Development_OptimizationCoupledTarget.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from lowEBMs.Packages.Configuration import importer, add_sellersparameters, parameterinterpolatorstepwise, reset\n",
    "#from lowEBMs.Packages.Configuration import import_parallelparameter, allocate_parallelparameter, write_parallelparameter\n",
    "from lowEBMs.Packages.Variables import variable_importer, Vars, reset, trackerreset, datareset\n",
    "from lowEBMs.Packages.RK4 import rk4alg\n",
    "from lowEBMs.Packages.ModelEquation import model_equation\n",
    "#from lowEBMs.Packages.Variables import \n",
    "#from lowEBMs.Packages.Functions import plotmeanstd\n",
    "from lowEBMs.Packages.Optimization import coremodule\n",
    "import lowEBMs.Packages.Constants as const\n",
    "from lowEBMs import update_plotstyle, moving_average\n",
    "import builtins\n",
    "import matplotlib\n",
    "update_plotstyle()\n",
    "matplotlib.rcParams['lines.linewidth']=1.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "time_HADCM3_str=np.genfromtxt('Data/gmt_hadcm3.csv',usecols=[0],delimiter=',',skip_header=1,dtype='str',unpack=True,encoding='ISO-8859-1')\n",
    "time_HADCM3=np.zeros(len(time_HADCM3_str))\n",
    "for i in range(len(time_HADCM3_str)):\n",
    "    if time_HADCM3_str[i][-4]=='.':\n",
    "        year=float(time_HADCM3_str[i][-3:])\n",
    "    if time_HADCM3_str[i][-5]=='.':\n",
    "        year=float(time_HADCM3_str[i][-4:])\n",
    "    if time_HADCM3_str[i][4]=='.':\n",
    "        month=(float(time_HADCM3_str[i][3:5])-1)/12\n",
    "    if time_HADCM3_str[i][5]=='.':\n",
    "        month=(float(time_HADCM3_str[i][3:5])-1)/12\n",
    "    day=float(time_HADCM3_str[i][:2])/365\n",
    "    time_HADCM3[i]=year+month+day\n",
    "GMT_HADCM3=np.genfromtxt('Data/gmt_hadcm3.csv',usecols=[17],delimiter=',',skip_header=1,unpack=True,encoding='ISO-8859-1')\n",
    "order=np.argsort(time_HADCM3)\n",
    "GMT_HADCM3_smoothed=moving_average(GMT_HADCM3[order],12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "Year_volc, CWL_GMT,  EVA_GMT, CWLcorr_GMT=np.genfromtxt('Data/Volc_800_2000.txt',skip_header=1,unpack=True)\n",
    "#Year_NorESM, SO4_FORC, SAT_GISS, SAT_VOLC, SAT_ZERO, SAT_AFIT, SAT_TREN= \\\n",
    "#np.genfromtxt('Data/NorESM_Pinatubo_GMST_response.txt',skip_header=1,unpack=True)\n",
    "Year_volc_1800_1850=Year_volc[int(1000*365/4):int(1040*365/4)]\n",
    "Year_volc_1808_1858=Year_volc[int(1008*365/4):int(1048*365/4)]\n",
    "EVA_GMT_1800_1850=EVA_GMT[int(1000*365/4):int(1040*365/4)]\n",
    "EVA_GMT_1808_1858=EVA_GMT[int(1008*365/4):int(1048*365/4)]\n",
    "Lat_10,ZMT_10=np.loadtxt('Data/ERA_ZMT_Mean_10deginterpolated.txt')\n",
    "Year_NorESM, SO4_FORC, SAT_GISS, SAT_VOLC, SAT_ZERO, SAT_AFIT, SAT_TREN= \\\n",
    "np.genfromtxt('Data/NorESM_Pinatubo_GMST_response.txt',skip_header=1,unpack=True)\n",
    "NORESM_1990_2005=SAT_VOLC-SAT_TREN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def coremodule(config,P0,P_pert_ratio,Pmin,Pmax,labels,ZMT,GMT,grid,maxlength,targetmode,target,targetfunction,ratio_ZMT_GMT,elevation,precision,num_paras,gamma0,control,controlconfig):\n",
    "    from tqdm import tqdm, tnrange\n",
    "    \n",
    "    F=np.reshape(np.zeros(maxlength*(2*num_paras+1)),(maxlength,2*num_paras+1))\n",
    "    dF=np.reshape(np.zeros(maxlength*(num_paras)),(maxlength,num_paras))\n",
    "    P=np.reshape(np.zeros(maxlength*(num_paras)),(maxlength,num_paras))\n",
    "    Ptrans=np.reshape(np.zeros(maxlength*(num_paras)),(maxlength,num_paras))\n",
    "    gamma=np.zeros(maxlength)\n",
    "    \n",
    "    if targetmode=='Single':\n",
    "        dataout=np.reshape(np.zeros(maxlength*(2*num_paras+1)),(maxlength,(2*num_paras+1)))\n",
    "    elif targetmode=='ZMT':\n",
    "        dataout=np.reshape(np.zeros(maxlength*len(grid)*(2*num_paras+1)),(maxlength,(2*num_paras+1),len(grid)))\n",
    "    elif targetmode=='GMT':\n",
    "        dataout=np.reshape(np.zeros(maxlength*int(number_of_integration/data_readout)*(2*num_paras+1)),(maxlength,(2*num_paras+1),int(number_of_integration/data_readout)))\n",
    "    elif targetmode=='Coupled':\n",
    "        dataout_ZMT=np.reshape(np.zeros(maxlength*len(grid)*(2*num_paras+1)),(maxlength,(2*num_paras+1),len(grid)))\n",
    "        dataout_GMT=np.reshape(np.zeros(maxlength*int(number_of_integration/data_readout)*(2*num_paras+1)),(maxlength,(2*num_paras+1),int(number_of_integration/data_readout)))     \n",
    "    for i in tnrange(maxlength):\n",
    "        print('Iteration no.'+str(i))\n",
    "        if i==0:\n",
    "            P[i]=P0\n",
    "            P_pert=(Pmax-Pmin)*P_pert_ratio\n",
    "            Ptrans[i]=(P0-Pmin)/(Pmax-Pmin)\n",
    "            Ptrans_pert=Ptrans[i]*P_pert_ratio\n",
    "\n",
    "        if targetmode=='Coupled':\n",
    "            data_ZMT,data_GMT=run_model(config,P[i],P_pert,labels,ZMT,GMT,targetmode,control,controlconfig,grid,elevation)\n",
    "            dataout_ZMT[i]=data_ZMT\n",
    "            dataout_GMT[i]=data_GMT\n",
    "        else:\n",
    "            data=run_model(config,P[i],P_pert,labels,ZMT,GMT,targetmode,control,controlconfig,grid,elevation)\n",
    "            dataout[i]=data\n",
    "            \n",
    "        if targetmode=='Coupled':\n",
    "            target_ZMT=target['ZMT']\n",
    "            target_GMT=target['GMT']\n",
    "            F_ZMT=target_comparison(data_ZMT,'ZMT',target_ZMT,targetfunction,num_paras,grid)\n",
    "            F_GMT=target_comparison(data_GMT,'GMT',target_GMT,targetfunction,num_paras,grid)\n",
    "            F[i]=ratio_ZMT_GMT*F_ZMT+(1-ratio_ZMT_GMT)*F_GMT\n",
    "        else:\n",
    "            F[i]=target_comparison(data,targetmode,target,targetfunction,num_paras,grid)\n",
    "\n",
    "        dF[i]=local_gradient(F[i],Ptrans_pert)\n",
    "        #dF[i]=local_gradient(F[i],P_pert)\n",
    "        if i==0:\n",
    "            gamma[i]=gamma0\n",
    "        else:\n",
    "            #gamma[i]=step_weighting(dF[i-1],dF[i],P[i-1],P[i])\n",
    "            gamma[i]=step_weighting(dF[i-1],dF[i],Ptrans[i-1],Ptrans[i])\n",
    "            \n",
    "        if precision_check(dF[0],dF[i],precision):\n",
    "            print('stop',i)\n",
    "            P=P[:i]\n",
    "            Ptrans=Ptrans[:i]\n",
    "            F=F[:i]\n",
    "            dF=dF[:i]\n",
    "            gamma=gamma[:i]\n",
    "            break\n",
    "                \n",
    "        #P_next=new_parameters(P[i],gamma[i],dF[i])        \n",
    "        Ptrans_next=new_parameters(Ptrans[i],gamma[i],dF[i])\n",
    "\n",
    "        for k in range(num_paras):\n",
    "            if Ptrans_next[k]<0:\n",
    "                Ptrans_next[k]=0.\n",
    "            if Ptrans_next[k]>1:\n",
    "                Ptrans_next[k]=1.\n",
    "\n",
    "        if i<maxlength-1:\n",
    "            Ptrans[i+1]=Ptrans_next\n",
    "            P[i+1]=Pmin+Ptrans_next*(Pmax-Pmin)\n",
    "            print(F[i])\n",
    "            print(gamma[i])\n",
    "            print(P[i+1])\n",
    "            \n",
    "        if targetmode=='Coupled':\n",
    "            dataout=[dataout_ZMT,dataout_GMT]\n",
    "            \n",
    "    return F, dF, P , Ptrans, gamma, dataout\n",
    "    \n",
    "def target_comparison(data,targetmode,target,targetfunction,num_paras,grid):\n",
    "    F=np.zeros(2*num_paras+1)\n",
    "    if targetfunction=='LeastSquare':\n",
    "        if targetmode=='Single':\n",
    "            F=(np.array(data)-target)**2\n",
    "        elif targetmode=='ZMT':\n",
    "            for i in range(len(F)):\n",
    "                if len(data[i])==len(target):\n",
    "                    F[i]=np.sum(((data[i]-target)*np.cos(grid*np.pi/180)/np.mean(np.cos(grid*np.pi/180)))**2)\n",
    "                elif len(data[i])==len(F):\n",
    "                    F[i]=np.sum(((data[:,i]-target)*np.cos(grid*np.pi/180)/np.mean(np.cos(grid*np.pi/180)))**2)\n",
    "        elif targetmode=='GMT':\n",
    "            for i in range(len(F)):\n",
    "                F[i]=np.sum((data[i]-target)**2)\n",
    "\n",
    "    return F\n",
    "\n",
    "def local_gradient(F,P_pert):\n",
    "    dF=np.zeros(len(P_pert))\n",
    "    for k in range(len(P_pert)):\n",
    "        dF[k]=(F[2*(k+1)-1]-F[2*(k+1)])/(2*P_pert[k])\n",
    "    return dF\n",
    "\n",
    "def step_weighting(dF0,dF1,P0,P1):\n",
    "    gamma=np.abs(np.dot(P1-P0,dF1-dF0)/np.dot(np.abs(dF1-dF0),np.abs(dF1-dF0)))\n",
    "    return gamma\n",
    "\n",
    "def precision_check(dF0,dF,precision):\n",
    "    dFabs=np.sqrt(np.dot(dF,dF))\n",
    "    dF0abs=np.sqrt(np.dot(dF0,dF0))\n",
    "    if dFabs/dF0abs <= precision:\n",
    "        return True\n",
    "    \n",
    "def new_parameters(P,gamma,dF):\n",
    "    P_next=P-gamma*dF\n",
    "    return P_next\n",
    "\n",
    "def run_model(config,P,P_pert,labels,ZMT,GMT,targetmode,control,controlconfig,grid,elevation):\n",
    "    \n",
    "    P_config=reshape_parameters(P,P_pert)\n",
    "    setup={'number_of_parameters': len(P), 'number_of_cycles': 1, 'number_of_parallels': len(P)*2+1}\n",
    "    \n",
    "    if targetmode=='Coupled':\n",
    "        control=True\n",
    "        \n",
    "    if control==True:\n",
    "        variable_importer(controlconfig,initialZMT=True,parallel=True,parallel_config=setup)\n",
    "        controlconfig=add_parameters(controlconfig,P_config,labels)\n",
    "        data_CTRL=rk4alg(model_equation,controlconfig['eqparam'],controlconfig['rk4input'],controlconfig['funccomp'],progressbar=True)\n",
    "        ZMT,GMT=data_CTRL[1][-1],data_CTRL[2][-1]\n",
    "\n",
    "    variable_importer(config,initialZMT=False,parallel=True,parallel_config=setup)\n",
    "    config=add_parameters(config,P_config,labels)\n",
