{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "from pandas import DataFrame, Series\n",
    "import numpy as np\n",
    "import math\n",
    "\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpatches\n",
    "import matplotlib.colors as colors\n",
    "from matplotlib.legend_handler import HandlerLine2D, HandlerTuple\n",
    "from matplotlib.colors import LinearSegmentedColormap\n",
    "from scipy import stats\n",
    "import scikit_posthocs as sp\n",
    "import sys\n",
    "\n",
    "from mpl_toolkits.mplot3d import axes3d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "AllName=\"dataCG_G.pkl\"\n",
    "ResizesName=\"dataCG_M.pkl\"\n",
    "NameExtension=\".pkl\"\n",
    "n_cores=20\n",
    "repet = 5 #CAMBIAR EL NUMERO SEGUN NUMERO DE EJECUCIONES POR CONFIG\n",
    "\n",
    "significance_value = 0.05\n",
    "processes = [2,10,20,40,80,120,160]\n",
    "\n",
    "positions = [321, 322, 323, 324, 325]\n",
    "positions_small = [221, 222, 223, 224]\n",
    "\n",
    "labels = ['(1,10)',   '(1,20)',   '(1,40)',  '(1,80)',  '(1,120)','(1,160)',\n",
    "            '(10,1)', '(10,20)',  '(10,40)', '(10,80)', '(10,120)','(10,160)',\n",
    "            '(20,1)', '(20,10)',  '(20,40)', '(20,80)', '(20,120)','(20,160)',\n",
    "            '(40,1)', '(40,10)',  '(40,20)', '(40,80)', '(40,120)','(40,160)',\n",
    "            '(80,1)', '(80,10)',  '(80,20)', '(80,40)', '(80,120)','(80,160)',\n",
    "            '(120,1)','(120,10)', '(120,20)','(120,40)','(120,80)','(120,160)',\n",
    "            '(160,1)','(160,10)', '(160,20)','(160,40)','(160,80)','(160,120)']\n",
    "\n",
    "labelsExpand = ['(1,10)',   '(1,20)',   '(1,40)',  '(1,80)',  '(1,120)','(1,160)',\n",
    "            '(10,20)',  '(10,40)', '(10,80)', '(10,120)','(10,160)',\n",
    "            '(20,40)', '(20,80)', '(20,120)','(20,160)',\n",
    "            '(40,80)', '(40,120)','(40,160)',\n",
    "            '(80,120)','(80,160)',\n",
    "            '(120,160)']\n",
    "labelsShrink = ['(10,1)', \n",
    "            '(20,1)', '(20,10)',\n",
    "            '(40,1)', '(40,10)',  '(40,20)',\n",
    "            '(80,1)', '(80,10)',  '(80,20)', '(80,40)',\n",
    "            '(120,1)','(120,10)', '(120,20)','(120,40)','(120,80)',\n",
    "            '(160,1)','(160,10)', '(160,20)','(160,40)','(160,80)','(160,120)']\n",
    "\n",
    "#                       WORST        BEST\n",
    "labels_dist = ['null', 'SpreadFit', 'CompactFit']\n",
    "                  #0          #1                #2                        #3\n",
    "labelsMethods = ['Baseline', 'Baseline single','Baseline - Asynchronous','Baseline single - Asynchronous',\n",
    "                 'Merge','Merge single','Merge - Asynchronous','Merge single - Asynchronous']\n",
    "                  #4      #5             #6                     #7\n",
    "    \n",
    "colors_m = ['green','darkgreen','red','darkred','mediumseagreen','seagreen','palegreen','springgreen','indianred','firebrick','darkgoldenrod','saddlebrown']\n",
    "linestyle_m = ['-', '--', '-.', ':']\n",
    "markers_m = ['.','v','s','p', 'h','d','X','P','^']\n",
    "\n",
    "OrMult_patch = mpatches.Patch(hatch='', facecolor='green', label='Baseline')\n",
    "OrSing_patch = mpatches.Patch(hatch='', facecolor='springgreen', label='Baseline single')\n",
    "OrPthMult_patch = mpatches.Patch(hatch='//', facecolor='blue', label='Baseline - Asyncrhonous')\n",
    "OrPthSing_patch = mpatches.Patch(hatch='\\\\', facecolor='darkblue', label='Baseline single - Asyncrhonous')\n",
    "MergeMult_patch = mpatches.Patch(hatch='||', facecolor='red', label='Merge')\n",
    "MergeSing_patch = mpatches.Patch(hatch='...', facecolor='darkred', label='Merge single')\n",
    "MergePthMult_patch = mpatches.Patch(hatch='xx', facecolor='yellow', label='Merge - Asyncrhonous')\n",
    "MergePthSing_patch = mpatches.Patch(hatch='++', facecolor='olive', label='Merge single - Asyncrhonous')\n",
    "\n",
    "handles_spawn = [OrMult_patch,OrSing_patch,OrPthMult_patch,OrPthSing_patch,MergeMult_patch,MergeSing_patch,MergePthMult_patch,MergePthSing_patch]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfG = pd.read_pickle( AllName )\n",
    "\n",
    "dfG['ADR'] = round((dfG['ADR'] / dfG['DR']) * 100,1)\n",
    "dfG['SDR'] = round((dfG['SDR'] / dfG['DR']) * 100,1)\n",
    "       \n",
    "out_group = dfG.groupby(['Groups', 'ADR','Spawn_Method','Redistribution_Method', 'Redistribution_Strategy'])['T_total']\n",
    "group = dfG.groupby(['ADR','Spawn_Method','Redistribution_Method', 'Redistribution_Strategy','Groups'])['T_total']\n",
    "\n",
    "grouped_aggG = group.agg(['median'])\n",
    "grouped_aggG.rename(columns={'median':'T_total'}, inplace=True) \n",
    "\n",
    "out_grouped_G = out_group.agg(['median'])\n",
    "out_grouped_G.rename(columns={'median':'T_total'}, inplace=True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_8483/1991315790.py:9: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  out_group = dfM.groupby(['NP','NC','ADR','Spawn_Method','Redistribution_Method', 'Redistribution_Strategy'])['T_Malleability','T_Redistribution','T_spawn','T_SR','T_AR']\n",
      "/tmp/ipykernel_8483/1991315790.py:10: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  group = dfM.groupby(['ADR','Spawn_Method','Redistribution_Method', 'Redistribution_Strategy','NP','NC'])['T_Malleability','T_Redistribution','T_spawn','T_SR','T_AR']\n"
     ]
    }
   ],
   "source": [
    "dfM = pd.read_pickle( ResizesName )\n",
    "\n",
    "dfM['ADR'] = round((dfM['ADR'] / dfM['DR']) * 100,1)\n",
    "dfM['SDR'] = round((dfM['SDR'] / dfM['DR']) * 100,1)\n",
    "dfM['T_Redistribution'] = dfM['T_SR'] + dfM['T_AR']\n",
    "dfM.loc[dfM['T_Malleability']==0,'T_Malleability'] = dfM['T_spawn'] + dfM['T_Redistribution']\n",
    "#dfM['T_Malleability'] = dfM['T_spawn'] + dfM['T_Redistribution'] #TODO Borrar esta linea\n",
    "       \n",
    "out_group = dfM.groupby(['NP','NC','ADR','Spawn_Method','Redistribution_Method', 'Redistribution_Strategy'])['T_Malleability','T_Redistribution','T_spawn','T_SR','T_AR']\n",
    "group = dfM.groupby(['ADR','Spawn_Method','Redistribution_Method', 'Redistribution_Strategy','NP','NC'])['T_Malleability','T_Redistribution','T_spawn','T_SR','T_AR']\n",
    "\n",
    "grouped_aggM = group.agg(['median'])\n",
    "grouped_aggM.columns = grouped_aggM.columns.get_level_values(0)\n",
    "\n",
    "out_grouped_M = out_group.agg(['median'])\n",
    "out_grouped_M.columns = out_grouped_M.columns.get_level_values(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bt_scheme import PartialSolution, BacktrackingSolver\n",
    "def elegirConf(parameters):\n",
    "    class StatePS(PartialSolution):\n",
    "        def __init__(self, config):\n",
    "            self.config= config\n",
    "            self.n= len(config) #Indica el valor a añadir\n",
    "\n",
    "        def is_solution(self):\n",
    "            return self.n == len(parameters)\n",
    "\n",
    "        def get_solution(self):\n",
    "            return tuple(self.config)\n",
    "\n",
    "        def successors(self):\n",
    "            array = parameters[self.n]\n",
    "            for parameter_value in array: #Test all values of the next parameter\n",
    "                self.config.append(parameter_value)\n",
    "                yield StatePS(self.config)\n",
    "                self.config.pop()\n",
    "\n",
    "    initialPs= StatePS([])\n",
    "    return BacktrackingSolver().solve(initialPs)\n",
    "\n",
    "\n",
    "def obtenerConfs(parameters):\n",
    "    soluciones=[]\n",
    "    for solucion in elegirConf(parameters):\n",
    "        soluciones.append(solucion)\n",
    "    return soluciones\n",
    "\n",
    "def modifyToGlobal(parameters, len_parameters, configuration):\n",
    "    usable_configuration = []\n",
    "    for i in range(len(parameters)):\n",
    "        if len_parameters[i] > 1:\n",
    "            aux = (parameters[i][0], configuration[i])\n",
    "        else:\n",
    "            aux = (configuration[i])\n",
    "        usable_configuration.append(aux)\n",
    "        \n",
    "    return usable_configuration\n",
    "\n",
    "def modifyToLocalDynamic(parameters, len_parameters, configuration):\n",
    "    usable_configuration = []\n",
    "    for i in range(len(parameters)):\n",
    "        if len_parameters[i] > 1:\n",
    "            aux = (configuration[i], -1)\n",
    "        else:\n",
    "            aux = (-1)\n",
    "        usable_configuration.append(aux)\n",
    "        \n",
    "    return tuple(usable_configuration)\n",
    "\n",
    "def CheckConfExists(configuration, dataSet, type_conf='global'):\n",
    "    exists = False\n",
    "    config = list(configuration)\n",
    "    for np_aux in processes:\n",
    "        for ns_aux in processes:\n",
    "            if np_aux != ns_aux:\n",
    "                \n",
    "                if type_conf == 'global':\n",
    "                    config.append((np_aux, ns_aux))\n",
    "                elif type_conf == 'malleability':\n",
    "                    config.append(np_aux)\n",
    "                    config.append(ns_aux)\n",
    "                elif type_conf == 'local':\n",
    "                    config.append(np_aux)\n",
    "                    \n",
    "                if tuple(config) in dataSet.index:     \n",
    "                    exists = True # FIXME Return here true?\n",
    "                config.pop()\n",
    "                \n",
    "                if type_conf == 'malleability':\n",
    "                    config.pop()\n",
    "    return exists"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0, 0, 0, 1], [0, 0, 1, 1], [0, 1, 0, 1], [0, 1, 1, 1], [96.6, 0, 0, 1], [96.6, 0, 0, 2], [96.6, 0, 1, 1], [96.6, 0, 1, 2], [96.6, 1, 0, 1], [96.6, 1, 0, 2], [96.6, 1, 1, 1], [96.6, 1, 1, 2]]\n",
      "[[0, (0, 0), (0, 0), (1, 1)], [0, (0, 0), (0, 1), (1, 1)], [0, (0, 1), (0, 0), (1, 1)], [0, (0, 1), (0, 1), (1, 1)], [96.6, (0, 0), (0, 0), (1, 1)], [96.6, (0, 0), (0, 0), (1, 2)], [96.6, (0, 0), (0, 1), (1, 1)], [96.6, (0, 0), (0, 1), (1, 2)], [96.6, (0, 1), (0, 0), (1, 1)], [96.6, (0, 1), (0, 0), (1, 2)], [96.6, (0, 1), (0, 1), (1, 1)], [96.6, (0, 1), (0, 1), (1, 2)]]\n",
      "12\n"
     ]
    }
   ],
   "source": [
    "adr = [0,96.6]\n",
    "sp_method = [0,1]\n",
    "rd_method = [0,1]\n",
    "rd_strat  = [1,2]\n",
    "parameters = [adr, sp_method, rd_method, rd_strat]\n",
    "parameters_names = ['ADR', 'Spawn_Method', 'Redistribution_Method', 'Redistribution_Strategy']\n",
    "len_parameters = [1,2,2,2]\n",
    "configurations_aux = obtenerConfs(parameters)\n",
    "configurations = []\n",
    "configurations_simple = []\n",
    "for checked_conf in configurations_aux:\n",
    "    aux_conf = modifyToGlobal(parameters, len_parameters, checked_conf)\n",
    "    if CheckConfExists(aux_conf, grouped_aggG):\n",
    "        configurations.append(aux_conf)\n",
    "\n",
    "    if CheckConfExists(checked_conf, grouped_aggM, 'malleability'):\n",
    "        configurations_simple.append(list(checked_conf))\n",
    "\n",
    "print(configurations_simple)\n",
    "print(configurations)\n",
    "print(len(configurations))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ALPHA COMPUTATION\n",
    "def compute_alpha(config_a, config_b):\n",
    "    for np_aux in processes:\n",
    "        for ns_aux in processes:\n",
    "            if np_aux != ns_aux:\n",
    "                config_a.append(np_aux)\n",
    "                config_a.append(ns_aux)\n",
    "                config_b.append(np_aux)\n",
    "                config_b.append(ns_aux)\n",
    "                grouped_aggM.loc[tuple(config_b),'Alpha'] = grouped_aggM.loc[tuple(config_b),'T_Malleability'] / grouped_aggM.loc[tuple(config_a),'T_Malleability']\n",
    "                #grouped_aggM.loc[tuple(config_b),'Alpha'] = grouped_aggM.loc[tuple(config_b),'T_Redistribution'] / grouped_aggM.loc[tuple(config_a),'T_Redistribution']\n",
    "                config_a.pop()\n",
    "                config_a.pop()\n",
    "                config_b.pop()\n",
    "                config_b.pop()\n",
    "                \n",
    "                \n",
    "                config_a.insert(0,ns_aux)\n",
    "                config_a.insert(0,np_aux)\n",
    "                config_b.insert(0,ns_aux)\n",
    "                config_b.insert(0,np_aux)\n",
    "                out_grouped_M.loc[tuple(config_b),'Alpha'] = out_grouped_M.loc[tuple(config_b),'T_Malleability'] / out_grouped_M.loc[tuple(config_a),'T_Malleability']\n",
    "                #out_grouped_M.loc[tuple(config_b),'Alpha'] = out_grouped_M.loc[tuple(config_b),'T_Redistribution'] / out_grouped_M.loc[tuple(config_a),'T_Redistribution']\n",
    "                \n",
    "                config_a.pop(0)\n",
    "                config_a.pop(0)\n",
    "                config_b.pop(0)\n",
    "                config_b.pop(0)\n",
    "\n",
    "if not ('Alpha' in grouped_aggM.columns):\n",
    "    for config_a in configurations_simple:\n",
    "        for config_b in configurations_simple:\n",
    "            if config_a[1:-1] == config_b[1:-1] and config_a[0] == 0 and config_b[0] != 0:\n",
    "                compute_alpha(config_a, config_b)\n",
    "else:\n",
    "    print(\"ALPHA already exists\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Las dos "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Coherence fails for inner times of malleability in 17 cases\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NP</th>\n",
       "      <th>NC</th>\n",
       "      <th>SDR</th>\n",
       "      <th>ADR</th>\n",
       "      <th>DR</th>\n",
       "      <th>Redistribution_Method</th>\n",
       "      <th>Redistribution_Strategy</th>\n",
       "      <th>Spawn_Method</th>\n",
       "      <th>Spawn_Strategy</th>\n",
       "      <th>Iters</th>\n",
       "      <th>T_spawn</th>\n",
       "      <th>T_SR</th>\n",
       "      <th>T_AR</th>\n",
       "      <th>T_Malleability</th>\n",
       "      <th>T_Redistribution</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>267</th>\n",
       "      <td>120</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>500</td>\n",
       "      <td>1.581953</td>\n",
       "      <td>1.396953</td>\n",
       "      <td>7.247200</td>\n",
       "      <td>9.159063</td>\n",
       "      <td>8.644153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>732</th>\n",
       "      <td>120</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>500</td>\n",
       "      <td>1.591676</td>\n",
       "      <td>1.058390</td>\n",
       "      <td>5.541655</td>\n",
       "      <td>7.344548</td>\n",
       "      <td>6.600045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>734</th>\n",
       "      <td>120</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>500</td>\n",
       "      <td>1.718427</td>\n",
       "      <td>1.474545</td>\n",
       "      <td>6.135146</td>\n",
       "      <td>8.408429</td>\n",
       "      <td>7.609691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>770</th>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>500</td>\n",
       "      <td>0.747981</td>\n",
       "      <td>0.496348</td>\n",
       "      <td>2.655852</td>\n",
       "      <td>3.537969</td>\n",
       "      <td>3.152200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>773</th>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>500</td>\n",
       "      <td>0.790737</td>\n",
       "      <td>0.478529</td>\n",
       "      <td>2.736482</td>\n",
       "      <td>3.641156</td>\n",
       "      <td>3.215011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>982</th>\n",
       "      <td>160</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>500</td>\n",
       "      <td>1.186916</td>\n",
       "      <td>0.900510</td>\n",
       "      <td>4.448269</td>\n",
       "      <td>5.804883</td>\n",
       "      <td>5.348779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>983</th>\n",
       "      <td>160</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>500</td>\n",
       "      <td>1.398092</td>\n",
       "      <td>0.798145</td>\n",
       "      <td>4.425738</td>\n",
       "      <td>6.013421</td>\n",
       "      <td>5.223883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>984</th>\n",
       "      <td>160</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>500</td>\n",
       "      <td>1.320479</td>\n",
       "      <td>1.678612</td>\n",
       "      <td>5.826839</td>\n",
       "      <td>7.358955</td>\n",
       "      <td>7.505451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1396</th>\n",
