diff --git a/Graph Algorithms/Centroid Decomposition.cpp b/Graph Algorithms/Centroid Decomposition.cpp
new file mode 100644
index 0000000..6441b74
--- /dev/null
+++ b/Graph Algorithms/Centroid Decomposition.cpp	
@@ -0,0 +1,35 @@
+#include <bits/stdc++.h>
+using namespace std;
+
+const int N = 1e5 + 1;
+const int K = 20;
+
+int n,m;
+vector<int> adj[N];
+int sz[N],pa[N];
+bool blocked[N];
+int res[N],dp[K][N],lv[N];
+
+void dfs(int u,int p)
+{
+    sz[u] = 1;
+    for(int v : adj[u]) if(v!=p and !blocked[v]) dfs(v,u),sz[u]+=sz[v];
+}
+ 
+void build(int u,int cp)
+{
+    dfs(u,0);
+    int c = u,prev = 0;
+    while(true)
+    {
+        int mx = -1,id;
+        for(int v : adj[c]) if(!blocked[v] and v!=prev) if(sz[v]>mx) mx = sz[v],id = v;
+        if(mx*2>sz[u]) prev = c,c = id;
+        else break;
+    }
+    pa[c] = cp;
+    blocked[c] = true;
+    for(int v : adj[c]) if(!blocked[v]) build(v,c);
+}
+
+void update_and_query(int x){ for(int u = x;u;u = pa[u]); } // go up on parent in centroid tree for update and query
diff --git a/verMay23-2.ipynb b/verMay23-2.ipynb
new file mode 100644
index 0000000..818c3dc
--- /dev/null
+++ b/verMay23-2.ipynb
@@ -0,0 +1,752 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "startup.ipynb",
+      "provenance": [],
+      "collapsed_sections": [],
+      "mount_file_id": "13InW790IWIvDA9KY-LXT_KlObk5wcdxX",
+      "authorship_tag": "ABX9TyO5pv+rSIXAtd78Xhw68bgE",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/Autoratch/Algorithms/blob/master/verMay23-2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from google.colab import drive\n",
+        "drive.mount('/content/drive')"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "jWlTS7WDk7cy",
+        "outputId": "e10afde3-9cc6-4524-d3d1-7647fb0475c4"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 54,
+      "metadata": {
+        "id": "S-E7wvs-ixAn"
+      },
+      "outputs": [],
+      "source": [
+        "import csv\n",
+        "import math\n",
+        "from datetime import datetime,timedelta\n",
+        "import matplotlib.pyplot as plt\n",
+        "import numpy as np\n",
+        "\n",
+        "# default param val\n",
+        "platform = \"MT\"\n",
+        "forexpair = \"EURUSD\"\n",
+        "forextype = \"M1\"\n",
+        "yearmonth = \"202204\"\n",
+        "datafilepath = \"/content/drive/My Drive/Colab Notebooks/forex_historical_data/DAT_\"+platform+\"_\"+forexpair+\"_\"+forextype+\"_\"+yearmonth+\".csv\"\n",
+        "paramfilepath = \"/content/drive/My Drive/Colab Notebooks/parameter.csv\"\n",
+        "forexfilepath = \"/content/drive/My Drive/Colab Notebooks/forex.csv\"\n",
+        "bbVal = 20\n",
+        "sdVal = 2\n",
+        "rsiVal = 14\n",
+        "width = 5\n",
+        "rsiUpperLim = 70\n",
+        "rsiLowerLim = 30\n",
+        "martingale = 0\n",
+        "\n",
+        "header = [\"date\",\"time\",\"open\",\"high\",\"low\",\"close\"]\n",
+        "allData = [] # list of data\n",
+        "dayData = [] # list of each day containing list of data\n",
+        "weekData = [] # list of each week containing list of data\n",
+        "weekDataK = [] # list of each week containing list of data with width of K\n",
+        "bbDataK = [] # list of each week containing list of bb data with width of K\n",
+        "rsiDataK = [] # list of each week containing list of rsi data with width of K\n",
+        "dataIdx = [] # idx corresponding to itself\n",
+        "bbDataIdx = [] # idx corresponding to weekDataK\n",
+        "rsiDataIdx = [] # idx corresponding to weekDataK\n",
+        "avaDataIdx = [] # idx of available to indicate signals, combining bb and rsi; corresponding to weekDataK\n",
+        "dataAmount = [] # amount of data in each week\n",
+        "bbAmount = [] # amuount of bb in each week\n",
+        "rsiAmount = [] # amount of rsi in each week\n",
+        "signal = [] # signal for buy or sell; 1 for up, -1 for down\n",
+        "sigSuccess = 0 # no of success signal\n",
+        "sigFail = 0 # no of fail signal\n",
+        "sigAll = 0 # no of all signal\n",
+        "sigPercent = 0\n",
+        "totalDate = 0\n",
+        "totalMin = 0\n",
+        "totalWeek = 0\n",
+        "\n",
+        "class eachData:\n",
+        "  def __init__(self,date,time,open,high,low,close):\n",
+        "    self.date = date\n",
+        "    self.time = time\n",
+        "    self.open = float(open)\n",
+        "    self.high = float(high)\n",
+        "    self.low = float(low)\n",
+        "    self.close = float(close)\n",
+        "  # def print(self):\n",
+        "  #   print(self.date+\" \"+self.time)\n",