    "    Vars.T,Vars.T_global=ZMT,GMT   \n",
    "    data=rk4alg(model_equation,config['eqparam'],config['rk4input'],config['funccomp'],progressbar=True)\n",
    "    \n",
    "    if targetmode=='Single':\n",
    "        data_out=data[2][-1]\n",
    "    elif targetmode=='ZMT':\n",
    "        dataZMT=data[1][-1]\n",
    "        for i in range(len(dataZMT)):\n",
    "            dataZMT[i]=dataZMT[i]+elevation\n",
    "        data_out=dataZMT\n",
    "    elif targetmode=='GMT':\n",
    "        data_out=np.transpose(data[2][:-1]-data[2][0])\n",
    "    elif targetmode=='Coupled':\n",
    "        dataZMT=data_CTRL[1][-1]\n",
    "        for i in range(len(dataZMT)):\n",
    "            dataZMT[i]=dataZMT[i]+elevation\n",
    "        dataGMT=np.transpose(data[2][:-1]-data[2][0])\n",
    "        data_out=[dataZMT,dataGMT]\n",
    "    return data_out\n",
    "\n",
    "def reshape_parameters(P,P_pert):\n",
    "    num_para=len(P)\n",
    "    P_config=np.reshape(np.zeros(num_para*(2*num_para+1)),(num_para,2*num_para+1))\n",
    "    for i in range(num_para):\n",
    "        P_config[i]=np.array([P[i]]*(2*num_para+1))\n",
    "        P_config[i][i*2+1]=P[i]+P_pert[i]\n",
    "        P_config[i][i*2+2]=P[i]-P_pert[i]\n",
    "                      \n",
    "    return P_config\n",
    "             \n",
    "def add_parameters(config,P_config,labels):\n",
    "    num_para=len(P_config)\n",
    "    \n",
    "    for i in range(num_para):\n",
    "        if labels[i][0][:4]=='func':\n",
    "            config['funccomp']['funcparam'][labels[i][0]][labels[i][1]]=P_config[i]\n",
    "        if labels[i][0]=='eqparam':\n",
    "            config[labels[i][0]][labels[i][1]]=P_config[i]\n",
    "    return config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading Configuration from: Dev_Data/Optimization/Volcanic_Budyko_CTRL.ini\n",
      "Loading Parameters from: /Home/siv32/bsc029/.local/lib/python3.6/site-packages/lowEBMs/Tutorials/Config/Data/SellersParameterization.ini\n",
      "Loading Configuration from: Dev_Data/Optimization/Volcanic_Budyko.ini\n",
      "Loading Parameters from: /Home/siv32/bsc029/.local/lib/python3.6/site-packages/lowEBMs/Tutorials/Config/Data/SellersParameterization.ini\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "533ba21b27244fdd9f2e9784efc02876",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration no.0\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "58320259afa14213a2fff45f0b84963e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6c3801510c4542f7a98247041f9dc949",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[17888.18999508 17888.1898724  17888.19011789 17889.14106855\n",
      " 17887.23894713 17886.6077993  17889.77243915 17888.19064922\n",
      " 17888.18934094 17888.19039401 17888.18959615 17888.19295096\n",
      " 17888.18703911]\n",
      "1e-08\n",
      "[2.94000017e+08 2.29991440e+02 2.50051689e+00 1.16499996e+00\n",
      " 1.16499998e+00 1.16499982e+00]\n",
      "Iteration no.1\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d9f0ee3ad81d42e181ba50123f255d33",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2d43aa60bc2a4b36bb87338f8774aa43",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[17880.99337678 17880.99325416 17880.99349953 17881.94406046\n",
      " 17880.04271862 17879.41223375 17882.57476789 17880.99403072\n",
      " 17880.99272285 17880.99377551 17880.99297806 17880.99633175\n",
      " 17880.99042173]\n",
      "1.5531209417215246e-05\n",
      "[2.94025766e+08 2.16702878e+02 3.30000000e+00 1.16493864e+00\n",
      " 1.16496259e+00 1.16472272e+00]\n",
      "Iteration no.2\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f347ad9050b047689a7096d98cef342f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "55f24395589c4d58b779b08a2df541df",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4002.92108031 4002.57494793 4003.26703769 4008.08262964 3997.75972029\n",
      " 4000.56407539 4005.28016333 4002.94202092 4002.90010367 4002.92948619\n",
      " 4002.91263856 4003.02271994 4002.81929405]\n",
      "5.562223848129566e-06\n",
      "[3.20036561e+08 1.90864629e+02 3.30000000e+00 1.16423478e+00\n",
      " 1.16467969e+00 1.16130687e+00]\n",
      "Iteration no.3\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ee27c7a795894680bbc7b3efcfe119af",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bf40723c2a18452f9494e849387d79c7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[35.39137754 35.39129021 35.39146495 35.42698157 35.35580048 35.40254574\n",
      " 35.38021033 35.39152787 35.3912272  35.39142778 35.39132729 35.39218661\n",
      " 35.3905685 ]\n",
      "3.704274007547896e-06\n",
      "[3.20040935e+08 1.90745975e+02 3.29864864e+00 1.16423142e+00\n",
      " 1.16467856e+00 1.16128878e+00]\n",
      "Iteration no.4\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0e5950bb03594f01a168a329595628b4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1896aa7731db4c8e883421b5f2558c16",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[34.58567521 34.58558773 34.58576279 34.62069576 34.55068167 34.59673161\n",
      " 34.57461983 34.58582671 34.58552371 34.58572568 34.58562473 34.58648829\n",
      " 34.58486216]\n",
      "0.00023764715799896603\n",
      "[3.20322035e+08 1.90000000e+02 3.21282021e+00 1.16401404e+00\n",
      " 1.16460614e+00 1.16012215e+00]\n",
      "Iteration no.5\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3de20ab367ad40a9b1f1be532b81ec2b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bcad23ba6ae24c4fb2696639d75d9f0f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[24.29905648 24.29895787 24.29915519 24.32700106 24.27114101 24.30859259\n",
      " 24.28952195 24.29921329 24.29889967 24.29910722 24.29900574 24.29987784\n",
      " 24.29823516]\n",
      "0.00027893374603307216\n",
      "[3.20693936e+08 1.90000000e+02 3.12593595e+00 1.16374995e+00\n",
      " 1.16452069e+00 1.15873890e+00]\n",
      "Iteration no.6\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8c1633aaf86d407ab8149a8ffa7a9556",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "06a8364c50674defbbb84c46d28481f2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[18.68215895 18.6820471  18.68227091 18.70566942 18.65867999 18.69058213\n",
      " 18.67373781 18.68231529 18.68200261 18.68220877 18.68210913 18.68296779\n",
      " 18.68135017]\n",
      "0.0003161036229208225\n",
      "[3.21171947e+08 1.90000000e+02 3.03896830e+00 1.16345157e+00\n",
      " 1.16442560e+00 1.15719525e+00]\n",
      "Iteration no.7\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "629a9ec13b284a7a8d3ff8331d442297",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "051a7e503a884018a99366fb9d28f3a9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[13.8445982  13.84447076 13.84472575 13.86286166 13.82636895 13.85158443\n",
      " 13.83761459 13.84475668 13.84443972 13.84464774 13.84454866 13.84540471\n",
      " 13.84379174]\n",
      "0.00028447888681851186\n",
      "[3.21662080e+08 1.90000000e+02 2.97405761e+00 1.16317936e+00\n",
      " 1.16434050e+00 1.15581002e+00]\n",
      "Iteration no.8\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f520b6af3c784fbba7457adc1cd49d62",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8a0b3a134c5447529ce21d13c80fab80",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10.87568502 10.87554425 10.8758259  10.88940884 10.86199767 10.88133607\n",
      " 10.87003714 10.87584727 10.87552278 10.8757349  10.87563514 10.87649851\n",
      " 10.87487159]\n",
      "0.00025740737513162165\n",
      "[3.22151935e+08 1.90000000e+02 2.92655328e+00 1.16292721e+00\n",
      " 1.16426298e+00 1.15454578e+00]\n",
      "Iteration no.9\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "062794bb8ac44b6a8a04a21766cf6ab6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "860146c0635e4a1b9ca3e7ccfd2d27a8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[9.12104632 9.12089485 9.1211979  9.1310589  9.111072   9.12554865\n",
      " 9.11654761 9.12121274 9.1208799  9.1210968  9.12099584 9.12187067\n",
      " 9.12022203]\n",
      "0.0002379825814605524\n",
      "[3.22639244e+08 1.90000000e+02 2.89156580e+00 1.16268808e+00\n",
      " 1.16419045e+00 1.15336134e+00]\n",
      "Iteration no.10\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9752ee47ff134d74b1d1d9d7d8832a88",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "53613ab659524fa2a98924190ceadca2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[8.0864889  8.08632908 8.08664883 8.093535   8.06351174 8.09003858\n",
      " 8.0802943  8.08665925 8.08631854 8.08654004 8.08643775 8.08732477\n",
      " 8.08565308]\n",
      "3.786516638498958e-05\n",
      "[3.22721053e+08 1.90000000e+02 2.88553932e+00 1.16264913e+00\n",
      " 1.16417876e+00 1.15317025e+00]\n",
      "Iteration no.11\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f471e6190bf54d0197732988dfce05ed",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3bf0bed574e044d69947c7af36d30cca",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[7.86385812 7.86370491 7.86401144 7.87291976 7.85484834 7.86795703\n",
      " 7.85977285 7.86400835 7.86370789 7.86390301 7.86381322 7.86456112\n",
      " 7.86316469]\n",
      "9.48447927883169e-06\n",
      "[3.22740697e+08 1.90000000e+02 2.88427148e+00 1.16264053e+00\n",
      " 1.16417619e+00 1.15313026e+00]\n",
      "Iteration no.12\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "036a099b0a584b52be296f9962048d66",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "96872c18b074446c84b4a744f149a1bd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[7.82619245 7.82604435 7.82634541 7.83514079 7.81730349 7.83025376\n",
      " 7.82214482 7.82635246 7.82604193 7.82624216 7.82614748 7.8268969\n",
      " 7.82549761]\n",
      "0.0002051182168736738\n",