       "      <td>120</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>500</td>\n",
       "      <td>0.787162</td>\n",
       "      <td>3.338027</td>\n",
       "      <td>5.996064</td>\n",
       "      <td>7.413570</td>\n",
       "      <td>9.334091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1397</th>\n",
       "      <td>120</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>500</td>\n",
       "      <td>0.823052</td>\n",
       "      <td>1.449019</td>\n",
       "      <td>3.250080</td>\n",
       "      <td>4.776255</td>\n",
       "      <td>4.699099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1398</th>\n",
       "      <td>120</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>500</td>\n",
       "      <td>0.780008</td>\n",
       "      <td>1.032783</td>\n",
       "      <td>3.219415</td>\n",
       "      <td>4.442129</td>\n",
       "      <td>4.252198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1399</th>\n",
       "      <td>120</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>500</td>\n",
       "      <td>0.615581</td>\n",
       "      <td>1.769193</td>\n",
       "      <td>3.842247</td>\n",
       "      <td>5.302729</td>\n",
       "      <td>5.611440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1635</th>\n",
       "      <td>80</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>500</td>\n",
       "      <td>0.696372</td>\n",
       "      <td>1.046508</td>\n",
       "      <td>3.413361</td>\n",
       "      <td>4.455621</td>\n",
       "      <td>4.459869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>160</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>500</td>\n",
       "      <td>0.758355</td>\n",
       "      <td>1.530185</td>\n",
       "      <td>3.496149</td>\n",
       "      <td>4.825279</td>\n",
       "      <td>5.026334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>160</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>500</td>\n",
       "      <td>0.760975</td>\n",
       "      <td>1.790997</td>\n",
       "      <td>3.244461</td>\n",
       "      <td>4.622727</td>\n",
       "      <td>5.035458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>160</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>500</td>\n",
       "      <td>0.790667</td>\n",
       "      <td>1.347515</td>\n",
       "      <td>3.790327</td>\n",
       "      <td>4.928468</td>\n",
       "      <td>5.137842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>160</td>\n",
       "      <td>2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3.947884e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>500</td>\n",
       "      <td>0.820370</td>\n",
       "      <td>1.477013</td>\n",
       "      <td>3.471610</td>\n",
       "      <td>5.212454</td>\n",
       "      <td>4.948623</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       NP  NC  SDR   ADR            DR  Redistribution_Method  \\\n",
       "267   120   2  3.4  96.6  3.947884e+09                      0   \n",
       "732   120   2  3.4  96.6  3.947884e+09                      1   \n",
       "734   120   2  3.4  96.6  3.947884e+09                      1   \n",
       "770    10   2  3.4  96.6  3.947884e+09                      1   \n",
       "773    10   2  3.4  96.6  3.947884e+09                      1   \n",
       "982   160   2  3.4  96.6  3.947884e+09                      1   \n",
       "983   160   2  3.4  96.6  3.947884e+09                      1   \n",
       "984   160   2  3.4  96.6  3.947884e+09                      1   \n",
       "1396  120   2  3.4  96.6  3.947884e+09                      0   \n",
       "1397  120   2  3.4  96.6  3.947884e+09                      0   \n",
       "1398  120   2  3.4  96.6  3.947884e+09                      0   \n",
       "1399  120   2  3.4  96.6  3.947884e+09                      0   \n",
       "1635   80   2  3.4  96.6  3.947884e+09                      0   \n",
       "2020  160   2  3.4  96.6  3.947884e+09                      0   \n",
       "2021  160   2  3.4  96.6  3.947884e+09                      0   \n",
       "2022  160   2  3.4  96.6  3.947884e+09                      0   \n",
       "2023  160   2  3.4  96.6  3.947884e+09                      0   \n",
       "\n",
       "      Redistribution_Strategy  Spawn_Method  Spawn_Strategy  Iters   T_spawn  \\\n",
       "267                         2             0               2    500  1.581953   \n",
       "732                         2             0               2    500  1.591676   \n",
       "734                         2             0               2    500  1.718427   \n",
       "770                         2             0               2    500  0.747981   \n",
       "773                         2             0               2    500  0.790737   \n",
       "982                         2             0               2    500  1.186916   \n",
       "983                         2             0               2    500  1.398092   \n",
       "984                         2             0               2    500  1.320479   \n",
       "1396                        1             0               1    500  0.787162   \n",
       "1397                        1             0               1    500  0.823052   \n",
       "1398                        1             0               1    500  0.780008   \n",
       "1399                        1             0               1    500  0.615581   \n",
       "1635                        1             0               1    500  0.696372   \n",
       "2020                        1             0               1    500  0.758355   \n",
       "2021                        1             0               1    500  0.760975   \n",
       "2022                        1             0               1    500  0.790667   \n",
       "2023                        1             0               1    500  0.820370   \n",
       "\n",
       "          T_SR      T_AR  T_Malleability  T_Redistribution  \n",
       "267   1.396953  7.247200        9.159063          8.644153  \n",
       "732   1.058390  5.541655        7.344548          6.600045  \n",
       "734   1.474545  6.135146        8.408429          7.609691  \n",
       "770   0.496348  2.655852        3.537969          3.152200  \n",
       "773   0.478529  2.736482        3.641156          3.215011  \n",
       "982   0.900510  4.448269        5.804883          5.348779  \n",
       "983   0.798145  4.425738        6.013421          5.223883  \n",
       "984   1.678612  5.826839        7.358955          7.505451  \n",
       "1396  3.338027  5.996064        7.413570          9.334091  \n",
       "1397  1.449019  3.250080        4.776255          4.699099  \n",
       "1398  1.032783  3.219415        4.442129          4.252198  \n",
       "1399  1.769193  3.842247        5.302729          5.611440  \n",
       "1635  1.046508  3.413361        4.455621          4.459869  \n",
       "2020  1.530185  3.496149        4.825279          5.026334  \n",
       "2021  1.790997  3.244461        4.622727          5.035458  \n",
       "2022  1.347515  3.790327        4.928468          5.137842  \n",
       "2023  1.477013  3.471610        5.212454          4.948623  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Malleability Coherence COMPUTATION\n",
    "test=dfM[(dfM.ADR > 0)]\n",
    "coherence_boundary = 1.10 # Allows a 1% error\n",
    "# Coherence of inner times\n",
    "aux_df = test[\"T_Malleability\"] * coherence_boundary < (test[\"T_spawn\"] + test[\"T_Redistribution\"])\n",
    "if not test[aux_df].empty:\n",
    "    print(\"Coherence fails for inner times of malleability in \" + str(len(test[aux_df])) + \" cases\")\n",
    "    display(test[aux_df])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "out_grouped_G.to_excel(\"resultG.xlsx\") \n",
    "out_grouped_M.to_excel(\"resultM.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>T_total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Groups</th>\n",
       "      <th>ADR</th>\n",
       "      <th>Spawn_Method</th>\n",
       "      <th>Redistribution_Method</th>\n",
       "      <th>Redistribution_Strategy</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">(2, 10)</th>\n",
       "      <th rowspan=\"4\" valign=\"top\">0.0</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">(0, 0)</th>\n",
       "      <th>(0, 0)</th>\n",
       "      <th>(1, 1)</th>\n",
       "      <td>361.352938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(0, 1)</th>\n",
       "      <th>(1, 1)</th>\n",
       "      <td>415.667817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">(0, 1)</th>\n",
       "      <th>(0, 0)</th>\n",
       "      <th>(1, 1)</th>\n",
       "      <td>377.230362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(0, 1)</th>\n",
       "      <th>(1, 1)</th>\n",
       "      <td>429.022780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96.6</th>\n",
       "      <th>(0, 0)</th>\n",
       "      <th>(0, 0)</th>\n",
       "      <th>(1, 1)</th>\n",
       "      <td>422.015817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">(160, 120)</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">96.6</th>\n",
       "      <th>(0, 0)</th>\n",
       "      <th>(0, 1)</th>\n",
       "      <th>(1, 2)</th>\n",
       "      <td>147.844352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">(0, 1)</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">(0, 0)</th>\n",
       "      <th>(1, 1)</th>\n",
       "      <td>127.604035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(1, 2)</th>\n",
       "      <td>131.328504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">(0, 1)</th>\n",
       "      <th>(1, 1)</th>\n",
       "      <td>133.644158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(1, 2)</th>\n",
       "      <td>130.914150</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>504 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                               T_total\n",
       "Groups     ADR  Spawn_Method Redistribution_Method Redistribution_Strategy            \n",
       "(2, 10)    0.0  (0, 0)       (0, 0)                (1, 1)                   361.352938\n",
       "                             (0, 1)                (1, 1)                   415.667817\n",
       "                (0, 1)       (0, 0)                (1, 1)                   377.230362\n",
       "                             (0, 1)                (1, 1)                   429.022780\n",
       "           96.6 (0, 0)       (0, 0)                (1, 1)                   422.015817\n",
       "...                                                                                ...\n",
       "(160, 120) 96.6 (0, 0)       (0, 1)                (1, 2)                   147.844352\n",
       "                (0, 1)       (0, 0)                (1, 1)                   127.604035\n",
       "                                                   (1, 2)                   131.328504\n",
       "                             (0, 1)                (1, 1)                   133.644158\n",
       "                                                   (1, 2)                   130.914150\n",
       "\n",
       "[504 rows x 1 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out_grouped_G"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_group_boundary(rms_boundary, np_aux, ns_aux):\n",
    "    tc_boundary = 0\n",
    "    boundaries = None\n",
    "    if rms_boundary != 0:\n",
    "        # El porcentaje de tc_boundary se tiene en cuenta para eliminar aquellos\n",
    "        # tiempos demasiado grandes en su malleability time respecto al más pequeño\n",
    "        boundaries = get_np_ns_data(\"T_Malleability\", grouped_aggM, configurations_simple, np_aux, ns_aux)\n",
    "        tc_boundary = min(boundaries)\n",
    "        tc_boundary = tc_boundary + tc_boundary*rms_boundary\n",
    "    return tc_boundary, boundaries\n",
    "\n",
    "# Aquellos grupos que tengán valores por encima del límite no se considerarán\n",
    "def check_groups_boundaries(dataLists, boundaries, tc_boundary):\n",
    "    for index in range(len(boundaries)):\n",
    "        if boundaries[index] > tc_boundary:\n",
    "            dataLists[index] = float('infinity')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_perc_differences(dataLists, boundaries, tc_boundary):\n",
    "    perc = 1.05\n",
    "    if boundaries != None: # Si se usa perspectiva de RMS, se desconsideran valores muy altos\n",
    "        check_groups_boundaries(dataLists, boundaries, tc_boundary) \n",
    "    indexes = np.argsort(dataLists)\n",
    "    \n",
    "    best = -1\n",
    "    bestMax = -1\n",
    "    otherBest=[]\n",
    "    for index in indexes: # Para cada metodo -- Empezando por el tiempo más bajo en media/mediana\n",
    "        if best == -1:\n",
    "            best = index\n",
    "            bestMax = dataLists[best] * perc\n",
    "        elif dataLists[index] <= bestMax: # Media/Medianas i < Media/Mediana best\n",
    "            otherBest.append(index)\n",
    "                \n",
    "    otherBest.insert(0,best)\n",
    "    return otherBest\n",
    "\n",
    "def get_stat_differences(dataLists, df_Res, boundaries, tc_boundary):\n",
    "    if boundaries != None: # Si se usa perspectiva de RMS, se desconsideran valores muy altos\n",
    "        check_groups_boundaries(dataLists, boundaries, tc_boundary) \n",
    "    indexes = np.argsort(dataLists)\n",
    "    \n",
    "    best = -1\n",
    "    otherBest=[]  \n",
    "    for index in indexes: # Para cada metodo -- Empezando por el tiempo más bajo en mediana\n",
    "        if dataLists[index] != float('infinity'):\n",
    "            if best == -1:\n",
    "                best = index\n",
    "            elif not df_Res.iat[best,index]: # df_Res == False indicates 'index' and 'best' have the same mean/median\n",
    "                otherBest.append(index)\n",
    "                \n",
    "    otherBest.insert(0,best)\n",
    "    return otherBest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped_np = [\"T_total\"]\n",
    "separated_np = [\"T_Malleability\", \"T_Redistribution\", \"T_spawn\", \"T_SR\", \"T_AR\", \"Alpha\"]\n",
    "\n",
    "def get_np_ns_data(tipo, data_aux, used_config, np_aux, ns_aux):\n",
    "    dataLists=[]\n",
    "    for config in used_config:\n",
    "        if tipo in grouped_np:\n",
    "            config.append((np_aux,ns_aux))\n",
    "        elif tipo in separated_np:\n",
    "            config.append(np_aux)\n",
    "            config.append(ns_aux)\n",
    "        \n",
    "        if tuple(config) in data_aux.index:\n",
    "            aux_value = data_aux.loc[tuple(config),tipo]\n",
    "            if isinstance(aux_value, pd.Series):\n",
    "                aux_value = aux_value.values[0]\n",
    "            if aux_value == 0: #Values of zero indicate it was not performed\n",
    "                aux_value = float('infinity')\n",
    "        else: # This configuration is not present in the dataset\n",
    "            aux_value = float('infinity')\n",
    "        dataLists.append(aux_value)\n",
    "        config.pop()\n",
    "        if tipo in separated_np:\n",
    "            config.pop()\n",
    "    return dataLists\n",
    "\n",
    "def get_config_data(tipo, data_aux, config):\n",
    "    dataLists=[]\n",
    "    procsLists=[]\n",
    "    for ns_aux in processes:\n",
    "        for np_aux in processes:\n",
    "            if np_aux != ns_aux:\n",
    "                \n",
    "                if tipo in grouped_np:\n",
    "                    config.append((np_aux,ns_aux))\n",
    "                elif tipo in separated_np:\n",
    "                    config.append(np_aux)\n",
    "                    config.append(ns_aux)\n",
    "                if tuple(config) in data_aux.index:\n",
    "                    procsLists.append((np_aux,ns_aux))\n",
    "                    aux_value = data_aux.loc[tuple(config),tipo]\n",
    "                    if isinstance(aux_value, pd.Series):\n",
    "                        aux_value = aux_value.values[0]\n",
    "                    if aux_value == 0: #Values of zero indicate it was not performed\n",
    "                        aux_value = float('infinity')\n",
    "                else: # This configuration is not present in the dataset\n",
    "                    aux_value = float('infinity')\n",
    "                dataLists.append(aux_value)\n",
    "                config.pop()\n",
    "                if tipo in separated_np:\n",
    "                    config.pop()\n",