+        "  #   print(self.open+\" \"+self.high+\" \"+self.low+\" \"+self.close)\n",
+        "\n",
+        "class eachBB:\n",
+        "  def __init__(self,middle,upper,lower):\n",
+        "    self.middle = middle\n",
+        "    self.upper = upper\n",
+        "    self.lower = lower\n",
+        "\n",
+        "def checkDiff(data1,data2): #check diff between data whether gap exist\n",
+        "  format = \"%Y.%m.%d\"\n",
+        "  datestr1 = datetime.strptime(data1.date,format)\n",
+        "  datestr2 = datetime.strptime(data2.date,format)\n",
+        "  expected = datestr1+timedelta(days=1)\n",
+        "  if datestr2<=expected:\n",
+        "    return 0 # no jump\n",
+        "  else:\n",
+        "    return 1 # gap exists\n",
+        "\n",
+        "def plot(wk):\n",
+        "  #plot data\n",
+        "  data = weekDataK[wk]\n",
+        "  x = dataIdx[wk]\n",
+        "  y = []\n",
+        "  for i in data:\n",
+        "    y.append(i.open)\n",
+        "  plt.plot(x,y) # data open\n",
+        "  y = []\n",
+        "  for i in data:\n",
+        "    y.append(i.close)\n",
+        "  plt.plot(x,y) # data close\n",
+        "  #plot bb\n",
+        "  bb = bbDataK[wk]\n",
+        "  x = bbDataIdx[wk]\n",
+        "  y = []\n",
+        "  for i in x:\n",
+        "    y.append(bb[i].middle)\n",
+        "  plt.plot(x,y) # bb middle\n",
+        "  y = []\n",
+        "  for i in x:\n",
+        "    y.append(bb[i].upper)\n",
+        "  plt.plot(x,y) # bb upper\n",
+        "  y = []\n",
+        "  for i in x:\n",
+        "    y.append(bb[i].lower)\n",
+        "  plt.plot(x,y) # bb lower\n",
+        "  plt.show()\n",
+        "  #plot rsi\n",
+        "  rsi = rsiDataK[wk]\n",
+        "  x = rsiDataIdx[wk]\n",
+        "  y = []\n",
+        "  for i in x:\n",
+        "    y.append(rsi[i])\n",
+        "  plt.plot(x,y) # rsi val\n",
+        "  y = []\n",
+        "  for i in x:\n",
+        "    y.append(rsiUpperLim)\n",
+        "  plt.plot(x,y) # rsi upper\n",
+        "  y = []\n",
+        "  for i in x:\n",
+        "    y.append(rsiLowerLim)\n",
+        "  plt.plot(x,y) # rsi lower\n",
+        "  plt.show()\n",
+        "\n",
+        "# read parameter from csv file\n",
+        "file = open(paramfilepath)\n",
+        "csvreader = csv.reader(file)\n",
+        "for x in csvreader:\n",
+        "  bbVal = int(x[0])\n",
+        "  sdVal = int(x[1])\n",
+        "  rsiVal = int(x[2])\n",
+        "  width = int(x[3])\n",
+        "  rsiUpperLim = int(x[4])\n",
+        "  rsiLowerLim = int(x[5])\n",
+        "  martingale = int(x[6])\n",
+        "file.close()\n",
+        "\n",
+        "# read forex from csv file\n",
+        "file = open(forexfilepath)\n",
+        "csvreader = csv.reader(file)\n",
+        "for x in csvreader:\n",
+        "  forexpair = x[0]\n",
+        "  yearmonth = x[1]\n",
+        "file.close()\n",
+        "datafilepath = \"/content/drive/My Drive/Colab Notebooks/forex_historical_data/DAT_\"+platform+\"_\"+forexpair+\"_\"+forextype+\"_\"+yearmonth+\".csv\"\n",
+        "\n",
+        "# read data from csv file\n",
+        "file = open(datafilepath)\n",
+        "csvreader = csv.reader(file)\n",
+        "for min in csvreader:\n",
+        "  allData.append(eachData(min[0],min[1],min[2],min[3],min[4],min[5]))\n",
+        "file.close()\n",
+        "\n",
+        "# store and organize into days and weeks data list\n",
+        "totalMin = len(allData)  \n",
+        "tmp = \"\"\n",
+        "for min in allData:\n",
+        "  if min.date!=tmp:\n",
+        "    tmp = min.date\n",
+        "    totalDate+=1\n",
+        "for i in range(totalDate):\n",
+        "  dayData.append([])\n",
+        "tmp = \"\"\n",
+        "totalDate = 0\n",
+        "for min in allData:\n",
+        "  if min.date!=tmp:\n",
+        "    tmp = min.date\n",
+        "    totalDate+=1\n",
+        "  dayData[totalDate-1].append(min)\n",
+        "# for today in range(totalDate):\n",
+        "#   print(dayData[today][0].date+\" : \"+dayData[today][0].time+\"->\"+dayData[today][len(dayData[today])-1].time)\n",
+        "first = 1\n",
+        "tmp = []\n",
+        "for i in range(len(allData)):\n",
+        "  if first==1 or checkDiff(allData[i-1],allData[i])==0:\n",
+        "    tmp.append(allData[i])\n",
+        "    first = 0\n",
+        "  else:\n",
+        "    weekData.append(tmp)\n",
+        "    weekDataK.append([])\n",
+        "    bbDataK.append([])\n",
+        "    rsiDataK.append([])\n",
+        "    tmp = []\n",
+        "    tmp.append(allData[i])\n",
+        "if tmp!=[]:\n",
+        "  weekData.append(tmp)\n",
+        "  weekDataK.append([])\n",