      "[3.23157949e+08 1.90000000e+02 2.85710439e+00 1.16244824e+00\n",
      " 1.16411756e+00 1.15226379e+00]\n",
      "Iteration no.13\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ea35259886a9495d8d0b8730d842e167",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "99a2f4c034f14826aae7624a27c11a1c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[7.13920306 7.13906304 7.13933658 7.14431842 7.13414087 7.14210019\n",
      " 7.13631062 7.13937364 7.13903433 7.13925503 7.13915452 7.13999665\n",
      " 7.13840643]\n",
      "0.00012939073269276652\n",
      "[3.23397100e+08 1.90000000e+02 2.84486883e+00 1.16231570e+00\n",
      " 1.16407829e+00 1.15164263e+00]\n",
      "Iteration no.14\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8df8aab32852437fb147ddfc950ea69e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1503cdf18e274d2fa066e45d623d5a22",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6.89586725 6.89573502 6.8959996  6.89920928 6.89260883 6.89821006\n",
      " 6.89353585 6.89604162 6.89569289 6.89591749 6.89581702 6.89670537\n",
      " 6.89503017]\n",
      "0.00012674741840276762\n",
      "[3.23623683e+08 1.90000000e+02 2.83519224e+00 1.16218226e+00\n",
      " 1.16403985e+00 1.15100164e+00]\n",
      "Iteration no.15\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "841a06186f634543b1f8350cd5930662",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "639e38eebd184016bd4e174b29fbf6da",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6.74067926 6.74055063 6.74080799 6.74289832 6.73849528 6.74265747\n",
      " 6.73870509 6.74085666 6.74050187 6.74073159 6.74062693 6.74153538\n",
      " 6.73982319]\n",
      "0.00016861461830522102\n",
      "[3.23916893e+08 1.90000000e+02 2.82430725e+00 1.16200167e+00\n",
      " 1.16398657e+00 1.15013010e+00]\n",
      "Iteration no.16\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3ff06947ff524b719ce1e7ff9ae3d132",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c9ed584a4f114d4097dea1e1db5df92c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6.57923074 6.57910026 6.57936132 6.58053941 6.57795752 6.58089044\n",
      " 6.5775752  6.57940889 6.57905259 6.57928311 6.57917837 6.58008617\n",
      " 6.57837536]\n",
      "0.00023899514075931115\n",
      "[3.24338470e+08 1.90000000e+02 2.81136591e+00 1.16174459e+00\n",
      " 1.16391100e+00 1.14889576e+00]\n",
      "Iteration no.17\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2b42edb6541347ac9261af161c0e96dc",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "62e40771e2b943cf8ea4b92c787babeb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6.415445   6.41531238 6.41557772 6.41564826 6.41527764 6.416714\n",
      " 6.4141803  6.41562408 6.41526591 6.41549741 6.41539258 6.4162996\n",
      " 6.41459044]\n",
      "0.00023530397181098107\n",
      "[3.24760341e+08 1.90000000e+02 2.80162812e+00 1.16149017e+00\n",
      " 1.16383654e+00 1.14768165e+00]\n",
      "Iteration no.18\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ebeb3f4e0b9b43eb9f0631e2b25f5425",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f12a4b8b16e04e4a93967116609e35b3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6.30974987 6.30961577 6.30988408 6.30910562 6.31043038 6.31071614\n",
      " 6.30878802 6.30992963 6.30957011 6.3098023  6.30969744 6.31060365\n",
      " 6.30889615]\n",
      "0.0002322886737172977\n",
      "[3.25181449e+08 1.90138477e+02 2.79431272e+00 1.16123805e+00\n",
      " 1.16376301e+00 1.14648427e+00]\n",
      "Iteration no.19\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "224481de45b541ccad5dff31bbd455d1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b6ad5bf9e0054261b4c7c174434f6131",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6.21730509 6.21717003 6.21744025 6.21685901 6.21778769 6.21832852\n",
      " 6.21628608 6.21748305 6.21712713 6.21735704 6.21725314 6.21815118\n",
      " 6.21645905]\n",
      "2.2499403539815302e-05\n",
      "[3.25222530e+08 1.90147880e+02 2.79356215e+00 1.16121388e+00\n",
      " 1.16375595e+00 1.14636934e+00]\n",
      "Iteration no.20\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2a706207860a4ea3ba2ee24c35d2ca59",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d5add540435b4a37bbd6fbee47ddb6b9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6.20847081 6.20833565 6.20860608 6.20801593 6.20896224 6.20949015\n",
      " 6.20745591 6.20864866 6.20829296 6.20852273 6.20841889 6.20931636\n",
      " 6.20762533]\n",
      "0.0012321067074340408\n",
      "[3.27473944e+08 1.90672560e+02 2.75262439e+00 1.15989083e+00\n",
      " 1.16336971e+00 1.14007943e+00]\n",
      "Iteration no.21\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "310c96100dce4c45ac248ac5bcffd380",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9c229fcfc6fe4dfb9b38980d73e6d365",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.73941529 5.73927413 5.73955656 5.73854461 5.74032408 5.74023089\n",
      " 5.73860432 5.73958697 5.73924362 5.73946534 5.73936524 5.74022914\n",
      " 5.73860151]\n",
      "0.0014829490726356912\n",
      "[3.30303840e+08 1.91860046e+02 2.71322639e+00 1.15835373e+00\n",
      " 1.16292160e+00 1.13279284e+00]\n",
      "Iteration no.22\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "17f3476f69d249e297063ab4e0b41448",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "79585e5d65e74a4189a9c04cdea7e461",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.54619622 5.54600525 5.54638731 5.55333198 5.53911874 5.54935536\n",
      " 5.54304807 5.54631981 5.54607836 5.54623381 5.54616149 5.54670875\n",
      " 5.54568956]\n",
      "5.2846963320334914e-05\n",
      "[3.30440264e+08 1.91522038e+02 2.70778215e+00 1.15831521e+00\n",
      " 1.16291006e+00 1.13263024e+00]\n",
      "Iteration no.23\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8a68784c6c0d40c084e584c3bfdee5dd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5af2dff7fb7b48308fc8bddeb1387e41",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.22238306 5.22222038 5.22254338 5.22362486 5.22124192 5.22378296\n",
      " 5.2209821  5.2225355  5.22223062 5.22242619 5.22233993 5.22309973\n",
      " 5.22166061]\n",
      "6.882328189714304e-05\n",
      "[3.30590470e+08 1.91448238e+02 2.70463366e+00 1.15825187e+00\n",
      " 1.16289213e+00 1.13233124e+00]\n",
      "Iteration no.24\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "75e9890ef9944a549e2b4ac4a0b972a9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d3652d02f15c4aac89d9cf106dea54cc",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.19117844 5.19105711 5.19129988 5.18939624 5.19415651 5.19162439\n",
      " 5.19082872 5.19135454 5.19099952 5.19123105 5.19112648 5.19204891\n",
      " 5.19030919]\n",
      "3.416189290880003e-05\n",
      "[3.30646507e+08 1.91521417e+02 2.70418970e+00 1.15821525e+00\n",
      " 1.16288135e+00 1.13215182e+00]\n",
      "Iteration no.25\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "82890476694743c5b15a462e0707dd26",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9d9daddaad2f4e3b9aaeb8ff9dd067b7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.17954928 5.17939482 5.17969771 5.18006237 5.17913884 5.1807234\n",
      " 5.17837693 5.17970485 5.17939371 5.1795932  5.17950535 5.18029108\n",
      " 5.17880767]\n",
      "2.191780093689688e-05\n",
      "[3.30691362e+08 1.91512308e+02 2.70334968e+00 1.15819466e+00\n",
      " 1.16287554e+00 1.13205367e+00]\n",
      "Iteration no.26\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2444be3bccd34571b035a6e808afcb96",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c0009bb095da4f36b0a7c0ee271240e4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.17037477 5.1702282  5.1705277  5.1705374  5.17034358 5.17144534\n",
      " 5.16932578 5.17053812 5.17022028 5.17041914 5.1703304  5.17113234\n",
      " 5.16962366]\n",
      "6.411826908209195e-05\n",
      "[3.30821117e+08 1.91506715e+02 2.70112994e+00 1.15813314e+00\n",
      " 1.16285836e+00 1.13176164e+00]\n",
      "Iteration no.27\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "061af5c864064b90b9638bf8784df01b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "03d318de287a48d5b284f336cbb522e3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.14951924 5.14937619 5.14965688 5.14886468 5.15040882 5.15033528\n",
      " 5.14873534 5.14968594 5.14935256 5.14957361 5.14947406 5.15030887\n",
      " 5.14872989]\n",
      "5.0531707344632724e-05\n",
      "[3.30916956e+08 1.91541828e+02 2.69980943e+00 1.15808229e+00\n",
      " 1.16284317e+00 1.13152077e+00]\n",
      "Iteration no.28\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4ee6e50763c8447a9a1cfb951b23aae4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6cbd33e22db0441b8b39f8f07ac111c0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.13339228 5.13323991 5.13353847 5.13328024 5.13364293 5.13437283\n",
      " 5.13242565 5.13354985 5.1332374  5.13343672 5.13334784 5.13415295\n",
      " 5.13263184]\n",
      "1.703008083694427e-05\n",
      "[3.30951311e+08 1.91544608e+02 2.69926781e+00 1.15806622e+00\n",
      " 1.16283860e+00 1.13144257e+00]\n",
      "Iteration no.29\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c0f03ccf13c94febb28197399fdb3ef2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7f439c9dc88f46989f563b3abd58d497",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.12795305 5.12780099 5.12809259 5.12775799 5.12828999 5.1288958\n",
      " 5.12701542 5.12811092 5.12778887 5.12799756 5.12790854 5.12870935\n",
      " 5.12719068]\n",
      "0.00011092388841586906\n",
      "[3.31169862e+08 1.91571163e+02 2.69586102e+00 1.15795838e+00\n",
      " 1.16280880e+00 1.13093402e+00]\n",
