt81SGARmp/W
zVoqitTn+qM4QmCJ2WsGxY1UtDutFOxGCRzl4lE32ExF1VGJt76NE1i6/9Ip
4XYqOsJ1ZnnfJIGjrewH1LuoqFsveqF5msAKdbZupr1U5DjhvC2aQ+AEg1Pz
NwaoSOzLaqw5R2CVgpP+b4apyNJ5e1jEPJm/trFoMYuK+mRTUiv+EXhrimHk
4CjJm0Aco2qBwNny++WFJ0l+Ip/kv1kk8H9Re1LUZ6jI/IZOEloi8DcxnW2m
c1Tk8fBDWxqpde9rF95YIHliqx0fJXXpwpZDb7hoiDrjTF0itYGn8p/vFBra
+d9R/jZS/xpebz3IT0P+gcv2BZH6qI3cEE2IhlaPM0r4SV3fKOmhLkxDT/L/
CzIm45sZrVgwEaOhcsfHTy+R/lqLRe/fEKchjTyPvpOkf+udQvQ3EjT0/WXA
LTqZX3c674vvq2nounahTdQsgS9sXFIYlKKhUx1mj8dnCDz8ejaVJkdDclJ/
RCXJ+jmvmNyuLk9De1/wdYqR9R1/wC4yUaShqi28fI1jBL7MM2R4YxMNRdZq
3nUiSD6u9TS8ViGvf6RnWcsk+SDaznxXo6HBYNWnfMMkHxeahgc0aOgyr4a6
4ADJR+tvT5o2DdVotmq39hD4wc+yABMdGgouKQsZbSV5QEWMG0BD00+fsNT/
kvslO//la10a2jIi+VP3D8lDbHrawAEaauR6Ta/7RfbX+0XTdRMashK0j0kl
+VaZfGb72oyGpIv/xTtlkv29GMossqSh1AdG1nOpBP580p+LZktDnqZvl/vH
kv1Rd9n42pmG7sWd8jMLIvDBBIeMIjcaKj2grvrMl8CVMud0BjzJ+m1TbHrr
RfaDan50y00aKnqw4qSyM4F7+nSvFd2nITNJp51cR8j+v6mKUXpAQ343JHYL
6ZN8mllUhj2ioRWBl/VbyfPidIXburPPaOgL2zmxaRO539Oif1FiacjIfTZW
k5vAOy6qzDi+o6GDoVrZPuR5FCH/ZW39BxqKUfOzekaeV6bPq6/EpdGQ/tLQ
p1V/2Pj3zUU5vW80NDXt/jMwno3VtYIOpRTSEFeuYpZUJBuHsldcWVFCQ+ml
Eq3XgtnYyGZzRV8F6df9ofZDdzYu17e6fO8vDdH6z3zcqMPGRfTcn2WTNNRu
/vcmKmHhtRV6k2ocGnJs1HrgnsXCPn61MhHzZL9ZRy65xLPw7plBD3seYWR5
o0Cq3I+Fc1tXygiKCSONXjtb/j0snPH+svtBZWHkMADBWR+ZOGaX+ppKG2EU
/cb1+t8LI7jISMh3/pwwqutu8pIxHsHd1j3Dm+yF0cY9d1q37xrB8nef5d5z
FkYy5wy2shkjOK501hzdFEZ60uqdp/OHcfyRoohPT4WRkoO45JVlwzjB5rhE
VJkwOuE/aHjt9iD+4a5y60e5MNL/zDOWfH4QD/ry9U9XCqN3R6/cyTs0iDe+
+5x1vF4Y3VWKErRbOYg/DK8xEe4SRuUfqVv/JQ/gRI/eJz5zwqhEQ+DB3tp+
nOJ/mW63WQSJukgPX1nqxUydU3f9t4gg/fllg3VdvSR/+yZit4oglwfPw+jF
vTjRdvmfzh0iqIZjHa0W0IsT4FOEhb4I8p0VDZ4X6cVxs6OyRtYiyFNgIm5O
ogdHXXJS1Xosglbdmxpop3fh+yZnD1GmRNAensmQ1V5/sVbr2w/3K0URO6Sz
Mv/XJxyx6UVK5SEx5Hw0KGCFTyVMTujH+x4WQ8K+NWmmG6rgyLfxlzuOiCH/
e4ftbaqqgP/4weB4YzFUaeltNyBcA5e9Zi96m4shBc/5Q5PmtWBcfXLjZjsx
ZPSgX0OQWQe0y8tjg++S6++Y21dMNoE9FETp+omh/wy8OKp7/8J3Qacwjr8Y
iiPG16wJ+ws3Xn+/cy5QDN04NXHCXq0Zhsrcz+iEiqEYkf0iZXYtUCpZK818
JYbu8iVmSVa3we2ChxGHcsTQ52sWZ5X/64LhtoKns7liSNd47tzHU11gOj8R
+j5fDJUel1RdcacLVLQtAikFpL8nH+T8y7qgKUnxRl6pGDqpZ9VIGHeDRji2
VK4XQyxu98K8sz3Qf2lMhkqIocGsL7Nhjn1w7IHCmpxRMXREyrqqNagP8hNO
rrQbJ/3rD63nTuyDJz1fRb9PiaHpH/L+TQN9gMyDuG7+E0PrVP8p5tv0Q9Q+
+e5hQTqKozYMbzQagMNrTOLLFehIsUYStAWGIKJXtcBSkY76r1frJskNQW+K
QAtzAx1xuV7eMbd9CLxQvpioMh2Frn7stN5hCJLPy3sdV6ejdstXY8llQyCU
NmbcuouOdHZ5eNp4D4Pp9YpLl4COukJ5+s89GYYY3fiARURHuyNlVqMPw7Dj
j9k3uX10ZOvWAN71w2A/hzedP0hHAi6xSyKbRqBs3yMutikdSb7ofu5ZPgIM
Efs1t83oSCwwRaGvbQRON+7RFrOgI8qyoNvKYyMw7TDlqHGKzE99ZsOOlUxQ
DLFqvHKWjjyvqqwzsWGC31+l1CUXOrrA2+t3lcWEmhjen6FudHQr5HHRtkUm
SDm196z1oKOXNzNX/RJhwafFx6v3XaGjJ3JbEl3VWNAtP+sX4EVH80Nun945
s2CPc5klPZCOpEvNytJ7WTDXNKRfHERHLW8PvqmbYEHmXprG1WA6qlkRIF/A
wwbF1ccE2kLoaKTvXylHlg204ubMhOdkvgcNPvSdZEOp6sIbywg6koi+KWZx
ng23I2UfiETR0Tf5FvMIdzaMO5+z8XxFR1+kNbTcg9nQtJotjOLoqMSu6XHE
VzaE+YnNjsfTUcYRxwfmP9lwiNDojX9PR0Pn1mX11LPhW/HVXGoSHclEbtl/
fIQNcS7cdo3pdHTZ5PXuVysION0sbxz0iY7WvboeEi9Lzu96+rt2ZdHR8c/1
V65sIiBI8oF47Bc6cj/n/91NhwDXkuUFzpiODPKqfX9ZE6C0ZVvS2kI64m2a
zlxpT0BPlPnz+iI62uEeM6/kSoCp62un/0rpqCPEPvTDbQLEWgpOsspIfvhY
RcvvE/BTr0c3+icdPRYtr9v/iACdNRtX81fSUY5d8im+lwRM+x/kzakiP3/t
zm8hMQR8HHUiHGvoaKeL1q+uBALWlaaX1NbR0SGJqu+tmQS0bqlP8/tDR8up
qyL8cwl49mL6xbZGOvo4rkBMYQIE3Ha6v2qmI6s3W5ZUygkoajl16mgr+f7H
S/ETVQTc1Pc5QGmnIyNCPelOHQHsNSUyDl10FDmRlTbRQkDCvQFBqR46Ypxa
fNvYQYDNmOBUVS8dxdSH193tIaC+1KhCc5COnG/xtKsOE/BI3S17YIis7+fx
RDUWAftfPnkbNULyK+cePUMQwLUsO/gwi45YGx/m3BsnINet6SoXQUffvbPG
WicJ8Gids/00SkeBIkX75qYJUNkvbXRhnI4qJYjUdg4B/emwY/UkHZ1WaFcJ
miPgjZStwq8pOton/Tzv3zwB/21VVrWdoSN76a0G8gukP4PJbRwOHd14u6ix
apEA5zNf9zyaI/l54XW1hdQCV+8dUvhHR24Ct1ZcWiIg5uERk9wFOlo9Kker
JLVO3Crro0t05GRfYzFP6obcLvt+Lga69GwfN+f/z/tqE929eBio+cPdpSJS
Cw16eDF4GWj1QKuJFanjFnXuJfAxUNHLcd5iMt7uFfyhu5cx0JsNacJzpL8m
5erIegEG0hs1clv8R4C7bkTsRSEG2uRgol5L5kMzt0nhojHQHlr4EXcy33cu
Sp+fCzOQtplmVRdZD3RvokBFlIFolVEfZWcIaH6ZX14kxkB2g37TylMEeH7y
rzdjMNChtXPx/BMEiJQbtbPFGcihx6jw4yjZ386Vg34rGGgqUMFwA5sA3ZnO
McmVDMRl4XDw0gjJl3DifNoqBrL3Miu4M/j/33/qiLatYaCsdzHrJboJSD7G
t9pDmoGKtSZlnrcToG9ftU5QloHEJNpie5sJuPHsjLbWOgbyhFQ71m8Clidv
QhXyDISWxjPek/ylFo0b2KxnoOvD92O2kHx2E36nHm5kIOfF+KDUAgK8+I3s
5JUY6JrF6OPYPAIkpFe65SgzULq6sKVdNgEHD37w61NloPMvAo9bJhGQEVeZ
tEuLgfKYlXVTYQQY5j3PqtNmILczf9psgkl+aq2xw3aynhd4J176EyC5NPb7
2U4GYjza5OBzlQBfc4k51h4Gyllr8XXBjAAZ1w6K314GGv1w/GTPUQK+3EsQ
ltQj+2NaZhZxgADmp//W6h9goIca3SWu2wg4IWJ94LURAz3Ix99bGQQofH//
3MiSgQJPj0qmFrChSoUT12rFQO6OnF0/s9hw7fmBTxdPM1CGnuzT7EQ2VDgM
Vd+zYSDd8jVSAk/Z4C6mLIjtGMhbduZ6wDk24FOpN9U8yXj3m/eJLLDAvmwx
8OtlBlrbMjVygmABQ/1IxKGrDMRtspHt3MWCC7yjmXY3GOiY/aKpdAkLaEnq
7Dc+JA+J8qIXglhgwck8I/aQgW48PhKeS2MBry2fy+tHDDR4LXXbnn9MSK0w
8VYJJfvh8uHVyxEmcL+ZjjzwhIFW+vyT/v2TCQl62+t8Ihnoa3dH9n9+TJgK
y9Mbi2cg+qeeo6vJ+1Xo5iKl398YSHwrR6c2aRgStlsK3i1goIjc2pOGT4cB
750cUC9ioLjlsT8jvIaBba4Y/7iE7E8Iy+yd4TAcuhcke+wXA00UqZZFDA8B
f4fx8pq/DES58WKcS2YIbob2LFROMtC5qUI52XMDEPbCq9V7moH88fu8NfsH
IPHdirzNHAYa3rr3OrFpAJry9197OM9AIwv5m6SJftAeSho35BFHiZJbqeFX
+2F0j+dAhag4KnfRoG+90wcXJnhrfyqJo5xwqmjwtR44nbivykpFHPnXh8Sv
NO8BUxu/CmKzOGJfHknw39ED+tWU0hXq4ujHxVOfBee6QTGJJ89mmzhizp7W
+3y9G/psueJn94qjiyHV+nUeXXDu9/y1TafEkbdVJqczoR1s08flAkPEEfV6
RFtY/B9wunv838HH4khK1q/ktPEfuHw8s5H2RBzVs6zFeJbqIWDq8qPQ5+Jo
e6LFwdqT9ZC6Y3Y+/JU4iqvpx7HL6mC2cKnhXZI4umW3Rzb+TA2E/qY9LC4T
R78pUrbLZ0sgKvaS/b2f4igq77LH9MESiPWs2nugQhxxMlumPr4shmyJ0LmK
KnEkEsb0ToXv0Gohbl/3Rxyt8a6fX/AtgA09q/d294gjO+eNoitEsmFL5g2Z
uD5xFPz5VMpSSib8598ye35AHBWtejFQdPgTGG54lTY0LI5CfmsltwWngbuj
nMzYmDi6fyu7xlL8HXjp3JnNmBBHQefXpR4+Fgv+wt31nlPi6E14GZYMiYaI
j7EPOBxx1HgSCX5e/hxifHjtcufEkUzj28ufQkIh6dh5Xa9/4sj47b1kuRX3
IHNdqfTuRXH0LOpO3pkVV+DbhOLs0pI4kvBOK/r//1n+B5ac2QM=
     "]]}, 
   {Hue[0.9060679774997897, 0.6, 0.6], LineBox[CompressedData["
1:eJwU2nc81P8fAHBnO44zSkNkhCSkLXm9G1RWpZRKilRkhFRCg+bXKCGU2RCl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     "]]}, 
   {Hue[0.1421359549995791, 0.6, 0.6], LineBox[CompressedData["
1:eJwVl3k4lN8bxjEIY5tRKQlFErJUlMhzWkhCyRJZkpSlkpQSvi2WiijJnrKn
Qoxlxn6G7FMiiqSSfR/72vJ7f/PHzPW55lznPM993+d5r3eT4+UT57g4ODgG
ia///z6/5cir7uSre+7f/z9sqG6VMTopYw1nnTh6Fwj+V1sRICPjCpv8okN/
EiwcQc8V6PCERL+O33SCnzPDpHlkboK+2+jOWwQrs50e/XO+DSXipB0aBH8X
fvH3d7s/vNziuPDtLxvkXvJrLq8EwSWuU4GeBF/c53VpQToYvg8bfl38w4b8
tu602YOhUNSXOu9O8PIFo64p58dgXN/T1fabDUmcXcELek/gh0ZkqCLBhz48
2TLfHgHC8Wa8HitsGIo9XDnrGglImWWYvsyGUKc/tjMrUfBxPP9U4xIbWldc
Iiel44A+xdvdu8CG63VSamxaPLhu2n6yY54NEk/bWOMHE8DEWud52RwbHBUR
adQ5ESxALd58hg1cKz4fZ/2SgIf3sBnfNBvaui02zuolQwIp82fmJBu8s8jF
0+0p8FnuzI2qcTYYRgzwTielgsh5myCNMTZIeleaT7mmwfW1MxdiR9jAPHhj
kr2SDtep4/XbB9mw6lvP1nHp13Cwsnci+icbOpjlXmNDr6H82d6JB9/Z8OZl
7LtR2hvQnnrS6vaNDSaeJqdHDmZBdLaA1d8vbIjmL4kedM6B2Sef7zp9YEPB
DUPPq+tyYSnFZ+RzIxsSRnavn/HLBcV9Koa769ng3kx1ntajAWev3WJDFRuo
CfVcU+15sGxkbanKYMOKMP21h04+2NDvlcsUsKHvburxyaR8IK27ocZFYwPd
+dYLtmsBZOwU0Yt6w4ZTO3ftnVgpBBMNY7/fCWxIbky8MipdDCUWo6Mtt9gw
G1uo+DO0GFh2HImXfNig78zq/bRUDMyiVx/nvdgwRlqwKGktAWpfX1nLRTbs
2WeyN/h+GTDVCkzfWLOhOec311Y2hoH448sjqkS9wG8vpMKEIiqZ7aDIBm35
yL33nZiQFvuPXi3Hhkezr2d8WpgwuvN1h8V6Nux68vmcY2YlvH1SKJLIyYbb
jcqG6qffge3FA1OfmibgFY0hnxn1Do7Oe4ttq5+AT7EHSFvev4PSUz+uXKqc
ADlnq7J1WtUwYi7AUZk/AY2kQBUOsRpoLvyoGhkzAWv3faN+rK0Fgc12wVM2
E/A2J/jbRZVG6EopMKxsH4cR6kio4ZlGoJyvuxX4cRy2XjfUVYhshOw13ZJa
deOQpENO7l1qBGn5+cLr9HGIaAg9f6qGBfXBdpqHIsfheu/jqcO2H0BI3d5D
1XgcEsmsAIpeM1xf9+vy3YIx0N3na3vHvhk+RaL6u2/GoMtdSYN9oxk6Y5rj
riWNwbpPDwfev2kG/rmsD+qhY/Ak1ujIA9EW0OeSu00+OwYBW5qE/31rgbBf
/50/JDwGztASN+bZCp7t/lEUm1HgSJkv+fawFRiNrefeHhuFWG7Jrsa0VrC7
XusCh0ahvuG81OsvrTD9Y1ZFd/soKJj/Tjm3tw3u/Dj5NefvCAy5bM36wfkZ
fF+uzb6YOAJuEf9VNId/AZrDf9ejO4bBvX9bb8HbrzC7yPtrnfIQCGwK3Ppz
TzdsWZv36eHaPngkylJMduiF5irzAfTxJzh+M8ek9wOQuGrr++PXv8CVmkDH
y1tHYGF+yb9BlAU0D0GzdUfGoXflstovTwa8jxe7mW05Dn6OBW3P5ugwUC2R
eMBpHDTsKu4ke9NBYv220Yu3x2HnVWu/x7cLIbBSL6CycBx+dcRXcDzJB0vq
7Xy3zRNEHkOq1wflwHL+lFj5ygQ0G3jPvK1JgmTfCyNqJydBc8fT8Q6zKKzG
5F+8bzcJ4t4P9lq2R2Mm9yuen2cn4ZuuhUugdSzuDuuTCfOYhK3+NmNs62dY
Ksnu5HDwJJQ/r2J5pSfh+Opj1cllk/Brxzobu+svcYTQrhfUzVNgk3LcI6wx
F28+8SnTVWEKPAtP+D+WoWFatEcxU2UKJrxn4ndfp+Fm6ew2d+0pOHh4cddN
mTwsvEOezDKfgsmoU17lHvk4xHKdd8D9KXBzDGTJc9Cxf+Jv09mxKbgiviX9
xtcSfFyt6IrSzBTUfWw7eXNzKZaqvPrEcWkK0rR81WUulOKSnpHmZp5pENH2
HbFdKcXTW74ey5aahlT51FuPxcuxY1ah8fnj0+Dmpt5cpYvx/mL3Ix3508Df
wVP5K7USCxsquoqUTEMF/Uzt86pK3NXZ/0CfOQ0rohqcSr8qsfdv2/qC99Nw
peXBYtHGKpwLRw8/6Z8G9LFwU0pkFZap3apnKD4DuuV9iak332GO1m5U5jMD
eY+0H4BMDQ4crkj2uTsDr/8+vaSuXYP5OZ5zaT0gmL334ahFDaZut64ujJqB
UxG/nYtCavCW+y2Hc3JngD91+G7BVA021K4ySRmYAWvz7yMahbW4yTQpx2F8
BjztEjkz39diM5dbotKzMzD4Pdh0qLcW20bt/fSMcxZ22Bi8LKXUYXd2nkWU
5CysjpW7VuNWh5+mpto+ODELVXx7uVyp9Xhdyd1yfetZ8L717/hZ+Xqc0Hxa
isdhFmajhyTl99bjl382dN+9NAvP1+zS5zlTj4tORp71fTAL+c89UxWz6nEX
OcjNvWIWdt4VD1q3pwE7bD7LUq6ZhT00Xe0XBg24f89+5VHWLOgoWs+OWTXg
iXN/xp2/zgJtvjCu37sBczK9rpyZnYVMVfXBQ/QGLH/tvLe54hyAL79IrXwj
3r73p1mi2hxMFDvFcu1sxLs4rFRHNOfgW6fSuAg04gOhRwZuH5wDUv96heeW
jdg+Tdk803YOKoQDdwcENOJzbumq845zcHk11+XDjxrxRTUp8n7XOXhiOdTW
FduIfcpEqr54zYG4e4+Db3Yjjm6bVuV6PAcR/9nNP2hrxM/jL5CNo+bgKPmV
ZMf3Rpzm0DcQ84w479Dsz8WBRpw39vn59ldzcHJIzztnsRE3cReTrSvnYFNi
ZuT0ehb+3Kg+mFo3B1zdSfrNm1i4K/xN1cSHOVizL17kzjYWHpFMuBnYOQfS
3VPylntYmEfj9mDOzBwYazvs/mHGwoIrC1XLS3MwFuh80eQUC1MrPV7occyD
xoGMfU8cWFjG2NHim+A82DzPXX50kYW3in1Tkxebh5Gadn5DTxZW+WomeGX9
PBzVnl5pv8HCOuf03vHKz4PqhfiWi/4sfFCp4oWp8jzsGO/+evU+CxtOafok
7JiHk0KhwiahLGz1n4L6DpgH+6JTBn5RLHz6YLLgf3rzUHzx0dXmOBY+zy8x
VHd0Hta26osvPmfha1HkRDureTBO1Vpblc7CvjaBPq/s58Epoz3W6TUL+2/6
YzHjNA93TCt7OrNYODx7QjD4yjw8/iW48WA+C8dcdR5qvTEPWqxNmhp0Fn6h
1f1O6tY8BMkMOa8UsXBWTYtPQcg8PL/PcOGuYOH8h4aW/8Ln4cVwxZnDTBYu
MX2nbhgzD4Grr9XZV7FwpbiOUNTzefDK0skxrGbh+u8FQz9T52FlbYYKuZaF
P6Zur1Z8Mw8DVm42SXUs/MX1ZaJX7jxMz5w7KtDAwt9VpX2Z9Hmwqk5efaSR
hfvmYizJ5fOg8MP4gy2LhVP277z6/d08qGlEbz75ntAnrOlxTuM8NBsprZH+
wMKSX12z7rbMw1O/icoCgjvleBrMOubhfseC3romFo71SOrf8nMeZH9HVRwh
2LJMm2uxfx7+tBkf+T+v5muXahybB/VLnSRxglvMPLUTZgi9CpUF84n9HiUK
Wbkvz8O9YxfubCTYaPTVNcS5AF8sp29ZEvUI7D70hMq3ADOKZvL2RL31/j+z
+4QXYN8e86hdRD/3mnwa6WsWYII5OfK1nsiDxNrBB5ILUJ1upW9C6MFxnkay
kV0AP5XJ2ic1LFxBM5LZrrgAvJ+Ohaa9Y2G/P4M6/9QWwOfvQfq9ShbWOhJg
3bJ7ATq63zvtwSw8Hyl1PVV3AR4oSxUVl7FwQXdxhJfeAjztedEsUMLCnsoW
OYeNFqBg3XCTEoOFVb0nWevNFmAzs6FVsoCF34hs5alwWACtdbe9LmezsItN
1aZw5wWInRg2byHytCXDTtfRfQFeC4kzSS9ZOEk38gav3wJIrOKv7CTyGHOJ
c8QkZgGChY4oWTxkYfPiBN5NLxbgbPS5LXCPuE88e2Rn0hagSrW7YvkOoWeC
u21M3gLcTjC3G/Ri4UDWt6afHxZAbsVGLd6OhQ+I3xiltS2A5zctwTUnWfif
I5Uv8NsCDG3kz3A8zsI+ywb7FYYXoCyhKOv6ARb22EbP9+BehDcyi3z35Ij7
6GXafIC8COaaJaPxkiw8yhwbW01dhJLrt4oCVhP3yUpWvlh6EUxW971qIbGw
3f3wWE7tRWh/dE/ybHcjNux3+y/iyiIk3HOIvvWkEev/J5t1yJtY3/jZdu19
Yh6u6eqcv7UI/XRLnnt+jXivnvEem9BFoBjORY+fb8SK6aozshmL4H3uz59f
Wo2YfG7WpbBrEXQv5Nn4dzRgvj9ZMc69i1DR/CHjDasBc0edq10/sginhsnH
sysa8O/qL7K3Foh6DytZHUhrwGNyxT/0qUtgUo6rcy414Pd9/5l3HF6CIpH/
zpct1eN6P82AEJMl6KcadzwfqcfVq9k0HYslGHCL3W/7rR6XHXIQSXZcAvKn
lHSPsnqclXag0fW/JWhs+HH+t189DnNahVbyliDoUWB1zUIdNukLV5KSWoZ3
tCEBi8+1+L1SX5ut3DLYllzo8npXi49e3X3rmeIy/OV4wP0frRYbcP1oXrd7
GerOnx7XDavFB2SUrosdX4YqFkMz6mAt1rCtYfL5L8OLjCz/rMwaLNm2ZDHT
vwy4v+3NY7dqPPLO8U599gqYPDvl8CyzEks/6XB7VLAC+8oq0oIjKrG5vYmF
eekKDHC4bDh3sxJXLGopdtevQKbTb9c+/UocsZ3SttC7Ao3ZZ9YK/GJi7Ri8
davEb3B2I5GlqEwc6ib5Mejebyj8EJQR01KGVShfNh48/Qd2xN93yh4oxAIw
d6Zr5i8kZZkf27UrGR8eP7Ww2YIDXdXM2ZbSGAkvVge03rbiQNvjku23xkTB
rHZmTpcNB8pdLv2542w0JIWsOEc7ciCXjbf1O5ZiYHlrQge/Bwfqlql23bfp
GWQ5fi+eDOFA2akrYeWZSSDacdqvgsmBVBkabMXsl3D+332rDdUc6IXIpd5a
gQwok8/d5V3Hgf7OTSutcckAVy+OcfUmDkSJpjfWbnoFVdRku/RvHGjvklCn
x5PXcM24Rzd0ngNJVs4Y3TiTBR1VTpynlDkRbhofjezOhcn9nRL/qXIi+S0F
m4+tosGqymO7knZwIuO83ed+baeBJt7rPLCHE9m9NnIJ86FBZKnoB089TsT4
+n7qLyUPjhWUxT6050SjkhamW7TyoTZ9tVp5OCf6fDeu+oZzIfyQCznS/ZQT
jccvvxx6UAhzqf8cSTGc6IRTw7Tym0KQSxmJOvKcExll7dFTHSsE/xfMlc+v
OdHeMDEbcXc66MZcrJuo4kTztBqXU64MKHxQbS8zx4kerxZb16dTDK8MWevu
L3Kibbs+xXSeKoZ4wU+fxlc40ZmvXx7FehfDnfCf+qVcXOjHEs8lt/xiMIpd
VrEU5ULM8qF6R/kS6MlQ+/dQiQvFed4+8oizFD677i6eVuFCjxVfHGFvKIV6
Jd2r1ju40LH9GuvXapZCds7RQXktLlQdxsUqcC0Fb8b5j5X6XCg59oDQrqZS
EK5LSFw4Q/zP+sWpEFoGnMGp1vbnuNAa8wfCXSllMGv4RqzGhQvZtPm8MS8u
g69NjPsRl7mQStVZk6f9ZZD25dPl7f9xIfec+seHtMth7wAfOhvLhdp3yMe6
fSuH7a9ElhuecaH3XDYMh4lykHFbW6CWyIXYF1TCJDgrgGdCVuFvOheSOPN8
19ctFdA8pysal8+FZH7f97h7sQLO83h1NzVxoZEnIl3XJypAQrqhfaWFC/UL
/E1P+10BTXs2flT4zIW2PZC5/VwAg+bFmnL/b1yopZXbbHILBt7WNc80h7jQ
bZE9uhKnMJSMuUacHeVCfkkxOknnMbjzVgSHT3AhVgXH3ilPDF+0znuPzHIh
WbWHqrMhGNKT6BYvOEmoSeIaz60iDFYlAsYsbhIKk19ZsnmHQbDN/tDiKhI6
S78zyd2E4dqqVTtPCJPQTFD6CKMHwyH3k6K8G0gobqhDsYWbCYv3M1ftlCKh
2a97jS/yMyEr+d/f05tISM7y8cqYEBNWf84YL95KQqOzZtyJa5nQp73YeGkX
CRnLWfDVyjMh1sKoKn43CXHPGrPCFJlgdDmpuG4vCZkGPFTRVmFCQYrBq037
SWgDmdmjr8EEl7KERJNDJLS8/GBv+h4mSH6ZjPY9TEI6PnvRsDYTAvnjgj4b
k5DQgXCnzQeYsEd23I/LlIRWf1d+KK7HhDGd/ddUzUlIMDTl8vRhJph7DDsG
nyKh1p0JAdbGTOAL2XeKbkdCGm06Zf3HmFCW+sS014GE+grZ1SdPMEGuXQvt
cyYhNTGLU+OWTOiYDNvt5kacd1l/StSaCaECPSoxlwg9X9ddlLBhApLTlK/2
IKEkqxOf+O2YMLsvZOPUVaIeTuK92p4Jr07+WC11g4RcuKU84x2YYHtlh+BR
HxK6/oinSNuRCdVpnctpd0jI043bRO0cE7wrVKZbAkhIxSH2TcB5Jih3+A//
vUdCJ/96bih3ZkL31JdupRAS0jyqlNHlwoRIslKHVRgJ4XRf8x5XJhhsuf0x
KJyEePL2Kza5MeG3bmtt3lMSeqh3SzXpAhNyrbZW/IwmoXNmFhesLjLhrKdv
oWA80W+HUP88wZo7fhRue05CY/ZrDG5eYoLANKLrJ5FQlGLWQg/B32mp9LOp
JFSkLbKy053Y7wov485LQo/0Z9YXCQ5Qd2U8f01Cm3ybJEIJtpxiMUqySMiw
7JD+U4K30VSK2nNIKOBAae9dgn97PCmazSOh+GzhlZMEf1SbLaLQSWj/ce3I
NQSnTFoWqxST0FVJO0YJcf713OLio2UkxHycc/EwwUc8JEtcMAm5JoaVlRL1
S6rdLgmqIiHbtCs54gRPsn+VpNSQEPXwnLEN0f+7nEOluJ6E0IWWpHuEPtGX
M0q7WCR0YcOP3DhCP1dVgbKlJhKyuka9H0noq8O+WLb2EwlZhAcq3yD0F835
WLbzM7G/p+ub/YQ/ve47yo93kNCWqdUCs05MoKtElV/6RkIryUvmj84yIWRi
oTzkBwndfvcqUpTwW829vKK6j4TsNh1a/4HIB0lFBv8aJKG7LqNXVhH5+TLu
j/+OEPkQaB3YRuTL75IBc88UkedseZOtJ5lwbHsm02KW6CcJLLgsmLB5XKjS
c4HIy8vp5Boivw0XWyuz/pDQHa1GTR4TJiQoa1Y1cHAj/46QyLtHmeAxFls1
QOJGKXc2nh0wYMLai/bvZAS4EYrQvO16kAmOF4arI9dyIw+K2JTlbiZoKBnV
0NZzo+CRy9R1u4j7M/q2pkmSG/UER3BUqTEhx+1aLZ8sN7q7cORq8zbCT9d/
dX6q3Mim9DX/VwnCz22O9XE7uFFEdsTgL2I+pAxX19M1uNHQBpe5Virhn2tI
w6Q2N1q0CWy7KkD44bKG5WTAjUpuxskYTGFQdVZqMjpDrBe8mp2WjOGHq/Tl
bCdudDsPGv5EYQi9KCYq7MKNbliZaskS82/4yorpR3duNIHyM1uvYEj1Y302
9eNGC/2n/jXpYhCPuPDdMoYbMQ+S/Uw/VkBt5OlbjHhuZKrJmLnLrIBrMWbS
615wI41bNI27tApoSdA+8zWNG83fjsRjERXwMIPcb5PHjfp//ArxM6uAf2WZ
Yw4fuFFcGKU9jVUOb3FiWGUzN3LHQSJfisvBtuqpyuY2blTjqfG+I6Mciut8
PXo7udGe9UHBZgHlcPXT0dlzQ9xoxpcqJ7unHAYHR1fcSDwo1rpDxjyuDD5S
lcleWjxIoXmHm5l2KeheujT8TIcHHT/9HpK3lMLburd1VcCDWg9Uz7JESuGR
n3qgqD4P6jlw+1VRbwkYDWj+yTzBg9zTNaZmgkugsXg/u+cCD3ppr2m6rrkY
ahxOth5/wYNuG/W/Nz1UBKVv/Z8pk3hRhuiF+6VfCoDXyEIihpcX7R/jvbmb
UQCmw1vjOAV4UYWfwURMTAEMyn6I/iLKi2J6T5xdZVUAYnHiEXekeJHqyBWf
jPZ8uBCQ9aBNixdtdxmplfuUBxusvnj5efCiF9me774V5oIvp+Lx9995UUco
h4NT2CsQ6PIxcC9YhcKscg0OegZD/8tNkYl+fMh4/ovsD23Cg8BfS6Q7fEil
ooxXvToSTzsmn3YJ4ENqgjdOaRlFYQ7pTUrqIXyo8orXwnmbaCwRI1NVFcOH
9lYOpktdj8XH70tP9ufxIf2b0nsPJyTgMueNRsrDfIipohQyeSIFv9P7Tgsf
40PillWFGU9ScKPsc/E5Nh9StQ3vUW5Owe0/JXvL5/nQ7KhtdaJRKp4+Kelz
jJsfjSv0OWw8mIYVDDa88pTmR3xeHupb5V/iSIX13MUW/Ii8cjSct+o1trWX
z+i14ke/xs7HS8y/xnKROw2FbflRUeGBgKVtb3DBP+Pws478yFL3xtjaJ29w
2xd/SeHL/Oim2BHRBttMLBY0tuvsA34U8nH5WutwFo74hc8JlRLnjzy9/a0j
B58S/8C3p4If/Vn+sXGEKxdvNu7MdKzkR1t3XNAwWJ+L84pmpxh1/Cg1w2Tr
a71c/OnxtluObfyo9oOJ7kpCLqboPo1mjPOjh8Ytso16NBwef77ujIwAklU0
6714Ow/fuO5/1U9WAJknbJOIfJKH7U+8kI6RF0BZ/DqXnqXmYWWBLzfeKwsg
TqObGw3r8nDDTT2F3VoCqNtmVcYWoXzMZS0XLHhCAGHf93y1Efl4eBfS2Goh
gOgscvZASj5uFrX9td9KAK1W/GE9kJePE+ufat2wF0CW01qP/T/lY509pJFf
bgLIrq6rUlm0AHuJ9xgyAgRQtN0lunZQAbad+TPfck8AlSyQ+PWfFuBDH9en
jgULoFhlnQCV5AJMvW+6silcAO15eKI8rqwAv51nZoYmCKCNsbHL7VMFeOhz
oqBjoQC6GafwZdiiEH+klRb5FRH1Sn883HKmENPD2p1iSgXQ4lqnndGXCnGg
nkj5+0oB1JQ8Z1YUWIg3Fd66tLtJADFuHKizpRXiU5F2TYKDAki1cTpAmpuO
JfMFNlwYEUC3o7mks4Xp+GcLw7lhXAAdTIQAyno6dhKhct6bFUAfZuyD7bfT
sXtI7c5/nGQkp5DQyGdOx2qvr96x4yGj348fjh61o+OZOpkPpXxk9MdwU/K5
83TszeN73luEjNI79QolvenY/45q3JQkGVmOKf+NjaPjQ4ld/cdkyCi3fw2E
J9PxqorgHW9lyei91/CU3Ws6Dl3pZbkpkpHrX81kvyI6jr4e+7d3NxnFZGr+
qm2jY6sovaMHtMnIvNzE7co3Ot5QMB2TpEtGsu3G5tO/6DhpykjdTo+M/tHK
Dt+YoOPXFzmdvpwgo2bxnrQwHga++PBt7i5LMrJ52aA0KsDAKm9s/kRYkxGl
ecdqaVEGzhssjD7mQEY9FmQRAQkGvsZ7tjf7LBlpC4zIVUox8O4tomqCzmS0
rk8h1USWgcsc3RrqL5FR1dO0njElBr51V3zt1itktIN66/UfVQben1TtGHSN
jL58n+zt28nAtd+lfu/3JaNizvZKTW0GfvCbZZB0i4z8iymXknUZ+OiGm1F/
75LR0+PXnvXsZ+Bmq1aV0gdklGO3O3LoMANH3Ljjuz6UjB5I3HfJNmRgi+jt
9Tcek9G02PdWA2MGXlfYufpLBBlJvuz6VnKMgTtb75/ZFU1GwbmX7pFOMHDC
9K63EXFk9J9f2dfN5gx8mtKzPJlARsMpWl3rLBl4s9rjw8eSyIhzOi6y/yQD
95noRGankpHZiS/8wdYM/PLScDc5g4yeZCodJNkwsGto9Ha3N0R/9RIG5rYM
rJx50Kc+m4yidVxk/OwYeKJhslaeRkYShyTbfOwZOHfouVhQARnFv/G/cPw0
A19dddShl0FG7ExF9m+CNeUXs/aXklHnlwHnOw4MvHgofSmxgvBj4v2PToL9
ShMDqivJ6M56IXOBMwzMsSNeaLiajO6ysuTXEhz4KjJGqJ6MRCre2P8l1q+S
frxpB4uMyPv2cL8jOCQqONOyiYzOiRZLOxEsLBio4dtC+HXuXfEv4vwI/1s4
sY2MrtOlv2kTvHbJ+0h1OxkVFNaHehL1x1++2jrUSUaaO0fbg4j+Ng5cshP6
QfTHO1DjRfSfZOsyqP6LjKizRxwOEPrItTpesewjo6HYr7mjhH6vjtit+AyS
UbVxcOUVK0Iv5smgxBEy2ip6O6GN0H9ntlHc0CQZhZi+71QzY2C67GFZoVky
Yko6mymaMvDe+P3Z6gtkJHOqiclB+Hvgvmalzx8yqud8+fIQkYfaP2pHEzkE
EUdrj0YekZcj15Q+vyMJomtvAwd/H2Lg42dkhgUFBNHhhVe/tgEDt7VLXFUX
EkQ+wf8dENRhYCuTNX8sRAXRu90286w9RD60BSiJawURv9hIcK86A7uvmd2j
LiuILNV7PlzbzMDTDyeqLOQF0Vo9rZ0HifvhxTVs5LNNEGn+GrRgryf8Yn93
eKdKrH+xQv5F3K+HDXUPLHQE0Z60DZ+U/tCxMKqi+oAgMuPlLBpeoOMIelnC
iwOCiOZ0tiVomo7jU2m5gwaCyAgpfLcapONX/z3ruGkhiNwFQ9Zd/EjHyrNR
ji+sBNEJg2GrjQ10nOsWPlZlI4hCLwSYZFfRMeNkEIegoyB66/bmuWshHdeq
X1Z44S6IrnK651sQ86i3/4B31X1BRLFMDCXb0PGBxKYUxYeCSKRnx54VU2Ke
WJ36EPFIEAntvCdVY0DH9qwrm89GCSLRpnCOIQ067sxNek9KJfr9u3n0IjFP
P/n+ldGrEEQ9wzLJIUWFWF0j5Gh2pSCy2LHNSDG7EIdPrLm+pkYQWZv2dacn
F2KTM9tZ/SxBFL6wtFc9pBA36tt63ftK6M93eeCZdSGuopQ01M0KosHtk1e/
Ec+HTSy9WdVFQSQYa1p4uK8A3wlskYpdEUSlfxTqnnwpwLoLQ1dduITQ60Wl
77ikAJd0iUvxiwqheX1bp/t3C3BehpenoZIQsr/QKvaLrwCn7FPf8OGMEIob
6EvI+5eHq0wEAlachNArH04tfXYe7jndO7LNRQjtPtfagX/kYVn/qJJ77kII
/61JPFeeh9Nql6yRrxDa8kGXcetmHk4/VhWbHymEmodXt3ON0/CrM2Zr4+uE
0Ok6XefdVbk4O8iL4rxdGFnvFK9Nts7CYzp2/kFqwsg4ID66QCWL8PPQTOpO
YWQuYsD1kpSF3ziu/tytJYw0r7vXbMnOxK8gP/aUvjByXn2iJOnvG5y2NClt
cloYLQiuflf17DWOv3RRReOJMFr9xfBOLvMlvm9x9ihpThitssxzO1qThDW6
kl/f/yCCaBoi54vtbuLYbc+yPxwVRUUJ9ns9PSJgdkY/PcBYFJ3gif/K1R4B
xyqmE7SOiaKZ0COzNvueAq+ZYWj6CVH0Mc14yok/Erz8ltz+sxZFril3/PCL
KDjx8aTCdmdRxDG7ayd3RSwIeq1ODfUXRfOBlCLzxhfgAsz4A4GiSHZ7WFiB
QiK8478YsRgkitibPBLq7yWCz4t3d52CRVFNtEMAz6YkGK7zdNAJF0UWDxUM
r3UmQa1Ey8ax56Lo0dfLPlV6KXCbGRZ7tFgUCYnNfVb+nQYj35mRSyWiyJHs
d/n4lnSwXJkJzygTRWrHgv7qm6SDsuapYBJTFN3M6FuVlZgOHZnyPqW1oujJ
pmb5Y+gl7IjBNkptokjKmkSv8c6AgUtTUmS2KDprUkQdqn4Npg/lNhRPiiIZ
8cPmy4OvoezVSXHnaVE0OX79SYfAG3jaWy7ybk4UBXnc2LN47A0g6xAO399E
fbLVPRXtbyD+kGzPCD8FLcUZ70PfM8F4g0V6oxwFzfnbO3ZVZENsnwrTRp6C
ysVfLKt/zYa+bL5vY1spyN/teqTFTDb4oTJRESUKCjyha8G79S1knZP1M1On
oBt3C78IhL4FgdypE137KOguv67OfaMcsLzJunQJKOiCwvPQnLM5kHIg/cFf
REFxg2vk0nxyQOuzVYXMIQr6bFFaPZWRAy7LeNs5Qwpyz2FQhTlyoe7QI44J
Swr6NHwh3sgsF6jCLhtuW1FQjGPjzX12uWDfvl9T9BQFcef+qxNzzoV517kL
O+wo6FKFTbCHTy7IP7Ztv36W6De8/elwYi4EflV8++8yBQkb7We39OdCcwp3
Q/gVCir5ss99zUQuSF780bvpKgWhGZ/mffO5kP/3yfpD1yno1i2fTft4adAj
uxT4wI+CKjX+qM/J0WC/e50NJZiCtCS6vPXsaLDcMaxfHUJBtu3OFg5ONCg4
KLjjRigFZUV/+n7qAg3k15vyfX9MQQI8pzsnvGkgWN1Z8CqagnR2Px98EkGD
WpU/iTaxFHRsqf3e61ga3I6TfigcT0F7/X5nJL2gwbS705lrzylIVdXo9PY3
NOhYPyGE0ihonBKrxcQ0iAgUXZpOpyCbozK3WqtpcJS9oy89g4LKMpYUahto
UFF9o4ScSUGPVNa8OtJKA2/V+PSKLAqq3rPJu7OdBurxZeFX3lLQWXHqS8Mu
GqRd5nRup1GQ/uXMNQ19NLDvlD0Rkk/4YTVo3j5EA3E9/X37CinoyIDKePUY
DUIkHoqlFlFQQIWvvO4sDTxqVjPdMQWtnMeMV5x5oKi2O3NTJQWdzvEtpnHn
QW+8dXRbFQVNZu1fE78qDyw9XlzcW0tBBteTf/IJ5YHoN+bJ8ToKitCVM30s
Qrz06/UeSGqgILFn/pvnKHmgs0FhPe8HCtqlSB23X5sH80GG3MVNFPTy/uSI
47o8yJm8yL7QTEE8edwn9CXywMXmcafUJwpat2HHFn7JPNhcS6tpaaUg3yuR
zpkb86BLrS038DMF/Qi/LbldOg+ins0/291OQSNXbh9+JJMHJrzr7490UFDL
equxpk15wHdF2/N5JwV5BvOIsDfnQdU3O7vjXRQkn1WaPyGbB776dwxIPyho
j/7Ajw9yebCLlrKT/pOCFnoUokK35MHEhhop118UdK3K/puifB68ujfIL9lL
QZ218fRXBJ+Z4p9r6iPu15mtyrxb80DCVrn77gDh7+17+w8S3FZrwto1REG5
Xld+nyb4kfoV+uAwBT0b73C0JfhwwtPk+FEK6v7Y57OHYI5V9FDjcQqiqM0a
zhL7l1zpuMHBpiDv3c+/Pib4ateyY/4kBUWJZG8nE6x8eKPJ+WkKOv5+q8l5
ot4BGmitn6WgOguDA8lEP4mSjnLv5yio3vQOpYzod+9OJRXHBQr6wFSSbCD0
aDsyu3txkYJKUyJVSwi93B3K9z9apiDHC4YnHhN68t24d1TuNwVN/+R5aEDo
nRJ2zKLkDwV95Hnd3U/4oZO27vTxfxSkTIFTzoRfHi1vPP24qGj1Nt0va9fn
gcDQVT8qNxWpDIUMHhLPg7S/Ovde8VCRz4cne0+uyYMOpY9xbXxUNC16skaB
yIvngdhUNwEqMn0HQkPCeSBofSabQ5CKhKR2Mx4K5gG6N8NUFqEiyTYnsztE
HjsTyhqrRKlIpIr/ZAuR12v5QW1WVCp6aRH/k5eL8KtbfChwDRW9eLA2Tfo3
DQ4sdE9JiFPR4Zt501xLNOgSerOSu46Kzj2IH22cowFFW0fk+wYqYvA7k/jZ
NMgy5Vl/dSMVNbL3at4epYG+S9NmfmkqisjV0u4cpIFPlIOmxmYq2mZl2K/b
TcwfdqBdmAIVTXqf7H/3kQZ+vCbOsopUlDlCbjvDosHajeJXipWoyMpfaKyv
lgaGhq8D+1UIPbrca+PLaZCX9iFznwYVLVvZeda+poFRaXRhqyYVPYrYuPgo
jQYDLaex6x4qOgFcfPsSaSDxb+pTlDYVmVf5Lh2JpEGA9drl8f1U1Kp4NELh
PxpIefwkBR6kIpen0C51gwZF914JSehR0YBhvuiKBw3G8vdu0jegotl2obhz
xDw0Fz5t8MKEipLnbR9zG9JA7l1GtIkNFRnEyPLfEKVBk/JiWpctFYWdeC+z
zEfMp2iDfDd7KrrZeFj8HCcNWK7DH++doSJe9fnv01O54CmqxI+dqWhnKd89
dksuYLu3vqrXCL/vmx7xDcsFl7q/weVeVHRKxaIiIJB4fqgfiz16g4ruNeav
8fLNhfPckwXOPlQUcDAvl+qaC4KZ6hOJd6ioyqzCX/tgLpxaLHAQDaOi78ya
9JcDOcDtyHP5xSMq2hzgEd7XkgNvWRb/KYcT502VBc6X5QBn4nycwVMq+rYt
TDYmIgde6e1pvRNHRd3T32981M6BuYhSval0KjIbLJWFe28hfHuV4qcKKgrd
0r5a+3cWvNpjw+/PJPRaPBRM7c4CfHB2UL2KihqWJs6UvcuCCWv59Cc1VLRu
fKP8g5AsOHovRNr0PRXRFIrMeNdmAe/PE6ubv1JRhrbBaLNcJviG9/75MEtF
zo8e6R2RfQ3nZ7hbGhTF0PXA1ubPtDSwf3OoyVZZDP38V09lPEoDyzOBLPZ2
McTKKHt760Ia6H8k1a5RF0NKm2c6K+XSQD6Tq/TMbjEkqiR/Uio6FfodOdKX
DoohvZCw947XUsDp04r3NjsxNOsRj+gySeBIm5YJfiyGmnXOe5x+GA0X/c1+
Gz4RQ8P+Eo+Kd0SDl1lBu+BTMbSrqcF06WsUPJjzehQeLYY+ZVn6KStEwVut
pZWY52LIb9pu77V3T2Gp8t+Xl5liqG30zlmZ+XAI/yQYVl0nhk7+Pa56JPke
xKdecrnXIIYCftS/J40FQeq1poMGLDHUbpX9rUAzCOhrw5dZTWLoqUdn9j9W
AHSdEnNp/SyGuOy3l9jN34GtvesP9vSKoeS1BT+boq+DWoGPVFq/GPJtOT5l
puwFe4O+LZ0bJPrXJOdPVl4Fo63Pc4dHxNDVu5yDvuMe4HlBRmpqSgxNGVjG
6oeeBz+du0t5M2LIu/W+jkPxWQgS6mm7NieGKqmHn7cOOEBsTurDxUUx9Ffh
qFFxkCWk3OF2LlkWQ+H3JV4u9RyHTNNzB/x+i6EjVK51qv76ULC5dqPuX0KP
MpVhrzuaUDEjv/TvnxhSjXvSyRy20P0ftaGffQ==
     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{{0, 5}, {-0.9999999976346008, 0.9999999999999828}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.530249595312283*^9, 3.530249638787245*^9}, {
  3.530338885546767*^9, 3.530338903877131*^9}}]
}, Open  ]],