    "    return dataLists, procsLists\n",
    "\n",
    "def get_df_np_ns_data(df_check, tipo, used_config, np_aux, ns_aux):\n",
    "    dataLists=[]\n",
    "    if tipo in grouped_np:\n",
    "        tuple_data = (np_aux, ns_aux)\n",
    "        df_npns_aux = df_check.loc[(df_check['Groups']==tuple_data)]\n",
    "    elif tipo in separated_np:\n",
    "        df_npns_aux = df_check.loc[(df_check['NP']==np_aux)]\n",
    "        df_npns_aux = df_npns_aux.loc[(df_npns_aux['NC']==ns_aux)]\n",
    "        \n",
    "    for config in used_config:\n",
    "        df_config_aux = df_npns_aux\n",
    "        for index in range(len(config)):\n",
    "            aux_name = parameters_names[index]\n",
    "            aux_value = config[index]\n",
    "            df_config_aux = df_config_aux.loc[(df_config_aux[aux_name] == aux_value)]\n",
    "                \n",
    "        aux_value = list(df_config_aux[tipo])\n",
    "        if len(aux_value) > 0:\n",
    "            dataLists.append(aux_value)\n",
    "    return dataLists\n",
    "\n",
    "def get_df_config_data(df_check, tipo, config):\n",
    "    dataLists=[]\n",
    "    df_config_aux = df_check\n",
    "    for index in range(len(config)):\n",
    "        aux_name = parameters_names[index]\n",
    "        aux_value = config[index]\n",
    "        df_config_aux = df_config_aux.loc[(df_config_aux[aux_name] == aux_value)]\n",
    "        \n",
    "    for np_aux in processes:\n",
    "        for ns_aux in processes:\n",
    "            if np_aux != ns_aux:\n",
    "                if tipo in grouped_np:\n",
    "                    tuple_data = (np_aux, ns_aux)\n",
    "                    df_aux = df_config_aux.loc[(df_config_aux['Groups']==tuple_data)]\n",
    "                elif tipo in separated_np:\n",
    "                    df_aux = df_config_aux.loc[(df_config_aux['NP']==np_aux)]\n",
    "                    df_aux = df_aux.loc[(df_aux['NC']==ns_aux)]\n",
    "                aux_value = list(df_aux[tipo])\n",
    "                if len(aux_value) > 0:\n",
    "                    dataLists.append(aux_value)\n",
    "    return dataLists\n",
    "                \n",
    "                "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def check_normality(df_check, tipo, used_config, fast=True):\n",
    "    normality_array=[True] * (len(processes) * (len(processes)-1) * len(used_config))\n",
    "    normality = True\n",
    "    total=0\n",
    "    i=-1\n",
    "    #Comprobar para cada configuración si se sigue una distribución normal/gaussiana\n",
    "    for np_aux in processes:\n",
    "        for ns_aux in processes:\n",
    "            if np_aux != ns_aux:\n",
    "                i+=1\n",
    "                dataLists = get_df_np_ns_data(df_check, tipo, used_config, np_aux, ns_aux)\n",
    "                for data_aux in dataLists:\n",
    "                    st,p = stats.shapiro(data_aux) # Tendrían que ser al menos 20 datos y menos de 50\n",
    "                    if p < significance_value: # Reject H0\n",
    "                        if fast:\n",
    "                            return False\n",
    "                        normality_array[i] = False\n",
    "                        normality = False\n",
    "                        total+=1\n",
    "    print(\"Se sigue una distribución guassiana: \" + str(normality) + \"\\nUn total de: \" + str(total) + \" no siguen una gaussiana\")\n",
    "    print(normality_array)\n",
    "    return normality\n",
    "\n",
    "def check_homoscedasticity(df_check, tipo, used_config, fast=True):\n",
    "    homoscedasticity_array=[True] * (len(processes) * (len(processes)-1))\n",
    "    homoscedasticity = True\n",
    "    total=0\n",
    "    i=-1\n",
    "    #Comprobar para cada configuración es homoestatica\n",
    "    for np_aux in processes:\n",
    "        for ns_aux in processes:\n",
    "            if np_aux != ns_aux:\n",
    "                i+=1\n",
    "                dataLists = get_df_np_ns_data(df_check, tipo, used_config, np_aux, ns_aux)\n",
    "                st,p = stats.levene(*dataLists) # Tendrían que ser al menos 20 datos y menos de 50\n",
    "                if p < significance_value: # Reject H0\n",
    "                    if fast:\n",
    "                        return False\n",
    "                    homoscedasticity_array[i] = False\n",
    "                    homoscedasticity = False\n",
    "                    total+=1\n",
    "    print(\"Se sigue una distribución de datos Homocedastica: \" + str(homoscedasticity) + \"\\nUn total de: \" + str(total) + \" no siguen una homocedastica\")\n",
    "    print(homoscedasticity_array)\n",
    "    return homoscedasticity\n",
    "\n",
    "def compute_global_stat_difference(dataLists, parametric, np_aux, ns_aux):\n",
    "    if parametric:\n",
    "        st,p=stats.f_oneway(*dataLists)\n",
    "    else:\n",
    "        st,p=stats.kruskal(*dataLists)\n",
    "    if p > significance_value:\n",
    "        print(\"For NP \" + str(np_aux) + \" and \" + str(ns_aux) + \" is accepted H0\")\n",
    "        return True # Equal values || Accept H0\n",
    "    return False # Some groups are different || Reject H0\n",
    "\n",
    "def compute_global_posthoc(dataLists, parametric): #TODO Comprobar CDF de los grupos\n",
    "    data_stats=[]\n",
    "    data_stats2=[]\n",
    "    ini=0\n",
    "    end=len(dataLists)\n",
    "    if parametric:\n",
    "        df_aux = sp.posthoc_ttest(dataLists)\n",
    "        df_Res = df_aux.copy()\n",
    "        for i in range(ini,end):\n",
    "            data_stats.append(np.mean(dataLists[i]))\n",
    "            \n",
    "            for j in range(ini,end):\n",
    "                if df_Res.iat[i,j] < significance_value: # Different means || Reject H0\n",
    "                    df_Res.iat[i, j] = True\n",
    "                else:\n",
    "                    df_Res.iat[i, j] = False\n",
    "    else:\n",
    "        df_aux = sp.posthoc_conover(dataLists)\n",
    "        df_Res = df_aux.copy()\n",
    "        for i in range(ini,end):\n",
    "            data_stats.append(np.median(dataLists[i]))\n",
    "            #data_stats2.append(stats.iqr(dataLists[i],axis=0))\n",
    "            for j in range(ini,end):\n",
    "                if df_Res.iat[i,j] < significance_value: # Different medians || Reject H0\n",
    "                    df_Res.iat[i, j] = True # Not equal medians\n",
    "                else:\n",
    "                    df_Res.iat[i, j] = False # Equal medians\n",
    "    #print(df_Res)\n",
    "    #print(df_aux)\n",
    "    #print(data_stats)\n",
    "    #print(data_stats2)\n",
    "    #aux_value = min(data_stats)\n",
    "    #print(data_stats.index(aux_value))\n",
    "    return df_Res, data_stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def results_with_perc(tipo, data_aux, used_config, rms_boundary=0):\n",
    "    results = []\n",
    "    for np_aux in processes:\n",
    "        for ns_aux in processes:\n",
    "            if np_aux != ns_aux:\n",
    "                tc_boundary, boundaries = create_group_boundary(rms_boundary, np_aux, ns_aux)\n",
    "                \n",
    "                #Get all values for particular config with these number of processes\n",
    "                dataLists = get_np_ns_data(tipo, data_aux, used_config, np_aux, ns_aux)\n",
    "\n",
    "                aux_data = get_perc_differences(dataLists, boundaries, tc_boundary)\n",
    "                results.append(aux_data)\n",
    "    return results\n",
    "\n",
    "def results_with_stats(tipo, df_check, used_config, rms_boundary=0):\n",
    "    results = []\n",
    "    use_parametric = check_normality(df_check, tipo, used_config)\n",
    "    if use_parametric:\n",
    "        use_parametric = check_homoscedasticity(df_check, tipo, used_config)\n",
    "    print(\"Se usan tests parametricos: \"+str(use_parametric))\n",
    "    for np_aux in processes:\n",
    "        for ns_aux in processes:\n",
    "            if np_aux != ns_aux:\n",
    "                tc_boundary, boundaries = create_group_boundary(rms_boundary, np_aux, ns_aux)\n",
    "                \n",
    "                #Get all values for particular config with these number of processes\n",
    "                dataLists = get_df_np_ns_data(df_check, tipo, used_config, np_aux, ns_aux)\n",
    "                equal_set = compute_global_stat_difference(dataLists, use_parametric, np_aux, ns_aux)\n",
    "                if equal_set:\n",
    "                    aux_data = list(range(len(used_config))) # All data is equal\n",
    "                else:\n",
    "                    res_aux, times_aux = compute_global_posthoc(dataLists, use_parametric)\n",
    "                    aux_data = get_stat_differences(times_aux, res_aux, boundaries, tc_boundary)\n",
    "                \n",
    "                results.append(aux_data)\n",
    "    \n",
    "    return results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Se usan tests parametricos: False\n",
      "[[1, 7, 0], [3, 2], [2, 1, 3], [1, 3, 2], [2, 3, 7, 1], [7, 3, 2, 1, 4], [0], [2, 3], [2, 3, 11], [3, 2], [3], [4, 3], [2, 3], [2, 3], [3, 2], [3, 2], [3, 2], [3], [0, 10], [3, 2], [2, 3], [2, 3], [3, 2], [3, 2], [10, 2], [2, 3], [2, 3], [2, 3], [2, 3], [2, 3], [10, 2], [2, 3], [2, 3], [2, 3], [2, 3], [2, 3], [10, 2], [2, 3], [2, 3], [3, 2], [3, 2], [2, 3]]\n",
      "42\n"
     ]
    }
   ],
   "source": [
    "checked_type='T_Redistribution'\n",
    "use_perc = False\n",
    "select_first_winner = False\n",
    "prefer_first_winner = False\n",
    "rms_boundary=0 # Poner a 0 para perspectiva de app. Valor >0 y <1 para perspectiva de RMS\n",
    "if checked_type=='T_total':\n",
    "    tipo=\"T_total\"\n",
    "    if use_perc:\n",
    "        data_aux = grouped_aggG\n",
    "    else:\n",
    "        data_aux = dfG\n",
    "    used_config = configurations\n",
    "elif checked_type=='T_Malleability' or checked_type=='T_spawn' or checked_type=='T_SR' or checked_type=='T_AR' or checked_type=='T_Redistribution':\n",
    "    tipo=checked_type\n",
    "    \n",
    "    if use_perc:\n",
    "        data_aux = grouped_aggM\n",
    "    else:\n",
    "        data_aux = dfM\n",
    "        if tipo == 'T_AR':\n",
    "            data_aux = data_aux[(data_aux.ADR > 0)]\n",
    "        elif tipo == 'T_SR':\n",
    "            data_aux = data_aux[(data_aux.ADR == 0)]\n",
    "        \n",
    "    used_config = configurations_simple\n",
    "    \n",
    "if use_perc:\n",
    "    results = results_with_perc(tipo, data_aux, used_config, rms_boundary)\n",
    "else:\n",
    "    results = results_with_stats(tipo, data_aux, used_config, rms_boundary)\n",
    "    \n",
    "if not use_perc and tipo == 'T_AR': #FIXME!!!! No tiene en cuenta total de configuraciones sincronos\n",
    "    for res_index in range(len(results)):\n",
    "        for inner_index in range(len(results[res_index])):\n",
    "            results[res_index][inner_index]+=4\n",
    "\n",
    "#Results is a 2 dimensional array. First dimension indicates lists of winners of a particulal number of processes (NP->NC). \n",
    "#Second dimension is an ordered preference of indexes in the array configurations.\n",
    "print(results)\n",
    "print(len(results))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0  1  2  3  4  7 10 11]\n",
      "[ 3  5 36 36  2  3  4  1]\n",
      "[[-1  1  2  2  2  2  2]\n",
      " [ 0 -1  2  2  2  3  3]\n",
      " [ 2  2 -1  2  2  2  3]\n",
      " [10  2  2 -1  2  2  2]\n",
      " [ 2  2  2  2 -1  2  2]\n",
      " [ 2  2  2  2  2 -1  2]\n",
      " [ 2  2  2  2  2  2 12]]\n"
     ]
    }
   ],
   "source": [
    "#Lista de indices de mayor a menor según el total de ocurrencias\n",
    "aux_array = []\n",
    "for data in results:\n",
    "    aux_array+=data\n",
    "aux_keys, aux_counts = np.unique(aux_array, return_counts=True)\n",
    "aux_ordered_index=list(reversed(np.argsort(aux_counts)))\n",
    "\n",
    "#Lista de indices de mayor a menor según el total de ocurrencias del primero de cada grupo\n",
    "aux_array = [0] * len(results)\n",
    "for index in range(len(results)):\n",
    "    aux_array[index] = results[index][0]\n",
    "aux_keys_best, aux_counts_best = np.unique(aux_array, return_counts = True)\n",
    "aux_ordered_best_index=list(reversed(np.argsort(aux_counts_best)))\n",
    "\n",
    "def heatmap_get_best(index, ordered_array, keys_array, counts_array, prefer_winner=False):\n",
    "    valid_candidates_indexes = []\n",
    "    prev_counts = -1\n",
    "    for tested_index in ordered_array:\n",
    "        if keys_array[tested_index] in results[index]:\n",
    "            if counts_array[tested_index] >= prev_counts:\n",
    "                prev_counts = counts_array[tested_index]\n",
    "                valid_candidates_indexes.append(tested_index)\n",
    "            else:\n",
    "                break\n",
    "                \n",
    "    if prefer_winner: # Si esta activo, en caso de empate en ocurrencias se selecciona el menor tiempo\n",
    "        for tested_index in results[index]:\n",
    "            if tested_index in valid_candidates_indexes:\n",
    "                return tested_index\n",
    "    return min(valid_candidates_indexes) # En caso de empate se devuelve el que tiene menor valor (Suele ser la config más simple)\n",
    "\n",
    "i=0\n",
    "j=0\n",
    "used_aux=0\n",
    "heatmap=np.zeros((len(processes),len(processes))).astype(int)\n",
    "\n",
    "if select_first_winner:\n",
    "    for i in range(len(processes)):\n",
    "        for j in range(len(processes)):\n",
    "            if i==j:\n",
    "                heatmap[i][j]=-1\n",
    "                used_aux+=1\n",
    "            else:\n",
    "                results_index = i*len(processes) + j - used_aux\n",
    "                heatmap[i][j] = results[results_index][0]\n",
    "else:\n",
    "    for i in range(len(processes)):\n",
    "        for j in range(len(processes)):\n",
    "            if i==j:\n",
    "                heatmap[i][j]=-1\n",
    "                used_aux+=1\n",
    "            else:\n",
    "                results_index = i*len(processes) + j - used_aux\n",
    "                index = heatmap_get_best(results_index, aux_ordered_index, aux_keys, aux_counts, prefer_first_winner)\n",
    "                heatmap[i][j]=aux_keys[index]\n",
    "                #index = heatmap_get_best(results_index, aux_ordered_best_index, aux_keys_best, aux_counts_best, prefer_first_winner)\n",
    "                #heatmap[i][j]=aux_keys_best[index]\n",
    "heatmap[-1][-1]=len(used_config)\n",
    "print(aux_keys)\n",
    "print(aux_counts)\n",
    "print(heatmap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Adapta results a una cadena asegurando que cada cadena no se sale de su celda\n",
    "def get_heatmap_multiple_strings(results): #FIXME Deprecated\n",
    "    results_str = []\n",
    "    max_counts = 1\n",
    "    max_per_line = 3\n",
    "    for i in range(len(results)):\n",
    "        results_str.append(list())\n",
    "        count = len(results[i])\n",
    "        results_aux = results[i]\n",
    "        if count > max_counts:\n",
    "            count = max_counts\n",
    "            results_aux = results[i][:count]\n",
    "        \n",
    "        remainder = count%max_per_line\n",
    "        if count <= max_per_line:\n",
    "            aux_str = str(results_aux).replace('[','').replace(']','')\n",
    "            results_str[i].append(aux_str)\n",
    "        else:\n",
    "            if remainder == 0:\n",
    "                index = count//2\n",
    "            else:\n",
    "                index = count - ((remainder-1)*max_per_line + 1)\n",
    "            aux_str = str(results_aux[:index]).replace('[','').replace(']','')\n",
    "            results_str[i].append(aux_str)\n",
    "            aux_str = str(results_aux[index:]).replace('[','').replace(']','')\n",
    "            results_str[i].append(aux_str)\n",
    "    return results_str\n",
    "\n",
    "def get_heatmap_strings(heatmap):\n",
    "    results_str = []\n",
    "    for i in range(len(processes)):\n",
    "        for j in range(len(processes)):\n",
    "            if i!=j:\n",
    "                results_str.append(list())\n",
    "                results_str[-1].append(heatmap[i][j])\n",
    "    return results_str"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_4348/633283794.py:65: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(['']+processes, fontsize=36)\n",