      "Iteration no.30\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1fa454a2a8ea43d7a606008d9aeaa983",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4061796626c441acb25e4a6a22f8df8b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.0937058  5.09355446 5.09383891 5.09315883 5.09442345 5.09454193\n",
      " 5.09288158 5.0938644  5.09353526 5.09375046 5.09365557 5.0944733\n",
      " 5.092933  ]\n",
      "9.822724257810851e-05\n",
      "[3.31358650e+08 1.91627062e+02 2.69319719e+00 1.15786078e+00\n",
      " 1.16278066e+00 1.13047727e+00]\n",
      "Iteration no.31\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7335ec3cb46a48df924518f6d0df4de3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5d55ae86ffc24e0d99de4d1d4e91b34d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.06390197 5.06375941 5.06405719 5.06393927 5.06399542 5.06491093\n",
      " 5.06291025 5.06406333 5.0637469  5.06395097 5.06385826 5.06464774\n",
      " 5.06317426]\n",
      "1.4727726949871921e-05\n",
      "[3.31388282e+08 1.91627434e+02 2.69271592e+00 1.15784671e+00\n",
      " 1.16277654e+00 1.13041175e+00]\n",
      "Iteration no.32\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "227b26b76e2f4c71a4c80f38e29bdd7c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "60f53d6d7b234cc8af465790734c6670",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.05918334 5.05902868 5.05932652 5.05910977 5.05937296 5.06014615\n",
      " 5.05821735 5.05933619 5.05901626 5.05922717 5.05913952 5.05992541\n",
      " 5.05843521]\n",
      "8.216848856089246e-05\n",
      "[3.31553644e+08 1.91637165e+02 2.69012730e+00 1.15776735e+00\n",
      " 1.16275480e+00 1.13004210e+00]\n",
      "Iteration no.33\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a8150189a3c64f94ac6da41a35663119",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ef5d09e97a1e4047b64e6599530e47d8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.03443924 5.03429278 5.03458027 5.03387796 5.03516295 5.03525155\n",
      " 5.03363314 5.03460288 5.03427006 5.03448988 5.03438945 5.03519869\n",
      " 5.03367449]\n",
      "7.256954574440376e-05\n",
      "[3.31694611e+08 1.91679128e+02 2.68820899e+00 1.15769443e+00\n",
      " 1.16273279e+00 1.12970818e+00]\n",
      "Iteration no.34\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "886aa433e7dd472399f2d4727e2f7e43",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "81143458d55942b5b87b89090b906205",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.01275905 5.01260855 5.01291396 5.01265937 5.0129967  5.01371668\n",
      " 5.01182589 5.01291882 5.01260988 5.01280785 5.01271555 5.01349511\n",
      " 5.01202222]\n",
      "1.5327343394867992e-05\n",
      "[3.31726240e+08 1.91681455e+02 2.68773564e+00 1.15768014e+00\n",
      " 1.16272852e+00 1.12964003e+00]\n",
      "Iteration no.35\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b5c6d47f08834ae687e353bfa66b2418",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bdc88a0fff8149019ad76598b7a28bcf",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.00813886 5.00799062 5.00829452 5.00795482 5.00844054 5.00906915\n",
      " 5.00722436 5.00830088 5.00798415 5.00818874 5.00809263 5.0088828\n",
      " 5.00740779]\n",
      "8.749069156947086e-05\n",
      "[3.31905895e+08 1.91700578e+02 2.68509941e+00 1.15759648e+00\n",
      " 1.16270314e+00 1.12925044e+00]\n",
      "Iteration no.36\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "012bcddef66f4fc8afb21788bba516a7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "08391a704c38475c857a287de39939d0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.98242149 4.98227301 4.98257647 4.98197226 4.9830206  4.98326041\n",
      " 4.98159941 4.98258007 4.98226883 4.98246519 4.98237779 4.98316979\n",
      " 4.98167981]\n",
      "0.00011582208992845009\n",
      "[3.32143381e+08 1.91755218e+02 2.68195720e+00 1.15748766e+00\n",
      " 1.16267258e+00 1.12872947e+00]\n",
      "Iteration no.37\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f57261429f644bca98acb13c8a34098b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2dc1e1a4b73d401b894fd7dc1fd6671d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.94903995 4.94888227 4.94919687 4.94894555 4.94923469 4.94998348\n",
      " 4.9481112  4.94919269 4.94888634 4.94908829 4.94899387 4.94976566\n",
      " 4.94831358]\n",
      "3.6673287183767846e-07\n",
      "[3.32144160e+08 1.91755266e+02 2.68194599e+00 1.15748732e+00\n",
      " 1.16267247e+00 1.12872786e+00]\n",
      "Iteration no.38\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "124d5a37875c47c7997f4b66367b362f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0e3d1d70c9d9400da3730ca92e884067",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.94892763 4.94877536 4.94909083 4.94883184 4.94914181 4.94987066\n",
      " 4.94801099 4.94908578 4.9487803  4.94897057 4.9488847  4.94965338\n",
      " 4.94820211]\n",
      "2.162286389823982e-05\n",
      "[3.32190251e+08 1.91758282e+02 2.68128920e+00 1.15746738e+00\n",
      " 1.16266687e+00 1.12863313e+00]\n",
      "Iteration no.39\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "535325ea760644c5b3903d15d61e5155",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "384695203adc48c88792f1aaeb696774",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.94261385 4.94245643 4.94276507 4.94242742 4.94291986 4.94351988\n",
      " 4.94171162 4.94276683 4.9424599  4.94265954 4.94257083 4.94333481\n",
      " 4.94188315]\n",
      "9.668317456898714e-05\n",
      "[3.32391880e+08 1.91779707e+02 2.67843367e+00 1.15737779e+00\n",
      " 1.16264097e+00 1.12820943e+00]\n",
      "Iteration no.40\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "53e905e3415b40588ac3a8f012bce22c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cf00569cfdcd4ffeb7db3534cc5afda5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.91514188 4.91499037 4.91528882 4.914702   4.91570589 4.91596729\n",
      " 4.91433599 4.9152954  4.91498738 4.91518503 4.91509873 4.91586622\n",
      " 4.91440502]\n",
      "0.00014740927430705378\n",
      "[3.32689144e+08 1.91846299e+02 2.67450601e+00 1.15724072e+00\n",
      " 1.16260257e+00 1.12755918e+00]\n",
      "Iteration no.41\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "84b51b77048945c99a85e914cd1d7f18",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4e2f2e5a4e5e4c22889818b5e9967ded",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.87430061 4.87414602 4.87446624 4.87424639 4.87447698 4.87523436\n",
      " 4.87338342 4.87445661 4.87415554 4.87434286 4.87425837 4.87501326\n",
      " 4.87359504]\n",
      "7.850817615764681e-06\n",
      "[3.32706131e+08 1.91847114e+02 2.67426866e+00 1.15723358e+00\n",
      " 1.16260057e+00 1.12752557e+00]\n",
      "Iteration no.42\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9e7737b3bf53473bb1000e98b36a5b6a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "aa283a9766e748ca88bd56557fa717f7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.87206877 4.87190883 4.87222796 4.87197387 4.8722775  4.87297723\n",
      " 4.87116151 4.87221941 4.87191727 4.87211648 4.87202649 4.87277578\n",
      " 4.87135484]\n",
      "0.00012828706970945236\n",
      "[3.32982759e+08 1.91864642e+02 2.67046408e+00 1.15711657e+00\n",
      " 1.16256572e+00 1.12697526e+00]\n",
      "Iteration no.43\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2dbf08194def40968fb9cf0bd8497730",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "445898711d4b42a5ac6f8437a872572e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.83737594 4.83722525 4.83753418 4.83673286 4.83815919 4.83810913\n",
      " 4.83664952 4.83752934 4.83722355 4.83741871 4.83733317 4.8381067\n",
      " 4.83665828]\n",
      "9.735807916634573e-05\n",
      "[3.33185983e+08 1.91927131e+02 2.66814304e+00 1.15702669e+00\n",
      " 1.16254058e+00 1.12654955e+00]\n",
      "Iteration no.44\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b089294efea6478faf013fa3e33f409f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b323bb90e6634e5984e78162070108f2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.81133993 4.8111774  4.81149537 4.81136016 4.8114217  4.81227509\n",
      " 4.81040577 4.81148809 4.81118551 4.81138149 4.81129837 4.81203212\n",
      " 4.8106381 ]\n",
      "2.4630490432159842e-05\n",
      "[3.33238901e+08 1.91927813e+02 2.66739101e+00 1.15700419e+00\n",
      " 1.16253440e+00 1.12644590e+00]\n",
      "Iteration no.45\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "174f7dfda4e7479fa3737d26c830b096",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "eada5051475047fc916ce57ebc72f199",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.80442572 4.80426384 4.80458143 4.80428994 4.80466837 4.80531189\n",
      " 4.80355099 4.80457452 4.80427694 4.80446745 4.804384   4.80512207\n",
      " 4.80372049]\n",
      "8.824987770394493e-05\n",
      "[3.33428277e+08 1.91942842e+02 2.66485283e+00 1.15692491e+00\n",
      " 1.16251216e+00 1.12607250e+00]\n",
      "Iteration no.46\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d3017083c5704e66babfca6b2a6f1ee5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "eb0d2ef28ec64d0fb57a703bd003efea",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.78109376 4.78092735 4.78124292 4.78067059 4.7816277  4.78188038\n",
      " 4.78030461 4.78123801 4.78093215 4.78113571 4.78104631 4.78179655\n",
      " 4.78037935]\n",
      "0.00011522613219726777\n",
      "[3.33673966e+08 1.91992470e+02 2.66188719e+00 1.15681852e+00\n",
      " 1.16248107e+00 1.12557952e+00]\n",
      "Iteration no.47\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a8624a04f46844868da75cc79d53cc91",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5411a76f9c7a4456baf93df249661540",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.7511177  4.75094895 4.75128123 4.75095836 4.75138564 4.75197933\n",