Cell[TextData[{
 "Der Befehl ",
 StyleBox["Show", "Input"],
 " dient allgemein dazu, graphischen Output zu kombinieren:"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5302497320921783`*^9, 3.530249776648695*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{"alternativ", ",", " ", 
    RowBox[{
    "f\[UDoubleDot]r", " ", "komplexere", " ", "Plots", " ", "zu", " ", 
     "empfehlen"}]}], " ", "*)"}], "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{
    RowBox[{"plot1", "=", 
     RowBox[{"Plot", "[", 
      RowBox[{
       RowBox[{"Sin", "[", 
        RowBox[{"Pi", "*", "x"}], "]"}], ",", 
       RowBox[{"{", 
        RowBox[{"x", ",", "0", ",", "5"}], "}"}]}], "]"}]}], ";"}], 
   "\[IndentingNewLine]", 
   RowBox[{
    RowBox[{"plot2", "=", 
     RowBox[{"Plot", "[", 
      RowBox[{
       RowBox[{"Sin", "[", 
        RowBox[{"2", "*", "Pi", "*", "x"}], "]"}], ",", 
       RowBox[{"{", 
        RowBox[{"x", ",", "0", ",", "5"}], "}"}]}], "]"}]}], ";"}], 
   "\[IndentingNewLine]", 
   RowBox[{"Show", "[", 
    RowBox[{"plot1", ",", "plot2"}], "]"}]}]}]], "Input",
 CellChangeTimes->{{3.530249784366866*^9, 3.530250007208297*^9}, {
   3.530250169485619*^9, 3.53025018637752*^9}, 3.530335041110312*^9}],

Cell[BoxData[
 GraphicsBox[{{{}, {}, 
    {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwVm3k8VO8XxzEIM5YZpZKtSIWIUH1T50lRSipFthItiOztlEIhRVosbbKU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      "]]}}, {{}, {}, 
    {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwU2nc81P8fAHBnO44zSkNkhCSkLXm9G1RWpZRKilRkhFRCg+bXKCGU2RCl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      "]]}}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{{0, 5}, {-0.9999995444593152, 0.9999994330066376}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.53024998158175*^9, 3.530250007718597*^9}, 
   3.530250172489862*^9, 3.530338921762741*^9}]
}, Open  ]],

Cell["\<\
Plot hat eine F\[UDoubleDot]lle an Optionen um die graphische Darstellung \
nahezu beliebig anzupassen:\
\>", "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530250686945703*^9, 3.530250744597929*^9}, 
   3.530335042226307*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"TableForm", "[", 
  RowBox[{"Options", "[", "Plot", "]"}], "]"}]], "Input",
 CellChangeTimes->{{3.530250746239161*^9, 3.530250749905097*^9}, {
  3.530251801979847*^9, 3.530251808180284*^9}}],

Cell[BoxData[
 TagBox[
  TagBox[GridBox[{
     {
      RowBox[{"AlignmentPoint", "\[Rule]", "Center"}]},
     {
      RowBox[{"AspectRatio", "\[Rule]", 
       FractionBox["1", "GoldenRatio"]}]},
     {
      RowBox[{"Axes", "\[Rule]", "True"}]},
     {
      RowBox[{"AxesLabel", "\[Rule]", "None"}]},
     {
      RowBox[{"AxesOrigin", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"AxesStyle", "\[Rule]", 
       RowBox[{"{", "}"}]}]},
     {
      RowBox[{"Background", "\[Rule]", "None"}]},
     {
      RowBox[{"BaselinePosition", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"BaseStyle", "\[Rule]", 
       RowBox[{"{", "}"}]}]},
     {
      RowBox[{"ClippingStyle", "\[Rule]", "None"}]},
     {
      RowBox[{"ColorFunction", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"ColorFunctionScaling", "\[Rule]", "True"}]},
     {
      RowBox[{"ColorOutput", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"ContentSelectable", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"CoordinatesToolOptions", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"DisplayFunction", "\[RuleDelayed]", "$DisplayFunction"}]},
     {
      RowBox[{"Epilog", "\[Rule]", 
       RowBox[{"{", "}"}]}]},
     {
      RowBox[{"Evaluated", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"EvaluationMonitor", "\[Rule]", "None"}]},
     {
      RowBox[{"Exclusions", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"ExclusionsStyle", "\[Rule]", "None"}]},
     {
      RowBox[{"Filling", "\[Rule]", "None"}]},
     {
      RowBox[{"FillingStyle", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"FormatType", "\[RuleDelayed]", "TraditionalForm"}]},
     {
      RowBox[{"Frame", "\[Rule]", "False"}]},
     {
      RowBox[{"FrameLabel", "\[Rule]", "None"}]},
     {
      RowBox[{"FrameStyle", "\[Rule]", 
       RowBox[{"{", "}"}]}]},
     {
      RowBox[{"FrameTicks", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"FrameTicksStyle", "\[Rule]", 
       RowBox[{"{", "}"}]}]},
     {
      RowBox[{"GridLines", "\[Rule]", "None"}]},
     {
      RowBox[{"GridLinesStyle", "\[Rule]", 
       RowBox[{"{", "}"}]}]},
     {
      RowBox[{"ImageMargins", "\[Rule]", "0.`"}]},
     {
      RowBox[{"ImagePadding", "\[Rule]", "All"}]},
     {
      RowBox[{"ImageSize", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"ImageSizeRaw", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"LabelStyle", "\[Rule]", 
       RowBox[{"{", "}"}]}]},
     {
      RowBox[{"MaxRecursion", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"Mesh", "\[Rule]", "None"}]},
     {
      RowBox[{"MeshFunctions", "\[Rule]", 
       RowBox[{"{", 
        RowBox[{"#1", "&"}], "}"}]}]},
     {
      RowBox[{"MeshShading", "\[Rule]", "None"}]},
     {
      RowBox[{"MeshStyle", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"Method", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"PerformanceGoal", "\[RuleDelayed]", "$PerformanceGoal"}]},
     {
      RowBox[{"PlotLabel", "\[Rule]", "None"}]},
     {
      RowBox[{"PlotPoints", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"PlotRange", "\[Rule]", 
       RowBox[{"{", 
        RowBox[{"Full", ",", "Automatic"}], "}"}]}]},
     {
      RowBox[{"PlotRangeClipping", "\[Rule]", "True"}]},
     {
      RowBox[{"PlotRangePadding", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"PlotRegion", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"PlotStyle", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"PreserveImageOptions", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"Prolog", "\[Rule]", 
       RowBox[{"{", "}"}]}]},
     {
      RowBox[{"RegionFunction", "\[Rule]", 
       RowBox[{"(", 
        RowBox[{"True", "&"}], ")"}]}]},
     {
      RowBox[{"RotateLabel", "\[Rule]", "True"}]},
     {
      RowBox[{"Ticks", "\[Rule]", "Automatic"}]},
     {
      RowBox[{"TicksStyle", "\[Rule]", 
       RowBox[{"{", "}"}]}]},
     {
      RowBox[{"WorkingPrecision", "\[Rule]", "MachinePrecision"}]}
    },
    GridBoxAlignment->{
     "Columns" -> {{Left}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}}, 
      "RowsIndexed" -> {}},
    GridBoxSpacings->{"Columns" -> {
        Offset[0.27999999999999997`], {
         Offset[0.5599999999999999]}, 
        Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> {
        Offset[0.2], {
         Offset[0.4]}, 
        Offset[0.2]}, "RowsIndexed" -> {}}],
   Column],
  Function[BoxForm`e$, 
   TableForm[BoxForm`e$]]]], "Output",
 CellChangeTimes->{3.530250751044368*^9, 3.530251808785676*^9, 
  3.530338931261972*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[TextData[{
 StyleBox["Die wichtigsten",
  FontWeight->"Bold"],
 " (als Optionen mittels \[OpenCurlyDoubleQuote]",
 StyleBox["->", "Input"],
 "\[CloseCurlyDoubleQuote] zugewiesen)",
 StyleBox[":",
  FontWeight->"Bold"]
}], "ItemParagraph",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530250776636777*^9, 3.5302508262681093`*^9}, {
   3.530251514520524*^9, 3.530251543592106*^9}, 3.5303358694341583`*^9}],

Cell[TextData[{
 StyleBox["AspectRatio", "Input"],
 ": Seitenverh\[ADoubleDot]ltnis H",
 "\[ODoubleDot]",
 "he/Breite,"
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{
  3.5302508041635017`*^9, 3.53025084717863*^9, {3.530250916803537*^9, 
   3.53025092267941*^9}, {3.530251069659691*^9, 3.53025106966402*^9}, {
   3.530251560214748*^9, 3.5302515761662693`*^9}, {3.5302516385676317`*^9, 
   3.530251672451968*^9}, 3.5303349334937067`*^9, 3.530335000142913*^9}],

Cell[TextData[{
 StyleBox["Axes", "Input"],
 ": ob Axen gezeichnet werden sollen (",
 StyleBox["True", "Input"],
 "/",
 StyleBox["False", "Input"],
 "),"
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530251070316552*^9, 3.530251070988331*^9}, {
  3.530251125485468*^9, 3.530251135290515*^9}, {3.530251171114195*^9, 
  3.53025118744925*^9}, {3.530251335309267*^9, 3.5302513832518*^9}, {
  3.530338977057386*^9, 3.530338981916699*^9}}],

Cell[TextData[{
 StyleBox["AxesLabel", "Input"],
 ": Beschriftung der Axen (",
 StyleBox["{\[OpenCurlyDoubleQuote]<x-Achse>\[CloseCurlyDoubleQuote],\
\[CloseCurlyDoubleQuote]<y-Achse>\[CloseCurlyDoubleQuote]}", "Input"],
 "),"
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530250923928688*^9, 3.5302509752455072`*^9}, {
  3.530251252175308*^9, 3.530251300398589*^9}, {3.5302513366534443`*^9, 
  3.53025133752514*^9}, {3.530251386652355*^9, 3.530251389747561*^9}}],

Cell[TextData[{
 StyleBox["Frame", "Input"],
 ": ob der Plot eingerahmt werden soll (",
 StyleBox["True", "Input"],
 "/",
 StyleBox["False", "Input"],
 "),"
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530250976143285*^9, 3.530250978318771*^9}, {
  3.530251142266595*^9, 3.530251146354001*^9}, {3.530251190321594*^9, 
  3.530251203528582*^9}, {3.5302513589729347`*^9, 3.530251359043281*^9}, {
  3.5302513913796663`*^9, 3.530251393571926*^9}, {3.5303389896712418`*^9, 
  3.530338995738954*^9}}],

Cell[TextData[{
 StyleBox["FrameLabel", "Input"],
 ": Beschriftung der Seiten des Rahmens (",
 StyleBox["{\[OpenCurlyDoubleQuote]<unten>\[CloseCurlyDoubleQuote],\
\[CloseCurlyDoubleQuote]<links>\[CloseCurlyDoubleQuote],\
\[CloseCurlyDoubleQuote]<oben>\[CloseCurlyDoubleQuote],\
\[CloseCurlyDoubleQuote]<rechts>\[CloseCurlyDoubleQuote]}", "Input"],
 "),"
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530250957031662*^9, 3.530250959495466*^9}, {
  3.530251011958076*^9, 3.530251013010388*^9}, {3.5302511495851*^9, 
  3.5302511538021603`*^9}, {3.530251233128355*^9, 3.530251274261423*^9}, {
  3.5302513042707987`*^9, 3.530251312670171*^9}, {3.53025139631546*^9, 
  3.530251398491725*^9}, {3.530251479449605*^9, 3.530251498617297*^9}}],

Cell[TextData[{
 StyleBox["PlotRange", "Input"],
 ": dargestellter Bereich (",
 StyleBox["{{<x_Min>,<x_Max>},{<y_Min>,<y_Max>}}", "Input"],
 "),"
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530251013678133*^9, 3.53025101882015*^9}, {
  3.530251157217916*^9, 3.530251157449806*^9}, {3.530251346700897*^9, 
  3.5302513665161533`*^9}, {3.530251400611627*^9, 3.530251432138801*^9}}],

Cell[TextData[{
 StyleBox["PlotStyle", "Input"],
 "."
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.53025101944602*^9, 3.530251021929791*^9}, 
   3.530251553023365*^9}]
}, Open  ]],

Cell[TextData[{
 StyleBox["PlotStyle", "Input"],
 " gibt genau vor, mit welchen Eigenschaften Kurven gezeichnet werden sollen. \
Je nach benutzter Variante des Plot-Befehls ist ",
 StyleBox["PlotStyle", "Input"],
 " Liste oder verschachtelte Liste von Grafik-Direktiven."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530252239190734*^9, 3.530252243795483*^9}, {
  3.530252284423687*^9, 3.5302523789197206`*^9}, {3.530253797386237*^9, 
  3.530253921588479*^9}}],

Cell[CellGroupData[{

Cell[TextData[StyleBox["Einige dieser Direktiven:",
 FontWeight->"Bold"]], "ItemParagraph",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5302539278663807`*^9, 3.5302539466269093`*^9}}],

Cell[TextData[{
 StyleBox["Thick", "Input"],
 ", ",
 StyleBox["Thin", "Input"],
 ", ",
 StyleBox["Thickness", "Input"],
 StyleBox["[<Zahl>]", "Input"]
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5302539632961187`*^9, 3.5302539927850637`*^9}, {
  3.530255061896366*^9, 3.530255073339973*^9}, {3.530255256663837*^9, 
  3.5302552759820004`*^9}, {3.530255673390047*^9, 3.530255681331053*^9}, {
  3.53025597089928*^9, 3.53025598753086*^9}}],

Cell[TextData[{
 StyleBox["Dashed", "Input"],
 ", ",
 StyleBox["Dotted", "Input"],
 ", ",
 StyleBox["DotDashed", "Input"],
 ", ",
 StyleBox["Dashing[{<Segment_L", "Input"],
 StyleBox["\[ADoubleDot]", "Input"],
 StyleBox["ngen>}]", "Input"]
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530253994041704*^9, 3.530253996264184*^9}, 
   3.530255207469894*^9, {3.530255293424513*^9, 3.530255313595688*^9}, {
   3.5302556772578897`*^9, 3.530255678531086*^9}, {3.530256025364327*^9, 
   3.530256040385562*^9}, 3.530259354452227*^9, 3.53033493551822*^9}],

Cell[TextData[{
 StyleBox["Darker", "Input"],
 ", ",
 StyleBox["Lighter", "Input"],
 " (Bezug auf vorangegangene Direktiven), ",
 StyleBox["Hue[<Zahl>]", "Input"]
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530253996769713*^9, 3.530253997384334*^9}, {
   3.5302556844989433`*^9, 3.530255684626429*^9}, {3.530255716708893*^9, 
   3.530255723225698*^9}, {3.530255757378435*^9, 3.530255772126782*^9}, {
   3.530255991515213*^9, 3.53025599494674*^9}, 3.5303390734375963`*^9}],

Cell[TextData[{
 StyleBox["Red", "Input"],
 ", ",
 StyleBox["Green", "Input"],
 ", ",
 StyleBox["Blue", "Input"],
 ", ",
 StyleBox["Yellow", "Input"],
 ", ",
 StyleBox["Orange", "Input"],
 ", ",
 StyleBox["...", "Input"],
 ", ",
 StyleBox["RGBColor[<Rot_Anteil>,<Gr", "Input"],
 StyleBox["\[UDoubleDot]", "Input"],
 StyleBox["n>,<Blau>]", "Input"],
 " (Anteile als Zahl zwischen 0 und 1)"
}], "Item",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5302539980175467`*^9, 3.530253999641474*^9}, {
   3.5302557977144747`*^9, 3.530255866582383*^9}, {3.530255907567398*^9, 
   3.530255941420725*^9}, 3.530335055706427*^9}]
}, Open  ]],

Cell[TextData[{
 "Obiges Beispiel mit ",
 StyleBox["Plot", "Input"],
 "-Optionen:"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5302595174430513`*^9, 3.530259542353724*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{
   RowBox[{"plotStyle", "=", 
    RowBox[{"{", "\[IndentingNewLine]", 
     RowBox[{
      RowBox[{"{", 
       RowBox[{"Blue", ",", "Thick", ",", 
        RowBox[{"Dashing", "[", 
         RowBox[{"{", 
          RowBox[{"0.05", ",", "0.025", ",", "0.1", ",", "0.025"}], "}"}], 
         "]"}]}], "}"}], ",", "\[IndentingNewLine]", 
      RowBox[{"{", 
       RowBox[{
        RowBox[{"Hue", "[", "0.4", "]"}], ",", "Dashed"}], "}"}], ",", 
      "\[IndentingNewLine]", 
      RowBox[{"{", 
       RowBox[{
        RowBox[{"RGBColor", "[", 
         RowBox[{"0.75", ",", "0.25", ",", "0"}], "]"}], ",", 
        RowBox[{"Thickness", "[", "0.01", "]"}]}], "}"}]}], 
     "\[IndentingNewLine]", "}"}]}], ";"}], 
  "\[IndentingNewLine]"}], "\[IndentingNewLine]", 
 RowBox[{"Plot", "[", "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     RowBox[{"Sin", "[", 
      RowBox[{"Pi", "*", "x"}], "]"}], ",", 
     RowBox[{"Sin", "[", 
      RowBox[{"2", "*", "Pi", "*", "x"}], "]"}], ",", 
     RowBox[{
      RowBox[{"Sin", "[", 
       RowBox[{"Pi", "*", "x"}], "]"}], "/", 
      RowBox[{"(", 
       RowBox[{"Pi", "*", "x"}], ")"}]}]}], "}"}], ",", "\[IndentingNewLine]", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "5"}], "}"}], ",", 
   RowBox[{"AspectRatio", "\[Rule]", 
    RowBox[{"1", "/", "2"}]}], ",", "\[IndentingNewLine]", 
   RowBox[{"Axes", "\[Rule]", "False"}], ",", "\[IndentingNewLine]", 
   RowBox[{"Frame", "\[Rule]", "True"}], ",", 
   RowBox[{"FrameLabel", "\[Rule]", 
    RowBox[{"{", 
     RowBox[{"\"\<x\>\"", ",", "\"\<y\>\"", ",", "\"\<Beispiel-Plot\>\""}], 
     "}"}]}], ",", "\[IndentingNewLine]", 
   RowBox[{"PlotStyle", "\[Rule]", "plotStyle"}]}], "\[IndentingNewLine]", 
  "]"}]}], "Input",
 CellChangeTimes->{{3.530259556190557*^9, 3.5302596497962637`*^9}, {
  3.530259719474514*^9, 3.530259823337344*^9}, {3.5302646562889347`*^9, 
  3.5302646759699793`*^9}, {3.53026489647668*^9, 3.530265007855212*^9}, {
  3.530265064806149*^9, 3.5302651083247423`*^9}, {3.530265168673913*^9, 
  3.5302652339231377`*^9}, {3.530265296308819*^9, 3.530265310453388*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {RGBColor[0, 0, 1], Thickness[Large], Dashing[{0.05, 0.025, 0.1, 0.025}], 
    LineBox[CompressedData["
1:eJwVm3k8VO8XxzEIM5YZpZKtSIWIUH1T50lRSipFthItiOztlEIhRVosbbKU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     "]]}, 
   {Hue[0.4], Dashing[{Small, Small}], LineBox[CompressedData["
1:eJwU2nc81P8fAHBnO44zSkNkhCSkLXm9G1RWpZRKilRkhFRCg+bXKCGU2RCl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     "]]}, 
   {RGBColor[0.75, 0.25, 0], Thickness[0.01], LineBox[CompressedData["
1:eJwVl3k4lN8bxjEIY5tRKQlFErJUlMhzWkhCyRJZkpSlkpQSvi2WiijJnrKn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     "]]}},
  AspectRatio->NCache[
    Rational[1, 2], 0.5],
  AxesOrigin->{0, 0},
  Frame->True,
  FrameLabel->{
    FormBox["\"x\"", TraditionalForm], 
    FormBox["\"y\"", TraditionalForm], 
    FormBox["\"Beispiel-Plot\"", TraditionalForm]},
  PlotRange->{{0, 5}, {-0.9999999976346008, 0.9999999999999828}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{
  3.530259572242531*^9, {3.53025963977877*^9, 3.530259643480772*^9}, 
   3.530259796456335*^9, {3.530264915854642*^9, 3.5302650013903923`*^9}, {
   3.530265071545113*^9, 3.530265108907148*^9}, {3.530265171841722*^9, 
   3.530265234565096*^9}, 3.530265310953684*^9, 3.5303390983768177`*^9}]
}, Open  ]],

Cell[TextData[{
 StyleBox["PlotRange", "Input"],
 " kann bei Funktionen mit starken Schwankungen oder Divergenzen zum Einsatz \
kommen:"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530265353296116*^9, 3.530265405939139*^9}, {
  3.530265750724985*^9, 3.530265751497855*^9}, {3.530339106198721*^9, 
  3.530339107039554*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"Log", "[", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{"1", "-", "x"}], ")"}], "/", 
     RowBox[{"(", 
      RowBox[{"1", "+", "x"}], ")"}]}], "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "2"}], "}"}]}], 
  "]"}], "\[IndentingNewLine]", 
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"Log", "[", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{"1", "-", "x"}], ")"}], "/", 
     RowBox[{"(", 
      RowBox[{"1", "+", "x"}], ")"}]}], "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "2"}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "Automatic"}]}], 
  "]"}], "\[IndentingNewLine]", 
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"Log", "[", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{"1", "-", "x"}], ")"}], "/", 
     RowBox[{"(", 
      RowBox[{"1", "+", "x"}], ")"}]}], "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "2"}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "All"}]}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"Log", "[", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{"1", "-", "x"}], ")"}], "/", 
     RowBox[{"(", 
      RowBox[{"1", "+", "x"}], ")"}]}], "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "2"}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "Full"}]}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"Log", "[", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{"1", "-", "x"}], ")"}], "/", 
     RowBox[{"(", 
      RowBox[{"1", "+", "x"}], ")"}]}], "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "2"}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", 
    RowBox[{"{", 
     RowBox[{
      RowBox[{"{", 
       RowBox[{"0", ",", "1"}], "}"}], ",", 
      RowBox[{"{", 
       RowBox[{
        RowBox[{"-", "4"}], ",", "4"}], "}"}]}], "}"}]}]}], "]"}]}], "Input",
 CellChangeTimes->{{3.530265783153151*^9, 3.530265817924096*^9}, {
  3.530265860451684*^9, 3.530265921521524*^9}, {3.530265951696548*^9, 
  3.530266202665814*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwVjns4lAkbh2fGME4xZsg3oqjItm0sPjrgKYe2vihahbYUSyEJK6WTypTk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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{{0, 2}, {-5.548782289980744, 0.}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.5302657921187468`*^9, 3.530265818354188*^9}, {
   3.5302658613399973`*^9, 3.5302659223092833`*^9}, {3.530265968277274*^9, 
   3.530266041880198*^9}, {3.530266072081565*^9, 3.5302661146991653`*^9}, 
   3.530266147787778*^9, {3.530266187002433*^9, 3.530266203090744*^9}, 
   3.5303391089736834`*^9}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwVjns4lAkbh2fGME4xZsg3oqjItm0sPjrgKYe2vihahbYUSyEJK6WTypTk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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{{0., 0.999971510457685}, {-5.548782289980744, 0.}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.5302657921187468`*^9, 3.530265818354188*^9}, {
   3.5302658613399973`*^9, 3.5302659223092833`*^9}, {3.530265968277274*^9, 
   3.530266041880198*^9}, {3.530266072081565*^9, 3.5302661146991653`*^9}, 
   3.530266147787778*^9, {3.530266187002433*^9, 3.530266203090744*^9}, 
   3.530339108994421*^9}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwVUmk0lQsbPcc8ZR46MlakbkW4NOCRaLgoSqFBEUIiPhEpiaJMyVxI0mRI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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{All, All},
  PlotRangeClipping->True,
  PlotRangePadding->{Automatic, Automatic}]], "Output",
 CellChangeTimes->{{3.5302657921187468`*^9, 3.530265818354188*^9}, {
   3.5302658613399973`*^9, 3.5302659223092833`*^9}, {3.530265968277274*^9, 
   3.530266041880198*^9}, {3.530266072081565*^9, 3.5302661146991653`*^9}, 
   3.530266147787778*^9, {3.530266187002433*^9, 3.530266203090744*^9}, 
   3.530339109013855*^9}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwVUmk0lQsbPcc8ZR46MlakbkW4NOCRaLgoSqFBEUIiPhEpiaJMyVxI0mRI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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{{0, 2}, {-11.159106410028755`, -8.163265308297384*^-8}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.5302657921187468`*^9, 3.530265818354188*^9}, {
   3.5302658613399973`*^9, 3.5302659223092833`*^9}, {3.530265968277274*^9, 
   3.530266041880198*^9}, {3.530266072081565*^9, 3.5302661146991653`*^9}, 
   3.530266147787778*^9, {3.530266187002433*^9, 3.530266203090744*^9}, 
   3.530339109032144*^9}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwdjnlUjAsYh2ermcnUULmdiSiU9eDWnGzprWS7iRliskWdSjKibreMKK4h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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{{0, 1}, {-4, 4}},
  PlotRangeClipping->True,
  PlotRangePadding->{Automatic, Automatic}]], "Output",
 CellChangeTimes->{{3.5302657921187468`*^9, 3.530265818354188*^9}, {
   3.5302658613399973`*^9, 3.5302659223092833`*^9}, {3.530265968277274*^9, 
   3.530266041880198*^9}, {3.530266072081565*^9, 3.5302661146991653`*^9}, 
   3.530266147787778*^9, {3.530266187002433*^9, 3.530266203090744*^9}, 
   3.530339109049837*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{"plot1", ",", "plot2", ",", "plotStyle"}], "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.5303447889951963`*^9, 3.5303447982184267`*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell["\<\
Andere M\[ODoubleDot]glichkeiten 2-dimensionalen Plottens\
\>", "Subsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5302663273743553`*^9, 3.5302663401870317`*^9}, 
   3.5303350023493443`*^9}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"list", "=", 
   RowBox[{"Table", "[", 
    RowBox[{
     RowBox[{
      RowBox[{"Exp", "[", 
       RowBox[{
        RowBox[{"-", "i"}], "/", "25"}], "]"}], "+", 
      RowBox[{"RandomReal", "[", "0.1", "]"}]}], ",", 
     RowBox[{"{", 
      RowBox[{"i", ",", "1", ",", "100"}], "}"}]}], "]"}]}], 
  ";"}], "\[IndentingNewLine]", 
 RowBox[{"ListPlot", "[", "list", "]"}]}], "Input",
 CellChangeTimes->{{3.53026702607274*^9, 3.530267028370895*^9}, {
  3.530267328099367*^9, 3.53026743268246*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, 
   {Hue[0.67, 0.6, 0.6], PointBox[CompressedData["
1:eJw1kQlQVVUch5+gYAWKCjxAREgCEaSQTY3lxyLwWN/OIwwUeEgxSipSQ8MS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     "]]}, {}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{{0., 100.}, {0., 1.0576525308667555`}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.530267382394611*^9, 3.530267433307889*^9}, 
   3.530339129230155*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"PolarPlot", "[", 
  RowBox[{
   RowBox[{"Exp", "[", 
    RowBox[{"phi", "/", "10"}], "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"phi", ",", "0", ",", "20"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.530267092303732*^9, 3.5302670946045113`*^9}, {
  3.530267476717944*^9, 3.530267547663644*^9}}],

Cell[BoxData[
 GraphicsBox[{{{}, {}}, {}, {{}, {}, 
    {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw0l3c8lW/4xx17J6nQEKGMMspMrgftZZSESiWjoZKRyExRdl8UskqFzMjm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      
      "]]}}, {}, {{{}, {}, {}, {}}, {}}},
  Axes->True,
  AxesOrigin->{0, 0},
  CoordinatesToolOptions:>{"DisplayFunction" -> ({
      Sqrt[Part[#, 1]^2 + Part[#, 2]^2], 
      Mod[
       ArcTan[
        Part[#, 1], 
        Part[#, 2]], 2 Pi]}& ), "CopiedValueFunction" -> ({
      Sqrt[Part[#, 1]^2 + Part[#, 2]^2], 
      Mod[
       ArcTan[
        Part[#, 1], 
        Part[#, 2]], 2 Pi]}& )},
  DisplayFunction:>Identity,
  PlotRange->{{Automatic, Automatic}, {Automatic, Automatic}},
  PlotRangeClipping->True,
  PlotRangePadding->Scaled[0.02]]], "Output",
 CellChangeTimes->{{3.5302674909313927`*^9, 3.530267548129994*^9}, 
   3.5303391317368917`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"ParametricPlot", "[", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     RowBox[{
      RowBox[{"Sin", "[", "t", "]"}], "*", 
      RowBox[{"Cos", "[", 
       RowBox[{"t", "/", "10"}], "]"}]}], ",", 
     RowBox[{
      RowBox[{"Sin", "[", "t", "]"}], "*", 
      RowBox[{"Sin", "[", 
       RowBox[{"t", "/", "10"}], "]"}]}]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", "100"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.494862256915543*^9, 3.494862257008041*^9}, {
  3.494862313232044*^9, 3.4948623433751*^9}, {3.494862385601258*^9, 
  3.494862429906587*^9}, {3.530267034638543*^9, 3.530267042984502*^9}, {
  3.530267567503564*^9, 3.5302677743157263`*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJxcl3k41N/3wFukIkuKkuwfLUJSkSxHK22IVFIJIUqUsmQpa7JF1qKE7Mq+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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{{-0.9878109604659221, 0.9878097640170771}, {-0.9878107791493771,
    0.9877987779218461}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.530267718304944*^9, 3.530267775027685*^9}, 
   3.530339138709628*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"ContourPlot", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"Sin", "[", "x", "]"}], "*", 
    RowBox[{"Sin", "[", "y", "]"}]}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", 
     RowBox[{"2", "*", "Pi"}]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"y", ",", "0", ",", 
     RowBox[{"2", "*", "Pi"}]}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.5302671350832777`*^9, 3.5302671386690617`*^9}, {
  3.530268117244894*^9, 3.5302681198033323`*^9}, {3.530268309703869*^9, 
  3.530268355466031*^9}}],

Cell[BoxData[
 GraphicsBox[GraphicsComplexBox[CompressedData["
1:eJzEnXd8V8Xy9xOSEAIBEtKIgh0Lir2LnoMCihcrIteCYsMKqIiK4sWCCmJv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   "], {{
     {RGBColor[0.293416, 0.0574044, 0.529412], EdgeForm[None], 
      GraphicsGroupBox[{PolygonBox[CompressedData["
1:eJw1mG+Q1WUVx59FuPuHe++ul+Ve2L33Llih9UKYiUqzorJxIVZgHYkVZBdB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         "]], PolygonBox[CompressedData["
1:eJwllm1M1XUUx08Ilwtc7iXAe4l77/+C5kO9gS2qtR6obEHZo6utcAqSD8EW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         "]]}]}, 
     {RGBColor[0.4150981865873199, 0.26897686037537194`, 0.7004510335088123], 
      EdgeForm[None], GraphicsGroupBox[{PolygonBox[CompressedData["
1:eJxFmgmUVNW1hi9d2C1tV3dXV9PV3XWrGnFKnKMPfc9nYtSowFvBKCpOqJio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         "]], PolygonBox[CompressedData["

1:eJwlmHeUVdUVxg882gzzAOeN0+59bwBrJBHXMsZeogIDWbGwVBQVhBgL0kRG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         "]]}]}, 
     {RGBColor[0.4962196443121998, 0.4100251672922865, 0.8144770558480205], 
      EdgeForm[None], GraphicsGroupBox[{PolygonBox[CompressedData["
1:eJxFmgeUldW1xz8YpjIDM3Pv3Jl77zdDLME8LJjYRfRZECUaFLuALZa8R1UJ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         "]], 
        PolygonBox[CompressedData["
1:eJwtmHmcz3Uex7/MDHMiv5nf/K4ZW4lNUqIUYStHlBRK6wg5dreYIR6KENku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         "]]}]}, 
     {RGBColor[0.5737613661287864, 0.5435370519035628, 0.9097253540741593], 
      EdgeForm[None], GraphicsGroupBox[{PolygonBox[CompressedData["
1:eJw1m3m8lVXVxx/gXu6598Cdzvice8854CfAAVGQUQgUp4ghUUSRKEohKzXF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         "]], PolygonBox[CompressedData["
1:eJwtmHd01VUSx38pkJeXkEDyevIehF0EVKoQQJAAAooIShcQZVdFLHTFdo5l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         "]]}]}, 
     {RGBColor[0.6334044084039064, 0.6393668249866483, 0.911085031734951], 
      EdgeForm[None], GraphicsGroupBox[{PolygonBox[CompressedData["
1:eJxNm3eclcXVx59dti/s3r17n9uWe1cUIqiogI0qxV6SiFFjiSAWLLSIJTZs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         "]], PolygonBox[CompressedData["
1:eJwtmXm4ztUWx3/HmQfnHOecdzze9+DSdQghknnoGopbmQqJSGnkOhoJUUkd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         "]], 
        PolygonBox[{{6391, 2564, 5145, 6233, 6234}, {6216, 6215, 5128, 2556, 
         6381}, {6379, 2555, 5127, 6215, 6216}, {6234, 6233, 5144, 2563, 
         6388}}]}]}, 
     {RGBColor[0.6930474506790265, 0.7351965980697337, 0.912444709395743], 
      EdgeForm[None], GraphicsGroupBox[{PolygonBox[CompressedData["
1:eJxNm3mYlMW1xr+ZDLMzdPf01z3TQ/coiCKrC6CiuOGCW/QqGuNCElBEISqo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         "]], PolygonBox[CompressedData["
1:eJwtmXl01dURx3+BvAQICVne772Xl7xEy74LhB2RRRBZFQXxHMQjIsgiaKsC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         "]], 
        PolygonBox[{{5164, 2581, 6414, 6241, 6242}, {6242, 6241, 6412, 2580, 
         5163}, {5148, 2565, 6393, 6236, 6237}, {6237, 6236, 6396, 2566, 
         5149}}]}]}, 
     {RGBColor[0.7526904929541466, 0.8310263711528192, 0.9138043870565347], 
      EdgeForm[None], GraphicsGroupBox[{PolygonBox[CompressedData["
1:eJxFmnmYlcWVxj96gdt0w+3uu363+95WwKiAC8giIIogaBQBISg8mkTBPfNI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         "]], 
        PolygonBox[CompressedData["
1:eJwlmHl01NUVx39JJoEkhEnIzPwyM5kBBHEBkX1VqqwFgbDIYg9FBWWzrWJl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         "]]}]}, 
     {RGBColor[0.80726725, 0.861883, 0.894034], EdgeForm[None], 
      GraphicsGroupBox[{PolygonBox[CompressedData["
1:eJxFmgmUVdWVhh9TVb0aqbqvXr3hVpVKlkMbO0iisdMaQVFUUJEYnFYwGAXH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         "]], PolygonBox[CompressedData["
1:eJwtmAmYz+UWx38ZY5gxJv7jP//lN3/FvehWN9TVcusaKsqSJZF6UiNr2lO6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         "]]}]}, 
     {RGBColor[0.86083075, 0.879745, 0.8700376000000001], EdgeForm[None], 
      GraphicsGroupBox[{PolygonBox[CompressedData["
1:eJxFmgeUldW1xz/nBkZm5jLM3Jl7Z+b77p1IsSTLkphnguYpGruggqDGhmJD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         "]], PolygonBox[CompressedData["
1:eJwlmHl4lNUVxr9kJIQkA5hJJpmZbwZZC9r2qVpbF2RR7GNFUUAQqa1lEbAq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         "]]}]}, 
     {RGBColor[0.91439425, 0.8976069999999999, 0.8460411999999999], EdgeForm[
      None], GraphicsGroupBox[{PolygonBox[CompressedData["
1:eJxFmGtwlOUVx98NJCSwmwybZDfJbt4Ugdpa/NBaLUVxZLgNCg4EUCFUMIh0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         "]], 
        PolygonBox[CompressedData["
1:eJwllltslFUQx6eF3e62u9vY0t12Lx+BtqKIT1ysJRBI0Qe0RAoapdwsgiZt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         "]]}]}}, {{}, 
     TagBox[
      TooltipBox[
       {GrayLevel[0], Opacity[0.4], LineBox[CompressedData["
1:eJwl0j1PE1AUBuDj4oAkBlRoRWzQOAA6seFkiE44gJGIytIWJ2lFgqJiW3Rg
IjGBwi9QvnSUERMNRhhV4B/4wcSAxUSiPMThyduee8+5tzdtSue7c4ciYoKr
xyPyDRH3GOTjqYgVOo9FLMt35NQHuEun/Z9PR3zh28mI97URDxojHjLMI0Y4
cyLiqSzwmFGe8MH+7/rW9X+lw7y0uRmy9DjvOh3OT8gkFfW/vv+S/+SGvk1+
mPOTLRbqIxYZqIt4I1+zbfaqtX61T/KOXJOXZVsq4oo8b+YF7vs8SFUi4pLc
1V/hrfMOq+067zcVaqxftNbOi6RehijZV6RAt7MX/N5F5mn1HkfNKuvtY+lg
Njv2TVufYZIyU7yiRc9LOccs1fb+cdcjcu/gzbxNmmvmNssWSupFCnTZl3Hf
LGnGzSuZM0aR5zzjrPot67e5wU16qfdG59y1TiZJpP7/X/YBslNXjg==
         "]], 
        LineBox[CompressedData["
1:eJwl0kkvnWEUB/DjGq+6FsbWGGraV3UIDYktCztq0UiwcFPDxkaImlJqpU3T
diPpwBdAv4ZhyScgKJaV9icWv/yf+zznPO9539y6ofG+txkRsU66JOJXZcQW
21xXRVwxUxxxKs/4af8H3xlTf14TcUHdXX2RS6wz+FcdkSkTvC6NyJV5ZJFD
Njfq6/X9sb5k2H1f/P7KN+Y8b5Zpz++Qr8ikSV1CNssrfdc8Vt9AI/vlEQdM
lEUcyUMSZjioMLO9fZmWh7JfttVGDMh2vR0sWi+QehjRLW/1/+W3OZL2UuoL
KaDKeZezTjYeRczzjk/qPrLBlDlfmPElzxk1S427NvW+4UTvMdn2y5yXU0wp
JTxlxFmrfEYbre7M8w2eyKRc5T1L7u2Rvex5l112mFT3Qd86a3x2X758QJIU
BQzaX5YrLLDE4t339a4tZq2XjTTU3v9f/gN4K0oe
         "]]},
       "0.8`"],
      Annotation[#, 0.8, "Tooltip"]& ], 
     TagBox[
      TooltipBox[
       {GrayLevel[0], Opacity[0.4], LineBox[CompressedData["
1:eJwl00tvjGEUAODTpUpI0Optpki0/gF2yIiNy3SIigVadYsGrVpQoouqtiul
1boskYi4RDTRdhq0bg0Gm9aGBWItUhsL8XyxeHJ6zvnec96Zr7O08WjuSFFE
vODtwoj7ZRFvxNl0xG9OVUa0k1V7uDiiTjwjP80rXjKo9lVvSJySv6arJOJ2
aURObfuiiJqqiBXUUizfbM8WsvyqcG5BxHIz3omz8tXlEfWeWyXuEA84d5Am
9rOPnWbfsaPXrg92fuS62g9zrokF+Xu66WGXWrteq/nHaeEEbUzr/fTMjDjs
Tm325qoj7skv2zXIAFcYYkz9r1mjyefz3Er3qHGu4P616k/kLWacdfdjYod4
ybl+LnCRPu46f9W5YXd4RJFz8+Tzk5q/R/Tz6oeZMecT05SnIso4adcmz7Qm
78SZuZ4r5hAb9Qb0JvUm6PQ93TIzo1ZpdxUVpEmx3h1LxIzY7zM1J9+9vJ5l
ZlXLl5AmRca+P2Zt1d9Glhx1rFO/aVeHnXm7x+lT22BOwf/VXndvYo96A2v1
buitEXcn74pG/QZS9pQylcwUv/CZ0eQ9MMI4ebrdvdPdzouPk747zHFuzHvp
Uu9RPyf2ipP6z3nKBM/4Zu53HpT9/z38A2CCeWc=
         "]], LineBox[CompressedData["
1:eJwl0z1szAEYx/HnDCQkBlrOa2PTWKoJYWqxYSoGk0RECVqDlxaNUiTCqeR6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         "]]},
       "0.6`"],
      Annotation[#, 0.6, "Tooltip"]& ], 
     TagBox[
      TooltipBox[
       {GrayLevel[0], Opacity[0.4], LineBox[CompressedData["
1:eJwl0stL1GEUxvHTojZRQU5OzkyFTnTBFplk15WFVGapQdAyodumVuqi/olw
UZCU40xBBW2KLuaI0xWCijJb6IxBQtFtYYuoRZePtPjyvOc95zzn/N6Z2q5T
nSfnRMQwMksiXldHvEJzMmJuVcTbVMQ4kksjzici9ju3ow0z6vfRocV65dO4
hIsoI48CBjCIHG4vj/iur0PfAXTiOt8bctdof03EfHNLPCfsMYlV6vtobkXE
Armncgv1LUKP+25M23dMboP+RqxHO78GWiX/x9wE/UvX8ssvsxsGMIgcVuvf
IvfA+REeoklcopvpKN1Ek+aes8sh/vWZiK1mbMc2jPP4aJfTZp1BSm0Nxuz8
SVzQ95n+0PuVfsEbuW/0qv477m95i7v0vXgaB8VFHiPYqK6eRxNdR3/Zp+ib
RjCEYdzHGnuMqinhMHrxzJyGtLdBme8UdvKo0Jvm5WidWVl8UN/hO6boO8zI
V2gZbe4v4wqK4udmtTq/oFkeK1GLFj11s3PsXUFB/NN75WmrHfdiF/ZgN7L6
j3rjYziCEzg++9uofyn/27dO8CljEn12b5ZL8EyZk0EaT/i02OcxvWe/fucL
2IF57s5W//+v/wNrenae
         "]], LineBox[CompressedData["
1:eJwl0ktvjHEUx/HTjkQk4tJ2njKdduoFCDOuC6WNS5fFoti0tFNGicsGLS8A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         "]]},
       "0.4`"],
      Annotation[#, 0.4, "Tooltip"]& ], 
     TagBox[
      TooltipBox[
       {GrayLevel[0], Opacity[0.4], LineBox[CompressedData["
1:eJwl0ztI11EUwPETqEMl5NssDRexqZcmao2Zj9SoBg0JioYeUJuV5WDp1hQ9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         "]], LineBox[CompressedData["
1:eJwl01tMj3EYwPEnh2EYqejoVM2m5KaUG5PDjcPCDRfc5NAMxdZxxI05H4qb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         "]]},
       "0.2`"],
      Annotation[#, 0.2, "Tooltip"]& ], 
     TagBox[
      TooltipBox[
       {GrayLevel[0], Opacity[0.4], LineBox[CompressedData["
1:eJwV0ctLVVEUB+ClVF6FGviqDA0n4eN6QbNBYNBDzZ6QlgOfINGgoqRRUI10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         "]], LineBox[CompressedData["
1:eJwV0UlL1VEYB+BXHBZlVpqVhlmUmkYZFDiVlq4icwKb3DjshJRo3bhNNFI3
7cscCvQu1E19CYdy6APYgNBgVlDPXTz87nv+Z3jPuUe7+9v6UiJijF4ShyM2
cyPO7Y8YLIw4KztzIl4au60eky9IM/5InSqXsyMa5ZD6qrzC8IGIZ+w090JB
RC3VnKeG99b8MO8nv/ZFbMstPhj/djDiO7fYovJQRJ29a1nxfTs/4jcFHKGQ
y845Los4xl/+sGr+Reddoo4G6sk0f0R/ozQ5t4Wn9m+Wa9aky8fqDPnK3An6
1OOyx3tMyX71azlJqd9lFHOCEj7aJ/Se0Ee5e6xbd99dO3y7J3vVM9beUSfk
NKed90R9Sj73XyzqdYmF5JuxzG7zWmUbTbTQTLe7pJLGP/tnyHp7pcu3eRE7
aFBnyi79ZMldvGOv8Wze6HWGaXqcUy1rqKCKSnKSd9RbKSWcpIw95t/Qx03a
uc615Hv7Vu4+A9adkbPmzXNXPSeHvMMX+VD9VW7wmQfqT7JK//8BlJdc4g==