      "/tmp/ipykernel_4348/633283794.py:66: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_yticklabels(['']+processes, fontsize=36)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Filename: Heatmap_T_Redistribution.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2400x1200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Crea un heatmap teniendo en cuenta los colores anteriores\n",
    "f=plt.figure(figsize=(24, 12))\n",
    "ax=f.add_subplot(111)\n",
    "\n",
    "myColors = (colors.to_rgba(\"white\"), \n",
    "    colors.to_rgba(\"green\"), #BCOLS\n",
    "    colors.to_rgba(\"darkgreen\"), #BP2PS\n",
    "    #colors.to_rgba(\"blue\"),  #BRMA1S\n",
    "    #colors.to_rgba(\"royalblue\"), #BRMA2S\n",
    "    colors.to_rgba(\"red\"), #MCOLS\n",
    "    colors.to_rgba(\"darkred\"),  #MP2PS\n",
    "    #colors.to_rgba(\"mediumblue\"),  #MRMA1S\n",
    "    #colors.to_rgba(\"mediumslateblue\"), #MRMA2S\n",
    "    #colors.to_rgba(\"blue\"),  #BIntraCOLS\n",
    "    #colors.to_rgba(\"royalblue\"), #BIntraP2PS\n",
    "    colors.to_rgba(\"mediumseagreen\"), #BCOLA\n",
    "    colors.to_rgba(\"seagreen\"),  #BCOLT\n",
    "    colors.to_rgba(\"palegreen\"), #BP2PA\n",
    "    colors.to_rgba(\"springgreen\"), #BP2PT\n",
    "    #colors.to_rgba(\"purple\"),  #BRMA1A\n",
    "    #colors.to_rgba(\"darkviolet\"), #BRMA1T\n",
    "    #colors.to_rgba(\"indigo\"),  #BRMA2A\n",
    "    #colors.to_rgba(\"rebeccapurple\"), #BRMA2T\n",
    "    colors.to_rgba(\"indianred\"), #MCOLA \n",
    "    colors.to_rgba(\"firebrick\"), #MCOLT\n",
    "    colors.to_rgba(\"darkgoldenrod\"), #MP2PA\n",
    "    colors.to_rgba(\"saddlebrown\"), #MP2PT\n",
    "    #colors.to_rgba(\"magenta\"),  #MRMA1A\n",
    "    #colors.to_rgba(\"violet\"), #MRMA1T\n",
    "    #colors.to_rgba(\"deeppink\"),  #MRMA2A\n",
    "    #colors.to_rgba(\"mediumvioletred\"), #MRMA2T\n",
    "    #colors.to_rgba(\"mediumblue\"),  #BIntraCOLA\n",
    "    #colors.to_rgba(\"mediumslateblue\"), #BIntraP2PA\n",
    "    colors.to_rgba(\"white\"))\n",
    "cmap = LinearSegmentedColormap.from_list('Custom', myColors, len(myColors))\n",
    "\n",
    "im = ax.imshow(heatmap,cmap=cmap,interpolation='nearest')\n",
    "\n",
    "# Loop over data dimensions and create text annotations.\n",
    "used_aux=0\n",
    "results_str = get_heatmap_strings(heatmap)\n",
    "for i in range(len(processes)):\n",
    "    for j in range(len(processes)):\n",
    "        if i!=j:\n",
    "            aux_color=\"white\"\n",
    "            if 0 <= heatmap[i, j] <= 1 or 4 <= heatmap[i, j] <= 7: # El 1 puede necesitar texto en negro\n",
    "                aux_color=\"black\"\n",
    "            results_index = i*len(processes) +j-used_aux\n",
    "            if len(results_str[results_index]) == 1:\n",
    "                text = results_str[results_index][0]\n",
    "                ax.text(j, i, text, ha=\"center\", va=\"center\", color=aux_color, fontsize=36)\n",
    "            else:\n",
    "                add_aux = 0.33\n",
    "                for line in range(len(results_str[results_index])):\n",
    "                    i_range = i - 0.5 + add_aux\n",
    "                    ax.text(j, i_range, results_str[results_index][line],\n",
    "                            ha=\"center\", va=\"center\", color=aux_color, fontsize=36)\n",
    "                    add_aux+=0.33\n",
    "        else:\n",
    "            used_aux+=1\n",
    "\n",
    "ax.set_ylabel(\"NS\", fontsize=36)\n",
    "ax.set_xlabel(\"NT\", fontsize=36)\n",
    "\n",
    "ax.set_xticklabels(['']+processes, fontsize=36)\n",
    "ax.set_yticklabels(['']+processes, fontsize=36)\n",
    "\n",
    "\n",
    "labelsMethods_aux = ['Baseline - COLS (0)', 'Baseline - P2PS (1)',\n",
    "                    'Merge - COLS (2)','Merge - P2PS (3)',\n",
    "                    'Baseline - COLA (4)', 'Baseline - COLT (5)','Baseline - P2PA (6)','Baseline - P2PT (7)',\n",
    "                    'Merge - COLA (8)','Merge - COLT (9)','Merge - P2PA (10)','Merge - P2PT (11)']\n",
    "\n",
    "#labelsMethods_aux = ['Baseline - COLS (0)', 'Baseline - P2PS (1)',\n",
    "#                    'Baseline - RMA1S (2)', 'Baseline - RMA2S (3)',\n",
    "#                    'Merge - COLS (4)','Merge - P2PS (5)',\n",
    "#                    'Merge - RMA1S (6)', 'Merge - RMA2S (7)',\n",
    "#                    'Baseline - COLA (8)', 'Baseline - COLT (9)','Baseline - P2PA (10)','Baseline - P2PT (11)',\n",
    "#                    'Baseline - RMA1A (12)', 'Baseline - RMA1T (13)','Baseline - RMA2A (14)','Baseline - RMA2T (15)',\n",
    "#                    'Merge - COLA (16)','Merge - COLT (17)','Merge - P2PA (18)','Merge - P2PT (19)',\n",
    "#                    'Merge - RMA1A (20)','Merge - RMA1T (21)','Merge - RMA2A (22)','Merge - RMA2T (23)']\n",
    "\n",
    "colorbar=f.colorbar(im, ax=ax)\n",
    "tick_bar = []\n",
    "for i in range(len(used_config)):\n",
    "    #tick_bar.append(0.41 + i*0.96) #Config de 24 valores\n",
    "    tick_bar.append(0.37 + i*0.92) #Config de 12 valores\n",
    "    #tick_bar.append(0.35 + i*0.89) #Config de 8 valores\n",
    "colorbar.set_ticks(tick_bar) \n",
    "colorbar.set_ticklabels(labelsMethods_aux)\n",
    "colorbar.ax.tick_params(labelsize=32)\n",
    "#\n",
    "\n",
    "f.tight_layout()\n",
    "print(\"Filename: Heatmap_\"+tipo+\".png\")\n",
    "f.savefig(\"Images/Heatmap_\"+tipo+\".png\", format=\"png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0  1  2  3  4  5  6  7  8  9 10 11]\n",
      "[25 18 33 29 10 12 14  8 35 33 38 25]\n",
      "[ 0  1  2  3  6  7  8  9 10 11]\n",
      "[ 8  2  7  2  2  1  6  2 10  2]\n"
     ]
    }
   ],
   "source": [
    "aux_array = [] #Counts all\n",
    "for data in results:\n",
    "    aux_array+=data\n",
    "aux_results, aux_counts = np.unique(aux_array, return_counts=True)\n",
    "print(aux_results)\n",
    "print(aux_counts)\n",
    "\n",
    "aux_array = [0] * len(results) # Counts ganador celda\n",
    "for index in range(len(results)):\n",
    "    aux_array[index] = results[index][0]\n",
    "aux_results, aux_counts = np.unique(aux_array, return_counts = True)\n",
    "print(aux_results)\n",
    "print(aux_counts)\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "El siguiente código asume que para cada número de procesos padre/hijo existen valores en todas las configuraciones que se van a probar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def normalize_arrays(arrays, norm_array):\n",
    "    new_arrays = arrays.copy()\n",
    "    for index in range(len(new_arrays)):\n",
    "        new_arrays[index] = np.divide(norm_array, new_arrays[index])\n",
    "    return new_arrays\n",
    "\n",
    "def create_labels_lineplot(used_direction, user_condition=lambda a, b: True):\n",
    "    labels_aux = []\n",
    "    if used_direction == 's':\n",
    "        for ns_aux in processes:\n",
    "            for np_aux in processes:\n",
    "                if used_direction=='s' and np_aux > ns_aux and np_aux != ns_aux and user_condition(np_aux, ns_aux):\n",
    "                    new_label = \"(\" + str(np_aux) + \",\" + str(ns_aux) + \")\"\n",
    "                    labels_aux.append(new_label)\n",
    "    else:\n",
    "        for np_aux in processes:\n",
    "            for ns_aux in processes:\n",
    "                if ((used_direction=='e' and np_aux < ns_aux) or used_direction=='a') and np_aux != ns_aux and user_condition(np_aux, ns_aux):\n",
    "                    new_label = \"(\" + str(np_aux) + \",\" + str(ns_aux) + \")\"\n",
    "                    labels_aux.append(new_label)\n",
    "    return labels_aux\n",
    "\n",
    "def reorder_data(plot_data, actual_order, expected_order):\n",
    "    ordered_indexes = []\n",
    "    len_order = len(actual_order)\n",
    "    for index in range(len_order):\n",
    "        actual_order[index] = str(actual_order[index]).replace(\" \", \"\")\n",
    "    for index in range(len_order):\n",
    "        ordered_indexes.append(actual_order.index(expected_order[index]))\n",
    "\n",
    "    for index in range(len(plot_data)):\n",
    "        old_array = plot_data[index]\n",
    "        new_array = []\n",
    "        for i in ordered_indexes:\n",
    "            new_array.append(old_array[i])\n",
    "        plot_data[index] = new_array\n",
    "\n",
    "    return plot_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.323355757346239, 3.030253505362803, 4.962079753591042, 5.073696347687594, 4.6485872310119865, 5.651829115400414, 1.4866254088519373, 1.7568049992214487, 1.6963376515513353, 1.991522711002849, 1.805715000130838, 1.9763324311846668, 2.0578737676831538, 2.0938902057975888, 2.1451717803079813, 2.0587975672804264, 2.1158460157292813, 2.213272985714554, 2.1406260270350006, 2.213937442726748, 2.138584606501875]\n",
      "[0.8517393348953153, 1.4210511821557898, 1.311014489752499, 1.2854102377743086, 1.1009843156343821, 1.129708579791164, 1.232902822925454, 2.079506903064128, 2.2989834619936427, 2.277810108246011, 1.9587084262524823, 3.254357815781628, 3.4032610885860834, 3.327166354871418, 3.7002653799106326, 3.3669801788617155, 3.3859212346474585, 3.5279209775250226, 3.4330575720472214, 3.616746479189376, 3.4689442385565115]\n",
      "[1.5331053129781154, 1.4437823145339799, 1.1840525276672385, 1.3910083416640837, 1.3537644110806226, 1.371240815535912, 1.7390375484752898, 1.6461807739785699, 1.3726129754977998, 1.9749969961805982, 2.0030820041028727, 2.1181121375208813, 2.1065001222540802, 2.235637718650906, 2.1703280987638456, 2.1200574092001316, 2.2264486578566878, 2.3882014274467376, 2.0702854045936525, 2.234172484003762, 2.128741025771664]\n",
      "[1.4881719455668072, 1.0544223150145582, 1.166138830987307, 1.1465049463124821, 1.3442988084811376, 1.0421919294507513, 2.565961639578289, 1.939816757165079, 2.3246991647113813, 2.5109178215694867, 1.7573988709826043, 3.539209310998196, 3.426336849449813, 3.307700165692954, 3.423939219914835, 3.417136638250337, 3.5867840373350717, 3.794399045957032, 3.374755462890734, 3.6419539146492275, 3.595285439748643]\n",
      "[1.9256290859911858, 1.633155592889165, 1.6002739185556067, 1.5344706234273549, 1.6171087441897987, 1.4250557500220744, 1.261505254239675, 1.4479958993785371, 1.1696977543338993, 1.1809791254264683, 1.1560227287813816, 1.235618819838239, 1.0413723342168184, 1.1502489425244313, 1.1180868435978668, 1.2677560652141224, 1.2541219852706196, 1.1493601140087222, 1.2072414992588787, 1.1534038769834178, 1.2745861538540628]\n",
      "[1.4506711207886875, 1.5549847977137223, 1.4256877147482565, 1.491834562122785, 1.5167160588150155, 1.293457302659703, 1.5481116684369813, 1.6374194928545591, 1.392589617231472, 1.3664871279430795, 1.2165509428284411, 1.2407540279545834, 1.4162399768384129, 1.20275755698058, 1.0912019767249304, 1.4231474530738426, 1.3879151662114706, 1.1717018251130065, 1.3160451142479224, 1.3920905932657732, 1.5478642677175158]\n",
      "[1.8312480899255763, 1.765109361764655, 1.4660082787877438, 1.8403986467506137, 1.5388273279472926, 1.4322267290154236, 1.1498677071532244, 1.3402093435765183, 1.2349244002951079, 1.1775649409742945, 1.2151692704038575, 1.3084252917463206, 1.2876422196120707, 1.1892569424002815, 1.1427325252015967, 0.9911302227827644, 1.184873408783355, 1.2372595344471262, 1.3376705038495857, 1.193320946872977, 1.1624725776326637]\n",
      "[1.1109679747826517, 1.7335703450481441, 1.310560265700932, 1.5591797452275975, 1.2950554138137105, 1.1008189733123208, 1.6501141953301166, 1.5353771271862118, 1.4753933374275592, 1.2855572204374124, 1.278548644653752, 1.1252530413600392, 1.2644622004982697, 1.2028435836469875, 1.1461303552682292, 1.208945185297192, 1.3634603088910302, 1.371173722439068, 1.5780612178714728, 1.3538289453564387, 1.4926984308117954]\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 2200x1400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "used_direction='e'\n",
    "test_parameter='alpha'\n",
    "\n",
    "if test_parameter == 'alpha':\n",
    "    name_fig=\"Alpha_\"\n",
    "    real_parameter='Alpha'\n",
    "    name_legend = \"Values of α\"\n",
    "    normalize = True\n",
    "    allow_all = False\n",
    "    used_config = configurations_simple\n",
    "    data_aux = grouped_aggM[grouped_aggM[real_parameter] > 0]\n",
    "elif test_parameter == 'T_Malleability':\n",
    "    name_fig=\"Malleability_\"\n",
    "    real_parameter='T_Malleability'\n",
    "    name_legend = \"Time(s)\"\n",
    "    normalize = False\n",
    "    allow_all = True\n",
    "    used_config = configurations_simple\n",
    "    data_aux = grouped_aggM\n",
    "elif test_parameter == 'T_Redistribution':\n",
    "    name_fig=\"Redistribution_\"\n",
    "    real_parameter='T_Redistribution'\n",
    "    name_legend = \"Tiempo(s)\"\n",
    "    normalize = False\n",
    "    allow_all = True\n",
    "    used_config = configurations_simple\n",
    "    data_aux = grouped_aggM\n",
    "    \n",
    "if used_direction=='s':\n",
    "    data_aux=data_aux.query('NP > NC')\n",
    "    name_fig= name_fig+\"Shrink\"\n",
    "elif used_direction=='e':\n",
    "    data_aux=data_aux.query('NP < NC')\n",
    "    name_fig= name_fig+\"Expand\"\n",
    "elif used_direction=='a':\n",
    "    name_fig= name_fig+\"All\"   \n",
    "#data_aux=data_aux.query('NP == 160 or NC == 160')\n",
    "\n",
    "plot_data = []\n",
    "for config in used_config:\n",
    "    if config[0] > 0 or allow_all:\n",
    "        dataLists,procsLists = get_config_data(real_parameter, data_aux, config)\n",
    "        dataLists = list(filter(lambda x: x != float('infinity'), dataLists))\n",
    "        plot_data.append(dataLists)\n",
    "    \n",
    "#labels_aux = create_labels_lineplot(used_direction, lambda a, b: a == 160 or b == 160)\n",
    "labels_aux = create_labels_lineplot(used_direction)\n",
    "plot_data = reorder_data(plot_data, procsLists, labels_aux)\n",
    "\n",
    "#labelsMethods_aux = ['Baseline - COLS', 'Baseline - P2PS',\n",
    "#                    'Merge - COLS','Merge - P2PS',\n",
    "#                    'Baseline - COLA', 'Baseline - P2PA',\n",
    "#                    'Merge - COLA','Merge - P2PA',]\n",
    "labelsMethods_aux = ['Baseline - COLS', 'Baseline - P2PS',\n",
    "                    'Merge - COLS','Merge - P2PS',\n",
    "                    'Baseline - COLA', 'Baseline - COLT','Baseline - P2PA','Baseline - P2PT',\n",
    "                    'Merge - COLA','Merge - COLT','Merge - P2PA','Merge - P2PT']\n",
    "#labelsMethods_aux = ['Baseline - COLS', 'Baseline - P2PS',\n",
    "#                    'Baseline - RMA1S', 'Baseline - RMA2S',\n",
    "#                    'Merge - COLS','Merge - P2PS',\n",
    "#                    'Merge - RMA1S', 'Merge - RMA2S',\n",
    "#                    'Baseline - COLA', 'Baseline - COLT','Baseline - P2PA','Baseline - P2PT',\n",
    "#                    'Baseline - RMA1A', 'Baseline - RMA1T','Baseline - RMA2A','Baseline - RMA2T',\n",
    "#                    'Merge - COLA','Merge - COLT','Merge - P2PA','Merge - P2PT',\n",
    "#                    'Merge - RMA1A','Merge - RMA1T','Merge - RMA2A','Merge - RMA2T'\n",
    "#                    ]\n",
    "#labelsMethods_aux = ['Baseline - COLS', 'Baseline - P2PS',\n",
    "#                    'Merge - COLS','Merge - P2PS',\n",
    "#                    'BaselineIntra - COLS', 'BaselineIntra - P2PS',\n",
    "#                    'Baseline - COLA', 'Baseline - P2PA',\n",
    "#                    'Merge - COLA','Merge - P2PA',\n",
    "#                    'BaselineIntra - COLA', 'BaselineIntra - P2PA']\n",
    "colors_m = ( \n",
    "    colors.to_rgba(\"green\"), #BCOLS\n",
    "    colors.to_rgba(\"darkgreen\"), #BP2PS\n",
    "    #colors.to_rgba(\"blue\"),  #BRMA1S\n",
    "    #colors.to_rgba(\"royalblue\"), #BRMA2S\n",
    "    colors.to_rgba(\"red\"), #MCOLS\n",
    "    colors.to_rgba(\"darkred\"),  #MP2PS\n",
    "    #colors.to_rgba(\"mediumblue\"),  #MRMA1S\n",
    "    #colors.to_rgba(\"mediumslateblue\"), #MRMA2S\n",
    "    #colors.to_rgba(\"blue\"),  #BIntraCOLS\n",
    "    #colors.to_rgba(\"royalblue\"), #BIntraP2PS\n",
    "    colors.to_rgba(\"mediumseagreen\"), #BCOLA\n",
    "    colors.to_rgba(\"seagreen\"),  #BCOLT\n",
    "    colors.to_rgba(\"palegreen\"), #BP2PA\n",
    "    colors.to_rgba(\"springgreen\"), #BP2PT\n",
    "    #colors.to_rgba(\"purple\"),  #BRMA1A\n",
    "    #colors.to_rgba(\"darkviolet\"), #BRMA1T\n",
    "    #colors.to_rgba(\"indigo\"),  #BRMA2A\n",
    "    #colors.to_rgba(\"rebeccapurple\"), #BRMA2T\n",
    "    colors.to_rgba(\"indianred\"), #MCOLA \n",
    "    colors.to_rgba(\"firebrick\"), #MCOLT\n",
    "    colors.to_rgba(\"darkgoldenrod\"), #MP2PA\n",