      " 4.75026094 4.75125969 4.75097038 4.75115897 4.75107108 4.75180866\n",
      " 4.75043059]\n",
      "4.778797337304472e-06\n",
      "[3.33684695e+08 1.91993389e+02 2.66175306e+00 1.15681435e+00\n",
      " 1.16247980e+00 1.12555964e+00]\n",
      "Iteration no.48\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d10ccd3aa53848ab85654d54665d08b3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "94f8e97f75a0499195b2f734aa523ea1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.74987288 4.74970949 4.75004172 4.74970721 4.75015859 4.7507309\n",
      " 4.7490264  4.75002023 4.74973087 4.74991683 4.7498316  4.75056666\n",
      " 4.7491883 ]\n",
      "0.00021441127222057916\n",
      "[3.34166001e+08 1.92036940e+02 2.65578382e+00 1.15662705e+00\n",
      " 1.16242463e+00 1.12466746e+00]\n",
      "Iteration no.49\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a079dd86dcab4fa4b4b7b1fe6d3eac8a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7d2f6a4c0da543768703ea361eb1628d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.69610888 4.69595326 4.69627104 4.6953993  4.69694393 4.69678983\n",
      " 4.69544365 4.69626396 4.69596024 4.69615367 4.69606179 4.69681732\n",
      " 4.69540711]\n",
      "0.0001344120930670261\n",
      "[3.34454613e+08 1.92130368e+02 2.65282840e+00 1.15650381e+00\n",
      " 1.16238735e+00 1.12409524e+00]\n",
      "Iteration no.50\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7eba7f212a2a4441bfaee1f71b262c90",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c752422c6302454cbffe1de5cc3b6cd4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.66404774 4.66387347 4.66421711 4.66437864 4.66381578 4.66503375\n",
      " 4.6630738  4.6641843  4.66390616 4.6640874  4.66400305 4.66470743\n",
      " 4.66339488]\n",
      "3.4750753033018595e-05\n",
      "[3.34535301e+08 1.92121566e+02 2.65171595e+00 1.15647463e+00\n",
      " 1.16237850e+00 1.12395754e+00]\n",
      "Iteration no.51\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "010d5e8de871497486a8df5f5436e0f4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a18e41bc1ea149e2b1cf0a80a5d24598",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.65395175 4.6537793  4.65410916 4.65390877 4.65409544 4.65481679\n",
      " 4.65309048 4.6540953  4.65379565 4.65399192 4.6539053  4.65461658\n",
      " 4.65327459]\n",
      "7.465240648269289e-05\n",
      "[3.34701685e+08 1.92127836e+02 2.64961102e+00 1.15640710e+00\n",
      " 1.16235898e+00 1.12365510e+00]\n",
      "Iteration no.52\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3732024cc9484b65a76489250b5d26df",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4ef57e0bf83d4ea3abea73eb67194e70",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.63567039 4.63550457 4.63583633 4.63528404 4.63617177 4.63642612\n",
      " 4.63492085 4.63581534 4.63552545 4.63571091 4.63562988 4.63635041\n",
      " 4.63499728]\n",
      "9.539825945712576e-05\n",
      "[3.34915536e+08 1.92165946e+02 2.64726555e+00 1.15632361e+00\n",
      " 1.16233564e+00 1.12326541e+00]\n",
      "Iteration no.53\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3d1486578f9a44ad84b4e28341d02002",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "95da198ab22f4270add45384b9146e18",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.61293594 4.61276839 4.61310361 4.61272521 4.61325169 4.61373985\n",
      " 4.61213506 4.61307918 4.61279272 4.61297596 4.61289593 4.61360531\n",
      " 4.61227312]\n",
      "8.864068299133076e-06\n",
      "[3.34935613e+08 1.92168046e+02 2.64703321e+00 1.15631595e+00\n",
      " 1.16233350e+00 1.12322976e+00]\n",
      "Iteration no.54\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3661fcc55c364ffc84da3d1fad59b5be",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fbe5f6921be84566b3fbcdc4b822d475",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.61083314 4.61066558 4.61100613 4.61061942 4.61115987 4.61163837\n",
      " 4.61002997 4.61097637 4.61069523 4.61087847 4.61079313 4.61149617\n",
      " 4.61016669]\n",
      "0.0005145650326658739\n",
      "[3.36119640e+08 1.92293190e+02 2.63351525e+00 1.15587923e+00\n",
      " 1.16220094e+00 1.12116454e+00]\n",
      "Iteration no.55\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8063c912f5b4429ba8296be5ad40828d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c89745c5331b4dbdad9ee22a07edc8bd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.49331051 4.493156   4.49348087 4.49239422 4.49436655 4.49386444\n",
      " 4.49278042 4.49346675 4.49317001 4.49335683 4.49327064 4.4939873\n",
      " 4.4926469 ]\n",
      "0.00023845758350745047\n",
      "[3.36643072e+08 1.92504833e+02 2.62929320e+00 1.15566561e+00\n",
      " 1.16213889e+00 1.12019962e+00]\n",
      "Iteration no.56\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "864cfcd661ec4ace8d9a08cb7659804e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b351ed99daa44bef817d3e22d82ae651",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.46205491 4.4618652  4.46224082 4.46381783 4.46037807 4.46340305\n",
      " 4.46070201 4.46217927 4.46192664 4.46208978 4.46201612 4.46260327\n",
      " 4.4614886 ]\n",
      "4.49113053868891e-05\n",
      "[3.36757057e+08 1.92435315e+02 2.62731184e+00 1.15563136e+00\n",
      " 1.16212890e+00 1.12004849e+00]\n",
      "Iteration no.57\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ecc68ee41aad486b99212c0c9ccbcd78",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2c8f5e28e4ff4c9987235cf96e42756b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.43217357 4.43199187 4.4323554  4.43247159 4.43197595 4.43307591\n",
      " 4.43128003 4.43230737 4.43204219 4.43221089 4.43213626 4.43278045\n",
      " 4.43156063]\n",
      "6.71035155108532e-05\n",
      "[3.36921882e+08 1.92420348e+02 2.62534352e+00 1.15557764e+00\n",
      " 1.16211378e+00 1.11980138e+00]\n",
      "Iteration no.58\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e19025ac408b4affae1fdfdfe1e26569",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b1256d089e7f412d906376c82135b304",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.41670288 4.41653075 4.41687622 4.41630309 4.41720666 4.41739806\n",
      " 4.41601772 4.41684032 4.41656016 4.41674109 4.41666466 4.4173315\n",
      " 4.4160681 ]\n",
      "6.92597280997335e-05\n",
      "[3.37083552e+08 1.92448510e+02 2.62378202e+00 1.15551907e+00\n",
      " 1.16209780e+00 1.11953723e+00]\n",
      "Iteration no.59\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "51b32bc0463f498988566bad066608d4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8d34ea9be0924f97b9bcb79908a2947f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.4022796  4.4020997  4.40244825 4.40207915 4.4026106  4.40301486\n",
      " 4.40154888 4.40241033 4.40213751 4.4023174  4.40223362 4.40289864\n",
      " 4.40165641]\n",
      "3.382240129740072e-05\n",
      "[3.37163206e+08 1.92456598e+02 2.62297217e+00 1.15549121e+00\n",
      " 1.16208925e+00 1.11941039e+00]\n",
      "Iteration no.60\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bf8fadd87a884d6da908a3e1b8222995",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b5876e022b0e49f1b71a1d673da9ab07",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.39537788 4.3951979  4.39555279 4.39514751 4.39574489 4.39610763\n",
      " 4.3946647  4.39550851 4.39524206 4.39541564 4.39533493 4.39599683\n",
      " 4.39474768]\n",
      "0.00020622945415268176\n",
      "[3.37657728e+08 1.92512037e+02 2.61811179e+00 1.15532533e+00\n",
      " 1.16203900e+00 1.11863269e+00]\n",
      "Iteration no.61\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7fe1f113c18540789fe8b43b2ad91027",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0078c581137440658ce8291aefd51567",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.3537679  4.35359189 4.35393762 4.35348917 4.35417273 4.35446548\n",
      " 4.35307146 4.3539024  4.35363339 4.35381037 4.35373052 4.35437902\n",
      " 4.35315573]\n",
      "0.0023170462063997984\n",
      "[3.43070443e+08 1.93224765e+02 2.56535510e+00 1.15344364e+00\n",
      " 1.16148048e+00 1.11007593e+00]\n",
      "Iteration no.62\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9034afb764fb486b8ced0799f5601c54",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "292c9034812543dfbf22edbef2f881fd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.9464146  3.94620883 3.94662048 3.94747502 3.94546649 3.9473576\n",
      " 3.94548404 3.94652035 3.94630509 3.94644366 3.94638365 3.94687858\n",
      " 3.94595733]\n",
      "0.00016575989104081654\n",
      "[3.43531504e+08 1.93074945e+02 2.56028260e+00 1.15333592e+00\n",
      " 1.16145045e+00 1.10961493e+00]\n",
      "Iteration no.63\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bf936896795b4ef2b62a38d6f79d67fa",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e0ec1bf280b247359e945210d9286533",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.94965015 3.94947151 3.94982806 3.9466655  3.95278178 3.94935932\n",
      " 3.94996649 3.94978187 3.94951154 3.94968908 3.94961425 3.95025784\n",
      " 3.94904193]\n",
      "5.591679780144939e-05\n",
      "[3.43666214e+08 1.93228846e+02 2.56083713e+00 1.15329028e+00\n",
      " 1.16143782e+00 1.10940968e+00]\n",
      "Iteration no.64\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "96294d746c984f3883bf0ad95296294a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e26ce9904c104beaa61083d2968daaa6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.91095743 3.91075537 3.9111596  3.91110386 3.91091962 3.9116093\n",
      " 3.91030255 3.91106808 3.91084678 3.91098776 3.91092709 3.91143192\n",
      " 3.9104704 ]\n",
      "4.787645747089733e-05\n",
      "[3.43796980e+08 1.93224877e+02 2.55981528e+00 1.15325830e+00\n",
      " 1.16142905e+00 1.10927070e+00]\n",