         "]]},
       "0"],
      Annotation[#, 0, "Tooltip"]& ], 
     TagBox[
      TooltipBox[
       {GrayLevel[0], Opacity[0.4], LineBox[CompressedData["
1:eJwl009Mz3EYwPEnDsqhJv2PiNnQXMmS/JuoHKRfbdI0Wy7+XWxsTG1thc3N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         "]], 
        LineBox[CompressedData["
1:eJwl00lsjWEUxvEjNDEs2tzqZOhgIUhESNTSFPMQMYTqwpioqaJX2VlIqKHa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         "]]},
       RowBox[{"-", "0.2`"}]],
      Annotation[#, -0.2, "Tooltip"]& ], 
     TagBox[
      TooltipBox[
       {GrayLevel[0], Opacity[0.4], LineBox[CompressedData["
1:eJwl0stL1GEUxvETBbWI6OaoaU2BJoVOdK9VN4eIIGy0rKCNf0D3RbWo/yEK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         "]], LineBox[CompressedData["
1:eJwl0stvzFEYxvF3LBq0dWlHb9OZxp4o7cpUZ4NEXBbsdEaHKgtpOyz8B1jw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         "]]},
       RowBox[{"-", "0.4`"}]],
      Annotation[#, -0.4, "Tooltip"]& ], 
     TagBox[
      TooltipBox[
       {GrayLevel[0], Opacity[0.4], LineBox[CompressedData["
1:eJwl08lvDGAUAPDHURB7R2vJWIIqf4CEm20ujdYSbcWSWMK0PZFMqaSDKIOL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         "]], 
        LineBox[CompressedData["
1:eJwl00lIlAEYxvE3yG5dtNI2o0tFRAsStJ/aj9GhU6BBVNBMqVEkWJCV6DSj
0iEiCCotRw2sQ3qygpDq0Cmt3MbxkkUeouVQVL+hw59n3vV5v/lmllclDyRm
RcQLTJVEvCyLyNOiZRFzkF0c0YV6ubelERdoj7gbk8ihXW5GrYNOifO4Pj+i
d0HERbmaeRE7l0Tsxi6sFR/jcxwnsEr/z+KIDXb8oqvFRxZG1OqromfoVXON
aMAVXC7Edj/mcYPXJzOfkZX7ak8n/SieRh/6kZJrUkstiriGZmSQxpfCnJ4Z
+sZN9XwPev5H4iyvLnSiB914Jh/6ntJD+ra7Y4f4t/sreLwW19lxye3naQO9
b+4B7qED7eg1f8tcvxv6MNdcsbgET3weUH8un8R3e37gG1YujViBRl51eu64
PW1mvb51OImjanfVxtRG0eZ7emhntdxm3luwCduwFVVurKCV9KZnSvA5Jz5b
eGd27RPvx17swWF+5Xpr1GtxCtU4Xfhc+J3wSvMc4j2M23KV9uTKI8bdPoEW
+VYk1QbVEjRTeBaMqY9iI581yKkN0L/4g3d83mMYI/iAFvc0uS1Dh8SDbig1
N+29pORb5ZtpG51Uz2McOUxgtloRXpX9/z/8AzERhhA=
         "]]},
       RowBox[{"-", "0.6`"}]],
      Annotation[#, -0.6, "Tooltip"]& ], 
     TagBox[
      TooltipBox[
       {GrayLevel[0], Opacity[0.4], LineBox[CompressedData["
1:eJwl0jtP01EYB+AXHRgcJIAi5VJIlNF2cJTFRVwgIRonWzVRBJMyFJHVS1tB
LsLi9TMoLCYFlEkXhQkSvH0CFRISQo1geIjDk19zzvu+5/xP2n59sDdXFRET
9NRHDDdF3GWEteaIVbrrIpblCnesD5GnW/16a8QXfiYiPtRGFFoiijzkESVO
HosYlxOM8pgxPqr/pe+b/q90mddv7gC3yTovwwXnJ2UbFeuH1O3Iw/K7vh/8
NmeDTV43RLwhdzxiTs6ypfazvT5rn+QtuSzPyzNJZ8vTZqYOvs/vPEdORJyT
f/RXeOse1dZ2nbfHX2rtd9o7y3Sjt2OEB+ruc49Lzn7ve5d4R9p71Jj1VG+G
eb1lttW9tP+KZ7zgOfOk9JTlIgvUqN1z16Py38GbeZt+LpubkmlK1osUuKju
pvv2cYNR86bMecIkM0xzyvpV+9e4QpYMTd6ow10TsoXm5P//yz60wFkF
         "]], 
        LineBox[CompressedData["
1:eJwl0jtPVFEUBtBNQhxIiCgKiMwTBEptgEQSLCiktgFtBDopmFBAYUCZsVET
Ehi0U9A/AHb+CoESEqig8AEJDxUEJSxisfLde87e5+47c3ND+QcjZRExzfD1
iIXGiA98ZDsZscXTaxEbcpN56+95xxP1X9MR30i636uJ2E9FHLDHTw55WBtx
LP/wiyN+s68+pe+H/u8MOK/kfo43jHveGKOe3yE7KaNJXchmuaNvl7T6DFm+
1Ecsk6+LWJUrhBlWbprZ2rIcvtiTfbI9E9Ev7+rtoui6QNWNiB55qv+Ez+ao
sFahvpIEjfbv2eum1BAxwSQldbPMkDdnixlbucWQWVLOmtf7mHW9a5Rbv2q/
hstcoZocg/ayspkm7jjzkt/gtkzIFxQpOPe+7OWTd1likRF1r/S95iVvnXfq
P/jLCWf845H1gv0iz5jiORnv2mbWtMyRzfz/Xs4BM99Umw==
         "]]},
       RowBox[{"-", "0.8`"}]],
      Annotation[#, -0.8, "Tooltip"]& ], {}, {}}}],
  AspectRatio->1,
  Frame->True,
  PlotRange->
   NCache[{{0, 2 Pi}, {0, 2 Pi}}, {{0, 6.283185307179586}, {
     0, 6.283185307179586}}],
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.5302683278947153`*^9, 3.530268356166008*^9}, 
   3.530339142052915*^9},
 ImageCache->GraphicsData["CompressedBitmap", "\<\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\
\>"]]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"DensityPlot", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"Sin", "[", "x", "]"}], "*", 
    RowBox[{"Sin", "[", "y", "]"}]}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", 
     RowBox[{"3", "*", "Pi"}]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"y", ",", "0", ",", 
     RowBox[{"3", "*", "Pi"}]}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.5302671350832777`*^9, 3.5302671386690617`*^9}, {
  3.530268117244894*^9, 3.5302681198033323`*^9}, {3.530268309703869*^9, 
  3.530268377349332*^9}}],

Cell[BoxData[
 GraphicsBox[GraphicsComplexBox[CompressedData["
1:eJyFm1uInVcVgE/GnJCGJJ5M88dkmsQzo4Yo6kOjFop4flEqah7UoIJPWjS+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   "], {
    {GrayLevel[0.8], EdgeForm[None], 
     GraphicsGroupBox[PolygonBox[CompressedData["
1:eJxN3Xf891P5B/D3Z5SZkBXCbWTLKjO5rUgiSUjGnRlue2+SLXvP296UWfam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       "]]]}, {}, {}, {}, {}},
   VertexColors->CompressedData["
1:eJztfHlUjmvYb8gQCkUImSokGVIhdZEQKkOmMmQoMpM5skU7M6GSsdjENlZC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    "]],
  AspectRatio->1,
  Frame->True,
  PlotRange->
   NCache[{{0, 3 Pi}, {0, 3 Pi}}, {{0, 9.42477796076938}, {
     0, 9.42477796076938}}],
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.530268367162196*^9, 3.530268377748583*^9}, 
   3.530339144664043*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"VectorPlot", "[", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     RowBox[{"y", "*", 
      RowBox[{
       RowBox[{"Exp", "[", 
        RowBox[{
         RowBox[{"-", 
          RowBox[{"x", "^", "2"}]}], "-", 
         RowBox[{"y", "^", "2"}]}], "]"}], "^", "2"}]}], ",", 
     RowBox[{
      RowBox[{"-", "x"}], "*", 
      RowBox[{
       RowBox[{"Exp", "[", 
        RowBox[{
         RowBox[{"-", 
          RowBox[{"x", "^", "2"}]}], "-", 
         RowBox[{"y", "^", "2"}]}], "]"}], "^", "2"}]}]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", 
     RowBox[{"-", "1"}], ",", "1"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"y", ",", 
     RowBox[{"-", "1"}], ",", "1"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.530267193795024*^9, 3.5302671958475847`*^9}, {
  3.530268400511257*^9, 3.530268939815805*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, 
   {Hue[0.67, 0.6, 0.6], 
    {Arrowheads[{{0.003921651836294859, 1.}}], 
     ArrowBox[{{-0.9938937108095929, -1.0061062891904071`}, \
{-1.0061062891904071`, -0.993893710809593}}]}, 
    {Arrowheads[{{0.006208796554761643, 1.}}], 
     ArrowBox[{{-0.9911024067400283, -0.8675233826128242}, \
{-1.0088975932599717`, -0.8467623316728902}}]}, 
    {Arrowheads[{{0.009076181784458948, 1.}}], 
     ArrowBox[{{-0.988383356491781, -0.730549015197221}, {-1.011616643508219, \
-0.6980224133742078}}]}, 
    {Arrowheads[{{0.012282329740131642`, 1.}}], 
     ArrowBox[{{-0.9865813941192958, -0.5949111317198039}, \
{-1.0134186058807042`, -0.5479460111373393}}]}, 
    {Arrowheads[{{0.015439108125198317`, 1.}}], 
     ArrowBox[{{-0.9866077731113562, -0.45981995797826447`}, \
{-1.0133922268886437`, -0.39732289916459307`}}]}, 
    {Arrowheads[{{0.018099962440735105`, 1.}}], 
     ArrowBox[{{-0.9890505307994545, -0.3240374279161951}, \
{-1.0109494692005456`, -0.24739114351237676`}}]}, 
    {Arrowheads[{{0.019870264911352794`, 1.}}], 
     ArrowBox[{{-0.9938121185202736, -0.1861723132152275}, \
{-1.0061878814797265`, -0.09954197249905863}}]}, 
    {Arrowheads[{{0.020490049162187492`, 1.}}], 
     ArrowBox[{{-1., -0.04511971338421193}, {-1., 0.04511971338421149}}]}, 
    {Arrowheads[{{0.019870264911352773`, 1.}}], 
     ArrowBox[{{-1.0061878814797263`, 
      0.0995419724990582}, {-0.9938121185202737, 0.18617231321522704`}}]}, 
    {Arrowheads[{{0.01809996244073509, 1.}}], 
     ArrowBox[{{-1.0109494692005454`, 
      0.2473911435123763}, {-0.9890505307994546, 0.32403742791619466`}}]}, 
    {Arrowheads[{{0.015439108125198357`, 1.}}], 
     ArrowBox[{{-1.013392226888644, 0.3973228991645926}, {-0.9866077731113561,
       0.4598199579782641}}]}, 
    {Arrowheads[{{0.012282329740131685`, 1.}}], 
     ArrowBox[{{-1.0134186058807042`, 
      0.5479460111373388}, {-0.9865813941192958, 0.5949111317198036}}]}, 
    {Arrowheads[{{0.009076181784458948, 1.}}], 
     ArrowBox[{{-1.011616643508219, 0.6980224133742073}, {-0.988383356491781, 
      0.7305490151972206}}]}, 
    {Arrowheads[{{0.006208796554761643, 1.}}], 
     ArrowBox[{{-1.0088975932599717`, 
      0.8467623316728897}, {-0.9911024067400283, 0.8675233826128238}}]}, 
    {Arrowheads[{{0.003921651836294859, 1.}}], 
     ArrowBox[{{-1.0061062891904071`, 
      0.9938937108095924}, {-0.993893710809593, 1.0061062891904067`}}]}, 
    {Arrowheads[{{0.006208796554761643, 1.}}], 
     ArrowBox[{{-0.8467623316728902, -1.0088975932599717`}, \
{-0.8675233826128242, -0.9911024067400283}}]}, 
    {Arrowheads[{{0.009714180855953485, 1.}}], 
     ArrowBox[{{-0.8420171907067436, -0.8722685235789708}, \
{-0.8722685235789708, -0.8420171907067436}}]}, 
    {Arrowheads[{{0.014008583182748974`, 1.}}], 
     ArrowBox[{{-0.8373948792707913, -0.7379832877321936}, \
{-0.8768908350149232, -0.6905881408392353}}]}, 
    {Arrowheads[{{0.018675305547881594`, 1.}}], 
     ArrowBox[{{-0.8343315922694335, -0.6056454687387071}, \
{-0.8799541220162808, -0.5372116741184362}}]}, 
    {Arrowheads[{{0.023118328940364277`, 1.}}], 
     ArrowBox[{{-0.8343764358381569, -0.4741042711808294}, \
{-0.8799092784475575, -0.3830385859620281}}]}, 
    {Arrowheads[{{0.026730784488901812`, 1.}}], 
     ArrowBox[{{-0.838529057439849, -0.34155568482331067`}, \
{-0.8757566568458655, -0.22987288660526115`}}]}, 
    {Arrowheads[{{0.02905771681835003, 1.}}], 
     ArrowBox[{{-0.846623627001195, -0.20597252370711663`}, \
{-0.8676620872845195, -0.07974176200716951}}]}, 
    {Arrowheads[{{0.0298564508881072, 1.}}], 
     ArrowBox[{{-0.8571428571428572, -0.06574481574339855}, \
{-0.8571428571428572, 0.0657448157433981}}]}, 
    {Arrowheads[{{0.029057716818350024`, 1.}}], 
     ArrowBox[{{-0.8676620872845194, 
      0.07974176200716906}, {-0.846623627001195, 0.2059725237071162}}]}, 
    {Arrowheads[{{0.026730784488901812`, 1.}}], 
     ArrowBox[{{-0.8757566568458655, 0.2298728866052607}, {-0.838529057439849,
       0.3415556848233102}}]}, 
    {Arrowheads[{{0.023118328940364277`, 1.}}], 
     ArrowBox[{{-0.8799092784475575, 
      0.38303858596202767`}, {-0.8343764358381569, 0.47410427118082893`}}]}, 
    {Arrowheads[{{0.018675305547881594`, 1.}}], 
     ArrowBox[{{-0.8799541220162809, 
      0.5372116741184357}, {-0.8343315922694337, 0.6056454687387066}}]}, 
    {Arrowheads[{{0.014008583182748974`, 1.}}], 
     ArrowBox[{{-0.8768908350149232, 
      0.6905881408392348}, {-0.8373948792707913, 0.7379832877321931}}]}, 
    {Arrowheads[{{0.009714180855953485, 1.}}], 
     ArrowBox[{{-0.8722685235789708, 
      0.8420171907067432}, {-0.8420171907067436, 0.8722685235789703}}]}, 
    {Arrowheads[{{0.006208796554761643, 1.}}], 
     ArrowBox[{{-0.8675233826128242, 
      0.9911024067400278}, {-0.8467623316728902, 1.0088975932599713`}}]}, 
    {Arrowheads[{{0.009076181784458948, 1.}}], 
     ArrowBox[{{-0.6980224133742078, -1.011616643508219}, \
{-0.730549015197221, -0.988383356491781}}]}, 
    {Arrowheads[{{0.014008583182748974`, 1.}}], 
     ArrowBox[{{-0.6905881408392353, -0.8768908350149232}, \
{-0.7379832877321936, -0.8373948792707913}}]}, 
    {Arrowheads[{{0.019870264911352773`, 1.}}], 
     ArrowBox[{{-0.6833463068870828, -0.7452251216843461}, \
{-0.7452251216843462, -0.6833463068870826}}]}, 
    {Arrowheads[{{0.025980489646377388`, 1.}}], 
     ArrowBox[{{-0.6785470162899425, -0.6161019439232864}, \
{-0.7500244122814862, -0.5267551989338568}}]}, 
    {Arrowheads[{{0.03148320952556872, 1.}}], 
     ArrowBox[{{-0.6786172732778188, -0.48801883025125475`}, \
{-0.74995415529361, -0.36912402689160284`}}]}, 
    {Arrowheads[{{0.03565907448128016, 1.}}], 
     ArrowBox[{{-0.6851232382094915, -0.35862047590484314`}, \
{-0.7434481903619373, -0.21280809552372867`}}]}, 
    {Arrowheads[{{0.03816248602002296, 1.}}], 
     ArrowBox[{{-0.6978051030058514, -0.22526019925645807`}, \
{-0.7307663255655774, -0.06045408645782807}}]}, 
    {Arrowheads[{{0.038980400233410116`, 1.}}], 
     ArrowBox[{{-0.7142857142857144, -0.08583603056350902}, \
{-0.7142857142857144, 0.08583603056350858}}]}, 
    {Arrowheads[{{0.038162486020022965`, 1.}}], 
     ArrowBox[{{-0.7307663255655774, 
      0.060454086457827585`}, {-0.6978051030058514, 
      0.22526019925645763`}}]}, 
    {Arrowheads[{{0.03565907448128018, 1.}}], 
     ArrowBox[{{-0.7434481903619373, 
      0.2128080955237282}, {-0.6851232382094915, 0.35862047590484275`}}]}, 
    {Arrowheads[{{0.03148320952556874, 1.}}], 
     ArrowBox[{{-0.74995415529361, 0.3691240268916023}, {-0.6786172732778188, 
      0.4880188302512543}}]}, 
    {Arrowheads[{{0.0259804896463774, 1.}}], 
     ArrowBox[{{-0.7500244122814863, 
      0.5267551989338564}, {-0.6785470162899425, 0.616101943923286}}]}, 
    {Arrowheads[{{0.019870264911352787`, 1.}}], 
     ArrowBox[{{-0.7452251216843462, 
      0.6833463068870822}, {-0.6833463068870828, 0.7452251216843457}}]}, 
    {Arrowheads[{{0.01400858318274899, 1.}}], 
     ArrowBox[{{-0.7379832877321936, 
      0.8373948792707908}, {-0.6905881408392353, 0.8768908350149228}}]}, 
    {Arrowheads[{{0.009076181784458948, 1.}}], 
     ArrowBox[{{-0.730549015197221, 0.9883833564917806}, {-0.6980224133742078,
       1.0116166435082186`}}]}, 
    {Arrowheads[{{0.012282329740131642`, 1.}}], 
     ArrowBox[{{-0.5479460111373393, -1.0134186058807042`}, \
{-0.5949111317198039, -0.9865813941192958}}]}, 
    {Arrowheads[{{0.018675305547881594`, 1.}}], 
     ArrowBox[{{-0.5372116741184362, -0.8799541220162809}, \
{-0.6056454687387071, -0.8343315922694337}}]}, 
    {Arrowheads[{{0.025980489646377388`, 1.}}], 
     ArrowBox[{{-0.5267551989338568, -0.7500244122814863}, \
{-0.6161019439232864, -0.6785470162899426}}]}, 
    {Arrowheads[{{0.03314111693426542, 1.}}], 
     ArrowBox[{{-0.5198255091116172, -0.6230316337455261}, \
{-0.6230316337455261, -0.5198255091116172}}]}, 
    {Arrowheads[{{0.03898040023341012, 1.}}], 
     ArrowBox[{{-0.5199269530904663, -0.4972402530222358}, \
{-0.6229301897666769, -0.3599026041206217}}]}, 
    {Arrowheads[{{0.042758534747934784`, 1.}}], 
     ArrowBox[{{-0.5293209078965632, -0.3699296127783027}, \
{-0.61353623496058, -0.20149895865026912`}}]}, 
    {Arrowheads[{{0.044556512777604286`, 1.}}], 
     ArrowBox[{{-0.5476322369623051, -0.23804248072220885`}, \
{-0.595224905894838, -0.04767180499207731}}]}, 
    {Arrowheads[{{0.04502700176984544, 1.}}], 
     ArrowBox[{{-0.5714285714285716, -0.09915083162196436}, \
{-0.5714285714285717, 0.09915083162196392}}]}, 
    {Arrowheads[{{0.04455651277760429, 1.}}], 
     ArrowBox[{{-0.595224905894838, 
      0.04767180499207682}, {-0.5476322369623052, 0.23804248072220843`}}]}, 
    {Arrowheads[{{0.04275853474793481, 1.}}], 
     ArrowBox[{{-0.61353623496058, 
      0.20149895865026862`}, {-0.5293209078965632, 0.36992961277830233`}}]}, 
    {Arrowheads[{{0.03898040023341014, 1.}}], 
     ArrowBox[{{-0.6229301897666769, 
      0.35990260412062125`}, {-0.5199269530904663, 0.49724025302223546`}}]}, 
    {Arrowheads[{{0.03314111693426547, 1.}}], 
     ArrowBox[{{-0.6230316337455262, 
      0.5198255091116166}, {-0.5198255091116172, 0.6230316337455257}}]}, 
    {Arrowheads[{{0.0259804896463774, 1.}}], 
     ArrowBox[{{-0.6161019439232864, 
      0.6785470162899421}, {-0.5267551989338568, 0.7500244122814859}}]}, 
    {Arrowheads[{{0.01867530554788161, 1.}}], 
     ArrowBox[{{-0.6056454687387071, 
      0.8343315922694331}, {-0.5372116741184362, 0.8799541220162804}}]}, 
    {Arrowheads[{{0.012282329740131685`, 1.}}], 
     ArrowBox[{{-0.594911131719804, 0.9865813941192954}, {-0.5479460111373392,
       1.0134186058807038`}}]}, 
    {Arrowheads[{{0.015439108125198345`, 1.}}], 
     ArrowBox[{{-0.39732289916459307`, -1.013392226888644}, \
{-0.45981995797826447`, -0.9866077731113561}}]}, 
    {Arrowheads[{{0.023118328940364277`, 1.}}], 
     ArrowBox[{{-0.38303858596202817`, -0.8799092784475575}, \
{-0.47410427118082943`, -0.8343764358381569}}]}, 
    {Arrowheads[{{0.03148320952556872, 1.}}], 
     ArrowBox[{{-0.3691240268916028, -0.74995415529361}, \
{-0.4880188302512547, -0.6786172732778188}}]}, 
    {Arrowheads[{{0.03898040023341012, 1.}}], 
     ArrowBox[{{-0.35990260412062175`, -0.6229301897666769}, \
{-0.49724025302223585`, -0.5199269530904663}}]}, 
    {Arrowheads[{{0.04401459193894536, 1.}}], 
     ArrowBox[{{-0.36003759686063397`, -0.49710526028222357`}, \
{-0.49710526028222357`, -0.36003759686063397`}}]}, 
    {Arrowheads[{{0.04587368524026628, 1.}}], 
     ArrowBox[{{-0.3725382471033762, -0.36976405791636474`}, \
{-0.4846046100394813, -0.2016645135122071}}]}, 
    {Arrowheads[{{0.04547480760956191, 1.}}], 
     ArrowBox[{{-0.3969053560426312, -0.23785536044353567`}, \
{-0.4602375011002264, -0.04785892527075046}}]}, 
    {Arrowheads[{{0.044938485352212565`, 1.}}], 
     ArrowBox[{{-0.4285714285714287, -0.09895591576979731}, \
{-0.4285714285714288, 0.09895591576979687}}]}, 
    {Arrowheads[{{0.045474807609561914`, 1.}}], 
     ArrowBox[{{-0.46023750110022627`, 
      0.047858925270749975`}, {-0.39690535604263133`, 
      0.23785536044353528`}}]}, 
    {Arrowheads[{{0.0458736852402663, 1.}}], 
     ArrowBox[{{-0.4846046100394813, 
      0.2016645135122066}, {-0.3725382471033763, 0.36976405791636435`}}]}, 
    {Arrowheads[{{0.044014591938945385`, 1.}}], 
     ArrowBox[{{-0.49710526028222357`, 
      0.36003759686063347`}, {-0.36003759686063397`, 0.49710526028222324`}}]}, 
    {Arrowheads[{{0.038980400233410144`, 1.}}], 
     ArrowBox[{{-0.49724025302223585`, 
      0.5199269530904659}, {-0.3599026041206217, 0.6229301897666766}}]}, 
    {Arrowheads[{{0.03148320952556875, 1.}}], 
     ArrowBox[{{-0.48801883025125475`, 
      0.6786172732778183}, {-0.36912402689160273`, 0.7499541552936095}}]}, 
    {Arrowheads[{{0.02311832894036431, 1.}}], 
     ArrowBox[{{-0.47410427118082943`, 
      0.8343764358381565}, {-0.38303858596202806`, 0.8799092784475572}}]}, 
    {Arrowheads[{{0.015439108125198357`, 1.}}], 
     ArrowBox[{{-0.4598199579782645, 
      0.9866077731113556}, {-0.39732289916459307`, 1.0133922268886435`}}]}, 
    {Arrowheads[{{0.018099962440735074`, 1.}}], 
     ArrowBox[{{-0.24739114351237676`, -1.0109494692005454`}, \
{-0.32403742791619505`, -0.9890505307994546}}]}, 
    {Arrowheads[{{0.026730784488901822`, 1.}}], 
     ArrowBox[{{-0.22987288660526115`, -0.8757566568458655}, \
{-0.3415556848233107, -0.838529057439849}}]}, 
    {Arrowheads[{{0.03565907448128016, 1.}}], 
     ArrowBox[{{-0.21280809552372867`, -0.7434481903619373}, \
{-0.35862047590484314`, -0.6851232382094915}}]}, 
    {Arrowheads[{{0.0427585347479348, 1.}}], 
     ArrowBox[{{-0.20149895865026912`, -0.6135362349605801}, \
{-0.3699296127783027, -0.5293209078965632}}]}, 
    {Arrowheads[{{0.04587368524026628, 1.}}], 
     ArrowBox[{{-0.2016645135122071, -0.48460461003948135`}, \
{-0.36976405791636474`, -0.37253824710337624`}}]}, 
    {Arrowheads[{{0.0441335105854572, 1.}}], 
     ArrowBox[{{-0.2169952892627019, -0.35443328216586995`}, \
{-0.35443328216586995`, -0.2169952892627019}}]}, 
    {Arrowheads[{{0.0394355043466104, 1.}}], 
     ArrowBox[{{-0.2468790693526605, -0.22052757558039388`}, \
{-0.3245495020759114, -0.06518671013389228}}]}, 
    {Arrowheads[{{0.0367416536006016, 1.}}], 
     ArrowBox[{{-0.28571428571428586`, -0.08090624217634415}, \
{-0.285714285714286, 0.0809062421763437}}]}, 
    {Arrowheads[{{0.03943550434661036, 1.}}], 
     ArrowBox[{{-0.3245495020759112, 
      0.06518671013389184}, {-0.2468790693526606, 0.22052757558039338`}}]}, 
    {Arrowheads[{{0.04413351058545717, 1.}}], 
     ArrowBox[{{-0.35443328216586983`, 
      0.21699528926270145`}, {-0.216995289262702, 0.3544332821658695}}]}, 
    {Arrowheads[{{0.045873685240266304`, 1.}}], 
     ArrowBox[{{-0.36976405791636474`, 
      0.3725382471033757}, {-0.2016645135122071, 0.4846046100394809}}]}, 
    {Arrowheads[{{0.042758534747934826`, 1.}}], 
     ArrowBox[{{-0.3699296127783028, 
      0.5293209078965627}, {-0.20149895865026907`, 0.6135362349605796}}]}, 
    {Arrowheads[{{0.03565907448128021, 1.}}], 
     ArrowBox[{{-0.35862047590484325`, 
      0.6851232382094911}, {-0.21280809552372862`, 0.743448190361937}}]}, 
    {Arrowheads[{{0.026730784488901854`, 1.}}], 
     ArrowBox[{{-0.3415556848233108, 
      0.8385290574398485}, {-0.2298728866052611, 0.8757566568458651}}]}, 
    {Arrowheads[{{0.018099962440735137`, 1.}}], 
     ArrowBox[{{-0.32403742791619516`, 
      0.989050530799454}, {-0.24739114351237668`, 1.0109494692005452`}}]}, 
    {Arrowheads[{{0.019870264911352787`, 1.}}], 
     ArrowBox[{{-0.09954197249905863, -1.0061878814797263`}, \
{-0.1861723132152275, -0.9938121185202736}}]}, 
    {Arrowheads[{{0.02905771681835003, 1.}}], 
     ArrowBox[{{-0.07974176200716951, -0.8676620872845194}, \
{-0.20597252370711663`, -0.8466236270011949}}]}, 
    {Arrowheads[{{0.03816248602002296, 1.}}], 
     ArrowBox[{{-0.06045408645782807, -0.7307663255655774}, \
{-0.22526019925645807`, -0.6978051030058514}}]}, 
    {Arrowheads[{{0.04455651277760428, 1.}}], 
     ArrowBox[{{-0.04767180499207731, -0.5952249058948381}, \
{-0.2380424807222088, -0.5476322369623052}}]}, 
    {Arrowheads[{{0.045474807609561914`, 1.}}], 
     ArrowBox[{{-0.04785892527075046, -0.4602375011002263}, \
{-0.23785536044353572`, -0.39690535604263116`}}]}, 
    {Arrowheads[{{0.03943550434661038, 1.}}], 
     ArrowBox[{{-0.06518671013389228, -0.3245495020759113}, \
{-0.22052757558039382`, -0.2468790693526605}}]}, 
    {Arrowheads[{{0.02819008018970477, 1.}}], 
     ArrowBox[{{-0.0989631948156625, -0.18675109089862363`}, \
{-0.18675109089862363`, -0.0989631948156625}}]}, 
    {Arrowheads[{{0.0207638373774646, 1.}}], 
     ArrowBox[{{-0.142857142857143, -0.04572260338723227}, \
{-0.14285714285714313`, 0.045722603387231824`}}]}, 
    {Arrowheads[{{0.028190080189704737`, 1.}}], 
     ArrowBox[{{-0.18675109089862352`, 
      0.09896319481566204}, {-0.09896319481566263, 0.1867510908986232}}]}, 
    {Arrowheads[{{0.03943550434661036, 1.}}], 
     ArrowBox[{{-0.22052757558039376`, 
      0.24687906935266002`}, {-0.06518671013389236, 0.32454950207591093`}}]}, 
    
    {Arrowheads[{{0.04547480760956191, 1.}}], 
     ArrowBox[{{-0.23785536044353567`, 
      0.3969053560426307}, {-0.04785892527075049, 0.4602375011002259}}]}, 
    {Arrowheads[{{0.04455651277760429, 1.}}], 
     ArrowBox[{{-0.23804248072220885`, 
      0.5476322369623047}, {-0.047671804992077293`, 0.5952249058948377}}]}, 
    {Arrowheads[{{0.038162486020023006`, 1.}}], 
     ArrowBox[{{-0.22526019925645815`, 
      0.697805103005851}, {-0.06045408645782799, 0.7307663255655771}}]}, 
    {Arrowheads[{{0.02905771681835004, 1.}}], 
     ArrowBox[{{-0.20597252370711666`, 
      0.8466236270011944}, {-0.07974176200716947, 0.867662087284519}}]}, 
    {Arrowheads[{{0.01987026491135281, 1.}}], 
     ArrowBox[{{-0.18617231321522754`, 
      0.9938121185202732}, {-0.09954197249905859, 1.006187881479726}}]}, 
    {Arrowheads[{{0.020490049162187492`, 1.}}], 
     ArrowBox[{{0.04511971338421149, -1.}, {-0.04511971338421193, -1.}}]}, 
    {Arrowheads[{{0.0298564508881072, 1.}}], 
     ArrowBox[{{
      0.0657448157433981, -0.8571428571428572}, {-0.06574481574339855, \
-0.8571428571428572}}]}, 
    {Arrowheads[{{0.038980400233410116`, 1.}}], 
     ArrowBox[{{
      0.08583603056350858, -0.7142857142857144}, {-0.08583603056350902, \
-0.7142857142857144}}]}, 
    {Arrowheads[{{0.04502700176984544, 1.}}], 
     ArrowBox[{{
      0.09915083162196392, -0.5714285714285716}, {-0.09915083162196436, \
-0.5714285714285715}}]}, 
    {Arrowheads[{{0.044938485352212565`, 1.}}], 
     ArrowBox[{{
      0.09895591576979687, -0.4285714285714288}, {-0.09895591576979731, \
-0.4285714285714287}}]}, 
    {Arrowheads[{{0.0367416536006016, 1.}}], 
     ArrowBox[{{
      0.0809062421763437, -0.285714285714286}, {-0.08090624217634415, \
-0.28571428571428586`}}]}, 
    {Arrowheads[{{0.0207638373774646, 1.}}], 
     ArrowBox[{{
      0.045722603387231824`, -0.14285714285714315`}, {-0.04572260338723227, \
-0.14285714285714302`}}]}, 
    {Arrowheads[{{0.020763837377464543`, 1.}}], 
     ArrowBox[{{-0.045722603387232136`, 0.14285714285714254`}, {
      0.04572260338723169, 0.14285714285714268`}}]}, 
    {Arrowheads[{{0.03674165360060156, 1.}}], 
     ArrowBox[{{-0.08090624217634407, 0.2857142857142854}, {
      0.08090624217634362, 0.28571428571428553`}}]}, 
    {Arrowheads[{{0.04493848535221255, 1.}}], 
     ArrowBox[{{-0.09895591576979729, 0.42857142857142827`}, {
      0.09895591576979684, 0.4285714285714284}}]}, 
    {Arrowheads[{{0.04502700176984545, 1.}}], 
     ArrowBox[{{-0.09915083162196439, 0.5714285714285712}, {
      0.09915083162196395, 0.5714285714285713}}]}, 
    {Arrowheads[{{0.03898040023341015, 1.}}], 
     ArrowBox[{{-0.08583603056350911, 0.714285714285714}, {
      0.08583603056350866, 0.714285714285714}}]}, 
    {Arrowheads[{{0.029856450888107237`, 1.}}], 
     ArrowBox[{{-0.06574481574339863, 0.8571428571428568}, {
      0.06574481574339819, 0.8571428571428568}}]}, 
    {Arrowheads[{{0.02049004916218752, 1.}}], 
     ArrowBox[{{-0.04511971338421199, 0.9999999999999996}, {
      0.04511971338421154, 0.9999999999999996}}]}, 
    {Arrowheads[{{0.019870264911352783`, 1.}}], 
     ArrowBox[{{0.18617231321522704`, -0.9938121185202736}, {
      0.0995419724990582, -1.0061878814797265`}}]}, 
    {Arrowheads[{{0.029057716818350024`, 1.}}], 
     ArrowBox[{{0.2059725237071162, -0.846623627001195}, {
      0.07974176200716906, -0.8676620872845194}}]}, 
    {Arrowheads[{{0.038162486020022986`, 1.}}], 
     ArrowBox[{{0.22526019925645768`, -0.6978051030058514}, {
      0.060454086457827585`, -0.7307663255655774}}]}, 
    {Arrowheads[{{0.04455651277760429, 1.}}], 
     ArrowBox[{{0.23804248072220843`, -0.5476322369623052}, {
      0.04767180499207682, -0.595224905894838}}]}, 
    {Arrowheads[{{0.045474807609561914`, 1.}}], 
     ArrowBox[{{0.23785536044353528`, -0.3969053560426313}, {
      0.047858925270749975`, -0.4602375011002262}}]}, 
    {Arrowheads[{{0.03943550434661038, 1.}}], 
     ArrowBox[{{0.22052757558039343`, -0.2468790693526606}, {
      0.06518671013389184, -0.32454950207591127`}}]}, 
    {Arrowheads[{{0.028190080189704737`, 1.}}], 
     ArrowBox[{{0.1867510908986232, -0.09896319481566263}, {
      0.09896319481566204, -0.18675109089862352`}}]}, 
    {Arrowheads[{{0.020763837377464543`, 1.}}], 
     ArrowBox[{{0.1428571428571427, 0.04572260338723169}, {
      0.14285714285714257`, -0.045722603387232136`}}]}, 
    {Arrowheads[{{0.028190080189704696`, 1.}}], 
     ArrowBox[{{0.09896319481566217, 0.18675109089862307`}, {
      0.18675109089862307`, 0.09896319481566217}}]}, 
    {Arrowheads[{{0.039435504346610355`, 1.}}], 
     ArrowBox[{{0.06518671013389189, 0.3245495020759108}, {
      0.22052757558039332`, 0.24687906935266013`}}]}, 
    {Arrowheads[{{0.04547480760956191, 1.}}], 
     ArrowBox[{{0.047858925270750016`, 0.4602375011002258}, {
      0.23785536044353528`, 0.3969053560426308}}]}, 
    {Arrowheads[{{0.044556512777604314`, 1.}}], 
     ArrowBox[{{0.047671804992076794`, 0.5952249058948376}, {
      0.23804248072220846`, 0.5476322369623047}}]}, 
    {Arrowheads[{{0.03816248602002301, 1.}}], 
     ArrowBox[{{0.0604540864578275, 0.730766325565577}, {0.2252601992564578, 
      0.697805103005851}}]}, 
    {Arrowheads[{{0.029057716818350055`, 1.}}], 
     ArrowBox[{{0.079741762007169, 0.867662087284519}, {0.20597252370711622`, 
      0.8466236270011944}}]}, 
    {Arrowheads[{{0.019870264911352797`, 1.}}], 
     ArrowBox[{{0.09954197249905815, 1.0061878814797258`}, {
      0.1861723132152271, 0.9938121185202733}}]}, 
    {Arrowheads[{{0.018099962440735112`, 1.}}], 
     ArrowBox[{{0.32403742791619466`, -0.9890505307994545}, {
      0.2473911435123763, -1.0109494692005456`}}]}, 
    {Arrowheads[{{0.026730784488901822`, 1.}}], 
     ArrowBox[{{0.3415556848233103, -0.838529057439849}, {
      0.2298728866052607, -0.8757566568458655}}]}, 
    {Arrowheads[{{0.03565907448128018, 1.}}], 
     ArrowBox[{{0.35862047590484275`, -0.6851232382094915}, {
      0.2128080955237282, -0.7434481903619373}}]}, 
    {Arrowheads[{{0.04275853474793481, 1.}}], 
     ArrowBox[{{0.36992961277830233`, -0.5293209078965633}, {
      0.20149895865026862`, -0.6135362349605801}}]}, 
    {Arrowheads[{{0.0458736852402663, 1.}}], 
     ArrowBox[{{0.36976405791636435`, -0.37253824710337624`}, {
      0.2016645135122066, -0.48460461003948124`}}]}, 
    {Arrowheads[{{0.04413351058545717, 1.}}], 
     ArrowBox[{{0.3544332821658695, -0.216995289262702}, {
      0.21699528926270145`, -0.35443328216586983`}}]}, 
    {Arrowheads[{{0.039435504346610376`, 1.}}], 
     ArrowBox[{{0.32454950207591093`, -0.06518671013389236}, {
      0.24687906935266002`, -0.22052757558039382`}}]}, 
    {Arrowheads[{{0.03674165360060156, 1.}}], 
     ArrowBox[{{0.28571428571428553`, 0.08090624217634362}, {
      0.2857142857142854, -0.08090624217634407}}]}, 
    {Arrowheads[{{0.03943550434661036, 1.}}], 
     ArrowBox[{{0.24687906935266013`, 0.22052757558039338`}, {
      0.3245495020759108, 0.06518671013389189}}]}, 
    {Arrowheads[{{0.04413351058545717, 1.}}], 
     ArrowBox[{{0.2169952892627015, 0.35443328216586945`}, {
      0.35443328216586945`, 0.2169952892627015}}]}, 
    {Arrowheads[{{0.04587368524026631, 1.}}], 
     ArrowBox[{{0.2016645135122066, 0.4846046100394809}, {
      0.36976405791636435`, 0.3725382471033758}}]}, 
    {Arrowheads[{{0.04275853474793484, 1.}}], 
     ArrowBox[{{0.2014989586502686, 0.6135362349605796}, {0.3699296127783024, 
      0.5293209078965627}}]}, 
    {Arrowheads[{{0.03565907448128022, 1.}}], 
     ArrowBox[{{0.2128080955237281, 0.7434481903619369}, {
      0.35862047590484286`, 0.6851232382094911}}]}, 
    {Arrowheads[{{0.026730784488901854`, 1.}}], 
     ArrowBox[{{0.22987288660526062`, 0.875756656845865}, {
      0.34155568482331033`, 0.8385290574398485}}]}, 
    {Arrowheads[{{0.018099962440735123`, 1.}}], 
     ArrowBox[{{0.24739114351237623`, 1.010949469200545}, {0.3240374279161947,
       0.989050530799454}}]}, 
    {Arrowheads[{{0.015439108125198326`, 1.}}], 
     ArrowBox[{{0.459819957978264, -0.9866077731113562}, {
      0.39732289916459257`, -1.0133922268886437`}}]}, 
    {Arrowheads[{{0.023118328940364283`, 1.}}], 
     ArrowBox[{{0.474104271180829, -0.8343764358381569}, {
      0.38303858596202767`, -0.8799092784475575}}]}, 
    {Arrowheads[{{0.03148320952556874, 1.}}], 
     ArrowBox[{{0.48801883025125437`, -0.6786172732778188}, {
      0.36912402689160234`, -0.74995415529361}}]}, 
    {Arrowheads[{{0.03898040023341014, 1.}}], 
     ArrowBox[{{0.4972402530222354, -0.5199269530904663}, {
      0.3599026041206212, -0.6229301897666769}}]}, 
    {Arrowheads[{{0.04401459193894538, 1.}}], 
     ArrowBox[{{0.4971052602822232, -0.36003759686063397`}, {
      0.3600375968606334, -0.4971052602822235}}]}, 
    {Arrowheads[{{0.045873685240266304`, 1.}}], 
     ArrowBox[{{0.48460461003948097`, -0.2016645135122071}, {
      0.37253824710337574`, -0.36976405791636474`}}]}, 
    {Arrowheads[{{0.0454748076095619, 1.}}], 
     ArrowBox[{{0.46023750110022593`, -0.04785892527075049}, {
      0.3969053560426308, -0.2378553604435356}}]}, 
    {Arrowheads[{{0.04493848535221255, 1.}}], 
     ArrowBox[{{0.4285714285714284, 0.09895591576979684}, {
      0.42857142857142827`, -0.09895591576979729}}]}, 
    {Arrowheads[{{0.0454748076095619, 1.}}], 
     ArrowBox[{{0.39690535604263083`, 0.23785536044353522`}, {
      0.4602375011002259, 0.047858925270750016`}}]}, 
    {Arrowheads[{{0.04587368524026631, 1.}}], 
     ArrowBox[{{0.37253824710337574`, 0.36976405791636435`}, {
      0.48460461003948085`, 0.2016645135122066}}]}, 
    {Arrowheads[{{0.0440145919389454, 1.}}], 
     ArrowBox[{{0.36003759686063347`, 0.4971052602822232}, {
      0.49710526028222324`, 0.36003759686063347`}}]}, 
    {Arrowheads[{{0.03898040023341013, 1.}}], 
     ArrowBox[{{0.35990260412062125`, 0.6229301897666765}, {
      0.4972402530222354, 0.5199269530904659}}]}, 
    {Arrowheads[{{0.03148320952556876, 1.}}], 
     ArrowBox[{{0.3691240268916023, 0.7499541552936096}, {
      0.48801883025125437`, 0.6786172732778184}}]}, 
    {Arrowheads[{{0.02311832894036433, 1.}}], 
     ArrowBox[{{0.3830385859620276, 0.8799092784475571}, {0.4741042711808291, 
      0.8343764358381563}}]}, 
    {Arrowheads[{{0.015439108125198357`, 1.}}], 
     ArrowBox[{{0.39732289916459257`, 1.0133922268886435`}, {
      0.4598199579782641, 0.9866077731113557}}]}, 
    {Arrowheads[{{0.012282329740131685`, 1.}}], 
     ArrowBox[{{0.5949111317198036, -0.9865813941192958}, {
      0.5479460111373388, -1.0134186058807042`}}]}, 
    {Arrowheads[{{0.018675305547881594`, 1.}}], 
     ArrowBox[{{0.6056454687387066, -0.8343315922694335}, {
      0.5372116741184357, -0.8799541220162808}}]}, 
    {Arrowheads[{{0.0259804896463774, 1.}}], 
     ArrowBox[{{0.616101943923286, -0.6785470162899425}, {
      0.5267551989338564, -0.7500244122814863}}]}, 
    {Arrowheads[{{0.03314111693426547, 1.}}], 
     ArrowBox[{{0.6230316337455257, -0.5198255091116171}, {
      0.5198255091116166, -0.6230316337455261}}]}, 
    {Arrowheads[{{0.038980400233410144`, 1.}}], 
     ArrowBox[{{0.6229301897666765, -0.3599026041206217}, {
      0.5199269530904658, -0.49724025302223585`}}]}, 
    {Arrowheads[{{0.042758534747934826`, 1.}}], 
     ArrowBox[{{0.6135362349605796, -0.20149895865026907`}, {
      0.5293209078965627, -0.3699296127783028}}]}, 
    {Arrowheads[{{0.04455651277760429, 1.}}], 
     ArrowBox[{{0.5952249058948377, -0.047671804992077293`}, {
      0.5476322369623047, -0.23804248072220885`}}]}, 
    {Arrowheads[{{0.04502700176984545, 1.}}], 
     ArrowBox[{{0.5714285714285712, 0.09915083162196395}, {
      0.5714285714285711, -0.09915083162196439}}]}, 
    {Arrowheads[{{0.044556512777604314`, 1.}}], 
     ArrowBox[{{0.5476322369623048, 0.23804248072220846`}, {
      0.5952249058948377, 0.047671804992076794`}}]}, 
    {Arrowheads[{{0.04275853474793484, 1.}}], 
     ArrowBox[{{0.5293209078965627, 0.3699296127783024}, {0.6135362349605796, 
      0.2014989586502686}}]}, 
    {Arrowheads[{{0.03898040023341013, 1.}}], 
     ArrowBox[{{0.5199269530904659, 0.4972402530222354}, {0.6229301897666765, 
      0.35990260412062125`}}]}, 
    {Arrowheads[{{0.03314111693426549, 1.}}], 
     ArrowBox[{{0.5198255091116166, 0.6230316337455257}, {0.6230316337455257, 
      0.5198255091116166}}]}, 
    {Arrowheads[{{0.025980489646377423`, 1.}}], 
     ArrowBox[{{0.5267551989338563, 0.7500244122814859}, {0.616101943923286, 
      0.6785470162899421}}]}, 
    {Arrowheads[{{0.018675305547881653`, 1.}}], 
     ArrowBox[{{0.5372116741184356, 0.8799541220162804}, {0.6056454687387067, 
      0.8343315922694331}}]}, 
    {Arrowheads[{{0.012282329740131699`, 1.}}], 
     ArrowBox[{{0.5479460111373388, 1.0134186058807038`}, {0.5949111317198036,
       0.9865813941192952}}]}, 
    {Arrowheads[{{0.009076181784458948, 1.}}], 
     ArrowBox[{{0.7305490151972206, -0.988383356491781}, {
      0.6980224133742073, -1.011616643508219}}]}, 
    {Arrowheads[{{0.014008583182748974`, 1.}}], 
     ArrowBox[{{0.7379832877321931, -0.8373948792707913}, {
      0.6905881408392348, -0.8768908350149232}}]}, 
    {Arrowheads[{{0.019870264911352787`, 1.}}], 
     ArrowBox[{{0.7452251216843457, -0.6833463068870826}, {
      0.6833463068870822, -0.7452251216843461}}]}, 
    {Arrowheads[{{0.0259804896463774, 1.}}], 
     ArrowBox[{{0.7500244122814859, -0.5267551989338568}, {
      0.6785470162899421, -0.6161019439232864}}]}, 
    {Arrowheads[{{0.03148320952556875, 1.}}], 
     ArrowBox[{{0.7499541552936096, -0.3691240268916028}, {
      0.6786172732778184, -0.4880188302512548}}]}, 
    {Arrowheads[{{0.03565907448128021, 1.}}], 
     ArrowBox[{{0.7434481903619369, -0.21280809552372862`}, {
      0.685123238209491, -0.35862047590484325`}}]}, 
    {Arrowheads[{{0.038162486020023006`, 1.}}], 
     ArrowBox[{{0.730766325565577, -0.06045408645782799}, {
      0.6978051030058509, -0.22526019925645815`}}]}, 
    {Arrowheads[{{0.03898040023341015, 1.}}], 
     ArrowBox[{{0.714285714285714, 0.08583603056350866}, {
      0.714285714285714, -0.08583603056350911}}]}, 
    {Arrowheads[{{0.038162486020023006`, 1.}}], 
     ArrowBox[{{0.697805103005851, 0.22526019925645774`}, {0.730766325565577, 
      0.0604540864578275}}]}, 
    {Arrowheads[{{0.03565907448128022, 1.}}], 
     ArrowBox[{{0.6851232382094911, 0.35862047590484286`}, {
      0.7434481903619369, 0.2128080955237281}}]}, 
    {Arrowheads[{{0.03148320952556876, 1.}}], 
     ArrowBox[{{0.6786172732778183, 0.48801883025125437`}, {
      0.7499541552936095, 0.3691240268916023}}]}, 
    {Arrowheads[{{0.02598048964637744, 1.}}], 
     ArrowBox[{{0.6785470162899421, 0.6161019439232861}, {0.7500244122814859, 
      0.5267551989338563}}]}, 
    {Arrowheads[{{0.019870264911352808`, 1.}}], 
     ArrowBox[{{0.6833463068870822, 0.7452251216843457}, {0.7452251216843457, 
      0.6833463068870822}}]}, 
    {Arrowheads[{{0.01400858318274899, 1.}}], 
     ArrowBox[{{0.6905881408392348, 0.8768908350149227}, {0.7379832877321931, 
      0.8373948792707907}}]}, 
    {Arrowheads[{{0.009076181784458964, 1.}}], 
     ArrowBox[{{0.6980224133742073, 1.0116166435082186`}, {0.7305490151972206,
       0.9883833564917804}}]}, 
    {Arrowheads[{{0.006208796554761643, 1.}}], 
     ArrowBox[{{0.8675233826128238, -0.9911024067400283}, {
      0.8467623316728897, -1.0088975932599717`}}]}, 
    {Arrowheads[{{0.009714180855953485, 1.}}], 
     ArrowBox[{{0.8722685235789703, -0.8420171907067436}, {
      0.8420171907067432, -0.8722685235789708}}]}, 
    {Arrowheads[{{0.01400858318274899, 1.}}], 
     ArrowBox[{{0.8768908350149227, -0.6905881408392353}, {
      0.8373948792707907, -0.7379832877321936}}]}, 
    {Arrowheads[{{0.01867530554788161, 1.}}], 
     ArrowBox[{{0.8799541220162804, -0.5372116741184362}, {
      0.8343315922694331, -0.6056454687387071}}]}, 
    {Arrowheads[{{0.02311832894036431, 1.}}], 
     ArrowBox[{{0.8799092784475571, -0.3830385859620281}, {
      0.8343764358381563, -0.4741042711808295}}]}, 
    {Arrowheads[{{0.026730784488901854`, 1.}}], 
     ArrowBox[{{0.875756656845865, -0.2298728866052611}, {
      0.8385290574398484, -0.3415556848233108}}]}, 
    {Arrowheads[{{0.029057716818350055`, 1.}}], 
     ArrowBox[{{0.8676620872845191, -0.07974176200716947}, {
      0.8466236270011945, -0.20597252370711672`}}]}, 
    {Arrowheads[{{0.029856450888107237`, 1.}}], 
     ArrowBox[{{0.8571428571428568, 0.06574481574339819}, {
      0.8571428571428568, -0.06574481574339863}}]}, 
    {Arrowheads[{{0.02905771681835007, 1.}}], 
     ArrowBox[{{0.8466236270011945, 0.20597252370711627`}, {
      0.8676620872845191, 0.079741762007169}}]}, 
    {Arrowheads[{{0.026730784488901854`, 1.}}], 
     ArrowBox[{{0.8385290574398485, 0.34155568482331033`}, {0.875756656845865,
       0.22987288660526062`}}]}, 
    {Arrowheads[{{0.023118328940364318`, 1.}}], 
     ArrowBox[{{0.8343764358381565, 0.47410427118082904`}, {
      0.8799092784475572, 0.3830385859620276}}]}, 
    {Arrowheads[{{0.018675305547881653`, 1.}}], 
     ArrowBox[{{0.8343315922694331, 0.6056454687387067}, {0.8799541220162804, 
      0.5372116741184356}}]}, 
    {Arrowheads[{{0.01400858318274899, 1.}}], 
     ArrowBox[{{0.8373948792707908, 0.7379832877321931}, {0.8768908350149228, 
      0.6905881408392348}}]}, 
    {Arrowheads[{{0.009714180855953521, 1.}}], 
     ArrowBox[{{0.8420171907067432, 0.8722685235789703}, {0.8722685235789704, 
      0.8420171907067431}}]}, 
    {Arrowheads[{{0.006208796554761643, 1.}}], 
     ArrowBox[{{0.8467623316728897, 1.0088975932599713`}, {0.8675233826128238,
       0.9911024067400278}}]}, 
    {Arrowheads[{{0.003921651836294859, 1.}}], 
     ArrowBox[{{1.0061062891904067`, -0.9938937108095929}, {
      0.9938937108095925, -1.0061062891904071`}}]}, 
    {Arrowheads[{{0.006208796554761643, 1.}}], 
     ArrowBox[{{1.0088975932599713`, -0.8467623316728902}, {
      0.9911024067400278, -0.8675233826128242}}]}, 
    {Arrowheads[{{0.009076181784458948, 1.}}], 
     ArrowBox[{{1.0116166435082186`, -0.6980224133742078}, {
      0.9883833564917806, -0.730549015197221}}]}, 
    {Arrowheads[{{0.012282329740131699`, 1.}}], 
     ArrowBox[{{1.0134186058807038`, -0.5479460111373392}, {
      0.9865813941192952, -0.594911131719804}}]}, 
    {Arrowheads[{{0.015439108125198345`, 1.}}], 
     ArrowBox[{{1.0133922268886435`, -0.397322899164593}, {
      0.9866077731113557, -0.45981995797826447`}}]}, 
    {Arrowheads[{{0.018099962440735123`, 1.}}], 
     ArrowBox[{{1.010949469200545, -0.24739114351237668`}, {
      0.989050530799454, -0.32403742791619516`}}]}, 
    {Arrowheads[{{0.019870264911352804`, 1.}}], 
     ArrowBox[{{1.0061878814797258`, -0.09954197249905859}, {
      0.9938121185202732, -0.18617231321522754`}}]}, 
    {Arrowheads[{{0.02049004916218752, 1.}}], 
     ArrowBox[{{0.9999999999999996, 0.04511971338421154}, {
      0.9999999999999996, -0.04511971338421199}}]}, 
    {Arrowheads[{{0.01987026491135281, 1.}}], 
     ArrowBox[{{0.9938121185202732, 0.1861723132152271}, {1.006187881479726, 
      0.09954197249905815}}]}, 
    {Arrowheads[{{0.018099962440735137`, 1.}}], 
     ArrowBox[{{0.989050530799454, 0.3240374279161947}, {1.0109494692005452`, 
      0.24739114351237623`}}]}, 
    {Arrowheads[{{0.015439108125198367`, 1.}}], 
     ArrowBox[{{0.9866077731113556, 0.4598199579782641}, {1.0133922268886435`,
       0.39732289916459257`}}]}, 
    {Arrowheads[{{0.012282329740131685`, 1.}}], 
     ArrowBox[{{0.9865813941192954, 0.5949111317198036}, {1.0134186058807038`,
       0.5479460111373388}}]}, 
    {Arrowheads[{{0.009076181784458948, 1.}}], 
     ArrowBox[{{0.9883833564917806, 0.7305490151972206}, {1.0116166435082186`,
       0.6980224133742073}}]}, 
    {Arrowheads[{{0.006208796554761643, 1.}}], 
     ArrowBox[{{0.9911024067400278, 0.8675233826128238}, {1.0088975932599713`,
       0.8467623316728897}}]}, 
    {Arrowheads[{{0.003921651836294876, 1.}}], 
     ArrowBox[{{0.9938937108095924, 1.0061062891904067`}, {
      1.0061062891904067`, 0.9938937108095924}}]}}},
  AspectRatio->1,
  Frame->True,
  Method->{"TransparentPolygonMesh" -> True},
  PlotRange->{{-1.1010152544552212`, 
   1.1010152544552212`}, {-1.1010152544552212`, 1.1010152544552212`}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.530268834834366*^9, 3.530268940474468*^9}, 
   3.530339147888962*^9}]
}, Open  ]],