    "    colors.to_rgba(\"saddlebrown\"), #MP2PT\n",
    "    #colors.to_rgba(\"magenta\"),  #MRMA1A\n",
    "    #colors.to_rgba(\"violet\"), #MRMA1T\n",
    "    #colors.to_rgba(\"deeppink\"),  #MRMA2A\n",
    "    #colors.to_rgba(\"mediumvioletred\"), #MRMA2T\n",
    "    #colors.to_rgba(\"mediumblue\"),  #BIntraCOLA\n",
    "    #colors.to_rgba(\"mediumslateblue\"), #BIntraP2PA\n",
    "    )\n",
    "\n",
    "f=plt.figure(figsize=(22, 14))\n",
    "ax=f.add_subplot(111)\n",
    "x = np.arange(len(labels_aux))\n",
    "for index in range(len(plot_data)):\n",
    "    array_aux = plot_data[index]\n",
    "    plot_index = index\n",
    "    if real_parameter == 'Alpha' or real_parameter == 'Omega' or real_parameter == 'count': #FIXME This line is a lie...\n",
    "        plot_index = 4 + index #FIXME This line is a lie...\n",
    "    print(array_aux)\n",
    "    ax.plot(x, array_aux, color=colors_m[plot_index%len(colors_m)], linestyle=linestyle_m[plot_index%len(linestyle_m)], \\\n",
    "        marker=markers_m[plot_index%len(markers_m)], markersize=18, label=labelsMethods_aux[plot_index])\n",
    "\n",
    "ax.set_xlabel(\"(NP,NH)\", fontsize=36)\n",
    "ax.set_ylabel(name_legend, fontsize=36)\n",
    "if normalize:\n",
    "    ax.axhline(y=1, color='black', linestyle='--')\n",
    "plt.xticks(x, labels_aux,rotation=90)\n",
    "ax.tick_params(axis='both', which='major', labelsize=36)\n",
    "ax.tick_params(axis='both', which='minor', labelsize=36)\n",
    "plt.legend(loc='best', fontsize=30,ncol=2,framealpha=0.8)\n",
    "        \n",
    "f.tight_layout()\n",
    "f.savefig(\"Images/LinePlot_\"+name_fig+\".png\", format=\"png\")"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Gráfica de lineas para generar tiempos del grupo G."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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XuuwcAcBZ4uPj1bRpUyUkJFw1N6/0N8Mw9Le//U2zZs2yvUoo1+hA8UTjCACXudpN/5wXXT4+PkpPT3dLXQBQ1HFxBaA4OnDggFq1aqWkpKR838zP/nfDMBQZGal58+apfPnytuYmNwEUN1f7ooUzXO3DgJyvIzcBFAeHDx9Wo0aNHO4fmqapUqVKKTIyUo0bN1apUqV07NgxLV++XCdPnrS+Qe/n56eoqCj985//1Lfffmvtr1u3rt58803deuutue5jHjt2TC+//LJmz56dqxFl/fr16tixo1vPHwDsGjx4sL777rtczXK+vr6KiIhQWFiYkpKSdODAAUVFRUlSrtcahqGbbrpJ8+fPV1BQUL7n5hodKJ78PF0AgJLr8OHDDtunTp3SqlWrtHLlSq1fv16JiYnW3+hhAwAAKN4efPDBXE0jpmkqJCREvXr1crgptXr1al26dMl6bdbN+9WrV6t79+5aunSpKleu7KlTAQC3cce1MNfbAEqCWbNmKS0tzXrfaBiGBgwYoBkzZqh69eoOr01LS9M777yjF154QaZpKiMjQzNnztSiRYus95/t27fX4sWLVbFixTznq1Wrlj766CPdeOONGj58uMPfPvzwQxpHABRpv/76q0PTSFZujhkzRhMmTMh1vb17927NmDFDH374odLS0iRdvk5ftmyZbr75Zv3www8qU6aM288FgPuw4ggAj0hPT9eWLVu0atUqrVixQps2bVJSUpKnywKAIoGufADFzdq1axUZGelwUyogIECvv/66Hn/8cfn5OX5n4cyZM/rkk080efJknT59OtdqdE2aNNGKFSsUGhqar/nJTQDFDSuOAIA9tWvXVkxMjJVbvXv31uLFi6+acTNmzNDo0aNlGIZKlSqllJQUSVLFihW1a9cu1ahRI19zjxs3Tu+++671IWrlypV18uRJp5wXALjCQw89ZK2YZJqmfHx89PHHH+u+++676nFRUVG69957tW3btlxNJ+3bt9ePP/6ocuXKXXN+rtGB4onGEQBFQmpqqgICAjxdBgAUCVxcAShuhg0bpq+++sq6KRUQEKBFixapZ8+eVz3u9OnTGjFiRK5vQklSgwYNtHLlynzd0Cc3ARQ3WY0jReG2HLkJoKiLjY1VjRo1rNz09/fXwYMHVbNmzWse26lTJ23atMnaNgxDzz33nF555ZV8z3/mzBlr9bys95sHDhxQnTp1CnQ+AOBqoaGh+vPPP63MeuKJJ/T222/n69j09HSNGzdO06ZNy9U80qZNGy1dulQVKlS46hhcowPFE4+qAVAk0DQCoCipW7euR+c/ceKER+cHALt++uknh2XDJ02adM2mEUkKCQnR/Pnz9a9//UvPPPOMMjMzrXH279+vbt26aeXKlQoLC3PDWQCAZ2R9g3PixIkKDAws9HgjRozQoUOHrExeuXKlE6oEAM/Zvn279bthGOrTp0++mkakvzJx06ZNDs16d999t635K1asqJtvvllz58619u3cuZPGEQBF0uHDh3Xq1Cmr6aNs2bKaMGFCvo/38/PT+++/ryZNmuixxx5zuE7ftm2bevbsqWXLlqlSpUquOgUAHkLjCAAAQA7R0dEe/waoK5cuBwBn2rt3r86ePWvlVpUqVTR27FhbY4wbN04NGzbUXXfdpaSkJGusQ4cOqVu3blq1apWuv/56J1cOAJ7ToEED7d+/38q7zZs3a+zYsZo1a5ZuvPHGQo2d89nz3bp1K9R4AOBpcXFxDtt2crJz584O22XLllXjxo1t19ChQweHxpHTp0/bHgMA3OHXX3+1fjcMQ/3798/X42VyGjVqlKpXr6677rpLly5dsu6V7tixQz179tTy5csVEhLixMoBeJqPpwsAAAAoqgzD8NgPABQXv/32m/W7YRjq16+fSpUqZXuc/v37a8WKFQ7fWjIMQ0eOHFG3bt106NAhp9QLAEXBzp07NXbsWIf3fVFRUerWrZv+8Y9/KCkpyYPVAUDRcvbsWUmXH2mY39VGJOV67GGVKlUKVEO1atUkXf6SR1ZNAFDUZDW2ZWVm+/btCzzWoEGD9MMPPyg4OFjS5QzcuXOnevTooVOnThWyWgBFCY0jAAAAAIACO3PmjKTLN6UiIiIKPFa7du20atUqhYaGWvsMw9CxY8cUGRmpAwcOFK5YACgiAgMD9a9//UurV69W3bp1rcfKZGZmatq0aWrevLlWrFjh6TIBoEi4dOmSw7adx3rlfG1BGpyl3I/ZTk1NLdA4AOBqWdfoWbJfXxdEjx499OOPP6ps2bKSLjeP/Pbbb+revbtOnjxZqPEBFB00jgAAAFyBaZoe+wGA4iLnTamCfoszS7NmzbR69Wpdd9111j7DMBQTE6PIyEjt27evUOMDQFHSuXNn7dq1S2PGjJF0+Ub84cOH1bt3bz388MM6f/68J0sEAI8rX768w7ad1T5yvjYhIaFANeRsli7IYx8AwB0yMzMdtjMyMgo9ZqdOnbRs2TJVqFBB0uX3rLt371b37t0VHx9f6DkAeB6NIwAAADnk/Kb7Y489pszMTLf9tGzZ0oNnDwD2+Pg4XlampKQUeswbbrhBa9euVa1atax9hmHoxIkT6t69u/bu3VvoOQCgqAgKCtL777+vlStX6vrrr7dWHzFNU7Nnz1bTpk21aNEiT5cJAB5TsWJFSY7fcs+v33//3WE7Pj7eeoyDHTnnzPrwFACKmpz55KwVQdq2bavly5fnyuQ9e/YoMjJSsbGxTpkHgOf4eboAAEWLaZo6duyYDh06ZF1IJSUlKTU1VaZpKiAgQMHBwQoJCVFoaKjq1KmjsLAwh+cyA0BxFxERoUWLFlnZtm3bNg9XBABFV86bUs56xnHdunW1Zs0ade/eXUeOHJH0142p2NhYRUZGatWqVWrcuLFT5gKAoqBbt2767bff9NRTT2nmzJnWe9Hjx49r0KBBGjZsmN5//31VqlTJw5UCgHs1atTI+t00TS1evFjvvvtuvo7Nq/Fu6dKlGjZsmK0ali5dajX1SVLt2rVtHQ8A7lK1alVJlxs7jh075rSxw8PDtXLlSvXq1UunT5+2cjEqKsq6Tq9evbrT5gPgXjSOANDatWu1ZMkSrVu3Tjt37lRSUpKt44OCgtSyZUt17dpVffv2Vbdu3VxUKQC4R1bjiPTXTamdO3cqMzMz17fqAQCyHimT/fEKzlK7dm2reSRrXMMwdPLkSUVGRmrlypVq2rSp0+YDAE8rXbq0/vOf/2jIkCEaPny4jhw5Yt2Q//LLL7Vs2TJNmzZNd9xxh6dLBQC3ad68uQICApSWliZJOnjwoL788strNn/ExcVp1qxZVo5m/d933nnHVuPI999/r3379lnvd318fNS6deuCnxAAuFCTJk2s303T1Pr16506fosWLazmkVOnTlnZun//fus6HUDxxKcfgJc6d+6cXn31VYWFhal79+568803tXHjRiUmJso0TVs/SUlJ2rRpk95880316NFDtWrV0quvvmrreaMAUJREREQ4bCcnJ+uPP/7wUDUAULRlb9wwTVNr16516vi1atXSmjVrVK9ePWufYRg6deqUevTooV27dllzA0BJ0aNHD/3222966KGHrA87pb9Wdbrrrrt0++238yx5AF7D399fPXv2dGj+ePTRR7V169YrHnPhwgUNGTLEuj8ZERFhZemOHTv00ksv5WvuuLg4jRo1ymG15RYtWqh06dIFPh8AcKUGDRqoVKlS1vaOHTuUmJjo1DmaNWumlStX5lrd5ODBg+rWrZsSEhK4RgeKIRpHAC80c+ZM1a1bVxMnTlRMTIxDE4hhGAX6yT7G8ePHNXHiRNWtW1czZszw9OkCgG1t2rTJtY/H1QBA3urUqaPg4GBr+48//tCZM2ecOkeNGjW0evVqNWjQwOHm06lTp9SzZ0/FxcU5dT4AKArKlCmjmTNn6qefflLNmjUdPjBdsGCBmjRpojlz5ni6TABwiwcffND63TAMnT17Vl27dtVTTz2lbdu2KTExUWlpaTp06JD+85//qFmzZtq4caN1zIgRI9SxY0dJfzUcv/LKK3r66aeVkpJyxTm3bdumzp07KzY21jrOMAzdf//9LjpLACg8Hx8ftW/f3rp2zsjI0Hfffef0eZo0aaJVq1apWrVqkhxXIY2JiXFouANQPBgmLV+A10hJSdE999yjBQsWWG8a8vrH224sXG0MwzA0aNAgffHFFwoKCipA1QDgGTVr1lRsbKx1Y2jUqFGaPn26W+YODw/Xrl27rLkzMjLcMi8AFFTfvn21dOlSSX+9//vggw/08MMPO32euLg49ejRQ3v37rXeg2b/Jj65CaCkunDhgsaOHatPPvkkV+b16dNHM2fOVK1atSTxXhJAyZSRkaGIiAhrtTnJ8X1gTtnvb1atWlXR0dGaO3eu7rvvPodH14SGhuqOO+5Qhw4dVKVKFSUnJ+vw4cNavHixli1bluu9ZpkyZXT06FFVqFDBpecLAIUxadIkTZo0ycqvHj16aNmyZS6Za9++ferevbvDFzqyNzzzfhQoPmgcAbxEWlqa+vbtq9WrV+e6qMoeA2FhYapXr57CwsJUq1YtlSlTRkFBQQoKCpJhGEpOTlZycrIuXryoY8eO6ejRozp48KCOHDlijZFzbMMw1LVrVy1dulT+/v7uOWEAKKRbb71VCxcutDItIiJCmzdvdsvc3OwHUNxMmTJFzz77rJWZbdu21aZNm1wy18mTJ9WjRw/t3r0714en5CaAkm7JkiV6+OGHdfz4cYfcK1OmjN58802NHDmS95IASqzt27erU6dOSktLs/Zd6eON7Bn52Wef6e6771ZGRoZatWql3bt3Oxx7teaTnO83p06dqtGjRzvztADA6X7++Wd16dLFykIfHx/t379fderUccl8Bw4cUI8ePXT8+HGH/bwfBYoXGkcAL/H4449r2rRpuZo6/P39NWjQIA0ZMkRdunRR9erVCzR+bGys1q9fr7lz52rBggVKS0vLdWE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      "text/plain": [
       "<Figure size 2200x1400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "used_direction='s'\n",
    "test_parameter='T_total' #Valores son \"alpha\" o \"omega\"\n",
    "intranode=False\n",
    "\n",
    "if test_parameter == 'T_total':\n",
    "    name_fig=\"Ttotal\"\n",
    "    real_parameter='T_total'\n",
    "    name_legend = \"Time(s)\"\n",
    "    used_config = configurations\n",
    "    data_aux = grouped_aggG\n",
    "    #data_aux = data_aux[data_aux.index.isin(df1.index)]\n",
    "    \n",
    "if used_direction=='s':\n",
    "    data_aux_cmp=grouped_aggM.reset_index().query('NP > NC')\n",
    "    name_fig= name_fig+\"Shrink\"\n",
    "elif used_direction=='e':\n",
    "    data_aux_cmp=grouped_aggM.reset_index().query('NP < NC')\n",
    "    name_fig= name_fig+\"Expand\"\n",
    "elif used_direction=='a':\n",
    "    data_aux_cmp=grouped_aggM.reset_index()\n",
    "    name_fig= name_fig+\"All\"\n",
    "    \n",
    "if intranode:\n",
    "    data_aux_cmp = data_aux_cmp.query('NP <= 20 and NC <= 20')\n",
    "#else:\n",
    "    #data_aux_cmp = data_aux_cmp.query('NP > 20 and NC > 20')\n",
    "data_aux_cmp = data_aux_cmp.query('NP == 160 or NC == 160')\n",
    "\n",
    "if used_direction!='a' or True:\n",
    "    pruebaG = data_aux.reset_index()\n",
    "    pruebaG = pruebaG.loc[pruebaG.index.intersection(data_aux_cmp.index)]\n",
    "    data_aux = data_aux[(data_aux.T_total.isin(pruebaG.T_total))]\n",
    "\n",
    "plot_data = []\n",
    "for config in used_config:\n",
    "    #if config[0] == 0:\n",
    "    dataLists,procsLists = get_config_data(real_parameter, data_aux, config)\n",
    "    dataLists = list(filter(lambda x: x != float('infinity'), dataLists))\n",
    "    plot_data.append(dataLists)\n",
    "\n",
    "plot_data_normalized = normalize_arrays(plot_data[1:], plot_data[0])\n",
    "name_legend=\"SpeedUp over Baseline\"\n",
    "\n",
    "labels_aux = create_labels_lineplot(used_direction, lambda a, b: a == 160 or b == 160)\n",
    "#labels_aux = create_labels_lineplot(used_direction)\n",
    "#labelsMethods_aux = ['Baseline - All', 'Baseline - P2P',\n",
    "#                   'Merge - All','Merge - P2P']\n",
    "labelsMethods_aux = ['Baseline - COLS', 'Baseline - P2PS',\n",
    "                    'Merge - COLS','Merge - P2PS',\n",
    "                    'Baseline - COLA', 'Baseline - COLT','Baseline - P2PA','Baseline - P2PT',\n",
    "                    'Merge - COLA','Merge - COLT','Merge - P2PA','Merge - P2PT']\n",
    "#labelsMethods_aux = ['Baseline - COLS', 'Baseline - P2PS',\n",
    "#                    'Baseline - RMA1S', 'Baseline - RMA2S',\n",
    "#                    'Merge - COLS','Merge - P2PS',\n",
    "#                    'Merge - RMA1S', 'Merge - RMA2S',\n",
    "#                    'Baseline - COLA', 'Baseline - COLT','Baseline - P2PA','Baseline - P2PT',\n",
    "#                    'Baseline - RMA1A', 'Baseline - RMA1T','Baseline - RMA2A','Baseline - RMA2T',\n",
    "#                    'Merge - COLA','Merge - COLT','Merge - P2PA','Merge - P2PT',\n",
    "#                    'Merge - RMA1A','Merge - RMA1T','Merge - RMA2A','Merge - RMA2T'\n",
    "#                    ]\n",
    "\n",
    "colors_m = ( \n",
    "    colors.to_rgba(\"green\"), #BCOLS\n",
    "    colors.to_rgba(\"darkgreen\"), #BP2PS\n",
    "    #colors.to_rgba(\"blue\"),  #BRMA1S\n",
    "    #colors.to_rgba(\"royalblue\"), #BRMA2S\n",
    "    colors.to_rgba(\"red\"), #MCOLS\n",
    "    colors.to_rgba(\"darkred\"),  #MP2PS\n",
    "    #colors.to_rgba(\"mediumblue\"),  #MRMA1S\n",
    "    #colors.to_rgba(\"mediumslateblue\"), #MRMA2S\n",
    "    #colors.to_rgba(\"blue\"),  #BIntraCOLS\n",
    "    #colors.to_rgba(\"royalblue\"), #BIntraP2PS\n",
    "    colors.to_rgba(\"mediumseagreen\"), #BCOLA\n",
    "    colors.to_rgba(\"seagreen\"),  #BCOLT\n",
    "    colors.to_rgba(\"palegreen\"), #BP2PA\n",
    "    colors.to_rgba(\"springgreen\"), #BP2PT\n",
    "    #colors.to_rgba(\"purple\"),  #BRMA1A\n",
    "    #colors.to_rgba(\"darkviolet\"), #BRMA1T\n",
    "    #colors.to_rgba(\"indigo\"),  #BRMA2A\n",
    "    #colors.to_rgba(\"rebeccapurple\"), #BRMA2T\n",
    "    colors.to_rgba(\"indianred\"), #MCOLA \n",
    "    colors.to_rgba(\"firebrick\"), #MCOLT\n",
    "    colors.to_rgba(\"darkgoldenrod\"), #MP2PA\n",
    "    colors.to_rgba(\"saddlebrown\"), #MP2PT\n",
    "    #colors.to_rgba(\"magenta\"),  #MRMA1A\n",
    "    #colors.to_rgba(\"violet\"), #MRMA1T\n",
    "    #colors.to_rgba(\"deeppink\"),  #MRMA2A\n",
    "    #colors.to_rgba(\"mediumvioletred\"), #MRMA2T\n",
    "    #colors.to_rgba(\"mediumblue\"),  #BIntraCOLA\n",
    "    #colors.to_rgba(\"mediumslateblue\"), #BIntraP2PA\n",
    "    )\n",
    "\n",
    "\n",
    "f=plt.figure(figsize=(22, 14))\n",
    "ax=f.add_subplot(111)\n",
    "ax2 = ax.twinx()\n",
    "x = np.arange(len(labels_aux))\n",
    "for index in range(len(plot_data_normalized)):\n",
    "    array_aux = plot_data_normalized[index]\n",
    "    index= index+1\n",
    "    ax.plot(x, array_aux, color=colors_m[index%len(colors_m)], linestyle=linestyle_m[index%len(linestyle_m)], \\\n",
    "        marker=markers_m[index%len(markers_m)], markersize=18, label=labelsMethods_aux[index])\n",
    "ax2.plot(x, plot_data[0], color='black', linestyle=linestyle_m[0], \\\n",
    "        marker=markers_m[0], markersize=18, label=labelsMethods_aux[0])\n",
    "ax.axhline(y=1, color='black', linestyle='--')\n",
    "\n",
    "ax.set_xlabel(\"(NS,NT)\", fontsize=36)\n",
    "ax.set_ylabel(name_legend, fontsize=36)\n",
    "ax.tick_params(axis='both', which='both', labelsize=36)\n",
    "ax.set_xticks(x)\n",
    "ax.set_xticklabels(labels_aux, rotation=90)\n",
    "#ax.legend(loc='best', fontsize=30,ncol=2,framealpha=0.8)\n",
    "\n",
    "ax2.set_ylabel('Baseline Time(s)', fontsize=36)\n",
    "ax2.tick_params(axis='y', which='both', labelsize=36)\n",
    "#ax2.legend(loc='best', fontsize=30,ncol=2,framealpha=0.8)\n",
    "\n",
    "f.legend(bbox_to_anchor=(0.5, 0.98), fontsize=26,ncol=2,framealpha=0.8)\n",
    "\n",
    "        \n",
    "f.tight_layout()\n",
    "f.savefig(\"Images/LinePlot_\"+name_fig+\".png\", format=\"png\")"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "El siguiente generá una imagen en 3d de T_total para cada una de las diferentes configuraciones."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_3d_image(config, name):\n",
    "    fig, ax = plt.subplots(1, 1, subplot_kw={'projection': '3d'}, figsize=(15, 15))\n",
    "\n",
    "    Z = [None] * len(processes)\n",
    "    X, Y = np.meshgrid(processes, processes)\n",
    "    for i in range(len(processes)):\n",
    "        np_aux = processes[i]\n",
    "        Z[i] = [0] * len(processes)\n",
    "        Z[i][i] = grouped_aggLSynch.loc[np_aux, 'T_iter'] * 1000\n",
    "        for j in range(len(processes)):\n",
    "            if i!=j:\n",
    "                ns_aux = processes[j]\n",
    "                config.append((np_aux,ns_aux))\n",
    "                aux = grouped_aggG.loc[tuple(config),'T_total']\n",
    "                config.pop()\n",
    "            \n",
    "                Z[i][j] = aux.values[0]\n",
    "                #Z[i][j] = Z[i][j] / Z[i][i]\n",
    "        #Z[i][i] = 1\n",
    "\n",
    "    Z = np.array(Z)\n",
    "\n",
    "    ax.plot_surface(X, Y, Z, rstride=1, cstride=1,\n",
    "                cmap='viridis', edgecolor='none')\n",
    "    ax.view_init(15, 25)\n",
    "    ax.set_xlabel(\"NC\", fontsize=16)\n",
    "    ax.set_ylabel(\"NP\", fontsize=16)\n",
    "    ax.set_zlabel(\"Normalized time\", fontsize=16)\n",
    "    ax.set_title(name, fontsize=10)\n",
    "    plt.show()\n",
    "    \n",
    "for index in range(len(configurations)):\n",
    "    used_config = configurations[index]\n",
    "    generate_3d_image(used_config,str(index))"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "El siguiente código es computar la coherencia de T_malleability respecto a los tiempos internos de maleabilidad (Coherency1)\n",
    "y por otro lado de T_malleability respecto a iteraciones asíncronas más los pasos síncronos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_5572/389841414.py:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  test[\"Resize_Coherency\"] = test[\"T_Malleability\"] >= (test[\"T_spawn\"] + test[\"T_SR\"] + test[\"T_AR\"])\n",
      "/tmp/ipykernel_5572/389841414.py:6: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  test[\"Resize_Coherency2\"] = test[\"T_Malleability\"] >= 0\n"
     ]
    },
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NP</th>\n",
       "      <th>NC</th>\n",
       "      <th>Total_Stages</th>\n",
       "      <th>Granularity</th>\n",
       "      <th>SDR</th>\n",
       "      <th>ADR</th>\n",
       "      <th>DR</th>\n",
       "      <th>Redistribution_Method</th>\n",
       "      <th>Redistribution_Strategy</th>\n",
       "      <th>Spawn_Method</th>\n",
       "      <th>...</th>\n",
       "      <th>T_iter</th>\n",
       "      <th>T_stages</th>\n",
       "      <th>T_spawn</th>\n",
       "      <th>T_spawn_real</th>\n",
       "      <th>T_SR</th>\n",
       "      <th>T_AR</th>\n",
       "      <th>T_Malleability</th>\n",
       "      <th>T_Redistribution</th>\n",
       "      <th>Resize_Coherency</th>\n",
       "      <th>Resize_Coherency2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3365</th>\n",
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       "      <td>((0.010719, 0.000228, 0.000233, 0.066149), (0....</td>\n",
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       "      <td>6.733354</td>\n",
       "      <td>8.737903</td>\n",
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       "      <td>False</td>\n",