      "Iteration no.65\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ad6ed1896e324d59aa9f4632100f24cf",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "afb5d911d1c442baa8ac438824a287be",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.90436706 3.90416639 3.90456786 3.90422047 3.90463292 3.90493145\n",
      " 3.90381845 3.9044796  3.90425006 3.90439785 3.9043318  3.90485549\n",
      " 3.90388144]\n",
      "7.607406943814522e-05\n",
      "[3.44003342e+08 1.93238996e+02 2.55843233e+00 1.15320559e+00\n",
      " 1.16141388e+00 1.10904701e+00]\n",
      "Iteration no.66\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d3e66796f168474ba2295960ffe25090",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9d4d4d4e9c40488db17c7c94287d6565",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.89484865 3.89464787 3.89504954 3.89465709 3.89515223 3.89538789\n",
      " 3.89430435 3.89496096 3.89473187 3.89487936 3.89481346 3.89533572\n",
      " 3.89435081]\n",
      "0.0002894221751938166\n",
      "[3.44788838e+08 1.93303483e+02 2.55331018e+00 1.15300542e+00\n",
      " 1.16135629e+00 1.10818647e+00]\n",
      "Iteration no.67\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "28e0599e383a41bf94c759e24b27ef14",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e29a602cc35946b49194e9120f77d53e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.85918243 3.85898    3.85937622 3.85905046 3.85942269 3.85972281\n",
      " 3.85863747 3.85929225 3.85906168 3.85921242 3.85914809 3.859652\n",
      " 3.85869999]\n",
      "0.0016581801018853365\n",
      "[3.49228102e+08 1.93581239e+02 2.52391523e+00 1.15185122e+00\n",
      " 1.16103424e+00 1.10342086e+00]\n",
      "Iteration no.68\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1087ec8f88b44c3fadabe7c85e0ae9b1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4bbabbb394f843e2a264e90a4f6c1d78",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.68499052 3.68478812 3.68518819 3.68341876 3.68667112 3.68500449\n",
      " 3.68498162 3.68509894 3.68487726 3.68501974 3.68495646 3.68545431\n",
      " 3.68452217]\n",
      "0.00026110128639726785\n",
      "[3.49933916e+08 1.93963377e+02 2.52381767e+00 1.15167648e+00\n",
      " 1.16098436e+00 1.10268612e+00]\n",
      "Iteration no.69\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fccd420a386a4a13a5fc502108b8151d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b45e561b777b4d4e84c189678594ab3b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.82455932 3.82430934 3.82480943 3.82385785 3.82532182 3.82493612\n",
      " 3.82418928 3.8246781  3.82444055 3.824594   3.82452465 3.8251188\n",
      " 3.82399996]\n",
      "0.0003182733173481463\n",
      "[3.51009372e+08 1.94173050e+02 2.51993522e+00 1.15144824e+00\n",
      " 1.16091772e+00 1.10161110e+00]\n",
      "Iteration no.70\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1a5b7fc2e1234efeb1321f768dfe69e0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "364e52f3767b40afa0bd9f9272f67d9f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.79018042 3.7899305  3.79043047 3.79109894 3.78932326 3.79107046\n",
      " 3.78929698 3.79029115 3.79006971 3.79021299 3.79014786 3.7907048\n",
      " 3.78965617]\n",
      "7.246019500736992e-05\n",
      "[3.51254158e+08 1.94115151e+02 2.51783628e+00 1.15139980e+00\n",
      " 1.16090347e+00 1.10138172e+00]\n",
      "Iteration no.71\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fd51196155d849a69ca0bb1897419efb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f4045e9aad2540d38e64282bc2816fea",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.77056783 3.77031729 3.77081849 3.7706035  3.77059367 3.77116874\n",
      " 3.76997363 3.77068167 3.77045399 3.77060117 3.77053449 3.77110493\n",
      " 3.77003085]\n",
      "0.00010306903461391365\n",
      "[3.51603203e+08 1.94114695e+02 2.51582436e+00 1.15132896e+00\n",
      " 1.16088272e+00 1.10104751e+00]\n",
      "Iteration no.72\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "19cc7d20fc7e4ed1b0234a1d2df4b787",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7256a8bf69044b279152ab1870f25a22",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.75656661 3.7563157  3.75681765 3.75632063 3.75687427 3.75707148\n",
      " 3.7560685  3.75668104 3.75645219 3.75660008 3.75653315 3.75710571\n",
      " 3.75602763]\n",
      "0.0001407903391790962\n",
      "[3.52080705e+08 1.94149771e+02 2.51351793e+00 1.15123169e+00\n",
      " 1.16085428e+00 1.10058930e+00]\n",
      "Iteration no.73\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "596627a3a2594e74ad582c3436671a5b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "224ee7dd35864258b648112492c29847",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.73837834 3.73812714 3.73862966 3.73817696 3.73864158 3.73889188\n",
      " 3.73787157 3.73849187 3.73826481 3.73841155 3.73834513 3.73891306\n",
      " 3.73784373]\n",
      "0.00026845668966649376\n",
      "[3.52992233e+08 1.94205900e+02 2.50904411e+00 1.15104767e+00\n",
      " 1.16080045e+00 1.09972267e+00]\n",
      "Iteration no.74\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1f50e68d1e2c42f6b8af0cef7e0587f8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "75347fa8a26a440f94a06e579ebd27e3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.70435572 3.70410393 3.70460764 3.70411788 3.7046558  3.70484623\n",
      " 3.70387202 3.70446803 3.70424342 3.70438856 3.70432289 3.70488414\n",
      " 3.70382743]\n",
      "0.0023309313671077735\n",
      "[3.60925503e+08 1.94770132e+02 2.47195398e+00 1.14946709e+00\n",
      " 1.16033831e+00 1.09228680e+00]\n",
      "Iteration no.75\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8a87262084a84e57a655b731687530b7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fdf3043ae17e4370ae4b4a00d0ebcd05",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.4379826  3.43772595 3.43823936 3.43853327 3.43749736 3.4386291\n",
      " 3.43734309 3.43807951 3.4378857  3.43801099 3.43795421 3.43843569\n",
      " 3.43752964]\n",
      "0.00023022398219682812\n",
      "[3.61724160e+08 1.94662811e+02 2.46711819e+00 1.14933240e+00\n",
      " 1.16029884e+00 1.09165707e+00]\n",
      "Iteration no.76\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "892be0a204734cd89e531484ac3253b1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "662c7e9cece1480d803131b8e07914bb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.42298258 3.42272477 3.42324051 3.42164851 3.4243825  3.42300954\n",
      " 3.42296287 3.42308626 3.42287891 3.42301266 3.4229525  3.42346334\n",
      " 3.42250195]\n",
      "9.893161182828247e-05\n",
      "[3.62068914e+08 1.94784527e+02 2.46704278e+00 1.14927047e+00\n",
      " 1.16028087e+00 1.09136994e+00]\n",
      "Iteration no.77\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c3dd7d67385d4f3697043979c7f25c8f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "22708e7ec34a41f9bc2b70e6ad25e009",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.40370544 3.40344823 3.40396276 3.40370523 3.40377151 3.40416236\n",
      " 3.4032556  3.40380312 3.40360775 3.40373396 3.40367691 3.40416052\n",
      " 3.40325048]\n",
      "8.05083561472537e-05\n",
      "[3.62348808e+08 1.94786928e+02 2.46585042e+00 1.14922299e+00\n",
      " 1.16026701e+00 1.09114877e+00]\n",
      "Iteration no.78\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d191373d5a7b4813870a4fa544fc6e03",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1af666d645574c808d5c5664e486f393",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.39622074 3.3959634  3.39647819 3.3960737  3.39643375 3.39662733\n",
      " 3.39582127 3.39631867 3.39612281 3.39624931 3.39619216 3.39667656\n",
      " 3.39576505]\n",
      "0.0001450748293189062\n",
      "[3.62853436e+08 1.94810433e+02 2.46394041e+00 1.14913720e+00\n",
      " 1.16024197e+00 1.09074956e+00]\n",
      "Iteration no.79\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5f584dcb11c9491ea564a69e6ddb6983",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "aaa0ea24c37049919b36227b039b2a15",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.38321968 3.38296222 3.38347725 3.38305471 3.38345079 3.38361532\n",
      " 3.38283118 3.38331704 3.38312232 3.38324808 3.38319128 3.38367249\n",
      " 3.38276699]\n",
      "0.002050752359475569\n",
      "[3.69989892e+08 1.95175953e+02 2.43767511e+00 1.14793174e+00\n",
      " 1.15989031e+00 1.08514366e+00]\n",
      "Iteration no.80\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b815a9a36e1140d4992890de4cc12b00",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7550199b5fcc4ebabf2ad4cc3068b932",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.21220323 3.21194425 3.21246233 3.2122812  3.21219387 3.21260315\n",
      " 3.21181064 3.21229019 3.21211629 3.21222858 3.21217789 3.21260383\n",
      " 3.21180278]\n",
      "0.00227760239237838\n",
      "[3.77962781e+08 1.95086447e+02 2.40819286e+00 1.14673607e+00\n",
      " 1.15954182e+00 1.07963578e+00]\n",
      "Iteration no.81\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b5173afa880b427c85883c202a0bf5a6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "14afb06a39874b158919235e7be7c9ba",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.27393145 3.27366979 3.27419323 3.26834509 3.27958933 3.27240182\n",
      " 3.27546935 3.27403388 3.27382903 3.27396042 3.27390248 3.27438994\n",
      " 3.27347311]\n",
      "0.00011474981903923579\n",
      "[3.78368626e+08 1.95667070e+02 2.41394215e+00 1.14666511e+00\n",
      " 1.15952175e+00 1.07931818e+00]\n",
      "Iteration no.82\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "249cacbaffab49528a0c1dd9d1da3efe",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "73453aa1b160470aab8e5972f7222a89",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.09587132 3.09561385 3.09612891 3.09813475 3.09367885 3.0968893\n",