Cell[TextData[{
 "Mit ",
 StyleBox["Animate", "Input"],
 " l",
 "\[ADoubleDot]",
 "sst sich im Allgemeinen das Ergebnis einer Funktion darstellen, wenn man \
einen Wert der Parameter zeitlich vaiiert. (Siehe auch ",
 StyleBox["Manipulate", "Input"],
 ".)"
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530268085418007*^9, 3.530268092686511*^9}, {
   3.530268175985107*^9, 3.530268202105349*^9}, {3.530268271891388*^9, 
   3.5302682906595*^9}, {3.530269388842505*^9, 3.5302694253959017`*^9}, 
   3.530334938172002*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Animate", "[", 
  RowBox[{
   RowBox[{"ParametricPlot", "[", 
    RowBox[{
     RowBox[{"{", 
      RowBox[{
       RowBox[{
        RowBox[{"Sin", "[", "t", "]"}], "*", 
        RowBox[{"Cos", "[", 
         RowBox[{"t", "/", "10"}], "]"}]}], ",", 
       RowBox[{
        RowBox[{"Cos", "[", "t", "]"}], "*", 
        RowBox[{"Sin", "[", 
         RowBox[{"t", "/", "10"}], "]"}]}]}], "}"}], ",", 
     RowBox[{"{", 
      RowBox[{"t", ",", "0", ",", "tmax"}], "}"}], ",", 
     RowBox[{"PlotRange", "\[Rule]", 
      RowBox[{"{", 
       RowBox[{
        RowBox[{"{", 
         RowBox[{
          RowBox[{"-", "1"}], ",", "1"}], "}"}], ",", 
        RowBox[{"{", 
         RowBox[{
          RowBox[{"-", "1"}], ",", "1"}], "}"}]}], "}"}]}]}], "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"tmax", ",", "0", ",", "50"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.494862256915543*^9, 3.494862257008041*^9}, {
  3.494862313232044*^9, 3.4948623433751*^9}, {3.494862385601258*^9, 
  3.494862429906587*^9}, {3.530267034638543*^9, 3.530267042984502*^9}, {
  3.530267567503564*^9, 3.5302680528118*^9}}],

Cell[BoxData[
 TagBox[
  StyleBox[
   DynamicModuleBox[{$CellContext`tmax$$ = 32.25517272949219, Typeset`show$$ =
     True, Typeset`bookmarkList$$ = {}, Typeset`bookmarkMode$$ = "Menu", 
    Typeset`animator$$, Typeset`animvar$$ = 1, Typeset`name$$ = 
    "\"untitled\"", Typeset`specs$$ = {{
      Hold[$CellContext`tmax$$], 0, 50}}, Typeset`size$$ = {
    360., {175., 180.}}, Typeset`update$$ = 0, Typeset`initDone$$, 
    Typeset`skipInitDone$$ = True, $CellContext`tmax$5017$$ = 0}, 
    DynamicBox[Manipulate`ManipulateBoxes[
     1, StandardForm, "Variables" :> {$CellContext`tmax$$ = 0}, 
      "ControllerVariables" :> {
        Hold[$CellContext`tmax$$, $CellContext`tmax$5017$$, 0]}, 
      "OtherVariables" :> {
       Typeset`show$$, Typeset`bookmarkList$$, Typeset`bookmarkMode$$, 
        Typeset`animator$$, Typeset`animvar$$, Typeset`name$$, 
        Typeset`specs$$, Typeset`size$$, Typeset`update$$, Typeset`initDone$$,
         Typeset`skipInitDone$$}, "Body" :> 
      ParametricPlot[{
        Sin[$CellContext`t] Cos[$CellContext`t/10], Cos[$CellContext`t] 
         Sin[$CellContext`t/10]}, {$CellContext`t, 0, $CellContext`tmax$$}, 
        PlotRange -> {{-1, 1}, {-1, 1}}], 
      "Specifications" :> {{$CellContext`tmax$$, 0, 50, 
         AppearanceElements -> {
          "ProgressSlider", "PlayPauseButton", "FasterSlowerButtons", 
           "DirectionButton"}}}, 
      "Options" :> {
       ControlType -> Animator, AppearanceElements -> None, DefaultBaseStyle -> 
        "Animate", DefaultLabelStyle -> "AnimateLabel", SynchronousUpdating -> 
        True, ShrinkingDelay -> 10.}, "DefaultOptions" :> {}],
     ImageSizeCache->{403., {212., 217.}},
     SingleEvaluation->True],
    Deinitialization:>None,
    DynamicModuleValues:>{},
    SynchronousInitialization->True,
    UnsavedVariables:>{Typeset`initDone$$},
    UntrackedVariables:>{Typeset`size$$}], "Animate",
   Deployed->True,
   StripOnInput->False],
  Manipulate`InterpretManipulate[1]]], "Output",
 CellChangeTimes->{{3.530267785756236*^9, 3.530267823713934*^9}, {
   3.530267854986518*^9, 3.530268053175959*^9}, 3.530339177525207*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", "list", "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.530344810961536*^9, 3.53034481523096*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell["3-dimensionales Plotten", "Subsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5302663982917223`*^9, 3.530266412764741*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot3D", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"Sin", "[", "x", "]"}], "*", 
    RowBox[{"Cos", "[", "y", "]"}]}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", 
     RowBox[{
      RowBox[{"-", "2"}], "*", "Pi"}], ",", 
     RowBox[{"2", "*", "Pi"}]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"y", ",", 
     RowBox[{
      RowBox[{"-", "2"}], "*", "Pi"}], ",", 
     RowBox[{"2", "*", "Pi"}]}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.494862459090159*^9, 3.494862547039816*^9}, {
  3.530269988337144*^9, 3.530270026446224*^9}}],