+        "  rsiDataK.append([])\n",
+        "  bbDataK.append([])\n",
+        "# print(len(weekData))\n",
+        "totalWeek = len(weekData)\n",
+        "# for i in range(len(weekData)):\n",
+        "#   print(weekData[i][0].date+\" \"+weekData[i][0].time+\" -> \"+weekData[i][len(weekData[i])-1].date+\" \"+weekData[i][len(weekData[i])-1].time)\n",
+        "\n",
+        "for i in range(len(weekData)):\n",
+        "  for j in range(len(weekData[i])):\n",
+        "    if j%width==width-1:\n",
+        "      tmp = weekData[i][j]\n",
+        "      tmp.open = weekData[i][j-width+1].open\n",
+        "      weekDataK[i].append(tmp)\n",
+        "\n",
+        "# for i in range(len(weekDataK)):\n",
+        "#   for j in range(len(weekDataK[i])):\n",
+        "#     tmp = weekDataK[0][j]\n",
+        "#     print(tmp.date+\" \"+tmp.time)\n",
+        "\n",
+        "for i in range(totalWeek):\n",
+        "  dataAmount.append(len(weekDataK[i]))\n",
+        "  bbAmount.append(0)\n",
+        "  rsiAmount.append(0)\n",
+        "\n",
+        "# calculate bollinger band\n",
+        "for i in range(totalWeek):\n",
+        "  each = weekDataK[i]\n",
+        "  for j in range(len(each)):\n",
+        "    if j>=bbVal-1:\n",
+        "      curSum = 0\n",
+        "      for k in range(j-bbVal+1,j): # only 19 in front\n",
+        "        curSum+=float(each[k].close)\n",
+        "      curAvr = curSum/(bbVal-1) \n",
+        "      curSD = 0\n",
+        "      for k in range(j-bbVal+1,j): \n",
+        "        curSD+=(curAvr-float(each[k].close))*(curAvr-float(each[k].close))\n",
+        "      curSD/=(bbVal-1)\n",
+        "      curSD = math.sqrt(curSD)\n",
+        "      curBB = eachBB(curAvr,curAvr+sdVal*curSD,curAvr-sdVal*curSD)\n",
+        "      # print(each[k].close,end=\" \")\n",
+        "      # print(curAvr,end=\" \")\n",
+        "      # print(curAvr+sdVal*curSD,end=\" \")\n",
+        "      # print(curAvr-sdVal*curSD)\n",
+        "      bbDataK[i].append(curBB)\n",
+        "      bbAmount[i]+=1\n",
+        "    else:\n",
+        "      bbDataK[i].append(eachBB(-1,-1,-1))\n",
+        "    \n",
+        "# calculate rsi value\n",
+        "for i in range(totalWeek):\n",
+        "  each = weekDataK[i]\n",
+        "  for j in range(len(each)):\n",
+        "    if j>=rsiVal-1:\n",
+        "      avrGain = 0\n",
+        "      avrLoss = 0\n",
+        "      for k in range(j-rsiVal+1,j+1): # all 14 including the current one\n",
+        "        change = each[k].close-each[k].open\n",
+        "        if change>0:\n",
+        "          avrGain+=change\n",
+        "        else:\n",
+        "          avrLoss-=change\n",
+        "      avrGain/=rsiVal\n",
+        "      avrLoss/=rsiVal\n",
+        "      if avrLoss!=0:\n",
+        "        rs = avrGain/avrLoss\n",
+        "        rsi = 100-(100/(1+rs))\n",
+        "      else:\n",
+        "        rsi = 100\n",
+        "      rsiDataK[i].append(rsi)\n",
+        "      rsiAmount[i]+=1\n",
+        "    else:\n",
+        "      rsiDataK[i].append(-1)\n",
+        "\n",
+        "# create idx of each data bb rsi\n",
+        "for i in range(totalWeek):\n",
+        "  data = weekDataK[i]\n",
+        "  bb = bbDataK[i]\n",
+        "  rsi = rsiDataK[i]\n",
+        "  dataIdx.append(range(dataAmount[i]))\n",
+        "  bbDataIdx.append(range(dataAmount[i]-bbAmount[i],dataAmount[i]))\n",
+        "  rsiDataIdx.append(range(dataAmount[i]-rsiAmount[i],dataAmount[i]))\n",
+        "  avaDataIdx.append(range(max(dataAmount[i]-bbAmount[i],dataAmount[i]-rsiAmount[i]),dataAmount[i]))\n",
+        "  # plot(i)\n",
+        "\n",
+        "# creating and evaluating signal\n",
+        "for i in range(totalWeek):\n",
+        "  signal.append([])\n",
+        "  for j in range(dataAmount[i]):\n",
+        "    signal[i].append(0)\n",
+        "  prevBbSig = -5\n",
+        "  prevRsiSig = -5\n",
+        "  curSideway = 0\n",
+        "  curSuccess = 0\n",
+        "  for j in avaDataIdx[i]:\n",
+        "    if weekDataK[i][j].close>=bbDataK[i][j].upper:\n",
+        "      bbSig = -1\n",
+        "    elif weekDataK[i][j].close<=bbDataK[i][j].lower:\n",
+        "      bbSig = 1\n",
+        "    else:\n",
+        "      bbSig = 0\n",
+        "    if rsiDataK[i][j]>=rsiUpperLim:\n",
+        "      rsiSig = -1\n",
+        "    elif rsiDataK[i][j]<=rsiLowerLim:\n",
+        "      rsiSig = 1\n",
+        "    else:\n",
+        "      rsiSig = 0\n",
+        "    curSig = 0\n",
+        "    if bbSig==rsiSig and bbSig!=0:\n",
+        "      if bbSig!=prevBbSig or rsiSig!=prevRsiSig:\n",