      " 3.09486061 3.09593889 3.09580377 3.09589126 3.09585139 3.0961809\n",
      " 3.0955619 ]\n",
      "7.960577932791849e-05\n",
      "[3.78645668e+08 1.95507448e+02 2.41130439e+00 1.14663264e+00\n",
      " 1.15951217e+00 1.07916943e+00]\n",
      "Iteration no.83\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5db85c55a9ee46f585d7fbcb3262acb6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f760847302144664a9aa4bc9484fd94b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.05260288 3.05234434 3.05286154 3.05255857 3.05271841 3.05288649\n",
      " 3.05232683 3.05268034 3.05252543 3.05262537 3.0525804  3.05295434\n",
      " 3.05225158]\n",
      "8.316507521855404e-05\n",
      "[3.78936300e+08 1.95513430e+02 2.41054416e+00 1.14659375e+00\n",
      " 1.15950088e+00 1.07899299e+00]\n",
      "Iteration no.84\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "85e59f86db58488c9ce6862ddbc6f4c8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bed2ea6ddab34ba29cadfe0402d88fdb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.0481955  3.04793703 3.04845409 3.04810558 3.04835671 3.04846233\n",
      " 3.04793624 3.04827287 3.04811814 3.04821796 3.04817305 3.04854633\n",
      " 3.04784483]\n",
      "0.00024024022689908897\n",
      "[3.79775621e+08 1.95540580e+02 2.40847980e+00 1.14648153e+00\n",
      " 1.15946831e+00 1.07848423e+00]\n",
      "Iteration no.85\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "baf425f29d52437ab18aba8d50c1bb46",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1b855774be464c6faa3d99c62ab5af9e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.03566092 3.03540273 3.03591923 3.03557784 3.03581551 3.03592373\n",
      " 3.0354057  3.03573743 3.03558443 3.03568312 3.03563873 3.03600733\n",
      " 3.03531467]\n",
      "0.011858767679225076\n",
      "[4.21161372e+08 1.96808865e+02 2.30814100e+00 1.14100419e+00\n",
      " 1.15787918e+00 1.05368725e+00]\n",
      "Iteration no.86\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4ac5ad38ab654c75afbc006ebe2c7fbc",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "53d42bca28ea4f54aab3caf4cead2685",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.61936235 2.61911179 2.619613   2.61919409 2.61961365 2.61926527\n",
      " 2.61946795 2.61939437 2.61933033 2.61937122 2.61935348 2.61947773\n",
      " 2.61924716]\n",
      "0.009513084450011167\n",
      "[4.53377843e+08 1.98604927e+02 2.33963287e+00 1.13916500e+00\n",
      " 1.15736978e+00 1.04706552e+00]\n",
      "Iteration no.87\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b69ea8c8ec324b929a12d56dd3c5157a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ddc86e2a14e1477987e456a097cc44e9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[7.94493908 7.94475061 7.94512762 7.97439511 7.91556231 7.9530653\n",
      " 7.93681767 7.94482235 7.94505582 7.94490844 7.94496972 7.94441002\n",
      " 7.94546837]\n",
      "7.619166523210921e-05\n",
      "[4.53571936e+08 1.96587771e+02 2.31941327e+00 1.13921870e+00\n",
      " 1.15738387e+00 1.04730895e+00]\n",
      "Iteration no.88\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4a69289c9b59489299e952519c13d2e9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3e6c06002733495f8f117d3427a9b3f9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.48628565 2.48608201 2.48648936 2.4854869  2.48716605 2.48602215\n",
      " 2.4865576  2.48631969 2.48625161 2.48629501 2.48627628 2.48640767\n",
      " 2.48616382]\n",
      "7.40221650579559e-05\n",
      "[4.53775673e+08 1.96643703e+02 2.32006065e+00 1.13920348e+00\n",
      " 1.15737968e+00 1.04725446e+00]\n",
      "Iteration no.89\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ff46db4a8efa4e9aa5c2a72d42616e57",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "afd2c9537af04acda73af16faf6205dd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.48114941 2.48094654 2.48135235 2.48123257 2.48114783 2.48116411\n",
      " 2.48114305 2.4811791  2.48111973 2.48115763 2.48114119 2.48125253\n",
      " 2.48104648]\n",
      "7.080084221225546e-05\n",
      "[4.53969804e+08 1.96641004e+02 2.32003630e+00 1.13919079e+00\n",
      " 1.15737617e+00 1.04721042e+00]\n",
      "Iteration no.90\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "70920896d08c46fea51a60e42f826807",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "90a37408a6f94484aa725d6747710380",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.48038524 2.48018257 2.48058799 2.48042947 2.48042259 2.48038766\n",
      " 2.48039117 2.48041509 2.4803554  2.48039351 2.48037698 2.48048902\n",
      " 2.48028166]\n",
      "7.414148947992519e-05\n",
      "[4.54172903e+08 1.96640774e+02 2.32004055e+00 1.13917743e+00\n",
      " 1.15737247e+00 1.04716400e+00]\n",
      "Iteration no.91\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "35058f70325341a2ae64bd9d6a27ffc7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8ffb34e2bcc3423398e682e33940af81",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.47959662 2.47939417 2.47979914 2.47964083 2.47963398 2.47959899\n",
      " 2.47960259 2.47962643 2.47956681 2.47960487 2.47958836 2.47970022\n",
      " 2.47949321]\n",
      "0.05873026829559489\n",
      "[6.14876783e+08 1.96459717e+02 2.32349158e+00 1.12860590e+00\n",
      " 1.15444611e+00 1.01046268e+00]\n",
      "Iteration no.92\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "14875cac0f264027b4e5c190ee772376",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "65a8ab3449f64383a2fac0d19b5493a0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.0896335  2.08953858 2.08972843 2.08982142 2.08952681 2.08959578\n",
      " 2.08967933 2.08963432 2.08963269 2.08963313 2.08963387 2.08958022\n",
      " 2.089687  ]\n",
      "0.04883407479603693\n",
      "[6.30000000e+08 1.90000000e+02 2.39013225e+00 1.12836678e+00\n",
      " 1.15455574e+00 1.02620424e+00]\n",
      "Iteration no.93\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d0c0b1cec7164f7eb08284124b57b3d5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "eafcf9c3a10041de9f82e5fbd0b6c0cb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[25.63561363 25.63558719 25.63564003 25.58913252 25.68214029 25.61689664\n",
      " 25.65434123 25.63577282 25.63545443 25.63565961 25.63556764 25.63630367\n",
      " 25.63492368]\n",
      "8.100391079794664e-05\n",
      "[6.30000000e+08 1.93390297e+02 2.43967382e+00 1.12828892e+00\n",
      " 1.15453325e+00 1.02586678e+00]\n",
      "Iteration no.94\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0161b0b10b63401ea03cd48cae3ab9cd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "19f8f7d436494dd29f23f24d7b1d44db",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.13807937 4.13804329 4.13811544 4.12317188 4.15304101 4.13322026\n",
      " 4.14294607 4.13819068 4.13796803 4.13810868 4.13805006 4.13850368\n",
      " 4.13765517]\n",
      "0.00011618132701357402\n",
      "[6.30000000e+08 1.94951903e+02 2.45812980e+00 1.12821083e+00\n",
      " 1.15451269e+00 1.02556918e+00]\n",
      "Iteration no.95\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ea66dc78d25e4be1b16bcba4bc9f8cf1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d91c0dc077b240b1ad2e087eaec40992",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.29311934 2.29306619 2.29317251 2.29603834 2.29026722 2.29435315\n",
      " 2.29189219 2.2931602  2.29307849 2.29313147 2.29310722 2.29328753\n",
      " 2.29295133]\n",
      "9.6359999217854e-05\n",
      "[6.30000000e+08 1.94701656e+02 2.45425654e+00 1.12818706e+00\n",
      " 1.15450563e+00 1.02547138e+00]\n",
      "Iteration no.96\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f44cdef8f1004d3ba353069abef6832a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f25ce5a92a164751b6b121278a0fec50",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.22300662 2.22294975 2.22306351 2.22255369 2.22352677 2.22317802\n",
      " 2.22284229 2.2230624  2.22295086 2.2230226  2.22299065 2.22323848\n",
      " 2.22277494]\n",
      "8.799354477006937e-05\n",
      "[6.30000000e+08 1.94740187e+02 2.45377402e+00 1.12815743e+00\n",
      " 1.15449715e+00 1.02534824e+00]\n",
      "Iteration no.97\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3df008e3326b4d9bbd5df8b043c60352",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "486ee00a40a84b178939c29a94ee1e51",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.21952952 2.21947286 2.21958619 2.21943958 2.21968672 2.21981412\n",
      " 2.21925194 2.21958334 2.21947571 2.21954498 2.21951406 2.21975272\n",
      " 2.21930649]\n",
      "7.173668718525216e-05\n",
      "[6.30000000e+08 1.94748164e+02 2.45311532e+00 1.12813412e+00\n",
      " 1.15449045e+00 1.02525160e+00]\n",
      "Iteration no.98\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0f8e0fd3db3a496a8c0ea253073f488e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7b6bb81db2364870b65fbfa256cfa357",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.21747637 2.21741956 2.2175332  2.21737943 2.21764063 2.21775679\n",
      " 2.21720298 2.21752997 2.21742278 2.21749176 2.21746098 2.2176984\n",
      " 2.21725451]\n",
      "0.0017329550992262026\n",
      "[6.30000000e+08 1.94951854e+02 2.43743958e+00 1.12757332e+00\n",
      " 1.15432943e+00 1.02292938e+00]\n",
      "Iteration no.99\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5c4f666a1e824640b5f4c1cf4e6d04fa",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1af4f072bc2746b0bde1f1b18a063428",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=5400), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "#labels=[['eqparam','c_ao'],['func1','a'],['func1','b'],['func2','factor_oc'],['func2','factor_kwv'],['func2','factor_kair']]\n",