Cell[BoxData[
 Graphics3DBox[GraphicsComplex3DBox[CompressedData["
1:eJx0XXm8TsUbt12iS2QrskehJC0q1zsTUtIiRYVCCYmS+pE1lRIpS8q+RipK
q2R5z4mLSFkrdBNZKt1EaCN+77nzfJ/3nK+Of+7nfu+YM/PMM8882zxT7b5H
Wj9QIF++fB+elS9fwdTPNaOLnHO82rk+fj5zzWtv3FL5ncRzxete/c3Isop3
f+ylvtmFfjbXvXBLuw+OlFJ8/Gp/8ZQGv5kzzt77R+VPMhVv2tnck8z+1rh+
MhT/6oYJn36a/a3n2p/wgNvSJ2pMbfCb4LmKH1x07o0rC/3s5ZN/wPG7tDfU
XsZzwlD/GI+l8WD8lsbvyXwtzdcT+liiD8ZtiZ5J/A66frL62nIt18xWOuNn
+Z7P3jylwfdKZ+DtljW/f8xje5TOwAuNLjT26lablM7AR8x76J1GrTYpnYGX
ub3666l+lM7Ad/z87deTGnyvdAbOdKb2SmfqX+lM41E60/iVzjRfpTPRR+lM
9FQ6g36V27Sd8fWXI5NoB3xOuZumfN5sNb6reMXzf6u5KvtzD3QGfo/tW+aB
jxd7oDPw7NUdzu3+8WLQQfu7sk7nZ1P9GNAZ+IOjvxu9rtlqA7oCl1+Hgs7U
HutoqH+Mx9J4MH5L48f/tzRfrJ8l+mD/WKJnAnQGnVoO/He6V32+0hn4mO39
2z85cr/OH3iJkW/kLqyYq3TGz86/zam0otB2pTPwFxecrLuq0Hals8qbW6+7
+d2KuUpn4APM6puGjNxvovybeRqdqb3SmfpXOtN4lM40fqUzzVfpTPRROhM9
E1G5keEf+rLBjmSIzsDbDMm/eEiIzsCven5j1TCdgff/5vLun4bojJ8DhwRy
LE1n4Je37PXUwhCdgf/yy81vDg7RGTjTmdornal/Lyo3dDxKZxq/icoNna+J
yg2lj4nKDaUn8fMJr/SeVxdtCMkN4A0eLbZzVUhuAC8+9It/l4fkBvA2Ixd9
dG9IbgAf0WLqks4huYGfL/UKzp3PiZ9PeHvqTd2cHZIbwP+bn7U98bP2T/ys
4yF+1vETP+t8iZ+VPsTPSk+ic67X9MzvnrgpdA4CP5ScO3la6BwEPrvChM1j
Q+cg8K9qH/vmmtA5CPzGHh2OZYXOQcUX9Sk7LnQO4mepaoGekD4HgfM5SO1N
lM7av4nSWcdjonTW8XtROut8vSidlT5elM5KzyTrSTuuj+p1wAcNiep1wB/Y
GtXrgI/uFdXrgFdrE9XrgDv6pPU64AVWRPU6/gc6U3ulM/WvdKbxKJ1p/Epn
mq/SmeijdCZ6JomfTQw/mxh+NjH8bGL42cTws4nhZxPDz4Z/p/bMzyaGn00M
P5sYfjYx/Gxi+NkwP2NcMfLZxMhnEyOfTYx8NjHy2cTIZxMjn/E7y2cTI59N
jHw2MfLZxMhnEyOfTYx8Niyf8f0YfcPG6Bs2Rt+wMfqGjdE3bIy+YWP0Dct0
pvasb9gYfcPG6Bs2Rt+wMfqGjdE37H/rG5k2Rn+2MfqzjdGfbYz+bGP0Zxuj
P9sY/fk0OlN71p9tjP5sY/RnG6M/2xj92cboz5b1Z/QXYw/aGHvQxtiDNsYe
tDH2oI2xB22MPXganak924M2xh60MfagjbEHbYw9aGPsQcv2IP5fjH/Dxvg3
bIx/w8b4N2yMf8PG+DdsjH/DRvk7zV8x/g0b49+wMf4NG+PfsDH+DRvj37Ds
38DfY/x1NsZfZ2P8dTbGX2dj/HU2xl9nY/x1p9GZ2rO/zsb462yMv87G+Ots
jL/OxvjrQM/k67dMuvDBtuV9/Nx4fsHXAvl5/o27elS7sKTi3/3ScOMglT9F
Fff6fNEvWX1K0o0zxwN+6OU3x69QuZdjCJf1ym+B9x72y87B6f4t9Z+Q3y2N
U7/Xdf2yFtd5pf3Ob7xTvFNqv2P8wI92bPbwp7qviype9/yGTdZ/OSAp41F8
wYj3+69Q+ZPjAf/gzrVn3KNyJscQrvOifnRe9N2EjNPSODEvS/PS+WJ+3Xo8
Py+R2nf4HT8rtm44eqrur6KKd3qzTp2b14xLYL7AZ525O2O6yoEc7W9WpWoj
03pvjiHcw3ypH3zX0neTmC+NE/xhaV7KNxjvnVMmdGocmi/wYVeWbzI5NF/g
tXqNXtMyNF9d5zw7KD1f4E/1rd+0UWi+hOt8qR+dL31X50vj1PnSvHS+bh8f
8yqMf6Rn1xA/A98679m6a0L8DLzI7D/qbAnxM/Anyh298rMQPwO/etCIbveH
+Jlw5WfqR/mZvqv8TONUfqZ5KT9jXJkPPnbX6pR8wLyAV6k7MctLyRnMC/im
ffc/ndbHcvRnwTw7Oi1/CNfxU/86fuAvX/fuY4FejfHTOHn8BuPHegGXfnhe
BvOi8ZuY8QPXdQEudOB5of8Ejd/w+GVdTAy/mRh+MzH8ZmL4zcTwm4nhNxPD
byaG30wMvxnmN3wnRp7YGHliY+SJjZEnNkae2Bh5YmPkiY2RJzZGnliWJ/h/
MeeFjTkvbMx5YWPOCxtzXtiY88LGnBc25rywMeeF5fNCzk0bow/YGH3AxugD
NkYfsDH6gI3RB2yMPmBj9AEbow9Y1gfwd+hvpKdZ6GmYF3DRu3RewGP0N+Cs
p6F/HT9w0Rs90t8s62/Q93tetvKxlSm9F3oP/l5swoaWgV0clVdl/ZL1qiwP
+A3/H39PPhKMZ34C/eDvVy2cdHegb8NeQPtjg/cueSfVP9rjZ+9eP/61JGUn
gn/QT6dW33+wQu0OpSf0WC8qJ8v6X3wW2DXjlP7o53D5O3YFdgTORfSze3eD
X1Lj8aJytaz/8Dv1xwVyCe3RT8fe9x6cErJTlC+WjL0zvL5oX+Wuh87y1d6B
fC7rX1pp8Yxr1N7MMdRe5TWN00Tlufaj7Wmcagehn5fNUxXTfo9jug4jJ/5v
UkB/7COimyF+g53iRc8Lpb/yJ62j7mfiNy96vpT176k8vGJgX6M98ZXaX+jn
mhbXdR0S4n/ic7XLiG+T0fNL+VzXCfSpOuHBU4E8iZ5rKTs4/8YpD6b9Idq+
zry2z7UPyUO079KsVrHA3wK7GO2zC2S9EPiNo+dgKb/cXYE/ZEACfEjrpXwI
/IZ+x48Ecgz2MfCovZyjfqmbn/v51a7qX0rvS+mHzlNtr34hGr+JnrOl/Ce/
Gl/2c5XnmZboQ+evzjeJdSf5oOtO6+JFz2VdF50P1uHMt54/GMQ10A5466Zm
ZIBH5VhR/5VPHL9hfdF+6KO9BjYKne9ov/Aux+dYX/w9d9XWiY3T+1T/38gy
b88P4iBReVXUt1XdvsP6ov3tDUbdGMR9onKpqL9sgNvvWGe0j/r9crT9XZ2j
cobGo/5A4H12V/hinPqXjhn6rvIDzdeLyhOdl/ID0VPPdVovE5UnSmf1o6F9
oZ1XfBroS1G5oetoovKhqD83y52D0fNRcZUDwD8e6Pw80fMxw/+gxdJ/g3M2
6h8r6h/e6PxF4Cus8183XfVkELeK6v8Z/lUVj1YLxRd0vaZVcv6r6DmV4c/8
eF79wB6J+s2K+o095wcDn+D/PbCsQ1Y6PphjiB80zkf9kB2R4Xtvd/4trbec
MDRO5RP6rvIDjZ/8bEo3Ez0XlD667rQuuu5EZz0vFZ9Y9vFAD4/alSe8I1XP
ahzYTVG/fX5/7q8HK4zVfZGZ9pPsHHT5NXpeZCi+tdje29L6UlHtv9j+IC42
IBH15+f3v35u3T1jQ3IAf3+m9e13rTrNn5//tH2N9gt61r6qU0ieo/2BM3r+
G+gzUTtX25P/X8dD/n+dF/n/lQ5kF+t8k9G4gNJT1xft2xTed1N2+py1tC4q
z8HXs5sUrbYipbdE1zHXW1uoZKFE2n+u7ct1L7evc+hcJv8DxQWOeXtGnvi5
S+hcRv93Fg/iyOOSaIef1fPyBNLnMvBpu7PeW6Pn/jHVB0ceLvZxoP9E4wjH
KL6eo/398/kb+xspvx0z9F0TXV9tT/EFnRf7N+DnobiD0s2Lrq/SAfq/pXWh
eMQx777m85cF/gq0x3cfeXNe+SCuF113XUeVn9Se8h9yPDtq2XMLQ/YF6IH2
4Ae0b7A/d8WnIT8S6P54e3e+gP/QfnKru39cGLIXyC9E+RI53qXnFDseyHNa
d4N1xzoSP1C+hH7XUHv0Q3kUOV6Lic03ZYf8V5hXRg2nV0TjoUo3L7of1Z9G
+RU53qPvLC8axJFpHUFnPTeBS3vepwb7lNbR8Dpi3tjv0Xh0jpH58j412Ke0
jua/1zHX9D3S6vupKid1HQ3WkfajwX7E79Se9yPa8/oaXl/8jO7rTKWz8C3v
R8w3Qetr/nt9c82K6+d1n6J2rq4v1ov3I9ZL1xfjlH1N63vC4DwlOWz+Ww6f
MCL/Ka/jmPlvOXzC4DwlOWxi5LCBHCZ5a/5b3p4wfJ5SP7S+2p7yQHT8JG9P
GDnfKT9E6UPrq/NNkrw1MfIW60LrqOtiSC+10EtJ/7HQf8g+smwfqV9U9CKy
jyzbR2gPfYn0VQt9lewjy/YR2ouew/aRZfuI5CLbR5btIxoP60s2qi+pfWTZ
PqL5sn1k2T4ierJ+i/Vi+8iyfaTtnd7L9pGNsY9sjH1kY+wjy/YR5rHj6bof
rD7dPrJsH2EesNOj8iHT/t6j56r/sI8s20don3FW1a3/YR9Zto/wXdjjZB/Z
GPvIsn2E7y7buGnOytPtI8v2EX3Xi8oHHT/bR5btI6IP20eW7SOis9pHwMWO
pjhO6vvi7yL/iYX/hPwkFn4S8odY+EPI32Xh78L6or34H3R90V78S+z3OG1f
oz37u9Be/Cq6jtSe/SE26g9Rvwfmxf4N0EH5gOar9hHRU7+Hv4v/kOJQui7s
V7fwq5M/38Kfj/VCe/ZbUnxB9S60Z78l+ocfnvyWNsZvaeG3JP+8hX+e/JmU
/6N+dQu/Ovm38V32n9uo/1z9mZb9mRTH0X1OdGN/OOig9hGtC/szLfyZ5Ce3
8JOTvxrrqPKT2pPcPtci7kNxHIs4DsVrLMdr0A/iO+AftL985aDiYXsK7RHH
wb5Ge4lHeNHz/VyLeA34RONaEmehuIyNxmU0/mIRf6F4iuV4CrXnuInluAl9
V/kH7at3/Lpi2P6ieal8ITp70XNc6cbxDot4B8VHsC4c77Ac7yB+0HOc4ilk
f5X1/yk/Zk0oX1Hby3w9Wl/Em/TcpHgZ2Ttl/Z0jPhwWytvUeI3wlUd0QzyR
/AOZ/k1vvjz43TQ9FWf9gfzbrD/40B+i9numf8ahP85L+xNyFJdzn+x0bc/n
u8/nO8Uj+HzH+E3U7tb5kt8s0xe9i9Yxw2/32tL3Qv4HPZ+35Fa+7XQ7VHEv
andoP7p+5Och+y7XE3uT6JnrTT9Q6Ghar9bvw29GdlOuJ3Y60SHXe2PwrivT
57L6H+CvUDrg/Ci6PBynVr8q/CRKH+D1h0Tiv7r+sPfZnpT2hvQS+Jc8Ps9k
PMTPuUbmRXyVa4RuvL4W60vxBcvxBbJfOL5gEV8gPrHgk+j5m2ElLsD8g/bs
/7fs/yd7k/3/GL8hPsR8TfR8zLASlyF/YKaFfKB9bbGvaf8CJ3+X9qP8T+c4
5XeVtRLXJnqWtSL3lK9IL6J8rbJW8hOIDmWtyGeW5zgvDMlhnKfyexG/XL0f
6s/sXc7/6PZ/7gz8Bj9t/F+RF38tZoEfrfbJ5EA/ufKRVlUbZJ2jeON9k68M
4rz4/ev5Ga0HbT/bn9t/RdOjdaYmL7y99f53h5VQ/JIG+2oeTuH4LvCPegyf
X6XiMNH/13vA/5xhylRK4W5e+wzw8XO3X/J7qh9Hh4IW+OKzv7z6SArH+IFv
2PjnoAqh/jGuTi2eLBbIGYzfrVs+/5eez9wR6FcYJ/Cquacad1E7Yr0H/JK/
ZpQI/FoYJ/BpW8YVD+wgjAf45pPm+yB/Cd9163zYq3Zew/sD+wjjA/7E2V8+
0Ujzr4oo3rvcY/4Daqes94B/cOjssfepP2qfAZ7zcPPzstSfUNAC77Ym6QU4
xgl8xKr3O3fUPKgiPvp7alv3+9eG+AT45s4XvL4yxA9O3/jb3N1309M3r3k6
gXkBLzD1p4dbpnD0D3zckFr7tn7ZI4l5AX9u1erem1I4vge8ReLKqjel+sG8
gN+f88ymAMc4gU8o3O3EF6H+8f8OHCp5alWIHz7sMeG+A8VL2eFrDjyaCPED
8Fsa7W/SLcQPwLP3PFu6S4gfgLco/E+dxiF+AP7lczX3dgrxwx+5j11bYm4Z
u++TDdc1CvED8Bq5XdtfHeIH4J2WjVp6X4gfgGf9c9GojiF+AD768u9PXh3i
B+2//52zrwnxA/AFDb7o0CHVj8gBn+QAj9/H+KUfxaUfHr+P8aM97V/sd20v
48S8MF9f5sV08IkOHskTyAdD7Q3RDf1j3Q3JK8g3S/NieoIO4CtL8hDyU9vL
umN/WaKz4iSHdd8Jv/kHZjw1PCvNh4oLHzKf++Bz0A248DPzvw/+B30I1/0G
fFP3Pl82Tu8vS9/l/eLTflFc9qnyG8lbfFfxi6uf+V6j0Dri7yIHwD+G5LyO
k84FnCuKX/FUhR7BPiJ56EEeYpzARS6xPPQgD9Ge5LOOG+1F7kFOQn56IidZ
rnokVz06L5QO1D5Bchj96z6i8wj73dK8WD6DDrqP6LyDPNT2co4kwQ9EZ8Xp
nFX+x7zl/NJxApfzjs9rg/Oa1sVgXei8Njivad1xHuH80vZyLnu0LobWRXE6
9z06H5O0LmhvSE9A/4bWHedvgtYF82L9wZD+YOl8h1zS9qLneLReoLNH6wu9
QvVM2XdW9p1HcsBCDpBeZ6HXgW7ARX9jfc9C3yP5AFzlG3CRMyw38F3WDy3p
h4qLXmpIbkN/UPkGXOSqjhP0Fr3XI/kMvYXlMPQclW/A5RwxpP9b6P90jluc
46T/W+j/pCdA31D5hvai5yfoHLd0jitOdoRH+o9H5zjaJ8nuQP9J0hOgXxk6
xzEvtkdAhwTpCdDfdJ3QXuymBJ3voHOC9AHojaynWehpoDNwse90/MDFHjRk
96Ef7R8//1eg4rbV2Z+rngS86m39igT2MvQS4NWPHZ4W+ElwfgN/4NYPvgr8
tMDht362+IGKy7bm6nmM9mvbvjAr8DNA7gM/80Re/4prfvuhU6l/v6ncRPvL
285oFPgTIF+oH93n9F3F0f9ZFfL9GowT+4TmpXxJdFAc/Xz7sxsn6E90Vv0V
8u/Klo/WDeKwwFX+/bQuEfiXQDe077vr4MHAPwAc7dsO6dsgnWd1WO3lLz9o
MC1oD1zl0MCR68N0Q/tPW7nxAEf74r+58YA+aF/r6b4tg/6Bo/03faZ3DfoH
f6N95TPm28C/Bxztlw64b+K7If6hfpQ+kEOdZ4/eEqK/D3lz+YgTJ1ekx+/R
+JVu6Ge4t31TiB+0n1ZNG+0aHKIb2jdN/vpQmH+I/ko3tL/xTTdO4Ojfe8mN
E/xD6670RD+rFuUvvDBNH4t+5ueuyBocoifav7RkVcMwPSFH939yXnbQHnSD
3F18w8VFg+8SboBj/dC+8ghzOPD/q34p/Q/7/cpXAn8s6In2mdUvLJD28ytu
gIPOaF+hatbUhafjBjjoj+92LvNKt/R9z7/1/J91qxs/4QY4zn20X7d/dKfA
f4t1Qf9/57p5gf5on1u+1ZXBeAg3wLEuaL+iUpnu756OG+BYL+pH6UzjVzoQ
PXX8tI68Xyz2C+0vi/1F+8JiX9A+sthHWC+0H1zhyZf+Yx9Z7CPaFxb7gvaR
xT4i/rfgf9ovFvsFdEb76t3+vHTI6fvF8n6hflg+W8hnkucW8hzrReNnuW0h
t0nOW8h5ktsWchvrTvRnuW0ht0nOW8h58AmtO8tzC3lO8t9C/pM8t5DnpG9Y
6BugM/STXhUe/GhQSC6hPfQN0BPtH6q5ovuKkJxBe+gVoBtw0RN0v6he1Gv3
XYNDcgPtoT+APmi/q4r7LukJFnoC6ABc9CjWB0AHjUdS/JTjEX5MPAJxWI17
oZ9o3sV69e82X353/1XpvE2Nz3IcHP3HxC8QX9b4NeI2l1cL7u2OTGKeWM/C
l25oUl31ec1f8jl/ieKhGmehe1Wcx4V4ro4H7W+eF9ybnp3AeHCOLdnmr1l/
WtxT7zVovJPuZVA89IS3u/9zFydD9zGBI1+U8vp8zutD+7Lt/xoV9IPxo/3Z
DwX33NPjB79P39GxV9qPfULjY8duaXU4yKelfGnEYake0THvgjY7xwbtKd8Y
8V+qR3TMKzkjqDOQXl/ss2VXbvktVG9K8705bx/rGRNfRpyU71UY5mfYeVOq
fDZsdYif0Z7z6tF/TDwacVuqQ5hjqlwY1IuYr/PFd58cVbRJin+YPobpA7ny
8aXP3b1N/XV6v8ny/SaKhypdKG+W73khnusR/1jmH5yDdzZqvezzEP9T3pry
P+XdUd5vKdu4zhttVoX4n/L9lP8pX5HyY0vZoudX+GhViP/Rnvevnv8vNu/T
I8T/6K/kc/XWLgnxP8Vhddxo/+2cZQ8uCfE/xX9ZvlmWb5D3Z/fPPRCK6xmS
t5rHRXIS8/JJTiLPUNvLODmvEvd2NQ8K7YUOnJeIe82Gxu9j/Bgnyc8k+ang
/zfkX0KcwtB6+Vgv9E/yDfT0Sb5pnhjyWKJ5C/vUf/bl/KKXTQnVwUB75BXg
/Eb7LmtqDw34GeMh+abrQvLNUDwUfmyOY8KfnyA54EEO4LuYn8iZBMYNHPdl
OI8yRh56kIfgQ8L5fooXvZ+ics+LkXseyT2f5KTSjeSkofFAbjP9DdOf5Kfm
PaK9nF98HxP3NXRfoL2cj3yfEfdZDJ1rBuca8S3kqu4L8hsbiivBv23oHLc4
x2nfQe7pviC5R/ebNI9d1xvfn9/igzfD9WHQHvlm2Bdov3folj+mh/YFyT1d
F5J7hvJG4P/kfA/4gVk/tFH9UPMVkZ/J+q1l/sc8oN+SHAbO+YrIg9X1Vb6r
tjTjZIe3E5DL5N9TOYv2dQdd0+TeHgfVfoH8F3uB7R2f7R2c//++MOfHpVvZ
Di3vf/XvsCYb/v5Z7UTyW7K9A7+o6oXAE08t3H5Pj4PaHuNp07xmkXSdlr91
/cXvqvuH+lG7Cf2IXWbIzvLZzsK8Oo5z843as+X9Oc33nwzmC74nfzLbWfBX
qx5A66LtNW9o9LS3gvlG5fO5/qbS5/85YeB6zeuDvBH9RPMSsD7fVjt83mqt
u4v7R6V80YvUX432nx8Z2i3Q6zAO+P1e2DH36pdT+idw+PGGmHV/BHopvkv+
PcXJj+qRH8NnPwbuAQw66vzVUb99Uf/c8o7Oen5H/Y3s3/DZv4F+Xqvh/OpR
f35Rf9xxx1fgQ+Bjqv5vWNAecgz978/tPzxdH2Cf+nULPtNmXQg3hKudQP3o
upBfV3Hyk3vkb/HZ30Lz0vZEB8XJz8x+GJ/9MLQuJhp30HVUPwzwVlVfaLM8
1R5ykPhKceJDysPUfF2NE2EdKl9z2ych/7/6e+G3BL+RH5X8zDnej9OXLA7F
XxRffHNEDqhf48YKjg7kF/XIL6rfFf8w+Z9zvJwp1y/d+HfaX6d619y88aic
RD+v/bytbDoP9rC2n/9nuXuCfijvF/nSGqenflTukZ88Hb+P+tXJj63jpH50
XoqDbltruf1I/mH4/9WvRfEC8m/runjRfnQdVd4Sn5DfOzX+a544d1OqH+Ir
A74CTn5y5isDvqJ4h/nveEeOieE3A34j/jHgH4p3mP+Od+SYGL4yMXxliK8M
4co/FAdhPsF4dN1p/Mw/JoZ/MH5D/AB6ehQfMf8dH1F6Mp+YGD7BulNe/Qkj
/jHlE4x3VpcJJVaGzl+0F7+c0hPtl950wd0rQucv/N44Z+lctjiX6ZyFf5vP
ZcQR9Nwk/zmfvzbm/LV8/pK/neObluOb6Cfm/LUx56/l8xf90zmrcQ06lw3h
Hp3L6IfPWcQ1+FxGnEjPTYqb8PlrY85fy+cvxVk4Dms5DkvrwuevjTl/LZ+/
xFd8LoMP+T4X7guoPNQ8I6fHmqi9fK4VPZbzNBCnYDsFcQ22R2yMPWJhj1De
COIdbB9Z2EeUH2KRH0J5IIi/qFyleI3iGI/YC6SXlrdiX7C9Y2HvROOS5W3l
uR/NDPej9wEl/4TsKQt7KnqPRu+JqNym73JeCuJWbE8hzsV2k42xm0AH/S7F
v9iOw/g5H8YiH4byXhCPUzlP8TvFiU9Iv1W+YrsM/OxF47PlbdcfnH5F+TYW
+TZk94HfdP3UznN2fZL2EexBE5Xn5X35riE+hD2rfEL2L/OnH8OfPvGnIXvc
ROVheV/40xD94U/wKF7pc7yS/Am8Lj6ti095O15UH8v0J3/3Rr9Af8N+R/vc
R/Z8ckmXnxSHffF45pnfB+tC5xryiCj/IdMv8qtbd9CN8pRI/8/068y9rtry
rel7iWhfol7xrqnxKI7x9DpraN9ALoHOlDflRfWuTL/VRKfXYR9R/4pT/3zu
II+L8jcy/W8aO30Y60J5YqS3Z/qfTXfzBf8T/RUn+iufww6VvAi6n17Eb3OG
G3+0XkFBf0S1P8fXS80X9Ke8JqUz+vko81jxEJ21PeWHGMLpPrj2Q3UDCvqT
91S9NhgP6EP5YEoHmhfnh/iUH6L2LOyOKK72i+Kws56q4c79qB673st+cdVb
wXcJN1G8oLaXfCSPcAMc9Md3K52KnlPop/dYJw8JN8DJvkD+Fdkdaucqju9+
WiOsNx4z9F3G8V31k1NemUe4AY71xXeL/BWV/0RnxkFnj/gfeUFkh2bYq8e6
/U78b8H/tF8s9gv5zZCn5EXt0ww7742ovkF5UJRfl2ELz7ikVYjO2l74n/ed
pX2neVbYX1F7M8Ned5s7p2h/oX/ej+if/VrIE6M8vQxb7Wj0HKc8NMq7y7Bz
Jrr5RutyKP15X1va12o34fyi88jiPKLzy+L8onMHeVN8jlg6R7Q95d8awvm8
QD98vlicL3QuIN+M5bwlOW+JDqznQL9ifQP6MNsX8JNrP8CXlXNyD35w/L8F
fz84N9AzEa8HXrqA4x98F/2cKOfkCex5aq91Oah/1vcQx0lG/T96bpLfRs9f
E/Xv6blP/hPVN8jvoXqLifq7VF9S+uBc/uI5J4ejfq0MX/hf843Q/tax7ryI
+qkyfNlfLB9wPpqo3ynDl/2udKb+0/d4pb3IH82joPGTvyjDF/nG+xf6g4n6
fzJ8kbdk/+7zerXsdcElOv50PvMTe+a/GfQDutG5wHnLOEcUR/uer63/d8aR
Pcqf6P/iek//G8g90Jn8qGo/0jlI9uA+77kzJ2wJxhmNR2v/yld0jnN+Ms59
xdF+4lWj+846skf3BdFH+ZP852pnkd6idcPw3TpF3b4DfYD/dbaTV5gX4VS/
VPthPoecJ7+9nhfMtzinyP+p5yP5sfWcZX7D+a58hXNk7TBn15PcsJAboAPa
73nR8T/JEwt5QvYI5DnLGQs5A3pS/x7JHwv5E623o+M3JJcs5BLZCzjvWF5Z
yCuKj8OO1vdEYL9f/fvQAvVC+xR4nTHesItD+5Tsd+UrtD/89SvbLg7tO/JL
6L4DLueF7jv002TRW+9cHNp31L/yD/l5lG9p/F7UH6j+Ky/q9zvXyjnI8WX4
5dQuhZ2e+PT82yZpXlxBtd835zSbHuQ14Xf8P8nT0Lgpfm7Pe596egK/49y5
aUjwLuoUvf+LfiQ/RP2/1E8SOPXD9zdxb1rXBbj423VedI9b6QZc/Pm6j9Bf
i4aZjYI8ENAf+OVFpz4b+P8xHsyvUscv10wO0RP4Ha8eLDMtRE/8XfLBmJ6W
6Qm5cXhT8J5vmp7oR/LQmJ6W6Un9KD3pnqbSE7jkD+j36N6o0hO45CcoPfH3
qgPev+jTED2BX3Ffk35+Cqc8H+QHqv8WuLTn+56o65KA/o/28l2+L4k6MwnK
d0LeoOo9oFOHATvrZmu93CLq93iqdNWf14buOWJcku9K9Q8zfKwj+kf7Ds16
V12Z7l/x8RPf++7099e0H73/Tu3VTqD+Sa/W/EDOo0PendIZuPCznivAhf+V
DpTPpusIXPYR1yVAPZYk1hHtZT/yvX7Uh+F8TuS5eURnS3RW+w50Qz/4juTt
U33pTAv5RnxiiU8UFz4xJN/QT5L4Cu11Hal/XUfKZ9P8QJwjIs91vYCL/Pfo
3PRxbtJ5B/uI4xfwD3t03vk47+icgr3G/nb4vakuUFG/3YBDDWYfScdDKc/E
Iz3Khx5Ffg/YBaxH+dCjwMfov+DBi5fMPJKOMxJO9qPmEXmkR6F/9kvAbmI9
CuNXvYHoQPXw13sxerIXoyd7MXoy+iF/e46Bv5HsIAM7iOwXA/uF8lUM8lXI
vwec7RT0w/YFvst5HRgn84+N4R/L/IN9BruY4gLQY9kutrCLiX9sDP/YGP6x
zD/UP/vtoeezXYzxM/9Y5h/oifCTkF8F+iT7Tyz8J+QnsVE/ifpVoCez/wTf
9UgPh9zwSB+GXGJ/Kex3ypNRv4Hswz/l/xXyp5o6U73cA3LuHFF8w5iyf1R6
Oe2PIn8F5Z+on8RUztr9RaebSlv0s/zV7WuD/t/pMHFV7QZlFK9Zb/ugyi//
rOcd2dEqn8k/wPEv2EeU56N2mc53YoMpB3+cXtw2e+23yX5ovsA3DyjzU+XQ
fMkepPwZtUN1vuin7Inpn/mh+QKvUWnbw1XS/ev9mAp1Vu7a8PduHY/7TgH/
+l4jt7/YPl13DO3Xlqx6/8ZUe/SP9sPalb3xpVR7GY/oFbu9+2/KahGMJ3of
Z59X+YXeI/qM3iP7Or+237b1gd71D+M9iz8N8IeOjqoY9BO9p7PPazT++emP
pvrpuWPp/owpuOey23vgm1snXHJ4P9kjJe3tla68fFNovosfK7qzf4+zbGa3
uhVHh+aL9jOKv7xoU2i+aP9Tu0UvjA7N997k8gXD9pSzlb/te6MXmi/2fa0X
3TgxX7S/baMbJ+YL/Ktha87zQvNFPy1mzfygd2i+aL93x9XJeof3q98K+/TJ
zR/2S997Oqz8e6j3P5v8dB6U7uumu7ZmB/Yg6ID2Kwb3GP6pvk+qehT0bUN6
EfTztP9L5O4leXVW0+MBvxfKq+OaHg/aT5g3pNH00Hg07tQ8+5Xs0HhIbzSk
b0PP1LxMzPe+SWVqB+sS9S+V9Ye/VbRhal/o/TW0Hz/oROmAb6N+pLJ+t1Fd
P0m3z1C9qETr4H2Tb1X/gH46/OortqwMvRejebw9zD3JVHuMH+3H9S49f5m2
z1V6fjPWjSd6vueaD+YOGrkxNH60LzF078nw+NH+0rHbMzedPn7L44de/IkJ
6lGfNn7L40f7e0fPahmM/8tphT9a+i/qD5f1X8l56M2CS741X0X8gWX9Oj0e
eiXw08p+U3z4gP1X5U+1Xx2x088N5HfjQG9fHbHvyvqtDr2UV99+q8gptC99
/NGqdbP2e5/m/f6z6tUNPhzav04Kd1L/syzgE7oVPGvjZWuyvnDttY7soj/O
LlogNZ51ET9kWb//w27837jvKp+809NsD9qvjfgHgvGPaRTYL8DRPrv/vLJB
XfqlInfQfkD30Ztrp8a5wdFT8WNZ968J5gU6Q7+4vNSRH59dt9IDnYGfPWdY
r+CeAugM/M6BdesMS7UHPYFXHZyd9+5Dtpx3wJ9umu+z1V3WGdAHeIcOK5NB
P6AP8Gvect8FfYAfuar97cE4QQfgp4oPmB68v4BzEPiyTs1XBt/FfOGnGr4l
X/snztir8wW+Rvy3mC/w6gdXTeibao/5Aj/nRM8ZwbpgXsA//rlevX6p9pgX
8Nrij8W8gG/cNSE7aI95AX/36cp59mZ0X2T4fwxfvLZfaPzAXxM/eXRfZPh3
LxxcODx+4EtunZ3n34jybYa/4PX9U/uGxg88Q/znUb7N8J+edOtl4fED7/D1
7duTofFDfyz0Se0vh4b4DXjbZTnHvC7riP4nvGKv3lfyyRC/Af+rWMbHwbtR
Ufqf8LJb/TPnyRBfAd877dV/gv6j9D/hnVVk3NVDQ3wFvO7UJR8F7zRFx5/r
dW2V76OMkFwCXnP90kLjQnIJ+PX+gGYFQ3IJ+K7L6/QP3jWLjj/X29RyXplC
IbkB/PGNrv/o+HO98zdt2VsoJDeAN002yXtHDOOHvnqq5d81Ltq7T8cPvLDE
xTDOfOl/efIT8hDgshFf76qzd5/KQ+CvlNlZ89Ufs1UeAl/j2uu8gJ8n8SyM
P/1ZJ/cgx4D+5cbv0bqYmHUxMetiYtbFxKyLiVkXE7MuJmZdDK8L7LOYfWHG
/nrfdcmQHAYesy8M9gXkMPAfHP8b2i8mZr+YxUfcd2m/mJj9YrBfovbICdPG
7Ws63zNsjByzMXLMxsgxGyPHbIwcszFyzMbIMfvfcizTxpwjNuYcsTHniI05
R2zMOWJjzhEbc45YPkdgr8ec+zbpzk0+923MuW9x7tP5bmPOdzvM6QN8vtuY
893ifCf90MbohzZGP7SsHwKHHkj6m43R32yM/mZZfwMOPQ3jV3+L08d0/MB3
SNwT4wfe2+l1rN9ayGeMH3gjp6/q+IEfkjgmxg+8mNN7Wf+0kMMYv/LRjr0/
1Jz3nY6/rNhBO+S+AMbzhbS/745bC5+fao/xoH1XyWNHvy9VrPP1hK5n+5Vm
vFV1Q7NFyp/p82pir7PazdH5vijtR37VqOyXqfboP93+wxrffDNX+Uf8Hn7+
Lx596MdSe7T/WmKfXi11ukB//Oz5yebfU/P18N1XpZ96v29otT/VD757gfST
LXW0QOdF0s/2x7pvuCDVD8bj7MfC/oGdD3xzxqm0PJkjdtW9Um8N42iY55c7
w+9T6eBlwfkLfsDPWavOfjOIS2KcZaT/h3Lvn1jkVFqezJX+r5f6aRjnFdL/
3z+W7Fc31T/4YZX03+Sm7HlBvBLjd3b9SW/Y3OebzuizXsePuOLRBfNP+l12
KN1qSvtCv+zqOy3VHuOpIe2TExZsCdqjf9fPIe/5XgeH9Lp2m65rU7FrWz+0
vd2KLjuU36pL+wI3VKvaM9Ue/TeR9lNf2PZs0D4qz5d5J0kv+qmU87ejzqHq
RZLvWuVA6ci+21bK9cN6ziHpB3UFQc+/Srl+Kr89M7K/1kh//Wqfu+6C0P56
Sez0I3KfUfeX/Gw14plfa4b21yhp/6Tc+0P/zv7+x2RMeuW97ND+Wqt62cai
v40ao/xzAO17BfW00/srrcfVT43/BR2/+FFtoUvPXLY/tL+6i7+lodQVBD9/
JXz36fTpZ54f2l9/ST+/dXpw1r7Q/uom/ayQeoDgW/z8KXH5TzVD++uJwxed
arPlTFtix+gbi4b21wHxQ1STen0Yz53vJs/KLlLMPlJ16o3h/fWZrNsc2l8D
pP9rd7945hmh/fWz9F9M6uxhfHdL/8t+Tb4Y3l/4mUX768Q/fXZ+ObSU3b55
jJkT2l8fSXz+zMcKXZUd2l//SvsjX/zUZ3Zof6F9iY4ZxbND+ysx+Nblv5cv
a0+Oe6vFQ6H9BT/Q8glDq3mh/WWkvR393YEHQ/vrT2lvP3nyJi+0v548VXdq
uYXn2AsbtSwe3l8NqY4f6H9w5+Nzbl5b3pb4blO3/3Xaq/tunuSdepe2eCIZ
2ndDpf9FAy9cF953DaP3xfS8+0367zHq/hl9U/2D7ug/efSrvsnQfpTx+xg/
jdOPGaePccJuGiL9zHfjVLtptfhn7lnQ9KVXQnaTzMvHvGj8fsz4fYwfdhO+
W82NX/lc/NZ+/9FXfPt2+7U6fq0T9XDpputTehf8Y29L+4PL638/JcVXwKuI
n3ti9TuOJlPyAeNcKO0zlw58f2Gqf4yzm/Q/YcwQm+pf/Vfo/4zzRpw9OdU/
cPT/dKP9Py1P9Y91ET736zVvfMbi9mt1XuL/9gv07/BCSv7r/kXdqu+Wdq5z
c0ofw/gfkvbXLal9IDhfgH8i/e1057XBOk6Wc//GLdtuTMk33RcnZTztlvxR
f1FqPFjfovDnPDJ53taDy5aBPr3kuxe776ocqCnjvHvYstqpcSZBB4yzgpuX
AS4//T5OPzFYd4zz0d6j7k7pOYbks1/n7DKLAvlMctiHHAbdmku8Yvmbv69p
GaIbfv7q5K3SbZHEMdoc3/dhIE9At4vk3O9974vmvRQ/gG5/ynhWP9lpXiDn
SZ77kOegz/UyngJHP1vdMkSfzdJ+tRu/0udjGc/Rb89p2yM1HtDnYhnPxNlb
yn2QGg/ogLjcynuDeumLdF88L3ma+WYHdajS+2KOtF+0J3hXYpHui+4SRzp+
3b7XPkzxA+b1lrTv4drrvhgp/e+Ylde/7otZ0j6zY954dF/0lP69zdPXv5/q
n/QHD/oDxl9S9JbXW+/LCvQWjNNIXOyZib2eC/gB+Li88Xzltdrf/9HgXMM6
4mdLp2/o71eJHrVc/EKkn3jQT6L+os+WwV8EOpwj4yyc82+eXoT5Xi3jnLrk
84cCPgE+XcZ574/9GgT6LdbXk+8+7uigeAsZ53/7kZYZ6IFR+/Erc5frn/VA
Az2Q6GCW/6d/7LMs9o+J3migN4JPBsh3Wzr6s95ooDfSvAzmhfFLPNOsc3yi
4x8m+bBFcjfXDfOz8K2ZuPmqb2eG5LzwuQGfY5z3SfuM5nl8ruN8WvpPlEjU
DvPzQ9L+lv1jSswIyXnhcwM+J/vCjHX7VOcl8VKb4/a1yqtmUodt6pOrI/JK
5JKFXCI5ZiHHsI5HRf9c4uSSyqtaMp6uTo7p+g4Tf9GF7yae3RyS8x/IdxPu
uyrHmso4L76h2pqwHBN5ZSGvSL5ZyDesO8ZZw8lzQ3au7e/kP9uzFvYsnY/2
+L4XI+ejnIMW5yCdmxbnJugGfbWLOwcN2cu2rTs32S62sItBnxoynsvqd4mc
g/iJ847OR4vzEfTBeK50eoLua+RHNHR6Bes/tvD5QV279L6ognwK0XNIL7IF
nJ6j86ok7W9y7XVfPCD9X+P6T5CeY6HnAF8g/T/s9DSP/DAWfhiMH/ez7OQK
efonxtlR8gH6/F34m30hOQ99u4/TJ1Weg373OL+NR3qshR5Lfh4LPw/ptxb6
LegwV8b5fo3L+iVDch7jvLHWA8v2huT8rzLOck7f1vHhZxNHB4/0Xgu9l/xv
PvvfkN94QupakB3kww4iv5wPvxzR0wc9if7+jeeczAnoD//8FZIfeobUtQBe
XvxjD0vdAPSD+O8S52/UdcH4+w5pckfgZwaO9m85f6ZHfkIffkKsF9p/trrk
45sOLsuCPYX+75X6EmT3+bD7yK/ow69I6+hjHYF3EvpsfvrGL8PrjvGMc/5b
XV+MZ2j7Mk8Ffm/gaP+S8w/rusOu6VL4umuHrFtpoudjaT/nvCHPDErhbAed
2WJuRA4An9bt7QWD163U9TomdLjI0UHx9P2zE9W/+WZuAuuCfrpnlz0n6Af0
B15sVf4yB16fk4X2iGvf4fzqKlfRvrfrR9cR7V97Zv9Zv78+R88jtH/FjV/l
EvAHd7S7NiyXgO919NF8M+yLhW5fKJ6eb5nAT6v6Cfq519Ff1wvjrOfiEYb8
Gz78G1G/Ykn/nT/uXxbcc8c6Aj+6vdmNhVLrTv4cn/05aJ+7sV/kvAN+1T/T
DgTxRKwj8kyrO/+J4rXF37tM7v+in7by3dXOz6P4VeJfLfRTnn9Vz018t1qv
RyuEv7uf3qkB/gbVV8S6ox/Ym+T/8eH/AY72J/9x9ASfAL/Y0YH9Vz77r9C+
ebsxkfMaeL4deeui97hBz3Pc+qp8uEP6H+DWS/FrhG6Dnd9bz3f0X/apdUsK
p/qPyvmi/hkDvTsuG7Tfi8ZZivoDpb5WVK5m+C+4OKCJ5v8U9ad+XaNAg0H7
lf5dJD90idzHB14L71Q6P7auS2Hck3okL19oGfDn5bvAo/K5qD/HfdeLyucM
f90PJXekztNl0fhOUX+s1LmKys8M/z4XPzXRvKCifkFHH10XjL/A23l+exON
G+b3x5x75cJgf0Xjhvn9W6aVvnlsaD8C7z/z3URw7kTjhvn9BeNzIvo58MKz
i35fMMT/wKfNyutf9xHyNMq7eDTJvfw+9HCsI9ovc/FuykfK77c9/7sSwXmB
ftC+ctFbluem5Gc0jpnfn+7GQ3HM/P7xWXnjpzhmfv+cysci/grgwxx9TDR/
Kb9/q6On8j/GU9rF/XUdgZ9cnJc/YMif78GfH7Vnj3k/FLt+2lOhcxD5sQ9u
X/FoYO9E46THvIJrukTsRODXzO67+unQOZit3y2Z8Kq/kMTvN0j85XkXfyH9
5Jj3ybadl4b7GSr5ocOljiLwqnIPYrrU84zui2PeWzdM7vpb6NxEPswql7/B
8QsP8Yvouud6lV7u+eqWlP4TjfMe8xq4+aqec5PQbUb/vkMD+ysa/z3mZd5V
IeLPAX7A0V/PzVU6nm3FUuuleRTXC92auTgX6TnHvOu7lWj/TOg8xfjvdfkw
lJ+Q4+2X+pbR/IQc7+jGarcG8oH8Pwb+H+DWzdfMd/P1onTO8TqvG7kv0D9p
vQzWi9bXYH2jeQ453g1SfzKa55Dq3zsyMJDP5P8x8P+Qv8g87viZ6JPjHV7Y
4ewgfyPq/8kxfzic8ohyDOhG8UeD+GM0ryPHHHijSOOwnw34g278XhTPNfVd
vhDT04CexM8G/BzNG0n179ob4mcDfiY6G9CZ4qQGcdJoPkmOGX7JJxG/HPB/
Hf94UTzXtHZ5Vkx/A/oT3xrwbTTf45i52fE5+eWOGcgxklcmRl4Zllcilwzk
EskxAzlG8spAXpH8Mf8tf04YPnfQ/lPXD63XCYNzh+SPgfwhOWNi5IxhOSPy
xECekPwxkD8kZ8x/y5kThs8d3H9C3J/0BBujJ1joCZTnYDnPAe1j9AfL+kMt
vMMr+hjpbxb6G+nnFvo56fMW+nzULstvb3T6A+vn+r4b6fNal5X0FvUfUl6E
RV4E6SE2Rg+x0EMor8NyXgfax+gnlvUT0BP6IennFvo56fMW+nzU7stvn3f6
JOvtNkZvt6y3I89tu8t/Y73dst4u9pqFvUb2nYV9R/q5Zb1d9Hkbo7db1tsx
Tu/a+Y++errebllv1/tiLm+Q9XbLejvGD3sqmj9T0lZy9hHb0TbGjrawo9k/
HGMvW7aXgYtdaaL7tJQ97vL92G61sFvJ72HZ74H2Fzl72Yvuo1IWfg+yc22M
nWth55I9a2PsWcv2LPCFjp4muo9K2Y4uf5L4v5Rlv4f8tMhzIz+VhZ8KOO55
rXZ+s9P82DH+K8v+q3T9POenIr+WhV+L/FcW/ivyW1r4LcnPaeHnJH+XZX8X
8ifht6S8Pou8PvJbWvgtyd9l4e8Cfo/QLeH8sewHszF+MMt+sDTdnL+L/GMW
/jHyg1n2g2H88FuSX9rCLx2NU5e3N43Yvvx/Ib0deZt8jwnt4R/GulBeKN97
sjH3nizuPZF/2MI/DDoDv+yR+Qf6hvR29MP3ldCe/bpoz/eY9H08157jIP7w
Q1mROAjwLDce1Z+BD3H0UX4AfnG/g33DcQrgbRz9PZJ7Pss93OvBORXNz9f7
QSaqN2b6C10eOMsZn+UM2vN5Afxpl6+u36V7PZSff8yDvh0dp95D8UiP9aDH
RvP/9V4M21ke7CzQJ5/82/L2o/ODczPtR3D/5J4I2zse7B3QAe2fOPXVXZeG
+oG+wX4k5PnD70f0wX0BE5VLGXaOu1/AfhvLfhu0Z/8b8EPuHgTzA/L8DcUv
LOIX0XFqXrpHcQGLuED0XrzmyfM+sthHtC8s9gXvr1sX1s/bX3y/snPG3Ly8
eor3+a/+XTgv3gd8OO4/3jowkieP+9PzSpw5wGu2iOO2PuK2wJE3Xu3BYaO/
aLbI4zgO4rnRvKZSfqW72kbuLyDf7LFLpz0cxG0pnusjngsc330568jkIP+c
4rw+4rzA8d3P78z7ruZ54v7370/f1KXn6fkMPvIZgBcTv9+JSx6L3IND/tWt
Dz+Z8R/5Bj7yDYBnSj8dWu/8MHzfDffgW3ujPp3VZz3Fy45497n8DRPVGw95
ld5e0jvIr6A8Ew95JsAzRT5srFImct8KeVMzv997NOif8ky8d1xeiuIXynfv
/274hiDuT/knHvJPgJeU797508N597AoP8p80O14Vvi+cCHxSxxqYfPGSXlK
5tf3NkXu5+aT9vXGl4vc88I9/tGVg3vxizjfzCDfDDjytLveGtxPT/Oz5KEZ
5KEBLyz2+NF9ry4K8wPydta8Ftx/T/Ot5KEZ5KEB3yvfve7Z4J5+mp8lP80g
Pw14Ifnucfdd5R/UIVjdesykh0/Pw7TIw4zyeSlbY3aDmeH9iLyOduetvKbX
6XmSFnmSwNFPg+xp08L7C3Ua/vfssFVTQ3wLvJLLO1UcedE2o1+jB0P8rO/J
Sn4s3ycy3z4RuU+E/JALD+X8NTnEt5Ifawsl8/JpFW8s311eutnkHiF+lrxZ
i7xZ4M/Kd799bUtEfsr4feR1Ex180IHlNsav+YHSz1Y3HtUPZZx+bZcHrjjy
fhNuvopDTibcPR09TyFXL3DyVvVMmZdf+YlJF+e+/qHmzyF/GDjlpfvISyf6
+6A/+oEc3pE1aeLy9UOXAofcBk509kFnnO/47p2OT1RfBX0OOvorDvo84+iv
+Gihz4HpefeeVE8Affq6c1DtdMlr8s9bMX5USj7TeVHKxz6ivCz/jC/z7gUo
/ZGH3MTtL6UP+hm98ZY/fnv9Q/V7ID8ZOPgW/U/ZknX3a6nx0H70sR8xr+PS
/kd3r0Hni/EscnJD9TTcG+ry+eX3TA+t47Oix5a9/+T69lNW6DiRJ8z4mXLe
1Zw8tPevoXnhfASO9a0u321Z6MUxwX6hezQe7tGQnPcg50k+e5DPmJfcr/HG
Onmr6yJy2FvSM+/ejeLIHx7g5LnuL5yDv1yfd+9JcZybH7nzVPdXhoyn+LN1
q7Xu2rUR8BFybgKne0Ae7gHR+eLhfEE/JeScnfVxtw8OhvbvM9I/cDpHPJwj
mi8k333PnYPKJ3sE3zIxj/6Kz5fx3OPor/urttCnv7tHpnhnoU8np+fwvTOD
e2ekFxnoRaTPGOgzWF+5j2YGOP2E18vErJfBehE/mBh+MOAHor+Job/idG/O
4N4c6WMG+hjxj4nhH8VJ7zLQuzTvUb57udMbeb1MzHoZrBfxg4nhBwN+gPxE
XnEnt6890qsN9GrQua60P9fdW1T6I7/3KqdvK31EzpgYOWOBQ36i//5Ovnmk
nxvo55iX3Kcw49y9S53v+zKeH5wdofIT98Kec/JZxyn3U2z3Io8t6BCSk8i/
ZRz6Vcy5oDjWV+7F2DPcOcX3fC3u+ZLdZ2H3kb1mYa9hXnL/137v7C9D+oaN
0Tcs9A3SZ2yMPmOhz5D+YGP0B8XpnrLFPWWyNy3sTdJ/bIz+ozjZlRZ2Jeg/
Sr7bw9nFhvQNG6NvWOgbpM/YGH3GQp+h+30+7vcBR75rFcHhx0D7MykPFnmk
8E/S/T601/g15dPqd+tInl59ud9N90B93AMFjrw7ee9Pv0v5fnzf08d9T+CU
v6f9I39P3vPle7I+7skCR75ZPcFBH/qu0oHyA/n+rI/7s8Apn02/e6Hk23wk
96DpfrRZTLi0N2hP92g83KOJ5p8s81r0cXnUmJfcX/aepPwQyv/he9ZmFuGU
f8L3azzcrwGOe0x7CvXJy1vGeKh/Xhdbj9ZrDuqb0foiLox1J/ojHs339O31
tI4UX2a+xTuVXN/AXk38L/vCYl9gvvRdQ/yM+DXXPbDZtC8o3uqRHLAsB6Qu
hJW6EB7ta8SPOA7iIw5CflHUW1O5jfa4j0BxCh9xCvKX+uwvhR8ecVWKS/oc
l4QfHvFfyh/wOX8AeX0fuzo8HDf3ETenejue1AsiOhzzztz82PZPsz/nvCMP
eUfR+R7z9n3u2lM+j4d8HsofM8gfo3gB6iMRHXIM7sFRfpdBfhfFEQzHEeBv
Rz4q5XNazueEvx15s5R3bTnvGvHZq109Os43tsg3prpzVurmaT/wF918Vuv3
loToD38R7nFE370qbWsVde3pHoTFPQjMC/7zJcWa3ZOyc1VPgL8dOPYd/OE1
Xf8cl/cRl8e+Q3sZP8e1fcS1Sc/0oWeSHuhDD6R4io94Ct2/8/e4+g+K415w
hx3XnBO8f0HxFB/xFLof55+on1ePQvFt0k+9d6v8MzXVD/ldPfhdyS/qwS9K
+X5eTL6fh3w/4n8P/A+8gOyvmz9enNUhtI5lpD1wysfzYvLxPOTjUf8mpn/F
o/WUjpm9Tg5w3rVB3nW0PtIxk+nkDOctG+Qtkz/HwJ9D/hYDfwvFQy3ioXQf
31Z3dXgUx73CU8vd+lI81CIeSvfl7d/r8+oCKY5+Hl9YKGd6iE9gXyDeRPEg
i3gQ38uLiUdbxKPpnNJ7c7Tfbcx+V5zi1zYmfm0Rv6Y6VD7qUAHHfbQ9Ut8J
8g3vGxQTvZ3qTUFvVz6he21qD0qdFh91WoDfJfdBqtWtsC0c979S7oNMvmfB
ogAnvQV1jUzUjtD7Econ50h9pK65efWRFEcdpOJfr+0e3I8D3lfGmeXqvSiO
ezEVZzUcGbSn+jA+6sMAx/2gmq694rgfVM59V+0sjHO/qxOl/Hm5tB/v6KA4
xlnM0VPxdhinoyfXF/JQXwj4EMFPCE76MOoaedFzX/O3lR9In1d+oDx//q7h
71JdI/6u4e9Snrnym9Tdsqi7RXxlwVfEhxZ8SPYX6vwwv1nmN1kXG8M/FvxD
/Glj+NOCP6nel0W9L+IrC74iPrTgQ+IfG8M/FvxD/Glj+NOCP6lenEW9OJIz
luUM1fNR+lPekUdyybJcIvuC5RLy1tgeQZ06/q7P36X6b9oP6p/7hKOOdybx
D9npJvrdIn4LkW84R1B/LNfZrR7hBnh0v6z3Zv7n/l1vgOO8eFP6b+3sdMYN
cBq/5fGj7nryv+dlW5DcJruS6WZBN/APzqNqx6J+ITqn0n4MoX8NsZdpnD7G
iX5ovah+6T7vL5FX5N8w8G8Azyf/ers8JdKj9nnPiLwiv4SBXwI4+lnn8qbo
3sp68/ENUX8IrS/dfy9iO4lfgvjWgm+j+X66XkoH1On/vkp0fwHvIfuL8lf9
hLvvr7jWOfitzZXB+3eUt+l3c3UMFBd5489c5ewC/H/0J/ob13PztxeuEqnn
tkTai97I9dn8r9bOz6vPRnVIfNQhofiCh/gC1QPxUQ+E/P8e/P90L8+MdXVv
qP7Az6b3Fjdf9NNS2j/h6vkoLueG2Zft9GHQR97psGIHcT1Ju43og3opYn9x
fUi7jeiDPBDU46L4tUX8mupiWdTFoviyRXyZ/P8+/P/k9/bh98a8EC9+psSr
O8J5aFK/xc++q+f2sH6O+kVCN5V7WwQX+nsUzzWI51Ic0yCOifEg/rJnSacZ
4TyiYoKXzWg4PWxXos6G8LmOB/gXbr/wfvRj9qOP/UhywO9E/kk6d+he4Xov
Rs54LGfw3gTkJMk98wzpgZDzNcgPT/LfI/lvY+Q/9AE9R8APBSXPEzjW5QLJ
w4z6bfZ5F/xyZESn8bvJP7PP+2V3w6c6pnC0h9z7fPBXizqG2gM/PvTcd+5N
4VR3xb/43hsuCN5nAQ6592upRS3C9xm1fa2Azt+n67ZI+9dz7uwS3NPkugeo
80N86DMfShzQRx0e4k8f/En1weR8SY8fcmn6/PP+Do9f6nSZZped/cu00Phv
lvblnkqW/jE0fqlHZ1GPjva15X0teSAW9eJov1vsd4wT++Lmp/o1CNYL4wHe
tu9ljYJ1j9ZhLupDTkbz8Iv6fQu48xrtiwjdbmncP0JntP9G5Gc0T76on/OI
0x/QHvUEWuYrHKE/9tHjP72S0Sk0fuA//Xxbic6nj9/GjN/y+IcL3Q6PeSdC
Z7SPGb/l8eNe1dHbG+XRH/4CnEv/vDvn4AU75ySAp+s5l+yeWNJlOfzdwP21
3Xc2zPec1hnX9rlrxwU4+sH5c1OHjmtq75yj38X8KtWcmOVVn5+Evx54rz25
K4J3jqBv8TsJ8C9r3usrzTcF7xDh3gL1n0BcAfQ+9MTzd09us1vrvAC//o5u
UydO26f3AYBPy+mRv0PjLeo/Bb50Xon29zbeou9e6LnU8IP9qX70PQngrU62
HzGpzW59j4Hz8eF/p/Z6r5X61/x4Go/672j8ul40X623TvTROubAizS7atSF
KT7Rd3FEfufLN/OtwseeS4CewOu3qb9s3alnlZ7p9q1+OzmgfwL0DNUxyCww
sH9S3xdR/N3M4TNHJUHPNH7o1YxjzyVBP77HAHpS+4S+xyD4u8u+KPJ5apyg
J40nAXrS+JOgZxq3bz2XGqfWo4/SB/wf7mf3v7NbLgc9IVeufrlXTkB/0BN4
qSerJXb9Ar7KVPzQOR+MC9YX9AT+xbG2uWl+OKHng+0zYESqH71nov6Ss6/N
DPYF6MfvkICe1F7fsaD+9R0IGo++r0Dj1zgQzVfvXRB9dL9rvbTNn9cO5Azo
CX/twCEv9Q3sKcgf6Nd9XXvlW7TvstVfHOgtoDPwl3q5d7VAZ+BV2+S9z6V0
Bl6y2okagb4EOgPPv+LcGwN/Wr7Iv/S7LqAztVc6U/9KZxqP0pnGr3Sm+Sqd
iW5KZ+DuHe13VJ6n65MP3Zni58agg/oFvbz9pfJH29+VJx90XWB/lHByRvvH
OVaZzgvgfF7w+zagj+ojdF5Q/yrfcK7OfLN1xymh8wL4P+O3/zApdF4A/73V
8Rr3hM4L4C+ZGYM7hs4LvUc1uObFk0PnBfDF1WuNnhw6L/jeFfiE2ut5Qf2r
fKPx6HlB49f1ovnqeUH00fMCeHN37is90/c3t57MbjgL8lPxVgfy9AelZ7r9
RQ3MeS8nQc80/tnwa897GfI8dK8284YHnpibAD3TeMn6qe8mQL80HqUntcd5
pPihNXn6j9KTxgP+tDR+yJkQbk92SY0T9CT6QB8L4RO7pfSxxqAn9M1v2732
9aTQeQH8hloFj+4MnRfAy0yt3rt96LwA/nib1WvvCZ0XGscr28F8HzovgHfc
37fwpNB5we9HgZ7UXuUY9a9yjMajcozGr3KM5qtyjOij+x34Kaf3JnFfAvpw
pYcLdQ30Z7xfArzaG2UeDe474B0R4F02dd8R5A/DD6X1dHc9darwqb0e7msB
nzWtxd9B3UXkYwFvvvzu/quaLfJ+FP8FcJvVZ3gwHrz3ALxek7teD/Jg8e4C
8JNVOu8M8ifhx9Fx/nLnqGA8uG+j9Wurv/tGYCeijifwL97q9VOQL4r3WqDn
l7nz9lqH60xN4t0U4Cs+vH9BlYrDEniPBPjEp5fUy8z3qsE7IsBLnt+pln/q
FQ/vfwDfPcOUqZTqB+9YAH+rYdY1R1LfxXsSwD+tsHVwhVR7vLug/Zeav7NE
6ru4H672S7tefZenvos4B/Di7r34BN4dgR3RqvNDZ/mp8xTvFgCflhW8v/mt
vrujcUipBw5/GfC1BX/8IIgf4T0b4L2yd28I7h/h/Rjgr3xdcl7gr8N9DOC3
73smEcTR8P4K8JKDfykd+B8QnwD+vyqfDVudWkf4y4Dft/WOr4Lx4P0P4E2H
1szolRoP3tsA/tmOM+YH/lXkNwO/9sDdnwfxL7xXAXxVZuuVwXjwLgXwMW/l
HNkYeg9F9YSq4/LqpyGuA/zVLk0fbrnm6QTizcCXzRz7w9YveyTxng3wvzpc
PGnbqVf0HRrgnSbmLj2SWnfEU4H3XrW696ZUP4ijAN8zZ+fGm1LfRdwReKna
m//+ItUe/Kbj71ylxbep7+J9Ds2LvO74mYdD/Ab8+kufu3tbqh+8VwT9Jynv
AuAdIOgnjzR9Os9vgPdsgLcg/gT+qvAn4v3Y15/90Htom7/WQo7pfs985ON7
26Vw1K+kfaTvrdO+9lCHF/b+yElPvN3xr7V4H1nxyWVHtAj4AXkGwMt9dXTz
pyl+aC713YD/eez4i0Fe/XCpOwb8sQWXbkiNE+844z1ov8YHv/0V9I+4svrv
Fxdtsj7VP+p3AH8l6/75wb0n1MmFnVv8Ez8R+L1RRxj4rMf6dEntCw/vQwA/
3PTHeoH8xDsWwFfKOiL/AHizz59b46fGg/vDwJd9ffPOIO6AdwKAn1eqUqNA
zo+RPFr1T7/32d67UuuF+nHqT/htcZMgroH6cdr+ljOvD+IgqM9O30W/ikud
dg/xbOCdSk258vPU+HFflOhgUFcaeOv3OvUO5AnqXwN/v+1ZK+9JjR955LCL
d55VsUNqXySQvwJ8+9t9n7k5tR9Rz1TrinXK23davxX4HYW7nUjt0wTqbAJf
3N7JB+RDAP/of99WTe33JPKegXd4rf1jgXxAfjPhCeQ9UD/4rqXvar0qrV81
pNa+lBzDvCzNS+PlRIck8nSJbri3on4AeZcB9rna6fKuhMG7OLDv6u//I7Dv
EoXJ/n1G7N/+Ik/0vlr29h53ptZR2uk9Fcm7W/Y82adlxT4tK/IH/XSeVLVF
h7/wbkLa3pTxQN76JG891O0i+e/h/R7I1fGO3/Qepsa7ZP8irwj4GNmnqDup
+YluH5l+su+Av+v2o95T0vrcsr+QRwJ8gewj1McB/omTMyqXYE9t+7r7mXNT
+xr1u4EPcXJM5ZLadyJv8W4N8EflPYI2Ml+Na211chjvuwDfLe8R4H0X4Oc4
eWvwXgjw0ZcdmBTIbbwXoriT28DVPu26otNZwfsXV4m8Ar7TyX8P7zTQdzFO
xX+Qdw2uFjoDHyTyH/KK6KPySvFjF28InQuKz3PnmoH8gV12YUl3PkLOAF/8
lNN7IQcI1zpo1A/sIrXLpN6+WS77BHh7qf+P/Bic437diX8EfjbUDSe9V+sX
o/2NHwR20Pgk8t2BP1v9xYfT/ucctVN2Dzg6tYPaiTmGcOj5hvR8rb9G300g
zxt4u9c7TZ8YstcoTpFEHhLNV+8hpOMXWacC+x30SeOFPmiSttND+Mw8PwPi
dmm8zNqVqX5gL6fxq54P/A+gZzRuckdj2Mtp/PGI/4HfhQad03jPe6z6N9L1
UKWfJOhP7TFOS+PE+obwnAnpfjIt0QHzsjQv+Kst0TmBdSE6J1AHAXpXme2T
ygd5p/BXAM//ivOnIQ8edtbLn0y6O+1HzdT2f4mfDeuF9u/d9f0HQf4Y1gvt
x4v/DffGgc9tMPqhIO6G97fQT+Oqd+xK+13T7wwnxS+Hd6rQftmAew+m68Pn
y8f5RyXJrrxX9Hbcc0b7i/Y+Miew7+AnAV5E/Hh4Twj9LHHfVX8UzdfDOz1o
38TNS/1+RE+De6HAZ/5zYlRAH+xT9LPA0Vn9gXpPSPyBuF+B9q+4ddQ6R8Dn
i52Cd/XIvtZ9DXzRQOeXfp3az5H2wKFn/vLcruEd0/4ibX94o/N7o24F2hfb
MWFbYM+iPhHwUg9VMEHeJvPbO8JvwNG+8dLrqoXid7ru0yo5v/11xG9G+A04
+hnVuM/htN8sV/vJ8lxcAHUB0P6luQsqBXZ9D7lvD7xpr5HbX2y/z+A9LfJv
6D0i6l/lPPA7I+1z1L64JTurXsh/aGi+Hu63o/3Dv/R6IKAz6uZonpEbv9YR
I/ooTvRRfyCt72l8K+ulOK2X8jPxm94fJn7QujPAh7Yre+NLKTqDD9Pxvt6T
Cw7sr+dFKG64+9/ZjZZj3dP4xqpB3BDnQiieODifxklzDOEqt6n/xphvKL5Z
PIifYj/SOJN4ZwV4p+Z5fgz4wRV/6p6MMwO/DeYL++K77y48t1NKnmC+wNdv
DeJu45OoU49+Jk5y/hnMF+2HFn3WC/gK9aOpPX5XvMCAckEd6QToQ/2oHkLj
0XqSWjf9+7LBvEAHS3TQfGiar8oB2C+PtXf8Br4FXqiG2++Qb7CDLpf4L+gJ
/GuhJ94BIv+S+vPRfrXEf0F/xYX+4DfgyTvufHxySN8D3l/oD/kAvHck/ptj
qL3WNyf/m/rz0f5nif9iXWicqh8Cb7m+zpxgv4P+RB89L9JxyU5vBPkJoGca
zzexYDq+H8L93CA/AeuYxncVC/IH9F0QxccUDfIWQOcQvjPY15Dbafzd8eG8
hdB4Inpg6N3ngen9nq4fL/0on1N7jNPSOBPgw1DctnJh7SfTEh0wL0vzQhzK
Ep1VnhCdk6jHBDu3pJyzOJeB3yJ5OKg/BX/mONID0f41yc9BvSS0f5/0QLRf
IXk7qO8DfIKcm6hnhH6uJj0Q7dtKPg/eE0V71gM5fxzvbqJ9F9EDUY8G7R+X
8xHnKfDfJf8H7z6in09ID6T5eqiHonUKSQ8kehrUpwBeUc471CtBP2+QHoj2
f0geEep0oD30wLnkr36P9EDyY+u+Bs56IPDXSA+E/T64/qNvdQrpgWh/iPRA
tD9L7BTogcAnOH1Y5Tz6YT0Q7Z/aftYFobi8rvtU0gOBsx6ofo/uWX9ODumB
+o656IEzhZ/RforYNXi/FnjhbnUrjk7pJ3jflOIIKuepf9X3gLclPRD9d77x
i1ahvCND8/XwLinaXyD2Dt4lBT7VjV/1PaKP4kQf1QNpfVXfo/VSnNZL+Zn4
TfVA4geD9yPVH9Vu0QujQ3pgOo4//v3A/4DzIo1P7Rb4DbDuabx3YKdDzofr
h3dI+wdyDOEqt6n/5ZhvGl/w2cqQ/U7jTMCPBHxme+dHgh6o7a89L6+OOuYL
P1W2+KMwX+C3iN8J7+6gn78kLoz5ov0+8TvhXQ1qL/bG32k6XHtVXt1y0If6
UT2QxoP5Wpqv6hs0L62bQ3kFmvcCP9U3kqcB/wbw5J8zuqfzMDMUfySSj5Gu
T9xe8ihwDxz491XuqJzOO81U/1hJyZeAXIKdPpzkEvkZVP5oPeCI/MnR9t3d
flf9ltrrfiQ/j+47Go/6B4APc3Jb631A327l9MB0XWzB7+m5ukvgR8J4gK90
+q36JYBPu+HshWG/E/TzM5a7cwp0IL1d630Av2RI+Pw9ZgjX+ZJdoHUr6Ls6
Hn3X141T113vlbr5Kn1w/jYl/wPpDzov4OMifoYcbX+Hs+t1fam9ri/pbzpf
Go+ur47H+Wd0/NhH9zo/sK4v8L2Oz3V9gY9w/mpdX+Ar3f5CXFj318hFe95d
12wR4tG6Xy7yNlwbxH0Qr9R6rjN73jW7z3p9LxZ+zunT6zc7Wmdqsg7lyXSY
Pz8vTwb1oYC/02P4/CBP5sKzo3kvf/5csWyQ94L72MCHrru+/u+pfrpQPsxv
L4zPy4fZT/kwb238c1CQD4M6UNhHt7k4i0HeEfBOLZ4stqbZIr0PD77q1631
siA+hXvLmr+xufHNQZwIdICevyFx0dNBfLY25W/ctD/ZK8jfAB2A3+rinhpv
Bb7tx0sfDuKtiKsC31J4bJUgrtqF8jRm1GqXl6exn/I03nbx3yTqT4Hfcg/m
xccN6k+pPXK45KlVKTpIHpRPeVCIX/vEDwZ1zSgfCevi07okcf8f+OrKM4P1
xbp7tO4J1P+i/Kik8I8h/kFelvKD5GWBDy3xYRL3tIHv+v35gJ8Rf7fE54kN
cg8Z/q7koTy66f1t+EnqXnQ8L17/M8Xlr9t7/GQQl0c+D/CxHZb+uDWdh5OO
+5euvTmIy6OuAfDiRztWC3Dk8wBHPg/qiBGeQF0D6gfjsTQezf+h8Sf1vrTg
92958ZEUnys9iQ5J1InAufOhy6cyiDurH8ntL4N7/uq/cvlgBnFk4CvcPtW6
eJSnhH3h074AHdJ1I57PDPYX9p1H+07pSXlTCeRF0P5VelK+FuSAJTmQAN2A
v+TPeyqgW3nCRc4kZwkfQt8u6eSYN1j2r+ajznf7F/kAwGfK/sW6AD/k8icN
6nfoeeTOBV0X4G1d/qdB/QWt1+jOFyPjsTQe5CdYGo+Hdxco/oJ8J5/ynQzy
ToEf3VVoZ1AXAu8HUFzJIB8V+KCuWbOCflAfX+M4Yn/hXjHlcRnklwJf9sOO
HkH/qPNO8T6DvFPgY47PbhXU/+F4n/gHELfyKW5l8B4D8CliRyNPEnKp5L4C
M4I6HngXgeJlBu8iaHxB7GjU/ae4nsdxBIkzmmYUd/hN7E3kSWodpl+31S2i
65KOi0l887S4wydib6LeN/b79S7f0iCPBfjP9a5aFuRfPUB6bFHRY1FXC+17
uvxPD3W60b6E3FtpSnrvGaL3ot408Ay5z/IM6cMXiz6Merv47l0uf9UgTwZ4
mTXTHwr4agTpz/VFf0a9J7Tf7PJptc4s8DYfnbk/wLEu6Oc+uedSk/TwfqKH
ow4s8Cfl/ks30s8LLw/zZ/rekPRvapL/X/o3GUTnUkJn1C8m+pumFC8Q+pvm
NK8HZF4P0Dhl3bXuP/nxkKfkU56SQX0E4OVkH6G+OfknDeqhA39y9OTngn5Q
L5v8q8i/Uv1f8q9UnmidBtkvqHtLfmODOrnAvzo3/5X7Q/xP/kblZ/J/mkzy
y00WeYJ69DhffhO5+jT5e8XvakqSX86KPBlJflrIk5rkj3qf5AnwgyJPUN8Z
4/lY5G038q+Kn9w8S/6rJSJP8B4Azp1u7l6AyhPgX9/x6qygTgjqvwNv7u4j
eKiLrXWy3X0Hg7rYmr/0w4lWwfqiDjLwGu6ehe5f4Ecq1p4Y4PDzkx9D7UTK
F1I7kfwhej8FOH6HfQR86/EuHaalzl/4z8kPo/Yv5UepPCd/juYv0X3qxlfQ
vYNqA+c3ra72WrqOiuRRqB+b/CHqF6K8FPXHkn9Gx0P3shOwc4FnuzxD2EGK
N6sxvv+mlD4D+lMcOQH6p/Gh3wb3YUE3imsnQLc0vqvx8HR7Pdd6Pz1qUHC/
Huev3g897+E3g7oB4BOKJ+o4KW6ofEL+E+UT4Phd8qu1/eZvM2vPCPEJxVuV
TyiuqnxC/hxdF7qXmkT+IfDSn5epOSf1XbSne5fLr6D7BYtvP9w2yAcGX1Fc
RvmK/DDKVxTnUr4iv5COh+5vJqDfAv9rcV5evfIV8M4X13x4Y4ivyC+dxHql
8fNrBPf7QGfykydB5zR+tGeovcq3y/psfKxjiK+A23PenxnUCXF5MsvS97Dc
/Szhn68MyQ2tk073iZCn7dN+1/uPafngB/cBlf8pT0/vrafxUcE9R+QrhuRM
Xr6i1nOg+/uaT0L5POr3o3ye0/K1JM9Kccqz0vu8dM+9sdZri9rLCdy7IXs/
0ZDy2/+R+zLon+59J+DP0foocu8J/h/gy2X/NpT1Be659kbaG2qvfKt2utxj
Ap8DP7kusk9VD5R70wm5D+XTfSjN96b9blBXTuWDjBP3PkguKR/SPaPEFYSL
fND776E4/ryU3Nb9QnkCeh82lCdQNCW3NU+D8iV0vehesPIhxROVDymeqPxG
cV7FKc6rfEj3Z5e3ED7Bfn9C7l32FT4Bvlr0ASt8AvxRkQPS3lB75E+qfvKr
02fUjqP7mAb3pLQOm+hdsN+BV/gpd1VwfxN2OvA5dy7tG/SPd1bo/qnBPSng
14g+Bjsd+Ogt5a4O8g1gj6flSe9egZxB3CGNvxHI4STnYc6PydsUe1btJrKX
Id8VHyTvjyPfHvi55Q9UDOqOov412ddeYfIPIN8S91KBv1Yj369BHao1Il+A
j5M6otdJXBL4mKr/Gxa0x/uFlMfr4V0i8id4eOeG/BUiH/429F29Z0fjxD1Q
Q/4Nrzn5H5D3iPsFRDeNjxKd9Z6s5oVWfaFNUI8L/AD5NnpvrYVBfQ+8uwZ8
k7vvCXtN8f3fnvNEYKfADiU7Xe9TQE62qODGCTuU/AZqt5LfQN/lAn6e3IeF
3Qq8xoGDhYJ+wM9aj+r4F/cH88J7UdSP5udQP2rnAn/14LTsOpovnU/t8S21
HL/BziV/jtrF5M/R93KIzvpeDtEZ93D1HJF7uPo+H/Bdsi54b4/8HrArFRe/
h77bin5uknXEfqR7wXhXUvGd4qfC/Ud9Z1jWEe+f0T1l5A8rXlnWEe9p0T1o
fU+L2hu810X+K/MM+Z3Ef6XveqKfUbK+2I90LxvzsjQvfV+T6ODhvSK6J468
I0t0Rp6SpXVUuZ0+fw9dE5zL4PNQ/t624HyfS3lTkn8FP5hPfgOV2+SXULkN
fCDJbX3HVeQ23icgP4ZXiPwwLLeBzya5DXwsyW3go0Vu4x1Zyrvz8F4a+W08
vAdGfiGV2/Rdlds0Tg919smPpHIb7VluE91UbhOdVW4Dv5XkNvSTKs+e8cD3
IbmtcQdX/0HlNvBxTh9QuU3+GSP+H4/8P574f3zy/3h4FxD4m1IHA+8C6rtY
oueAb7Uu4MyF5wbjx3t11I/Be3XUj8G7dPpOnehL4gez5AdTOUx+MJXDRDeV
w0Q31NlQvU7qbEDv8knvgp7mk57m4Z0MqgeCuiKq70ldEb1PRHoj9ExLeqa+
30b1TxCHsqTH6rwojqPyR+vOZl55x+5f9ul7qBQn0nkBr3Bu80FBHh3sffVT
VfvujFQ/iFsZilspn1B71GMxFBfT+apf6/pt7YLvwm9A49f3bqF3rXV+5tPu
qcHPDBztsz4uXyyoY4ZzDfjqkffXqxOaL98jQ30PtH9M/Oo47whXOnDcCjja
H9+QTAb1fHDuAO++9FhmnRAd+N4W6nsQHfSeKc7NoTWc/EG9V+B1pE4a5Dbw
8045+SlyW89fv4aT26gPC3yi1DGL1m9K6Sd/uX4g3yguoOsC/DpZF/AnxR30
XVite03rBbzQxjx6qt5IcRClP7XXuBjFWZQ/gT9K60LjV/7E+TKM9iPOhfHE
n2h/RPYp3n/VeDrtR/SzVPhT3hPV9r0ljox3RglXOlA/iqN9M9m/eE8ReCPa
pzQv5U+ig46f+F/7oX2qea3EV+BDn/jQ4L0B4D1fW//vjCN7VG8h/R98rvwv
fK56Be0L7CPlc9lHBvX9dTxXje47K/Vd6A9kT3nQE2ifah4j0V/pQ3xiUEde
4xTuvryHOu+QGyXWXfZGUK8Geb9oP+XewP8zPoF669qPqxsgdW/SdetRHx51
0tH/rFVnB/VwNM+Z+k+iLjP2y4OuDomeo8BRjx115zXv/abseeHxa1385oEf
dXwCdZaBX+bqtGhdZuCo34667ei/t6vno+On/pN4n5LqXyH/zac8wATeHaQ6
XYk6hEteYgJ1gUC3d97pMDbwd6EuEPAFG7q8GOSlwG+J/VLW+e31fhnWZVue
nzNNN7RvK3TDOz3Ax+T7KHtKqn/UvwJ+4TfL/CBfcQ2tu/SvdKP+k3iXhfrx
UM+Kvqv+UvIzJ5AHSP5ezSMif6/B+2fA27s6WvqOGnDUt8c7WMCfdXXAvI9l
v2n8S+reIy+O6lMhL9SnfEjNT6M6WshTtZSfqflp+m6nrAvynYCXEXoOFfpA
PhyvnhcfVH4An39D/ID240UODJTvAl8hfFha+AH4p44PlR+of+UH6j8p/Vjq
x5PvWvqurqO+x+vq7Hl4x071f3kXAOsIvL6rE6jrCBzvBcDfDjnUJFKn8YTq
7QWkLiLqoYP/2w041GD2kT2Q5z7561CXXPXJggcvXjLzCM7BfYZw1bvIz4n6
7Ja+q3Um4X8oGqlLfEL9Mw0jdYZPGMK1vij1o3Xhsb5303zJztX5Ai9A8yVc
50v+AZ0vfVfnReuiee+0jvqeDZ3L+r4L6QmqD0Au3VB91se1mqTzbYAbub+P
cxz470tfuPGCJuk8GeCD5B46+gefj+j+4U9B+050Lyy/3AtD/8C/KTZj4IWp
9u/S/abv5H6TnONKn239Fr0QyDHUWwNep8g/fnC+Iw8f58tmV59H62rSuWOQ
nw+8vKsXp3Uv6fzS+mnKV3OfORDsX9T50fdj266pEugteH+O6jIhz9MnuYd8
XZWHUicKeaSW5Kfe19O4zPXXFgvizlgX4A8/Ub5Kat21finwVpM6fhe0x7oA
X128wPvp9hkqB4q3jtZ/Bj6wh9NXMR7Q4aLb/j27U2g8wOetqdPqgtB4gPsL
K+7vFBoP8DkPlN1zQWg82EeZNB7gA2Q80Pcwr3ulrlFZumcheenInzeUP5/8
SugOfsiRelBcr0Pqlnh434LqvUCPtaTHIq/bp/xkzSenPOoE3vOge7Ie3smg
+8WS91/Ap/FDD9Z59XL1u/S+BtXl03fmqN6gkfqEiq9w9Qn1nXXoP95tZ/cO
39egOnWqbwCvN+7tzSE9xBKu9zKoLp/qIfTdJPadvtvs6sLpe35at8HVnVO/
IfD/uXp33nCKa/STuMbz5JeQenQe3oUF/u+nzg9cgOIFgpvC5JeQ+nj4rqXv
qh4I+fCTq69o8O4p8OWyLlLHTPWfESInpW6byuH1rm6byivQ4/jDefU8lW7A
P3T1P2X/FlI95Lsnm78fyEmpe6xy5pLO349/UO27v9P1qbx+wf3KhPyezj/x
Rgf3QBOiF+k6XlFg47dBnVvRr3S9FjRp+HdQL+5PGQ/kyXiHe1IvV+VMZdcP
7ifoPYWTz9Zu5FV/IYnxAH9y9uygrmwS4wEdrnXz0vEA/83RAfnGPvkJ4bdU
+/Rc5yeBP/+0+kKoA0x+NsSpT6uTgzq95CfU/sFXkverdQwo/uhlUF6x5Bsj
v1r5XPKr4Xfyye8EP5jasxtpPBS/gN/GJ78N4juqd2G+B6V/vXcv9BS/vUd+
e5xPqhfhfWq8ywUc701/Je3RP94pXi/tgePdYc5b+FDiX4XovsA1kt9biOL+
guu5Sf0oX1EeO/LzNY4s+fla34nijyrfNH4n48xHecgNZZz5KM4luMor6kfH
Sfm6yAfWeIrkA0vdhj9Vn5kr64V6GuC3fHKPoAbl4T8iefg1KH9ecNTlsNSP
wbmP7+JdQtTj1Xo18n4f6twCxzt9a4Xu6Afvgsnv2j/e/wIfoh+8w6XvwwmO
97bAl+inbcHa54fflQP+0xtV200KtU/n29x1ReLmGYlsksNdpj+aJ4fRT7r9
5R2yUu2/JvncdfqIPPm8lfQNqZ+Zfk9C8CGib9A7feaK4ZceDL/TB7xmKTcv
tA/llfWrvXNYMpvk9rQWt+TJbfSTbm+zLky1/5rk+b9H3suT51vpPP1bztOl
dJ5ul/MU+1DfUXp6Sp4/CnwP/OIvHn0h8CNpPrSMN1++mYnUePQdtDTu59Xv
wvfS+Gf9U/PV/kP5kLuC+jnoH/u9lqObjhN42xPn1An8GPS+pCf01/0MfPGz
l+bVTYrmu3+Wdarl3zUu2pu2/3Uf5cvXOPyuGfBlI77eVWfvPuVv4Gscrt9N
9zOmUfDOWvQdiM+y/nLfVbmJ9ak3ZUWe/0fjAYLft2/i6toh+ofexWif4uck
+gm9r5FXbxP0SeMXXp7aL/oOXRr/qWtQBwP9Y7z73b5T+gDftONwXp0Kev/U
tnb7V+kA/LouxfLqSIBuWIceYtegH3z/K7FTQH99/0vOtQ10rlWRc03f/RK6
7ZD9i36A58p5t4HOu85y3qF9Wm6MuaFxSm5g/YDvyJo0cfn6oUvRT7r9u9VM
qj1+x7x+n3ngseAcVzsNdqjkh6Ad8EOVrzMBvykfy9//X9fZhOgURnG8TNNM
ZiSNmLLxkaGxICQfr3clJpGSxdRci0n5SpFJ1NBIZiMLi1kMJtnIxmKSmDQh
JaNmISQfw5QdYRokk5L3vs/5/Z/nHlm+//fcc89znnPP87/3nnueradDnGMP
+ODhS9dffB0eVj2r4ePXwnnB0U+dBv4Hf/Np35lllfMyLvRkP9cNXUn2b0W+
vvv+rlUn4/7LzENrc31Luj+46qVfLpq2siKP/eDbDtfMfLrq8TDzofXB8hXx
qv6ETUG/6s4NP3405GHsBr9v/efdfrIPGptDfsYP4B+s3zvzxfh+N/ycnvf3
w5+q3749uTHvs/e/vnn+vqzL7sv0Xb3Z5fqTJ33Pnr7O8z9+A5/Ru2zBzr17
N6A/yv+a3VqRx37Gtzn4TePS8wcXh+KxLg7RY35THIIvHSz3PkviEHx1iAeN
B/0XXByCv3VxyP/dYX4178jXuTjU+h/iX3GoemkXh+DEIfOIno/h+tV5wdvD
dSG/qY+39RXnvOBt4frVeMV3LO8xL5z/UufCah8h/AZ+sbNc7eeDPHbVPprT
k/NP5MG/Pwk4v+P62z63EifiUfq+vnNqtDXeXyR9NdeO5es+diDflwV59IOf
sngu7u84Unoe9g1Pvo8K+Dyrf+C86MmsP39x36+R0omwj7n8xnHngj3yg/p4
hHEpPyruLD8U96fO18fP8yv5XDyNeJwK/pSdUX5Fvl6IpyHfEOZF+rXfrPUz
R4/q6m19JD9y3NhE3US+/hKv4C3r339ZkvCcuB7dytcj8YeID2Qpf0jq2Kv8
AXsi/qM6LtWRRLzAKyKeVftroR992azlVf6GPHh/R22Bp7k8Vsb+iLeVUv6Z
9Fccz/kneiP+Ks+fZex3PFy8K+JX3+W8lDjTe949f0Y7Lj8c5rfjt+KNEV8x
luZt9dmwvE08R/n+nFdrvXDXqfRw3P66rhtZYk+Mw/P5vJSxJ+KjW1I+Aw6f
QW+UP5TzTPHYhDfOT3mO6kaainne8YGEV4Xz11o9SbHvp/KA4s/lYel3eV55
hDi6O33T7sp8aX1S/aHdFxNXxMtBuy9GD/j2O0OlLNED/trul5HH38iD4z/s
YV4dH9N4XV6Vf1x+Vl52+U3z7fLhP/tM9dg+U+hx67LscXlM9rh8KHvcuiN7
3Dql68TxVeVTx5+lX3UmxjORdzxH88s8HAnrhXiJ+FRYj5SH1f/tXqEeRjy5
sWGout+0r59ZafUz6AHfb3UvHC8eEup2dJ3y/0DgJ/F7KsNrAs9RHKDnspPX
e16T5zrkuG9Wd6E6AMPPWn0F8ui7ae/3kQcft/f4HI8/FtvzIuSE2/MixoOf
17j7X/ADdv+rfXPNr307ivvOg6+x50vox/+T7vmGeKk939DzZTuO/ccZLzj7
iavu0/Qdc/LisSb/F0CW5Jo=
   "], {{
     {EdgeForm[None], GraphicsGroup3DBox[{Polygon3DBox[CompressedData["
1:eJxNnXX8FNX3xvezuzO7kyuiYoOEgd2tCIIKYqAiiqKCATbYimKiomKhooKK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         "]], Polygon3DBox[CompressedData["
1:eJxFnXO8JMnztRv3tqqxto1Z2+bsrG3bNmet79qa9c7atm3btvl7njn9ft4/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         "]], Polygon3DBox[CompressedData["
1:eJwt13m8z1Uex/Ef5V53cYskD2TGWvdmN6FkjUYiuTRkLTOWi5AKPWR5IGOX
ZCskXGt2bhfZsme/pMYMI2uWHmSyxIzHPM/j64/P4/d9v8778znn+/2e8z3n
V6JT7/ReuWOxWLbII/YmxWJLcsViPeJisUrxsVhDumpyLFaNqVneWKypqEz3
E6uwTLobX0++clhlrBFWXRSgt+Dz1MtQ7xm+OvRBsQx7G6uM/Zke4Xq4aEgX
0nbW9TT5g1wvxK6pN5X+QqQkuKbzamsq90tsr+urfNXFrJRYbAY2BFtM3+Sd
Ti8Sx7DfsZpiDl/VfLHYpYfUVfOvWIZ6q/kS3EdpeU/hq+hZYqTclTz38Jn0
Bt45WFdjTcNr0WvxJLllecrLXUNniwJYeawq9jVdMwTWHGsgitMLRGHt0+l8
6rZUry+2lG8u9pY+umEVjLtRIs5byjsrT5/Hj8gZaCwN+NrSeUVJ7a2wNfKH
qLUMq44dxDrJ3yz3S6wStg/riG3CHsaKYunYSrkfyi2B/45N4Kmm/5L0q/gm
bAVfX75mdCORhS3FumAv00t4WxhXEfq+ce6Wf18U5GvMtxwfyDcKexybxztf
rJH3tLFMxqbz/cg3kW8f30dYGv2M2MCXkBQ9j9Z867ChYczYFXqbMRd/OBZr
532nYGl87fENfCP4RqtXDFumz+VirXr5+FKxdnzZfMP5ngxzFZuIHcRGYWV4
y7mnWfqoq05ZOlVUxmZj9bG08JzFC2rfjY/m4WK5A7Ce2rdj07EP6NmiBv1L
fDSv5/J9iPXlq6LPwubDIDoNr+h6vrF05+1jbH96sFYXYL2x/thg3vfk1pVb
WtuQMF78eljjWCEsRV5rLL/+/ievuHEvwVokRXPxP2FdYplh7WM1sbZy62Hr
sYVhLvDkx37TtjW8W74L+kjCrob1Sc/ne5kvEbuMZfN9HtYhdl5sxT7DmvMm
u76OFdDHPH00wB7CTmEJ2GysJDbW+/hEP0fUHIOVFTd8zNqpM5hvr/ql+Mbx
TeY7yjeWpyV+CFvI04L3dfq/4V3wtPSbo8ZfsCmuX+RbxbdaHMRyq7eT73Vt
3/O1wh7HLmJtsEtYB6ye6CJ3mrymeH06m682dpj3JJ6D7cYaYsewC9gxLF3s
wTLpdLkt6KJ8l3ja0r/o403sB9df8e0J9yoOY4Xd3xzsBu9AbA9WR3TEptBN
wnygT/ldE9Y+tl8cCc8qvE/sN7m3sX9gVbDl2B0sJuefWDI2g7yGDeDbjV00
vnvez+RQy3e1hPX2BDaIbyzffs/+7/KGhTlO91erm/g5zGfeP3i/tek64gL2
N94D2K9qvqPmDuykek3V6yP/En6KHopXo/vJ6yIu0k/hn4Rnjx/X7wS1vgtz
AvsjXUKs53sWv+NZttc2TB/7sDLGUlS/L2C1xHnsMeyi3Cp0VXEO26GPA8ZQ
IswfNR7FRora+hyM9QpzgR4l6mJD6D7iMl1Rv42NoRw9UG4xrLx6t/mGhrni
dwx2Fmup3/fom/o6R38nTod5x5dhzNv4uql32phzqVkQP431wC5hecN3A/sJ
ew57zppfpF4f9T5Qqx/eXfs6ehx//3AP7rez66nYIn3UohuEdc73bUK0nl6k
94sR9HCxAjuh/SWsmd8dCdG3uyF9VX4eYy6Ab1JzcdijwniwJ7Hnw7jDO8KG
yhsiFsk9qu2M3Ju+34+4zpa7IOwJfJfdw8cil/sZLbcbX468d9Vqj2XQbfAR
rsdjn8tdLe+6Oj3CdzScX8RGrGZK9P05x1NFfEb/Wz+7wvPQR22sTZhTYc3R
vcR6Y69BVxdZfCd4yokZdCv9DtXHmLBnYauwieGbI6+zGK+tY9iTjaWDOqX8
XjH24zyfhufFMyUuOk+M57ul77v6KKxegsgO3yZxKy7aA8JekMr3r/B9UivX
g7VdC7vvOaTqowj2rNz82FS+u3HRPAjzoQb2aHK0v1TledOYl/KcEaXlNYmP
1sRl4zgb1lf4TsdHa/YKdgK7Z/x3E6LvUQW1+uI946MzYTgblsc2y7suJyWc
J8O7lLczMbq3J7D0MDewdeEbgMVjd7AsbDl2EothV7B12IbEaH8J+8wrWCb2
LXYLewx7Lcxf7DbWzxhGYO+Lb7BrSdFYHqFzi6+xDGMs5FkV4u/vXnZhxZKj
vbMeT1f1vsI2hnsOewRfZ74tWFNRn68VXw++ZWEsYR1q7y5eCucY/nHh2+G5
vxoXrbHRajX3jjby3IqPznLp9B3eaub9MfwjfKW8JmGOa79NPy++wN7AbmMF
9buFtzU9IewfYT+Ki87Cw9zDK/ju8A7lVRMzeX4N5wp9HJI3GFuBHRU/0acT
or1vu/G9lhytqaxwVucbjjXG0rHV2CBsGLZVbld5XUQduZPUL8NXLpxj+TL4
evF9z/czz0XRmC8H+xjLiYv+L4T/DZuxSdjxuOj/QvjfcABboWYBY84Ofag3
l2e82BX2ZPE+3+BwDuUrxLcpPHu+eeGZPPiPk0MfFrvCuT3sG95lWb/XeH/g
24Zn8u3j2SAW0t9of5svNfzybQ9zKJxFsQp+84T5iTUP78n9vuV9vBPOlPR2
bb350vy+K3cndjjciz6O8ewO5136R/yG9jxyz2gr653dkjNWbkW/ieIUz6qk
6My4Q97T4fyIZSZF3++ssCeJaVilcOaSsywhOvdWpIuoudf+PBErzVdD3szE
6D2sxdaJQ+H7F/Z5fBJP+7BO5HXyXCe5t0+NLzX8l5LbARuLTcJKhv9h2ADs
DawXNlK9A2r9H4Re7fI=
         "]]}]}, {}, {}, {}, {}}, {
     {GrayLevel[0], Line3DBox[CompressedData["
1:eJwl00lI1VEcxfGfPrMybVhERFFEizbpKqhFtmig0leQaZAZpc0imkWUNNCA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       "]]}, {
      Line3DBox[CompressedData["
1:eJwVz0suw3EUxfFbj0rQ1nMBdsACWAKJpC0GBjVpPVoSRkg8qogy8FgEM5Zg
D97ERELCEigfg2/Oueee+/vnP1CojJcTETGNWnvEcWfECaodEdfJiCx/k4q4
RY6fpaOZiG/dXDpizjyPNIZkP0jxg+5rKOiuumvI8/TSzSd27e70fuVF8z1/
qvvKZ/gFbPKht0HfcW6/TPdk3fYJ2kWr8mE6gn1ZXadfNuF7D7JHTPJlOiZv
0snrVMyL6MWbeceu2a7n/1/oAWZka25b+Cl6pfeFuvlJr5WWzM/8me4L7cMS
tuVJ+y36gQv7FXokW/dWGz3EH3/kMuo=
       "]], Line3DBox[CompressedData["
1:eJwVzlkuA1AYxfHPi9BRH3hC0gUYwgKMKxArkKJeNKl3rSmGxNwWbdUi2INY
jGEJfvfhn3PON91b3qpt7A9FxCbOMxFL+Yhl3GUjDnMR14WISjHiVj5DXe9z
OGKFLsgP2NZvmB3h79Hi22jxO3pNfpR/xIx7s/jGqhsZtQvvvss/yMptTNrr
2HtKyEc0RzuY0nuWXxLyMb2xu5vq8hUO3P7yzzW6KPdQ1T8xm+e7Cb6HV35P
75Qv8H3MuTePX6y7UVS79M8P+Q9j8gDT9vrpBt7kCbMlOk7/AT23Ku0=
       "]], 
      Line3DBox[CompressedData["
1:eJwNzLkyA2AUhuGjURDS2YlEZtSM3V0o7XIBSWe5AAqNThQKxjCGmEyMlsK+
XQOx11yBp3jnO997zv+nc4WJfE1ETGK9LmKgPqKlIaKr0aw3m1+ww7/Ky0RE
Khlxbr/LVblBOcU/10bsmfvshmS3PHa7KJewzxXlL2bcX+Ea03jzz6bbAzfv
5hvuFod6hh+Ws/oq1nCk9/Ajss192p8ZbHOt+gdKdp/yzn2Wv7A/4b64UTnH
b3BNdmW93zwms7LELcsVVLgt+YcFb+7xgHl8+6vo9tTNj/mRe8KZ3suPy5ze
YdeJdvwD7lEzmQ==
       "]], Line3DBox[CompressedData["
1:eJwV0EkrBWAUxvFjY2EsPgASia2FTyBrK+PGwpKNKTMZFte8tyAlKRkypXBT
SIbr3ovPoJTyCfzu4un/nOec97xvb1VPf2tfXkT0UqIg4rww4pIGiiPaSiLq
SiPSeCEblLXz2/w3/1wUMYyVZm7kV/Ih9Qjt8Ne0Jq/SX7K7gm+kTH7EHB7J
d80k6cWuMede8VY9yo9Twsye+odP6U3gO97JMnZs6XfgvrpZrwyX3dUgv+cf
aVLeaaZelsUH2ZSsiz/gf/m0nTNYYyYpf5JPq2fpMPc+WpfX6q/YX8030QZt
yubxGE/MpXJvs2/e2Sy+qef4BTrl//BTvohfmJZ95P7V+W48U7foleOqu/4B
WcZCSQ==
       "]], Line3DBox[CompressedData["
1:eJwVz7kuRGEYxvFXJbGraJUSawSxjH2MpXMDEjUziU5D4Qbs2+BChJAJhZCZ
CO5BCCHKUfid4p/nvP/n/b5zTstSbiFbERGLOKuKmK+OmK2NmJPN9RGluohT
/pfLes7hRdcon2W7nR9d3s5rjbPcE9r4vJ0TfihJ/GEAM/pBeazrtpcxFzGN
TXcd8QX9hu6R++Ye5Jc81HXxafM9pnDuvavcgW7SnLE3IZu4onv2+U9u2fMK
7nQN8la22vnQ7dkpuWecKyT/VRmxy/Un34kyejGm65M7uk5nR83XGMGae7b5
G/267op75y7lm9zSdfAp8wWG0WM3rfsHGlg2ww==
       "]], Line3DBox[CompressedData["
1:eJwVzklOAmEQhuFyZeJ4A5UrKEtPgODQiMKWA8AC1MsoTQMC6nmc0cRooitv
4PD04k19w1/VXWi2k9ZcRNRwsxBRWY5oLEbMUMf1UsTZqqn74gv6T7Mou5Id
08845bMVmfdT+dTs8yF/0h9hIpvoym6kuj9s0DXdWL7l7Qf9jks+4cd2DvlH
VPOcP5GP9CM6kT3gAEO+qxvq3vh1t7/nIwb8Pn+Pjr7nuwNvM3lmXvC/uNPv
oZ//u27H/rn8B2v0ri6Vb7rxSr+gl9/mUzsV/hZlbNsp2fkHZX01PQ==
       "]], 
      Line3DBox[CompressedData["
1:eJwVz8kug2EYhuG3SCTGY8AxWNbQA6BTItEdZclpmGqOYVvDRtXYYu8YlFgo
ReIsXF3c+b73ft7vyf8PzS1nlxIRUcBTT0SuPyKPv96I0cGI04GIR/6IO8Zi
X8Q3crKW80F2wB9iBOd8yptJ1GUnzi7uV1/V/iVqfJ3v5BfMn2jinm/wJX5f
1w72sIs72Qxf0PODLJfBKncrm3ZP40uW6o644bbM2yjqftabsfvufi0r8ZsY
xhk/IR/Hlazs7OCauir2L1Dla3yCnze/4bX9P/wLv8Gv61rBWvu7UJHl+Vk9
Hxizl8SU7B9/ETgx
       "]], Line3DBox[CompressedData["
1:eJwVzjkvwwEYx/HHYnAu7lviLFYvxOAaWjUStbO3fws7iVvialcSb8QbIAhx
NdTm0+Gb3/X8j8Hl9ZlcTURkcFcXMdsYMYe3+ojp5ogW+opd3R7WGiL26YKt
VZ9uijiQDzGMBzlva7MNyWn6gRVdwbPt/Dtu3H3jkz9y10Ez8jG/7faeH+FP
UOA77Xn6jKJ9g37pxuxddLR6p5+v/hvKuqda36Cn8hlyvn9OF91165e840K+
RAqPcmLrsY3LWfqLVV3i2V7+B7fuyqjwV+76aFa+5nfcFukEStjS99sT+oKS
fZP+6absA3SS/gMxIDfU
       "]], Line3DBox[CompressedData["
1:eJwVzskuA1AUBuBjQakpMQ8rTySRVCxIm27QCq/A3tbGsNTiEcRcxTOIsWJq
DRvjzmfx5x/PzR3Kzo3M1kVEBs6SEdnmiGR7xFZbxCn/2BIxSD/hGXiH39aI
N3yiv8cD+gech1t6zH0e/9iVbTbpJlnG28d8H98PK7I7XJO/ul2yf8Elm7J8
Qd+LK7IcFPXfUIAjmw1do81wIuKQT3snwRflB/yVmx76Gk///5ce1X+5r/H7
Nhe4W36Jp+CGTtnk8Kfdnk2BbpBNeH+X7+S7YFlWwVV51e2i/TPesSnJ5/Ud
+Fw2CWv6D1iFbZt1Xb3NuPuU7A/D4T+9
       "]], Line3DBox[CompressedData["
1:eJwVzkkyg2EUheEbTRAJawiirWIYGWsWoMpEE1VkSMIyNEEV+xDR2wHWIrOQ
IsRj8NY555773f/PbldWyomIWMVLKmItE7GO78GIw3TExVDE7nDEl9zAle5c
zvIb/A79wZ7Zkf0Rvv2/x9fQ4cu6Y36U/8WCm4toYtONMbNX336SP5CTw37e
u2taRxdOMK5L0HndDb1FD6q49LZi3s037dXcfk9GFGlJTprv60/phNxL73CP
fhzozuikro8uubeMT2y5MWX+5j+f5Ram5QF7Be8e6CNSmLM7o5ulf+2YLfA=