+        "        curSig = bbSig\n",
+        "        curSideway = 0\n",
+        "        curSuccess = 0\n",
+        "        sigAll+=1\n",
+        "      else:\n",
+        "        curSideway+=1\n",
+        "        if curSideway<=martingale and curSuccess==0:\n",
+        "          curSig = bbSig\n",
+        "    signal[i][j] = curSig\n",
+        "    prevBbSig = bbSig\n",
+        "    prevRsiSig = rsiSig\n",
+        "    if curSig!=0 and j<dataAmount[i]-1:\n",
+        "      curStatus = -1\n",
+        "      if signal[i][j]==-1 and weekDataK[i][j].close>weekDataK[i][j+1].close:\n",
+        "        curStatus = 1\n",
+        "      if signal[i][j]==1 and weekDataK[i][j].close<weekDataK[i][j+1].close:\n",
+        "        curStatus = 1\n",
+        "      if weekDataK[i][j].close==weekDataK[i][j+1].close:\n",
+        "        curStatus = 0\n",
+        "      if curStatus==0:\n",
+        "        curSideway-=1\n",
+        "      elif curStatus==1:\n",
+        "        curSuccess = 1\n",
+        "        sigSuccess+=1\n",
+        "  #   print(cursig,end = \" \")\n",
+        "  # print()\n",
+        "\n",
+        "sigPercent = sigSuccess/sigAll*100\n",
+        "file = open(\"/content/drive/My Drive/Colab Notebooks/result.csv\",\"w\")\n",
+        "bbP = str(bbVal)\n",
+        "rsiP = str(rsiVal)\n",
+        "sigP = str(sigPercent)\n",
+        "file.write(bbP+\",\"+rsiP+\",\"+sigP)\n",
+        "file.close()\n",
+        "\n",
+        "#print(sigPercent)\n",
+        "    \n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "bbLo = 10\n",
+        "bbHi = 30\n",
+        "sdVal = 2\n",
+        "rsiLo = 8\n",
+        "rsiHi = 20\n",
+        "width = 5\n",
+        "rsiUpperLim = 70\n",
+        "rsiLowerLim = 30\n",
+        "martingale = 1\n",
+        "\n",
+        "def printToFile(bbVal,sdVal,rsiVal,width,rsiUpperLim,rsiLowerLim,martingale):\n",
+        "  bbVal = str(bbVal)\n",
+        "  sdVal = str(sdVal)\n",
+        "  rsiVal = str(rsiVal)\n",
+        "  width = str(width)\n",
+        "  rsiUpperLim = str(rsiUpperLim)\n",
+        "  rsiLowerLim = str(rsiLowerLim)\n",
+        "  martingale = str(martingale)\n",
+        "  filepath = \"/content/drive/My Drive/Colab Notebooks/parameter.csv\"\n",
+        "  file = open(filepath,\"w\")\n",
+        "  file.write(bbVal+\",\"+sdVal+\",\"+rsiVal+\",\"+width+\",\"+rsiUpperLim+\",\"+rsiLowerLim+\",\"+martingale)\n",
+        "  file.close()\n",
+        "\n",
+        "file = open(\"/content/drive/My Drive/Colab Notebooks/forex.csv\",\"w\")\n",
+        "file.write(\"EURJPY,202204\")\n",
+        "file.close()\n",
+        "\n",
+        "bestSigPercent = -1\n",
+        "\n",
+        "for bbVal in range(bbLo,bbHi+1):\n",
+        "  for rsiVal in range(rsiLo,rsiHi+1):\n",
+        "    printToFile(bbVal,sdVal,rsiVal,width,rsiUpperLim,rsiLowerLim,martingale)\n",
+        "    print(\"BB:\",end = \"\")\n",
+        "    print(bbVal,end = \" \")\n",
+        "    print(\"RSI:\",end = \"\")\n",
+        "    if rsiVal<10:\n",
+        "      print(\" \",end=\"\")\n",
+        "    print(rsiVal,end = \"\")\n",
+        "    print(\"; percent accuracy : \",end = \"\")\n",
+        "    exec(open(\"/content/drive/My Drive/Colab Notebooks/run.py\").read())\n",
+        "    file = open(\"/content/drive/My Drive/Colab Notebooks/result.csv\")\n",
+        "    csvreader = csv.reader(file)\n",
+        "    for x in csvreader:\n",
+        "      sigPercent = float(x[2])\n",
+        "    print(sigPercent)\n",
+        "    if sigPercent>bestSigPercent:\n",
+        "      bestSigPercent = sigPercent\n",
+        "      bestBB = bbVal\n",
+        "      bestRSI = rsiVal\n",
+        "\n",
+        "print()\n",
+        "print(\"best parameter config is\")\n",
+        "print(\"BB:\",end = \"\")\n",
+        "print(bestBB,end = \" \")\n",
+        "print(\"RSI:\",end = \"\")\n",
+        "if bestRSI<10:\n",
+        "  print(\" \",end=\"\")\n",
+        "print(bestRSI,end = \"\")\n",
+        "print(\"; percent accuracy : \",end = \"\")\n",
+        "print(bestSigPercent)\n",
+        "    \n"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "uvQ4Hb6WUEpN",
+        "outputId": "8c4988c4-c8fc-4d9f-fe0d-19da6ffa0199"
+      },
+      "execution_count": 70,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "BB:10 RSI: 8; percent accuracy : 74.06639004149378\n",
+            "BB:10 RSI: 9; percent accuracy : 73.47417840375586\n",
+            "BB:10 RSI:10; percent accuracy : 71.64556962025317\n",
+            "BB:10 RSI:11; percent accuracy : 73.92550143266476\n",