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       "      <td>0</td>\n",
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       "      <td>1.386556</td>\n",
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       "      <td>6.351965</td>\n",
       "      <td>8.302590</td>\n",
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       "      <td>100000</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>(0.161248, 0.144384, 0.144557, 0.14431, 0.1442...</td>\n",
       "      <td>((0.12486, 2.3e-05, 4e-06, 0.036361), (0.12485...</td>\n",
       "      <td>1.305879</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.335867</td>\n",
       "      <td>6.975850</td>\n",
       "      <td>8.601865</td>\n",
       "      <td>7.311717</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>3378</th>\n",
       "      <td>10</td>\n",
       "      <td>80</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>2</td>\n",
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       "      <td>0</td>\n",
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       "      <td>(0.161471, 0.14405, 0.14408, 0.144116, 0.14397...</td>\n",
       "      <td>((0.124837, 5.1e-05, 4e-06, 0.036579), (0.1248...</td>\n",
       "      <td>1.258065</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.387988</td>\n",
       "      <td>7.279656</td>\n",
       "      <td>8.921822</td>\n",
       "      <td>7.667644</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>3379</th>\n",
       "      <td>10</td>\n",
       "      <td>80</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>2</td>\n",
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       "      <td>0</td>\n",
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       "      <td>1.281582</td>\n",
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       "      <td>0.324005</td>\n",
       "      <td>4.475577</td>\n",
       "      <td>6.053441</td>\n",
       "      <td>4.799582</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>4942</th>\n",
       "      <td>80</td>\n",
       "      <td>120</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>(0.084336, 0.068905, 0.069441, 0.069713, 0.068...</td>\n",
       "      <td>((0.01874, 0.000139, 0.000249, 0.065207), (0.0...</td>\n",
       "      <td>1.562654</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.566601</td>\n",
       "      <td>9.522060</td>\n",
       "      <td>11.642518</td>\n",
       "      <td>10.088661</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4946</th>\n",
       "      <td>10</td>\n",
       "      <td>160</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>(0.158281, 0.141393, 0.14133, 0.141432, 0.1413...</td>\n",
       "      <td>((0.124845, 7.9e-05, 6e-06, 0.033346), (0.1248...</td>\n",
       "      <td>1.207222</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.331889</td>\n",
       "      <td>4.651429</td>\n",
       "      <td>6.166739</td>\n",
       "      <td>4.983318</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5015</th>\n",
       "      <td>20</td>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>(0.11029, 0.096805, 0.096761, 0.09668, 0.09663...</td>\n",
       "      <td>((0.071351, 4.6e-05, 4e-06, 0.038875), (0.0713...</td>\n",
       "      <td>1.572005</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.383955</td>\n",
       "      <td>8.767849</td>\n",
       "      <td>10.691947</td>\n",
       "      <td>9.151804</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5019</th>\n",
       "      <td>20</td>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>(0.112086, 0.100412, 0.100434, 0.100389, 0.100...</td>\n",
       "      <td>((0.071344, 6e-05, 5e-06, 0.040672), (0.071354...</td>\n",
       "      <td>1.422274</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.397735</td>\n",
       "      <td>10.347937</td>\n",
       "      <td>12.158303</td>\n",
       "      <td>10.745672</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5024</th>\n",
       "      <td>80</td>\n",
       "      <td>160</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>3.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>(0.075681, 0.067709, 0.077475, 0.072077, 0.061...</td>\n",
       "      <td>((0.018734, 0.000245, 0.000277, 0.056425), (0....</td>\n",
       "      <td>1.461519</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.402368</td>\n",
       "      <td>9.199978</td>\n",
       "      <td>11.053583</td>\n",
       "      <td>9.602346</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>112 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       NP   NC  Total_Stages  Granularity  SDR   ADR          DR  \\\n",
       "3365  160   40             4       100000  3.4  96.6  3947883503   \n",
       "3369  160   40             4       100000  3.4  96.6  3947883503   \n",
       "3377   10   80             4       100000  3.4  96.6  3947883503   \n",
       "3378   10   80             4       100000  3.4  96.6  3947883503   \n",
       "3379   10   80             4       100000  3.4  96.6  3947883503   \n",
       "...   ...  ...           ...          ...  ...   ...         ...   \n",
       "4942   80  120             4       100000  3.4  96.6  3947883503   \n",
       "4946   10  160             4       100000  3.4  96.6  3947883503   \n",
       "5015   20   40             4       100000  3.4  96.6  3947883503   \n",
       "5019   20   40             4       100000  3.4  96.6  3947883503   \n",
       "5024   80  160             4       100000  3.4  96.6  3947883503   \n",
       "\n",
       "      Redistribution_Method  Redistribution_Strategy  Spawn_Method  ...  \\\n",
       "3365                      3                        1             0  ...   \n",
       "3369                      3                        1             0  ...   \n",
       "3377                      2                        1             0  ...   \n",
       "3378                      2                        1             0  ...   \n",
       "3379                      2                        1             0  ...   \n",
       "...                     ...                      ...           ...  ...   \n",
       "4942                      2                        1             0  ...   \n",
       "4946                      2                        1             0  ...   \n",
       "5015                      3                        1             0  ...   \n",
       "5019                      3                        1             0  ...   \n",
       "5024                      3                        1             0  ...   \n",
       "\n",
       "                                                 T_iter  \\\n",
       "3365  (0.080089, 0.068342, 0.07505, 0.072798, 0.0699...   \n",
       "3369  (0.086699, 0.066044, 0.075696, 0.06642, 0.0639...   \n",
       "3377  (0.161248, 0.144384, 0.144557, 0.14431, 0.1442...   \n",
       "3378  (0.161471, 0.14405, 0.14408, 0.144116, 0.14397...   \n",
       "3379  (0.159191, 0.142719, 0.142697, 0.142688, 0.142...   \n",
       "...                                                 ...   \n",
       "4942  (0.084336, 0.068905, 0.069441, 0.069713, 0.068...   \n",
       "4946  (0.158281, 0.141393, 0.14133, 0.141432, 0.1413...   \n",
       "5015  (0.11029, 0.096805, 0.096761, 0.09668, 0.09663...   \n",
       "5019  (0.112086, 0.100412, 0.100434, 0.100389, 0.100...   \n",
       "5024  (0.075681, 0.067709, 0.077475, 0.072077, 0.061...   \n",
       "\n",
       "                                               T_stages   T_spawn  \\\n",
       "3365  ((0.010719, 0.000228, 0.000233, 0.066149), (0....  1.361993   \n",
       "3369  ((0.010715, 0.000236, 0.000177, 0.075494), (0....  1.386556   \n",
       "3377  ((0.12486, 2.3e-05, 4e-06, 0.036361), (0.12485...  1.305879   \n",
       "3378  ((0.124837, 5.1e-05, 4e-06, 0.036579), (0.1248...  1.258065   \n",
       "3379  ((0.12483, 6.2e-05, 5e-06, 0.034293), (0.12483...  1.281582   \n",
       "...                                                 ...       ...   \n",
       "4942  ((0.01874, 0.000139, 0.000249, 0.065207), (0.0...  1.562654   \n",
       "4946  ((0.124845, 7.9e-05, 6e-06, 0.033346), (0.1248...  1.207222   \n",
       "5015  ((0.071351, 4.6e-05, 4e-06, 0.038875), (0.0713...  1.572005   \n",
       "5019  ((0.071344, 6e-05, 5e-06, 0.040672), (0.071354...  1.422274   \n",
       "5024  ((0.018734, 0.000245, 0.000277, 0.056425), (0....  1.461519   \n",
       "\n",
       "     T_spawn_real      T_SR       T_AR  T_Malleability  T_Redistribution  \\\n",
       "3365          0.0  0.655943   6.733354        8.737903          7.389297   \n",
       "3369          0.0  0.571906   6.351965        8.302590          6.923871   \n",
       "3377          0.0  0.335867   6.975850        8.601865          7.311717   \n",
       "3378          0.0  0.387988   7.279656        8.921822          7.667644   \n",
       "3379          0.0  0.324005   4.475577        6.053441          4.799582   \n",
       "...           ...       ...        ...             ...               ...   \n",
       "4942          0.0  0.566601   9.522060       11.642518         10.088661   \n",
       "4946          0.0  0.331889   4.651429        6.166739          4.983318   \n",
       "5015          0.0  0.383955   8.767849       10.691947          9.151804   \n",
       "5019          0.0  0.397735  10.347937       12.158303         10.745672   \n",
       "5024          0.0  0.402368   9.199978       11.053583          9.602346   \n",
       "\n",
       "     Resize_Coherency Resize_Coherency2  \n",
       "3365            False              True  \n",
       "3369            False              True  \n",
       "3377            False              True  \n",
       "3378            False              True  \n",
       "3379            False              True  \n",
       "...               ...               ...  \n",
       "4942            False              True  \n",
       "4946            False              True  \n",
       "5015            False              True  \n",
       "5019            False              True  \n",
       "5024            False              True  \n",
       "\n",
       "[112 rows x 28 columns]"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test=dfM[(dfM.Asynch_Iters > 0)]\n",
    "\n",
    "# Seguro con barriers en Malleability\n",
    "test[\"Resize_Coherency\"] = test[\"T_Malleability\"] >= (test[\"T_spawn\"] + test[\"T_SR\"] + test[\"T_AR\"])\n",
    "# Seguro al usar Rigid para iteraciones\n",
    "test[\"Resize_Coherency2\"] = test[\"T_Malleability\"] >= 0\n",
    "\n",
    "for index in range(len(test)):\n",
    "    time_malleability_aux = test[\"T_Malleability\"].values[index]\n",
    "    time_synch_aux = test[\"T_SR\"].values[index]\n",
    "    time_spawn_aux = test[\"T_spawn\"].values[index]\n",
    "    is_asynch_spawn = (test[\"Spawn_Strategy\"].values[index] % 2 == 0)\n",
    "    \n",
    "    total_asynch_iters = int(test[\"Asynch_Iters\"].values[index])\n",
    "    asynch_iters = test[\"T_iter\"].values[index][-total_asynch_iters:]\n",
    "    time_iters_aux = np.sum(asynch_iters[:])\n",
    "    \n",
    "    sum_times = time_synch_aux + is_asynch_spawn * time_spawn_aux + time_iters_aux\n",
    "    \n",
    "    if time_malleability_aux < sum_times:\n",
    "        real_index = test.index.values[index]\n",
    "        test.at[real_index, \"Resize_Coherency2\"] = False\n",
    "test[(test.Resize_Coherency == False)].query('Redistribution_Method > 1')"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "El siguiente código es para utilizar Dask. Una versión que paraleliza una serie de tareas de Pandas.\n",
    "Tras llamar a compute se realizan todas las tareas que se han pedido."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dask.dataframe as dd\n",
    "ddf = dd.from_pandas(dfL[(dfL.Asynch_Iters == False)], npartitions=10)\n",
    "group = ddf.groupby('NP')['T_iter']\n",
    "grouped_aggLSynch = group.agg(['mean'])\n",
    "grouped_aggLSynch = grouped_aggLSynch.rename(columns={'mean':'T_iter'}) \n",
    "grouped_aggLSynch = grouped_aggLSynch.compute()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Las siguientes dos celdas de código son para comprobar los Empirical Comulative distribution functions(ecdf).\n",
    "Si dos ecdf crean una intersección el test de Conover-Iman no es fiable.\n",
    "#TODO No esta terminado. Falta obtener cual ha sido el metodo ganador antes de llamar a \"check_specific_ecdf\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "def test_ecdf(data1, data2):\n",
    "    diff_aux = data1[0] - data2[0]\n",
    "    cmp_f = (lambda a, b: a-b < 0) # Se esperan siempre diferencias positivas, si una es negativa se cruzan los ecdf's\n",
    "    if diff_aux < 0:\n",
    "        cmp_f = (lambda a, b: a-b > 0) # Se esperan siempre diferencias negativas, si una es positivas se cruzan los ecdf's\n",
    "        \n",
    "    for index_value in range(1,len(data1)):\n",
    "        if cmp_f(data1[index_value], data2[index_value]):\n",
    "            return False\n",
    "    return True\n",
    "\n",
    "def plot_ecdf(data1, data2, ecdf1, ecdf2, title):\n",
    "    f=plt.figure(figsize=(22, 14))\n",
    "    ax=f.add_subplot(111)\n",
    "\n",
    "    ax.plot(data1, ecdf1, color=colors_m[0], linestyle=linestyle_m[0], \\\n",
    "        marker=markers_m[0], markersize=18)\n",
    "    ax.plot(data2, ecdf2, color=colors_m[2], linestyle=linestyle_m[2], \\\n",
    "        marker=markers_m[2], markersize=18)\n",
    "\n",
    "    ax.set_xlabel(\"Values\", fontsize=36)\n",
    "    ax.set_ylabel(\"Bins\", fontsize=36)\n",
    "    ax.tick_params(axis='both', which='major', labelsize=36)\n",
    "    ax.tick_params(axis='both', which='minor', labelsize=36)\n",
    "    ax.set_title(title, fontsize=40)\n",
    "        \n",
    "    f.tight_layout()\n",
    "\n",
    "def check_specific_ecdf(np_aux, ns_aux, configuration_index):\n",
    "    df_check = dfM\n",
    "    tipo = 'T_Redistribution'\n",
    "    used_config = configurations_simple\n",
    "    dataLists = get_df_np_ns_data(df_check, tipo, used_config, np_aux, ns_aux)\n",
    "    ecdfLists = []\n",
    "    for index_i in range(len(dataLists)):\n",
    "        dataLists[index_i].sort()\n",
    "        ecdfLists.append( np.arange(1, len(dataLists[index_i])+1)/float(len(dataLists[index_i])) )\n",
    "\n",
    "    index_i = configuration_index\n",
    "    data_i = dataLists[index_i]\n",
    "    ecdf_i = ecdfLists[index_i]\n",
    "    for index_j in range(len(dataLists)):\n",
    "        if index_i != index_j:\n",
    "            data_j = dataLists[index_j]\n",
    "            ecdf_j = ecdfLists[index_j]\n",
    "            res_aux = test_ecdf(data_i, data_j)\n",
    "            if not res_aux:\n",
    "                aux_title = \"NP=\"+str(np_aux)+\"/NC=\"+str(ns_aux)+\" -- Comparing C\"+str(index_i) + \" vs C\"+str(index_j)\n",
    "                plot_ecdf(data_i, data_j, ecdf_i, ecdf_j, aux_title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for np_aux in processes:\n",
    "    for ns_aux in processes:\n",
    "        if np_aux != ns_aux and not (np_aux==2 and ns_aux==20):\n",
    "            check_winner_ecdf(np_aux, ns_aux, 9)\n",
    "\n",
    "        \n",
    "        "
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5\n"
     ]
    }
   ],
   "source": [
    "a = 5\n",
    "b = 3\n",
    "c = False\n",
    "d = a + b * c\n",
    "print(d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Ethernet\n",
    "b1_aux = [82.747868, 83.191989, 95.520019, 87.435987, 90.843995, 150.356100]\n",
    "b2_aux = [75.238174, 74.380054, 74.755995, 42.656109, 21.588040, 17.843997]\n",
    "m1_aux = [74.654167, 74.357901, 74.351350, 43.599915, 21.637509, 15.128712]\n",
    "m2_aux = [74.353249, 74.359214, 74.356160, 43.874266, 21.511082, 14.969010]\n",
    "\n",
    "b3_aux = [105.128014, 110.004008, 126.552019, 116.312400, 95.752019, 151.023994]\n",
    "b4_aux = [83.021885, 77.632630, 75.396010, 43.076039, 24.028075, 19.556047]\n",
    "m3_aux = [118.275992, 83.027866, 81.008479, 46.432212, 24.247949, 17.725083]\n",
    "m4_aux = [119.286457, 84.205993, 80.741585, 47.144632, 24.206617, 17.738496]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Infiniband\n",
    "b1_aux = [64.669525, 35.171971, 38.916010, 47.456630, 56.288048, 119.428020]\n",
    "b2_aux = [36.538361, 15.536046, 13.396083, 9.652013, 5.772058, 5.615009]\n",
    "m1_aux = [61.664380, 18.400559, 19.112526, 22.155880, 11.712381, 30.775627]\n",
    "m2_aux = [33.428639, 13.905561, 14.691367, 7.363081, 6.629037, 12.150872]\n",
    "\n",