       "]], Line3DBox[CompressedData["
1:eJwNzr0ug3EYhvGnJAatqogQIWIgKh1KMUiQWJit3SQ+K4pi8nEKbCwcAAln
weBgUEXr8zdcua/3fp7/k3dwuby0nYiIIp5aI1aSEWNtEUPpiGFctUfkfTeQ
TEV8yWc5rX8wT/Fv3ap3ZV7U53iaL5iv8RF5pz+Sx8iY3cg6dvkLXrGDH7cu
7HbwX16Vb+jEjH7dvT1+hnN0YVa/oS/Yz7o5imvduO8/dNsJXU3O6R95D0/I
Te8qvNoS0SsXdSVdTt7bPZGn6DO7lQ0c8Hd8YB9Nuku7/byZf8o6BjCv33Lv
kE/6lylM4B/Y3TAj
       "]], Line3DBox[CompressedData["
1:eJwNz8sqxGEcxvHfyEjGmJKUlAwijUNIyVAkFhYW7sBp7LgPVhasFTfAjJzJ
YSM5LR2uxAifxbfn8D7v+++fXVyfX0tERAFPNRFttREdOEhHLNZFTGUi3mm7
7lC3xKf5JP2mJV3e5kHulIvyETJ8N7b1Y86fvd3Fz2JX7k1FbPBFvt6uB2Wc
uPtDczjmT7Fl0yBX2//SM90f7cOHbs/5Mm2UF5z1efvF92b0A7ohnOtXbKZ1
n3RQd6Er8E18ioZ8hQmbR3lYfylfo5kfwY5+0vmr93P8HMpVEZu0pG+xySPh
zi0qMCrf0Du08nW2lfw9khjXfen23V+lWXlJ3+8/3nznH3KMM9Q=
       "]], 
      Line3DBox[CompressedData["
1:eJwVzskug3EUhvEjRKP9qmvTwkKIRFgIkQgbCVViuAHS2GqrNQ8broelxM5a
LMzzcCUSv29x8vzP877na3vL1dVKU0Ssmd9sxEkuYiMfcYxdhYj79ogfvoB1
0zDTSUQPTuGsTt77W6fZ3ZG7Sb6eifjiVmQXJtFbwkP5Mn7KStyBfUJ/H6/d
f/C38jPZOJ94j2EW32Xz/J7uKLeLV+kt9ybbsZd9Yxs7uTs3r3wb1syWGdHv
xmGc0cl4v+j82RvuhtL/jh2yZ35Rfm5y9lL6DdkCPsmKXM0+6KaKl377kb+R
n8oG+FbvfmzBB9kcX9Ht4zaxyK+7+wcMcC5o
       "]], 
      Line3DBox[{2797, 1073, 3143, 848, 3965, 2796, 3154, 3386, 2168, 2795, 
       2945, 3142, 3964, 847, 2794, 845, 3856, 3141, 844, 2793, 1072, 3855, 
       3385, 2944, 2792, 3917, 3151, 3150, 2791, 3934, 842, 3140, 841, 3963, 
       2790, 839, 3139, 838, 3962, 2789, 3148, 3384, 2155, 2788, 2943, 3138, 
       3961, 837, 2787, 835, 3854, 3137, 834, 2786, 1071, 3853, 3383, 2942, 
       2785, 3916, 3145, 3144, 2784, 3932, 833, 3136, 1487, 3429}], 
      Line3DBox[CompressedData["
1:eJwNzrkyQwEYhuFfI2RhhBtwHVwBY4YkGjNGKCwNpaVDY5RcBF3UElthCWJv
uYTYY2s8xTvf+d7v/GdO98RcbrYpIkbwl4w4TEccIY+1RMQvd5+JeMASl5Zj
7REp+WO7lXfoxTY/3BZRwLdtR3ZxQ+4OsI8vvsJ38ot60l0rGvwTv8nf6DVc
4wqftnF+NRUx6GaGm8Y692Gb9DyFAduyf37nLvRLLHA13x31bov+ZqvKc/Rg
i8/bc3i1lWSW63e3hwpe+DLfwc/rCXfNeOYf+Q3+TD/GKU5QtxX5Ff/c56aM
XRTwD0/gOmo=
       "]]}, {Line3DBox[CompressedData["
1:eJwV0DEohHEYx/GH4Y5T75XBSLrVpDDKJFdKSqeU4R2UV52ipBuETUazYjAJ
i7cMbmOilNvOdkZ2g5LPO3z7vc/v+/z/d+87nm4vN/siYg0LpYikHHEyEHGD
tBpxK+v6LznCXeLe8waXy1XuT47pc2SViGtuS6ZcS05hHx1zhrrn3yRiwn4X
j863scNVB93Hzei/8aR/Rovrd++s7sFOz3yEkm5Rl9h5QWZ+ladczd4KN2p+
R5PryDNumlvnJovf9X/uuF15zh3LORzix3zBXckl81Dxbs41nOvio/hW3Lz7
Em6P29T18ImcG9Yf6N/slGVb9w/g3zKs
       "]], Line3DBox[CompressedData["
1:eJwVzS1LA2AUxfE7g1ODGyioaQ5WtQi+JF0bKIaBTiyTYRLdwsJc8aUaHAxM
FhGGQRBkIMwomCx28ROoQcRg87fw55x77rnPk63UitVERJSwOhhxnow4G4po
0Y/RiDb9NE/Qa0ziS14YibgdjrjDtOwBWXzbtfR7fFPnPhXxyL9gBm+YRdLd
O03Tus5i/10s4UK25rYjr9AVWU+Wp2PmS+9v2I3zCT6FAfz4O01zupu6Gb5E
f+Xruk/yZ5Rlc3Y79M/uip/HqU7Xuwt8Afv2U+Yt/oBfdrvd39GmvCHbMx/S
jqzo/ka+S49lr7ITeqTzDxosLHs=
       "]], Line3DBox[CompressedData["
1:eJwVzj0vg2EUxvEjEsXSKIlELH3ibTPWYmEqjaGjWBiYPI1EDAbSfgLCB1Ai
YpBg9QFK4jt4m9HBVITfM/zzv86Vc+7cxbVaNe2KiGVUeiLyuYgjbPRH7GAd
l/mIY917b8QHzuU2j+o/+cL8x9EXcScn+oQPda+6Nzyam/oX+RnXuMEthvUH
PG3nCQPytq7AbfMQD+JLnkO3d+e54b85e0vZja7mr3tIcZXd68bdTSCRp7ik
n+Qxc4lnMuRZ/ap3TuUf3S/K8pn+W+6ghXs8YER/wqmbFXtleVe3wJvmCi9i
S67b2ecG1/kfq6YvjA==
       "]], Line3DBox[CompressedData["
1:eJwV0DEvQwEYheGvBloGBiQkhqYiQZiVRIow9Wp0MUg6sJcQicTWSkQXm6GL
TfQvlOAfoHZJfwKis8dw8p73fDc3Nze7f1iupiJiV5L+iJGBiEYmoiUXwxH3
eGP7Skd8y53ewym3X2zxlGf65EnP2afxmr/iPH/DjqRtxzyDn3wIB6Wrj+Gp
2zj+8EmckJ7+gFduj9iWTVvdt5awyV/k0v0ZR33TLM5JTl/EJbcFnOF5XJYV
fdV+4B23vMi3eIIlKdjO+Bru8Q1cl4qe4LnbNh7xMu7Iid7BhtsHvv//Q++v
2f8A/NcqsQ==
       "]], Line3DBox[CompressedData["
1:eJwVzrErxHEYx/FHCYe4otSZLLIpi4FBKYvpfiZdBkQJpytuOLHoTMpqMRhF
OeMpIRPlJnUWNxH/gcTgZXj3+T6f9/P9/n4DCxtJvikicsi2RPS0Rhy0RVxg
sTuiIhP9l8xwZ6g6r3BXco5rTkUM6u+x1h5xzq3LZW5HjmIbx/q6Lo9p829X
xIg7b7jx1i2KXL/3wu6Y/hsP+kfs/n9LP6W7tvNu3kdKl+j67Dxh1VyTh9yw
vVluyFxHgXuRR9w4t8RNmDf9T4XbkidcWU5iDz/mU2SdO+0U3Jl35xUNXHIz
3kpzJa6o+8Anqlyvvqx/ttMh73R/H90yYA==
       "]], Line3DBox[CompressedData["
1:eJwVzb8rxHEcx/G3xd1JZ3RiMTllUIwMcoXhEqdObIe7jaIYfEc/JpNBIZPu
DKRkNl3nH+BPkEUpKTJ53PDs9Xq/3q/35zNY2Vrc7IiIMkqdEeepiJN0xAX9
yEZc0l9zP73FAD7lc10Rd5mIewzJmsjjy+5Uv8UnOg89Ec/8C0b4MfqGcXS7
fW+/SXftJvg/TOJMVnRfl6/RGdmTbJb2mq/8sWyX49N8Dhl8+7+Pjuqu6A7z
q/RHPq/blLdQlU3Z1dp/2l3z0zjQefRugV/Atn2F7tCCu3V+iSY6+7I9c0Ib
spLbG/kGPZK9yo7poc4/YXsujA==
       "]], 
      Line3DBox[{868, 867, 1260, 1258, 3989, 2444, 1965, 1966, 3824, 1630, 
       1989, 2194, 3991, 1277, 1278, 892, 1129, 3462, 1127, 1545, 1290, 3885, 
       2022, 2006, 2451, 2043, 3892, 2454, 2044, 2201, 3923, 909, 1156, 1153, 
       1310, 3577, 917, 1179, 1177, 3983, 2460, 2090, 2091, 3832, 1689, 2114, 
       2211, 3993, 1329, 1330, 940, 1209, 3523, 1207, 1555, 1342, 3911, 2147, 
       2131, 2467, 2168, 2470, 2169, 2218, 3935, 952, 1243, 1240, 1246}], 
      Line3DBox[CompressedData["
1:eJwVzjsvw2EYhvGnDsV/6WIQTYtJJDo4dDDUIOnAWMfEJpHU4pBImhCxOaxi
1aFhMSDBdxCsPoPyDRzjZ7hy38/1Pu+bd2Blo7KeiohlzKUjujsizrCWRNRQ
xWUmos59dEZ84lr/lnn+S96Y27si0njQB/kheersjXvHi7nBN/VX3OIO9+jh
T2TRThM5vcbl5Y+5X/bhVy/y0zLx9ow89OeEm9V7uS3/3ccmrvgsN+LuKIb1
cTnBj8mCuSQnUdan+Kp3LvRW99tQ0c/5Fj2FR7tPeEaWb8htd1btzet73ILc
MS/JRezqR3YO5PH/n+UfeeotQg==
       "]], Line3DBox[CompressedData["
1:eJwV0L8rxHEcx/G3cn6d4x9ww5lkuElGKbmURXIm5bqupORGk6zflDIZrlAW
xcTIxKBY2LicmJQbTH4sBo/v8Oz9fj/fr8/n8+1bqNbn1zsiYhEXXRGd3RGn
PRGVwYhN/TkX6it3jFJvxJLdtHpi94cmv4AZflX2iPvCr8wUV7L70X+jwX/i
gJ/si9hP73Nml2tjjb+XH8KwXQEJP86/q1l+Vj5j3jK/oZG+b57gN8wtXHF7
GHB+zi6n1vknXPKPskV+VF3hHvAiM8Ldci39M5b5O4z51h1z3q5svkFN9sxd
h1xb/Uj/D3+NRN/Pb+MfJqcxnQ==
       "]], Line3DBox[CompressedData["
1:eJwVzr0vw2EUxfHbofUS4j/wEpNIKjHyB3QRg9BoI7QSZaCMJVKNxCAMWI02
JowmMUiYLF4Gg0mkEjEYhc9v+Oace869eZ6++dWJaioiyrjKRKRbImbbI3ba
IjZbIzJ8FmkcdUVc2knZGeMr+jPzL6b4bVnD3RZOZD+YcVc3j+pydjb4Qdk6
PdZ/ocaP6If0WRzKDsxNeq3rlO3yBdk7Lbr/lnfIq3TAvEIbyfv6N0zLlmV/
/vpJ+81Num+npn/FMP+hX+Nf8MzXZYv2KliSPSDvdsHcq7uzU068rERL+nvM
8T36C/058rJbnCZvmnP8uP6GTrp9ku/Ji7TbXKCP+AfOcDTG
       "]], 
      Line3DBox[CompressedData["
1:eJwVzz8oxHEYx/HPLedPHRmM1BWTwd1A1Nko6qZLDDJQ8qc4BoPBKimLSTIY
jCZkMrFS2GysLCab8rrh3fM878/zfH/9ysvNxlYhSQP3xaTYluy3J2vo6U5u
uU/9B1axKy/xzx3JlWyqM5nEnGyG35Bf8r+omav8uX5B/6NWzIt2RtyfmF/N
m7IXtQ+zsiP+gJvwbg2nduv8gP6MH1S3uSbi5ltW4PfcPZof8MWN4q8rubO3
Ixt3N4Z3ftj+kLrOv6Hc+lfzkv4JN/r+1r235luzumLnWr3gezHNV71XwaFv
lLhj/AMaaypm
       "]], Line3DBox[CompressedData["
1:eJwVz61Lg2EUhvGjQV8tQ0S0iqxshiX/ANFimLIyEBS2BYPgG4xGbRs2waCz
iYIYF5dEVhaEJRERnGKwiAbT9LdwcZ5z3ffzfsxX09LeSESU0R6LSMYjbpKI
Sibi0LnFjZp97hobExHbsnXzVjbAE7+FNT7VveR+EZMRq1xR9qc/QJP/wgW/
LG9yVXdOuE+kfE8/i0VZHg3+A9PD9+smOkf2V5xzZfsKf2B/xj13ijl3S7JZ
c59/RJt/0S3wBXOX6+FdJ8c9cG/OfdT4Ls74Jd96zC3IN7kOdviW511xP+Y3
ivwdZmR1+9Tw3/APNZoyzQ==
       "]], Line3DBox[CompressedData["
1:eJwVz70rBHAcx/Gv1HFnMLGKMCgZrMQ/oJOSuM7p3OIh6tzmJI5MNylsRou6
8cZTMlgsMmBQshhEYjDxMrz7PH1/w687vz611hQRC2gkIpItEblUxEEyotIa
0cYPIYXD9oi6m2Y3E3zRXpN/keMrur3/dzjT/SDr3a48bpt0s8UP6sr01P6J
TX7MPmofwZHuDZf6TrnKz9lfacbbL32HvkQH5A26Y9+3v2BWV9Ql3HzQfvmd
Vt2U7U8Y5r/9o8Q/4pnf1q24W8aq7g4z3i7JfbZbNwW+R7dIC/Yb5Ple+4W9
gYzuGuf6EznNp+1XdNrbB/2xfp52yVl6jz9t8jTL
       "]], Line3DBox[CompressedData["
1:eJwVziFLA2AQh/EbgtMFBwoD44LOOm0bTFY0WDYtBoOIgkVdcIOFNQVBWBWx
GMVk26JaNGmaX0D0CxgUi/7e8PDePf+74y3uHK0fZiJiA/fjEblsxMlERBsz
+Ygh96n+wDG68jz/MhlxJ1vNRaxgW7bGt+Q3/C/q+mX+Wv2FmnpXXrV7oX/T
t8yMvCVsyvr8Wdpzs4Yrs02+lGp+wdvh2sja+ZGN8T17z/onfHMV/E1FDNKs
rGqvgne+bL7sPUh/wLz+Ub+nfkVB/6CfS7ftb3FDd/f5gfeWn0WDP+WW3F3E
udlp/hL/qnorYg==
       "]], Line3DBox[CompressedData["
1:eJwNz88rw3Ecx/G3wjaxoSi/yo7KkQPnnThxUAvFToq2nFy5KKm1b82vUlqW
/Acc+BM4O4i/wGRK3DwOr57P9/v9+hw++VJludwRESXZT0ekeiIyUuFpLONh
JmI9F3HLd6Rp3sYGLmJRCu4LOO3NuGzKjflXZ4LP80TnzzzHx+wOeIOP8FGZ
5ec6Vzgj9e6In2xEnk/KhX7VvY1d5m/sxGFv9/iK26X5gw/ZtVMRLf6Fu7jk
fub+aa6bW5jgM77KlPsT5r0dkA050X/TGeSPbsc67+YH3m+3xWs6WZ6Te/tT
nardHS/6Q8sfmvxajvTr7r26ibkPa/hivypr8g936DO+
       "]]}, {}, {}}},
   VertexNormals->CompressedData["
1:eJycPWV4lcnOeHF3L+6upT2DFbfiDos7FC0uxd2d4lpcFitnkKLF3d3dXb7J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    "]],
  AutomaticImageSize->True,
  Axes->True,
  BoxRatios->{1, 1, 0.4},
  ImageSize->{347.5856180284344, 263.88594376361505`},
  Method->{"RotationControl" -> "Globe"},
  PlotRange->
   NCache[{{(-2) Pi, 2 Pi}, {(-2) Pi, 2 Pi}, {-0.9999999999999748, 
     0.9999999999999748}}, {{-6.283185307179586, 
    6.283185307179586}, {-6.283185307179586, 
    6.283185307179586}, {-0.9999999999999748, 0.9999999999999748}}],
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02], 
    Scaled[0.02]},
  ViewPoint->{0.2283917988639563, 2.9164827481901767`, 1.7005780093017684`},
  ViewVertical->{0., 0., 1.}]], "Output",
 CellChangeTimes->{
  3.530268980527418*^9, {3.5302699909773417`*^9, 3.53027002713627*^9}, 
   3.5303391928890944`*^9},
 ImageCache->GraphicsData["CompressedBitmap", "\<\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\
\>"]]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Animate", "[", 
  RowBox[{
   RowBox[{"ParametricPlot3D", "[", 
    RowBox[{
     RowBox[{"{", 
      RowBox[{
       RowBox[{"Cos", "[", "t", "]"}], ",", 
       RowBox[{"Sin", "[", "t", "]"}], ",", 
       RowBox[{"t", "/", 
        RowBox[{"(", 
         RowBox[{"10", "*", "Pi"}], ")"}]}]}], "}"}], ",", 
     RowBox[{"{", 
      RowBox[{"t", ",", "0", ",", "tmax"}], "}"}], ",", 
     RowBox[{"PlotRange", "\[Rule]", 
      RowBox[{"{", 
       RowBox[{
        RowBox[{"{", 
         RowBox[{
          RowBox[{"-", "1"}], ",", "1"}], "}"}], ",", 
        RowBox[{"{", 
         RowBox[{
          RowBox[{"-", "1"}], ",", "1"}], "}"}], ",", 
        RowBox[{"{", 
         RowBox[{"0", ",", "1"}], "}"}]}], "}"}]}]}], "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"tmax", ",", "0", ",", 
     RowBox[{"10", "*", "Pi"}]}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.530270103998288*^9, 3.530270294216524*^9}}],

Cell[BoxData[
 TagBox[
  StyleBox[
   DynamicModuleBox[{$CellContext`tmax$$ = 3.7138783415515118`, 
    Typeset`show$$ = True, Typeset`bookmarkList$$ = {}, 
    Typeset`bookmarkMode$$ = "Menu", Typeset`animator$$, Typeset`animvar$$ = 
    1, Typeset`name$$ = "\"untitled\"", Typeset`specs$$ = {{
      Hold[$CellContext`tmax$$], 0, 10 Pi}}, Typeset`size$$ = {
    360., {151., 155.}}, Typeset`update$$ = 0, Typeset`initDone$$, 
    Typeset`skipInitDone$$ = True, $CellContext`tmax$5244$$ = 0}, 
    DynamicBox[Manipulate`ManipulateBoxes[
     1, StandardForm, "Variables" :> {$CellContext`tmax$$ = 0}, 
      "ControllerVariables" :> {
        Hold[$CellContext`tmax$$, $CellContext`tmax$5244$$, 0]}, 
      "OtherVariables" :> {
       Typeset`show$$, Typeset`bookmarkList$$, Typeset`bookmarkMode$$, 
        Typeset`animator$$, Typeset`animvar$$, Typeset`name$$, 
        Typeset`specs$$, Typeset`size$$, Typeset`update$$, Typeset`initDone$$,
         Typeset`skipInitDone$$}, "Body" :> ParametricPlot3D[{
         Cos[$CellContext`t], 
         Sin[$CellContext`t], $CellContext`t/(10 Pi)}, {$CellContext`t, 
         0, $CellContext`tmax$$}, PlotRange -> {{-1, 1}, {-1, 1}, {0, 1}}], 
      "Specifications" :> {{$CellContext`tmax$$, 0, 10 Pi, 
         AppearanceElements -> {
          "ProgressSlider", "PlayPauseButton", "FasterSlowerButtons", 
           "DirectionButton"}}}, 
      "Options" :> {
       ControlType -> Animator, AppearanceElements -> None, DefaultBaseStyle -> 
        "Animate", DefaultLabelStyle -> "AnimateLabel", SynchronousUpdating -> 
        True, ShrinkingDelay -> 10.}, "DefaultOptions" :> {}],
     ImageSizeCache->{403., {187., 192.}},
     SingleEvaluation->True],
    Deinitialization:>None,
    DynamicModuleValues:>{},
    SynchronousInitialization->True,
    UnsavedVariables:>{Typeset`initDone$$},
    UntrackedVariables:>{Typeset`size$$}], "Animate",
   Deployed->True,
   StripOnInput->False],
  Manipulate`InterpretManipulate[1]]], "Output",
 CellChangeTimes->{{3.530270128029748*^9, 3.530270137519969*^9}, 
   3.530270179001485*^9, {3.530270210378261*^9, 3.530270294868682*^9}, 
   3.530339193826728*^9}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["Einfache grafische Objekte", "Subsection",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.53027090852808*^9, 3.530270918765161*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Show", "[", "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"Graphics", "[", 
    RowBox[{"{", 
     RowBox[{"Red", ",", 
      RowBox[{"Disk", "[", 
       RowBox[{
        RowBox[{"{", 
         RowBox[{"0", ",", "0"}], "}"}], ",", "1"}], "]"}]}], "}"}], "]"}], 
   ",", "\[IndentingNewLine]", 
   RowBox[{"Graphics", "[", 
    RowBox[{"{", 
     RowBox[{"Green", ",", 
      RowBox[{"Circle", "[", 
       RowBox[{
        RowBox[{"{", 
         RowBox[{"1", ",", "0"}], "}"}], ",", "1"}], "]"}]}], "}"}], "]"}], 
   ",", "\[IndentingNewLine]", 
   RowBox[{"Graphics", "[", 
    RowBox[{"{", 
     RowBox[{"Blue", ",", 
      RowBox[{"Translate", "[", 
       RowBox[{
        RowBox[{"Rotate", "[", 
         RowBox[{
          RowBox[{"Rectangle", "[", 
           RowBox[{
            RowBox[{"{", 
             RowBox[{"0", ",", "0"}], "}"}], ",", 
            RowBox[{"{", 
             RowBox[{"1", ",", "4"}], "}"}]}], "]"}], ",", 
          RowBox[{"Pi", "/", "4"}]}], "]"}], ",", 
        RowBox[{"{", 
         RowBox[{"0", ",", 
          RowBox[{"-", "4"}]}], "}"}]}], "]"}]}], "}"}], "]"}], ",", 
   "\[IndentingNewLine]", 
   RowBox[{"Graphics", "[", 
    RowBox[{"{", 
     RowBox[{"Yellow", ",", 
      RowBox[{"Polygon", "[", 
       RowBox[{"{", 
        RowBox[{
         RowBox[{"{", 
          RowBox[{"2.5", ",", "0"}], "}"}], ",", 
         RowBox[{"{", 
          RowBox[{"1.5", ",", 
           RowBox[{"-", 
            RowBox[{"Sqrt", "[", "2", "]"}]}]}], "}"}], ",", 
         RowBox[{"{", 
          RowBox[{"0.5", ",", "0"}], "}"}]}], "}"}], "]"}]}], "}"}], "]"}]}], 
  "\[IndentingNewLine]", "]"}]], "Input",
 CellChangeTimes->{{3.5301945299919367`*^9, 3.530194544375839*^9}, 
   3.530250041207149*^9, 3.530252269960226*^9, {3.530271699510849*^9, 
   3.530272101307002*^9}, {3.530272329846505*^9, 3.530272662225069*^9}, {
   3.5302730967724447`*^9, 3.5302731321562157`*^9}}],

Cell[BoxData[
 GraphicsBox[{
   {RGBColor[1, 0, 0], DiskBox[{0, 0}]}, 
   {RGBColor[0, 1, 0], CircleBox[{1, 0}]}, 
   {RGBColor[0, 0, 1], 
    GeometricTransformationBox[
     GeometricTransformationBox[
      RectangleBox[{0, 0}, {1, 4}], {{{
       0.7071067811865475, -0.7071067811865475}, {0.7071067811865475, 
       0.7071067811865475}}, Center}], {0, -4}]}, 
   {RGBColor[1, 1, 0], 
    PolygonBox[
     NCache[{{2.5, 0}, {1.5, -2^Rational[1, 2]}, {0.5, 0}}, {{2.5, 0}, {
       1.5, -1.4142135623730951`}, {0.5, 0}}]]}}]], "Output",
 CellChangeTimes->{{3.530272402109483*^9, 3.5302725297748213`*^9}, {
   3.530272609745816*^9, 3.530272642733376*^9}, {3.530273088487233*^9, 
   3.530273132424069*^9}, 3.530339242687667*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Show", "[", "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"Graphics3D", "[", 
    RowBox[{"{", 
     RowBox[{"Red", ",", 
      RowBox[{"Sphere", "[", 
       RowBox[{
        RowBox[{"{", 
         RowBox[{"0", ",", "0", ",", "0"}], "}"}], ",", "1"}], "]"}]}], "}"}],
     "]"}], ",", "\[IndentingNewLine]", 
   RowBox[{"Graphics3D", "[", 
    RowBox[{"{", 
     RowBox[{"Green", ",", 
      RowBox[{"Cylinder", "[", 
       RowBox[{
        RowBox[{"{", 
         RowBox[{
          RowBox[{"{", 
           RowBox[{"1", ",", "0", ",", "1"}], "}"}], ",", 
          RowBox[{"{", 
           RowBox[{"1", ",", "0", ",", 
            RowBox[{"-", "1"}]}], "}"}]}], "}"}], ",", "1"}], "]"}]}], "}"}], 
    "]"}], ",", "\[IndentingNewLine]", 
   RowBox[{"Graphics3D", "[", 
    RowBox[{"{", 
     RowBox[{"Blue", ",", 
      RowBox[{"Cone", "[", 
       RowBox[{
        RowBox[{"{", 
         RowBox[{
          RowBox[{"{", 
           RowBox[{"0.5", ",", "0.5", ",", "0"}], "}"}], ",", 
          RowBox[{"{", 
           RowBox[{"0.5", ",", "0.5", ",", 
            RowBox[{"-", "2"}]}], "}"}]}], "}"}], ",", "1"}], "]"}]}], "}"}], 
    "]"}]}], "\[IndentingNewLine]", "]"}]], "Input",
 CellChangeTimes->{{3.5301945299919367`*^9, 3.530194544375839*^9}, 
   3.530250041207149*^9, 3.530252269960226*^9, {3.530271699510849*^9, 
   3.530272101307002*^9}, {3.530272329846505*^9, 3.530272662225069*^9}, {
   3.5302730967724447`*^9, 3.5302731321562157`*^9}, {3.53027318707872*^9, 
   3.5302734114031143`*^9}, {3.530273466749609*^9, 3.530273531778038*^9}}],

Cell[BoxData[
 Graphics3DBox[{
   {RGBColor[1, 0, 0], SphereBox[{0, 0, 0}, 1]}, 
   {RGBColor[0, 1, 0], CylinderBox[{{1, 0, 1}, {1, 0, -1}}, 1]}, 
   {RGBColor[0, 0, 1], ConeBox[{{0.5, 0.5, 0}, {0.5, 0.5, -2}}, 1]}},
  AutomaticImageSize->True,
  ImageSize->{382.69559504338184`, 397.9787301417577},
  ViewPoint->{-2.8988959020189844`, 0.501565149096883, -1.6717759869279618`},
  ViewVertical->{-0.1073227818221641, 
   0.8052107424925167, -0.7336407886250246}]], "Output",
 CellChangeTimes->{{3.5302731948011417`*^9, 3.530273321320545*^9}, {
   3.530273354811798*^9, 3.530273411878112*^9}, {3.530273475286421*^9, 
   3.530273532236373*^9}, 3.530273599869652*^9, 3.5303392472028513`*^9}]
}, Open  ]],

Cell[BoxData[""], "Input",
 CellChangeTimes->{{3.530273162129175*^9, 3.5302731634306507`*^9}}]
}, Open  ]]
}, Open  ]],

Cell[CellGroupData[{

Cell["2.7 Differentialgleichungen", "Subsubtitle",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.52974144712798*^9, 3.5297414538862247`*^9}, {
   3.5297414860870447`*^9, 3.529741486396851*^9}, 3.529773051415864*^9, {
   3.529924371489483*^9, 3.529924372035397*^9}, {3.5301892823347797`*^9, 
   3.5301892846641893`*^9}, {3.530191468559938*^9, 3.530191468634067*^9}}],

Cell[TextData[{
 "Wie f\[UDoubleDot]r algebraische Gleichungen gibt es f",
 "\[UDoubleDot]",
 "r Differentialgleichungen eine Funktion zum Auffinden der \
L\[ODoubleDot]sungen: ",
 StyleBox["DSolve", "Input"],
 " (analytisch), bzw. ",
 StyleBox["NDSolve", "Input"],
 " (numerisch)."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530189321347843*^9, 3.5301893221574287`*^9}, {
   3.530189404158413*^9, 3.530189636497501*^9}, {3.5301896906363287`*^9, 
   3.530189708376135*^9}, {3.5301897391027193`*^9, 3.530189772158428*^9}, {
   3.530190660782638*^9, 3.530190667387738*^9}, 3.5303350037347107`*^9, {
   3.530335065067623*^9, 3.530335066818371*^9}}],

Cell[TextData[{
 StyleBox["Bemerkung",
  FontSlant->"Italic"],
 ": in ",
 StyleBox["Mathematica",
  FontSlant->"Italic"],
 " sind \[OpenCurlyDoubleQuote]",
 StyleBox["+", "Input"],
 "\[OpenCurlyDoubleQuote], \[OpenCurlyDoubleQuote]",
 StyleBox["*", "Input"],
 "\[CloseCurlyDoubleQuote], usw. Shortcuts f\[UDoubleDot]r Funktionen (",
 StyleBox["Plus", "Input"],
 ", ",
 StyleBox["Times", "Input"],
 "), im kommenden ist es n\[UDoubleDot]tzlich ",
 StyleBox["f[x]\[CloseCurlyQuote]", "Input"],
 " oder ",
 StyleBox["f\[CloseCurlyQuote]", "Input"],
 " als Ersatz f\[UDoubleDot]r ",
 StyleBox["D[f[x],x]", "Input"],
 " oder ",
 StyleBox["D[f,x]", "Input"],
 " zu haben."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.5301897882796373`*^9, 3.530189971588325*^9}, {
  3.5301900865266647`*^9, 3.5301901145657673`*^9}, {3.5301906252586937`*^9, 
  3.530190628340589*^9}, {3.53033506880329*^9, 3.5303350708287992`*^9}, {
  3.53033856382749*^9, 3.530338565147805*^9}}],