+            "BB:10 RSI:12; percent accuracy : 73.4567901234568\n",
+            "BB:10 RSI:13; percent accuracy : 71.72413793103448\n",
+            "BB:10 RSI:14; percent accuracy : 72.47386759581882\n",
+            "BB:10 RSI:15; percent accuracy : 77.32342007434944\n",
+            "BB:10 RSI:16; percent accuracy : 76.98412698412699\n",
+            "BB:10 RSI:17; percent accuracy : 78.57142857142857\n",
+            "BB:10 RSI:18; percent accuracy : 75.25773195876289\n",
+            "BB:10 RSI:19; percent accuracy : 75.0\n",
+            "BB:10 RSI:20; percent accuracy : 76.33136094674556\n",
+            "BB:11 RSI: 8; percent accuracy : 76.80851063829788\n",
+            "BB:11 RSI: 9; percent accuracy : 76.16822429906543\n",
+            "BB:11 RSI:10; percent accuracy : 74.35897435897436\n",
+            "BB:11 RSI:11; percent accuracy : 76.61971830985915\n",
+            "BB:11 RSI:12; percent accuracy : 75.15527950310559\n",
+            "BB:11 RSI:13; percent accuracy : 73.10344827586206\n",
+            "BB:11 RSI:14; percent accuracy : 74.56445993031359\n",
+            "BB:11 RSI:15; percent accuracy : 79.182156133829\n",
+            "BB:11 RSI:16; percent accuracy : 79.03225806451613\n",
+            "BB:11 RSI:17; percent accuracy : 80.53097345132744\n",
+            "BB:11 RSI:18; percent accuracy : 76.53061224489795\n",
+            "BB:11 RSI:19; percent accuracy : 74.86033519553072\n",
+            "BB:11 RSI:20; percent accuracy : 76.19047619047619\n",
+            "BB:12 RSI: 8; percent accuracy : 76.28205128205127\n",
+            "BB:12 RSI: 9; percent accuracy : 76.6743648960739\n",
+            "BB:12 RSI:10; percent accuracy : 73.9240506329114\n",
+            "BB:12 RSI:11; percent accuracy : 77.29885057471265\n",
+            "BB:12 RSI:12; percent accuracy : 75.63291139240506\n",
+            "BB:12 RSI:13; percent accuracy : 72.88732394366197\n",
+            "BB:12 RSI:14; percent accuracy : 73.83512544802868\n",
+            "BB:12 RSI:15; percent accuracy : 78.4090909090909\n",
+            "BB:12 RSI:16; percent accuracy : 78.18930041152264\n",
+            "BB:12 RSI:17; percent accuracy : 79.01785714285714\n",
+            "BB:12 RSI:18; percent accuracy : 76.04166666666666\n",
+            "BB:12 RSI:19; percent accuracy : 76.0\n",
+            "BB:12 RSI:20; percent accuracy : 74.69879518072288\n",
+            "BB:13 RSI: 8; percent accuracy : 75.89285714285714\n",
+            "BB:13 RSI: 9; percent accuracy : 75.88652482269504\n",
+            "BB:13 RSI:10; percent accuracy : 74.02597402597402\n",
+            "BB:13 RSI:11; percent accuracy : 75.65217391304347\n",
+            "BB:13 RSI:12; percent accuracy : 74.03846153846155\n",
+            "BB:13 RSI:13; percent accuracy : 71.73144876325088\n",
+            "BB:13 RSI:14; percent accuracy : 72.92418772563177\n",
+            "BB:13 RSI:15; percent accuracy : 77.77777777777779\n",
+            "BB:13 RSI:16; percent accuracy : 76.98744769874477\n",
+            "BB:13 RSI:17; percent accuracy : 78.18181818181819\n",
+            "BB:13 RSI:18; percent accuracy : 75.93582887700535\n",
+            "BB:13 RSI:19; percent accuracy : 74.85380116959064\n",
+            "BB:13 RSI:20; percent accuracy : 74.21383647798741\n",
+            "BB:14 RSI: 8; percent accuracy : 77.44874715261959\n",
+            "BB:14 RSI: 9; percent accuracy : 76.2589928057554\n",
+            "BB:14 RSI:10; percent accuracy : 73.94736842105263\n",
+            "BB:14 RSI:11; percent accuracy : 75.93123209169055\n",
+            "BB:14 RSI:12; percent accuracy : 75.39936102236422\n",
+            "BB:14 RSI:13; percent accuracy : 73.83512544802868\n",
+            "BB:14 RSI:14; percent accuracy : 74.72924187725631\n",
+            "BB:14 RSI:15; percent accuracy : 77.77777777777779\n",
+            "BB:14 RSI:16; percent accuracy : 78.90295358649789\n",
+            "BB:14 RSI:17; percent accuracy : 79.63800904977376\n",
+            "BB:14 RSI:18; percent accuracy : 78.49462365591397\n",
+            "BB:14 RSI:19; percent accuracy : 77.84431137724552\n",
+            "BB:14 RSI:20; percent accuracy : 75.15923566878982\n",
+            "BB:15 RSI: 8; percent accuracy : 76.12293144208037\n",
+            "BB:15 RSI: 9; percent accuracy : 75.18427518427518\n",
+            "BB:15 RSI:10; percent accuracy : 73.17073170731707\n",
+            "BB:15 RSI:11; percent accuracy : 73.83720930232558\n",
+            "BB:15 RSI:12; percent accuracy : 72.84345047923323\n",
+            "BB:15 RSI:13; percent accuracy : 72.69503546099291\n",
+            "BB:15 RSI:14; percent accuracy : 73.68421052631578\n",