    "b3_aux = [91.368664, 60.648074, 53.663981, 49.152031, 64.752057, 118.243807]\n",
    "b4_aux = [84.941260, 34.039990, 26.008021, 12.298989, 7.916004, 5.736054]\n",
    "m3_aux = [105.839726, 26.822071, 23.834452, 12.876862, 9.063136, 7.007535]\n",
    "m4_aux = [75.412319, 25.566336, 22.129483, 12.491161, 7.903744, 6.534291]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[64.669525, 35.171971, 38.91601, 47.45663, 56.288048, 119.42802]\n",
      "[61.66438, 18.400559, 19.112526, 22.15588, 11.712381, 30.775627]\n",
      "[36.538361, 15.536046, 13.396083, 9.652013, 5.772058, 5.615009]\n",
      "[33.428639, 13.905561, 14.691367, 7.363081, 6.629037, 12.150872]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "plot_data_e = [b1_aux, m1_aux, b2_aux, m2_aux] #Expand\n",
    "plot_data_s = [b3_aux, m3_aux, b4_aux, m4_aux] #Shrink\n",
    "\n",
    "labels_aux_e = create_labels_lineplot('e', lambda a, b: a == 160 or b == 160)\n",
    "labels_aux_s = create_labels_lineplot('s', lambda a, b: a == 160 or b == 160)\n",
    "#labels_aux = create_labels_lineplot(used_direction)\n",
    "\n",
    "labelsMethods_aux = ['Baseline - AllS', 'Merge - AllS',\n",
    "                     'Baseline - AllA','Merge - AllA']\n",
    "\n",
    "#labelsMethods_aux = ['Baseline - All', 'Baseline - P2P','Merge - All','Merge - P2P']\n",
    "\n",
    "f, (axe, axs)=plt.subplots(1,2,figsize=(12, 7))\n",
    "x = np.arange(len(labels_aux_e))\n",
    "for index in range(len(plot_data_e)):\n",
    "    array_aux_e = plot_data_e[index]\n",
    "    array_aux_s = plot_data_s[index]\n",
    "    plot_index = index\n",
    "    if index > 0:\n",
    "        plot_index = 2**plot_index\n",
    "    print(array_aux_e)\n",
    "    axe.plot(x, array_aux_e, color=colors_m[plot_index%len(colors_m)], linestyle=linestyle_m[plot_index%len(linestyle_m)], \\\n",
    "        marker=markers_m[plot_index%len(markers_m)], markersize=9, label=labelsMethods_aux[index])\n",
    "    axs.plot(x, array_aux_s, color=colors_m[plot_index%len(colors_m)], linestyle=linestyle_m[plot_index%len(linestyle_m)], \\\n",
    "        marker=markers_m[plot_index%len(markers_m)], markersize=9, label=labelsMethods_aux[index])\n",
    "\n",
    "axe.set_xlabel(\"(NP,NC)\", fontsize=18)\n",
    "axe.set_ylabel(\"Time(s)\", fontsize=18)\n",
    "axe.set_xticks(x)\n",
    "axe.set_xticklabels(labels_aux_e, rotation=90)\n",
    "axe.tick_params(axis='both', which='major', labelsize=18)\n",
    "axe.tick_params(axis='both', which='minor', labelsize=18)\n",
    "\n",
    "axs.set_xlabel(\"(NP,NC)\", fontsize=18)\n",
    "axs.set_ylabel(\"Time(s)\", fontsize=18)\n",
    "axs.set_xticks(x)\n",
    "axs.set_xticklabels(labels_aux_s, rotation=90)\n",
    "axs.tick_params(axis='both', which='major', labelsize=18)\n",
    "axs.tick_params(axis='both', which='minor', labelsize=18)\n",
    "\n",
    "plt.legend(loc='best', fontsize=15,ncol=2,framealpha=0.8)\n",
    "        \n",
    "f.tight_layout()\n",
    "f.savefig(\"Images/LinePlot_100Gb.png\", format=\"png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Total_Resizes</th>\n",
       "      <th>Total_Groups</th>\n",
       "      <th>Total_Stages</th>\n",
       "      <th>Granularity</th>\n",
       "      <th>SDR</th>\n",
       "      <th>ADR</th>\n",
       "      <th>DR</th>\n",
       "      <th>Redistribution_Method</th>\n",
       "      <th>Redistribution_Strategy</th>\n",
       "      <th>Spawn_Method</th>\n",
       "      <th>...</th>\n",
       "      <th>Stage_Bytes</th>\n",
       "      <th>Iters</th>\n",
       "      <th>Asynch_Iters</th>\n",
       "      <th>T_iter</th>\n",
       "      <th>T_stages</th>\n",
       "      <th>T_spawn</th>\n",
       "      <th>T_spawn_real</th>\n",
       "      <th>T_SR</th>\n",
       "      <th>T_AR</th>\n",
       "      <th>T_total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>0</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>(0, 1)</td>\n",
       "      <td>(1, 1)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>...</td>\n",
       "      <td>(0, 8, 8, 33176880)</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>((0.18652, 0.124731, 0.122231, 0.127332, 0.123...</td>\n",
       "      <td>(((0.010703, 0.020441, 0.003143, 0.142669), (0...</td>\n",
       "      <td>(2.74715,)</td>\n",
       "      <td>(0,)</td>\n",
       "      <td>(0.582089,)</td>\n",
       "      <td>(0,)</td>\n",
       "      <td>128.164538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>0</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>(0, 1)</td>\n",
       "      <td>(1, 1)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>...</td>\n",
       "      <td>(0, 8, 8, 33176880)</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>((0.197356, 0.134512, 0.13265, 0.129822, 0.162...</td>\n",
       "      <td>(((0.010705, 0.021922, 0.000115, 0.163755), (0...</td>\n",
       "      <td>(2.996832,)</td>\n",
       "      <td>(0,)</td>\n",
       "      <td>(0.509344,)</td>\n",
       "      <td>(0,)</td>\n",
       "      <td>145.846459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>0</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>(0, 1)</td>\n",
       "      <td>(1, 1)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>...</td>\n",
       "      <td>(0, 8, 8, 33176880)</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>((0.256422, 0.250623, 0.138498, 0.124174, 0.13...</td>\n",
       "      <td>(((0.010715, 0.015873, 0.00522, 0.224576), (0....</td>\n",
       "      <td>(3.072206,)</td>\n",
       "      <td>(0,)</td>\n",
       "      <td>(0.786317,)</td>\n",
       "      <td>(0,)</td>\n",
       "      <td>137.029088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>0</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>(0, 1)</td>\n",
       "      <td>(1, 1)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>...</td>\n",
       "      <td>(0, 8, 8, 33176880)</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>((0.24732, 0.136378, 0.131872, 0.126541, 0.146...</td>\n",
       "      <td>(((0.010702, 0.021948, 0.005109, 0.193134), (0...</td>\n",
       "      <td>(2.90208,)</td>\n",
       "      <td>(0,)</td>\n",
       "      <td>(0.561077,)</td>\n",
       "      <td>(0,)</td>\n",
       "      <td>138.441495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>0</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>(0, 1)</td>\n",
       "      <td>(1, 1)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>...</td>\n",
       "      <td>(0, 8, 8, 33176880)</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>((0.263267, 0.154895, 0.154232, 0.136061, 0.13...</td>\n",
       "      <td>(((0.010699, 0.021253, 0.031983, 0.180843), (0...</td>\n",
       "      <td>(3.057507,)</td>\n",
       "      <td>(0,)</td>\n",
       "      <td>(0.772008,)</td>\n",
       "      <td>(0,)</td>\n",
       "      <td>134.787217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2515</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>134228039</td>\n",
       "      <td>3813655464</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>(0, 1)</td>\n",
       "      <td>(1, 2)</td>\n",
       "      <td>(0, 1)</td>\n",
       "      <td>...</td>\n",
       "      <td>(0, 8, 8, 33176880)</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(4, 0)</td>\n",
       "      <td>((0.636517, 0.619039, 0.618972, 0.627083, 0.62...</td>\n",
       "      <td>(((0.608709, 8.1e-05, 6.7e-05, 0.02766), (0.60...</td>\n",
       "      <td>(1.890009,)</td>\n",
       "      <td>(1.223675,)</td>\n",
       "      <td>(0.04302,)</td>\n",
       "      <td>(2.052849,)</td>\n",
       "      <td>390.234822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2516</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>134228039</td>\n",
       "      <td>3813655464</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>(0, 1)</td>\n",
       "      <td>(1, 2)</td>\n",
       "      <td>(0, 1)</td>\n",
       "      <td>...</td>\n",
       "      <td>(0, 8, 8, 33176880)</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(3, 0)</td>\n",
       "      <td>((0.635635, 0.618535, 0.618144, 0.626595, 0.62...</td>\n",
       "      <td>(((0.607468, 8.8e-05, 7.6e-05, 0.028002), (0.6...</td>\n",
       "      <td>(1.815736,)</td>\n",
       "      <td>(1.162094,)</td>\n",
       "      <td>(0.043152,)</td>\n",
       "      <td>(1.395158,)</td>\n",
       "      <td>389.026864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2517</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>134228039</td>\n",
       "      <td>3813655464</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>(0, 1)</td>\n",
       "      <td>(1, 2)</td>\n",
       "      <td>(0, 1)</td>\n",
       "      <td>...</td>\n",
       "      <td>(0, 8, 8, 33176880)</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(4, 0)</td>\n",
       "      <td>((0.636777, 0.619522, 0.619269, 0.627039, 0.62...</td>\n",
       "      <td>(((0.608581, 8.7e-05, 8.6e-05, 0.028023), (0.6...</td>\n",
       "      <td>(1.809099,)</td>\n",
       "      <td>(1.142486,)</td>\n",
       "      <td>(0.042895,)</td>\n",
       "      <td>(2.210734,)</td>\n",
       "      <td>403.614798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2518</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>134228039</td>\n",
       "      <td>3813655464</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>(0, 1)</td>\n",
       "      <td>(1, 2)</td>\n",
       "      <td>(0, 1)</td>\n",
       "      <td>...</td>\n",
       "      <td>(0, 8, 8, 33176880)</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(3, 0)</td>\n",
       "      <td>((0.635619, 0.618949, 0.618275, 0.625932, 0.62...</td>\n",
       "      <td>(((0.6076, 0.000165, 4e-06, 0.02785), (0.60803...</td>\n",
       "      <td>(1.937833,)</td>\n",
       "      <td>(1.334051,)</td>\n",
       "      <td>(0.043258,)</td>\n",
       "      <td>(1.315052,)</td>\n",
       "      <td>380.287968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2519</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>134228039</td>\n",
       "      <td>3813655464</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>(0, 1)</td>\n",
       "      <td>(1, 2)</td>\n",
       "      <td>(0, 1)</td>\n",
       "      <td>...</td>\n",
       "      <td>(0, 8, 8, 33176880)</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(4, 0)</td>\n",
       "      <td>((0.636218, 0.618677, 0.618391, 0.625867, 0.62...</td>\n",
       "      <td>(((0.607191, 0.000613, 6e-06, 0.028407), (0.60...</td>\n",
       "      <td>(1.856861,)</td>\n",
       "      <td>(1.225623,)</td>\n",
       "      <td>(0.043226,)</td>\n",
       "      <td>(2.033379,)</td>\n",
       "      <td>385.788391</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2520 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Total_Resizes  Total_Groups  Total_Stages  Granularity         SDR  \\\n",
       "0                 1             2             4       100000  3947883504   \n",
       "1                 1             2             4       100000  3947883504   \n",
       "2                 1             2             4       100000  3947883504   \n",
       "3                 1             2             4       100000  3947883504   \n",
       "4                 1             2             4       100000  3947883504   \n",
       "...             ...           ...           ...          ...         ...   \n",
       "2515              1             2             4       100000   134228039   \n",
       "2516              1             2             4       100000   134228039   \n",
       "2517              1             2             4       100000   134228039   \n",
       "2518              1             2             4       100000   134228039   \n",
       "2519              1             2             4       100000   134228039   \n",
       "\n",
       "             ADR          DR Redistribution_Method Redistribution_Strategy  \\\n",
       "0              0  3947883504                (0, 1)                  (1, 1)   \n",
       "1              0  3947883504                (0, 1)                  (1, 1)   \n",
       "2              0  3947883504                (0, 1)                  (1, 1)   \n",
       "3              0  3947883504                (0, 1)                  (1, 1)   \n",
       "4              0  3947883504                (0, 1)                  (1, 1)   \n",
       "...          ...         ...                   ...                     ...   \n",
       "2515  3813655464  3947883503                (0, 1)                  (1, 2)   \n",
       "2516  3813655464  3947883503                (0, 1)                  (1, 2)   \n",
       "2517  3813655464  3947883503                (0, 1)                  (1, 2)   \n",
       "2518  3813655464  3947883503                (0, 1)                  (1, 2)   \n",
       "2519  3813655464  3947883503                (0, 1)                  (1, 2)   \n",
       "\n",
       "     Spawn_Method  ...          Stage_Bytes       Iters Asynch_Iters  \\\n",
       "0          (0, 0)  ...  (0, 8, 8, 33176880)  (500, 500)       (0, 0)   \n",
       "1          (0, 0)  ...  (0, 8, 8, 33176880)  (500, 500)       (0, 0)   \n",
       "2          (0, 0)  ...  (0, 8, 8, 33176880)  (500, 500)       (0, 0)   \n",
       "3          (0, 0)  ...  (0, 8, 8, 33176880)  (500, 500)       (0, 0)   \n",
       "4          (0, 0)  ...  (0, 8, 8, 33176880)  (500, 500)       (0, 0)   \n",
       "...           ...  ...                  ...         ...          ...   \n",
       "2515       (0, 1)  ...  (0, 8, 8, 33176880)  (500, 500)       (4, 0)   \n",
       "2516       (0, 1)  ...  (0, 8, 8, 33176880)  (500, 500)       (3, 0)   \n",
       "2517       (0, 1)  ...  (0, 8, 8, 33176880)  (500, 500)       (4, 0)   \n",
       "2518       (0, 1)  ...  (0, 8, 8, 33176880)  (500, 500)       (3, 0)   \n",
       "2519       (0, 1)  ...  (0, 8, 8, 33176880)  (500, 500)       (4, 0)   \n",
       "\n",
       "                                                 T_iter  \\\n",
       "0     ((0.18652, 0.124731, 0.122231, 0.127332, 0.123...   \n",
       "1     ((0.197356, 0.134512, 0.13265, 0.129822, 0.162...   \n",
       "2     ((0.256422, 0.250623, 0.138498, 0.124174, 0.13...   \n",
       "3     ((0.24732, 0.136378, 0.131872, 0.126541, 0.146...   \n",
       "4     ((0.263267, 0.154895, 0.154232, 0.136061, 0.13...   \n",
       "...                                                 ...   \n",
       "2515  ((0.636517, 0.619039, 0.618972, 0.627083, 0.62...   \n",
       "2516  ((0.635635, 0.618535, 0.618144, 0.626595, 0.62...   \n",
       "2517  ((0.636777, 0.619522, 0.619269, 0.627039, 0.62...   \n",
       "2518  ((0.635619, 0.618949, 0.618275, 0.625932, 0.62...   \n",
       "2519  ((0.636218, 0.618677, 0.618391, 0.625867, 0.62...   \n",
       "\n",
       "                                               T_stages      T_spawn  \\\n",
       "0     (((0.010703, 0.020441, 0.003143, 0.142669), (0...   (2.74715,)   \n",
       "1     (((0.010705, 0.021922, 0.000115, 0.163755), (0...  (2.996832,)   \n",
       "2     (((0.010715, 0.015873, 0.00522, 0.224576), (0....  (3.072206,)   \n",
       "3     (((0.010702, 0.021948, 0.005109, 0.193134), (0...   (2.90208,)   \n",
       "4     (((0.010699, 0.021253, 0.031983, 0.180843), (0...  (3.057507,)   \n",
       "...                                                 ...          ...   \n",
       "2515  (((0.608709, 8.1e-05, 6.7e-05, 0.02766), (0.60...  (1.890009,)   \n",
       "2516  (((0.607468, 8.8e-05, 7.6e-05, 0.028002), (0.6...  (1.815736,)   \n",
       "2517  (((0.608581, 8.7e-05, 8.6e-05, 0.028023), (0.6...  (1.809099,)   \n",
       "2518  (((0.6076, 0.000165, 4e-06, 0.02785), (0.60803...  (1.937833,)   \n",
       "2519  (((0.607191, 0.000613, 6e-06, 0.028407), (0.60...  (1.856861,)   \n",
       "\n",
       "     T_spawn_real         T_SR         T_AR     T_total  \n",
       "0            (0,)  (0.582089,)         (0,)  128.164538  \n",
       "1            (0,)  (0.509344,)         (0,)  145.846459  \n",
       "2            (0,)  (0.786317,)         (0,)  137.029088  \n",
       "3            (0,)  (0.561077,)         (0,)  138.441495  \n",
       "4            (0,)  (0.772008,)         (0,)  134.787217  \n",
       "...           ...          ...          ...         ...  \n",
       "2515  (1.223675,)   (0.04302,)  (2.052849,)  390.234822  \n",
       "2516  (1.162094,)  (0.043152,)  (1.395158,)  389.026864  \n",
       "2517  (1.142486,)  (0.042895,)  (2.210734,)  403.614798  \n",
       "2518  (1.334051,)  (0.043258,)  (1.315052,)  380.287968  \n",
       "2519  (1.225623,)  (0.043226,)  (2.033379,)  385.788391  \n",