    "#labels=[['eqparam','c_ao'],['func1','a'],['func1','b']]\n",
    "#labels=[['eqparam','c_ao'],['func1','m'],['func1','gamma'],['func3','f'],['func2','factor_oc'],['func2','factor_kwv'],['func2','factor_kair']]\n",
    "#P0=np.array([70*4.2e6,230,2.5])\n",
    "#P0=np.array([50*4.2e6,0.5,1.9e-15,0,1.165,1.165,1.165])\n",
    "#Pmin=np.array([0.5*10*4.2e6,0.4,0.6e-15,-50,0.9,0.9,0.9])\n",
    "#Pmax=np.array([100*4.2e6,0.6,5e-15,50,1.2,1.2,1.2])\n",
    "#P_pert_ralative=[1/10000,1/10000,1/10000,1/10000,1/10000,1/10000]\n",
    "#labels=[['func3','f1'],['func3','f2'],['func3','f3'],['func3','f4'],['func3','f5'],['func3','f6'],['func3','f7'],['func3','f8'],['func3','f9'],['func3','f10'],\\\n",
    "#       ['func3','f11'],['func3','f12'],['func3','f13'],['func3','f14'],['func3','f15'],['func3','f16'],['func3','f17'],['func3','f18']]\n",
    "#P0=np.zeros(18)\n",
    "\"\"\"labels=[['eqparam','c_ao'],['func1','k'],['func1','m'],['func1','gamma'],['func2','factor_oc'],['func2','factor_kwv'],['func2','factor_kair']]\n",
    "P0=np.array([70*4.2e6,1,0.5,1.9e-15,1.165,1.165,1.165])\n",
    "P0=np.array([3.7081e+08, 9.8089e-01, 4.8458e-01, 5.0000e-15, 1.1702e+00, 1.1674e+00, 1.1998e+00])\n",
    "Pmin=np.array([1*4.2e6,0.9,0.4,0.5e-15,0.9,0.9,0.9])\n",
    "Pmax=np.array([150*4.2e6,1.1,0.6,5e-15,1.3,1.3,1.3])\"\"\"\n",
    "\n",
    "labels=[['eqparam','c_ao'],['func1','a'],['func1','b'],['func2','factor_oc'],['func2','factor_kwv'],['func2','factor_kair']]\n",
    "P0=np.array([70*4.2e6,210,2.5,1.165,1.165,1.165])\n",
    "Pmin=np.array([1*4.2e6,190,1.9,0.9,0.9,0.9])\n",
    "Pmax=np.array([100*4.2e6,240,3.3,1.3,1.3,1.3])\n",
    "#Pmax=np.full(18,50)\n",
    "#Pmin=np.full(18,-50)\n",
    "#print(Pmax)\n",
    "P_pert_ratio=1/10000\n",
    "#Pmin=np.array([20*4.2e6,190,1.7])\n",
    "#Pmax=np.array([120*4.2e6,250,3.3])\n",
    "#P_pert=(Pmax-Pmin)/100\n",
    "precision=1e-5\n",
    "maxlength=int(100)\n",
    "targetmode='Coupled'\n",
    "target={'GMT':NORESM_1990_2005,'ZMT':ZMT_10}\n",
    "targetfunction='LeastSquare'\n",
    "ratio_ZMT_GMT=0.1\n",
    "num_params=6\n",
    "gamma0=1e-8\n",
    "setup={'number_of_parameters': num_params, 'number_of_cycles': 1, 'number_of_parallels': int(num_params*2+1)}\n",
    "control=True\n",
    "\n",
    "config_CTRL=importer('Dev_Data/Optimization/Volcanic_Budyko_CTRL.ini')\n",
    "#print(config_CTRL)\n",
    "variable_importer(config_CTRL,initialZMT=True,parallel=False)\n",
    "config_CTRL,ParasCTRL=add_sellersparameters(config_CTRL,\\\n",
    "                                        parameterinterpolatorstepwise,'SellersParameterization.ini',2,0,True,True)\n",
    "        \n",
    "config_base=importer('Dev_Data/Optimization/Volcanic_Budyko.ini')\n",
    "variable_importer(config_base,initialZMT=True,parallel=True,parallel_config=setup)\n",
    "\n",
    "config_base,ParasCTRL=add_sellersparameters(config_base,\\\n",
    "                                    parameterinterpolatorstepwise,'SellersParameterization.ini',2,0,True,True)\n",
    "\n",
    "elevation=-0.0065*np.array(ParasCTRL[1][1])\n",
    "Zero_ZMT,Zero_GMT=Vars.T,Vars.T_global\n",
    "grid=Vars.Lat\n",
    "\n",
    "F, dF, P, Ptrans , gamma, data=coremodule(config_base,P0,P_pert_ratio,Pmin,Pmax,labels,Zero_ZMT,Zero_GMT,grid,maxlength\\\n",
    "        ,targetmode,target,targetfunction,ratio_ZMT_GMT,elevation,precision,num_params,gamma0,control,config_CTRL)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'Year_NorESM' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-3-2400e712d08e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m16\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m7\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m99\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m     \u001b[0max\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mYear_NorESM\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfiglegend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfontsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m18\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mncol\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mbbox_to_anchor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0.6\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m0.96\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcolumnspacing\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.8\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mhandlelength\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1.5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m99\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'Year_NorESM' is not defined"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,2,figsize=(16,7))\n",
    "for i in [0,1,2,10,99]:\n",
    "    ax[0].plot(Ha,data[1][i,0],label=i)\n",
    "plt.figlegend(fontsize=18,ncol=5,bbox_to_anchor=(0.6,0.96),columnspacing=0.8,handlelength=1.5)\n",
    "for i in [0,1,2,10,99]:\n",
    "    ax[1].plot(Vars.Lat,data[0][i,0])\n",
    "#plt.plot(Year_volc_1808_1858,data[1,1])\n",
    "#plt.plot(Year_volc_1808_1858,data[1,2])\n",
    "#plt.plot(Year_volc_1808_1858,data[1,3])\n",
    "#plt.plot(Year_volc_1808_1858,data[1,4])\n",
    "line1=ax[0].plot(Year_NorESM,NORESM_1990_2005,c='k',linewidth=1.7,label='NorESM-Target Pinatubo Response')\n",
    "line2=ax[1].plot(Lat_10,ZMT_10,c='k',linewidth=1.7,label='ERA-Target ZMT')\n",
    "ax[1].set_xticks(np.linspace(-90,90,7)), ax[1].set_xlim(-90,90)\n",
    "ax[0].set_xlabel('Time'),ax[0].set_ylabel('$T_{response}$ [K]')\n",
    "ax[1].set_xlabel('Lat'),ax[1].set_ylabel('$T_{zonal mean}$ [K]')\n",
    "ax[0].set_xticks(np.linspace(1990,2005,4)), ax[0].set_xlim(1989.8,2005.2)\n",
    "ax[0].legend((line1),['NorESM-Target Pinatubo Response'],fontsize=13,loc='upper right')\n",
    "ax[1].legend((line2),['ERA-Target ZMT'],fontsize=13,loc='upper right')\n",
    "#plt.figlegend(fontsize=18,ncol=5,bbox_to_anchor=(0.6,0.96),columnspacing=0.8,handlelength=1.5)\n",
    "#plt.xlim(1808,1858)\n",
    "plt.savefig('Data/Coupled_Optimization_BudykoRup_010.eps',format='EPS',bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading Configuration from: Dev_Data/Optimization/Volcanic_Sellers_CTRL_Offset.ini\n",
      "Loading Parameters from: /Home/siv32/bsc029/.local/lib/python3.6/site-packages/lowEBMs/Tutorials/Config/Data/SellersParameterization.ini\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c124ae6b6490490b86e9a8f7b89e6598",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=36500), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Loading Configuration from: Dev_Data/Optimization/Volcanic_Sellers_Offset.ini\n",
      "Loading Parameters from: /Home/siv32/bsc029/.local/lib/python3.6/site-packages/lowEBMs/Tutorials/Config/Data/SellersParameterization.ini\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5c6fcd35feff4219a46e1d364e81612f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=14600), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "#setup={'number_of_parameters': num_params, 'number_of_cycles': 1, 'number_of_parallels': int(num_params*2+1)}\n",
    "#labels=[['eqparam','c_ao'],['func1','m'],['func1','gamma'],['func2','factor_oc'],['func2','factor_kwv'],['func2','factor_kair']]\n",
    "#P=[3.02794273e+08, 4.80868504e-01, 2.47299528e-15, 1.16506701e+00, 1.16500290e+00, 1.16499030e+00]\n",
    "#P1=[2.10056979e+08, 5.00042362e-01, 2.01124229e-15, 1.16500050e+00,1.16500009e+00, 1.16500191e+00]\n",
    "P=[ -7.09368689, -24.3554691,  -36.65052905, -47.96235225, -49.82912432,\n",
    "   -49.07644568, -46.95244629, -45.62632961, -44.43208399, -43.93356111,\n",
    " -43.94788769, -42.54654785, -40.14638466, -31.07944123, -38.64653433,\n",
    " -31.9551132 , -20.29119435,  -5.61999035]\n",
    "labels=[['func3','f1'],['func3','f2'],['func3','f3'],['func3','f4'],['func3','f5'],['func3','f6'],['func3','f7'],['func3','f8'],['func3','f9'],['func3','f10'],\\\n",
    "       ['func3','f11'],['func3','f12'],['func3','f13'],['func3','f14'],['func3','f15'],['func3','f16'],['func3','f17'],['func3','f18']]\n",
    "config_CTRL=importer('Dev_Data/Optimization/Volcanic_Sellers_CTRL_Offset.ini')\n",
    "variable_importer(config_CTRL,initialZMT=True,parallel=False)\n",
    "config_CTRL,ParasCTRL=add_sellersparameters(config_CTRL,\\\n",
    "                                        parameterinterpolatorstepwise,'SellersParameterization.ini',2,0,True,True)\n",
    "config_CTRL=add_parameters(config_CTRL,P,labels)\n",
    "data_CTRL=rk4alg(model_equation,config_CTRL['eqparam'],config_CTRL['rk4input'],config_CTRL['funccomp'],progressbar=True)\n",
    "ZMT,GMT=data_CTRL[1][-1],data_CTRL[2][-1]\n",
    "\n",
    "config_base=importer('Dev_Data/Optimization/Volcanic_Sellers_Offset.ini')\n",
    "variable_importer(config_base,initialZMT=False)\n",
    "config_base,ParasCTRL=add_sellersparameters(config_base,\\\n",
    "                                    parameterinterpolatorstepwise,'SellersParameterization.ini',2,0,True,True)\n",
    "config=add_parameters(config_base,P,labels)\n",
    "Vars.T,Vars.T_global=ZMT,GMT   \n",
    "data1=rk4alg(model_equation,config['eqparam'],config['rk4input'],config['funccomp'],progressbar=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f41bcd48f28>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,2,figsize=(16,7))\n",
    "#ax[0].plot(data[0]/constants.time_sec_year,data[2]-data[2][0])\n",
    "ax[0].plot(data1[0]/const.time_sec_year,data1[2]-data1[2][0])\n",
    "ax[0].plot(Year_volc_1808_1858,EVA_GMT_1808_1858,c='k')\n",
    "\n",
    "elevation=-0.0065*np.array(ParasCTRL[1][1])\n",
    "#ax[1].plot(Vars.Lat,data[1][0]+elevation)\n",
    "ax[1].plot(Vars.Lat,data1[1][0]+elevation)\n",
    "ax[1].plot(Lat_10,ZMT_10,c='k')\n",
    "\n",
    "#plt.savefig('Coupled_Optimization.eps',format='EPS')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}