Cell["\<\
Einfacher (ged\[ADoubleDot]mpfter, freier) harmonischer Oszillator:\
\>", "Text",
 CellChangeTimes->{{3.530190832619277*^9, 3.530190883693012*^9}, {
   3.530191543209627*^9, 3.530191549786256*^9}, 3.5303349396009398`*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"deqn", "=", 
  RowBox[{"(", 
   RowBox[{
    RowBox[{
     RowBox[{"a", "*", 
      RowBox[{
       RowBox[{"f", "''"}], "[", "x", "]"}]}], "+", 
     RowBox[{"b", "*", 
      RowBox[{
       RowBox[{"f", "'"}], "[", "x", "]"}]}], "+", 
     RowBox[{"c", "*", 
      RowBox[{"f", "[", "x", "]"}]}], "+", "d"}], "\[Equal]", "0"}], 
   ")"}]}]], "Input",
 CellChangeTimes->{{3.53019128888398*^9, 3.530191314479385*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"d", "+", 
   RowBox[{"c", " ", 
    RowBox[{"f", "[", "x", "]"}]}], "+", 
   RowBox[{"b", " ", 
    RowBox[{
     SuperscriptBox["f", "\[Prime]",
      MultilineFunction->None], "[", "x", "]"}]}], "+", 
   RowBox[{"a", " ", 
    RowBox[{
     SuperscriptBox["f", "\[Prime]\[Prime]",
      MultilineFunction->None], "[", "x", "]"}]}]}], "\[Equal]", 
  "0"}]], "Output",
 CellChangeTimes->{
  3.5301913148994017`*^9, 3.5301932100260973`*^9, {3.5303385782767487`*^9, 
   3.5303385804845963`*^9}, 3.530338659046876*^9, 3.530338807042824*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"DSolve", "[", 
  RowBox[{"deqn", ",", 
   RowBox[{"f", "[", "x", "]"}], ",", "x"}], "]"}]], "Input",
 CellChangeTimes->{{3.530190681287055*^9, 3.530190686235244*^9}, {
  3.5301907214941874`*^9, 3.530190814244617*^9}, {3.5301912958655157`*^9, 
  3.530191319771661*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"{", 
   RowBox[{
    RowBox[{"f", "[", "x", "]"}], "\[Rule]", 
    RowBox[{
     RowBox[{"-", 
      FractionBox["d", "c"]}], "+", 
     RowBox[{
      SuperscriptBox["\[ExponentialE]", 
       FractionBox[
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           RowBox[{"-", "b"}], "-", 
           SqrtBox[
            RowBox[{
             SuperscriptBox["b", "2"], "-", 
             RowBox[{"4", " ", "a", " ", "c"}]}]]}], ")"}], " ", "x"}], 
        RowBox[{"2", " ", "a"}]]], " ", 
      RowBox[{"C", "[", "1", "]"}]}], "+", 
     RowBox[{
      SuperscriptBox["\[ExponentialE]", 
       FractionBox[
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           RowBox[{"-", "b"}], "+", 
           SqrtBox[
            RowBox[{
             SuperscriptBox["b", "2"], "-", 
             RowBox[{"4", " ", "a", " ", "c"}]}]]}], ")"}], " ", "x"}], 
        RowBox[{"2", " ", "a"}]]], " ", 
      RowBox[{"C", "[", "2", "]"}]}]}]}], "}"}], "}"}]], "Output",
 CellChangeTimes->{{3.530190772550969*^9, 3.5301908148014507`*^9}, 
   3.530190886216744*^9, 3.5301913207906322`*^9, 3.5301932105276747`*^9, 
   3.5303386599320803`*^9, 3.5303388076354113`*^9}]
}, Open  ]],

Cell[TextData[{
 StyleBox["Bemerkung",
  FontSlant->"Italic"],
 ": die Funktion \[OpenCurlyDoubleQuote]",
 StyleBox["C", "Input"],
 "\[CloseCurlyDoubleQuote] steht f\[UDoubleDot]r Integrationskonstanten, die \
nicht durch die ",
 "\[UDoubleDot]",
 "bergebenen Gleichungen festlegbar sind."
}], "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530190893727076*^9, 3.530191034608279*^9}, {
  3.530193211164345*^9, 3.530193211828514*^9}, {3.530335072113031*^9, 
  3.5303350733553247`*^9}, {3.530335292602408*^9, 3.530335295184401*^9}}],

Cell["\<\
Spezifikation auf die Anfangsbedingungen f(0) = 10 und f\[CloseCurlyQuote](0) \
= 5 durch die Angabe aller Gleichungen in geschweiften Klammern:\
\>", "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530191107312977*^9, 3.530191153045138*^9}, {
  3.530191822765435*^9, 3.530191844818708*^9}, {3.53033867887669*^9, 
  3.530338679781892*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"sol", "=", 
   RowBox[{"DSolve", "[", 
    RowBox[{
     RowBox[{"{", "\[IndentingNewLine]", 
      RowBox[{
       RowBox[{"deqn", "/.", 
        RowBox[{"{", 
         RowBox[{
          RowBox[{"a", "\[Rule]", "1"}], ",", 
          RowBox[{"b", "\[Rule]", 
           RowBox[{"1", "/", "2"}]}], ",", 
          RowBox[{"c", "\[Rule]", "8"}], ",", 
          RowBox[{"d", "\[Rule]", 
           RowBox[{"-", "4"}]}]}], "}"}]}], ",", "\[IndentingNewLine]", 
       RowBox[{
        RowBox[{"f", "[", "0", "]"}], "\[Equal]", "10"}], ",", 
       "\[IndentingNewLine]", 
       RowBox[{
        RowBox[{
         RowBox[{"f", "''"}], "[", "0", "]"}], "\[Equal]", "5"}]}], 
      "\[IndentingNewLine]", "}"}], ",", 
     RowBox[{"f", "[", "x", "]"}], ",", "x"}], "]"}]}], 
  ";"}], "\[IndentingNewLine]", 
 RowBox[{"fp", "=", 
  RowBox[{
   RowBox[{"f", "[", "x", "]"}], "/.", 
   RowBox[{"sol", "[", 
    RowBox[{"[", "1", "]"}], "]"}]}]}]}], "Input",
 CellChangeTimes->{{3.530190681287055*^9, 3.530190686235244*^9}, {
  3.5301907214941874`*^9, 3.530190814244617*^9}, {3.530191160078377*^9, 
  3.530191195915104*^9}, {3.5301912276905518`*^9, 3.530191274056252*^9}, {
  3.5301913265574217`*^9, 3.53019144938868*^9}, {3.530191783266835*^9, 
  3.530191806409946*^9}, {3.530193197871591*^9, 3.530193201779496*^9}, {
  3.5303387817374897`*^9, 3.530338793979555*^9}}],

Cell[BoxData[
 RowBox[{
  FractionBox["1", "254"], " ", 
  SuperscriptBox["\[ExponentialE]", 
   RowBox[{
    RowBox[{"-", "x"}], "/", "4"}]], " ", 
  RowBox[{"(", 
   RowBox[{
    RowBox[{"127", " ", 
     SuperscriptBox["\[ExponentialE]", 
      RowBox[{"x", "/", "4"}]]}], "+", 
    RowBox[{"2413", " ", 
     RowBox[{"Cos", "[", 
      FractionBox[
       RowBox[{
        SqrtBox["127"], " ", "x"}], "4"], "]"}]}], "-", 
    RowBox[{"1277", " ", 
     SqrtBox["127"], " ", 
     RowBox[{"Sin", "[", 
      FractionBox[
       RowBox[{
        SqrtBox["127"], " ", "x"}], "4"], "]"}]}]}], ")"}]}]], "Output",
 CellChangeTimes->{
  3.530191449907174*^9, 3.5301918071902447`*^9, {3.530193206046739*^9, 
   3.530193214118555*^9}, 3.5303386831779613`*^9, {3.530338802702889*^9, 
   3.530338811275182*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot", "[", 
  RowBox[{"fp", ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "10"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.530191526328842*^9, 3.530191532454178*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwUV3c81e8Xt/eeF/dyr33tdc34HFtCJUolq0IqGSmrqIQoSUSR0VdlE5UU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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{{0, 10}, {-48.93667071648538, 37.909239690692004`}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{3.5301915330796633`*^9, 3.530193216346208*^9, 
  3.5303386913626633`*^9, 3.530338815421455*^9}]
}, Open  ]],

Cell["\<\
Dasselbe nun erneut f\[UDoubleDot]r eine numerisch gel\[ODoubleDot]ste \
Differentialgleichung: getriebener harmonischer Oszillator.\
\>", "Text",
 PageWidth->PaperWidth,
 CellChangeTimes->{{3.530191863481986*^9, 3.530191921983226*^9}, {
   3.530191991613628*^9, 3.5301920077335033`*^9}, 3.5303349741799307`*^9, 
   3.5303350744626226`*^9, {3.530338737545096*^9, 3.530338744835782*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"deqn", "=", 
  RowBox[{"(", 
   RowBox[{
    RowBox[{
     RowBox[{"a", "*", 
      RowBox[{
       RowBox[{"f", "''"}], "[", "x", "]"}]}], "+", 
     RowBox[{"b", "*", 
      RowBox[{
       RowBox[{"f", "'"}], "[", "x", "]"}]}], "+", 
     RowBox[{"c", "*", 
      RowBox[{"f", "[", "x", "]"}]}], "+", "d"}], "\[Equal]", 
    RowBox[{"g", "[", "x", "]"}]}], ")"}]}]], "Input",
 CellChangeTimes->{{3.53019128888398*^9, 3.530191314479385*^9}, {
  3.530192021542975*^9, 3.530192022497035*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"d", "+", 
   RowBox[{"c", " ", 
    RowBox[{"f", "[", "x", "]"}]}], "+", 
   RowBox[{"b", " ", 
    RowBox[{
     SuperscriptBox["f", "\[Prime]",
      MultilineFunction->None], "[", "x", "]"}]}], "+", 
   RowBox[{"a", " ", 
    RowBox[{
     SuperscriptBox["f", "\[Prime]\[Prime]",
      MultilineFunction->None], "[", "x", "]"}]}]}], "\[Equal]", 
  RowBox[{"g", "[", "x", "]"}]}]], "Output",
 CellChangeTimes->{
  3.5301913148994017`*^9, 3.5301920242992363`*^9, 3.530192330727076*^9, 
   3.530193217900138*^9, {3.53033875127421*^9, 3.530338767689142*^9}, 
   3.530338818690362*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", " ", 
   RowBox[{
   "bei", " ", "NDSolve", " ", "m\[UDoubleDot]ssen", " ", "alle", " ", 
    "Parameter", " ", "spezifiziert", " ", "werden"}], " ", "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{
    RowBox[{"sol", "=", 
     RowBox[{"NDSolve", "[", 
      RowBox[{
       RowBox[{"{", "\[IndentingNewLine]", 
        RowBox[{
         RowBox[{"deqn", "/.", 
          RowBox[{"{", 
           RowBox[{
            RowBox[{
             RowBox[{"g", "[", "x", "]"}], "\[Rule]", 
             RowBox[{"1", "/", 
              RowBox[{"(", 
               RowBox[{"1", "+", "x"}], ")"}]}]}], ",", 
            RowBox[{"a", "\[Rule]", 
             RowBox[{"-", "1"}]}], ",", 
            RowBox[{"b", "\[Rule]", 
             RowBox[{"1", "/", "2"}]}], ",", 
            RowBox[{"c", "\[Rule]", 
             RowBox[{"-", "3"}]}], ",", 
            RowBox[{"d", "\[Rule]", 
             RowBox[{"1", "/", "4"}]}]}], "}"}]}], ",", "\[IndentingNewLine]", 
         RowBox[{
          RowBox[{"f", "[", "0", "]"}], "\[Equal]", "0"}], ",", 
         "\[IndentingNewLine]", 
         RowBox[{
          RowBox[{
           RowBox[{"f", "'"}], "[", "0", "]"}], "\[Equal]", "10"}]}], 
        "\[IndentingNewLine]", "}"}], ",", 
       RowBox[{"f", "[", "x", "]"}], ",", 
       RowBox[{"{", 
        RowBox[{"x", ",", "0", ",", "10"}], "}"}]}], "]"}]}], ";"}], 
   "\[IndentingNewLine]", 
   RowBox[{
    RowBox[{"fp", "=", 
     RowBox[{
      RowBox[{"f", "[", "x", "]"}], "/.", 
      RowBox[{"sol", "[", 
       RowBox[{"[", "1", "]"}], "]"}]}]}], ";"}]}]}]], "Input",
 CellChangeTimes->{{3.530190681287055*^9, 3.530190686235244*^9}, {
   3.5301907214941874`*^9, 3.530190814244617*^9}, {3.530191160078377*^9, 
   3.530191195915104*^9}, {3.5301912276905518`*^9, 3.530191274056252*^9}, {
   3.5301913265574217`*^9, 3.53019144938868*^9}, {3.530191783266835*^9, 
   3.530191806409946*^9}, {3.530192140925129*^9, 3.5301923137639847`*^9}, {
   3.5301923589087143`*^9, 3.530192414498876*^9}, {3.530192453185767*^9, 
   3.530192467921386*^9}, 3.5301927716580353`*^9, {3.5301928145360003`*^9, 
   3.5301928228874283`*^9}, {3.530192883543232*^9, 3.5301930839760313`*^9}, {
   3.5301931207035103`*^9, 3.530193180454666*^9}, {3.530193245155645*^9, 
   3.530193283008535*^9}, 3.530335075848782*^9, {3.5303388234698563`*^9, 
   3.530338829812851*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot", "[", 
  RowBox[{"fp", ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "10"}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", 
    RowBox[{"{", 
     RowBox[{
      RowBox[{"-", "100"}], ",", "100"}], "}"}]}]}], "]"}]], "Input",
 CellChangeTimes->{{3.530191526328842*^9, 3.530191532454178*^9}, {
  3.530192389364134*^9, 3.5301923967267113`*^9}, {3.530192427899544*^9, 
  3.530192480532546*^9}, {3.530192782443966*^9, 3.530192808098764*^9}, {
  3.5301929729188213`*^9, 3.53019297490906*^9}, {3.5301930483169003`*^9, 
  3.530193048524061*^9}, {3.5301930976114407`*^9, 3.5301931155948563`*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwVV3k8lN8Xtu/CWGdMDMOQfZB18h7bFFEoW/kSCSlCWYpWFUKplCVriGRL
SJKuJRIJSZIiW5HslaXye39/zef53Hnvec5znnPuvXJexxwOsbGwsGizs7D8
/zfzjBcX3Tve5FzEh8osmUaTlrcUG2fKYaxH3cMrNyAb22htiKZQTmK7ihti
z4WUY5koUZaTEoelnRPsDYp6jh3dFhrwWzYNY/vnJFJ57Q32dt0veV72PuZe
fSRivXIY4/44qvRD9gl2iW+gV2BmDst9lR38XbYd8+A3id4kygLLqdUqwwnt
mGHvsUgxVxZg+naM9a62YylP/PaKZLPADPtvx7q3r7DcA48tf6iwgsG2XUZx
MZ3Y8EVJn81mbNBd/odNae4NJvRuv/BAAAecfaVmTfd4ixHHZ/0ia3igrDzu
41GNQSxpW8E/jVBhmCZMJ1h7DmJzfpGU2zeEQSnM2kQ5eRA75mr837dyYchh
8OeOrQ5iH0w+q9pOC8ON9gSffS8+Yn9OxWEi7iIQNnZtYbvbJyy/r+eSjSkB
svk7okUsR/D97uR8WhYFk22RbufcR7AqsuM1TSExGApU3ToXPoLljQaNeG8R
A6ne+MnO4hEso0ryScR/YnA91cYqVvgLJqhZXm3SIgbRil2bNj5+wTz1O3uE
EsTBF+tJmwkZw0xI/OHq7JLAcvdX3cf4MSzId2aRlygJqRzkoVf5Y5jA0sel
Zg1JeNnuI3O/fwzjOdTx6I2rJCjv/XP3kNE49nL15Gkok4Rvfkoln1knMMx3
7959dlJwrsPm9WvSBMbWI7X266AUSGmEzNbrTGCSg5eXA8KlYMdSvdadQxPY
jdZ7ctOZUnD/tEO1c/sEVtZUvSE+JQX+N043dCdNYr8lfWJEIojA9vPu8PP7
k9iR/eFVjDgipDu/ZClvmsTUzYP0sHQivCKLmicuT2JHZSPOtT8lgmphUZuV
y1dM4FWb2uwfIsw8fdvdJPsNMz8vedcunAQXZVYXHhp8w/jEZRY+XiIB+byM
aK79N6wm/GGncTIJbJiHHc9Gf8NCvXPORlSQoLT73wfjr98w02WHbV8mSRA4
sWWsqmwKO7TxWtNmpzSMuH/gaWyfwsrio9p5XaRhz0CsxuvxKSy+Xsr0urc0
GHR8PTlBmsbUnu3m+hslDewPC4QlYqaxoO3MPLMH0hCm4qgnf3caU/7nNG5V
Iw3f8jjcNJ5NYw6zqZeIjdLQdftgIXNpGus9KU0X6ZeG1Cg5k3CP71h90gzj
v7/SwPer+2D0qe/YiTMFiXe5yHD62Lm4a7e+Y3sDMz+UCZHBy2u4r7DjO2a6
9UCttBwZ+j5eXXs0+R37c7/2V+QWMmx3NKEg1hlMJOBozF06GdR2ZB4Z0J/B
KkovrpuakiGr0eb6uMMM5ru1JbFuBxlEjP/UzAfMYMfnxLtXdpPhl/p+Nt78
Geyw+462F/+RoVGUmGYo/AObO0bbkRlGBt3Elw2Wqj+wkmkzChZFhntcEeP2
zB9Y+9C2iILzZEhY7df0j/qBFZd/lXweT4Z/IZcdw1J+YJNn66RCksgQPLM1
8kLlDyz5eBX/VDIZnIaTW9O//cDO9zMw+UwyvHSxmLnHPoupxIQxxnPIYNy7
JPJIZhaLC9MsOJxPhrKdefrPDWcxwe2fXCoLyUB54fBfx95ZzNXaX7+hmAw3
TNii3x+bxXwHt8ollpKBs/Zh0diVWSy7Uuy3TAUZIuieXXMFs9jSDvv045Vk
mC4WXl5Hs9gvWsnMlSoyuCkgIs/QLLZh5tbtXUOGN5nHMLHfsxjDVUiZtZYM
ZpKyhyiEOeyNxXS/xxMyVCV1XVFTn8NmXOLQuToyKPGdqTDYMYfNPWFpP/iU
DOnR6v0WB+ewUzVDfTz1ZBD4O7Rud2YOu0aRbz+G47NhCXL/pc1hD+7tik/F
8eKc8fbDVXPYFzVX1mgcex/+fjT0zRy2rFgpoonj96PpN85Pz2FBM+Z5Gfj+
ihqKQ61s85io5vHMDjz+5+k/szbC81i2rPy3pzi/1MI+1reb57GY6xVHAnD+
9t4lYq6q81ig8YrwCJ4fn9xFpWGDecy3zLZRtBrXn3Fd84zlPJZzOdda/REZ
Lrtk6W92mMdCR70/CD0kg8WJB1i9+zw29dPe7WkZGdiSarfvPzKPuaxHN2mW
kAE9eLF7LXwe2zUUvn70PhnOtPU6p13E+fXy/A65R4a1fzO+7zPnsfog298D
2WSoJa0dCyuex5ZtMj4ZZJAhTI87QvzxPKah0mDlmYrrESAXu6d7HjvWMnaK
H/dPRZxG0uLQPKadf1UhEfdXYIFx6vWpeczSZN/m95fJ8H3IsegN2wJGEO9t
b8b9WbziVREotID98tU/5BNOBj+xoFpB8gK2w0FTtieYDOM7r7zcuXUB03K+
0fTvEBnu+qZ0T5suYKIX+m43epDhQHT+QNyuBSzykLOHjSsZhuoavrX5LmBn
GyQKn+zE69vfMe9zYgEL67QSy7Agg8viwArn+QVs2+8Se+Y2vD+3LPFYpC9g
x1XsNy+qk6EzVWkL6lzAeFtOaN0TIMOVKl26x4cFzO1P495WdjLs6DY1/Dex
gJlHa4mVrUlDC7ebFWNjAatovGTf91Ua6sOSDtfSFzGIcHCJfC4Np25kBjub
LGJWUYSJ91X4fCorPvnLehF7MXp3Yf2+NFRNtMTpei9iUrJwMf2mNJTuXb1f
cXsR+/fpbRQdn2dHg7gqd+ctYmteqYvtztKgkiBaN1u+iD0MX5ncgs/De83q
r9TaFzFyb50D0KUhS9trumh9ETNQ6z/btkaCq8IdKrkHljDZv4+GzKJJ8ER/
c/WuwCWMPhq/9ieYBOPux7A/kUtYf/43idADJDAuFd3rnLKEPRt/FpbNIME3
K7fTgl1L2O0ZWYXPC0Qwj/7x5qTxMuYnXVIsZEeEwGJsn5LVMrYYS2OpMMLP
i57r431Oy5h6sjhTSJEI87J6q5ohy5h7mOMy36oUZNWfkZ8sWsY4iiO1V/Hz
aOWnUKiDxE/sg8DHyRcfJYG62Wtjg4rjZJ51jyZJ2GVRFVdK/4npe5rE1hVJ
QsENlywe258Y7UjqxYcnJMFBM7etIfonVur791AxrySU+mmTVBd+YjPv2FrG
lSTA6+Pe5+ydv7B9UtxlF/TEgO/Ol4DgD78wNuXkGH4JMajcF0genvyFqYtM
du3/KQrsgzEn61h/Y3r7wt33PBKF/IE6nWD939iC1FB+npooTL6jFH2++xtD
2wzLlsQI4N89k/Tk5ArG4NC3iosUguAXF72OKa1hWTyZZrNrHCAzzuT6pbOG
1YSZtm0r5IAONt7iKFjDAjllRyz3cIAiJC7Eua5h3ynxHeeL2eFD3a1z+fFr
GDvLrTs1jmxgWnEv68PcGrYhxL4kiG1gIndeDprXrmOirNI9qzzL2MMggT1S
Vn+x8sSaklMvOp/nRh6Z1nJmgTibQ5lnBwXQhew/9sszrBDkd4cRnEdCdlq1
wapLrPDs5oV2r24Skmk8ft1rlRUizEb2b/1LQnWj093dnGxgEmIlHeUkjRYV
P+wulWED5c3RPZe4ycirpNrWx44N8o8qdxkc3IxMnwRaDTxiAyf93l2p/2TR
JmuVw0J1bJC2zKyJFKWgocGJWCZiAwHsP/7bShQU8cftZVUnG0QQDR2v7Kag
Cmzn9usTbOCymhZzNIuCKK1KltaS7NAf5f9wXl8OsbwdgfpT7CAlKHOtzUUe
XZxqyD11Hl/3lRQOOiKPeFky2Qxj2SEt5aT26ml5RFB3bam+xQ6RdZTYkrvy
SDGmZ3t5BTucfpD05Pq0PLI2btp1d5Idqkgd48onqKjLPqf8wA92sJmWJjZf
pKI9fmeEZZfZ4bM292OjW1Tkdsuo9w4rB5Aa0/waq6kocK7S8RaZAz5s+cpQ
+klFN/Py3GIdOGBdL5SuEqCApOrOP2O6coC26xT5YqQCyuj2kOE8wAGv930J
rI1TQPf+So+cx++51y9fSywvUEC1zskHI2M5oKrgeXXvRwU0xH/JP7CBA5oz
Qs6+AEV0QP5gh9oLDvhhzl5aYaOIJgxM1b53cMA575xTx10U0eyhvz98P3DA
MMXP9uwxRcSKQoM9lzmAtk3F4sEdRUQ74ROxV4UT9odv/aU1o4jUjYb3ZGtx
goF3X+74siLSZXHRnNbjhG9ssashfxWRWYLV5FlzTvhi2qotu4mG3PPV9j5w
4wSPSyfOVarT0CH/As1fXpwQvY8FM9hKQ0e1ZPhND3NCXN3TuhQGDZ2qF2rq
D+WErCvlYWPWNHS7b1GT7Ron5DWbfis+REOZ6Uf4bW9xQgj5QNj6ERrKPzA+
mXKHE36FPvqiEEJDlTPvMtWLOCE05co46xkaelK562REGScw5ZeY1dE0hCLa
9jZX4fFf7CObxtFQF8cTftdGTrC/W1D75SYNvXtF/5rXxgkOUz42v1JpaCip
uGn2NScU/hybGc2koWlyxsmLg5yQ9vrqvHkhDXFuPfu1fIkTnvsyXeRraUhg
/XfT2ion1Be2FCw/pSFCY1CWJQsXBHemYlnPaYhi6+X4UYALrAV//glrpSEl
0Y9aNFEuoHieXipopyGND3sEgolc8KXYbehBJw0xDlk2c9G4YBPGpcHopSFz
1YYsezUuqD3z40hrHw1ZL+idytDmglBZH6bSexqyf1zu+NWAC1Tz7he5f6Ah
l9PKdG2MC/r99M4c/UhDHua5AqctuWB05k2l3Sca8uElfWvbyQXhvGe1+Ydp
KODNjWaCAxf06N2YujNCQydu8Wf/58IFNzsyW9hGaShy/8VTRe5cQNoWVYGN
0dAFub+OS95c0OWxK91hnIbivobSTY5wQWRh5DHjCRpKKp0ViAvmgizfys1r
OE457vvtbTgXNIh+u3F1koayDEeaZc5wQf1Z12crOC7YcMk+fJELlCnx8QZf
aajkRc+pqitckGxtNWOL40fx1k4bSVxw/URR1//X6+yb6dYpXEC15ZRfxb9v
lGQI3srkgu55jv7/7//yU9W34TwueGt1a3AVj/8mT71FpZgL1nf8kDXCcf/h
e9mhFVygQU68vRvn/0lTNhLVcMGkt4mmEZ7f+M8UJ/5nXFAVKPZx9QsN3TXV
Of6pGY8fPiUWiOvjkdh1rfwVF7jy5Dwt/0xD5A+HS873cMHZdbdnDUM0NKjA
2b5ngAt4pEp47gzSUGpQzoTiMM734LkEiwEacqo3ZluZ4IJHwboGT9/RUM+e
EOOMJVyv8dJWoW4aupot6BK4xgV2svQrP3A/2HwvOgGs3AABwvqpuF9eXhgu
Hd/EDQq+Xwh7m2joctepVzXi3BCsOKh4qAH3C0niayyZG1482zZtVkdDDQ9t
KOoq3HDAf2yP90Maivr7lbGhxQ08OmdHCktoyNAq2rVHnxt+DRv+eIz7u2rk
yY1QS27Qd96/bxvu/xA1x/LtNtzw1CO8oDKFhjQj5juIe7ihf9dm5vJ1GioW
UuJsOMAN+6elvIYu0ZDf/ia5JF9uEH8e03HhLA0pFv5n4hXIDct2j3x+RtBQ
jklyOFcUN+wQoIlieD+nBLBO70rhBvbXvRcO2tLQ3icZXHJZ3HAyPrra3xLv
J04D6lI+N4QpLUxu24brkxHollLJDYM7ke4ONRq62PGxa/g1Nyw97JGe4aYh
M8nw7w/7uCHnHfsXh3+KaMOLwHPxIzc05HUnXsLn16m1HabKU9xw4xbXnV0j
iihoS82jIA4e0Hm86/KxakWkEWrfbcbPA9Nni2O2Fiui72hmRozAA8+TWkPb
shSRjwuV9kSWB66N2FB3xyii/2KSUlmNeWCsXUpl1lERWU/4n74RzAOhiW9u
HZtSQMzT1BKLCBwLSPUZ4fPaTHxo8NcZHvjFK4P1dSogI0tbg/0JPHC6fmtj
cLkCUinQXKIW8kCyneJtlxAFxH9o2a96iAds98X+GJ6lIp6/JSm+YzxQdFJ8
x81PVMRx61ArcZoHfoBMqngnFf1p6aee+c0DKY6vXGOKqGhG4clnJoEXbPiK
zOU8qKhz/PTege28cE9PRhprlkcvo/Sir+ziBRfI2DNdJo9axOYeMhzx9Ume
2kPp8qje4oBQrhcv5P509nwdJI9K8s1eHT7NC6GMmH4vaXmU6M0N65W84Gk5
+KTeVw7tGk9SlZHhg5qhU49nnsqiTtXxPjcFPnB/PJmIxcuincf1z9xR4YPj
q7F3LffJoh1sn7ul9Plgsmdz6NHfMsiMohomascHIlZLh1U1ZNBWtxeI5wIf
7LWQXS9IJCNy36rj0gQftNf3CvhLENF0s9e5l6X8INddxydxQATJXh/wv1rF
D96rCtajUiJor/sux71P+WEHaJ070iOMGlYMVUZe8oNFtHBrjakwuqEu0vd7
jB90V/mNTptsQsYpz5WUSALAT1qW58vkRQn+5DeXLuN4krEI7CxIQ6R/s7mH
IMi0psn4a33B+LCfnkNLm+BqdrZ6EEUCIkyVeWrWNkHHi2MGvuESMGm+v+wa
qxC8FRTVceiSgKYdjWtmQkLg8GBlgiVKEk45JN68ryIEvyucnzzol4LvhxRf
hHkKQcrBj+pXYqWhM8FRWeSNENimtESfPkqB7T/2/ZZ3FIYK3jK2yHOKkCUW
/fasizCUPWs3qrinCMvGD8qH9gvDl4WbhW2dipBzZd33tpcw6G3iLr4jRYM1
pYwB3iBh2HqrldpVRoMSr09P5q8Iw+50nl7+d0ogPOAR1YCEwdAvlOrHpQI+
GzEu0i3C8Ls8NJSurAL1tArdiDZhoG9/eL3HSgUOh7L8oHcJQ4t+RGtyggo0
EXL/K/goDG8fjERuFlaFE7ajJgm/8Hjz0ZnfN6nBQJM36z41EWi+xy9PnVKH
edNB0mlNEVDQUduOsWsAd+Nu3RxtESAm6jpobNYAvedGvpMGIsB0XBW9aKcB
yU+FX4dYikBqGnkLd7UG7K6qT413FwGvd2VhOqGa4KOjXVnmKQKjm7yaPBI0
4UxlYUePtwgcPXzu9748TSipuPFP8ogIcFokKT3r1gS+Uj/v/HAR8EQHV5LF
tKC1QEzrWZIIJG59amPgpwWfFa5YjdwUAeOgvmT9EC34mbfhxZ4iAmY6iSfI
UVqgcHf6llWmCFw4Hxt7+5oWXMhC6+/ui8CBiPvTO6q1wCTlaNtskwj45hx3
vrquBU4SoyMirSLQoPScfZCdDgG3nNd020WAOsCbxCtAh4ybZuqRb0TAUsdg
RJRMh7VrUje5h0Qg5FFwYq8RHapjW9wpP0Wg/pUVeTSEDkXWHVIxKyLgzwGn
pk/SIV2gt/fHughIjbguvjlHh3NJw8ynbASY3cpWR79KB5vUNQ0nYQI4Fzqd
sC2kA7aPdapelAC9CV8DjUvpoE3myaNKEqCVWzeD8xEdJHPEJRc2E2CpUI6i
0UCH0UKtjXhVAljPv3jb2UuHd4f1nyxqEOCi5LBf2ns6vFQ1Oe6qTQDSLuRq
OkSH0vKdX2mGBAjrOvRNfoIOOcEOuYkMAjQs39njNkWHGzqu+5cxAmybPVMd
9IMOEY993jQyCdCtprm+5ScdjpwMiFO2JkDHwayyrhU6uBufML9mS4CokX+/
bf/Qwfz5+cduewlwXm589iObNuidjw1udiZA4JJ54DSnNiibX1NV2U+Amaqd
Sm95tGFTW0b2b0/8HfZb7of2Jm1gjctzdT9EgEsJgl33hbVh2bpY9IUfAaRe
fkxaI2jDpMDD16pHCRAg4kBRFNeGD12PY24cI0BRwVnfLZLa0JnUYLoaQgBZ
eoM9N1EbGhxerHuEEcCHXPmqgaQND8U6q1tPEqC+w7phN1kb8vt7j6mfxvl/
bpKq26wNKakftiSfI8CNwJzWvzLacGXfyNhaNAGmdldXkSjaEEX+mukZQ4DP
u2W7heW04djnH84vrxCg8sQOrhEce+Usi2heJcAa46tFrLw27PVa77h1nQCi
w/9O8lK1YbsC2+U/yQS4Hjt88yCOjSZ54GAqAR5m0s7fxrF6kdBa+x0CvF5p
0LqLY4q/RJVWNgFqt3y5fhnHBLXNgSl3CTDYIJpsjmPOWaryvwJ8vUdV6QMe
b6VcZdT7PgGeh9kab8fxdDA9o6OEACa/v6NEnN8nHQMn7QoCtPG8KirB8+n+
aSKc9ogAMRxrY3my2tD82PLVRg0B8mU+HzyO519z0uaiTx0BbmUqk6RxfYqM
95i8fobXR2RoJV1aG+78dV3RaSTA3fidi4u43lefH6hMbyHA5XekVXkpbTh3
3vco60sCxBeZsKhKaIMPZ+hIVxcBzF/NDDWJaANJtv39eg8BLD1LTU8LaUOX
weY3yu8I8OuRWpaYIO6foy+eXfhIgNUbFsRBbjyfS8Tq8s8E2NH2TZEH91NW
dkDJ0BcCpB06yCWK+43rrfgdvW8E6JIvlnu+Toe6mcM3Dn4nAPFPpM0B3K+B
XA1xSbME4P2lqfp5mQ79hj4R08sEKHbj+noM93tBTo1jFqsocCh8TZvG+8Wl
js+2g0MUnpRezgsaoINAn7vFCrcogPxm9bdv6XCCm1vHYZMosAD7A/VXdLAI
dBbmkhYFJrmzQ7+aDisxD7h1ZERh0T3UNrecDiW5G/885ERhdNpb9et9Ooi9
K/zxREkU+oTl5riz6DBuvPIqQFcULOXeWmVepEOqo01Tur4odKTf85g6jc+L
YzlP2oxEIdjvRoNIOB2q7u4okjMVhQabTXt++9HhIm/apXe2otCS1N4ivpMO
BtQfUWz2onAt9LmQhTkdZhimJzT3isIFL7fcXcZ02Bs05RW3TxT01lwyVlTo
oPDeELb5ioJT4mdSDg8dBuYT9f39RWE45FFTxYYWJPCNaqQEiELxy+rnmb+0
YHnblc0Lx0Vht0DqC4FxLWjJH1zLPycKB/Zq+GDPtOBgSGS1QLooLKcp8qzj
81tP+3P1lkxRUGFGBfG7awHfItQwc0Rh8FTI51UHLagI5np87p4otH+Q/xrE
0II/QddrlytFYbptLuqloBbcPlb4dKhDFLoHb2lb79WEw5p89atdolC/5mmj
Y6QJjLmj9RK9oqCQqxH/QVYTxgK1n9kNiIKnzdKb/6Y1QCvwWUPLuCjse1+z
vj1KA9qPvm0s+YvXJ+fUo9qb6pChptfUziIGg91Hz54NVYegmdSmSXYxoNas
8nM6q4PEUfdmCp8YdNNvD9sQ1cHryFRLsoQY9BeqDfamq8GfwxttUZpiQA5o
FXl3XRU0fVW7bDzFgJh8qrfKbgt8Pix7rNRbDPq2f+RzVdoCCUdFhTf5icG6
xIhwzV9lmApet38TKAacfu9D7txXhryojnf2UWLwlyynRfqnBJI3jnxyShGD
3gPUzzLpNNiofzBz4LUYlJeIMKg5VHhDUOMPNRQHqfs2VsHTRDAJCJi6wxCH
dwmrBoxzRChrK2trwsTh1aZHq6XiRLgaRb8ozBSHt2Mmp2MxKbCZ1Pv7wEEc
5pvcC1WvScCrJ6Zzo0fE4a5Io2kD7uMXB5zf2mWJw6lH14nPuXngadmFO2rs
EnCjQrbSKebr80hWFbvOTxJgpkfvbIuRR5MW/AO0L/g9TOV12+greWQXO+Nx
flwCNvIXyIuCVKQgVH5M77sEhNR/jft+E78Pk3Wv5axIQBIp3tMwWwHJGJh0
nRCVhO5L/4xQJQ01BTrYbLaShGTFZfdj7SqIb+jUjsAqSTDae/peoDUd6YXf
F7z2WBJq6hUZ4ENHnoSB3vI6SbjHwlb55zwd1e7Y+t8CkoQ3uun2W5/QkU/1
XPCJ15KwrNY0nUXTRo1Xve+cmpQEGaMUUcpfbRRhumv2spQUeIbw/TRL0UX5
Q1GPCqWlYKQ9de9GuS56E/4g4qWMFOybfuWY/VIX0cp42PkUpUCSMbc/blUX
vSU1SybSpeCqa6fjhutWpLGsb3rTWgpYiyrczcT10MQ9ueTsKCl4O9Iwf++4
Ppq5+GWV/ZwU+LgPh6pd0UeLXrkeftFSoLZFMjc2Rx+xyMqp0q9IwZRK8Whz
pz4ipVCamlKk4GO6zKwJ1QDZxcjOT1RKgVVc9cCmlwbI+dCwo3WNFPC80wkc
+WiA3M2zn5Y9wdeDUfHFOQN0ZEMmJhxJgUhLjryFhCG6HC4jw9uF89evPpDq
aYjqfTfbqE1JwWJWTYHnnCFqtvz0MGkGz/fmGR9TFiP0ipop+XNOCo6TJyTm
hY3Q+2Hy2LNfUuBx8vjBJ3QjtOhMPrWbgwiUs2yxP4OM0OrWoeFH3ETwTlvO
Zp4zQixiGZZS/ETYsfpmyvuaERLslhb5IkIE2cKnRjylRkh5h3RRiCwR2PZP
r4xNGCFN2kfB9/JEiFzd/SJ1yQjpcdw5bkwjQs5QgjSR1RiZIxLGoU7E75n0
1EhpY+RuQOq/ZUSElf/GdzTZGqNkZSLHE0civF/SOa5aZIzc3GmFYy5EuMMX
w3z70BgpJOtYb3IjwuEjUs+tnxqjqg3bpINeRHDJcxMoem2M+vovkDcdI8IT
V4Ks1LwxyhBIem4QgvM5Oi1nuGKMvM0yvQ6GEuFta3GxMgsDLZc+LqqNJEKG
sUBLiBADiV6a0T0YS4RrNjNe5aoMNFi3+j4xnghCf8OHQZuB7s5zRdZeJcLG
qG9/tgEDabvJNQrewvO58uzRCwsGWruu4W2QivOrltifYM1ATW3G3Afv4Prm
Pv0na8dADjpOtrW5RDhrcgiV7mMg0uGD86P5RBhOXcst9GCg0aygm4JFRJBr
+MsV6M1AIXzxH7zKiPDJSmzSI4CBjCA1KvEhEfrkPWnxwQzEFlYgW1tFhJ3e
18IuhDLQjS/PDwk+JYL88dr+vigG2if5mseggQgq3LnlmucYSN528IFXIxHu
W21XcYpmoOkLX3clthBB0Pmv6o7LDFRZu7zwuI0InhCQzhnHQKdmWW+NviKC
k0Pa/qvxDGSmIGQg2EUEy8Yhx9FEBuLbR/6o30MEzfXvx1iTGKj32pYzXn1E
GFruS/p+nYHSX+jJJb4nwr+wjeycmwzktW7e8niQCA5H1C9RbjGQCt3ed/QT
EZq2RCofuc1Aiz7ufIJfiBD3wiPkXAoD1WUcKdUfx/+/r3TngVQGutAbYef1
lQj7Xa9n8qUxkDXP5aUEfI6m9Cfbn8WxiMnN249/EKHnXYZ9A44HjucYjs4T
oTNlOqYNxzn3S4cElong81V6OB3HfsN1Z/V/E6HOR9XMAMda4i/lvdaIYDYU
lJGNx1uxfvci4S8Rfp3N/dCN80HnRv0es5DgxI7uiQ6cb2zNHP8oOwmkDQJL
k/B87Gb+lAlwk0Cn2HqzbDIDScnzOejzkYAv56Z8+A0GGnGW/OkpSALSpv7i
VFyvokSF1ARhEiht+ZcXfZWBgprpxo9FSXDokfMf/QQGMlg1+fxFggS3ra7e
rcbrwaJpc16ARAL1itJLf/B6JaX7tHlSSFB4qxZN4PUND7twPIpKgtccdifT
TjOQu0OWbAqNBGmztnulTjGQGl9/eKcaCTyieA3DQ3C/Ty5Qv2qSQFz7mJJz
IO7fRsFuVh0S7FuNZ2XzZ6D2k5bK+oYk8CmSY9YeYKAKR88+ewYJOERJqc37
GSiVfvrcUYwEX/+9zE9zYiCfqaqBXEtcH0vDxoKduD9dFeIEHEjwoUh8mKHD
QFO6sFXJkQRn3ZaGMtQYqFvY7YupCwkek19atCkyUPbLm4bh7iRYPvZJK1KS
gRgG7NNf/EngcGsm3x3vX6qY7O0/AbgeR1RJInh/880bmUkGk2BPyJ/niV+N
0UBhSLpNOAlaLxXFTLwzRqGSo9aPo0nQI7X34qYKfJ4s/f3Vc5kEFg9qVkTu
GSOLN8S8mTgShBF5o4bvGCNCjP26XBIJWi51FQxcNkZlv9CDhAwSMLR1nc33
GaNbvUPOhdkkOPnfa5GUXcYoqmyFvekuCSqyO3uqzIzRTh8tt99FJPg7GeK9
S8UYfXuXLeBVTYJ7Pv/WVn8ZoTcPn9ZG1ZJg8nEDR9aUEapJfO+d8pQEtLQX
8gJDRuiipdCzzkYShOw4VMxERkiu+kyAfhcJxMbbvLdeNkL7kv/rEviK11+Y
89E/biNEfsQnfWSaBE8uXO15/9MQDfc89m3/QYJNKUGzwWOGyFuIwHp5mQS3
zIydpp4ZosArrTobrNLwI9PRc/KYIbpwTjNtgSwNGs1opxJ+HllkD03spkhD
t2mdv2SlAeJuiNMuo0pDdqfHzfY7BihhfazDX0UaFhIeOZ8INEC3w1L/jelL
w6dyP8VJYQN0/yird7+DNKhV9/jbWeujo/FlFbpO0kB6hdyOaukjjeL9f2+4
SsMjc6v5nRL6qPJr9e3dB6RhfMMv1OmLHqr38m9/GSANLyuv+Gac0EPdLm81
nsZKQx3juR5v0la0YlGwmt0gDerAWxJwRwdFPc2ObmmUhkv9g4dPR+kgFu10
wakWaej9JPDa7T8dxC17TU67Qxqy4opl4mV0kMRqhFXLe2nwJ9iaF2dpI51S
m7Rv89LwS88hXuI2HQWKLxvQqWR45DTOWftCA41NmEU0xZCBz0yglvhPAZll
d91ViSfD6vWqzz/yFFCOy77XN66SwX/5cEiglQJy7wiWP3iLDEalQ77h+H1p
sCKnkz2PDHcCvYPrqPKoN/IfxbKBjL/TCss1jsigJpG69rZlMuz1bPIbYRLQ
3W106deem+Hfll2fxCL/YqWXQkV81WVgNKim51O/Gv4++O/CJS0ZiLs9OFdq
qA5qyxZLeToyYOiUevRYhjoUe4m9GzGUgazSL2nNnhpQhD1K3ceUgag6fa+M
75qQvzovu8tDBjhrFzbV4O+V9ICjGluvy8B6lFW9VrQuxDge3Mn+UwZOJjwl
a9gZwd3dQ26HVmQgM4cvuOCcEdRbOQa2rcvAtWdVoSsVRrC4bfv1eDZZ2J6X
/0hTxBjcaKrvRYVlIVZQiLX/jTFo/170UlCVBUG5RGa65Tb4nHrhlKWnLASx
K7lPcgP+blyPL/SWhcfZZzf8NwOIJZ7I5PWTBZEjEWr92gBW533Q60BZMPzh
xPT4D6DqsDWXU5Qs7GeXsNF7CHDFiHDDJ0UWcieGs1r3mMLWodz7Ma9lQdn6
TP/cBTMQ1vBbKe+WhSufNpfcv2kGM2c1tg+8lQVhpRjf7flmkE99Oq48KAsD
E/Jf1V+YgdiRPtlXk7Lwwflk6F1Oc1iLYt/JxUKBJTZyMed5c/hW4BOSzkqB
gPVYv+lr5tDf1Z6mwU4BNo7syIosc6ikJH1z4qKAusYiy8hTc/BvIV8uFKDA
iZZyw5fL5vCBX69xB5ECTizTp+8csIBW3bRvQyQK3FyONI8OsICq//4IBZMp
wK+o8cvqlAUklTe5p8lS4PiM1bXjNy1gx57df6YUKbC7FK7rtFhAbbqffrw2
BaIyeaK2y1rCveYOd1ldCli1t6gIqlhC8ozG5UdbKcAZvv1qua4lBJn87Pto
QIFu13MzcVaWoDx6PkQNo8DDkiSP68GWkLrlTunrnRQI9+LK7aqzhOUlZkG0
LQW2nN9Uw9FiCbsbFjMMd1MgyFBwZdNrS+DaY51Q4EABBWazX/ZnSwiNWvU/
7UoBg2233z/YsIRuZoGXzn4K/H13X+0sNxPUROz3TblR4LZr7gVFISaMFxRZ
OR6gQDK/fe70ZiY4vHFWVvelwM7Yok4HQyaUpbFTxvwo8LkswaoOYwKvd7lk
mj8FMgpFK5YsmYBWuLg5Aynwtbql6qM9E8jNlf/qjlGg46KSyBVnJkQkuv8K
CqaA54nst7z/MUFTvmZi6AQFAnU38Z/2ZcKVGc9PN8IosLHCbhp0lAmTNYLv
dkRQIP2MoIduMBOydh5qqYqkwHiy/geNU0xYExep9z+N59OvvOp9hgmOI/WP
KGcpIP7zTeyRC0wQCBXLS7iA1/9j14WpOCb4YSjd7CIFzJP7Hh1IZEIz79Eb
K5cokNY886UwiQkyfZJXymIoYHjUaaHhJhNOZTWf947D/RJe1lpwmwn9fsdO
kuIpoBk0z3RLY4K2jnRwdwIFjnwMcx69w4Srf1v9Ll+lQGbc+if9LCZMtYUc
YCRRgPdbCnLLYYLFDRmXxesUIDq8mLC7y4Qct1e7i25SoNbrP12xfCb8oYVt
d79FgfuW6TfvFTDBZUEOE0uhwCiP5HfuQiZUPX2t9yoV1/fHG3mDIiYIXT6p
cS6dAjJP5an695ngb6dI08uggJbgmz6OYia0kno2z2RSwK3oFyUXx/ITUeJ3
synwtn3zAv8DJpwuVxZ0yaWA8ElVTUscD5zs49iURwG6sf8LGxzrWpz705xP
gdeiV7LkcZy0SW355D0KQFZWQSu+3/eB9981i/D8amVaDXDMzIsem7hPgeyD
E98jcD53AzQ/3nmAr5dos8fgfP/pf+y1L6VARGzJiheejytbzCvucgoMPPd4
InAPz69Tu+lZBQX6biLti7gewimfnxyvpIBQaZFDO67XUc8rD7dUUeDqkDP3
EK7nS1W9+8PVuH7cYVg9rrfCry85tx5ToEFedPpwBhPOosTUnU8ocFi28Nc4
Xq/pTyh5tY4CfJ3fw4xSmOC0vpRUWE8BE9eWTR7JeD/o7YtjRxTYvHJtp/hV
JqTsSbz0sBH3Y2Jh370rTGALRuc9mnH/HMnYxh2D6/WAduppKwUEs7Ijdc8y
wbzdNezwSwr4Zk7os0bi/TKZECL5igJJaxF3M8KYcEluyf/4awqs7d7miAXg
/kl5vl+1jwInC4X5dFyYkFm16PzhHe7Xk8ObTjgwgadXcW/MewpU2t8KjrZh
wrBAgs3YIAVczVm0BIEJCRdctt35QoExpmJThwITfmfHG1qN4Xx21Y2fwfvX
61nD1t/juF8SVDVYJJhguKKgsecbBeL1G+QCuPD+CliQ4Z/D17cTJOfHLcE+
XkH6yTwFXnxVXBUdsoT6ImdJ30UKPAsbHOd8awk3x54JNf/E59MWq949yBLA
9QpL5B+cb7TuTEqqJTwIe/ZH+R8Fqtv8N1SvWoJE8vxK/wYFoj8xiFejLeFH
l9OCNrsc6Gtu8q0PsIR0C+roNK8cNJcrlTdilsDp5fQ5lV8OsnOkDFp18Pl4
Nm6QKSiHv4e1hlOVLGF73VzvXWE5eLly7U7RJnweatY375OUg+GS2sCQQQuw
lXYseKUgBwkOJ2ar/SwgdVwD7afJwdhmpfP5+yxgvJTn44ySHMzyh5L8bCwg
CuqFhVTlINmt7nKgpgWUHKJG7aHLgVUEi+fJJXPgq1hwGNomB5avr3FfP24O
Tic7AgIwOThIaJN952UOd80KYv+BHKgFP1yftTcHw3cuDRQLOSiptTXM1zQH
v7XnWw5Zy8HM0pMIiSkzaLO4yjLrJAf8/+05r7zXDAib/KTPusjBI3KJZzeY
gft7Uz3hfXJQU2kksVvdDH4d/nlE+z852B8Qs7OH0wxo19zehx2Ug/eLzYrf
q0zh4geVso1jcvB7r8DdGH5TMA1s2y8SJwcPs96pkfQwWBuYYrZckYNzmoY2
+1kxqDIX0A5PkANaMcucWacJ0Ij2PJ+uyYHzpsQlLk8TEGgZrCq6jX+vnJrh
f3kbDBBnBSFfDiZ2n/L7howh6IUYCnwuB58uXQtQ/a0P2WQvhc6fcsByi3qU
558GGOmoanj9loPei1BrHK4BfVbL+isrclD/aUOTZV4deMIv71T4IwdluoIL
2IgaBPUUh0SxyYMwipStfKoCcHkJqQnJw7czuvwUDxqMzl38L1FZHlpLFCvy
60mg0Fx4e9d+ebCmUXu36nKhJPUmld4GeSCpTMs80NNDRQb7eS8geQjweRVu
Eq+Hnpsvf6U3yYOCKzf2YlgPzbrSCq6/kIcvpaNaxbH6aOflK7L2nfLg8D7J
9NkHA8Q17CDW/UEejt1MuOAdYYwik8b+vl6WB3YF7wkre0A+Sxw97SpUuFjX
cfwGWCL3YosuNzUq2HfZDn4+aImcPC92zKlT4Rr7LQeRGEvEfMPeKk6nwiLP
ayul15aI9oDtqac+FWLXCoSFXJhowoulYNWcCsMPT+om+G1H3r3rEVv+o0LM
c/dUnRAr5BZnHFbvTgXxkPPOD69bob0QeXz3ASooGhSP8j+0QhZlawGhB6kQ
QoxgOM1ZIYUrq16Nh6nAqLCUN/C3RmOmv21cw6igdWN9/6LLTuT1cJESd40K
/QbieU5StujohT1/rK9TIelpEefqVlsUuqfqvcBNKogYjRR777FFsT9Drybd
pkJh3Xmb24m2qMxwdT0lkwpbp5qmXTZs0WrjRv+9B1TItbSqEBjYhdhuHqj0
K6UCdD1rklrchQS8GxNVyqmQUpN05hv/biTDFW1RVkmFp+6WaT0mu5GFNVdl
9RMqfJ/ZxtaYuxsl9QoktrRRQWzzmcwJdTuUnhfgd7mdCsQTKUo/DexQ3oku
8x0dVDDYenNmzNwO1UgkrXV0UWH68pFYd1c7NLRP1O/tOyqYV6s8a75ghyZV
T5jfek8FVk3b3pcJdmjuT5+M8wcqxIcMTD+4bYfYsm+/GxyiwmOb5av8xXZI
aYxoPjpGhefcN66qvbFDWlWnZPInqECxzijaPGCHjC59XD30lQq3iyWyvo/Y
IRulzIqpaSocuaiasHnRDoUcocgsLFBBQEkw7R3BHkUxzq9WLlHh4WPuh/dJ
9uiS4GjfiZ94fU9/TnCVt0ep5XnxKytU8Ij35rWh26O75zh869aoYNlz0Peq
gT16YH/ILOoPFXZRR9hLMHtUJd+62eQfFZRP0RvymfaoYYm2urFBhXu/f4VG
2Nqj/wEDYO+v
     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{{0, 10}, {-100, 100}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], Automatic}]], "Output",
 CellChangeTimes->{{3.530192386189715*^9, 3.530192481019793*^9}, {
   3.530192774862842*^9, 3.530192824761695*^9}, {3.530192929152526*^9, 
   3.530193085565352*^9}, {3.530193116091311*^9, 3.530193122679349*^9}, 
   3.530193182742345*^9, 3.5301932326815968`*^9, 3.5303388364726133`*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{"Clear", "[", 
   RowBox[{
   "deqn", ",", "f", ",", "x", ",", "a", ",", "b", ",", "c", ",", "d", ",", 
    "sol", ",", "g", ",", "fp"}], "]"}], ";"}]], "Input",
 CellChangeTimes->{{3.5303386242006397`*^9, 3.53033865097471*^9}, {
  3.530338759961563*^9, 3.5303387647415047`*^9}, {3.530427511524323*^9, 
  3.530427511712665*^9}}]
}, Open  ]]
}, Open  ]]
}, Open  ]]
},
WindowSize->{1043, 852},
WindowMargins->{{0, Automatic}, {Automatic, 0}},
PrintingCopies->1,
PrintingPageRange->{1, Automatic},
ShowSelection->True,
FrontEndVersion->"8.0 for Mac OS X x86 (32-bit, 64-bit Kernel) (October 5, \
2011)",
StyleDefinitions->"Default.nb"
]
(* End of Notebook Content *)