       "\n",
       "[2520 rows x 26 columns]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.read_pickle( 'predataG.pkl' )\n",
    "df1.reset_index(drop=True, inplace = True)\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Total_Resizes</th>\n",
       "      <th>Total_Groups</th>\n",
       "      <th>Total_Stages</th>\n",
       "      <th>Granularity</th>\n",
       "      <th>SDR</th>\n",
       "      <th>ADR</th>\n",
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       "      <th>Redistribution_Method</th>\n",
       "      <th>Redistribution_Strategy</th>\n",
       "      <th>Spawn_Method</th>\n",
       "      <th>...</th>\n",
       "      <th>Iters</th>\n",
       "      <th>Asynch_Iters</th>\n",
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       "      <th>T_stages</th>\n",
       "      <th>T_spawn</th>\n",
       "      <th>T_spawn_real</th>\n",
       "      <th>T_SR</th>\n",
       "      <th>T_AR</th>\n",
       "      <th>T_Malleability</th>\n",
       "      <th>T_total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
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       "      <td>...</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(0, 0)</td>\n",
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       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>0</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>(1, 1)</td>\n",
       "      <td>(0, 0)</td>\n",
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       "      <td>((0.161298, 0.14421, 0.144174, 0.144144, 0.144...</td>\n",
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       "      <td>(1.035181,)</td>\n",
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       "      <td>[3.035842]</td>\n",
       "      <td>147.887674</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>0</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>(1, 1)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>...</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>((0.160962, 0.144373, 0.144386, 0.144318, 0.14...</td>\n",
       "      <td>(((0.124523, 0.000222, 4e-05, 0.036171), (0.12...</td>\n",
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       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
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       "      <td>100000</td>\n",
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       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>0</td>\n",
       "      <td>3947883504</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>(1, 1)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>...</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>((0.160918, 0.144082, 0.144104, 0.144344, 0.14...</td>\n",
       "      <td>(((0.124538, 0.000211, 4e-05, 0.036128), (0.12...</td>\n",
       "      <td>(1.851496,)</td>\n",
       "      <td>(0,)</td>\n",
       "      <td>(1.025062,)</td>\n",
       "      <td>(0,)</td>\n",
       "      <td>[2.878599]</td>\n",
       "      <td>144.362447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>134228039</td>\n",
       "      <td>3813655464</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>(1, 2)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>...</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(2, 0)</td>\n",
       "      <td>((0.230742, 0.134476, 0.122002, 0.137031, 0.13...</td>\n",
       "      <td>(((0.035669, 0.019326, 5.2e-05, 0.175653), (0....</td>\n",
       "      <td>(2.484273,)</td>\n",
       "      <td>(1.608697,)</td>\n",
       "      <td>(0.084463,)</td>\n",
       "      <td>(4.248563,)</td>\n",
       "      <td>[6.922865]</td>\n",
       "      <td>383.875881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>416</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>134228039</td>\n",
       "      <td>3813655464</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>(1, 2)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>...</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(2, 0)</td>\n",
       "      <td>((0.145871, 0.114355, 0.118651, 0.119111, 0.12...</td>\n",
       "      <td>(((0.035674, 0.000269, 8.4e-05, 0.109808), (0....</td>\n",
       "      <td>(1.905202,)</td>\n",
       "      <td>(1.065241,)</td>\n",
       "      <td>(0.138339,)</td>\n",
       "      <td>(2.575336,)</td>\n",
       "      <td>[5.181274]</td>\n",
       "      <td>375.685916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>417</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>134228039</td>\n",
       "      <td>3813655464</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>(1, 2)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>...</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(2, 0)</td>\n",
       "      <td>((0.172331, 0.141966, 0.135298, 0.129448, 0.13...</td>\n",
       "      <td>(((0.036336, 0.004186, 6.3e-05, 0.129964), (0....</td>\n",
       "      <td>(2.037602,)</td>\n",
       "      <td>(1.121461,)</td>\n",
       "      <td>(0.104254,)</td>\n",
       "      <td>(4.067741,)</td>\n",
       "      <td>[6.441992]</td>\n",
       "      <td>382.392757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>134228039</td>\n",
       "      <td>3813655464</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>(1, 2)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>...</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(2, 0)</td>\n",
       "      <td>((0.215291, 0.136414, 0.131944, 0.131725, 0.13...</td>\n",
       "      <td>(((0.035676, 0.000244, 9e-05, 0.176667), (0.03...</td>\n",
       "      <td>(1.499816,)</td>\n",
       "      <td>(1.016316,)</td>\n",
       "      <td>(0.071393,)</td>\n",
       "      <td>(4.59475,)</td>\n",
       "      <td>[6.535292]</td>\n",
       "      <td>384.905547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>419</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "      <td>134228039</td>\n",
       "      <td>3813655464</td>\n",
       "      <td>3947883503</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>(1, 2)</td>\n",
       "      <td>(0, 0)</td>\n",
       "      <td>...</td>\n",
       "      <td>(500, 500)</td>\n",
       "      <td>(2, 0)</td>\n",
       "      <td>((0.196158, 0.135622, 0.137968, 0.127833, 0.13...</td>\n",
       "      <td>(((0.035667, 0.000221, 8.5e-05, 0.16016), (0.0...</td>\n",
       "      <td>(2.343399,)</td>\n",
       "      <td>(1.268019,)</td>\n",
       "      <td>(0.32804,)</td>\n",
       "      <td>(6.3607,)</td>\n",
       "      <td>[9.051677]</td>\n",
       "      <td>386.394841</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>420 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Total_Resizes  Total_Groups  Total_Stages  Granularity         SDR  \\\n",
       "0                1             2             4       100000  3947883504   \n",
       "1                1             2             4       100000  3947883504   \n",
       "2                1             2             4       100000  3947883504   \n",
       "3                1             2             4       100000  3947883504   \n",
       "4                1             2             4       100000  3947883504   \n",
       "..             ...           ...           ...          ...         ...   \n",
       "415              1             2             4       100000   134228039   \n",
       "416              1             2             4       100000   134228039   \n",
       "417              1             2             4       100000   134228039   \n",
       "418              1             2             4       100000   134228039   \n",
       "419              1             2             4       100000   134228039   \n",
       "\n",
       "            ADR          DR Redistribution_Method Redistribution_Strategy  \\\n",
       "0             0  3947883504                (0, 0)                  (1, 1)   \n",
       "1             0  3947883504                (0, 0)                  (1, 1)   \n",
       "2             0  3947883504                (0, 0)                  (1, 1)   \n",
       "3             0  3947883504                (0, 0)                  (1, 1)   \n",
       "4             0  3947883504                (0, 0)                  (1, 1)   \n",
       "..          ...         ...                   ...                     ...   \n",
       "415  3813655464  3947883503                (0, 0)                  (1, 2)   \n",
       "416  3813655464  3947883503                (0, 0)                  (1, 2)   \n",
       "417  3813655464  3947883503                (0, 0)                  (1, 2)   \n",
       "418  3813655464  3947883503                (0, 0)                  (1, 2)   \n",
       "419  3813655464  3947883503                (0, 0)                  (1, 2)   \n",
       "\n",
       "    Spawn_Method  ...       Iters Asynch_Iters  \\\n",
       "0         (0, 0)  ...  (500, 500)       (0, 0)   \n",
       "1         (0, 0)  ...  (500, 500)       (0, 0)   \n",
       "2         (0, 0)  ...  (500, 500)       (0, 0)   \n",
       "3         (0, 0)  ...  (500, 500)       (0, 0)   \n",
       "4         (0, 0)  ...  (500, 500)       (0, 0)   \n",
       "..           ...  ...         ...          ...   \n",
       "415       (0, 0)  ...  (500, 500)       (2, 0)   \n",
       "416       (0, 0)  ...  (500, 500)       (2, 0)   \n",
       "417       (0, 0)  ...  (500, 500)       (2, 0)   \n",
       "418       (0, 0)  ...  (500, 500)       (2, 0)   \n",
       "419       (0, 0)  ...  (500, 500)       (2, 0)   \n",
       "\n",
       "                                                T_iter  \\\n",
       "0    ((0.161107, 0.14413, 0.144082, 0.144121, 0.144...   \n",
       "1    ((0.161298, 0.14421, 0.144174, 0.144144, 0.144...   \n",
       "2    ((0.160962, 0.144373, 0.144386, 0.144318, 0.14...   \n",
       "3    ((0.166277, 0.146431, 0.144191, 0.144273, 0.14...   \n",
       "4    ((0.160918, 0.144082, 0.144104, 0.144344, 0.14...   \n",
       "..                                                 ...   \n",
       "415  ((0.230742, 0.134476, 0.122002, 0.137031, 0.13...   \n",
       "416  ((0.145871, 0.114355, 0.118651, 0.119111, 0.12...   \n",
       "417  ((0.172331, 0.141966, 0.135298, 0.129448, 0.13...   \n",
       "418  ((0.215291, 0.136414, 0.131944, 0.131725, 0.13...   \n",
       "419  ((0.196158, 0.135622, 0.137968, 0.127833, 0.13...   \n",
       "\n",
       "                                              T_stages      T_spawn  \\\n",
       "0    (((0.124547, 0.000239, 7.2e-05, 0.036249), (0....  (2.025396,)   \n",
       "1    (((0.124634, 0.000371, 0.000111, 0.036171), (0...  (2.000317,)   \n",
       "2    (((0.124523, 0.000222, 4e-05, 0.036171), (0.12...  (2.217718,)   \n",
       "3    (((0.126563, 0.00257, 1.2e-05, 0.03711), (0.12...  (1.892621,)   \n",
       "4    (((0.124538, 0.000211, 4e-05, 0.036128), (0.12...  (1.851496,)   \n",
       "..                                                 ...          ...   \n",
       "415  (((0.035669, 0.019326, 5.2e-05, 0.175653), (0....  (2.484273,)   \n",
       "416  (((0.035674, 0.000269, 8.4e-05, 0.109808), (0....  (1.905202,)   \n",
       "417  (((0.036336, 0.004186, 6.3e-05, 0.129964), (0....  (2.037602,)   \n",
       "418  (((0.035676, 0.000244, 9e-05, 0.176667), (0.03...  (1.499816,)   \n",
       "419  (((0.035667, 0.000221, 8.5e-05, 0.16016), (0.0...  (2.343399,)   \n",
       "\n",
       "    T_spawn_real         T_SR         T_AR T_Malleability     T_total  \n",
       "0           (0,)  (0.916423,)         (0,)     [2.942172]  136.677510  \n",
       "1           (0,)  (1.035181,)         (0,)     [3.035842]  147.887674  \n",
       "2           (0,)  (0.960566,)         (0,)     [3.178658]  143.926548  \n",
       "3           (0,)   (1.13518,)         (0,)     [3.028146]  141.104274  \n",
       "4           (0,)  (1.025062,)         (0,)     [2.878599]  144.362447  \n",
       "..           ...          ...          ...            ...         ...  \n",
       "415  (1.608697,)  (0.084463,)  (4.248563,)     [6.922865]  383.875881  \n",
       "416  (1.065241,)  (0.138339,)  (2.575336,)     [5.181274]  375.685916  \n",
       "417  (1.121461,)  (0.104254,)  (4.067741,)     [6.441992]  382.392757  \n",
       "418  (1.016316,)  (0.071393,)   (4.59475,)     [6.535292]  384.905547  \n",
       "419  (1.268019,)   (0.32804,)    (6.3607,)     [9.051677]  386.394841  \n",
       "\n",
       "[420 rows x 27 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.read_pickle( 'dataIntraB.pkl' )\n",
    "df2.reset_index(drop=True, inplace = True)\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[30 31 32 33 34]\n",
      "[10 11 12 13 14]\n",
      "[625 626 627 628 629]\n",
      "[160 161 162 163 164]\n",
      "[590 591 592 593 594]\n",
      "[140 141 142 143 144]\n",
      "[200 201 202 203 204]\n",
      "[50 51 52 53 54]\n",
      "[505 506 507 508 509]\n",
      "[110 111 112 113 114]\n",
      "[680 681 682 683 684]\n",
      "[175 176 177 178 179]\n",
      "[640 641 642 643 644]\n",
      "[165 166 167 168 169]\n",
      "[350 351 352 353 354]\n",
      "[85 86 87 88 89]\n",
      "[40 41 42 43 44]\n",
      "[15 16 17 18 19]\n",
      "[5 6 7 8 9]\n",
      "[0 1 2 3 4]\n",
      "[565 566 567 568 569]\n",
      "[125 126 127 128 129]\n",
      "[785 786 787 788 789]\n",
      "[200 201 202 203 204]\n",
      "[20 21 22 23 24]\n",
      "[5 6 7 8 9]\n",
      "[770 771 772 773 774]\n",
      "[190 191 192 193 194]\n",
      "[105 106 107 108 109]\n",
      "[30 31 32 33 34]\n",
      "[335 336 337 338 339]\n",
      "[75 76 77 78 79]\n",
      "[220 221 222 223 224]\n",
      "[60 61 62 63 64]\n",
      "[60 61 62 63 64]\n",
      "[20 21 22 23 24]\n",
      "[810 811 812 813 814]\n",
      "[205 206 207 208 209]\n",
      "[300 301 302 303 304]\n",
      "[70 71 72 73 74]\n",
      "[75 76 77 78 79]\n",
      "[25 26 27 28 29]\n",
      "[340 341 342 343 344]\n",
      "[80 81 82 83 84]\n",
      "[430 431 432 433 434]\n",
      "[100 101 102 103 104]\n",
      "[495 496 497 498 499]\n",
      "[105 106 107 108 109]\n",
      "[585 586 587 588 589]\n",
      "[135 136 137 138 139]\n",
      "[700 701 702 703 704]\n",
      "[180 181 182 183 184]\n",
      "[185 186 187 188 189]\n",
      "[45 46 47 48 49]\n",
      "[205 206 207 208 209]\n",
      "[55 56 57 58 59]\n",
      "[780 781 782 783 784]\n",
      "[195 196 197 198 199]\n",
      "[285 286 287 288 289]\n",
      "[65 66 67 68 69]\n",
      "[510 511 512 513 514]\n",
      "[115 116 117 118 119]\n",
      "[120 121 122 123 124]\n",
      "[40 41 42 43 44]\n",
      "[355 356 357 358 359]\n",
      "[90 91 92 93 94]\n",
      "[390 391 392 393 394]\n",
      "[95 96 97 98 99]\n",
      "[765 766 767 768 769]\n",
      "[185 186 187 188 189]\n",
      "[675 676 677 678 679]\n",
      "[170 171 172 173 174]\n",
      "[580 581 582 583 584]\n",
      "[130 131 132 133 134]\n",
      "[595 596 597 598 599]\n",
      "[145 146 147 148 149]\n",
      "[560 561 562 563 564]\n",
      "[120 121 122 123 124]\n",
      "[620 621 622 623 624]\n",
      "[155 156 157 158 159]\n",
      "[605 606 607 608 609]\n",
      "[150 151 152 153 154]\n",
      "[115 116 117 118 119]\n",
      "[35 36 37 38 39]\n"
     ]
    }
   ],
   "source": [
    "def a_func(df, np_aux, ns_aux):\n",
    "    where_true_spawn = df.Spawn_Method==(0,0)\n",
    "    where_true_spawn_st = df.Spawn_Strategy==(1,1)\n",
    "    where_true_red_m = df.Redistribution_Method==(0,0)\n",
    "    where_true_red_st = df.Redistribution_Strategy==(1,1)\n",
    "    where_true_adr = df.ADR==0\n",
    "    where_true_np = df.Groups==(np_aux,ns_aux)\n",
    "    where_true_list = where_true_spawn & where_true_spawn_st & where_true_red_m & where_true_red_st & where_true_adr & where_true_np\n",
    "    return np.where(where_true_list)[0]\n",
    "    \n",
    "\n",
    "for np_aux in processes:\n",
    "    for ns_aux in processes:\n",
    "        if(np_aux == ns_aux):\n",
    "            continue\n",
    "        where_true_df1 = a_func(df1, np_aux, ns_aux)\n",
    "        where_true_df2 = a_func(df2, np_aux, ns_aux)\n",
    "        #print(where_true_df1)\n",
    "        #print(where_true_df2)\n",
    "        for i in range(len(where_true_df1)):\n",
    "            index_df1 = where_true_df1[i]\n",
    "            index_df2 = where_true_df2[i]\n",
    "            #print(df1.loc[index_df1])\n",
    "            #print(df2.loc[index_df2])\n",
    "            df1.loc[index_df1] = df2.loc[index_df2]\n",
    "            #print(df1.loc[index_df1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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