+            "BB:15 RSI:15; percent accuracy : 75.39682539682539\n",
+            "BB:15 RSI:16; percent accuracy : 75.74468085106383\n",
+            "BB:15 RSI:17; percent accuracy : 78.3410138248848\n",
+            "BB:15 RSI:18; percent accuracy : 76.37362637362637\n",
+            "BB:15 RSI:19; percent accuracy : 75.75757575757575\n",
+            "BB:15 RSI:20; percent accuracy : 72.43589743589743\n",
+            "BB:16 RSI: 8; percent accuracy : 75.41766109785203\n",
+            "BB:16 RSI: 9; percent accuracy : 74.2014742014742\n",
+            "BB:16 RSI:10; percent accuracy : 72.99465240641712\n",
+            "BB:16 RSI:11; percent accuracy : 73.5632183908046\n",
+            "BB:16 RSI:12; percent accuracy : 72.44582043343654\n",
+            "BB:16 RSI:13; percent accuracy : 72.91666666666666\n",
+            "BB:16 RSI:14; percent accuracy : 74.72527472527473\n",
+            "BB:16 RSI:15; percent accuracy : 76.5873015873016\n",
+            "BB:16 RSI:16; percent accuracy : 76.47058823529412\n",
+            "BB:16 RSI:17; percent accuracy : 78.63636363636364\n",
+            "BB:16 RSI:18; percent accuracy : 76.28865979381443\n",
+            "BB:16 RSI:19; percent accuracy : 76.47058823529412\n",
+            "BB:16 RSI:20; percent accuracy : 73.75\n",
+            "BB:17 RSI: 8; percent accuracy : 73.96593673965937\n",
+            "BB:17 RSI: 9; percent accuracy : 72.9113924050633\n",
+            "BB:17 RSI:10; percent accuracy : 72.35772357723577\n",
+            "BB:17 RSI:11; percent accuracy : 74.19354838709677\n",
+            "BB:17 RSI:12; percent accuracy : 73.27044025157232\n",
+            "BB:17 RSI:13; percent accuracy : 73.42657342657343\n",
+            "BB:17 RSI:14; percent accuracy : 75.18248175182481\n",
+            "BB:17 RSI:15; percent accuracy : 76.98412698412699\n",
+            "BB:17 RSI:16; percent accuracy : 76.62337662337663\n",
+            "BB:17 RSI:17; percent accuracy : 79.62962962962963\n",
+            "BB:17 RSI:18; percent accuracy : 78.3068783068783\n",
+            "BB:17 RSI:19; percent accuracy : 77.24550898203593\n",
+            "BB:17 RSI:20; percent accuracy : 74.83870967741936\n",
+            "BB:18 RSI: 8; percent accuracy : 74.55012853470437\n",
+            "BB:18 RSI: 9; percent accuracy : 73.17073170731707\n",
+            "BB:18 RSI:10; percent accuracy : 72.59887005649718\n",
+            "BB:18 RSI:11; percent accuracy : 74.77203647416414\n",
+            "BB:18 RSI:12; percent accuracy : 73.61563517915309\n",
+            "BB:18 RSI:13; percent accuracy : 74.28571428571429\n",
+            "BB:18 RSI:14; percent accuracy : 75.64575645756457\n",
+            "BB:18 RSI:15; percent accuracy : 78.714859437751\n",
+            "BB:18 RSI:16; percent accuracy : 76.99115044247787\n",
+            "BB:18 RSI:17; percent accuracy : 80.09708737864078\n",
+            "BB:18 RSI:18; percent accuracy : 78.37837837837837\n",
+            "BB:18 RSI:19; percent accuracy : 77.91411042944786\n",
+            "BB:18 RSI:20; percent accuracy : 76.51006711409396\n",
+            "BB:19 RSI: 8; percent accuracy : 73.9946380697051\n",
+            "BB:19 RSI: 9; percent accuracy : 73.46368715083798\n",
+            "BB:19 RSI:10; percent accuracy : 71.67630057803468\n",
+            "BB:19 RSI:11; percent accuracy : 74.38271604938271\n",
+            "BB:19 RSI:12; percent accuracy : 73.26732673267327\n",
+            "BB:19 RSI:13; percent accuracy : 73.02158273381295\n",
+            "BB:19 RSI:14; percent accuracy : 74.25373134328358\n",
+            "BB:19 RSI:15; percent accuracy : 77.04918032786885\n",
+            "BB:19 RSI:16; percent accuracy : 77.82805429864254\n",
+            "BB:19 RSI:17; percent accuracy : 78.43137254901961\n",
+            "BB:19 RSI:18; percent accuracy : 78.2122905027933\n",
+            "BB:19 RSI:19; percent accuracy : 78.48101265822784\n",
+            "BB:19 RSI:20; percent accuracy : 75.86206896551724\n",
+            "BB:20 RSI: 8; percent accuracy : 73.65439093484419\n",
+            "BB:20 RSI: 9; percent accuracy : 73.48703170028818\n",
+            "BB:20 RSI:10; percent accuracy : 72.23880597014926\n",
+            "BB:20 RSI:11; percent accuracy : 73.81703470031546\n",
+            "BB:20 RSI:12; percent accuracy : 73.4006734006734\n",
+            "BB:20 RSI:13; percent accuracy : 74.28571428571429\n",
+            "BB:20 RSI:14; percent accuracy : 74.43609022556392\n",
+            "BB:20 RSI:15; percent accuracy : 76.85950413223141\n",
+            "BB:20 RSI:16; percent accuracy : 76.47058823529412\n",
+            "BB:20 RSI:17; percent accuracy : 78.43137254901961\n",