(* Internal cache information *)
(*CellTagsOutline
CellTagsIndex->{
 "Info3530337229-1666942"->{
  Cell[6702, 180, 463, 11, 39, "Print",
   CellTags->"Info3530337229-1666942"]},
 "Info3530337230-1666942"->{
  Cell[7368, 202, 1770, 30, 55, "Print",
   CellTags->"Info3530337230-1666942"]},
 "Info3530342477-3033539"->{
  Cell[221525, 6714, 1742, 30, 55, "Print",
   CellTags->"Info3530342477-3033539"]}
 }
*)
(*CellTagsIndex
CellTagsIndex->{
 {"Info3530337229-1666942", 1246409, 24542},
 {"Info3530337230-1666942", 1246519, 24545},
 {"Info3530342477-3033539", 1246630, 24548}
 }
*)
(*NotebookFileOutline
Notebook[{
Cell[CellGroupData[{
Cell[422, 15, 148, 2, 76, "Title"],
Cell[573, 19, 1672, 34, 161, "Text"],
Cell[CellGroupData[{
Cell[2270, 57, 294, 5, 17, "ItemParagraph"],
Cell[2567, 64, 584, 13, 33, "Item"],
Cell[3154, 79, 261, 7, 20, "Item"],
Cell[3418, 88, 283, 4, 20, "Item"],
Cell[CellGroupData[{
Cell[3726, 96, 437, 8, 20, "Subsubitem"],
Cell[4166, 106, 330, 9, 20, "Subsubitem"],
Cell[4499, 117, 741, 19, 33, "Subsubitem"],
Cell[5243, 138, 565, 14, 33, "Subsubitem"]
}, Open  ]],
Cell[5823, 155, 678, 14, 46, "Item"]
}, Open  ]],
Cell[CellGroupData[{
Cell[6538, 174, 161, 4, 27, "Input"],
Cell[6702, 180, 463, 11, 39, "Print",
 CellTags->"Info3530337229-1666942"]
}, Open  ]],
Cell[CellGroupData[{
Cell[7202, 196, 163, 4, 27, "Input"],
Cell[7368, 202, 1770, 30, 55, "Print",
 CellTags->"Info3530337230-1666942"]
}, Open  ]],
Cell[CellGroupData[{
Cell[9175, 237, 143, 3, 27, "Input"],
Cell[9321, 242, 3378, 84, 73, "Print"]
}, Open  ]],
Cell[CellGroupData[{
Cell[12736, 331, 245, 4, 17, "ItemParagraph"],
Cell[12984, 337, 172, 3, 20, "Item"],
Cell[13159, 342, 157, 3, 20, "Item"],
Cell[13319, 347, 185, 3, 20, "Item"],
Cell[13507, 352, 170, 3, 20, "Item"],
Cell[13680, 357, 218, 3, 20, "Item"],
Cell[13901, 362, 273, 6, 33, "Item"],
Cell[14177, 370, 169, 3, 20, "Item"],
Cell[14349, 375, 166, 3, 20, "Item"],
Cell[14518, 380, 136, 3, 20, "Item"]
}, Open  ]],
Cell[14669, 386, 967, 21, 86, "Text"],
Cell[CellGroupData[{
Cell[15661, 411, 196, 3, 46, "Subtitle"],
Cell[15860, 416, 347, 9, 26, "Subsubtitle"],
Cell[CellGroupData[{
Cell[16232, 429, 241, 4, 24, "Subsubsection"],
Cell[16476, 435, 925, 21, 41, "Text"],
Cell[CellGroupData[{
Cell[17426, 460, 143, 3, 27, "Input"],
Cell[17572, 465, 166, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[17775, 474, 144, 3, 27, "Input"],
Cell[17922, 479, 169, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[18128, 488, 188, 5, 27, "Input"],
Cell[18319, 495, 215, 5, 47, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[18571, 505, 144, 3, 27, "Input"],
Cell[18718, 510, 172, 4, 27, "Output"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[18939, 520, 188, 3, 24, "Subsubsection"],
Cell[19130, 525, 547, 13, 26, "Text"],
Cell[CellGroupData[{
Cell[19702, 542, 93, 1, 27, "Input"],
Cell[19798, 545, 185, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[20020, 554, 93, 1, 27, "Input"],
Cell[20116, 557, 183, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[20336, 566, 122, 2, 27, "Input"],
Cell[20461, 570, 175, 4, 27, "Output"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[20685, 580, 161, 3, 24, "Subsubsection"],
Cell[20849, 585, 600, 15, 56, "Text"],
Cell[CellGroupData[{
Cell[21474, 604, 174, 4, 27, "Input"],
Cell[21651, 610, 210, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[21898, 619, 147, 3, 27, "Input"],
Cell[22048, 624, 184, 4, 27, "Output"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[22281, 634, 213, 4, 24, "Subsubsection"],
Cell[CellGroupData[{
Cell[22519, 642, 357, 9, 20, "Item"],
Cell[22879, 653, 301, 6, 20, "Item"],
Cell[23183, 661, 232, 7, 20, "Item"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[23464, 674, 177, 3, 24, "Subsubsection"],
Cell[23644, 679, 408, 12, 26, "Text"],
Cell[24055, 693, 303, 11, 26, "Text"],
Cell[CellGroupData[{
Cell[24383, 708, 203, 5, 27, "Input"],
Cell[24589, 715, 265, 4, 27, "Output"]
}, Open  ]],
Cell[24869, 722, 297, 8, 26, "Text"],
Cell[CellGroupData[{
Cell[25191, 734, 163, 3, 27, "Input"],
Cell[25357, 739, 142, 3, 47, "Output"]
}, Open  ]],
Cell[25514, 745, 182, 4, 26, "Text"]
}, Open  ]],
Cell[CellGroupData[{
Cell[25733, 754, 277, 4, 26, "Subsubtitle"],
Cell[CellGroupData[{
Cell[26035, 762, 163, 3, 24, "Subsubsection"],
Cell[CellGroupData[{
Cell[26223, 769, 247, 4, 27, "Input"],
Cell[26473, 775, 252, 7, 32, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[26762, 787, 137, 3, 27, "Input"],
Cell[26902, 792, 171, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[27110, 801, 200, 3, 27, "Input"],
Cell[27313, 806, 210, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[27560, 815, 226, 4, 27, "Input"],
Cell[27789, 821, 213, 4, 27, "Output"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[28051, 831, 164, 3, 24, "Subsubsection"],
Cell[CellGroupData[{
Cell[28240, 838, 213, 4, 27, "Input"],
Cell[28456, 844, 170, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[28663, 853, 234, 5, 27, "Input"],
Cell[28900, 860, 210, 5, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[29147, 870, 240, 5, 27, "Input"],
Cell[29390, 877, 171, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[29598, 886, 255, 4, 27, "Input"],
Cell[29856, 892, 211, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[30104, 901, 216, 4, 27, "Input"],
Cell[30323, 907, 168, 4, 27, "Output"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[30540, 917, 169, 3, 24, "Subsubsection"],
Cell[CellGroupData[{
Cell[30734, 924, 271, 5, 27, "Input"],
Cell[31008, 931, 220, 5, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[31265, 941, 197, 3, 27, "Input"],
Cell[31465, 946, 192, 4, 27, "Output"]
}, Open  ]],
Cell[31672, 953, 318, 13, 26, "Text"]
}, Open  ]],
Cell[CellGroupData[{
Cell[32027, 971, 165, 3, 24, "Subsubsection"],
Cell[CellGroupData[{
Cell[32217, 978, 222, 4, 27, "Input"],
Cell[32442, 984, 189, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[32668, 993, 124, 3, 27, "Input"],
Cell[32795, 998, 262, 5, 27, "Output"]
}, Open  ]],
Cell[33072, 1006, 305, 13, 26, "Text"]
}, Open  ]],
Cell[CellGroupData[{
Cell[33414, 1024, 158, 3, 24, "Subsubsection"],
Cell[33575, 1029, 197, 3, 27, "Input"],
Cell[CellGroupData[{
Cell[33797, 1036, 250, 4, 27, "Input"],
Cell[34050, 1042, 263, 5, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[34350, 1052, 182, 3, 27, "Input"],
Cell[34535, 1057, 239, 5, 27, "Output"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[34823, 1068, 193, 4, 24, "Subsubsection"],
Cell[CellGroupData[{
Cell[35041, 1076, 231, 3, 20, "Item"],
Cell[35275, 1081, 344, 11, 20, "Item"],
Cell[35622, 1094, 295, 10, 33, "Item"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[35966, 1110, 177, 3, 24, "Subsubsection"],
Cell[CellGroupData[{
Cell[36168, 1117, 147, 3, 27, "Input"],
Cell[36318, 1122, 94, 1, 27, "Output"]
}, Open  ]],
Cell[36427, 1126, 311, 11, 26, "Text"],
Cell[CellGroupData[{
Cell[36763, 1141, 125, 2, 27, "Input"],
Cell[36891, 1145, 92, 1, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[37020, 1151, 128, 2, 27, "Input"],
Cell[37151, 1155, 91, 1, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[37279, 1161, 129, 2, 27, "Input"],
Cell[37411, 1165, 92, 1, 27, "Output"]
}, Open  ]],
Cell[37518, 1169, 943, 31, 56, "Text"],
Cell[38464, 1202, 621, 22, 56, "Text"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[39134, 1230, 275, 4, 26, "Subsubtitle"],
Cell[39412, 1236, 918, 16, 86, "Text"],
Cell[CellGroupData[{
Cell[40355, 1256, 272, 8, 27, "Input"],
Cell[40630, 1266, 404, 8, 27, "Output"]
}, Open  ]],
Cell[41049, 1277, 297, 9, 27, "Input"],
Cell[41349, 1288, 913, 21, 71, "Text"],
Cell[CellGroupData[{
Cell[42287, 1313, 91, 1, 27, "Input"],
Cell[42381, 1316, 205, 3, 27, "Output"]
}, Open  ]],
Cell[42601, 1322, 435, 9, 41, "Text"],
Cell[CellGroupData[{
Cell[43061, 1335, 265, 5, 27, "Input"],
Cell[43329, 1342, 445, 9, 20, "Print"]
}, Open  ]],
Cell[CellGroupData[{
Cell[43811, 1356, 352, 5, 30, "ItemParagraph"],
Cell[44166, 1363, 247, 7, 20, "Item"],
Cell[44416, 1372, 252, 8, 20, "Item"]
}, Open  ]],
Cell[CellGroupData[{
Cell[44705, 1385, 207, 5, 27, "Input"],
Cell[44915, 1392, 116, 1, 30, "Output"]
}, Open  ]],
Cell[45046, 1396, 201, 5, 27, "Input"],
Cell[45250, 1403, 827, 17, 86, "Text"],
Cell[46080, 1422, 396, 10, 41, "Text"],
Cell[CellGroupData[{
Cell[46501, 1436, 1232, 26, 208, "Input"],
Cell[47736, 1464, 108, 1, 27, "Output"],
Cell[47847, 1467, 111, 1, 27, "Output"],
Cell[47961, 1470, 111, 1, 27, "Output"],
Cell[48075, 1473, 113, 1, 27, "Output"],
Cell[48191, 1476, 114, 1, 27, "Output"],
Cell[48308, 1479, 112, 1, 27, "Output"]
}, Open  ]],
Cell[48435, 1483, 982, 18, 101, "Text"],
Cell[49420, 1503, 346, 8, 73, "Input"],
Cell[49769, 1513, 536, 15, 56, "Text"],
Cell[50308, 1530, 177, 4, 27, "Input"],
Cell[CellGroupData[{
Cell[50510, 1538, 165, 3, 24, "Subsubsection"],
Cell[50678, 1543, 918, 22, 41, "Text"]
}, Open  ]],
Cell[CellGroupData[{
Cell[51633, 1570, 177, 3, 24, "Subsubsection"],
Cell[CellGroupData[{
Cell[51835, 1577, 507, 10, 133, "Input"],
Cell[52345, 1589, 120, 2, 27, "Output"],
Cell[52468, 1593, 461, 10, 23, "Message"],
Cell[52932, 1605, 120, 2, 27, "Output"],
Cell[53055, 1609, 120, 2, 27, "Output"],
Cell[53178, 1613, 475, 10, 23, "Message"],
Cell[53656, 1625, 122, 2, 27, "Output"],
Cell[53781, 1629, 506, 11, 23, "Message"],
Cell[54290, 1642, 120, 2, 27, "Output"],
Cell[54413, 1646, 120, 2, 27, "Output"],
Cell[54536, 1650, 462, 10, 23, "Message"],
Cell[55001, 1662, 118, 2, 27, "Output"],
Cell[55122, 1666, 490, 11, 23, "Message"],
Cell[55615, 1679, 119, 2, 27, "Output"]
}, Open  ]],
Cell[55749, 1684, 1135, 27, 71, "Text"],
Cell[56887, 1713, 180, 4, 27, "Input"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[57116, 1723, 254, 4, 26, "Subsubtitle"],
Cell[57373, 1729, 963, 17, 107, "Text"],
Cell[58339, 1748, 454, 11, 56, "Text"],
Cell[CellGroupData[{
Cell[58818, 1763, 1208, 31, 163, "Input"],
Cell[CellGroupData[{
Cell[60051, 1798, 314, 7, 20, "Print"],
Cell[60368, 1807, 366, 8, 20, "Print"],
Cell[60737, 1817, 392, 9, 20, "Print"],
Cell[61132, 1828, 349, 7, 20, "Print"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[61530, 1841, 752, 19, 103, "Input"],
Cell[CellGroupData[{
Cell[62307, 1864, 314, 7, 20, "Print"],
Cell[62624, 1873, 325, 7, 20, "Print"]
}, Open  ]]
}, Open  ]],
Cell[62976, 1884, 785, 15, 86, "Text"],
Cell[63764, 1901, 175, 4, 27, "Input"]
}, Open  ]],
Cell[CellGroupData[{
Cell[63976, 1910, 149, 3, 26, "Subsubtitle"],
Cell[64128, 1915, 1379, 26, 146, "Text"],
Cell[CellGroupData[{
Cell[65532, 1945, 592, 16, 73, "Input"],
Cell[66127, 1963, 210, 5, 27, "Output"],
Cell[66340, 1970, 202, 5, 27, "Output"],
Cell[66545, 1977, 212, 5, 27, "Output"],
Cell[66760, 1984, 263, 7, 27, "Output"]
}, Open  ]],
Cell[67038, 1994, 569, 15, 41, "Text"],
Cell[CellGroupData[{
Cell[67632, 2013, 638, 19, 58, "Input"],
Cell[68273, 2034, 253, 6, 27, "Output"],
Cell[68529, 2042, 353, 10, 27, "Output"]
}, Open  ]],
Cell[68897, 2055, 624, 17, 58, "Input"],
Cell[CellGroupData[{
Cell[69546, 2076, 510, 10, 43, "Input"],
Cell[70059, 2088, 217, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[70313, 2097, 440, 9, 43, "Input"],
Cell[70756, 2108, 172, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[70965, 2117, 368, 8, 43, "Input"],
Cell[71336, 2127, 238, 5, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[71611, 2137, 505, 10, 43, "Input"],
Cell[72119, 2149, 139, 2, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[72295, 2156, 578, 12, 73, "Input"],
Cell[72876, 2170, 194, 3, 27, "Output"],
Cell[73073, 2175, 194, 3, 27, "Output"],
Cell[73270, 2180, 194, 3, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[73501, 2188, 611, 14, 73, "Input"],
Cell[74115, 2204, 196, 3, 27, "Output"],
Cell[74314, 2209, 194, 3, 27, "Output"],
Cell[74511, 2214, 194, 3, 27, "Output"]
}, Open  ]],
Cell[74720, 2220, 841, 21, 86, "Text"],
Cell[75564, 2243, 228, 5, 26, "Text"],
Cell[CellGroupData[{
Cell[75817, 2252, 458, 12, 43, "Input"],
Cell[76278, 2266, 421, 8, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[76736, 2279, 363, 7, 43, "Input"],
Cell[77102, 2288, 378, 8, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[77517, 2301, 316, 7, 43, "Input"],
Cell[77836, 2310, 351, 7, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[78224, 2322, 399, 9, 58, "Input"],
Cell[78626, 2333, 210, 5, 27, "Output"],
Cell[78839, 2340, 175, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[79051, 2349, 478, 10, 43, "Input"],
Cell[79532, 2361, 886, 38, 333, "Output"]
}, Open  ]],
Cell[80433, 2402, 245, 6, 27, "Input"],
Cell[CellGroupData[{
Cell[80703, 2412, 163, 3, 24, "Subsubsection"],
Cell[80869, 2417, 581, 13, 41, "Text"]
}, Open  ]],
Cell[CellGroupData[{
Cell[81487, 2435, 177, 3, 24, "Subsubsection"],
Cell[81667, 2440, 344, 14, 26, "Text"],
Cell[CellGroupData[{
Cell[82036, 2458, 779, 21, 88, "Input"],
Cell[82818, 2481, 803, 13, 43, "Output"]
}, Open  ]],
Cell[83636, 2497, 190, 4, 27, "Input"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[83875, 2507, 187, 2, 26, "Subsubtitle"],
Cell[84065, 2511, 856, 15, 101, "Text"],
Cell[84924, 2528, 407, 10, 86, "Text"],
Cell[CellGroupData[{
Cell[85356, 2542, 417, 12, 58, "Input"],
Cell[85776, 2556, 212, 6, 30, "Output"]
}, Open  ]],
Cell[86003, 2565, 975, 20, 86, "Text"],
Cell[CellGroupData[{
Cell[87003, 2589, 528, 16, 43, "Input"],
Cell[87534, 2607, 380, 11, 30, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[87951, 2623, 512, 13, 88, "Input"],
Cell[88466, 2638, 193, 3, 27, "Output"],
Cell[88662, 2643, 193, 3, 27, "Output"],
Cell[88858, 2648, 191, 3, 27, "Output"]
}, Open  ]],
Cell[89064, 2654, 290, 7, 27, "Input"],
Cell[CellGroupData[{
Cell[89379, 2665, 212, 4, 24, "Subsubsection"],
Cell[89594, 2671, 764, 16, 56, "Text"]
}, Open  ]],
Cell[CellGroupData[{
Cell[90395, 2692, 175, 3, 24, "Subsubsection"],
Cell[CellGroupData[{
Cell[90595, 2699, 876, 28, 58, "Input"],
Cell[91474, 2729, 1227, 36, 49, "Output"],
Cell[92704, 2767, 1831, 59, 61, "Output"]
}, Open  ]],
Cell[94550, 2829, 189, 4, 27, "Input"]
}, Open  ]]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[94800, 2840, 249, 3, 46, "Subtitle"],
Cell[95052, 2845, 92, 1, 27, "Input"],
Cell[CellGroupData[{
Cell[95169, 2850, 254, 4, 26, "Subsubtitle"],
Cell[95426, 2856, 855, 20, 41, "Text"],
Cell[CellGroupData[{
Cell[96306, 2880, 147, 3, 27, "Input"],
Cell[96456, 2885, 74, 1, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[96567, 2891, 146, 3, 27, "Input"],
Cell[96716, 2896, 73, 1, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[96826, 2902, 227, 6, 27, "Input"],
Cell[97056, 2910, 98, 1, 27, "Output"]
}, Open  ]],
Cell[97169, 2914, 134, 2, 26, "Text"],
Cell[CellGroupData[{
Cell[97328, 2920, 413, 10, 27, "Input"],
Cell[97744, 2932, 230, 6, 30, "Output"]
}, Open  ]],
Cell[97989, 2941, 435, 12, 41, "Text"],
Cell[CellGroupData[{
Cell[98449, 2957, 350, 7, 27, "Input"],
Cell[98802, 2966, 790, 25, 55, "Output"]
}, Open  ]],
Cell[99607, 2994, 405, 7, 41, "Text"],
Cell[CellGroupData[{
Cell[100037, 3005, 222, 6, 27, "Input"],
Cell[100262, 3013, 326, 10, 55, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[100625, 3028, 225, 6, 27, "Input"],
Cell[100853, 3036, 336, 10, 55, "Output"]
}, Open  ]],
Cell[101204, 3049, 460, 13, 41, "Text"],
Cell[101667, 3064, 331, 9, 27, "Input"],
Cell[CellGroupData[{
Cell[102023, 3077, 198, 5, 27, "Input"],
Cell[102224, 3084, 454, 10, 23, "Message"],
Cell[102681, 3096, 216, 6, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[102934, 3107, 218, 5, 27, "Input"],
Cell[103155, 3114, 187, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[103379, 3123, 603, 13, 43, "Input"],
Cell[103985, 3138, 165, 3, 27, "Output"]
}, Open  ]],
Cell[104165, 3144, 647, 13, 86, "Text"],
Cell[104815, 3159, 279, 3, 26, "Text"],
Cell[105097, 3164, 428, 9, 27, "Input"],
Cell[CellGroupData[{
Cell[105550, 3177, 191, 4, 24, "Subsubsection"],
Cell[105744, 3183, 453, 8, 41, "Text"]
}, Open  ]],
Cell[CellGroupData[{
Cell[106234, 3196, 174, 3, 24, "Subsubsection"],
Cell[CellGroupData[{
Cell[106433, 3203, 507, 14, 27, "Input"],
Cell[106943, 3219, 356, 9, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[107336, 3233, 315, 9, 27, "Input"],
Cell[107654, 3244, 13940, 236, 231, "Output"]
}, Open  ]]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[121655, 3487, 201, 3, 26, "Subsubtitle"],
Cell[121859, 3492, 403, 9, 41, "Text"],
Cell[CellGroupData[{
Cell[122287, 3505, 274, 7, 27, "Input"],
Cell[122564, 3514, 470, 14, 30, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[123071, 3533, 218, 5, 27, "Input"],
Cell[123292, 3540, 264, 8, 33, "Output"]
}, Open  ]],
Cell[123571, 3551, 289, 6, 41, "Text"],
Cell[CellGroupData[{
Cell[123885, 3561, 329, 10, 27, "Input"],
Cell[124217, 3573, 389, 13, 53, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[124643, 3591, 270, 7, 27, "Input"],
Cell[124916, 3600, 360, 12, 52, "Output"]
}, Open  ]],
Cell[125291, 3615, 572, 13, 56, "Text"],
Cell[CellGroupData[{
Cell[125888, 3632, 600, 18, 27, "Input"],
Cell[126491, 3652, 548, 18, 46, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[127076, 3675, 630, 18, 27, "Input"],
Cell[127709, 3695, 153, 4, 46, "Output"]
}, Open  ]],
Cell[127877, 3702, 644, 16, 56, "Text"],
Cell[CellGroupData[{
Cell[128546, 3722, 576, 16, 58, "Input"],
Cell[129125, 3740, 157, 4, 39, "Output"],
Cell[129285, 3746, 122, 2, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[129444, 3753, 1003, 25, 73, "Input"],
Cell[130450, 3780, 268, 5, 33, "Output"],
Cell[130721, 3787, 197, 3, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[130955, 3795, 734, 21, 43, "Input"],
Cell[131692, 3818, 343, 10, 30, "Output"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[132084, 3834, 191, 2, 26, "Subsubtitle"],
Cell[CellGroupData[{
Cell[132300, 3840, 119, 2, 34, "Subsection"],
Cell[132422, 3844, 554, 12, 56, "Text"],
Cell[132979, 3858, 198, 3, 26, "Text"],
Cell[CellGroupData[{
Cell[133202, 3865, 474, 13, 58, "Input"],
Cell[133679, 3880, 178, 4, 27, "Output"],
Cell[133860, 3886, 176, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[134073, 3895, 341, 9, 43, "Input"],
Cell[134417, 3906, 141, 3, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[134595, 3914, 689, 20, 58, "Input"],
Cell[135287, 3936, 269, 8, 33, "Output"],
Cell[135559, 3946, 262, 7, 33, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[135858, 3958, 440, 12, 43, "Input"],
Cell[136301, 3972, 621, 20, 30, "Output"]
}, Open  ]],
Cell[136937, 3995, 360, 8, 41, "Text"],
Cell[CellGroupData[{
Cell[137322, 4007, 348, 9, 27, "Input"],
Cell[137673, 4018, 529, 17, 30, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[138239, 4040, 165, 3, 24, "Subsubsection"],
Cell[138407, 4045, 875, 19, 72, "Text"]
}, Open  ]],
Cell[CellGroupData[{
Cell[139319, 4069, 175, 3, 24, "Subsubsection"],
Cell[139497, 4074, 933, 25, 73, "Input"],
Cell[CellGroupData[{
Cell[140455, 4103, 488, 14, 43, "Input"],
Cell[140946, 4119, 357, 7, 27, "Output"],
Cell[141306, 4128, 330, 6, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[141673, 4139, 588, 15, 43, "Input"],
Cell[142264, 4156, 271, 4, 27, "Output"],
Cell[142538, 4162, 271, 4, 27, "Output"]
}, Open  ]],
Cell[142824, 4169, 172, 3, 26, "Text"],
Cell[CellGroupData[{
Cell[143021, 4176, 488, 14, 43, "Input"],
Cell[143512, 4192, 552, 18, 56, "Output"],
Cell[144067, 4212, 372, 11, 53, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[144476, 4228, 584, 15, 73, "Input"],
Cell[145063, 4245, 1321, 44, 56, "Output"],
Cell[146387, 4291, 195, 3, 27, "Output"],
Cell[146585, 4296, 1355, 46, 56, "Output"],
Cell[147943, 4344, 196, 3, 27, "Output"]
}, Open  ]],
Cell[148154, 4350, 363, 7, 26, "Text"],
Cell[CellGroupData[{
Cell[148542, 4361, 541, 15, 43, "Input"],
Cell[149086, 4378, 285, 9, 39, "Output"],
Cell[149374, 4389, 151, 3, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[149562, 4397, 814, 19, 73, "Input"],
Cell[150379, 4418, 410, 12, 54, "Output"],
Cell[150792, 4432, 335, 9, 54, "Output"],
Cell[151130, 4443, 449, 14, 54, "Output"],
Cell[151582, 4459, 335, 9, 54, "Output"]
}, Open  ]],
Cell[151932, 4471, 199, 3, 26, "Text"],
Cell[152134, 4476, 492, 10, 27, "Input"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[152675, 4492, 125, 2, 34, "Subsection"],
Cell[152803, 4496, 348, 9, 41, "Text"],
Cell[CellGroupData[{
Cell[153176, 4509, 420, 12, 43, "Input"],
Cell[153599, 4523, 323, 10, 50, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[153959, 4538, 850, 24, 88, "Input"],
Cell[154812, 4564, 219, 4, 27, "Output"],
Cell[155034, 4570, 392, 10, 30, "Output"],
Cell[155429, 4582, 221, 4, 27, "Output"],
Cell[155653, 4588, 272, 6, 50, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[155962, 4599, 1262, 40, 88, "Input"],
Cell[157227, 4641, 428, 11, 49, "Output"],
Cell[157658, 4654, 326, 8, 27, "Output"],
Cell[157987, 4664, 662, 20, 67, "Output"],
Cell[158652, 4686, 1222, 37, 44, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[159911, 4728, 1654, 47, 103, "Input"],
Cell[161568, 4777, 267, 6, 27, "Output"],
Cell[161838, 4785, 219, 4, 27, "Output"],
Cell[162060, 4791, 225, 4, 27, "Output"],
Cell[162288, 4797, 234, 5, 32, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[162559, 4807, 121, 2, 24, "Subsubsection"],
Cell[162683, 4811, 389, 9, 41, "Text"]
}, Open  ]],
Cell[CellGroupData[{
Cell[163109, 4825, 135, 2, 24, "Subsubsection"],
Cell[CellGroupData[{
Cell[163269, 4831, 705, 20, 43, "Input"],
Cell[163977, 4853, 138, 2, 27, "Output"]
}, Open  ]]
}, Open  ]]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[164188, 4863, 251, 3, 26, "Subsubtitle"],
Cell[CellGroupData[{
Cell[164464, 4870, 129, 2, 34, "Subsection"],
Cell[164596, 4874, 380, 7, 26, "Text"],
Cell[164979, 4883, 164, 2, 26, "Text"],
Cell[165146, 4887, 740, 15, 71, "Text"],
Cell[CellGroupData[{
Cell[165911, 4906, 380, 9, 43, "Input"],
Cell[166294, 4917, 732, 23, 50, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[167063, 4945, 417, 10, 43, "Input"],
Cell[167483, 4957, 398, 12, 50, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[167918, 4974, 904, 26, 73, "Input"],
Cell[168825, 5002, 418, 11, 30, "Output"],
Cell[169246, 5015, 724, 20, 46, "Output"],
Cell[169973, 5037, 726, 20, 46, "Output"]
}, Open  ]],
Cell[170714, 5060, 410, 12, 41, "Text"],
Cell[CellGroupData[{
Cell[171149, 5076, 592, 17, 43, "Input"],
Cell[171744, 5095, 287, 8, 50, "Output"],
Cell[172034, 5105, 252, 7, 50, "Output"]
}, Open  ]],
Cell[172301, 5115, 490, 10, 56, "Text"],
Cell[CellGroupData[{
Cell[172816, 5129, 447, 13, 27, "Input"],
Cell[173266, 5144, 961, 33, 47, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[174264, 5182, 362, 9, 27, "Input"],
Cell[174629, 5193, 791, 24, 50, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[175457, 5222, 204, 4, 27, "Input"],
Cell[175664, 5228, 1186, 40, 47, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[176887, 5273, 238, 6, 27, "Input"],
Cell[177128, 5281, 1082, 38, 47, "Output"]
}, Open  ]],
Cell[178225, 5322, 216, 5, 27, "Input"],
Cell[178444, 5329, 458, 9, 41, "Text"]
}, Open  ]],
Cell[CellGroupData[{
Cell[178939, 5343, 126, 2, 34, "Subsection"],
Cell[179068, 5347, 587, 16, 71, "Text"],
Cell[CellGroupData[{
Cell[179680, 5367, 488, 14, 43, "Input"],
Cell[180171, 5383, 162, 4, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[180370, 5392, 493, 14, 43, "Input"],
Cell[180866, 5408, 188, 4, 50, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[181091, 5417, 467, 12, 43, "Input"],
Cell[181561, 5431, 165, 2, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[181763, 5438, 825, 22, 58, "Input"],
Cell[182591, 5462, 262, 5, 44, "Output"],
Cell[182856, 5469, 244, 4, 44, "Output"]
}, Open  ]],
Cell[183115, 5476, 179, 4, 27, "Input"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[183343, 5486, 265, 4, 26, "Subsubtitle"],
Cell[183611, 5492, 355, 8, 41, "Text"],
Cell[CellGroupData[{
Cell[183991, 5504, 926, 23, 148, "Input"],
Cell[184920, 5529, 731, 22, 61, "Output"],
Cell[185654, 5553, 730, 21, 61, "Output"]
}, Open  ]],
Cell[186399, 5577, 412, 9, 41, "Text"],
Cell[186814, 5588, 728, 19, 103, "Input"],
Cell[CellGroupData[{
Cell[187567, 5611, 391, 7, 73, "Input"],
Cell[187961, 5620, 121, 2, 27, "Output"],
Cell[188085, 5624, 120, 2, 27, "Output"],
Cell[188208, 5628, 732, 22, 61, "Output"],
Cell[188943, 5652, 710, 20, 61, "Output"]
}, Open  ]],
Cell[189668, 5675, 635, 18, 71, "Text"],
Cell[CellGroupData[{
Cell[190328, 5697, 272, 5, 27, "Input"],
Cell[190603, 5704, 756, 22, 61, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[191396, 5731, 254, 5, 43, "Input"],
Cell[191653, 5738, 930, 29, 79, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[192620, 5772, 167, 3, 27, "Input"],
Cell[192790, 5777, 708, 20, 61, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[193535, 5802, 229, 5, 27, "Input"],
Cell[193767, 5809, 761, 20, 61, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[194565, 5834, 132, 2, 27, "Input"],
Cell[194700, 5838, 109, 2, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[194846, 5845, 127, 2, 27, "Input"],
Cell[194976, 5849, 94, 1, 27, "Output"]
}, Open  ]],
Cell[195085, 5853, 236, 6, 27, "Input"],
Cell[CellGroupData[{
Cell[195346, 5863, 140, 2, 24, "Subsubsection"],
Cell[195489, 5867, 1370, 44, 142, "Text"]
}, Open  ]],
Cell[CellGroupData[{
Cell[196896, 5916, 151, 2, 24, "Subsubsection"],
Cell[CellGroupData[{
Cell[197072, 5922, 734, 22, 43, "Input"],
Cell[197809, 5946, 921, 29, 83, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[198767, 5980, 520, 13, 43, "Input"],
Cell[199290, 5995, 1119, 34, 83, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[200446, 6034, 449, 11, 27, "Input"],
Cell[200898, 6047, 608, 18, 46, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[201543, 6070, 3369, 99, 193, "Input"],
Cell[204915, 6171, 3217, 89, 81, "Output"]
}, Open  ]],
Cell[208147, 6263, 361, 14, 26, "Text"],
Cell[CellGroupData[{
Cell[208533, 6281, 513, 11, 58, "Input"],
Cell[209049, 6294, 461, 16, 46, "Output"],
Cell[209513, 6312, 2608, 81, 81, "Output"]
}, Open  ]],
Cell[212136, 6396, 287, 8, 41, "Text"],
Cell[CellGroupData[{
Cell[212448, 6408, 282, 7, 27, "Input"],
Cell[212733, 6417, 487, 16, 46, "Output"]
}, Open  ]],
Cell[213235, 6436, 482, 9, 27, "Input"]
}, Open  ]],
Cell[CellGroupData[{
Cell[213754, 6450, 189, 6, 24, "Subsubsection"],
Cell[213946, 6458, 742, 17, 41, "Text"],
Cell[CellGroupData[{
Cell[214713, 6479, 134, 2, 27, "Input"],
Cell[214850, 6483, 311, 6, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[215198, 6494, 184, 3, 27, "Input"],
Cell[215385, 6499, 229, 6, 27, "Output"]
}, Open  ]],
Cell[215629, 6508, 618, 20, 58, "Input"],
Cell[CellGroupData[{
Cell[216272, 6532, 121, 2, 27, "Input"],
Cell[216396, 6536, 249, 7, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[216682, 6548, 191, 3, 43, "Input"],
Cell[216876, 6553, 243, 7, 27, "Output"],
Cell[217122, 6562, 217, 6, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[217376, 6573, 127, 2, 27, "Input"],
Cell[217506, 6577, 263, 7, 49, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[217806, 6589, 127, 2, 27, "Input"],
Cell[217936, 6593, 264, 6, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[218237, 6604, 122, 2, 27, "Input"],
Cell[218362, 6608, 367, 12, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[218766, 6625, 171, 4, 27, "Input"],
Cell[218940, 6631, 368, 12, 27, "Output"]
}, Open  ]],
Cell[219323, 6646, 690, 16, 43, "Input"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[220062, 6668, 287, 4, 26, "Subsubtitle"],
Cell[220352, 6674, 496, 11, 56, "Text"],
Cell[CellGroupData[{
Cell[220873, 6689, 257, 6, 34, "Subsection"],
Cell[221133, 6697, 251, 9, 26, "Text"],
Cell[CellGroupData[{
Cell[221409, 6710, 113, 2, 27, "Input"],
Cell[221525, 6714, 1742, 30, 55, "Print",
 CellTags->"Info3530342477-3033539"]
}, Open  ]],
Cell[CellGroupData[{
Cell[223304, 6749, 447, 13, 43, "Input"],
Cell[223754, 6764, 17317, 289, 231, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[241108, 7058, 1010, 28, 43, "Input"],
Cell[242121, 7088, 58214, 962, 231, "Output"]
}, Open  ]],
Cell[300350, 8053, 224, 6, 26, "Text"],
Cell[CellGroupData[{
Cell[300599, 8063, 1013, 29, 73, "Input"],
Cell[301615, 8094, 42662, 706, 231, "Output"]
}, Open  ]],
Cell[344292, 8803, 243, 6, 41, "Text"],
Cell[CellGroupData[{
Cell[344560, 8813, 214, 4, 27, "Input"],
Cell[344777, 8819, 4505, 148, 933, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[349319, 8972, 409, 11, 17, "ItemParagraph"],
Cell[349731, 8985, 467, 11, 20, "Item"],
Cell[350201, 8998, 445, 12, 20, "Item"],
Cell[350649, 9012, 475, 10, 20, "Item"],
Cell[351127, 9024, 506, 13, 20, "Item"],
Cell[351636, 9039, 744, 14, 33, "Item"],
Cell[352383, 9055, 392, 9, 33, "Item"],
Cell[352778, 9066, 180, 6, 20, "Item"]
}, Open  ]],
Cell[352973, 9075, 473, 10, 56, "Text"],
Cell[CellGroupData[{
Cell[353471, 9089, 185, 3, 17, "ItemParagraph"],
Cell[353659, 9094, 449, 12, 20, "Item"],
Cell[354111, 9108, 558, 15, 20, "Item"],
Cell[354672, 9125, 485, 11, 20, "Item"],
Cell[355160, 9138, 616, 21, 46, "Item"]
}, Open  ]],
Cell[355791, 9162, 186, 6, 26, "Text"],
Cell[CellGroupData[{
Cell[356002, 9172, 2141, 52, 208, "Input"],
Cell[358146, 9226, 58610, 971, 225, "Output"]
}, Open  ]],
Cell[416771, 10200, 336, 8, 41, "Text"],
Cell[CellGroupData[{
Cell[417132, 10212, 2071, 66, 88, "Input"],
Cell[419206, 10280, 3154, 57, 235, "Output"],
Cell[422363, 10339, 3169, 57, 235, "Output"],
Cell[425535, 10398, 3373, 60, 231, "Output"],
Cell[428911, 10460, 3435, 62, 232, "Output"],
Cell[432349, 10524, 2534, 46, 236, "Output"]
}, Open  ]],
Cell[434898, 10573, 196, 4, 27, "Input"]
}, Open  ]],
Cell[CellGroupData[{
Cell[435131, 10582, 209, 5, 35, "Subsection"],
Cell[CellGroupData[{
Cell[435365, 10591, 532, 15, 43, "Input"],
Cell[435900, 10608, 1891, 37, 242, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[437828, 10650, 323, 8, 27, "Input"],
Cell[438154, 10660, 34123, 570, 405, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[472314, 11235, 705, 18, 27, "Input"],
Cell[473022, 11255, 46532, 769, 370, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[519591, 12029, 527, 14, 27, "Input"],
Cell[520121, 12045, 232667, 3889, 381, 178196, 2994, "CachedBoxData", \
"BoxData", "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[752825, 15939, 527, 14, 27, "Input"],
Cell[753355, 15955, 32206, 538, 381, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[785598, 16498, 850, 27, 27, "Input"],
Cell[786451, 16527, 36380, 692, 367, "Output"]
}, Open  ]],
Cell[822846, 17222, 529, 14, 41, "Text"],
Cell[CellGroupData[{
Cell[823400, 17240, 1124, 31, 43, "Input"],
Cell[824527, 17273, 2136, 42, 446, "Output"]
}, Open  ]],
Cell[826678, 17318, 144, 3, 27, "Input"]
}, Open  ]],
Cell[CellGroupData[{
Cell[826859, 17326, 137, 2, 34, "Subsection"],
Cell[CellGroupData[{
Cell[827021, 17332, 565, 17, 27, "Input"],
Cell[827589, 17351, 354807, 5859, 279, 145752, 2429, "CachedBoxData", \
"BoxData", "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[1182433, 23215, 940, 28, 43, "Input"],
Cell[1183376, 23245, 2153, 42, 396, "Output"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[1185578, 23293, 137, 2, 34, "Subsection"],
Cell[CellGroupData[{
Cell[1185740, 23299, 1930, 55, 103, "Input"],
Cell[1187673, 23356, 730, 16, 447, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[1188440, 23377, 1574, 41, 88, "Input"],
Cell[1190017, 23420, 687, 12, 413, "Output"]
}, Open  ]],
Cell[1190719, 23435, 94, 1, 27, "Input"]
}, Open  ]]
}, Open  ]],
Cell[CellGroupData[{
Cell[1190862, 23442, 365, 5, 26, "Subsubtitle"],
Cell[1191230, 23449, 660, 15, 41, "Text"],
Cell[1191893, 23466, 969, 28, 56, "Text"],
Cell[1192865, 23496, 231, 4, 26, "Text"],
Cell[CellGroupData[{
Cell[1193121, 23504, 441, 14, 27, "Input"],
Cell[1193565, 23520, 572, 16, 27, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[1194174, 23541, 292, 6, 27, "Input"],
Cell[1194469, 23549, 1218, 36, 61, "Output"]
}, Open  ]],
Cell[1195702, 23588, 537, 13, 41, "Text"],
Cell[1196242, 23603, 355, 7, 41, "Text"],
Cell[CellGroupData[{
Cell[1196622, 23614, 1397, 35, 103, "Input"],
Cell[1198022, 23651, 805, 25, 54, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[1198864, 23681, 207, 5, 27, "Input"],
Cell[1199074, 23688, 24313, 404, 231, "Output"]
}, Open  ]],
Cell[1223402, 24095, 396, 7, 41, "Text"],
Cell[CellGroupData[{
Cell[1223823, 24106, 516, 15, 27, "Input"],
Cell[1224342, 24123, 618, 17, 27, "Output"]
}, Open  ]],
Cell[1224975, 24143, 2385, 57, 118, "Input"],
Cell[CellGroupData[{
Cell[1227385, 24204, 629, 13, 27, "Input"],
Cell[1228017, 24219, 17582, 293, 238, "Output"]
}, Open  ]],
Cell[1245614, 24515, 362, 8, 27, "Input"]
}, Open  ]]
}, Open  ]]
}, Open  ]]
}
]
*)