+            "BB:20 RSI:18; percent accuracy : 77.52808988764045\n",
+            "BB:20 RSI:19; percent accuracy : 77.12418300653596\n",
+            "BB:20 RSI:20; percent accuracy : 74.82517482517483\n",
+            "BB:21 RSI: 8; percent accuracy : 73.57954545454545\n",
+            "BB:21 RSI: 9; percent accuracy : 73.54651162790698\n",
+            "BB:21 RSI:10; percent accuracy : 73.03030303030303\n",
+            "BB:21 RSI:11; percent accuracy : 73.73417721518987\n",
+            "BB:21 RSI:12; percent accuracy : 73.8255033557047\n",
+            "BB:21 RSI:13; percent accuracy : 74.55197132616487\n",
+            "BB:21 RSI:14; percent accuracy : 74.34944237918215\n",
+            "BB:21 RSI:15; percent accuracy : 75.80645161290323\n",
+            "BB:21 RSI:16; percent accuracy : 75.1111111111111\n",
+            "BB:21 RSI:17; percent accuracy : 76.32850241545893\n",
+            "BB:21 RSI:18; percent accuracy : 74.86033519553072\n",
+            "BB:21 RSI:19; percent accuracy : 74.68354430379746\n",
+            "BB:21 RSI:20; percent accuracy : 72.72727272727273\n",
+            "BB:22 RSI: 8; percent accuracy : 73.77521613832853\n",
+            "BB:22 RSI: 9; percent accuracy : 73.23529411764706\n",
+            "BB:22 RSI:10; percent accuracy : 72.2560975609756\n",
+            "BB:22 RSI:11; percent accuracy : 73.88535031847134\n",
+            "BB:22 RSI:12; percent accuracy : 74.32432432432432\n",
+            "BB:22 RSI:13; percent accuracy : 75.82417582417582\n",
+            "BB:22 RSI:14; percent accuracy : 74.33962264150942\n",
+            "BB:22 RSI:15; percent accuracy : 76.19047619047619\n",
+            "BB:22 RSI:16; percent accuracy : 74.89177489177489\n",
+            "BB:22 RSI:17; percent accuracy : 75.23364485981308\n",
+            "BB:22 RSI:18; percent accuracy : 74.86338797814209\n",
+            "BB:22 RSI:19; percent accuracy : 74.53416149068323\n",
+            "BB:22 RSI:20; percent accuracy : 75.16778523489933\n",
+            "BB:23 RSI: 8; percent accuracy : 73.29376854599407\n",
+            "BB:23 RSI: 9; percent accuracy : 72.97297297297297\n",
+            "BB:23 RSI:10; percent accuracy : 71.38364779874213\n",
+            "BB:23 RSI:11; percent accuracy : 72.9903536977492\n",
+            "BB:23 RSI:12; percent accuracy : 73.63013698630137\n",
+            "BB:23 RSI:13; percent accuracy : 75.09293680297398\n",
+            "BB:23 RSI:14; percent accuracy : 74.70817120622569\n",
+            "BB:23 RSI:15; percent accuracy : 76.20967741935483\n",
+            "BB:23 RSI:16; percent accuracy : 75.65217391304347\n",
+            "BB:23 RSI:17; percent accuracy : 75.5868544600939\n",
+            "BB:23 RSI:18; percent accuracy : 74.17582417582418\n",
+            "BB:23 RSI:19; percent accuracy : 74.07407407407408\n",
+            "BB:23 RSI:20; percent accuracy : 74.65753424657534\n",
+            "BB:24 RSI: 8; percent accuracy : 74.23312883435584\n",
+            "BB:24 RSI: 9; percent accuracy : 74.22360248447205\n",
+            "BB:24 RSI:10; percent accuracy : 72.90322580645162\n",
+            "BB:24 RSI:11; percent accuracy : 74.25742574257426\n",
+            "BB:24 RSI:12; percent accuracy : 75.71428571428571\n",
+            "BB:24 RSI:13; percent accuracy : 75.5813953488372\n",
+            "BB:24 RSI:14; percent accuracy : 76.09561752988047\n",
+            "BB:24 RSI:15; percent accuracy : 78.18930041152264\n",
+            "BB:24 RSI:16; percent accuracy : 77.57847533632287\n",
+            "BB:24 RSI:17; percent accuracy : 76.55502392344498\n",
+            "BB:24 RSI:18; percent accuracy : 75.70621468926554\n",
+            "BB:24 RSI:19; percent accuracy : 73.61963190184049\n",
+            "BB:24 RSI:20; percent accuracy : 73.61111111111111\n",
+            "BB:25 RSI: 8; percent accuracy : 74.14330218068535\n",
+            "BB:25 RSI: 9; percent accuracy : 74.4408945686901\n",
+            "BB:25 RSI:10; percent accuracy : 71.76079734219269\n",
+            "BB:25 RSI:11; percent accuracy : 75.0\n",
+            "BB:25 RSI:12; percent accuracy : 75.82417582417582\n",
+            "BB:25 RSI:13; percent accuracy : 73.91304347826086\n",
+            "BB:25 RSI:14; percent accuracy : 74.48559670781893\n",
+            "BB:25 RSI:15; percent accuracy : 77.35042735042735\n",
+            "BB:25 RSI:16; percent accuracy : 76.60550458715596\n",
+            "BB:25 RSI:17; percent accuracy : 76.58536585365854\n",
+            "BB:25 RSI:18; percent accuracy : 75.0\n",
+            "BB:25 RSI:19; percent accuracy : 72.04968944099379\n",
+            "BB:25 RSI:20; percent accuracy : 71.94244604316546\n",
+            "BB:26 RSI: 8; percent accuracy : 74.375\n",
+            "BB:26 RSI: 9; percent accuracy : 75.8957654723127\n",
+            "BB:26 RSI:10; percent accuracy : 73.15436241610739\n",
+            "BB:26 RSI:11; percent accuracy : 75.34246575342466\n",
+            "BB:26 RSI:12; percent accuracy : 76.75276752767527\n",
+            "BB:26 RSI:13; percent accuracy : 74.59677419354838\n",
+            "BB:26 RSI:14; percent accuracy : 74.27385892116183\n",
+            "BB:26 RSI:15; percent accuracy : 77.11864406779661\n",
+            "BB:26 RSI:16; percent accuracy : 76.92307692307693\n",
+            "BB:26 RSI:17; percent accuracy : 76.92307692307693\n",
+            "BB:26 RSI:18; percent accuracy : 75.86206896551724\n",
+            "BB:26 RSI:19; percent accuracy : 72.67080745341616\n",
+            "BB:26 RSI:20; percent accuracy : 72.85714285714285\n",
+            "BB:27 RSI: 8; percent accuracy : 74.92063492063492\n",
+            "BB:27 RSI: 9; percent accuracy : 75.73770491803279\n",
+            "BB:27 RSI:10; percent accuracy : 73.46938775510205\n",
+            "BB:27 RSI:11; percent accuracy : 74.30555555555556\n",
+            "BB:27 RSI:12; percent accuracy : 76.11940298507463\n",
+            "BB:27 RSI:13; percent accuracy : 73.38709677419355\n",
+            "BB:27 RSI:14; percent accuracy : 74.18032786885246\n",
+            "BB:27 RSI:15; percent accuracy : 76.59574468085107\n",
+            "BB:27 RSI:16; percent accuracy : 76.71232876712328\n",
+            "BB:27 RSI:17; percent accuracy : 76.4423076923077\n",
+            "BB:27 RSI:18; percent accuracy : 75.42857142857143\n",
+            "BB:27 RSI:19; percent accuracy : 73.00613496932516\n",
+            "BB:27 RSI:20; percent accuracy : 72.22222222222221\n",
+            "BB:28 RSI: 8; percent accuracy : 74.4336569579288\n",
+            "BB:28 RSI: 9; percent accuracy : 74.74747474747475\n",
+            "BB:28 RSI:10; percent accuracy : 72.91666666666666\n",
+            "BB:28 RSI:11; percent accuracy : 74.11347517730496\n",
+            "BB:28 RSI:12; percent accuracy : 75.37878787878788\n",
+            "BB:28 RSI:13; percent accuracy : 72.98387096774194\n",
+            "BB:28 RSI:14; percent accuracy : 73.87755102040816\n",
+            "BB:28 RSI:15; percent accuracy : 76.06837606837607\n",
+            "BB:28 RSI:16; percent accuracy : 75.79908675799086\n",
+            "BB:28 RSI:17; percent accuracy : 75.48076923076923\n",
+            "BB:28 RSI:18; percent accuracy : 74.28571428571429\n",
+            "BB:28 RSI:19; percent accuracy : 71.95121951219512\n",
+            "BB:28 RSI:20; percent accuracy : 72.22222222222221\n",
+            "BB:29 RSI: 8; percent accuracy : 73.17880794701986\n",
+            "BB:29 RSI: 9; percent accuracy : 74.32432432432432\n",
+            "BB:29 RSI:10; percent accuracy : 71.77700348432056\n",
+            "BB:29 RSI:11; percent accuracy : 73.11827956989248\n",
+            "BB:29 RSI:12; percent accuracy : 74.42748091603053\n",
+            "BB:29 RSI:13; percent accuracy : 71.900826446281\n",
+            "BB:29 RSI:14; percent accuracy : 72.31404958677686\n",
+            "BB:29 RSI:15; percent accuracy : 74.78632478632478\n",
+            "BB:29 RSI:16; percent accuracy : 75.46296296296296\n",
+            "BB:29 RSI:17; percent accuracy : 75.0\n",
+            "BB:29 RSI:18; percent accuracy : 73.5632183908046\n",
+            "BB:29 RSI:19; percent accuracy : 70.73170731707317\n",
+            "BB:29 RSI:20; percent accuracy : 70.83333333333334\n",
+            "BB:30 RSI: 8; percent accuracy : 72.16494845360825\n",
+            "BB:30 RSI: 9; percent accuracy : 73.5191637630662\n",
+            "BB:30 RSI:10; percent accuracy : 70.9090909090909\n",
+            "BB:30 RSI:11; percent accuracy : 72.99270072992701\n",
+            "BB:30 RSI:12; percent accuracy : 74.4186046511628\n",
+            "BB:30 RSI:13; percent accuracy : 71.78423236514523\n",
+            "BB:30 RSI:14; percent accuracy : 72.3404255319149\n",
+            "BB:30 RSI:15; percent accuracy : 74.8898678414097\n",
+            "BB:30 RSI:16; percent accuracy : 74.88151658767772\n",
+            "BB:30 RSI:17; percent accuracy : 74.8792270531401\n",
+            "BB:30 RSI:18; percent accuracy : 73.83720930232558\n",
+            "BB:30 RSI:19; percent accuracy : 70.80745341614907\n",
+            "BB:30 RSI:20; percent accuracy : 70.92198581560284\n",
+            "\n",
+            "best parameter config is\n",
+            "BB:11 RSI:17; percent accuracy : 80.53097345132744\n"
+          ]
+        }
+      ]
+    }
+  ]
+}
\ No newline at end of file